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shape
-../../../_images/baf283b204423ee199e9e1581a1ef7838092698e5c53563ba79367fc8738e4ec.png +../../../_images/4da602b7d74b83686ca3fbd0947db04e170faf1282523a3cf3c26a929e335ddd.png
@@ -2969,7 +2969,7 @@

spacing<
-../../../_images/b4c3737a7dd6a0845cd47862886456cfafe3f2c5445218808e49e3206d291704.png +../../../_images/5c1072134f1ba13e065837feae8c1cd91d5d2ca1633bd49f58a1867a420b8d0f.png
@@ -2991,7 +2991,7 @@

axis
-../../../_images/ad56931a8b50d8622d1c9b1e8a71f38a3ec4b9e912dc743f42451cd6f5e343fd.png +../../../_images/218ffd9b93f4541638d07ef6f6e3a2e754e74badfb439b27f48413ccd5a88c26.png
@@ -3013,7 +3013,7 @@

trim_edges
-../../../_images/76c59b8f5d38f216358f260c4d3a539f0887517df46ecac04874ba47921451e2.png +../../../_images/c9602605fc303b15eda70eed3850d3af5928659870db4c5fd43e8c1497cb0b4e.png
@@ -3035,7 +3035,7 @@

label
-../../../_images/7f2c3404fd581c8b9aab68630923de78270968eba87ec15ea444552b8ad19b52.png +../../../_images/2c23e93d3b1d7a6b393fa007120a72d8081e459c2373b09042e7d074e6df2569.png
diff --git a/examples/filters/reference/apply_chords_3D.html b/examples/filters/reference/apply_chords_3D.html index 611dd5403..1c584dedc 100644 --- a/examples/filters/reference/apply_chords_3D.html +++ b/examples/filters/reference/apply_chords_3D.html @@ -2943,7 +2943,7 @@

im
-../../../_images/c0bfe3e35d2325aef36f26d79c7d980daa25d623c0461862dd35e330d16362c3.png +../../../_images/354ff33326062535dacecfaa662da72bc3a8d80ba12f5eaaadde41b94f8e0465.png

The chords in each direction are given different integer values so they can isolated by thresholding.

@@ -2956,7 +2956,7 @@

im
-../../../_images/9347b4dd8fdc5b9895ccd688032a187addd4bfeeb1a67ab5797fbddcc900a320.png +../../../_images/915a2ddfae2b9ac10d258308d64a88f597b7692380d86f557741d0230c9df32d.png
@@ -2977,7 +2977,7 @@

spacing<
-../../../_images/021ebfb72206cb23f174cc444d52bad48dd60f30ea57a3fd12e72fa0fcb64db8.png +../../../_images/657737360860e90ca9c4ca7c6bbf6b85bbe06e0b2498a18fad53e3a03aba7e34.png
@@ -2999,7 +2999,7 @@

trim_edges
-../../../_images/f22b7062432f0eb56d930f88d423df64a552f0213d40576f3f95a4dc79d5e2b9.png +../../../_images/a3ac2d2be2f4806a35fcc1b6320bcfcd5cdf77391ed97dbd626ae8c295a64fc8.png
diff --git a/examples/filters/reference/apply_padded.html b/examples/filters/reference/apply_padded.html index c29be7290..a66e2e977 100644 --- a/examples/filters/reference/apply_padded.html +++ b/examples/filters/reference/apply_padded.html @@ -2939,11 +2939,11 @@

im
-
/tmp/ipykernel_2495/1290140162.py:2: DeprecationWarning: Call to deprecated function (or staticmethod) rsa. (This function will be renamed random_spheres in a future version)
+
/tmp/ipykernel_2781/1290140162.py:2: DeprecationWarning: Call to deprecated function (or staticmethod) rsa. (This function will be renamed random_spheres in a future version)
   im = ps.generators.rsa(im, r=20, volume_fraction=0.4) == 0
 

 

-../../../_images/9357240abc8b612439d1ae9fc15e5c41fa06188c215b6c6fc0f9276fe7a37a23.png
+../../../_images/6b32ddc698d1c07d118657bad23075e2fdd55361a1024f6b85f7c2b2aa79cef8.png
@@ -2977,7 +2977,7 @@

pad_width

-../../../_images/ae8171ce743a6d8fd61283a74e1baf2423b9b6a8bd749c621a2a6591bf174fc1.png +../../../_images/dc3e28c444b1c84d5fc2b8b0cebc7110e856a26c03fc9272959ab3cfdcdc32db.png

It’s also useful for morphological operations such as binary_opening

@@ -3004,7 +3004,7 @@

pad_width
-../../../_images/6f0faff1c35a3eac4eeb791ac0714d574aa3b3bd170bcfe203b91103ff386c51.png +../../../_images/0462ecf42440c3d976e679aa074aaf2ee3174e7ae52e7b6e0e90b0d272c20f2f.png
@@ -3034,7 +3034,7 @@

pad_val<
-../../../_images/912a5855bf5ef858e180f72a7b141085144bd9f45bafef1eb5b56316fde035eb.png +../../../_images/e88bfdd41c1b6b70c1c2437894f6584ee2f065c7ea2e1eec96a24801ac0cf050.png
diff --git a/examples/filters/reference/chunked_func.html b/examples/filters/reference/chunked_func.html index 5cbdbdfe2..0e2522b32 100644 --- a/examples/filters/reference/chunked_func.html +++ b/examples/filters/reference/chunked_func.html @@ -2968,7 +2968,7 @@

im
-../../../_images/6a8404a3ba548db35d5f247419142287e99a7496be02231c8bf7a39850bcb8e1.png +../../../_images/d3b04c42267b88f962eaa6822928b971bd649cca4a7fb1e5204979a91abb08c7.png
@@ -2999,11 +2999,11 @@

overlap< 
OPERATION TIME:
-cores=1: 0.018918275833129883 seconds
-cores=4: 0.027689456939697266 seconds
+cores=1: 0.02565741539001465 seconds
+cores=4: 0.02136993408203125 seconds
-../../../_images/c14619ef7e15e22b1f900adf5bd1043eee1f16b87d3b4550a9920d8c4469698f.png +../../../_images/f1948dbe5d368e6d4793679c7ef9d3379d16b661f24c83e4eeaab24dababf29c.png
diff --git a/examples/filters/reference/distance_transform_lin.html b/examples/filters/reference/distance_transform_lin.html index bf8459d6f..363a27066 100644 --- a/examples/filters/reference/distance_transform_lin.html +++ b/examples/filters/reference/distance_transform_lin.html @@ -2944,7 +2944,7 @@

axis
-../../../_images/08c009c885156b22a4ccd1fb82484feeed90bb3344811b9e0a87549a6b96457d.png +../../../_images/08b6659c768de5e96bdaa94c2d3fe390afb328e48ac6d7c3cb25e19ce183bd3c.png
@@ -2981,7 +2981,7 @@

mode
-../../../_images/ac617553e8fd51dd5a1721cbc35dc2a822287a16eebec8872bbf1992d3f7a5e7.png +../../../_images/6c8a8aa8bb74f847075f48eeddfa56644254f6d655c1e1ef588d953970bcf9c6.png
diff --git a/examples/filters/reference/fill_blind_pores.html b/examples/filters/reference/fill_blind_pores.html index c22536d45..d76dfe30d 100644 --- a/examples/filters/reference/fill_blind_pores.html +++ b/examples/filters/reference/fill_blind_pores.html @@ -2944,7 +2944,7 @@

im
-../../../_images/a15727860f820e9ebf8fae86ce39e121b3043a876831aab6275a72514b96dea6.png +../../../_images/c10e29bd302f9c594659d279081df37a1f72212371351cb384ea08ecb2731ff8.png
@@ -2967,7 +2967,7 @@

conn
-../../../_images/1a103ed3dae0a9cd1fe812bc753fc43bad52d3e41a82e0711442caba7eccd3ae.png +../../../_images/3ce3280abbcac6801965ed379bb73505610f40cb63ed221ec1a13818f1dbd46a.png
@@ -2992,7 +2992,7 @@

surface<
-../../../_images/1c88537489b3efe197fe936cb93d15a87efaff1a9d5aa1cdee4dfd671fd8280b.png +../../../_images/763626e43964db3be75d4f13d85c214a4c75fc4718225a5be43d370e90e04027.png
diff --git a/examples/filters/reference/flood.html b/examples/filters/reference/flood.html index 39b3c0c8f..8f4d1af5e 100644 --- a/examples/filters/reference/flood.html +++ b/examples/filters/reference/flood.html @@ -42,7 +42,7 @@ - + @@ -2941,7 +2941,7 @@

im
-../../../_images/0f6c6569c223cefb1f034fe2e9858e28e80526d6665e35f24fd19a3d5bc22a75.png +../../../_images/2214e28180534b4e99377142e2a2931a9c0ef4b1b1f335c7aa29a2ca47fe17e0.png
@@ -2960,7 +2960,7 @@

labels
-../../../_images/8f0fcfebba9aadb1c6a1daa6ef26c36406a5df085d2083a325eba55c95e74bbc.png +../../../_images/19c725783ea9f1d96c1aa91834474a69d0329cfd82f1f496fe1fd949f532150e.png
@@ -2987,7 +2987,7 @@

mode
-../../../_images/19ca7ec9abb63223aa287c8bd4f864720361ebf85df32aae33594fdc4ded7a41.png +../../../_images/532fbc65666965ced2553f51a2ce490cfaa331499830fd349a60f83352c90083.png
diff --git a/examples/filters/reference/flood_func.html b/examples/filters/reference/flood_func.html index 5b9789d95..53fcd61d0 100644 --- a/examples/filters/reference/flood_func.html +++ b/examples/filters/reference/flood_func.html @@ -2944,7 +2944,7 @@

func
-../../../_images/189914d9e8c62eb9117c3a725f36530a926316bddd51311b2758cf22757bdb92.png +../../../_images/14cb739e650f6689a12c1399105af303833e94c6ec659d64dd8cbfb6d324a36b.png
@@ -2969,7 +2969,7 @@

labels
-../../../_images/fac166b6214f8940ec855f07b4cffc0c7f316219b157ec63e58bb6a29d8d4406.png +../../../_images/0d74b6fb714d0543c8e2c60f4b09b7e9fc2c2e91c41152ed700f2ddad20d840f.png
diff --git a/examples/filters/reference/hold_peaks.html b/examples/filters/reference/hold_peaks.html index 2da5614d3..1ee1ebc64 100644 --- a/examples/filters/reference/hold_peaks.html +++ b/examples/filters/reference/hold_peaks.html @@ -2936,7 +2936,7 @@

im
-../../../_images/643fa295b8af32d9ee56cd75be0bbd277043e60c0e571d8f34e6b0790f09a27a.png +../../../_images/567790cbf470707cd2f58c5701257bae4039439e3823adad61895bdef1239e90.png
@@ -2962,7 +2962,7 @@

axis
-../../../_images/27c0a8a158129b2799b8e63e847ab8ae5f3f8dc10d138a54246c0e3e55def53a.png +../../../_images/6254a774c294ac99d5bcf89ff1887b772028bce300df47b2c615676dbf355456.png
@@ -2988,7 +2988,7 @@

ascending
-../../../_images/5b30df0d17c324dfb19e3aae78c2c4b8c9f3008974aef063574c0c384c67abe4.png +../../../_images/286334c65a9eedaa210bc6311627591d23e883af324f059c68daf2bf8e77cd2f.png
diff --git a/examples/filters/reference/local_thickness.html b/examples/filters/reference/local_thickness.html index 90b7d7d33..d81df4e0c 100644 --- a/examples/filters/reference/local_thickness.html +++ b/examples/filters/reference/local_thickness.html @@ -42,7 +42,7 @@ - + @@ -2952,7 +2952,7 @@

im
-../../../_images/062b4b02ca5cb3aa35560b0d71098de99604b6110acef73f3c8e7641636ef14b.png +../../../_images/9f149845e36cad5e90dc3655821de1131101fe8ed9012148f366d64c5e8f2493.png
@@ -2969,7 +2969,7 @@

sizes
-../../../_images/f12dff59f76593aeb3da46e024603431168d3aaa3e276584b5f93ee851924b23.png +../../../_images/a64a45aa8d89a056c87e0d37b3f5b1681e58260cf061a25d94d406c3059f5b50.png
@@ -2992,7 +2992,7 @@

mode
-../../../_images/78f223ef1e1f8873f04d915c634a5cd2b2a505bea66e1ee1b98f1586b33f9ee4.png +../../../_images/6fe3d9b42510c402fc7fa44bd095f2c328bee7cdf1d45868b063a12f924858ef.png
@@ -3026,7 +3026,7 @@

divs

-../../../_images/d7ac701faedff2cbb353b3099c9c02152e414bd7e37375ba476c03df30f19bb6.png +../../../_images/613699c3bd727fe09661c3851258902e20d98dcc4e64611661594a4e1fb58e64.png
diff --git a/examples/filters/reference/nphase_border.html b/examples/filters/reference/nphase_border.html index e4c2b5e69..2641b35b1 100644 --- a/examples/filters/reference/nphase_border.html +++ b/examples/filters/reference/nphase_border.html @@ -2935,11 +2935,11 @@

im

-
/tmp/ipykernel_3382/2381005276.py:2: DeprecationWarning: Call to deprecated function (or staticmethod) rsa. (This function will be renamed random_spheres in a future version)
+
/tmp/ipykernel_3665/2381005276.py:2: DeprecationWarning: Call to deprecated function (or staticmethod) rsa. (This function will be renamed random_spheres in a future version)
   inclusions = ps.generators.rsa(~matrix, r=5, return_spheres=True, clearance=3)
 

 

-../../../_images/f64155adb25684f1c5e4256490f9bad110256c4b6c60368e9e3fa847b9f35f99.png
+../../../_images/980884d9003827cd3008408a66a9366580e3a6e4a8399a2fc4c533cd015fba83.png
@@ -2973,7 +2973,7 @@

include_diagona

-../../../_images/788129da888012e3e03b9ffc2885afa4632a6e2ef91b68f8a71ca13aacecc0aa.png +../../../_images/33f96643da4cb4596fcdbda656da7ea9d5413d80ab8fcbfe661a4eecbcf68c74.png
diff --git a/examples/filters/reference/pc_to_satn.html b/examples/filters/reference/pc_to_satn.html index 5e1455458..dd92856f4 100644 --- a/examples/filters/reference/pc_to_satn.html +++ b/examples/filters/reference/pc_to_satn.html @@ -42,7 +42,7 @@ - + @@ -2926,7 +2926,7 @@

pc_to_satn
-
+

pc and im#

@@ -2943,7 +2943,7 @@

pc
-../../../_images/5caa264631113d6bcdbca63902fea8e15f7fb9272046455a2b41f8c5c88d9c4c.png +../../../_images/9c0166b43ab228e1e5cafbc9f424059c34aaa9bc03c1ad9aa192d253a1b62943.png

The saturation image allows for easy determination of a desired fluid configuration:

@@ -2958,7 +2958,7 @@

pc
-../../../_images/dd2e4a5c776f318fe16bef44604f50bf6e34562d03e84c1488eecf4f6faa832a.png +../../../_images/5bbcb4f05d362f6b4221cb8effeef93428a90178f12c2d6036d1e34fb2c2fab4.png

diff --git a/examples/filters/reference/porosimetry.html b/examples/filters/reference/porosimetry.html index 18ff388ef..d44d3bbe9 100644 --- a/examples/filters/reference/porosimetry.html +++ b/examples/filters/reference/porosimetry.html @@ -42,7 +42,7 @@ - + @@ -2973,7 +2973,7 @@

im
-../../../_images/ed4914233a6d4b60a3a631fd8fd60d4948fe062402224a10fdee5023a26b0207.png +../../../_images/4456a6589428a4c19bb7f8a4430c66d3198e610473f4c6a3fdd4e4d4c1bcecd8.png

A cumulative histogram of the voxel values is analogous to a porosimetry experiment:

@@ -2987,7 +2987,7 @@

im
-../../../_images/bfa5aeedd4ae1c776cbb19a029386b6a28e2305a883d419ec336098bfb91f8b0.png +../../../_images/141fa61c30a2cd03d2e848e752e3d4089c847d3e27908613ecfd1c969f4a6d8b.png
@@ -3007,7 +3007,7 @@

sizes
-../../../_images/ecda183d4fbb83fe1cc46c7fc589e4cc78e5c800daeb74af3337f2de68738e32.png +../../../_images/a06b1fefd0d67fdbd9306eb9832423cc51440d07ee3995a6fad4653ff7771834.png
@@ -3029,7 +3029,7 @@

inlets
-../../../_images/e23c2ef7a33086a9dbaa04cfaccc777cf7b6dd5e138bacb6e8082feb4b6f0da2.png +../../../_images/610ee00563beb00c004609a16d79f95f8416eb05ef1c0954959f523b5dc7cc17.png
@@ -3052,7 +3052,7 @@

access <
-../../../_images/2167e1fc31a2b6f4aa3baf4e8e590a4233e87473538136ae4a4707623652b308.png +../../../_images/2f2c65f4f457252c82f511b756b77e3c6d549b37b20a7f5070470561bab5133d.png

As can be seen the case with access limitations appears to have smaller pores, which is because the invading fluid cannot reach the large pores that are shielded by smaller ones, so their volume gets attributed to the smaller voids.

@@ -3076,7 +3076,7 @@

mode
-../../../_images/3deb3779d370581abc1ed0a02c08f900561cb733a902f8ae232f7dcb3c53477b.png +../../../_images/73f79f1abe1eee9a0d44db3d2bd1fee67cb653c7d4e82473a2ead0da1ba5ff8e.png
@@ -3099,7 +3099,7 @@

divs
-../../../_images/3deb3779d370581abc1ed0a02c08f900561cb733a902f8ae232f7dcb3c53477b.png +../../../_images/73f79f1abe1eee9a0d44db3d2bd1fee67cb653c7d4e82473a2ead0da1ba5ff8e.png
diff --git a/examples/filters/reference/prune_branches.html b/examples/filters/reference/prune_branches.html index c872ad9d1..5ea354e8d 100644 --- a/examples/filters/reference/prune_branches.html +++ b/examples/filters/reference/prune_branches.html @@ -2923,7 +2923,7 @@

im
-../../../_images/63a8bb53353a4635573c366a1600c41cccbc6b8c6e985ea11df5792cae114e46.png +../../../_images/2cc8bda291eec1c357e582fa10cf587a22106b12c50af03e20c8260474744b7a.png
@@ -2947,7 +2947,7 @@

iterations
-../../../_images/be3b4465d0f81881d7776ad5aaa8cce022d5851465908544c05ee52133b47d0f.png +../../../_images/644a40075f9858a8ab90ed3528234951df2b27fa328420f6507c5714974c5bf2.png
diff --git a/examples/filters/reference/reduce_peaks.html b/examples/filters/reference/reduce_peaks.html index 20efcb68b..29a25fa4c 100644 --- a/examples/filters/reference/reduce_peaks.html +++ b/examples/filters/reference/reduce_peaks.html @@ -2933,7 +2933,7 @@

peaks
-../../../_images/072ac4fee1d5e170c67df266878a33a96dbbd5884783a3892c59747dff217cf1.png +../../../_images/85f721d5456867e9cf8b8d032194fe35d152a542390710ab9b66a7019d66ae05.png
@@ -2949,7 +2949,7 @@

Apply reduce_pe
-../../../_images/43085110588dc1686e5cd8920186c0402c896011f8bdec313e372dcce1f3d500.png +../../../_images/483bfc135b45334d8c06e20e5d148d1ec5d1bc047373af9c4309a13a5de1056f.png
diff --git a/examples/filters/reference/region_size.html b/examples/filters/reference/region_size.html index 8df74c059..70f1d46dc 100644 --- a/examples/filters/reference/region_size.html +++ b/examples/filters/reference/region_size.html @@ -2930,7 +2930,7 @@

im
-../../../_images/de5d0fa7864a6cffb7a680085ca0e0641124406a2ad411283a67689db9416d57.png +../../../_images/1de079eadab8afabad3cc0984209e6b9c38aa40f15e5cd4501f62583fbaa66ca.png
@@ -2947,7 +2947,7 @@

Apply region_si
-../../../_images/767db9af68c7c8b1a386db37275f9736f835e5552a723b95b33196eb96c60b66.png +../../../_images/7017677437696e29ec8c1cecae152a0e5e503bb26bd097896fbdab2f683426d3.png
diff --git a/examples/filters/reference/satn_to_seq.html b/examples/filters/reference/satn_to_seq.html index 159b5bab1..86a3e3171 100644 --- a/examples/filters/reference/satn_to_seq.html +++ b/examples/filters/reference/satn_to_seq.html @@ -42,7 +42,7 @@ - + @@ -2931,7 +2931,7 @@

satn_to_seq
-
+

satn#

@@ -2949,7 +2949,7 @@

satn
-../../../_images/7993e4df6ae01ceaf6917561c3d1b263f6724a6c9a4a134df5df58893c0610ec.png +../../../_images/912aeef6362a4a54a3507e5f963bb2156dde88986baa2ac2db3b246aaa19636e.png

@@ -2973,7 +2973,7 @@

im
-../../../_images/308ae35d711c48a7d9418438bba970f066d8723801c352b52dda8690193f2d07.png +../../../_images/11b9f20cb1b5c56fc0d4e222683b2b6481a2138a32be8889fb8f694e6c899294.png
diff --git a/examples/filters/reference/seq_to_satn.html b/examples/filters/reference/seq_to_satn.html index 034aaab6e..3964b5e38 100644 --- a/examples/filters/reference/seq_to_satn.html +++ b/examples/filters/reference/seq_to_satn.html @@ -42,7 +42,7 @@ - + @@ -2922,7 +2922,7 @@

seq_to_satn
-
+

Then convert the sizes to sequence values:

@@ -2948,7 +2948,7 @@

seq

-../../../_images/8043102aeda1860c7e3d37f7af249a879e49bbc0ba1bfc4f80fd7fed5915a245.png +../../../_images/8461987b91aa7c380f5970562974948ca3e26b65f96bd4fdd5b47ccd499a16b6.png

The saturation map makes it very easy to obtain a desired fluid configuration just by applying a threhold:

@@ -2969,7 +2969,7 @@

seq
-../../../_images/70a1412f91553aed1ef604767a694ae41d6cd95bbcad06d04e1fe20641258716.png +../../../_images/013402fab22c488a9d40df1c162a1dc6cc5074675e62c3f94a5cf342246c50c3.png
diff --git a/examples/filters/reference/size_to_satn.html b/examples/filters/reference/size_to_satn.html index 569180e27..29670b4b8 100644 --- a/examples/filters/reference/size_to_satn.html +++ b/examples/filters/reference/size_to_satn.html @@ -42,7 +42,7 @@ - + @@ -2940,7 +2940,7 @@

size_to_satn
-
+

size#

@@ -2959,7 +2959,7 @@

size
-../../../_images/61918db22e61102a85d4e36e173cee92e0f69d90e4898ecf35ed5a2cafe7ff5d.png +../../../_images/71fb0349324e995730299758532ae5c31add84fde9422bd7d4893bc926dbd97e.png

The saturation map makes it very easy to obtain a desired fluid configuration just by applying a threhold:

@@ -2980,7 +2980,7 @@

size
-../../../_images/70a1412f91553aed1ef604767a694ae41d6cd95bbcad06d04e1fe20641258716.png +../../../_images/013402fab22c488a9d40df1c162a1dc6cc5074675e62c3f94a5cf342246c50c3.png

@@ -3004,7 +3004,7 @@

im
-../../../_images/b88a19dcafeb546a83d4666b7d6b636e46a33b895df699209faba39a3b5056a2.png +../../../_images/0bd3a1afea524aa9a05e5bdc9ce2ae0e274315a2616907e3fefab9b646f856dd.png

The different between the two images above is that when im is not supplied, then uninvaded regions are given a lable of 0, matching solid. When im is supplied, the uninvaded regions are labelled -1.

@@ -3031,7 +3031,7 @@

bins
-../../../_images/894e113304f86d32490efa0132764ef19a1965cbead6d5119553c0b2942fdb4b.png +../../../_images/5258588bac55c88b0573153ca54c81edfe3010f7849a11797aa001baaef3b37d.png
diff --git a/examples/filters/reference/size_to_seq.html b/examples/filters/reference/size_to_seq.html index 825fe905e..2231ee4eb 100644 --- a/examples/filters/reference/size_to_seq.html +++ b/examples/filters/reference/size_to_seq.html @@ -42,7 +42,7 @@ - + @@ -2940,7 +2940,7 @@

size_to_seq
-
+

size#

@@ -2959,7 +2959,7 @@

size
-../../../_images/3db2c5dfa39ae64fbc5dee3f9795dfa89ba69e2204c2a6a5c6dbd0295cbdc54c.png +../../../_images/bb15caed26a0a39ca3b4a0908aa408b46aa61585c8c3c4f060706bec6c1bd51d.png

@@ -2980,7 +2980,7 @@

im
-../../../_images/1e2f588ec6f5c2ba8999012bb8acc66d47f54b9e90b8acd2c019255cf2deb5f4.png +../../../_images/387861a25cf4931955c9a8fd8cd0c88aafb684b03a9aba85be4f37b7eb54550d.png

In the right image above, there can be seen several regions that are isolated by the void space. They are colored yellow indicating they are filled last. This is caused by the fact that these regions were uninvaded so were set to 0, which makes them the last regions invaded. This may or may not be desired.

@@ -3007,7 +3007,7 @@

bins
-../../../_images/4636a00e713782b720e3c5748ca4f76710b314446559d819d5c6ef68dc2a33a0.png +../../../_images/ef17c6d21655b668d9df9be2351871163fd3049863bf5226177f82a215232581.png
diff --git a/examples/filters/reference/snow_partitioning.html b/examples/filters/reference/snow_partitioning.html index 56e4242be..0abf69fb3 100644 --- a/examples/filters/reference/snow_partitioning.html +++ b/examples/filters/reference/snow_partitioning.html @@ -42,7 +42,7 @@ - + @@ -2940,7 +2940,7 @@

im
-
+

The function returns are Results object which has several images attached as attributes:

@@ -2951,7 +2951,7 @@

im 
――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――
-Results of snow_partitioning generated at Thu Aug 24 13:05:19 2023
+Results of snow_partitioning generated at Thu Sep 14 04:50:01 2023
 ――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――
 im                        Array of size (200, 200)
 dt                        Array of size (200, 200)
@@ -2973,7 +2973,7 @@ 
im
-../../../_images/29deb04de8a0fca63c3ad665a20a3d222c1f713b5111cbf020ee356ae3128801.png +../../../_images/078c73e25b65a999db701a7de9f14b449449fc9c0f0b2cbb7a39e27edfd6e503.png
@@ -2999,7 +2999,7 @@

sigma

-../../../_images/cf49c4460b8316751fb1f835698d4d8cac1b090c6ec0dc6f3c46d5647372c03a.png +../../../_images/51c77efff0e5beede2eeb6d84d323e2c7a983cd5dab6304dee2bcd5b89233038.png

As can be seen above, a higher value of sigma results in several peaks being missed or skipped. This may or may not be desireable.

@@ -3026,7 +3026,7 @@

r_max
-../../../_images/cb53361254c25c1aa211e7292b757980ebd2778bb2a7316562b522c679dbc568.png +../../../_images/560e058af49ce93d80bfbd78d1245f94e878d9ef719ebda2798922649b591362.png
diff --git a/examples/filters/reference/snow_partitioning_n.html b/examples/filters/reference/snow_partitioning_n.html index da8676c2e..84cb0059d 100644 --- a/examples/filters/reference/snow_partitioning_n.html +++ b/examples/filters/reference/snow_partitioning_n.html @@ -42,7 +42,7 @@ - + @@ -2935,7 +2935,7 @@

im
-../../../_images/e1cdd9a9c6b1431a1480b1017a2dda558a4cbbf34e1e4a0c551b115e24648fe5.png +../../../_images/d882f1860dbaf64e062ee175de8f58c9e6ac504c9e1651e6c07c1082058de129.png
@@ -2950,8 +2950,8 @@

Apply snow_part
-
――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――
-Results of snow_partitioning_n generated at Thu Aug 24 13:05:28 2023
+
――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――
+Results of snow_partitioning_n generated at Thu Sep 14 04:50:10 2023
 ――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――
 im                        Array of size (200, 200)
 dt                        Array of size (200, 200)
@@ -2974,7 +2974,7 @@ 
Apply snow_part
 

 

 

-../../../_images/1ab910fd7fa6ee027870ad551f56466fe3d6775ae81ff8bd39c8680f8bfd5c55.png
+../../../_images/9fd66c038dd0e4fbbd583636a23b03b4139a625ac7ab3dfaa2f3b785d8d2ec44.png
diff --git a/examples/filters/reference/snow_partitioning_parallel.html b/examples/filters/reference/snow_partitioning_parallel.html index 42fffae93..15e512e89 100644 --- a/examples/filters/reference/snow_partitioning_parallel.html +++ b/examples/filters/reference/snow_partitioning_parallel.html @@ -42,7 +42,7 @@ - + @@ -2944,7 +2944,7 @@

im

-../../../_images/87e2d2bf77d3a84c13348438370b8a1a31b5d99321caabc7a67bd88bf615b54d.png +../../../_images/cfbfd114b101e807a87b32573eba59244371cb69aad6fbe4c3671bce4dbfed5e.png
@@ -2966,9 +2966,9 @@

overlap<
-
OPERATION TIME:
-cores=1: 5.360652685165405 seconds
-cores=4: 0.7770392894744873 seconds
+
OPERATION TIME:
+cores=1: 5.813374042510986 seconds
+cores=4: 0.7496254444122314 seconds
@@ -2982,7 +2982,7 @@

overlap< 

――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――
-Results of snow_partitioning_parallel generated at Thu Aug 24 13:05:39 2023
+Results of snow_partitioning_parallel generated at Thu Sep 14 04:50:21 2023
 ――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――
 im                        Array of size (800, 800)
 dt                        Array of size (800, 800)
@@ -3006,7 +3006,7 @@ 
overlap<
-../../../_images/1e61d9d2f2114a599701d8cae831dcdc1f82bb6179c5d900086a80184bdc6494.png +../../../_images/efe7f624b296918b6f07110ddcf30ecccf7b4cd3e39d7fae7541c60db74f7824.png
diff --git a/examples/filters/reference/trim_disconnected_blobs.html b/examples/filters/reference/trim_disconnected_blobs.html index 4ded7e4ca..ac3bc80c2 100644 --- a/examples/filters/reference/trim_disconnected_blobs.html +++ b/examples/filters/reference/trim_disconnected_blobs.html @@ -2945,7 +2945,7 @@

im

-../../../_images/9d6281759c47e87861b083399cdcb0fd90f7d251149da682df1577c73b94c2ae.png +../../../_images/e4da6a1eceb536c2d8eee1021ed523f687c79647d841eb4cecfce06a4504cd08.png
@@ -2968,7 +2968,7 @@

strel
-../../../_images/47c2c81e6f8093ff837b4a8bcd5ecb64de694263623ee3125ada38f60a151445.png +../../../_images/da9d88a8f21481b2868ca8e0f101dc0c00e67df1ae7e767974efcc33c7911351.png
diff --git a/examples/filters/reference/trim_extrema.html b/examples/filters/reference/trim_extrema.html index 1f46bd9fa..7c08a9e48 100644 --- a/examples/filters/reference/trim_extrema.html +++ b/examples/filters/reference/trim_extrema.html @@ -2927,7 +2927,7 @@

im
-../../../_images/c509ce995b71f593dcedad9d55d6cd3123420cdace5679b219a96beb237a47ad.png +../../../_images/36bda68466aa92b37873611a2c09c4b47d18e800b35371fa4d3da24645fc2914.png
@@ -2957,7 +2957,7 @@

im

-../../../_images/35f2e2c92fe51a69d49f1c5057d884778822fb3c2113ed01e7b322937cc7b6e1.png +../../../_images/c52aac8c5bd87cea51cbd43076027b87ecf16432ea16860abe2edd259639515f.png
@@ -2988,7 +2988,7 @@

mode
-../../../_images/0c8a68fd1b2a83be5644b95902af3f82d60c1684ed47e317ffce4f8609a43493.png +../../../_images/dcaa4b301b14671f1a0a8828398a988e2e186552691657d48342b0d9b4cc69b2.png
@@ -3015,7 +3015,7 @@

mode

-../../../_images/91b9843fc297dea7a820886b72f7067bc9fa8b404bd7632b8e0aaae5af25b832.png +../../../_images/93c48f6932ceb156bdce2b7f48f2532130abdbdbce7e5a48ddcf1a351ee6eb7d.png
diff --git a/examples/filters/reference/trim_floating_solid.html b/examples/filters/reference/trim_floating_solid.html index fe60e8bfc..9675d9b88 100644 --- a/examples/filters/reference/trim_floating_solid.html +++ b/examples/filters/reference/trim_floating_solid.html @@ -2948,31 +2948,6 @@

im 966 im = 1 / 2 * erfc(-im / np.sqrt(2)) 967 im = (im - im.min()) / (im.max() - im.min()) -File <__array_function__ internals>:200, in std(*args, **kwargs) - -File /opt/hostedtoolcache/Python/3.8.17/x64/lib/python3.8/site-packages/numpy/core/fromnumeric.py:3605, in std(a, axis, dtype, out, ddof, keepdims, where) - 3602 else: - 3603 return std(axis=axis, dtype=dtype, out=out, ddof=ddof, **kwargs) --> 3605 return _methods._std(a, axis=axis, dtype=dtype, out=out, ddof=ddof, - 3606 **kwargs) - -File /opt/hostedtoolcache/Python/3.8.17/x64/lib/python3.8/site-packages/numpy/core/_methods.py:269, in _std(a, axis, dtype, out, ddof, keepdims, where) - 267 def _std(a, axis=None, dtype=None, out=None, ddof=0, keepdims=False, *, - 268 where=True): ---> 269 ret = _var(a, axis=axis, dtype=dtype, out=out, ddof=ddof, - 270 keepdims=keepdims, where=where) - 272 if isinstance(ret, mu.ndarray): - 273 ret = um.sqrt(ret, out=ret) - -File /opt/hostedtoolcache/Python/3.8.17/x64/lib/python3.8/site-packages/numpy/core/_methods.py:236, in _var(a, axis, dtype, out, ddof, keepdims, where) - 231 arrmean = arrmean / rcount - 233 # Compute sum of squared deviations from mean - 234 # Note that x may not be inexact and that we need it to be an array, - 235 # not a scalar. ---> 236 x = asanyarray(arr - arrmean) - 238 if issubclass(arr.dtype.type, (nt.floating, nt.integer)): - 239 x = um.multiply(x, x, out=x) - KeyboardInterrupt: diff --git a/examples/filters/reference/trim_nearby_peaks.html b/examples/filters/reference/trim_nearby_peaks.html index fd3cb51c4..1839a2b3e 100644 --- a/examples/filters/reference/trim_nearby_peaks.html +++ b/examples/filters/reference/trim_nearby_peaks.html @@ -2921,7 +2921,7 @@

dt
-../../../_images/9f1d612f90b262c88c758da12b4affe2b7991cabcea3676d88328d99af796415.png +../../../_images/498b999e94a1168c44ec514faf2b8f4356dc1a12a0adf860fe6ac59cf328243c.png
@@ -2945,7 +2945,7 @@

peaks
-../../../_images/0b8e21f4013930ee0a59b7a3d0640a8f5600d0aaa398c7aa0728047e11335140.png +../../../_images/869d3e7c99eaa995ce0e30f3aff4ace51f25ef9b29f09ff6b0e240ecdba0b792.png
diff --git a/examples/filters/reference/trim_nonpercolating_paths.html b/examples/filters/reference/trim_nonpercolating_paths.html index 54a605d60..fa33c6632 100644 --- a/examples/filters/reference/trim_nonpercolating_paths.html +++ b/examples/filters/reference/trim_nonpercolating_paths.html @@ -2925,7 +2925,7 @@

im
-../../../_images/2056a5af64552e7b23707196f2fd3350a5fd2c49285bbccaa52f8f52a91b5eaf.png +../../../_images/a3042eb7e883d62a958a5e5b3ae758e25dc6a321b07a4059a4f78d36c8f78758.png
@@ -2952,7 +2952,7 @@

inlets
-../../../_images/13b2e4211d06c7b929f2867da5680a94c77f9e00745d347e6f9359e3ae7283f3.png +../../../_images/7841017d2bb1519703ea27c04a68f4ce2649186240102da186fa4c06488301fc.png
diff --git a/examples/filters/reference/trim_saddle_points.html b/examples/filters/reference/trim_saddle_points.html index fd3d00456..68ef397f7 100644 --- a/examples/filters/reference/trim_saddle_points.html +++ b/examples/filters/reference/trim_saddle_points.html @@ -42,7 +42,7 @@ - + @@ -2924,7 +2924,7 @@

dt
-../../../_images/34b31db69a26a9843cb5dc07def59445d21df82f2ac5679092f477ae369ba49c.png +../../../_images/ab56d365a4486e5d8b2fe46a19e15ac834fd46f04d9aba9e388c75e25b7455c8.png
@@ -2948,7 +2948,7 @@

peaks
-../../../_images/50cef559f2bd334ae1f7be5bf64f586fffc5362f83702d4f94d31b9bd55af9db.png +../../../_images/b83ae371460bfcccab52938562b64682d93203c096e411590f6a6293fde3eab9.png
diff --git a/examples/filters/reference/trim_small_clusters.html b/examples/filters/reference/trim_small_clusters.html index ec98840ce..6f8b94d7a 100644 --- a/examples/filters/reference/trim_small_clusters.html +++ b/examples/filters/reference/trim_small_clusters.html @@ -2919,7 +2919,7 @@

im
-../../../_images/293631ba1d298c6a9854bf38ac6439a25f384903ac998c465049061d13f1ece4.png +../../../_images/d1f3188f644c5731afa3fe2bc3421f68231f375163005da430c326bd524a1b59.png
@@ -2946,7 +2946,7 @@

size
-../../../_images/e048ab8da1c01a98e4ea235331b084a5167ea84339fadc96c193c21df12310c8.png +../../../_images/cf2aaf956b142bf653588d2d353eca4f05b3f708c0f5f7a78625b5e51aba13cd.png
diff --git a/examples/filters/tutorials/adding_chords.html b/examples/filters/tutorials/adding_chords.html index b7f12f55f..5562e03e6 100644 --- a/examples/filters/tutorials/adding_chords.html +++ b/examples/filters/tutorials/adding_chords.html @@ -42,7 +42,7 @@ - + @@ -2919,7 +2919,7 @@

Demonstration on 2D Image -../../../_images/47c4613c0b431c82d8d48b5c4159f5b7b960e75e810d033ca4c183669e00a8ba.png +../../../_images/b687ac2a6e12ab61fab0c0f0e5c0fa39dca5a81ac19764ea69f4ad957d669c32.png

Determining chord-length distributions requires first adding chords to the image, which is done using the apply_chords function. The following code applies chords to the image in the x-direction (along axis=0), then applies them in the y-direction (axis=1). The two images are then plotted using matplotlib.

@@ -2936,7 +2936,7 @@

Demonstration on 2D Image -../../../_images/c977315230d6cf7c1042e63c18ca81a81d4fb1bfecbd4b16d4e0cac6326d6f84.png +../../../_images/f8b3d2ee9b64e2348846406826cad3259a5029b759f17ec0ab5900365fb4b825.png

Note that none of the chords touch the edge of the image. These chords are trimmed by default since they are artificially shorter than they should be and would skew the results. This behavior is optional and these chords can be kept by setting trim_edges=False.

@@ -2954,7 +2954,7 @@

Demonstration on 2D Image -../../../_images/6a776384840ce26479fd8065c31031e27044402595049ec034fc978e7db49dcf.png +../../../_images/9503c45a6ccad1b0b182bf4307981c976706a779ffecc4524b4f5cf4ec1dea76.png

Although the above images are useful for quick visualization, they are not quantitative. To get quantitative chord length distributions, pass the chord image(s) to the chord_length_distribution functions in the metrics submodule:

@@ -2975,7 +2975,7 @@

Demonstration on 2D Image 
――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――
-Results of chord_length_distribution generated at Thu Aug 24 13:07:06 2023
+Results of chord_length_distribution generated at Thu Sep 14 04:51:47 2023
 ――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――
 L                         Array of size (25,)
 pdf                       Array of size (25,)
@@ -3001,7 +3001,7 @@ 
Demonstration on 2D Image
-../../../_images/92de69d7ea0afb750ee28511f51d5757090e4b1d6c3222af4dd397e36b6259af.png
+../../../_images/f049cfa5ba37372fe5c091bf805a85068380558b27ec4089c89572b22196c900.png

The key point to see here is that the blue bars are for the y-direction, which was the elongated direction, and as expected they show a tendency toward longer chords.

@@ -3018,7 +3018,7 @@

Application to 3D images -../../../_images/a9d610b0dfd1d777ed97aa4a4c935c78088f8042e09e1bfd15712573c3e66393.png +../../../_images/d1eb1786cf9fd4fd1b36884c66ba6e37688f63cfb9b59e8861aa0c59c9eb18d3.png

As above, we must apply chords to the image then pass the chord image to the chord_length_distribution function:

@@ -3032,7 +3032,7 @@

Application to 3D images -../../../_images/d69a4e4517fe145a9109ca8e96bdc36e38b7fd1ad1185024c8292fc169b5231a.png +../../../_images/17f9743836405e3b998eb17966e64f8bb0000704489fedb63b002d80814c43c0.png
@@ -3046,7 +3046,7 @@

Application to 3D images -../../../_images/7f70337726017d5471d92d38e89c7d33126b852187acf9f8b39e1a08066d3d2f.png +../../../_images/1f8dca07576ea6754691aaca71c0395d2613862c713525d9a8957763a8279668.png

diff --git a/examples/filters/tutorials/local_thickness.html b/examples/filters/tutorials/local_thickness.html index 08492cb1b..8f0ae9070 100644 --- a/examples/filters/tutorials/local_thickness.html +++ b/examples/filters/tutorials/local_thickness.html @@ -44,7 +44,7 @@ - + @@ -2928,17 +2928,17 @@

Generate Test Image -
/tmp/ipykernel_5116/1607336354.py:2: DeprecationWarning: Call to deprecated function (or staticmethod) rsa. (This function will be renamed random_spheres in a future version)
+
/tmp/ipykernel_5443/1607336354.py:2: DeprecationWarning: Call to deprecated function (or staticmethod) rsa. (This function will be renamed random_spheres in a future version)
   im = ps.generators.rsa(im, r=20, volume_fraction=0.2)
 

 

-
/tmp/ipykernel_5116/1607336354.py:3: DeprecationWarning: Call to deprecated function (or staticmethod) rsa. (This function will be renamed random_spheres in a future version)
+
/tmp/ipykernel_5443/1607336354.py:3: DeprecationWarning: Call to deprecated function (or staticmethod) rsa. (This function will be renamed random_spheres in a future version)
   im = ps.generators.rsa(im, r=15, volume_fraction=0.4)
-/tmp/ipykernel_5116/1607336354.py:4: DeprecationWarning: Call to deprecated function (or staticmethod) rsa. (This function will be renamed random_spheres in a future version)
+/tmp/ipykernel_5443/1607336354.py:4: DeprecationWarning: Call to deprecated function (or staticmethod) rsa. (This function will be renamed random_spheres in a future version)
   im = ps.generators.rsa(im, r=10, volume_fraction=0.6)
 

 

-../../../_images/fe945b9be56aaa1964eac46ffe33d847c8d20b86a205ba0d6256e4520a52c12a.png
+../../../_images/170487c5cd113142314563aa09d3194206b53fb88cf2c81e898613284f724891.png
 

 

 
@@ -2955,7 +2955,7 @@ 
Apply Local Thickness Filter
-../../../_images/4c0068b643199b3e5358939fc7c35013bd02802f5ebb95ac1a2284966ef08aa9.png
+../../../_images/481eaf880c94db6adf73fca81d9393280f17ec3ba56780aed06e1cf9eb585ebb.png
@@ -2978,7 +2978,7 @@

Extracting PSD as a Histogram 
――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――
-Results of pore_size_distribution generated at Thu Aug 24 13:07:21 2023
+Results of pore_size_distribution generated at Thu Sep 14 04:52:05 2023
 ――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――
 LogR                      Array of size (10,)
 pdf                       Array of size (10,)
@@ -3003,7 +3003,7 @@ 
Extracting PSD as a Histogram
-../../../_images/4d138ab1a324f8c876d641cc0b91522347136bfced6e7586679589977de7488a.png
+../../../_images/c3fe4c0896cc01cf9ccd03eb933aa9f6a6e186793a15339935fbc119d9cbd8c7.png
@@ -3022,7 +3022,7 @@

PoreSpy Implementation
-../../../_images/2dca592fc65a9dc96fc5dc9a6025f694af6553e8f924d8e1cafeb5f19256e4f5.png +../../../_images/59cc869f00aaae90134caeb2a9216fa776d5d4a236021d443c22be814eaac478.png

The key is to make a master array containing the numerical value of the largest sphere that covers each voxel. We’ll initialize a new array with the current locations where R=10 fits:

@@ -3060,7 +3060,7 @@

PoreSpy Implementation
-../../../_images/4a6a4372c7f67409e463aeb8553d624feb063e45f1ebea8832235d48107e1b87.png +../../../_images/c61f0cc8c3b72565c4cd617e238cb7976a2579b14f283380ba1c820d656b07be.png

The procedure is then repeated for smaller structuring elements down to R = 1. It’s possible to specify which sizes are used, but by default all integers between \(R_{max}\) and 1. This yields the image showed above:

@@ -3072,7 +3072,7 @@

PoreSpy Implementation
-../../../_images/35c3a2e8a7d900363eaf822e5031b370fbe66b1649b511b69ecce25f0ee4ef96.png +../../../_images/4df341481d44026d5e35722d6b67f06f938ccd8a8a7421fbd4d4caad8cc54251.png
diff --git a/examples/filters/tutorials/snow_partitioning.html b/examples/filters/tutorials/snow_partitioning.html index 9b99cb5d8..07ab3f765 100644 --- a/examples/filters/tutorials/snow_partitioning.html +++ b/examples/filters/tutorials/snow_partitioning.html @@ -42,7 +42,7 @@ - + @@ -2895,7 +2895,7 @@

SNOW partitioning -../../../_images/ca149bc683e5b9d9e134b8c6ece57d131e7a3bf0dd9998d587fc94da60c287d4.png +../../../_images/b29af6704a3a705060e17ee3060c7d40f43c79f4b9010c9c8a05dd2fb11e33ec.png
@@ -2906,8 +2906,8 @@

SNOW partitioning -
――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――
-Results of snow_partitioning generated at Thu Aug 24 13:07:30 2023
+
――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――
+Results of snow_partitioning generated at Thu Sep 14 04:52:14 2023
 ――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――
 im                        Array of size (500, 500)
 dt                        Array of size (500, 500)
@@ -2936,7 +2936,7 @@ 
SNOW partitioning
-../../../_images/7ef5d162f880f6303900a65bc936f9e96183b02e04920fe7f5283493722bb45e.png
+../../../_images/cd1222947745dc47ff4f8fcb83755a574ed4a40b22368d74d691673f12805ae2.png
 

 

 
diff --git a/examples/filters/tutorials/snow_partitioning_parallel.html b/examples/filters/tutorials/snow_partitioning_parallel.html
index 8ea8f47b7..4d1526f03 100644
--- a/examples/filters/tutorials/snow_partitioning_parallel.html
+++ b/examples/filters/tutorials/snow_partitioning_parallel.html
@@ -42,7 +42,7 @@
     
     
     
-    
+    
     
     
     
@@ -2914,7 +2914,7 @@ 
Create a random image of overlapping spheres
-../../../_images/3fa43672e1a78a5bc2aafe1182994685e0192a07fefed802d2ae2f81de47bd70.png
+../../../_images/e3a58caf165079b476ce429ff8ced028a22421d46264341dccc57bed4d34d9fe.png
@@ -2929,7 +2929,7 @@

Apply SNOW_partitioning_parallel on the binary image

-
+

The result will be indentical to the serial version if sufficient overlap was chosen between the chunks. There is an automated computation of this overap in the function. The results are shown below:

@@ -2941,7 +2941,7 @@

Apply SNOW_partitioning_parallel on the binary image

-../../../_images/9725193a90ec0c2058cb7950967ad13f0c9195a027cfd4938cdbed626a725950.png +../../../_images/2e4680f80aa717c4df34fa54887c68c1c5a61154cb7b1e58c40f750e3af98c10.png
diff --git a/examples/general/denoising_and_segmenting_images.html b/examples/general/denoising_and_segmenting_images.html index c8039f07e..144cbb44e 100644 --- a/examples/general/denoising_and_segmenting_images.html +++ b/examples/general/denoising_and_segmenting_images.html @@ -2927,7 +2927,7 @@

The Noise Problem -../../_images/76c662aa81a7c773d08e4230a0b7e803f4d1494b478d415045db07e865dcbd26.png +../../_images/5587954e3edde441f85c693489fd6bff4af8ad60c3b4249addc449f6767be69f.png

The above image now contains some noise in each phase, which is more realistic, though as we will see it not close to reality. Let’s look at a histogram of this image:

@@ -2939,7 +2939,7 @@

The Noise Problem -../../_images/71b882734c1d3ad76f43f6900b2abea4612dd6ac5f90ac20b7eaac813d7aa80c.png +../../_images/444a3db1c9a02913d2a29e91c07a5df9d1287db3dd6e3a712448f2e46cde289f.png

We can see above that all pixels with a value less than 0.5 belong to the dark phase, while the other pixels belong to the light phase. A simple global threshold can reproduce the original image perfectly:

@@ -2951,7 +2951,7 @@

The Noise Problem -../../_images/7ddf528dd6f8f7cbafddeabd4db5d7480c6a2bc27da70cdb877733ef4355b138.png +../../_images/a9fc92713eaae665c04d6a084654a142ed8b5b94ab2ea73140ababfd50f7a2fc.png

Now let’s look at a more realistic noise distribution, though still artificially generated:

@@ -2966,7 +2966,7 @@

The Noise Problem -../../_images/888d3c5a3b675879e7770405a57296e39596648da2ff5ceb6cd6acfa1522ef59.png +../../_images/971a4b5f2ee260fe824e59efb5f69ffefcb1218185f67042152ff0659440a79f.png

Now we can see that the noise is much less separated, and in fact the tails of the distributions just touch each other in the middle. Let’s see how the simple threshold we used above would work now:

@@ -2978,7 +2978,7 @@

The Noise Problem -../../_images/7893d0cf5bf4dd86697359717de8ad788b800dd475d031533c2eceb2a1333194.png +../../_images/243bc7901ee6adeada756b3241cc806aee12f3164bea32f9ef98f4c0fdcdc753.png

Now there are a few pixels in the dark phase which have been identified as bright and vice-versa. Let’s take this further but putting more extreme, but more realistic noise:

@@ -2994,7 +2994,7 @@

The Noise Problem -../../_images/46e31906d96ed57c0ffe1d465bf9893ceb7c818d20f74ea524511ef4863e9d75.png +../../_images/4e87a01d01718e82107df186b0048084b747cacf4717b82d2d50511b8ab7a66b.png

In the above case our eyes can differentiate the light and dark phases pretty well, but the histogram is fully merged into one, and the global threshold produces a very problematic result. Just to show this is not an exageration, below is an actual slice of a tomogram taken of an electrospun flow-battery electrode:

@@ -3017,13 +3017,13 @@

The Noise Problem 2 im = (im - im.min())/(im.max() - im.min()) 3 fig, ax = subplots(1, 3, figsize=[15, 5]) -File /opt/hostedtoolcache/Python/3.8.17/x64/lib/python3.8/site-packages/imageio/v2.py:522, in volread(uri, format, **kwargs) +File /opt/hostedtoolcache/Python/3.8.18/x64/lib/python3.8/site-packages/imageio/v2.py:522, in volread(uri, format, **kwargs) 520 imopen_args = decypher_format_arg(format) 521 imopen_args["legacy_mode"] = True --> 522 with imopen(uri, "rv", **imopen_args) as file: 523 return file.read(index=0, **kwargs) -File /opt/hostedtoolcache/Python/3.8.17/x64/lib/python3.8/site-packages/imageio/core/imopen.py:113, in imopen(uri, io_mode, plugin, extension, format_hint, legacy_mode, **kwargs) +File /opt/hostedtoolcache/Python/3.8.18/x64/lib/python3.8/site-packages/imageio/core/imopen.py:113, in imopen(uri, io_mode, plugin, extension, format_hint, legacy_mode, **kwargs) 111 request.format_hint = format_hint 112 else: --> 113 request = Request(uri, io_mode, format_hint=format_hint, extension=extension) @@ -3031,14 +3031,14 @@

The Noise Problem 117 # fast-path based on plugin 118 # (except in legacy mode) -File /opt/hostedtoolcache/Python/3.8.17/x64/lib/python3.8/site-packages/imageio/core/request.py:247, in Request.__init__(self, uri, mode, extension, format_hint, **kwargs) +File /opt/hostedtoolcache/Python/3.8.18/x64/lib/python3.8/site-packages/imageio/core/request.py:247, in Request.__init__(self, uri, mode, extension, format_hint, **kwargs) 244 raise ValueError(f"Invalid Request.Mode: {mode}") 246 # Parse what was given --> 247 self._parse_uri(uri) 249 # Set extension 250 if extension is not None: -File /opt/hostedtoolcache/Python/3.8.17/x64/lib/python3.8/site-packages/imageio/core/request.py:407, in Request._parse_uri(self, uri) +File /opt/hostedtoolcache/Python/3.8.18/x64/lib/python3.8/site-packages/imageio/core/request.py:407, in Request._parse_uri(self, uri) 404 if is_read_request: 405 # Reading: check that the file exists (but is allowed a dir) 406 if not os.path.exists(fn): diff --git a/examples/general/loading_images.html b/examples/general/loading_images.html index be6f9a3ef..cff4c7342 100644 --- a/examples/general/loading_images.html +++ b/examples/general/loading_images.html @@ -2974,7 +2974,7 @@

Directly in Python 1 fig, ax = subplots(figsize=[5, 5]) ----> 2 ax.imshow(seq[0]); -File /opt/hostedtoolcache/Python/3.8.17/x64/lib/python3.8/site-packages/skimage/io/collection.py:301, in ImageCollection.__getitem__(self, n) +File /opt/hostedtoolcache/Python/3.8.18/x64/lib/python3.8/site-packages/skimage/io/collection.py:301, in ImageCollection.__getitem__(self, n) 298 raise TypeError('slicing must be with an int or slice object') 300 if type(n) is int: --> 301 n = self._check_imgnum(n) @@ -2982,7 +2982,7 @@

Directly in Python 304 if ((self.conserve_memory and n != self._cached) or 305 (self.data[idx] is None)): -File /opt/hostedtoolcache/Python/3.8.17/x64/lib/python3.8/site-packages/skimage/io/collection.py:357, in ImageCollection._check_imgnum(self, n) +File /opt/hostedtoolcache/Python/3.8.18/x64/lib/python3.8/site-packages/skimage/io/collection.py:357, in ImageCollection._check_imgnum(self, n) 355 n = n % num 356 else: --> 357 raise IndexError(f"There are only {num} images in the collection") @@ -2991,7 +2991,7 @@

Directly in PythonIndexError: There are only 0 images in the collection -../../_images/26f4ba9b7e9ed4c8437a4492768176299335dd3bad04d67f58f9100574cfa0d3.png +../../_images/a7663852885818c489c8eebf335162a8d8a53fcae218b7308ef5390397bc3f44.png

We can convert this list into a 3D image as follows:

diff --git a/examples/generators/reference/blobs.html b/examples/generators/reference/blobs.html index ffd61d7c5..2b189b6df 100644 --- a/examples/generators/reference/blobs.html +++ b/examples/generators/reference/blobs.html @@ -2930,7 +2930,7 @@

shape
-../../../_images/405eebfd6f1ef6534707a76bd6e3e12035c8cbe63322982460ef425a60874486.png +../../../_images/35a965eeee72798e65c3bd4eda6db1ef99025bdbdbcbd3be3c604eb94f6cb23d.png
@@ -2948,7 +2948,7 @@

porosity
-../../../_images/e404eea8961cf32506a7a38b64fcee5c93674334743f24591b4cdde63955377d.png +../../../_images/878f8217ba0012f0330008339bea62f41804cc140e70f8e4a0100365e96215e6.png

Specifying porosity=None will return a greyscale image which can then be thresholded to get a boolean image. The greyscale value are adjusted to a unifrom distribution:

@@ -2965,7 +2965,7 @@

porosity
-../../../_images/0fbf752b3317faa2b52ddd7f4c757c2ef5118080dc35819d36fb34197107508a.png +../../../_images/e34dc299282d7599befcea14dbdbe576954ed966e6d455f31497f5ae913f8587.png
@@ -2982,7 +2982,7 @@

porosity

-../../../_images/b43bfca79104375b34c7321cae6f0108795d58d57fa6e7bd501b918c4b0ed10f.png +../../../_images/78ba8eadb94dd87c92854f10e1fbff8e2966e7ee7fe7a29fbaf4d27dc4f247dd.png
@@ -3004,7 +3004,7 @@

blobiness
-../../../_images/71211bafd35ec27d9240135f576cae20fdee9dfaf6bb3280dcf56ce524b6f6e2.png +../../../_images/c56cc8c3f8b211a461c3f71abb52d7c7f31e984edb3a1d724d856bf48d6da138.png
@@ -3022,7 +3022,7 @@

blobiness

-../../../_images/e157e0eee5d2d2e1a41d28992a2fd1dc9fb145f0f600a0a679c433ac457131d5.png +../../../_images/0b5eca66b12dbbd7ee0470ce143bb55f0e38dd629749033a657c863f15daec45.png
@@ -3044,7 +3044,7 @@

Reproducing Images -../../../_images/ab3edf5fa708fb15a783e82ecfbb129d596a59d34bcbfd6f8ef7d60498e005f4.png +../../../_images/ce1586c07c3c84db933bd1af7f1d56ce9490a271fe83fd6606c17ab5797c35db.png diff --git a/examples/generators/reference/cylinders.html b/examples/generators/reference/cylinders.html index 7e987fd12..b238daa76 100644 --- a/examples/generators/reference/cylinders.html +++ b/examples/generators/reference/cylinders.html @@ -42,7 +42,7 @@ - + @@ -2984,7 +2984,7 @@

shape
-../../../_images/65d932f8bb0ab55daa7e65e847e713866f6ce6b7494f468ce3ae50515a63b761.png +../../../_images/7e2e82d868269af794bd21f4ae65aac88c18f6631e0c9fc7cb6ecf233a5ac7ae.png
@@ -3009,7 +3009,7 @@

r
-../../../_images/1e8890b8b9a3945eb6c0ae676e9ef29d390089b210df88ef2957a21e74f86db9.png +../../../_images/bc9209119904cc9315ced3abc7ba0b0560019f40bddee8f0272ab0fe9cdb81d0.png
@@ -3035,7 +3035,7 @@

ncylinders
-../../../_images/5f0530cd540b743d229e93b7ef24ebfdf55e500b2867a71e2f96c4972d04bbbd.png +../../../_images/44210dac99b2b585a6201277a5715ed8b78355a5044162e8450680b259da8644.png
@@ -3063,7 +3063,7 @@

porosity
-../../../_images/1a3c681edf9bfa93645ed4a8da9fb86864ff5541d54840ce1f5b5ca57c21811e.png +../../../_images/3035437ec9c49adfe1a68f94cbc5774bbb22b9406457a8d97f17ded429c33416.png
@@ -3086,7 +3086,7 @@

phi_max<
-../../../_images/49226c9101c6ee4f3d20d98dcc83b8c3a0cb371e2c08f16611aa62a4a06ac1e7.png +../../../_images/7377f7e649d19e36d2bcaa19cb85728ad28e94154d4c3bf3935ecb17a29c354c.png
@@ -3105,7 +3105,7 @@

phi_max<

-../../../_images/2aec9083684fba1ab9106a937972eebef5789a992575d3cfdd2c8a84504f0601.png +../../../_images/7546d5ab9aee111bf09f126fb8a55f7acc948135c9fd617ca6a237495ae72d83.png
@@ -3128,7 +3128,7 @@

length
-../../../_images/3cbbd4ea482e0153d7cacf9e68634b00ce4e00a95a2ad91112b59b7bb9220033.png +../../../_images/e602a14f009bad057af46c0835642c0a17e3521d45d22a7e8a90992cd50e1328.png
@@ -3154,7 +3154,7 @@

maxiter<
-../../../_images/bcbbe84ee1d4fb1d5ddd109bc58b6128f55f3a499cb152b32c12f297d9734acb.png +../../../_images/85529be584c12d13dc83e5be3f26b67ebb977d459497653e9a9da1f6f79d5887.png
diff --git a/examples/generators/reference/cylindrical_plug.html b/examples/generators/reference/cylindrical_plug.html index 1d08ff140..b9104063e 100644 --- a/examples/generators/reference/cylindrical_plug.html +++ b/examples/generators/reference/cylindrical_plug.html @@ -2939,7 +2939,7 @@

shape
-../../../_images/970bcdab6864d3cf4986cffdda9a25b2b3b55ddea72c5e42a6622b894c25765f.png +../../../_images/1c42d8e40d2a4a08e46d2efc05bc1107d99aae64fefbf7ecd8b1c39e6a039f03.png

Or to generate a 2D disk

@@ -2953,7 +2953,7 @@

shape
-../../../_images/cab0bb27eee5e8e72212c89d5a735b05438da8153f4a7b0956f81c730ddeeef2.png +../../../_images/5dbc8622688fcd444bc61c800c74b576d98d85a5c0373cc97c1969ee28864f50.png
@@ -2979,7 +2979,7 @@

r
-../../../_images/d9af28f8de8cbdf48166523440aebd8a41b596cf6b192ed03e0218381dd8f9d8.png +../../../_images/1c0a1ec429a591a4b1023e7f5cf859291a14e0f4e3fa71a4025f0f6223f09810.png
@@ -3002,7 +3002,7 @@

axis
-../../../_images/a4057bb3875e9df28fffca596bc4082e0b3b23648987e475a049d2363aed787c.png +../../../_images/0f359431a4e8a365316810def3f85a24c001be842f53ae33f27929cf5c166013.png
diff --git a/examples/generators/reference/faces.html b/examples/generators/reference/faces.html index 9fdbcf4bb..500602f34 100644 --- a/examples/generators/reference/faces.html +++ b/examples/generators/reference/faces.html @@ -2936,7 +2936,7 @@

shape
-../../../_images/7a84dcffb6ababd28e90dfd5a6656abb9127a436a605629dfe603bd57690d173.png +../../../_images/18c460b7c705857fd0722571040af8465c73eb0debd50daefe9d404dd75e5770.png
@@ -2953,7 +2953,7 @@

inlet
-../../../_images/afbc3bc5fefc2766b5030bed22ea04af7350ecfd18e46f30675acf9b3397668d.png +../../../_images/ab6f343867bad3dc71b1a76c286957ceb4e3f8438cd305d64ac0875390d48884.png
diff --git a/examples/generators/reference/lattice_spheres.html b/examples/generators/reference/lattice_spheres.html index 3e6518cdf..afdff24e1 100644 --- a/examples/generators/reference/lattice_spheres.html +++ b/examples/generators/reference/lattice_spheres.html @@ -2956,7 +2956,7 @@

radius
-../../../_images/1efa227d41afe3f0046b4c6446f9754658ac58748baa9e91e9ab5dc88339c72c.png +../../../_images/312252eb76588ec1e21e1cb5dec8e2918c0f4a3473ee6ad89295d09f06bd3cf7.png
@@ -2983,7 +2983,7 @@

spacing<
-../../../_images/6277f389b1521b1b6c7e2f51e0dbb5d557ae19cdf6557c43a1133230beef8e2d.png +../../../_images/f5ea339814e5d110b141886a2f94fe7a10e412195fd53e82333a18df1ab00d08.png
@@ -3009,7 +3009,7 @@

offset
-../../../_images/ef1762d378a71f5898f510cd7f7be959ef60c0f4389f65e67f1e0fe92751b426.png +../../../_images/fcbf40012e1a9cbd75f905659a9678c454200479dfdecbc98455ac6f761b0a81.png
@@ -3038,7 +3038,7 @@

lattice<
-../../../_images/9ec60b6162972c618002b41d511c9992ee7d1cc2ddb61fad77eb8ea562bbb763.png +../../../_images/9ea64f88cc5c42cf3103b0edcc3b16f540199cb266db1d65cbf3de1c3b6b53d2.png

In 3D the options are simple cubic (‘sc’), face centered cubic (‘fcc’), and body centered cubic (‘bcc’). It’s more difficult to visualize in 3D but PoreSpy has a basic function called “show_3D” that works if the image is small:

@@ -3070,7 +3070,7 @@

lattice<
-../../../_images/acbff07116d3cf4b7555864ec17a2ca74a11d7e91f5b9a6fdead9a3405d68881.png +../../../_images/399395a2b763fdc9fdbaacb9028f9c576c470b2fbcd49a5e9477c0898f3feb64.png
diff --git a/examples/generators/reference/overlapping_spheres.html b/examples/generators/reference/overlapping_spheres.html index 6d90548b5..223b397ba 100644 --- a/examples/generators/reference/overlapping_spheres.html +++ b/examples/generators/reference/overlapping_spheres.html @@ -2960,7 +2960,7 @@

radius
-../../../_images/6e47a78caee843fb30bd8a2ce4d2b2e278529a8174f128b19e5a8d474fc75960.png +../../../_images/bf243d110b93483104aae2c4cca61084bb24dd80fba93f70335fa17e6215aacf.png
@@ -2987,7 +2987,7 @@

porosity
-../../../_images/b9aa295547d685dc772a2c9496157e3144f311b54c3425a43d69c88cee49d375.png +../../../_images/359c887845ea3149548260dd109479c68dc78449066deee04c7d124f1aadb712.png
@@ -3022,7 +3022,7 @@

max_iter porosity = 0.406125 -../../../_images/af6d97c6fcee8119f6ac5c33713d38273c17e3ca97a950486e2693bc1397eece.png +../../../_images/b74d9b08129010d13a08fbaf14f62babcdda1673cbf150d1591421a6777605f4.png

@@ -3057,10 +3057,12 @@

tol 
target porosity = 0.4
 porosity =  0.406125
-porosity =  0.400225
-../../../_images/0d02a5810376ecd8550db15d64b802d1a94558fd00a5b5c3b1455ee59537f5b3.png +
porosity =  0.400225
+
+
+../../../_images/06ae40cef6e1c0f73b21bfaae76304b749ba3d9a20ba4617711fced715a31b9b.png diff --git a/examples/generators/reference/pseudo_electrostatic_packing.html b/examples/generators/reference/pseudo_electrostatic_packing.html index aeda99206..4bd5e6e9c 100644 --- a/examples/generators/reference/pseudo_electrostatic_packing.html +++ b/examples/generators/reference/pseudo_electrostatic_packing.html @@ -42,7 +42,7 @@ - + @@ -2972,7 +2972,7 @@

im
-../../../_images/f95ea3ea675dd893fffa9a78192529c5a78658fce2a2479efc086635774676ef.png +../../../_images/0660d421f907c22d7c60d0b9bedd098d0a4993346ed980197bfe4fa169b64f93.png
@@ -2994,7 +2994,7 @@

sites
-../../../_images/fcda6af98f6f8880a9bb091d11731c317ea38439f6b0cae5439c68ac21f08aee.png +../../../_images/bc88d230d2e4ec58e14724ea78d99df3daae2b7ff7b11dd1449dd86bfc692d1b.png
@@ -3020,7 +3020,7 @@

r
-../../../_images/1ac25e48bf4e7de0c8b0e2b2e9c647d9beecc576dcb284f9bbe98cc077ffc1b4.png +../../../_images/dab75ae2f7cd2ffb83a5e0c13aedec0d74f0f722dcb4064d1948ea1279aa553b.png
@@ -3044,7 +3044,7 @@

clearance
-../../../_images/3823da553653aedf5d4693debd3decdba8d0b659ed7c6e9300b59ce384f09400.png +../../../_images/fac278f815e8a7e58fb53c03204b3f5140ca3fca3e55cfcd3c5ca58b4dcbafd0.png
@@ -3068,7 +3068,7 @@

protrusion
-../../../_images/9ebd9fb02a80e5551af31ab3cbbd4724e4c32b0713d08d51b66238d2f4f0e71e.png +../../../_images/37b88fd60e45437cc3966dbab4139d25e09f83c0008a03326493d03c65e73fd4.png
@@ -3092,7 +3092,7 @@

maxiter<
-../../../_images/58fa7be8798e344d666068a664fdd3a804067287cd058e40a71d41bcf850b0fa.png +../../../_images/54ce52b23d8b48ff9440791f579f1c91a662619984ff57c2344a6f95b9445a29.png
diff --git a/examples/generators/reference/rsa.html b/examples/generators/reference/rsa.html index 3d9648b87..f30f5abcc 100644 --- a/examples/generators/reference/rsa.html +++ b/examples/generators/reference/rsa.html @@ -2955,11 +2955,11 @@

im_or_shape
-
/tmp/ipykernel_7936/3616168134.py:3: DeprecationWarning: Call to deprecated function (or staticmethod) rsa. (This function will be renamed random_spheres in a future version)
+
/tmp/ipykernel_8230/3616168134.py:3: DeprecationWarning: Call to deprecated function (or staticmethod) rsa. (This function will be renamed random_spheres in a future version)
   im = ps.generators.rsa(im_or_shape=shape, r=r)
 

 

-../../../_images/70ae8f15376101e79e01ffb4d84936655365634f76d07b388b8ec99b61c56ab4.png
+../../../_images/f4e2fa626ab97e4a28d268bca449576232532abf7936fed525da68144e4cca57.png

Now let’s fill up the remaining space with as many smaller spheres as possible:

@@ -2974,11 +2974,11 @@

im_or_shape

-
/tmp/ipykernel_7936/3742233897.py:2: DeprecationWarning: Call to deprecated function (or staticmethod) rsa. (This function will be renamed random_spheres in a future version)
+
/tmp/ipykernel_8230/3742233897.py:2: DeprecationWarning: Call to deprecated function (or staticmethod) rsa. (This function will be renamed random_spheres in a future version)
   im = ps.generators.rsa(im_or_shape=im, r=r)
 

 

-../../../_images/cef97188cb6b5eeb9fd65b4b0a5b87fd0620d2ddd1428171341345fbf0a5e4bc.png
+../../../_images/bb376ce953113459af996881e51977bba166417f382e48b5722ff2a020142b81.png
@@ -3005,15 +3005,13 @@

mode

-
/tmp/ipykernel_7936/880368931.py:5: DeprecationWarning: Call to deprecated function (or staticmethod) rsa. (This function will be renamed random_spheres in a future version)
+
/tmp/ipykernel_8230/880368931.py:5: DeprecationWarning: Call to deprecated function (or staticmethod) rsa. (This function will be renamed random_spheres in a future version)
   im1 = ps.generators.rsa(im_or_shape=shape, r=r, mode=mode)
-

-

-
/tmp/ipykernel_7936/880368931.py:11: DeprecationWarning: Call to deprecated function (or staticmethod) rsa. (This function will be renamed random_spheres in a future version)
+/tmp/ipykernel_8230/880368931.py:11: DeprecationWarning: Call to deprecated function (or staticmethod) rsa. (This function will be renamed random_spheres in a future version)
   im2 = ps.generators.rsa(im_or_shape=shape, r=r, mode=mode)
 

 

-../../../_images/22aa83eb65b61771b18c52b52186653b78ba81fd824cc942088bd3861cebd4bb.png
+../../../_images/7a84b5dd526be20a40b6087e04e1f5c5533c62301c0a05ddb6b2cf54e544f25d.png
@@ -3039,13 +3037,13 @@

clearance

-
/tmp/ipykernel_7936/2646574643.py:4: DeprecationWarning: Call to deprecated function (or staticmethod) rsa. (This function will be renamed random_spheres in a future version)
+
/tmp/ipykernel_8230/2646574643.py:4: DeprecationWarning: Call to deprecated function (or staticmethod) rsa. (This function will be renamed random_spheres in a future version)
   im1 = ps.generators.rsa(im_or_shape=shape, r=r, clearance=c)
-/tmp/ipykernel_7936/2646574643.py:10: DeprecationWarning: Call to deprecated function (or staticmethod) rsa. (This function will be renamed random_spheres in a future version)
+/tmp/ipykernel_8230/2646574643.py:10: DeprecationWarning: Call to deprecated function (or staticmethod) rsa. (This function will be renamed random_spheres in a future version)
   im2 = ps.generators.rsa(im_or_shape=shape, r=r, clearance=c)
 

 

-../../../_images/cbf21480b9334f7b152a5ec31652f4efeb23f1173a6de91ec1231a9bac218afc.png
+../../../_images/76324074c7fc3afb51357aee4f1bf4d56d3bcc768ab5cc06a8d8f40320ec8665.png

When adding additional spheres to an existing image, the clearance only applies to new spheres. To enforce clearance between the existing spheres you can dilate them by the amount of clearance desired (or erode them if overlap is desired). In this case you’ll want to set return_sphers=True to obtain an image of only the new spheres, which can be added to the original ones:

@@ -3062,11 +3060,11 @@

clearance

-
/tmp/ipykernel_7936/2892074603.py:2: DeprecationWarning: Call to deprecated function (or staticmethod) RSA. (This function has been renamed to rsa (lowercase to meet pep8))
+
/tmp/ipykernel_8230/2892074603.py:2: DeprecationWarning: Call to deprecated function (or staticmethod) RSA. (This function has been renamed to rsa (lowercase to meet pep8))
   im4 = ps.generators.RSA(im_or_shape=im3, r=5, clearance=5, return_spheres=True)
 

 

-../../../_images/9ea6702d92a913f8f819033663c608f8ee89de1c33212f0813660225085d5795.png
+../../../_images/4029f91d6cb4a47e7618bc7cf36039f0348d939c535a0ed6a5313d643019ae2f.png
@@ -3092,13 +3090,13 @@

volume_fraction

-
/tmp/ipykernel_7936/1007371573.py:4: DeprecationWarning: Call to deprecated function (or staticmethod) rsa. (This function will be renamed random_spheres in a future version)
+
/tmp/ipykernel_8230/1007371573.py:4: DeprecationWarning: Call to deprecated function (or staticmethod) rsa. (This function will be renamed random_spheres in a future version)
   im1 = ps.generators.rsa(shape, r=r, clearance=c, n_max=n_max)
-/tmp/ipykernel_7936/1007371573.py:10: DeprecationWarning: Call to deprecated function (or staticmethod) rsa. (This function will be renamed random_spheres in a future version)
+/tmp/ipykernel_8230/1007371573.py:10: DeprecationWarning: Call to deprecated function (or staticmethod) rsa. (This function will be renamed random_spheres in a future version)
   im2 = ps.generators.rsa(shape, r=r, clearance=c, volume_fraction=vf)
 

 

-../../../_images/3469cdc3a142d5fae716d5d5e53404ce80b9f92207380629a61eea8f4da37319.png
+../../../_images/1239c9bcd693ccd2594a4369935480c3abc95312cbc745748c86d05a0b59913e.png

Note that this function returns the spheres as True which usually indicates the pore phase in porespy, so these will treated as images of holes. If you intended to make an image of sphers, just invert the image:

@@ -3115,7 +3113,7 @@

volume_fraction

-../../../_images/1520925fb9105ddb549e2fdea8be54274a0b082326f286403839053f8b4d8d0e.png +../../../_images/8de2da85e0b7e63146a3889806dd0010d61ca07b582b9139c1bc2424c8bd1910.png
diff --git a/examples/generators/reference/spheres_from_coords.html b/examples/generators/reference/spheres_from_coords.html index d8866909e..1148118e6 100644 --- a/examples/generators/reference/spheres_from_coords.html +++ b/examples/generators/reference/spheres_from_coords.html @@ -2967,7 +2967,7 @@

df
-../../../_images/d40939ccaa9387ebe8e49742fc75042a261890fa22cca30d8e5e4e3f1de99452.png +../../../_images/7d0f94d7cea9f1f04009e52595d20d212e1d30ae2b3b936653f8a1bb2662dedd.png

It is also acceptable to pass a python dict:

@@ -2980,7 +2980,7 @@

df
-../../../_images/d40939ccaa9387ebe8e49742fc75042a261890fa22cca30d8e5e4e3f1de99452.png +../../../_images/7d0f94d7cea9f1f04009e52595d20d212e1d30ae2b3b936653f8a1bb2662dedd.png

It is also acceptable to leave the ‘X’ or ‘Y’ columns as 0’s. The function will ignore the column with all 0’s and return a 2D image.

@@ -2993,7 +2993,7 @@

df
-../../../_images/d40939ccaa9387ebe8e49742fc75042a261890fa22cca30d8e5e4e3f1de99452.png +../../../_images/7d0f94d7cea9f1f04009e52595d20d212e1d30ae2b3b936653f8a1bb2662dedd.png

Of course, it also works with 3D images:

@@ -3006,7 +3006,7 @@

df
-../../../_images/4a3a3c9b1cd8edd1afc899bf232f265ab58094dfd1cb5c32b58df7c08de9255e.png +../../../_images/f6b7b6f2d36e056c5bb7e3b31b9de9b3857dec98868519d061d567f785220d2b.png
@@ -3024,7 +3024,7 @@

mode
-../../../_images/88eb5fb8816b92edbb2f6a3ed4988f23ab2611b4d783f992d2378df4f8814da8.png +../../../_images/78b910f3e04927e3e24c13762cd5e6574e1791538987a897e8eb2280e19c3d04.png
@@ -3042,7 +3042,7 @@

smooth
-../../../_images/d21142cefc87a6493910bd400c5d0d68daf5af45d01ada0c150f28fa1843ca1b.png +../../../_images/e5ba1930faf66cafb5e726c780407ec33f5705f46e1ce24f817ad358c9ed5f7a.png
diff --git a/examples/generators/reference/voronoi_edges.html b/examples/generators/reference/voronoi_edges.html index cca54d6ca..da34d1ca5 100644 --- a/examples/generators/reference/voronoi_edges.html +++ b/examples/generators/reference/voronoi_edges.html @@ -2949,7 +2949,7 @@

shape
-../../../_images/aed46c89a6a047b8999a3129465d080988b88dc7b5c91c6621824d080fc901f8.png +../../../_images/ae1aac11968b4673765e87458ec4fd1005c9a24e81b8d7b1038c405776e211a9.png
@@ -2964,7 +2964,7 @@

shape

-../../../_images/a83e34e2f3da024c65c4c81cff558979c583f30ba2c91cd9e4d6ad49d6fd63b2.png +../../../_images/ce88cacdac803fcf6c0d29c718129c62b5f312f2dd35a26ca7afb75cba5b6a87.png
@@ -2983,7 +2983,7 @@

flat_faces
-../../../_images/cbd80fc7c2452c0e50d337bf60bfdc656a818e08fdf39b9f4ed21cd698db56bb.png +../../../_images/cb99eec29c9f3b984824ef257cc2b4212c1a22000cd7e4c53097d21dcefe8db1.png
@@ -3010,7 +3010,7 @@

r
-../../../_images/bd4e2c1af83867153ef19d6298bf59154ff72f034c408bdf00b1c8b455abf7e1.png +../../../_images/15e610634f07073e5286a400092265498279fceb5521ee672d7174f139ee817a.png
@@ -3036,7 +3036,7 @@

ncells
-../../../_images/0e2ac5ab2628f95b2a860d6805adadaea0088d092f4f340294e225803d038855.png +../../../_images/146a23ec34110352ba0d9cbadd534b73ae7baf0c93df23b58cf24d8d0d3038dd.png
diff --git a/examples/generators/tutorials/Creating_Multiscale_Images.html b/examples/generators/tutorials/Creating_Multiscale_Images.html index 1e78884dc..67862dcb9 100644 --- a/examples/generators/tutorials/Creating_Multiscale_Images.html +++ b/examples/generators/tutorials/Creating_Multiscale_Images.html @@ -42,7 +42,7 @@ - + @@ -2936,7 +2936,7 @@

Using blobs
-../../../_images/a13609cd1d768532aca2c060c79d424f549d17d07edcff30410dd66ec4fc07cf.png +../../../_images/dcb59b4fe72ead478ab2cadbfdcd075b2fec37b2c8f85961187e023972081efa.png

Now we’ll can create a second image of blobs, but with a different scale. These will represent the ‘sub-structure’:

@@ -2950,7 +2950,7 @@

Using blobs
-../../../_images/c5a5f1c4e7a1d28defbe988c793b35289d8c5f5d3c49265eb703ed4552de424b.png +../../../_images/92d146fd94e9b5c06d4dee662a61439ed0561009fb6046363ddea2ad03fb068c.png

Finally, we can multiply these two image (i.e. arrays) together, which will have the effect of perforating the foreground phase of im1 with holes defined by the background phase of im2. Note the inverting of the image to ensure the foreground and background are maintained:

@@ -2964,7 +2964,7 @@

Using blobs
-../../../_images/15f286f3ff72f1b5a7285ea7d2fe31deb418338ff539d22d0bd4548d615501bf.png +../../../_images/c1b7119367cf4c6e42ac2a746a852a704dd20c5d06809f6f791891006a35b221.png

The pore sizes can be analyzed using local_thickess, to confirm a bi-modal pore size distribution:

@@ -2976,7 +2976,7 @@

Using blobs
-
+
@@ -2985,7 +2985,7 @@

Using blobs

-../../../_images/ad007a3d9e51eb363ea088af7813396aaebef432f3e7769cd3debd207003c5f3.png +../../../_images/58d21eee8e1a5a6d4f80ec8176a1086f391462fc8895db388d8b80ed16915f57.png
@@ -3002,11 +3002,11 @@

Using rsa
-
/tmp/ipykernel_8141/1658317612.py:1: DeprecationWarning: Call to deprecated function (or staticmethod) rsa. (This function will be renamed random_spheres in a future version)
+
/tmp/ipykernel_8426/1658317612.py:1: DeprecationWarning: Call to deprecated function (or staticmethod) rsa. (This function will be renamed random_spheres in a future version)
   im4 = ps.generators.rsa(im1, r=10, clearance=-2)
 

 

-../../../_images/d4fa8c14e7733d8056204617b3543a9b0894be5ac3aad532b17816182f5e3585.png
+../../../_images/90cefe1536de23b4c5ee851e8029ba1e0752c5536b363737046dc1a8c0147fcc.png
diff --git a/examples/generators/tutorials/cylinders.html b/examples/generators/tutorials/cylinders.html index 66cdb94e7..d3acf02df 100644 --- a/examples/generators/tutorials/cylinders.html +++ b/examples/generators/tutorials/cylinders.html @@ -2955,7 +2955,7 @@

Generating fibrous mats

-../../../_images/2d76ca0ad1d1c00972310139d110337eac359e56a9bb528c30dbcdc2bdfe40c6.png +../../../_images/1e299a1661d87294d064b5e22aee50e1cdaf608972a7a2021034dc4ce8d69755.png

This next block shows that the time penalty over inserting the same number of fibers using generators.cylinders is about 2x, and the time penalty ratio increases with requested porosity, when image generation is faster anyway.

@@ -3009,7 +3009,7 @@

Generating fibrous mats
-../../../_images/30f204911c5f555d35fb663bd89c638e2e331b28f925133c570a4bf581e23f65.png +../../../_images/b255d0a3efb65ab30c9e34c3ca2c8deee8e47b9c5830d6456d9ff8f2e0672fbd.png

Lastly, this block shows that more iterations improves proximity to goal porosity.

@@ -3039,7 +3039,7 @@

Generating fibrous mats
-../../../_images/75527b994bc3df698d63238b2132e283d1cee7df26cfbec67496042aa2108411.png +../../../_images/73ee803c2d0faadfe8beaa178fcc6d044ecf157ef63178dcff15f0d0f021c94e.png
diff --git a/examples/generators/tutorials/generate_spheres_packings.html b/examples/generators/tutorials/generate_spheres_packings.html index 3293a8a80..97e6d3439 100644 --- a/examples/generators/tutorials/generate_spheres_packings.html +++ b/examples/generators/tutorials/generate_spheres_packings.html @@ -2958,7 +2958,7 @@

Finney Packing -../../../_images/79c91c901dd96e39aeaec9745aa16995badc0db76b8b3de2c4c11af50bbaa085.png +../../../_images/64db45b31cd5d7215752896c1695017d28b31d058064fa2c6da641631c5aaac9.png

That was easy!

@@ -3087,7 +3087,7 @@

Bidisperse Sphere Packs
-../../../_images/8195767621e4df8d55aaa0e5b940b6ecd287a44db45713bb85814c7a511e1c0e.png +../../../_images/a89141aa974211e45087705b418bfc96f33fa29355b57e5e747ba6f55b4772cf.png
diff --git a/examples/generators/tutorials/making_blobs.html b/examples/generators/tutorials/making_blobs.html index ba44c5840..56b9e9302 100644 --- a/examples/generators/tutorials/making_blobs.html +++ b/examples/generators/tutorials/making_blobs.html @@ -2894,7 +2894,7 @@

Making blobs -../../../_images/0bc4eb94ee721b313c8b2ea73ae18a84d5bbdab32f3f3bc03a87569085d55d86.png +../../../_images/c2eb82e14e01f055e77d01c22a915379db86038c806bc360d8b60b2fa456b91e.png

The distribution of the values in these images has been renormalized to be a uniform distribution, which can be confirmed by plotting a histogram. Because the image is not very large, the histogram is not perfectly flat:

@@ -2906,7 +2906,7 @@

Making blobs -../../../_images/797ecfdecd10363d162d30882161027e226da20d0b595e2194824ca8080b59fd.png +../../../_images/dbdeee07754bba57580e7c8ed06ba0c8d8c6220fa4580e06a1b7566461944583.png

Next is easy to threshold the noise field to produce a binary image of ‘solid’ and ‘void’:

@@ -2919,7 +2919,7 @@

Making blobs -../../../_images/fa6df6ddbf2a4b7fe68345d0c19750df99c5b89a22896bcc1ab1b3a9b1eee4c9.png +../../../_images/61a1d5ea99fcdebe615cd0709d3586226b43c62b1942d403787818e62c399fe6.png

And we can check the porosity of the thresholded image:

@@ -2947,7 +2947,7 @@

Making blobs -../../../_images/25b404f9586fa37ef88f72be5b6d1bfafdea394356698c058a59ca550a4e9697.png +../../../_images/cc33d40190fda007b6030748d30e044b01794f4e329ec44cc8e4b381d13f0175.png
@@ -2979,7 +2979,7 @@

Making blobs -../../../_images/f52a3aee80abbcfec43b94dce03609a447a892c01f54133c3f08b997b746dfa2.png +../../../_images/b922f92cb2c72c886288f09236ef1e32f7157fb48270666b7101bee61f5d4db0.png

diff --git a/examples/metrics/reference/boxcount.html b/examples/metrics/reference/boxcount.html index 944c92f60..6160c4856 100644 --- a/examples/metrics/reference/boxcount.html +++ b/examples/metrics/reference/boxcount.html @@ -42,7 +42,7 @@ - + @@ -2929,7 +2929,7 @@

boxcount
-../../../_images/f7fd43bfc4ba84f2aca5c7cff7c080fb80ad6574a9b114541e6daa3310adf17e.png +../../../_images/64a100a3c4b3152cdf1656199271d4f5dbe9f71bcd46fde6732462c13a8f338d.png
@@ -2943,8 +2943,8 @@

im
-
――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――
-Results of boxcount generated at Thu Aug 24 13:11:41 2023
+
――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――
+Results of boxcount generated at Thu Sep 14 04:56:38 2023
 ――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――
 size                      Array of size (10,)
 count                     [6505, 4095, 1435, 552, 206, 77, 24, 9, 4, 1]
@@ -2971,7 +2971,7 @@ 
im
 

 

-../../../_images/4a1a535be7e4022543169c35e2ce7b9a97671c9a39a934702fb765b38b11db9c.png
+../../../_images/8a5bdc40de5979c4f4a556f7716b0a88a1fe5f240b6f5c01dfe2a1889a1adb6c.png

@@ -2995,7 +2995,7 @@

bins
-../../../_images/e5dbd84b3482815d5b7c7e14b3a43d6b5dc0ac18c8a2f939427dc496c946b2c6.png +../../../_images/12c4744559e5f0a446784b2afa44d9fb2d77160e012a62f66d7ec3caa03cb27c.png
diff --git a/examples/metrics/reference/find_h.html b/examples/metrics/reference/find_h.html index 61306b39c..3bb13b899 100644 --- a/examples/metrics/reference/find_h.html +++ b/examples/metrics/reference/find_h.html @@ -42,7 +42,7 @@ - + @@ -2930,7 +2930,7 @@

find_h
-../../../_images/dd9435975d4a5ea969734674c327ed5663c7115fb597538d501c0484e748e687.png +../../../_images/1a8fbdada61f078bfee60bd52b862d230dafa79c5e74205031d0324d655278a9.png

Next we need to find to convert the fluid configuration image into a saturation profile:

@@ -2944,7 +2944,7 @@

find_h
-../../../_images/52c590a3e14fadcc902d890d5336dbfb7d9b3a6f9af147c011260e08ac158c43.png +../../../_images/52f188b6249c33c7442bc33fda827477c60a526a8fa7e40bce3ee9f612171078.png

Finally, we can determine the height of the two phase zone:

@@ -2956,11 +2956,11 @@

find_h
-
[13:11:52] WARNING  The requested saturation range was adjusted to (0.01, 0.9768292682926829) to     _funcs.py:1305
+
[04:56:49] WARNING  The requested saturation range was adjusted to (0.01, 0.9768292682926829) to     _funcs.py:1305
                     accomodate data                                                                                
 

 
――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――
-Results of find_h generated at Thu Aug 24 13:11:52 2023
+Results of find_h generated at Thu Sep 14 04:56:49 2023
 ――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――
 valid                     False
 zmax                      4.5
@@ -2985,7 +2985,7 @@ 
srange
 

 
――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――
-Results of find_h generated at Thu Aug 24 13:11:52 2023
+Results of find_h generated at Thu Sep 14 04:56:49 2023
 ――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――
 valid                     True
 zmax                      24.5
diff --git a/examples/metrics/reference/lineal_path_distribution.html b/examples/metrics/reference/lineal_path_distribution.html
index 918b3e548..5ebd0bfe2 100644
--- a/examples/metrics/reference/lineal_path_distribution.html
+++ b/examples/metrics/reference/lineal_path_distribution.html
@@ -2926,7 +2926,7 @@ 
lineal_path_dis
 

 

 

-../../../_images/d124b00588f9618799dbeb0fc0bc472601220f660054ad874ad1b90bfe5adcc5.png
+../../../_images/19264588760e6deb506609c8757a49cc937cccef409c21191ad9ec8b800600ce.png
 

 

 
Now the test image is ready to be passed to lineal_path_distribution. The method returns a custom object with information of the distribution of the lineal path lengths.

@@ -2944,7 +2944,7 @@ 
lineal_path_dis
 

 

 

-../../../_images/c4acb02939576fa98f81ea44766b234cdb744825906056669bfbbd698cffaaf3.png
+../../../_images/5959604b9d3ddf96a33fbcacc3b3e8918bd886a7a00245a7e467d6e08cadc3ea.png
@@ -2964,7 +2964,7 @@

bins

-../../../_images/868a0f32a69b95d0fb567528e29a7e4b81f330089234f8e663de0e4233b5ddcd.png +../../../_images/5ee953b76b32789f1ae329216019a1dbe61806710429169499c5ecc256b55a09.png
@@ -2986,7 +2986,7 @@

log
-../../../_images/76f6064f0bf91ff3f99556aa0f150dfa6790788736b5da1af9f93187a0b3aa95.png +../../../_images/37c76700cdf8ef48b5322c5a182e2a5f82a285b3ea7edbab4c65cf03f8ebd09b.png
@@ -3007,7 +3007,7 @@

voxel_size
-../../../_images/6f53907e20bc0cb71241b463954a25b3805b960435b0f3be1157194cc4fe4398.png +../../../_images/7ed669d858285c6bf34caca5d039b3859ba793d2ce2404071ee6369bdd7ae389.png
diff --git a/examples/metrics/reference/pc_curve.html b/examples/metrics/reference/pc_curve.html index f63ffc8e1..d3fbdc8bc 100644 --- a/examples/metrics/reference/pc_curve.html +++ b/examples/metrics/reference/pc_curve.html @@ -42,7 +42,7 @@ - + @@ -2915,7 +2915,7 @@

pc_curve
-
+

sizes#

@@ -2927,7 +2927,7 @@

sizes
-
+

The function results a Results object, whose attributes can be inspected by printing:

@@ -2938,7 +2938,7 @@

sizes 
――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――
-Results of pc_curve generated at Thu Aug 24 13:12:05 2023
+Results of pc_curve generated at Thu Sep 14 04:57:04 2023
 ――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――
 pc                        [407.8608703277795, 815.721740655559, 924.1694802519894, 1047.0350190039558, 1186.2351597260008, 1343.9415383726086, 1522.6145033338332, 1725.041498880861, 1954.3805515746424, 2214.2095380610917, 2508.582002870727, 2842.090397026047, 3219.9377240305935, 3648.018710975678, 4133.011771100392, 4682.483192495964, 5305.005178383415, 6809.339411869592, 7714.620502905222, 11218.720341000993, 14399.999999999998]
 snwp                      [0.0, 0.04955537590945837, 0.07877930476960388, 0.0881568310428456, 0.09280517380759903, 0.21883589329021827, 0.2791430881164107, 0.3557801131770412, 0.4190784155214228, 0.6601455133387227, 0.8425222312045271, 0.8719482619240096, 0.9545675020210186, 0.9654405820533549, 0.9690379951495554, 0.9706548100242522, 0.9867016976556184, 0.9870654810024252, 0.9881568310428456, 0.9896928051738076, 0.9897736459175425]
@@ -2957,7 +2957,7 @@ 
sizes
-../../../_images/6e34e2d0fbe172f1fc48334564578ae7b507c93f1d1c7806128355a55f2cd2bc.png +../../../_images/3fc7bb0ef39fa458de438b175e1b591c89add7f8f5c0ca622af3148a990bad62.png

Or, other options:

@@ -2974,7 +2974,7 @@

sizes

-../../../_images/a1fc151eb81aeb5d1774d92ddb026ef46bd4c9f177140d3d00453f9d6ec1380b.png +../../../_images/c83d6666ab0e0dd9a6f9451e3b2f9271d3aefbe426ef00e49918a8a1b0f85f7e.png

@@ -3001,7 +3001,7 @@

pc
-../../../_images/b59ce7a573c76bad022d7fd6d62c7a2656256196c3c3d93c1f96663e72c26553.png +../../../_images/3a31c31b6a4238626c6ca83f7b7465f26c9d0972677eff946b5e6cd4fa0ec5e4.png

Note that some voxels in pc had a value of np.inf since they were uninvaded. The pc_curve function replaces these with 2*pressure.max() to improve the plotting.

diff --git a/examples/metrics/reference/porosity.html b/examples/metrics/reference/porosity.html index dc64f44d3..3da66a88b 100644 --- a/examples/metrics/reference/porosity.html +++ b/examples/metrics/reference/porosity.html @@ -2941,7 +2941,7 @@

im
0.49670287539936103
-../../../_images/56fe6af59af480dea76a547a09389361f50ee33dd49f7faadc53ea54dd078117.png +../../../_images/d4196f1b42135cc3f299debf0b65fa7a1bf26911ccd87ede3c234e0ce3f75141.png

The porosity specified when generatign the blobsimage was 50%, and the computed porosity is also 50%, despite having a regions of 2’s around the outside.

diff --git a/examples/metrics/reference/porosity_profile.html b/examples/metrics/reference/porosity_profile.html index 85f68db3c..79af256dd 100644 --- a/examples/metrics/reference/porosity_profile.html +++ b/examples/metrics/reference/porosity_profile.html @@ -2916,7 +2916,7 @@

im
-../../../_images/8a0663890538f0ba179b62287663d621406d816aca05f8411a4a47c112ef27f2.png +../../../_images/86bfd02e61e70f0bec93c194ea4bcbfca14b515bea68d958262b6d8f6b7db9df.png
@@ -2937,7 +2937,7 @@

axis
-../../../_images/a422f180bf916fb16264a28f56d2afd3817a6ceebf9f65c50866e71d2b67eace.png +../../../_images/a76ef0752d21b671e089dedd55dda260c50088a5618a490a6408ae9c6113a80e.png
diff --git a/examples/metrics/reference/props_to_DataFrame.html b/examples/metrics/reference/props_to_DataFrame.html index a5775245e..f9e122eb2 100644 --- a/examples/metrics/reference/props_to_DataFrame.html +++ b/examples/metrics/reference/props_to_DataFrame.html @@ -2889,7 +2889,7 @@

props_to_DataFr
-../../../_images/82ac31f530e915666e82a2ae960f5c5ae78184334085c086485b335c9b6b35ee.png +../../../_images/eef50f4e8fa74c1edc71519fc0422a6731505e1d00d33c74cd9ce58b78965642.png
@@ -2901,7 +2901,7 @@

props_to_DataFr

-../../../_images/95ae7dafbbe90064d43ce1f7312f0f93a6e450bf0c6515ad4c3bab78260188a8.png +../../../_images/e2396b3f0fc022d58fac86627f4a8b4d7edd168786254d76b8b3c0c63aecc131.png
diff --git a/examples/metrics/reference/props_to_image.html b/examples/metrics/reference/props_to_image.html index 92f7da77a..25cfe0952 100644 --- a/examples/metrics/reference/props_to_image.html +++ b/examples/metrics/reference/props_to_image.html @@ -2889,7 +2889,7 @@

props_to_image<

-../../../_images/82ac31f530e915666e82a2ae960f5c5ae78184334085c086485b335c9b6b35ee.png +../../../_images/eef50f4e8fa74c1edc71519fc0422a6731505e1d00d33c74cd9ce58b78965642.png
@@ -2901,7 +2901,7 @@

props_to_image<

-../../../_images/95ae7dafbbe90064d43ce1f7312f0f93a6e450bf0c6515ad4c3bab78260188a8.png +../../../_images/e2396b3f0fc022d58fac86627f4a8b4d7edd168786254d76b8b3c0c63aecc131.png
@@ -2918,7 +2918,7 @@

props_to_image<

-../../../_images/0b6f7bc62abc8ee1fafc6f95a21f90db59e9099d7505a072d0235077337bb83b.png +../../../_images/8f82763ccdf8698a4e5f3186c1d86124ae3f8927a08cb071de4ad42f9402873e.png
diff --git a/examples/metrics/reference/regionprops_3D.html b/examples/metrics/reference/regionprops_3D.html index 0dd00ef25..4723d4108 100644 --- a/examples/metrics/reference/regionprops_3D.html +++ b/examples/metrics/reference/regionprops_3D.html @@ -2888,11 +2888,11 @@

regionprops_3D<
-
/tmp/ipykernel_9284/538947285.py:1: DeprecationWarning: Call to deprecated function (or staticmethod) rsa. (This function will be renamed random_spheres in a future version)
+
/tmp/ipykernel_9583/538947285.py:1: DeprecationWarning: Call to deprecated function (or staticmethod) rsa. (This function will be renamed random_spheres in a future version)
   im = ps.generators.rsa([80, 80, 80], r=10, clearance=3)
 

 

-../../../_images/fff9ef913dc0cb864b8a6af32455e5bb9eac3c4de520dd4ba3a5a80043b4b616.png
+../../../_images/54ff4e9fec2d442d4540fe3bd1990ba23d343fe6e36f33864494908ce0b820b8.png

We need to label each sphere so they are recognized as individual regions:

@@ -2904,7 +2904,7 @@

regionprops_3D<

-../../../_images/4f1768b76622bb660003ce83f65371c1c5cb53e2c4124c3764c20c63f8b1d39a.png +../../../_images/e4b8abb8600e98a03fe0753db422bc26455b6c9d397ab818541bb3686e1a088a.png
@@ -2922,31 +2922,33 @@

regionprops_3D<

-
[<porespy.metrics._regionprops.RegionPropertiesPS at 0x7f9b4abfbdc0>,
- <porespy.metrics._regionprops.RegionPropertiesPS at 0x7f9b94cfe670>,
- <porespy.metrics._regionprops.RegionPropertiesPS at 0x7f9b94cfe1c0>,
- <porespy.metrics._regionprops.RegionPropertiesPS at 0x7f9b94cfe7f0>,
- <porespy.metrics._regionprops.RegionPropertiesPS at 0x7f9b94cfeac0>,
- <porespy.metrics._regionprops.RegionPropertiesPS at 0x7f9b4b1f7910>,
- <porespy.metrics._regionprops.RegionPropertiesPS at 0x7f9b4b1f7970>,
- <porespy.metrics._regionprops.RegionPropertiesPS at 0x7f9b4b1f7610>,
- <porespy.metrics._regionprops.RegionPropertiesPS at 0x7f9b94c84eb0>,
- <porespy.metrics._regionprops.RegionPropertiesPS at 0x7f9b94c84d90>,
- <porespy.metrics._regionprops.RegionPropertiesPS at 0x7f9b94c84dc0>,
- <porespy.metrics._regionprops.RegionPropertiesPS at 0x7f9b5061a460>,
- <porespy.metrics._regionprops.RegionPropertiesPS at 0x7f9b4aef2ee0>,
- <porespy.metrics._regionprops.RegionPropertiesPS at 0x7f9b4af5bbe0>,
- <porespy.metrics._regionprops.RegionPropertiesPS at 0x7f9b4af5b0a0>,
- <porespy.metrics._regionprops.RegionPropertiesPS at 0x7f9b4abfb220>,
- <porespy.metrics._regionprops.RegionPropertiesPS at 0x7f9b4abfb280>,
- <porespy.metrics._regionprops.RegionPropertiesPS at 0x7f9b4abfbca0>,
- <porespy.metrics._regionprops.RegionPropertiesPS at 0x7f9b4abfb250>,
- <porespy.metrics._regionprops.RegionPropertiesPS at 0x7f9b4abfb3a0>,
- <porespy.metrics._regionprops.RegionPropertiesPS at 0x7f9b4abfbe80>,
- <porespy.metrics._regionprops.RegionPropertiesPS at 0x7f9b4abfbf10>,
- <porespy.metrics._regionprops.RegionPropertiesPS at 0x7f9b4abfbeb0>,
- <porespy.metrics._regionprops.RegionPropertiesPS at 0x7f9b4abfbd60>,
- <porespy.metrics._regionprops.RegionPropertiesPS at 0x7f9b4abfbc40>]
+
[<porespy.metrics._regionprops.RegionPropertiesPS at 0x7f4aaffa7760>,
+ <porespy.metrics._regionprops.RegionPropertiesPS at 0x7f4ab53d11c0>,
+ <porespy.metrics._regionprops.RegionPropertiesPS at 0x7f4ab4236d30>,
+ <porespy.metrics._regionprops.RegionPropertiesPS at 0x7f4aff0ecfa0>,
+ <porespy.metrics._regionprops.RegionPropertiesPS at 0x7f4afc01bd90>,
+ <porespy.metrics._regionprops.RegionPropertiesPS at 0x7f4afc01b670>,
+ <porespy.metrics._regionprops.RegionPropertiesPS at 0x7f4afc01be50>,
+ <porespy.metrics._regionprops.RegionPropertiesPS at 0x7f4afc01b5b0>,
+ <porespy.metrics._regionprops.RegionPropertiesPS at 0x7f4afd0594c0>,
+ <porespy.metrics._regionprops.RegionPropertiesPS at 0x7f4ab40865e0>,
+ <porespy.metrics._regionprops.RegionPropertiesPS at 0x7f4ab4086550>,
+ <porespy.metrics._regionprops.RegionPropertiesPS at 0x7f4ab4086910>,
+ <porespy.metrics._regionprops.RegionPropertiesPS at 0x7f4ab4086970>,
+ <porespy.metrics._regionprops.RegionPropertiesPS at 0x7f4ab4086c10>,
+ <porespy.metrics._regionprops.RegionPropertiesPS at 0x7f4ab40869a0>,
+ <porespy.metrics._regionprops.RegionPropertiesPS at 0x7f4ab4086430>,
+ <porespy.metrics._regionprops.RegionPropertiesPS at 0x7f4ab4086b20>,
+ <porespy.metrics._regionprops.RegionPropertiesPS at 0x7f4ab4086a30>,
+ <porespy.metrics._regionprops.RegionPropertiesPS at 0x7f4ab4086a90>,
+ <porespy.metrics._regionprops.RegionPropertiesPS at 0x7f4ab4086610>,
+ <porespy.metrics._regionprops.RegionPropertiesPS at 0x7f4aaff953a0>,
+ <porespy.metrics._regionprops.RegionPropertiesPS at 0x7f4aaff95340>,
+ <porespy.metrics._regionprops.RegionPropertiesPS at 0x7f4aaff95670>,
+ <porespy.metrics._regionprops.RegionPropertiesPS at 0x7f4aaff952b0>,
+ <porespy.metrics._regionprops.RegionPropertiesPS at 0x7f4aaff95070>,
+ <porespy.metrics._regionprops.RegionPropertiesPS at 0x7f4aaff95d60>,
+ <porespy.metrics._regionprops.RegionPropertiesPS at 0x7f4aaffa7940>]
@@ -3067,7 +3069,7 @@

regionprops_3D<

-../../../_images/6b153d60211a19507935f3c59c21cdec3e68d70df3d8c68579ed68cab130a403.png +../../../_images/7956e6ff002a355b6f13c78e6751ba8c1599089ca8af6190e1fb6f6e96ddf6cc.png
diff --git a/examples/metrics/reference/satn_profile.html b/examples/metrics/reference/satn_profile.html index a920948ab..02e8f9af7 100644 --- a/examples/metrics/reference/satn_profile.html +++ b/examples/metrics/reference/satn_profile.html @@ -42,7 +42,7 @@ - + @@ -2966,7 +2966,7 @@

satn_profile
-../../../_images/dd9435975d4a5ea969734674c327ed5663c7115fb597538d501c0484e748e687.png +../../../_images/1a8fbdada61f078bfee60bd52b862d230dafa79c5e74205031d0324d655278a9.png
@@ -2982,7 +2982,7 @@

satn
-../../../_images/52c590a3e14fadcc902d890d5336dbfb7d9b3a6f9af147c011260e08ac158c43.png +../../../_images/52f188b6249c33c7442bc33fda827477c60a526a8fa7e40bce3ee9f612171078.png

@@ -3009,7 +3009,7 @@

s
-../../../_images/8153e37bbb540275cce09c8ecee5fa944e9ddcbd8eb758d103c5b390b3ddc8bb.png +../../../_images/4c1c72916d24c102141a9cb4016b61eaafe34dbd5ed10c074ad37b91d702c7da.png
@@ -3036,7 +3036,7 @@

span
-../../../_images/190e6b37d1c86992ad5ad302029122a06effad7eb43ea3f066f1c67d0dde7d84.png +../../../_images/3552e5e533ee775e76896af017da5f179bb3bc5695dbb02dae685e4cdff63322.png
@@ -3058,7 +3058,7 @@

mode
-../../../_images/80349e8df8da6250211c20b9e45645a7d9aafc558033980b7cf4a6df93bd4f26.png +../../../_images/93c9897bf54a23b07f86a6254833fa617ee3fb67520b3aee84dc7c3b6ef0becb.png
@@ -3080,7 +3080,7 @@

axis
-../../../_images/a2a0142ec2abf1b3b29c7b4ad8a93a057a5989a635b1902b5b1de4558ffb51fd.png +../../../_images/bc49cb32f4c16e419131001567118dd646230bfde8f40fbb8ec9e7d24796832b.png
diff --git a/examples/metrics/tutorials/computing_fractal_dim.html b/examples/metrics/tutorials/computing_fractal_dim.html index 894f6b0d8..2fb002a5e 100644 --- a/examples/metrics/tutorials/computing_fractal_dim.html +++ b/examples/metrics/tutorials/computing_fractal_dim.html @@ -44,7 +44,7 @@ - + @@ -2947,7 +2947,7 @@

Example -../../../_images/f35df386382972d4960b332e829d626b086adc2fd05e27f765cbd20918045313.png +../../../_images/40d087e34a2a5e425afce986a189213693dd8eddcbfd7651759fcd60c38fb20d.png

Finally, apply the box count function and visualize.

@@ -2958,7 +2958,7 @@

Example - +
@@ -2976,7 +2976,7 @@

Example -../../../_images/2dcee2757f9d27a3840e0100bd4a7e8bd8ffee131300a2aec6c95855c8a1bd0b.png +../../../_images/baffb8746f8a95e69fa032d80924243dc49209e956da297191d3f5879a50bbf7.png

The horizontal portion of the slope vs box edge length curve, between \(10^1\) and \(10^2\) is a flat line with a value of approximately 1.9. Beyond a box edge length of \(10^2\) the analysis becomes impacted by the finite image size so the result begins to diverge.

diff --git a/examples/metrics/tutorials/lineal_path_function.html b/examples/metrics/tutorials/lineal_path_function.html index 7e6223a6d..834135b38 100644 --- a/examples/metrics/tutorials/lineal_path_function.html +++ b/examples/metrics/tutorials/lineal_path_function.html @@ -2892,7 +2892,7 @@

The lineal path function -../../../_images/5317b31cdc0cbe76e7efa71cbe24ee2e0bd80a7e8c9649aba6bd4686083369e4.png +../../../_images/a51100ded44855c2ea2083e58b1a54c3a7b67285d5836d759176150235cb5087.png

Next apply the distance_transform_lin function along the 0 axis.

@@ -2904,7 +2904,7 @@

The lineal path function -../../../_images/63b01daf66110e93192e40a5160bb6fd087ff581114ba681d857570683371b57.png +../../../_images/40a745dddead973d15991f173f8838677a6e468840fbde53f5f4c26107459030.png

The greyscale values of the above image are worth a comment. They indicated the length of a path that can be drawn from each voxel to the nearest solid voxel, in the specified direction. Or in terms of Torquato’s definition, each greyscale value represents a random starting point (A) and moving along this line until solid is encountered represents the end of the line (B), providing the path length A \(\rightarrow\) B. The ‘counter associated with the distance between A and B is then incremented’, which corresponds to the binning the greyscale values in the above image. In other words, the above representation includes ALL possible starting points on each path, so provides the largest possible data set.

@@ -2927,7 +2927,7 @@

The lineal path function -../../../_images/adc35e436b0348dc23a4512ff817244e395e2108047b34f5267a22d848d9fb98.png +../../../_images/5a46c835a7ade513662787d7ec8a35139252170220ddcca3c9e86eefa2f74000.png

Since the image is anisotropic, the process will yeild a different result in the perpendicular direction, so repeating the above with axis=1 instead of the default axis=0.

@@ -2939,7 +2939,7 @@

The lineal path function -../../../_images/f399b21e66a1b2d211528c9d61bb22ad765f6e7f9f432b44320b0014045447c5.png +../../../_images/0973494de5e739613d2fb03ffbd71a9e193d4ff688208aed61a17b51a7d86ff5.png

Overlaying this result wit the previous one:

@@ -2952,7 +2952,7 @@

The lineal path function -../../../_images/336a7036b86f26b746b26237da4d51d4e60c884a377b8c405b225054663c9a2b.png +../../../_images/f182fa94c5a16e6a5b8c1a7d47d5fc5c1ffd6cd2b458ef508cc720ddb6c89c32.png

The anisotropy of the image is clearly visible with the first axis possessing longer lineal-path values.

diff --git a/examples/metrics/tutorials/porosity_profiles.html b/examples/metrics/tutorials/porosity_profiles.html index 04c90716d..eb2c12f88 100644 --- a/examples/metrics/tutorials/porosity_profiles.html +++ b/examples/metrics/tutorials/porosity_profiles.html @@ -2891,7 +2891,7 @@

Obtaining the porosity profile along each principle axis -../../../_images/ffc174d13feffde403408c11339b06e65b41ebb310223e69dfa73acd10d007b5.png +../../../_images/5fe7ed207e69ade604547613e64ffde69b1210296460b0461529c0e536f7937d.png

All results in PoreSpy are reported in voxels, so it is up to the user to scale these values to the physical size of each voxel. Here we’ll assume that each voxel corresponds to 5.9 microns.

@@ -2927,7 +2927,7 @@

Obtaining the porosity profile along each principle axis -../../../_images/aa376b63c1c2de4aa014d961cd88e1593fc3d8e46a88d24e6885b519e6a5ad2e.png +../../../_images/6a0f859965fe1f21986d77516dea69afce22b63169160d0c1a0406dcdc05689f.png

Note how each line ends at a different position on the x-axis. This is caused by the fact that image had different total length in each direction. We can also do the plots with each axis normalized by their total length:

@@ -2945,7 +2945,7 @@

Obtaining the porosity profile along each principle axis -../../../_images/e370331083e9f6dfe831ae41ef2cc849d105347b4e1aba0b352cd70e7fa4aaaf.png +../../../_images/d7a9cfe3db6bb661037dd7632967da0d1366d0be1072e5d5cd13d25192a673d3.png diff --git a/examples/metrics/tutorials/regionprops_3d.html b/examples/metrics/tutorials/regionprops_3d.html index f854c6fe5..86766b0ae 100644 --- a/examples/metrics/tutorials/regionprops_3d.html +++ b/examples/metrics/tutorials/regionprops_3d.html @@ -42,7 +42,7 @@ - + @@ -2942,7 +2942,7 @@

Generating a test image
-../../../_images/f7612376fdc8f3e8878f3d6ad7ab50aeb37e464cb9ccda046766432d29cb745c.png +../../../_images/2352ffd9f102cfd425ff26440ab61f4b46d60407e19643eb132f6cf356d78e18.png
@@ -2957,7 +2957,7 @@

Segementing void space into regions for individual analysis - +
@@ -2967,7 +2967,7 @@

Segementing void space into regions for individual analysis -../../../_images/0ed7a5aa37dc0f76e75f713f48971686901fef1667306c5cde4c709b9eb23633.png +../../../_images/c38e406edb9b1097513f1e7274ba1abeff91569d49b5eeaa15b0ba715b124c6a.png

@@ -3017,7 +3017,7 @@

Analyze properties for a single region -../../../_images/8b675cedeb9fad912bc7835eb23e2ffbc897f1926b8edb28c4d560e1f04d2df9.png +../../../_images/55ad88b2008e531da75ea53fb0d83472d033f31e2672e5c8c36d09ff43b80132.png

View image of region’s border and largest incribed sphere together.

@@ -3029,7 +3029,7 @@

Analyze properties for a single region -../../../_images/8a0966fd850754a088eac7b0f848fe39379a165d9d437a768c893132ab11faf4.png +../../../_images/36ce68ec4581640a9228aacb8aceb12af0c4219f0edf693f4964b6da5656d487.png

One of the more interesting properties is the convex image, which is an image of the region with all the depressions in the boundary filled in. This is useful because one can compare it to the actual region and learn about the shape of the region. One such metric is the solidity which is defined as the ratio of pixels in the region to pixels of the convex hull image.

@@ -3041,7 +3041,7 @@

Analyze properties for a single region -../../../_images/cb02cd164c659bcb55de16b3a0b134fee48d82421c7873017ed344337560f060.png +../../../_images/5d53ab08529531d3429a9c9bb76911aef1bdb190ad9e4e9127739ca8303c0c30.png
@@ -3082,7 +3082,7 @@

Extracting one property for all regions as an array

-../../../_images/ae08abcefb8f4d79a4be5d6198857f4d96771dcddb03a58e054acc44fce5e5a6.png +../../../_images/4f6e13d76f406ae4e5bfc0e13e47aae0fc9e9e7a5b34dcd0189b0d422a843ad7.png

Another useful feature of the Pandas DataFrame is the ability to look at all metrics for a given pore at once, which is done by looking at a single row in all columns:

@@ -3134,7 +3134,7 @@

Creating a composite image of region images -../../../_images/87f9041132f72cef9023014a1f60f077888684c61454b86a82206a8cb4d396c2.png +../../../_images/051cf71591c99ff95bedfccdf83ef6e0d3e11739a0e60f1c19d347c2f687548b.png @@ -3151,7 +3151,7 @@

Creating a colorized image based on region properties
-../../../_images/051182c27335dd68384799e8254bae2fc3171f5af2f0d06a11f9a89cd91b0564.png +../../../_images/8e205c521b1646a845ada0a47ad7c655dfc70a372e8b0a454350a2895773ddf6.png

An interesting result can be seen where the regions at the edges are darker signifying more solidity. This is because the straight edges conform exactly to their convex hulls.

diff --git a/examples/networks/reference/diffusive_size_factor_AI.html b/examples/networks/reference/diffusive_size_factor_AI.html index ad4f02112..bf2f839fc 100644 --- a/examples/networks/reference/diffusive_size_factor_AI.html +++ b/examples/networks/reference/diffusive_size_factor_AI.html @@ -2954,58 +2954,103 @@

Trained model and supplementary materials -
Requirement already satisfied: tensorflow in /opt/hostedtoolcache/Python/3.8.17/x64/lib/python3.8/site-packages (2.13.0)
-Requirement already satisfied: absl-py>=1.0.0 in /opt/hostedtoolcache/Python/3.8.17/x64/lib/python3.8/site-packages (from tensorflow) (1.4.0)
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-Requirement already satisfied: flatbuffers>=23.1.21 in /opt/hostedtoolcache/Python/3.8.17/x64/lib/python3.8/site-packages (from tensorflow) (23.5.26)
-Requirement already satisfied: gast<=0.4.0,>=0.2.1 in /opt/hostedtoolcache/Python/3.8.17/x64/lib/python3.8/site-packages (from tensorflow) (0.4.0)
+
Collecting tensorflow
+  Obtaining dependency information for tensorflow from https://files.pythonhosted.org/packages/88/cc/14affad82a28640974ff2a37c177269a0a088266104ddf76a01eac21c9ac/tensorflow-2.13.0-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata
+  Using cached tensorflow-2.13.0-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (3.4 kB)
 

 

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Requirement already satisfied: google-pasta>=0.1.1 in /opt/hostedtoolcache/Python/3.8.17/x64/lib/python3.8/site-packages (from tensorflow) (0.2.0)
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+
Collecting absl-py>=1.0.0 (from tensorflow)
+  Using cached absl_py-1.4.0-py3-none-any.whl (126 kB)
 

 

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+
Collecting astunparse>=1.6.0 (from tensorflow)
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+Requirement already satisfied: flatbuffers>=23.1.21 in /opt/hostedtoolcache/Python/3.8.18/x64/lib/python3.8/site-packages (from tensorflow) (23.5.26)
+Requirement already satisfied: gast<=0.4.0,>=0.2.1 in /opt/hostedtoolcache/Python/3.8.18/x64/lib/python3.8/site-packages (from tensorflow) (0.4.0)
+Requirement already satisfied: google-pasta>=0.1.1 in /opt/hostedtoolcache/Python/3.8.18/x64/lib/python3.8/site-packages (from tensorflow) (0.2.0)
+Requirement already satisfied: grpcio<2.0,>=1.24.3 in /opt/hostedtoolcache/Python/3.8.18/x64/lib/python3.8/site-packages (from tensorflow) (1.58.0)
+Requirement already satisfied: h5py>=2.9.0 in /opt/hostedtoolcache/Python/3.8.18/x64/lib/python3.8/site-packages (from tensorflow) (3.9.0)
+Requirement already satisfied: keras<2.14,>=2.13.1 in /opt/hostedtoolcache/Python/3.8.18/x64/lib/python3.8/site-packages (from tensorflow) (2.13.1)
+Requirement already satisfied: libclang>=13.0.0 in /opt/hostedtoolcache/Python/3.8.18/x64/lib/python3.8/site-packages (from tensorflow) (16.0.6)
+Requirement already satisfied: numpy<=1.24.3,>=1.22 in /opt/hostedtoolcache/Python/3.8.18/x64/lib/python3.8/site-packages (from tensorflow) (1.24.3)
+Collecting opt-einsum>=2.3.2 (from tensorflow)
+  Using cached opt_einsum-3.3.0-py3-none-any.whl (65 kB)
+Requirement already satisfied: packaging in /opt/hostedtoolcache/Python/3.8.18/x64/lib/python3.8/site-packages (from tensorflow) (23.1)
+Requirement already satisfied: protobuf!=4.21.0,!=4.21.1,!=4.21.2,!=4.21.3,!=4.21.4,!=4.21.5,<5.0.0dev,>=3.20.3 in /opt/hostedtoolcache/Python/3.8.18/x64/lib/python3.8/site-packages (from tensorflow) (4.24.3)
+Requirement already satisfied: setuptools in /opt/hostedtoolcache/Python/3.8.18/x64/lib/python3.8/site-packages (from tensorflow) (56.0.0)
 

 

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+
Requirement already satisfied: six>=1.12.0 in /opt/hostedtoolcache/Python/3.8.18/x64/lib/python3.8/site-packages (from tensorflow) (1.16.0)
+Collecting tensorboard<2.14,>=2.13 (from tensorflow)
 

 

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Requirement already satisfied: tensorflow-estimator<2.14,>=2.13.0 in /opt/hostedtoolcache/Python/3.8.18/x64/lib/python3.8/site-packages (from tensorflow) (2.13.0)
+Requirement already satisfied: termcolor>=1.1.0 in /opt/hostedtoolcache/Python/3.8.18/x64/lib/python3.8/site-packages (from tensorflow) (2.3.0)
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+Requirement already satisfied: wrapt>=1.11.0 in /opt/hostedtoolcache/Python/3.8.18/x64/lib/python3.8/site-packages (from tensorflow) (1.15.0)
+Requirement already satisfied: tensorflow-io-gcs-filesystem>=0.23.1 in /opt/hostedtoolcache/Python/3.8.18/x64/lib/python3.8/site-packages (from tensorflow) (0.34.0)
+Requirement already satisfied: wheel<1.0,>=0.23.0 in /opt/hostedtoolcache/Python/3.8.18/x64/lib/python3.8/site-packages (from astunparse>=1.6.0->tensorflow) (0.41.2)
+

+

+
Collecting google-auth<3,>=1.6.3 (from tensorboard<2.14,>=2.13->tensorflow)
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+  Using cached google_auth-2.23.0-py2.py3-none-any.whl.metadata (4.2 kB)
+

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Collecting google-auth-oauthlib<1.1,>=0.5 (from tensorboard<2.14,>=2.13->tensorflow)
+  Using cached google_auth_oauthlib-1.0.0-py2.py3-none-any.whl (18 kB)
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Collecting markdown>=2.6.8 (from tensorboard<2.14,>=2.13->tensorflow)
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+  Using cached Markdown-3.4.4-py3-none-any.whl.metadata (6.9 kB)
+Requirement already satisfied: requests<3,>=2.21.0 in /opt/hostedtoolcache/Python/3.8.18/x64/lib/python3.8/site-packages (from tensorboard<2.14,>=2.13->tensorflow) (2.31.0)
+Requirement already satisfied: tensorboard-data-server<0.8.0,>=0.7.0 in /opt/hostedtoolcache/Python/3.8.18/x64/lib/python3.8/site-packages (from tensorboard<2.14,>=2.13->tensorflow) (0.7.1)
+Requirement already satisfied: werkzeug>=1.0.1 in /opt/hostedtoolcache/Python/3.8.18/x64/lib/python3.8/site-packages (from tensorboard<2.14,>=2.13->tensorflow) (2.3.7)
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+

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+  Using cached rsa-4.9-py3-none-any.whl (34 kB)
+Requirement already satisfied: urllib3<2.0 in /opt/hostedtoolcache/Python/3.8.18/x64/lib/python3.8/site-packages (from google-auth<3,>=1.6.3->tensorboard<2.14,>=2.13->tensorflow) (1.26.16)
+

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+Requirement already satisfied: oauthlib>=3.0.0 in /opt/hostedtoolcache/Python/3.8.18/x64/lib/python3.8/site-packages (from requests-oauthlib>=0.7.0->google-auth-oauthlib<1.1,>=0.5->tensorboard<2.14,>=2.13->tensorflow) (3.2.2)
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Installing collected packages: rsa, pyasn1-modules, opt-einsum, astunparse, absl-py, requests-oauthlib, markdown, google-auth, google-auth-oauthlib, tensorboard, tensorflow
+

+

+
Successfully installed absl-py-1.4.0 astunparse-1.6.3 google-auth-2.23.0 google-auth-oauthlib-1.0.0 markdown-3.4.4 opt-einsum-3.3.0 pyasn1-modules-0.3.0 requests-oauthlib-1.3.1 rsa-4.9 tensorboard-2.13.0 tensorflow-2.13.0
 

 

 
[notice] A new release of pip is available: 23.0.1 -> 23.2.1
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Trained model and supplementary materials
Requirement already satisfied: numpy>=1.17.3 in /opt/hostedtoolcache/Python/3.8.17/x64/lib/python3.8/site-packages (from scikit-learn) (1.24.3)
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Requirement already satisfied: numpy>=1.17.3 in /opt/hostedtoolcache/Python/3.8.18/x64/lib/python3.8/site-packages (from scikit-learn) (1.24.3)
+Requirement already satisfied: scipy>=1.5.0 in /opt/hostedtoolcache/Python/3.8.18/x64/lib/python3.8/site-packages (from scikit-learn) (1.10.1)
 

 

 
Collecting joblib>=1.1.1 (from scikit-learn)
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Trained model and supplementary materials
Using cached scikit_learn-1.3.0-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (11.1 MB)
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Installing collected packages: threadpoolctl, joblib, scikit-learn
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Successfully installed joblib-1.3.2 scikit-learn-1.3.0 threadpoolctl-3.2.0
 

 

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[notice] A new release of pip is available: 23.0.1 -> 23.2.1
+
Downloading joblib-1.3.2-py3-none-any.whl (302 kB)
+?25l   ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 0.0/302.2 kB ? eta -:--:--^C
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+?25hERROR: Operation cancelled by user
+
+[notice] A new release of pip is available: 23.0.1 -> 23.2.1
 [notice] To update, run: pip install --upgrade pip
 

 

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-Receiving objects:  27% (10/36), 150.95 MiB | 43.14 MiB/s
-Receiving objects:  30% (11/36), 150.95 MiB | 43.14 MiB/s
-Receiving objects:  33% (12/36), 150.95 MiB | 43.14 MiB/s
-Receiving objects:  36% (13/36), 150.95 MiB | 43.14 MiB/s
-Receiving objects:  38% (14/36), 150.95 MiB | 43.14 MiB/s
-Receiving objects:  41% (15/36), 150.95 MiB | 43.14 MiB/s
-Receiving objects:  44% (16/36), 150.95 MiB | 43.14 MiB/s
-Receiving objects:  47% (17/36), 150.95 MiB | 43.14 MiB/s
-Receiving objects:  50% (18/36), 150.95 MiB | 43.14 MiB/s
-Receiving objects:  52% (19/36), 150.95 MiB | 43.14 MiB/s
-Receiving objects:  55% (20/36), 150.95 MiB | 43.14 MiB/s
-Receiving objects:  58% (21/36), 150.95 MiB | 43.14 MiB/s
-Receiving objects:  61% (22/36), 150.95 MiB | 43.14 MiB/s
-Receiving objects:  63% (23/36), 150.95 MiB | 43.14 MiB/s
-Receiving objects:  66% (24/36), 150.95 MiB | 43.14 MiB/s
-Receiving objects:  69% (25/36), 150.95 MiB | 43.14 MiB/s
-Receiving objects:  72% (26/36), 150.95 MiB | 43.14 MiB/s
-Receiving objects:  75% (27/36), 150.95 MiB | 43.14 MiB/s
-Receiving objects:  77% (28/36), 150.95 MiB | 43.14 MiB/s
-

-

-
Receiving objects:  77% (28/36), 174.80 MiB | 43.71 MiB/s
-

-

-
Receiving objects:  77% (28/36), 224.36 MiB | 46.74 MiB/s
-

-

-
Receiving objects:  80% (29/36), 246.57 MiB | 46.74 MiB/s
-

-

-
Receiving objects:  80% (29/36), 267.58 MiB | 46.38 MiB/s
-

-

-
Receiving objects:  80% (29/36), 312.36 MiB | 46.07 MiB/s
-

-

-
remote: Total 36 (delta 0), reused 2 (delta 0), pack-reused 31
-Receiving objects:  83% (30/36), 332.93 MiB | 45.36 MiB/s
-Receiving objects:  86% (31/36), 332.93 MiB | 45.36 MiB/s
-Receiving objects:  88% (32/36), 332.93 MiB | 45.36 MiB/s
-Receiving objects:  91% (33/36), 332.93 MiB | 45.36 MiB/s
-Receiving objects:  94% (34/36), 332.93 MiB | 45.36 MiB/s
-Receiving objects:  97% (35/36), 332.93 MiB | 45.36 MiB/s
-Receiving objects: 100% (36/36), 332.93 MiB | 45.36 MiB/s
-Receiving objects: 100% (36/36), 334.57 MiB | 44.37 MiB/s, done.
-Resolving deltas:   0% (0/8)
-Resolving deltas:  12% (1/8)
-Resolving deltas:  25% (2/8)
-Resolving deltas:  37% (3/8)
-Resolving deltas:  50% (4/8)
-Resolving deltas:  62% (5/8)
-Resolving deltas:  75% (6/8)
-Resolving deltas:  87% (7/8)
-Resolving deltas: 100% (8/8)
-Resolving deltas: 100% (8/8), done.
-

-

-
Updating files:  87% (7/8)
-Updating files: 100% (8/8)
-Updating files: 100% (8/8), done.
+
Receiving objects:  16% (6/36), 28.04 MiB | 27.81 MiB/s
 

 

 

@@ -3204,37 +3175,14 @@ 
model
 

 

-
---------------------------------------------------------------------------
-ModuleNotFoundError                       Traceback (most recent call last)
-Cell In[4], line 5
-      3 path_weights = os.path.join(path, 'model_weights.h5')
-      4 g_train = h5py.File(path_train, 'r')['g_train'][()]
-----> 5 model = ps.networks.create_model()
-      6 model.load_weights(path_weights)
-
-File ~/work/porespy/porespy/porespy/networks/_size_factors.py:612, in create_model()
-    604 def create_model():
-    605     '''
-    606     Returns
-    607     -------
-   (...)
-    610 
-    611     '''
---> 612     from tensorflow.keras.optimizers import Adam
-    613     model = _resnet3d()
-    614     model.compile(loss='mse', optimizer=Adam(lr=1e-4), metrics=['mse'])
-
-File /opt/hostedtoolcache/Python/3.8.17/x64/lib/python3.8/site-packages/tensorflow/__init__.py:38
-     35 import sys as _sys
-     36 import typing as _typing
----> 38 from tensorflow.python.tools import module_util as _module_util
-     39 from tensorflow.python.util.lazy_loader import LazyLoader as _LazyLoader
-     41 # Make sure code inside the TensorFlow codebase can use tf2.enabled() at import.
-
-ModuleNotFoundError: No module named 'tensorflow.python'
+
2023-03-23 14:30:39.889200: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  SSE4.1 SSE4.2
+To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
 

 

-

+
[14:30:41] WARNING  `lr` is deprecated, please use `learning_rate` instead, or use the legacy      optimizer.py:106
+                    optimizer, e.g.,tf.keras.optimizers.legacy.Adam.                                               
+

+

 

 
 

diff --git a/examples/networks/reference/label_boundaries.html b/examples/networks/reference/label_boundaries.html
index 6b7d00810..c2d826a7b 100644
--- a/examples/networks/reference/label_boundaries.html
+++ b/examples/networks/reference/label_boundaries.html
@@ -42,7 +42,7 @@
     
     
     
-    
+    
     
     
     
@@ -2923,7 +2923,7 @@ 
network<
 

 

 

-

+

 

 

 

@@ -2983,7 +2983,7 @@ 
labels
 

 

-
throat.conns
+
throat.conns
 pore.coords
 pore.all
 throat.all
diff --git a/examples/networks/reference/label_phases.html b/examples/networks/reference/label_phases.html
index fa0d30ab8..5e68269ae 100644
--- a/examples/networks/reference/label_phases.html
+++ b/examples/networks/reference/label_phases.html
@@ -42,7 +42,7 @@
     
     
     
-    
+    
     
     
     
@@ -2918,7 +2918,7 @@ 
label_phases
 

 

-../../../_images/f9c5bc7c283c0bfcd1d65aaf869957db063e2a6a6cf819ddfdcca4786346bc77.png
+../../../_images/31eb139abb4ce0f8085c177ef79e6e80baf1e3020b6e205bae44bea8ab0d487a.png
 

 

 

@@ -2931,7 +2931,7 @@ 
network<
 

 

 

-

+

 

 

 

@@ -2996,7 +2996,7 @@ 
alias
 

 

-
throat.conns
+
throat.conns
 pore.coords
 pore.all
 throat.all
diff --git a/examples/networks/reference/map_to_regions.html b/examples/networks/reference/map_to_regions.html
index 4beaef8a5..7990e7c55 100644
--- a/examples/networks/reference/map_to_regions.html
+++ b/examples/networks/reference/map_to_regions.html
@@ -42,7 +42,7 @@
     
     
     
-    
+    
     
     
     
@@ -2931,7 +2931,7 @@ 
Create <
 

 

 

-../../../_images/92ba1511f878a7d9ff2497a1d0d933f7bc87465dab1034f5002bdefb30e41bc1.png
+../../../_images/5b96ad897297cc4f2b8d6e41c2c985dac53d4927a49831e2f16230e5a9f10ec7.png
 

 

 
@@ -2948,11 +2948,7 @@ 
Plot the pore network
 

 

-
/opt/hostedtoolcache/Python/3.8.17/x64/lib/python3.8/site-packages/openpnm/visualization/_plottools.py:344: UserWarning: The figure layout has changed to tight
-  fig.tight_layout()
-

-

-../../../_images/01e11824f359053480cae76774655235ef846dfbeea698c573afeeef40ba4619.png
+../../../_images/c84680a0530ac2f3f18ea26c3ddc53af8deb4e0901432d98fd2e48dca54a1a9c.png
 

 

 
Now assign some values to the network:

@@ -2972,7 +2968,7 @@ 
Plot the pore network
 

 

-../../../_images/6c0488d877240c4989d9f14c6738fabd73ff588634c91455a609ff2879968f99.png
+../../../_images/72993b26d6f99b152be7bb9b6f8db00f366c459d32495543a63a45b49fc4df6a.png
 

 

 
diff --git a/examples/networks/reference/regions_to_network.html b/examples/networks/reference/regions_to_network.html
index 023a754a0..78b8bf8dc 100644
--- a/examples/networks/reference/regions_to_network.html
+++ b/examples/networks/reference/regions_to_network.html
@@ -42,7 +42,7 @@
     
     
     
-    
+    
     
     
     
@@ -2933,7 +2933,7 @@ 
regions_to_netw
 

 

 

-../../../_images/438704d7c714df2b0a541ef25beb72883f3c958282fc7e1f02838571a6ed2ce9.png
+../../../_images/e00d38f94519f533caa827beb35fac25fc9ec09a5aaacc24e1bf0e61b421722b.png
 

 

 

@@ -3058,7 +3058,7 @@ 
regions<
 

 

 

-../../../_images/8020ae0a2dbc91cfc910e16fb5c38ba79318ad5f9afe18580509d8c0d9388525.png
+../../../_images/159d29918b84d54e8de8ea4dfdc4554a4532bbe78fd85b4cb313dbf1142e0043.png
 

 

 

@@ -3068,7 +3068,7 @@ 
regions<
 

 

 

-

+

 

 
The regions_to_network functions returns dict containing all the network information in OpenPNM format:

 

@@ -3118,7 +3118,7 @@ 
phases
 

 

-../../../_images/274068d285a011706f8aa3900b6dbe18e02990be793eeb893edf8f555f40c40d.png
+../../../_images/76acfc458c3b725e9e3322d9e9da639751979da3995ec3e9653c444d4c09d05f.png
 

 

 
We can manually combine these two watersheds:

@@ -3130,7 +3130,7 @@ 
phases
 

 

-../../../_images/6ce908b663d477c567b297fd7e0a4901d232f060e136d8e938cd1f1dd751240e.png
+../../../_images/dc77bfbb85b8ccb0e1ae768e0572c0aaece5203447b9a2ee036cfc8617bbe649.png

Now we can send this combined watershed image, along with an image with each phase labelled as 1 and 2 to regions_to_network:

@@ -3141,7 +3141,7 @@

phases

-
+
diff --git a/examples/networks/reference/snow2.html b/examples/networks/reference/snow2.html index 17340e26c..d4c00d7d1 100644 --- a/examples/networks/reference/snow2.html +++ b/examples/networks/reference/snow2.html @@ -42,7 +42,7 @@ - + @@ -2978,11 +2978,11 @@

snow2

-
/tmp/ipykernel_3839/1531839659.py:1: DeprecationWarning: Call to deprecated function (or staticmethod) rsa. (This function will be renamed random_spheres in a future version)
+
/tmp/ipykernel_4112/1531839659.py:1: DeprecationWarning: Call to deprecated function (or staticmethod) rsa. (This function will be renamed random_spheres in a future version)
   im = ~ps.generators.rsa([400, 400], r=15, clearance=5)
 

 

-../../../_images/b5b2184aca125d82825aafad07f7a8c997f30b4395ecd580ee36cec229f77551.png
+../../../_images/d4a12953c0a95098a1218739953d017613630345f96c3a16cb61d6398c8171f4.png
@@ -3003,7 +3003,7 @@

phases

-
+

The “object” returned by the snow2 function is a dataclass-like object, meaning it has data attached to it as attributes. These attributes are the segmented image called regions, the OpenPNM compatible network called network, and a copy of the input image called phases which will be padded to be the same size as regions if any boundaries were added.

@@ -3015,7 +3015,7 @@

phases

-../../../_images/03c4f87f7013b31c54d37e0416d5aeb59efad38996a02a3b8534ff9349808d56.png +../../../_images/977163bcb920d9b58753a8fee8d3566a22efb1dc8c6336eb86c8450e1613e2dc.png

On the left we can see that the spherical particles are all purple, which indicates 0, because they have not been labelled by the function. On the right the particles each have a unique greyscale value because they have been labelled as distinct regions.

@@ -3038,11 +3038,7 @@

phases
-
/opt/hostedtoolcache/Python/3.8.17/x64/lib/python3.8/site-packages/openpnm/visualization/_plottools.py:344: UserWarning: The figure layout has changed to tight
-  fig.tight_layout()
-
-
-../../../_images/e071deea3f08d790a752acafe993116a0c671969359685f0e8405573289f8a81.png +../../../_images/a69417af904e49ced8812edde621ade4cadb9ba985351c5e2f38f20c7dacfbd7.png

The image needed to be rotated so that the x and y directions lined up with the OpenPNM network. The agreement between the image and network is pretty good. Clearly the the red pore centers lie within each labelled regions and the black throat connections follow the topology quite well.

@@ -3065,7 +3061,7 @@

phases
-../../../_images/d6b9e18663bae60d336b37b38a1d50bac09cd1c2a87776067a547012f69d18a7.png +../../../_images/5044f92a0e91c97e397a70075103b8fac4faacac4052c79b27b750bf3f270f62.png

The above shows the additional network comprised of the solids (although they don’t actually connect in this 2D example) as well as the void-solid connections. We can improve this plot by coloring the different types of pores and throats differently. If we print pn2 we can see that snow2 has created some labels for us, by assuming phase names of “phase1” and “phase2”.

@@ -3077,41 +3073,41 @@

phases 
══════════════════════════════════════════════════════════════════════════════
-net : <openpnm.network.Network at 0x7f14248ff590>
+net : <openpnm.network.Network at 0x7fc159b55bd0>
 ――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――
   #  Properties                                                   Valid Values
 ――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――
-  2  throat.conns                                                    693 / 693
-  3  pore.coords                                                     242 / 242
-  4  pore.region_label                                               242 / 242
-  5  pore.phase                                                      242 / 242
-  6  throat.phases                                                   693 / 693
-  7  pore.region_volume                                              242 / 242
-  8  pore.equivalent_diameter                                        242 / 242
-  9  pore.local_peak                                                 242 / 242
- 10  pore.global_peak                                                242 / 242
- 11  pore.geometric_centroid                                         242 / 242
- 12  throat.global_peak                                              693 / 693
- 13  pore.inscribed_diameter                                         242 / 242
- 14  pore.extended_diameter                                          242 / 242
- 15  throat.inscribed_diameter                                       693 / 693
- 16  throat.total_length                                             693 / 693
- 17  throat.direct_length                                            693 / 693
- 18  throat.perimeter                                                693 / 693
- 19  pore.volume                                                     242 / 242
- 20  pore.surface_area                                               242 / 242
- 21  throat.cross_sectional_area                                     693 / 693
- 22  throat.equivalent_diameter                                      693 / 693
+  2  throat.conns                                                    755 / 755
+  3  pore.coords                                                     263 / 263
+  4  pore.region_label                                               263 / 263
+  5  pore.phase                                                      263 / 263
+  6  throat.phases                                                   755 / 755
+  7  pore.region_volume                                              263 / 263
+  8  pore.equivalent_diameter                                        263 / 263
+  9  pore.local_peak                                                 263 / 263
+ 10  pore.global_peak                                                263 / 263
+ 11  pore.geometric_centroid                                         263 / 263
+ 12  throat.global_peak                                              755 / 755
+ 13  pore.inscribed_diameter                                         263 / 263
+ 14  pore.extended_diameter                                          263 / 263
+ 15  throat.inscribed_diameter                                       755 / 755
+ 16  throat.total_length                                             755 / 755
+ 17  throat.direct_length                                            755 / 755
+ 18  throat.perimeter                                                755 / 755
+ 19  pore.volume                                                     263 / 263
+ 20  pore.surface_area                                               263 / 263
+ 21  throat.cross_sectional_area                                     755 / 755
+ 22  throat.equivalent_diameter                                      755 / 755
 ――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――
   #  Labels                                                 Assigned Locations
 ――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――
-  2  pore.all                                                              242
-  3  throat.all                                                            693
-  4  pore.phase1                                                           103
-  5  throat.phase1_phase2                                                  452
-  6  pore.phase2                                                           139
-  7  throat.phase2_phase1                                                  452
-  8  throat.phase2_phase2                                                  241
+  2  pore.all                                                              263
+  3  throat.all                                                            755
+  4  pore.phase1                                                           105
+  5  throat.phase1_phase2                                                  493
+  6  pore.phase2                                                           158
+  7  throat.phase2_phase1                                                  493
+  8  throat.phase2_phase2                                                  262
 ――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――
@@ -3130,11 +3126,7 @@

phases

-
/opt/hostedtoolcache/Python/3.8.17/x64/lib/python3.8/site-packages/openpnm/visualization/_plottools.py:180: UserWarning: The figure layout has changed to tight
-  fig.tight_layout()
-
-
-../../../_images/b1cb9f999faf68175339dad530c33765b53015cc0d0a258e35a6efe52319ae35.png +../../../_images/03e05c365dba13275632c059f00ac29315e44b6d9b2714b1cea3da2aaf44a1f8.png

Now can see the particles are indicated by a green marker, the void pores by a red marker, the solid-void interconnections are in grey, and the void-void throats are black.

@@ -3149,7 +3141,7 @@

phase_alias
-
+
@@ -3160,41 +3152,41 @@

phase_alias 
══════════════════════════════════════════════════════════════════════════════
-net : <openpnm.network.Network at 0x7f14246c7c70>
+net : <openpnm.network.Network at 0x7fc170540c70>
 ――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――
   #  Properties                                                   Valid Values
 ――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――
-  2  throat.conns                                                    693 / 693
-  3  pore.coords                                                     242 / 242
-  4  pore.region_label                                               242 / 242
-  5  pore.phase                                                      242 / 242
-  6  throat.phases                                                   693 / 693
-  7  pore.region_volume                                              242 / 242
-  8  pore.equivalent_diameter                                        242 / 242
-  9  pore.local_peak                                                 242 / 242
- 10  pore.global_peak                                                242 / 242
- 11  pore.geometric_centroid                                         242 / 242
- 12  throat.global_peak                                              693 / 693
- 13  pore.inscribed_diameter                                         242 / 242
- 14  pore.extended_diameter                                          242 / 242
- 15  throat.inscribed_diameter                                       693 / 693
- 16  throat.total_length                                             693 / 693
- 17  throat.direct_length                                            693 / 693
- 18  throat.perimeter                                                693 / 693
- 19  pore.volume                                                     242 / 242
- 20  pore.surface_area                                               242 / 242
- 21  throat.cross_sectional_area                                     693 / 693
- 22  throat.equivalent_diameter                                      693 / 693
+  2  throat.conns                                                    755 / 755
+  3  pore.coords                                                     263 / 263
+  4  pore.region_label                                               263 / 263
+  5  pore.phase                                                      263 / 263
+  6  throat.phases                                                   755 / 755
+  7  pore.region_volume                                              263 / 263
+  8  pore.equivalent_diameter                                        263 / 263
+  9  pore.local_peak                                                 263 / 263
+ 10  pore.global_peak                                                263 / 263
+ 11  pore.geometric_centroid                                         263 / 263
+ 12  throat.global_peak                                              755 / 755
+ 13  pore.inscribed_diameter                                         263 / 263
+ 14  pore.extended_diameter                                          263 / 263
+ 15  throat.inscribed_diameter                                       755 / 755
+ 16  throat.total_length                                             755 / 755
+ 17  throat.direct_length                                            755 / 755
+ 18  throat.perimeter                                                755 / 755
+ 19  pore.volume                                                     263 / 263
+ 20  pore.surface_area                                               263 / 263
+ 21  throat.cross_sectional_area                                     755 / 755
+ 22  throat.equivalent_diameter                                      755 / 755
 ――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――
   #  Labels                                                 Assigned Locations
 ――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――
-  2  pore.all                                                              242
-  3  throat.all                                                            693
-  4  pore.solid                                                            103
-  5  throat.solid_void                                                     452
-  6  pore.void                                                             139
-  7  throat.void_solid                                                     452
-  8  throat.void_void                                                      241
+  2  pore.all                                                              263
+  3  throat.all                                                            755
+  4  pore.solid                                                            105
+  5  throat.solid_void                                                     493
+  6  pore.void                                                             158
+  7  throat.void_solid                                                     493
+  8  throat.void_void                                                      262
 ――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――
@@ -3225,7 +3217,7 @@

boundary_width<

-../../../_images/1659e174c6f915457be1bf20587c729bfa79529144b2d832a8fe31c267fe2a0c.png +../../../_images/992a30f08bc6b41d3f2629bd1e85e3c5c1bbe8fca07f24cdfeec279e9f5cde30.png

A few things to note:

@@ -3250,11 +3242,7 @@

boundary_width<
-
/opt/hostedtoolcache/Python/3.8.17/x64/lib/python3.8/site-packages/openpnm/visualization/_plottools.py:344: UserWarning: The figure layout has changed to tight
-  fig.tight_layout()
-
-
-../../../_images/d565de9fe5bd80b1e39343821d6273bdff4d792f846ec84af70a1427178b32eb.png +../../../_images/390bdfb8871baa192e6c693cecacb1a4efd8b349891c1ad47df37eb65fe55bfa.png
@@ -3293,7 +3281,7 @@

sigma
-../../../_images/f00d789f850433bd821332933b3c8ffbe04c34fe1e955f983adae4b431aeb1a0.png +../../../_images/f88a88c7802d4161f2853e6f8e2739f6e53e49c90fe11119caf46a9d88b98ed4.png
@@ -3309,7 +3297,7 @@

peaks
-
+
@@ -3322,7 +3310,7 @@

peaks

-../../../_images/fb283c99aa394a8f33dd6a6f5b3edad574d69282b4fd93fb10e0ef623d524610.png +../../../_images/377ccb07dd4f05734d9ccd1223698379ff713f373c7595e62f365891d96537ab.png

Clearly the image on the left is ‘over segmented’ while the image on the right seems to have identified the pores nearly perfectly, even without subsequent processing of the peaks that normally occur in snow2 like trim_saddle_points and trim_nearby_peaks.

@@ -3348,7 +3336,7 @@

parallelization
-
+
@@ -3363,7 +3351,7 @@

parallelization

-../../../_images/48acfe1435556a0a91e8bdd2540784e1b94b1a3de39b022fcc23d2658831b78b.png +../../../_images/6581463830bf6ec8f30a151dc00f25f5c1a159e2f72b0b331dca6d568c12383f.png
diff --git a/examples/networks/tutorials/adding_boundary_pores.html b/examples/networks/tutorials/adding_boundary_pores.html index 9d95d8883..5871daf92 100644 --- a/examples/networks/tutorials/adding_boundary_pores.html +++ b/examples/networks/tutorials/adding_boundary_pores.html @@ -42,7 +42,7 @@ - + @@ -2917,7 +2917,7 @@

Create image -../../../_images/cb6b0a829f04cf49a55520b96b436084894c9821269e982b4867ec6058832f1e.png +../../../_images/6e532b2abb93563e74e76e9a949c4d0140fdf7471427eb1859fd3f131036c9fc.png
@@ -2931,7 +2931,7 @@

Create image -../../../_images/a4534e4606c2c04de2f45542178a79aa8618317b637ac6975512d44a57340c28.png +../../../_images/434f9adf7470d4f357afd83cdb800c4fc153545ae95dabd60a104bed0988383a.png

@@ -2944,7 +2944,7 @@

Create image -../../../_images/5bd65f331a5ef4373af7d4444e5f599e7313b7b694fbd62d348e2a13259efb95.png +../../../_images/41ada6cd699c9a8b1c3e07d7fb8ab3bd9a88b372f82a36c3fa71c915ff02d7e2.png

The image above shows how boundary regions appear. They are 3-voxel thick slices that are padded onto each face and given a unique label to differentiate them from the internal pores to which they connect. There are a few key things to note:

@@ -2961,7 +2961,7 @@

Create image - +

Next we’ll open the net dictionary in OpenPNM using the PoreSpy IO class:

@@ -2976,11 +2976,7 @@

Create image -
/opt/hostedtoolcache/Python/3.8.17/x64/lib/python3.8/site-packages/openpnm/visualization/_plottools.py:344: UserWarning: The figure layout has changed to tight
-  fig.tight_layout()
-
-
-../../../_images/c17eabc8b39988343f55d8f1f2a35ec8d639c0fb865296c2f7bd971b9c198996.png +../../../_images/5e5d54fafffd536f422bfb3319b9d64c46553d81005bc377a8cad2d3cd7e9449.png

The approach outlined above is missing one important feature. The boundary pores are not labelled. When the process is performed internally by the regions_to_network function this is taken care of.

diff --git a/examples/networks/tutorials/snow_advanced.html b/examples/networks/tutorials/snow_advanced.html index 387bd31b2..624a22023 100644 --- a/examples/networks/tutorials/snow_advanced.html +++ b/examples/networks/tutorials/snow_advanced.html @@ -2917,7 +2917,7 @@

Generate artificial image -../../../_images/dddf53fdb382e178836a4f3a078380546d7f291c0685be16449dd584c3692b31.png +../../../_images/747bdc1f41f26fefc8ef39d6fcb34323dc89a4eddbef9c27a46deea75f96621c.png @@ -2976,7 +2976,7 @@

Step-by-step application of the SNOW algorithm -../../../_images/2ad05689802c001f3868ddacb7a9a0657e29d460f69dbd83f5ce4cd27420a50d.png +../../../_images/d171c3e79ba1cc64d43920be1b5b3d1a0f9d0b18551a18dc5d65044158b32818.png

Finally, this partitioned image can be passed to the network extraction function which analyzes the image and returns a Python dict containing the numerical properties of the network.

@@ -3004,7 +3004,7 @@

Step-by-step application of the SNOW algorithm 
══════════════════════════════════════════════════════════════════════════════
-net : <openpnm.network.Network at 0x7fb582512130>
+net : <openpnm.network.Network at 0x7fee075a7040>
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   #  Properties                                                   Valid Values
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diff --git a/examples/networks/tutorials/snow_basic.html b/examples/networks/tutorials/snow_basic.html
index 72c7a80d4..e31633ded 100644
--- a/examples/networks/tutorials/snow_basic.html
+++ b/examples/networks/tutorials/snow_basic.html
@@ -42,7 +42,7 @@
     
     
     
-    
+    
     
     
     
@@ -2896,7 +2896,7 @@ 
SNOW network extraction
-../../../_images/746919384696446e605876e02346ce55b6da417edacb080459d17dcd77a36cbc.png +../../../_images/7ad28e333b679eecd5936d24f615560e9086fda192ff13dc0edd2b0fd4ef87e8.png

SNOW is composed of a series of filters, but PoreSpy has a single function that applies all the necessary steps:

@@ -2907,7 +2907,7 @@

SNOW network extraction
-
+

The snow function returns an object that has a network attribute. This is a dictionary that is suitable for loading into OpenPNM. The best way to get this into OpenPNM is to use the PoreSpy IO class. This splits the data into a network and a geometry:

@@ -2926,7 +2926,7 @@

SNOW network extraction 
══════════════════════════════════════════════════════════════════════════════
-net : <openpnm.network.Network at 0x7f4a7a3753b0>
+net : <openpnm.network.Network at 0x7f174fe9e3b0>
 ――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――
   #  Properties                                                   Valid Values
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@@ -2982,11 +2982,7 @@ 
SNOW network extraction
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/opt/hostedtoolcache/Python/3.8.17/x64/lib/python3.8/site-packages/openpnm/visualization/_plottools.py:180: UserWarning: The figure layout has changed to tight
-  fig.tight_layout()
-
-
-../../../_images/a67a49776cabff62c5dcca4baac12ddd562e3ba3c06a02de53d1f7a952004736.png +../../../_images/d2bf0cc5a19504f76203a25f8bd35f02e72c9a94b70fb8240ac9cee947380114.png
diff --git a/examples/networks/tutorials/using_diffusive_size_factor_AI_with_snow.html b/examples/networks/tutorials/using_diffusive_size_factor_AI_with_snow.html index 15d5c99e0..382ef1730 100644 --- a/examples/networks/tutorials/using_diffusive_size_factor_AI_with_snow.html +++ b/examples/networks/tutorials/using_diffusive_size_factor_AI_with_snow.html @@ -2940,87 +2940,129 @@

Trained model and supplementary materials 
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Collecting wheel<1.0,>=0.23.0 (from astunparse>=1.6.0->tensorflow)
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Collecting pyasn1<0.6.0,>=0.4.6 (from pyasn1-modules>=0.2.1->google-auth<3,>=1.6.3->tensorboard<2.14,>=2.13->tensorflow)
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Collecting oauthlib>=3.0.0 (from requests-oauthlib>=0.7.0->google-auth-oauthlib<1.1,>=0.5->tensorboard<2.14,>=2.13->tensorflow)
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+   ━━━━━━╺━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 82.3/524.1 MB 65.0 MB/s eta 0:00:07
+

+

+
   ━━━━━━╸━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 85.2/524.1 MB 61.6 MB/s eta 0:00:08
+

+

+
   ━━━━━━╸━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 88.2/524.1 MB 83.2 MB/s eta 0:00:06
+   ━━━━━━╸━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 91.4/524.1 MB 84.5 MB/s eta 0:00:06
+

+

+
   ━━━━━━━╺━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 94.3/524.1 MB 83.0 MB/s eta 0:00:06
+

+

+
   ━━━━━━━╺━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 98.1/524.1 MB 91.0 MB/s eta 0:00:05
+

+

+
   ━━━━━━━╸━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 102.3/524.1 MB 102.1 MB/s eta 0:00:05
+   ━━━━━━━╸━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 106.0/524.1 MB 105.9 MB/s eta 0:00:04
+

+

+
   ━━━━━━━━╺━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 109.9/524.1 MB 104.9 MB/s eta 0:00:04
+

+

+
   ━━━━━━━━╺━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 113.9/524.1 MB 107.3 MB/s eta 0:00:04
+   ━━━━━━━━╸━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 117.2/524.1 MB 104.4 MB/s eta 0:00:04
+

+

+
   ━━━━━━━━━╺━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 120.9/524.1 MB 102.3 MB/s eta 0:00:04
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+

+
   ━━━━━━━━━╺━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 124.9/524.1 MB 102.1 MB/s eta 0:00:04
+   ━━━━━━━━━╺━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 127.6/524.1 MB 105.6 MB/s eta 0:00:04
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+

+
   ━━━━━━━━━╸━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 131.0/524.1 MB 92.0 MB/s eta 0:00:05
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+
   ━━━━━━━━━━╺━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 134.2/524.1 MB 84.6 MB/s eta 0:00:05
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+
   ━━━━━━━━━━╺━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 136.7/524.1 MB 76.9 MB/s eta 0:00:06
+   ━━━━━━━━━━╸━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 139.3/524.1 MB 76.9 MB/s eta 0:00:06
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+

+
   ━━━━━━━━━━╸━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 141.3/524.1 MB 71.7 MB/s eta 0:00:06
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+
   ━━━━━━━━━━╸━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 144.1/524.1 MB 67.8 MB/s eta 0:00:06
+   ━━━━━━━━━━━╺━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 147.9/524.1 MB 74.6 MB/s eta 0:00:06
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+
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+
   ━━━━━━━━━━━╸━━━━━━━━━━━━━━━━━━━━━━━━━━━ 155.4/524.1 MB 107.6 MB/s eta 0:00:04
+   ━━━━━━━━━━━╸━━━━━━━━━━━━━━━━━━━━━━━━━━━ 159.3/524.1 MB 107.1 MB/s eta 0:00:04
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+

+
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+
   ━━━━━━━━━━━━╺━━━━━━━━━━━━━━━━━━━━━━━━━━ 166.8/524.1 MB 107.6 MB/s eta 0:00:04
+   ━━━━━━━━━━━━╸━━━━━━━━━━━━━━━━━━━━━━━━━━ 170.6/524.1 MB 106.0 MB/s eta 0:00:04
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+

+
   ━━━━━━━━━━━━╸━━━━━━━━━━━━━━━━━━━━━━━━━━ 174.3/524.1 MB 104.1 MB/s eta 0:00:04
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+
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+   ━━━━━━━━━━━━━╸━━━━━━━━━━━━━━━━━━━━━━━━━━ 180.9/524.1 MB 95.1 MB/s eta 0:00:04
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   ━━━━━━━━━━━━━━╺━━━━━━━━━━━━━━━━━━━━━━━━━ 183.9/524.1 MB 87.6 MB/s eta 0:00:04
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+   ━━━━━━━━━━━━━━╺━━━━━━━━━━━━━━━━━━━━━━━━ 194.5/524.1 MB 101.0 MB/s eta 0:00:04
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+
   ━━━━━━━━━━━━━━╸━━━━━━━━━━━━━━━━━━━━━━━━ 198.1/524.1 MB 100.3 MB/s eta 0:00:04
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+

+
   ━━━━━━━━━━━━━━━╺━━━━━━━━━━━━━━━━━━━━━━━━ 201.5/524.1 MB 98.6 MB/s eta 0:00:04
+   ━━━━━━━━━━━━━━━╸━━━━━━━━━━━━━━━━━━━━━━━━ 204.9/524.1 MB 98.5 MB/s eta 0:00:04
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+

+
   ━━━━━━━━━━━━━━━╸━━━━━━━━━━━━━━━━━━━━━━━━ 208.5/524.1 MB 99.5 MB/s eta 0:00:04
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+
   ━━━━━━━━━━━━━━━━╺━━━━━━━━━━━━━━━━━━━━━━━ 210.2/524.1 MB 82.5 MB/s eta 0:00:04
+   ━━━━━━━━━━━━━━━━╺━━━━━━━━━━━━━━━━━━━━━━━ 212.2/524.1 MB 73.7 MB/s eta 0:00:05
+

+

+
   ━━━━━━━━━━━━━━━━╺━━━━━━━━━━━━━━━━━━━━━━━ 216.0/524.1 MB 75.7 MB/s eta 0:00:05
+

+

+
   ━━━━━━━━━━━━━━━━╸━━━━━━━━━━━━━━━━━━━━━━━ 219.8/524.1 MB 76.5 MB/s eta 0:00:04
+   ━━━━━━━━━━━━━━━━╸━━━━━━━━━━━━━━━━━━━━━━ 223.4/524.1 MB 103.0 MB/s eta 0:00:03
+

+

+
   ━━━━━━━━━━━━━━━━╸━━━━━━━━━━━━━━━━━━━━━━ 227.2/524.1 MB 105.9 MB/s eta 0:00:03
+

+

+
   ━━━━━━━━━━━━━━━━━╺━━━━━━━━━━━━━━━━━━━━━ 230.6/524.1 MB 101.4 MB/s eta 0:00:03
+   ━━━━━━━━━━━━━━━━━╺━━━━━━━━━━━━━━━━━━━━━ 234.3/524.1 MB 101.6 MB/s eta 0:00:03
+

+

+
   ━━━━━━━━━━━━━━━━━╸━━━━━━━━━━━━━━━━━━━━━ 237.9/524.1 MB 101.8 MB/s eta 0:00:03
+

+

+
   ━━━━━━━━━━━━━━━━━╸━━━━━━━━━━━━━━━━━━━━━ 241.2/524.1 MB 100.0 MB/s eta 0:00:03
+

+

+
   ━━━━━━━━━━━━━━━━━━╸━━━━━━━━━━━━━━━━━━━━━ 244.7/524.1 MB 98.5 MB/s eta 0:00:03
+   ━━━━━━━━━━━━━━━━━━╸━━━━━━━━━━━━━━━━━━━━━ 247.7/524.1 MB 91.4 MB/s eta 0:00:04
+

+

+
   ━━━━━━━━━━━━━━━━━━━╺━━━━━━━━━━━━━━━━━━━━ 250.0/524.1 MB 83.4 MB/s eta 0:00:04
+

+

+
   ━━━━━━━━━━━━━━━━━━━╺━━━━━━━━━━━━━━━━━━━━ 253.5/524.1 MB 82.9 MB/s eta 0:00:04
+   ━━━━━━━━━━━━━━━━━━━╸━━━━━━━━━━━━━━━━━━━━ 257.0/524.1 MB 84.4 MB/s eta 0:00:04
+

+

+
   ━━━━━━━━━━━━━━━━━━━╸━━━━━━━━━━━━━━━━━━━━ 260.2/524.1 MB 93.7 MB/s eta 0:00:03
+

+

+
   ━━━━━━━━━━━━━━━━━━━━╺━━━━━━━━━━━━━━━━━━━ 263.0/524.1 MB 87.4 MB/s eta 0:00:03
+   ━━━━━━━━━━━━━━━━━━━━╺━━━━━━━━━━━━━━━━━━━ 266.1/524.1 MB 84.3 MB/s eta 0:00:04
+

+

+
   ━━━━━━━━━━━━━━━━━━━━╸━━━━━━━━━━━━━━━━━━━ 269.1/524.1 MB 83.2 MB/s eta 0:00:04
+

+

+
   ━━━━━━━━━━━━━━━━━━━━╸━━━━━━━━━━━━━━━━━━━ 272.3/524.1 MB 81.7 MB/s eta 0:00:04
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+
   ━━━━━━━━━━━━━━━━━━━━━╺━━━━━━━━━━━━━━━━━━ 275.5/524.1 MB 89.7 MB/s eta 0:00:03
+   ━━━━━━━━━━━━━━━━━━━━━╺━━━━━━━━━━━━━━━━━━ 278.9/524.1 MB 88.9 MB/s eta 0:00:03
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+

+
   ━━━━━━━━━━━━━━━━━━━━━╺━━━━━━━━━━━━━━━━━━ 281.6/524.1 MB 86.9 MB/s eta 0:00:03
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   ━━━━━━━━━━━━━━━━━━━━━╸━━━━━━━━━━━━━━━━━━ 284.8/524.1 MB 83.3 MB/s eta 0:00:03
+   ━━━━━━━━━━━━━━━━━━━━━╸━━━━━━━━━━━━━━━━━━ 287.5/524.1 MB 82.5 MB/s eta 0:00:03
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+   ━━━━━━━━━━━━━━━━━━━━━━╸━━━━━━━━━━━━━━━━━ 299.5/524.1 MB 81.5 MB/s eta 0:00:03
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   ━━━━━━━━━━━━━━━━━━━━━━━╺━━━━━━━━━━━━━━━━ 302.3/524.1 MB 78.4 MB/s eta 0:00:03
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+   ━━━━━━━━━━━━━━━━━━━━━━━╸━━━━━━━━━━━━━━━━ 308.4/524.1 MB 78.0 MB/s eta 0:00:03
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   ━━━━━━━━━━━━━━━━━━━━━━━╸━━━━━━━━━━━━━━━━ 311.3/524.1 MB 85.5 MB/s eta 0:00:03
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+   ━━━━━━━━━━━━━━━━━━━━━━━━╺━━━━━━━━━━━━━━━ 317.5/524.1 MB 83.0 MB/s eta 0:00:03
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   ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╺━━━ 478.1/524.1 MB 87.1 MB/s eta 0:00:01
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+   ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╺━━ 487.0/524.1 MB 84.2 MB/s eta 0:00:01
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+   ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╸━━ 496.7/524.1 MB 88.8 MB/s eta 0:00:01
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+   ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╸━ 504.7/524.1 MB 80.1 MB/s eta 0:00:01
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+   ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╺ 515.9/524.1 MB 76.3 MB/s eta 0:00:01
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   ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╸ 524.1/524.1 MB 83.6 MB/s eta 0:00:01
+   ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╸ 524.1/524.1 MB 83.6 MB/s eta 0:00:01
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   ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╸ 524.1/524.1 MB 83.6 MB/s eta 0:00:01
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   ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╸ 524.1/524.1 MB 83.6 MB/s eta 0:00:01
+   ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╸ 524.1/524.1 MB 83.6 MB/s eta 0:00:01
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   ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╸ 524.1/524.1 MB 83.6 MB/s eta 0:00:01
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   ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╸ 524.1/524.1 MB 83.6 MB/s eta 0:00:01
+   ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╸ 524.1/524.1 MB 83.6 MB/s eta 0:00:01
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   ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╸ 524.1/524.1 MB 83.6 MB/s eta 0:00:01
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   ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╸ 524.1/524.1 MB 83.6 MB/s eta 0:00:01
+   ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╸ 524.1/524.1 MB 83.6 MB/s eta 0:00:01
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   ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╸ 524.1/524.1 MB 83.6 MB/s eta 0:00:01
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   ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╸ 524.1/524.1 MB 83.6 MB/s eta 0:00:01
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   ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╸ 524.1/524.1 MB 83.6 MB/s eta 0:00:01
+   ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╸ 524.1/524.1 MB 83.6 MB/s eta 0:00:01
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   ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╸ 524.1/524.1 MB 83.6 MB/s eta 0:00:01
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   ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╸ 524.1/524.1 MB 83.6 MB/s eta 0:00:01
+   ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╸ 524.1/524.1 MB 83.6 MB/s eta 0:00:01
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   ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╸ 524.1/524.1 MB 83.6 MB/s eta 0:00:01
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   ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╸ 524.1/524.1 MB 83.6 MB/s eta 0:00:01
+   ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╸ 524.1/524.1 MB 83.6 MB/s eta 0:00:01
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   ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╸ 524.1/524.1 MB 83.6 MB/s eta 0:00:01
+   ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╸ 524.1/524.1 MB 83.6 MB/s eta 0:00:01
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   ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╸ 524.1/524.1 MB 83.6 MB/s eta 0:00:01
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   ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╸ 524.1/524.1 MB 83.6 MB/s eta 0:00:01
+   ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╸ 524.1/524.1 MB 83.6 MB/s eta 0:00:01
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   ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╸ 524.1/524.1 MB 83.6 MB/s eta 0:00:01
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   ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╸ 524.1/524.1 MB 83.6 MB/s eta 0:00:01
+   ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╸ 524.1/524.1 MB 83.6 MB/s eta 0:00:01
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   ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╸ 524.1/524.1 MB 83.6 MB/s eta 0:00:01
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   ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╸ 524.1/524.1 MB 83.6 MB/s eta 0:00:01
+   ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╸ 524.1/524.1 MB 83.6 MB/s eta 0:00:01
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   ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╸ 524.1/524.1 MB 83.6 MB/s eta 0:00:01
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   ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╸ 524.1/524.1 MB 83.6 MB/s eta 0:00:01
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   ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╸ 524.1/524.1 MB 83.6 MB/s eta 0:00:01
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+?25h
 

 

 
Installing collected packages: libclang, flatbuffers, wheel, werkzeug, urllib3, typing-extensions, termcolor, tensorflow-io-gcs-filesystem, tensorflow-estimator, tensorboard-data-server, pyasn1, protobuf, oauthlib, numpy, keras, grpcio, google-pasta, gast, cachetools, absl-py, rsa, pyasn1-modules, opt-einsum, markdown, astunparse, requests-oauthlib, google-auth, google-auth-oauthlib, tensorboard, tensorflow
@@ -3133,9 +3934,7 @@ 
Trained model and supplementary materials
  Attempting uninstall: urllib3
     Found existing installation: urllib3 2.0.4
-

-

-
    Uninstalling urllib3-2.0.4:
+    Uninstalling urllib3-2.0.4:
       Successfully uninstalled urllib3-2.0.4
 

 

@@ -3164,21 +3963,38 @@ 
Trained model and supplementary materials
Collecting scikit-learn
   Obtaining dependency information for scikit-learn from https://files.pythonhosted.org/packages/bf/15/d1b649fc7685d11b806b4546a5438191fb2ad761de70da95ff676189dcec/scikit_learn-1.3.0-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata
-  Using cached scikit_learn-1.3.0-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (11 kB)
 

 

-
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+
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+Requirement already satisfied: scipy>=1.5.0 in /opt/hostedtoolcache/Python/3.8.18/x64/lib/python3.8/site-packages (from scikit-learn) (1.10.1)
 

 

 
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diff --git a/examples/simulations/reference/ibip.html b/examples/simulations/reference/ibip.html
index ed1a5f54f..ed9c69ae0 100644
--- a/examples/simulations/reference/ibip.html
+++ b/examples/simulations/reference/ibip.html
@@ -42,7 +42,7 @@
     
     
     
-    
+    
     
     
     
@@ -282,11 +282,11 @@ 
im
 

 

-
/tmp/ipykernel_7341/4038669023.py:2: DeprecationWarning: Call to deprecated function (or staticmethod) ibip. (The ibip function will be moved to the ``simulations`` module in a future version)
+
/tmp/ipykernel_7699/4038669023.py:2: DeprecationWarning: Call to deprecated function (or staticmethod) ibip. (The ibip function will be moved to the ``simulations`` module in a future version)
   ip = ps.filters.ibip(im=im)
 

 

-../../../_images/ccb8f203e4fa2ed970aa563aea12809add4d63be1e4c1061982bfa4f7ddfba1a.png
+../../../_images/2f5a14e791a7e2180ea636747e609e6096d31b779af3ccf8a746082381cdc0d0.png
 

 

 
The function results a Results object with an image containing the invasion sequence of each voxel (left) and the invasion size of each voxel (right).  These can be used to generate a capillary pressure curve.

@@ -309,11 +309,11 @@ 
inlets
 

 

-
/tmp/ipykernel_7341/2594871715.py:3: DeprecationWarning: Call to deprecated function (or staticmethod) ibip. (The ibip function will be moved to the ``simulations`` module in a future version)
+
/tmp/ipykernel_7699/2594871715.py:3: DeprecationWarning: Call to deprecated function (or staticmethod) ibip. (The ibip function will be moved to the ``simulations`` module in a future version)
   ip = ps.filters.ibip(im=im, inlets=inlets)
 

 

-../../../_images/1cb0b4d0a316ebdae116d545bd40e14868b94015ff0f1a72cb23419ea7e96f7d.png
+../../../_images/c8c12b486df0c5b270102f6b625134e115a9e5b857a2c3f6e23df45fe53ad400.png
 

 

 
@@ -331,11 +331,11 @@ 
maxiter<
 

 

 

-
/tmp/ipykernel_7341/1089625677.py:1: DeprecationWarning: Call to deprecated function (or staticmethod) ibip. (The ibip function will be moved to the ``simulations`` module in a future version)
+
/tmp/ipykernel_7699/1089625677.py:1: DeprecationWarning: Call to deprecated function (or staticmethod) ibip. (The ibip function will be moved to the ``simulations`` module in a future version)
   ip = ps.filters.ibip(im=im, inlets=inlets, maxiter=500)
 

 

-../../../_images/99f16960d6fe62d62afb5b9b543b676bc7e5f7de00686e75d6ede9a1bf66c352.png
+../../../_images/6b7040dc1e3ebeea526fc83243af5c3e9142321d55cbe66cf13e151120551380.png
 

 

 
diff --git a/examples/simulations/tutorials/drainage_with_gravity_advanced.html b/examples/simulations/tutorials/drainage_with_gravity_advanced.html
index 3edd9e138..b5950498e 100644
--- a/examples/simulations/tutorials/drainage_with_gravity_advanced.html
+++ b/examples/simulations/tutorials/drainage_with_gravity_advanced.html
@@ -44,7 +44,7 @@
     
     
     
-    
+    
     
     
     
@@ -2899,7 +2899,7 @@ 
Details of Drainage Simulations with and without Gravity
-../../../_images/1481d8bd0c52735e54dad9cfb6f8cb9e084a1f90c9f5fb759dc8207fb7daeda8.png
+../../../_images/b5c40dae760d897d02b2ca03ce43e4b24e5840c0cfd8e44cde5ac318c796eccc.png
 

 

 
The algorithm works by first computing the hypothetical capillary pressure of the largest sphere that can be centered on each voxel. This requires computing the distance transform of the image, which supplies the radius of the largest sphere that can be centered on each voxel, then applying the Washburn equation (or any capillary pressure equation of your choice).  First let’s specify some physical properties of the system:

@@ -2933,7 +2933,7 @@ 
Details of Drainage Simulations with and without Gravity
-../../../_images/379328fe22d3fc608df7324ae577ecda3a7d8ae5c5855f6fcf30d94bbe6b5232.png
+../../../_images/051c02ad86f5412cc0e54a7673e14e87ae95299646e27e7831bd235d45f845c4.png
 

 

 
The left shows the full image, while the right shows a subsection.  In this subsection it can be seen that higher values of \(P_C\) are found closer to the walls (indicated by the greyscale value).  This is because only very small circles can be draw in those locations, but these are immaterial because as we’ll see the larger spheres drawn in the center of the void regions will consume these at much lower capillary pressures.

@@ -2955,7 +2955,7 @@ 
Details of Drainage Simulations with and without Gravity
-../../../_images/a35919635cf81ceaf355f07d19bc9eaba7ac344e79922de8e61e754d96618720.png
+../../../_images/097ccf95edc622af335860c33464de6805298a902c4b24f0dad132efc13c6b4a.png
 

 

 
Now we can see that the hypothetical capillary pressure has a noticable gradient, indicating that the voxels higher in the image require more capillary pressure to invade. Not only must the invading non-wetting phase overcome the geometrical constraints, but it must also overcome the force of gravity pulling it down.

@@ -2971,7 +2971,7 @@ 
Details of Drainage Simulations with and without Gravity
-../../../_images/7ffa8396ab7a0352baf761a61749f488027205ec329d3732457d2c34c8e019b7.png
+../../../_images/deb08c3bf46010c2278d15826a0a4c6b1ca37f70c4e4280cce49045e5921f5d6.png
 

 

 
All the yellow values are void voxels that can potentially be penetrated by the applied capillary pressure. Howeve, there is an issue that needs to be addressed.  There are several clusters of seeds that are not connected.  These indicate regions of void space that are (a) large enough to accomodate capillary mensicii of the given size, and (b) low enough that gravity does not prevent the fluid from reaching them.  However, they are not connected to the seeds at the inlet because they are shielded by a tight constriction.  We can remove these seeds using the trim_disconnected_voxels function in porespy, or manually. Let’s do it manually for illustration purposes.  Start by labeling each clusters of seeds:

@@ -2985,7 +2985,7 @@ 
Details of Drainage Simulations with and without Gravity
-../../../_images/4c9bcddd16895837fc625d8729fb9ab4ba19ecc428acc7068ac69ee3669c14ed.png
+../../../_images/c1de24b264aaf918534eef190d5fe97fcc9f9afcbd580b2bd75f392fff61d978.png
 

 

 
We can see that any voxels that are not dark blue/purple should be removed.  Or more generally, we can scan the inlet edge of the image for unique values, then enure only those remain:

@@ -3001,7 +3001,7 @@ 
Details of Drainage Simulations with and without Gravity
-../../../_images/db253c34ece031efa3f80e8ad7ecd1109cb60e1108236f01c6b8564b36265535.png
+../../../_images/8eb73a7968e32ecb643081ca084453f748f0137e9c2598a16fc3a4bdb8a9c4de.png
 

 

 
Now that we’ve removed these inaccessible seed voxels, we can proceed. To convert this result into a fluid configuration requires inserting spheres at each yellow voxel, the diameter of each sphere taken from the value of the distance transform.  This last step means that we must analyze and process each yellow pixel separately, but this is necessary:

@@ -3017,7 +3017,7 @@ 
Details of Drainage Simulations with and without Gravity
-

+

 

 

 
 

 
Above we can see that the fluid front is quite compact, indicating that the gravitational effects have been applied.  Now let’s calculate the saturation of the image to generate a point for a capillary pressure curve:

@@ -3043,7 +3043,7 @@ 
Details of Drainage Simulations with and without Gravity
-
386.7885437011719 0.17263321934115405
+
394.62359619140625 0.4228988573113003
 

 

 

@@ -3059,7 +3059,7 @@ 
Details of Drainage Simulations with and without Gravity
-../../../_images/8761d438b5fb0572644ab246f5b8dc8c76d6042e2c70a866912f9552854f1b61.png
+../../../_images/709a150ee26185ab687f70a898b036d786b8230646613c050ba0a25947f6bdef.png
 

 

 
The above images, show the actual capillary entry pressure for each voxel, including the impact of height and connectivity which we processed manually in the above example.  We can now pass this image to pc_curve_from_pressures to get the full pseudo-capillary pressure curve:

@@ -3071,11 +3071,11 @@ 
Details of Drainage Simulations with and without Gravity
-
――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――
-Results of pc_curve generated at Thu Aug 24 13:08:56 2023
+
――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――
+Results of pc_curve generated at Thu Sep 14 04:53:56 2023
 ――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――
-pc                        Array of size (24,)
-snwp                      [0.0, 0.007947707891433271, 0.04239643305484611, 0.07728669754556079, 0.16710099129907796, 0.17516124843080386, 0.36620059737673694, 0.4087961560105623, 0.5356045192848794, 0.6063633608934678, 0.7861218129085321, 0.8696246915717935, 0.9711094757802693, 0.9786243019782693, 0.9805982425003247, 0.9809272325873338, 0.9847712220250205, 0.9847971949266265, 0.9848318254621012, 0.9848751136314445, 0.986433487727804, 0.9864681182632786, 0.9865027487987533, 0.9865027487987533]
+pc                        Array of size (22,)
+snwp                      [0.0, 0.013256229300688387, 0.07168247472733263, 0.17712541832116663, 0.2456347210903227, 0.37315982036031975, 0.43918087080161605, 0.5356071509077353, 0.5554351407119696, 0.6291810441989908, 0.6597683411073156, 0.6659933068613341, 0.6664268002982435, 0.6732759966014115, 0.6733280158138406, 0.6733626952887933, 0.6733973747637461, 0.6734320542386988, 0.6735187529260807, 0.6735621022697716, 0.6739175668880373, 0.6739175668880373]
 ――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――
 

 

@@ -3092,7 +3092,7 @@ 
Details of Drainage Simulations with and without Gravity
-../../../_images/c094878d4339bfbd07ce963fdd2bb41936602b557f71d55dcee8364c311ab42b.png
+../../../_images/d5c0e3d71283efcee2525a1388440d1eb0bf02f4cd17b48a11905f02a4ea7293.png
 

 

 
And lastly, just for comparison, let’s do the simulation with no gravity:

@@ -3105,7 +3105,7 @@ 
Details of Drainage Simulations with and without Gravity
-../../../_images/22b85d4047e1f791f054534ebcbca0946a2db8f6975a42336ea129e18666a82f.png
+../../../_images/c27b4d0c428da2eaffb0495f70c6a94b8a79e02c5b72b200f432c492f24e45d5.png
 

 

 
Note that the pc and snwp values are actually already computed for us and attached to the object that is returned from the drainage function.  Internally the pc_curve function is called as above.

diff --git a/examples/simulations/tutorials/drainage_with_gravity_basic.html b/examples/simulations/tutorials/drainage_with_gravity_basic.html
index 6d3851c19..4cbd5c05e 100644
--- a/examples/simulations/tutorials/drainage_with_gravity_basic.html
+++ b/examples/simulations/tutorials/drainage_with_gravity_basic.html
@@ -44,7 +44,7 @@
     
     
     
-    
+    
     
     
     
@@ -2896,7 +2896,7 @@ 
Basics of Peforming Drainage Simulations with and without Gravity
-../../../_images/802ff9c0ea73aa639e626ca1cfedd91a71d957a0a4454fb70aca95c82937f186.png
+../../../_images/aea7927783567cabab83d9c446880d86836b533dbb87befc94757ef88761e68c.png
 

 

 
First we’ll compute a reference capillary pressure curve with no gravity effects using the new drainage function. This function requires us to supply an image of capillary pressure values associated with each voxel.  Typicall one would use the Washburn equation:

@@ -2929,7 +2929,7 @@ 
Basics of Peforming Drainage Simulations with and without Gravity
-../../../_images/201fa41ced818d6e8bd7e051d6f09a405d75643c793862bd74b29d12b9494adc.png
+../../../_images/8418bdab4412d4563c762273ce4867e6d3ef34a7898f3535f4801bd08107deeb.png
 

 

 
Both of the above images are colored according to the capillary pressure at which a given voxel was invaded. In the right image we have applied a base-10 logarithm to the values to improve visibility.  The format is handy since it contains the entire invasion sequence in a single image.

@@ -2946,7 +2946,7 @@ 
Basics of Peforming Drainage Simulations with and without Gravity
-../../../_images/89d87d0b494b0753ff4a78a9505dbea460a7c113bc2dbcbdad7a16b9a1637def.png
+../../../_images/2c3536514fab8f0b4db06dceca8777baf45978d4a2363611f61a4e86b8afc2a3.png
 

 

 
Now let’s perform the same experiment but including the gravity effects, by setting g to earth’s gravity:

@@ -2960,7 +2960,7 @@ 
Basics of Peforming Drainage Simulations with and without Gravity
-../../../_images/7e860a6c9f1b306506229c3cca622bb2f36f07c963fbb376c905be399d13788a.png
+../../../_images/e267e5e5fdd7ad2d3c74bbf8010796441cf6a03198c66d368b23558340316a14.png
 

 

 
We can see from the colormap that the invasion pattern is different.  Plotting the capillary pressure curve will make the differences more obvious:

@@ -2973,7 +2973,7 @@ 
Basics of Peforming Drainage Simulations with and without Gravity
-../../../_images/0791c1fe6972c7d6d42d3b6dec3e1e31f5ac33f4bc77b5bb7543c908761623e1.png
+../../../_images/310074a0d3d827e374e5f9f5412762e82a1555bd264647a405a90aa69094825c.png
 

 

 
Combining both plots together for a better comparison:

@@ -2987,7 +2987,7 @@ 
Basics of Peforming Drainage Simulations with and without Gravity
-../../../_images/4d08ca2ea52c533b6ea9715ae1107eaa409ce3a748e1815a8cca4bffb48daad1.png
+../../../_images/4b7484323d67b3543d5fdb1a753aa407bb9b49b229d27a016d3b6ddb9322edd3.png

The red curve above is shifted to the right with a lower slope. This is the expected result since the impact of gravity makes it more difficult for the heavy non-wetting fluid to rise up the domain and penetrate into pores. The decreased slope is also expected since pores are invaded more gradually rather than in a larger percolation event.

diff --git a/examples/simulations/tutorials/finding_tortuosity_from_image.html b/examples/simulations/tutorials/finding_tortuosity_from_image.html index ce357f417..75d4e023a 100644 --- a/examples/simulations/tutorials/finding_tortuosity_from_image.html +++ b/examples/simulations/tutorials/finding_tortuosity_from_image.html @@ -2962,7 +2962,7 @@

Generating the image:
(-0.5, 199.5, -0.5, 199.5)

-../../../_images/7a8df7b7e5fc15e8a6b9b0f9b9762d901a8219e93a4beb59056c66eb1469a59e.png +../../../_images/686f0456b4f3a7d27fe37bd880681745fc934729ecbb99952a379c358eb6dd24.png

@@ -2977,10 +2977,10 @@

Running the algorithm
-
[13:09:30] WARNING  Found non-percolating regions, were filled to percolate                              _dns.py:73
+
[04:54:28] WARNING  Found non-percolating regions, were filled to percolate                              _dns.py:73
 

 
――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――
-Results of tortuosity_fd generated at Thu Aug 24 13:09:31 2023
+Results of tortuosity_fd generated at Thu Sep 14 04:54:29 2023
 ――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――
 im                        Array of size (200, 200)
 tortuosity                1.8776173160636371
@@ -3034,7 +3034,7 @@ 
Calling Values From The Output
2.9043927701204795
 

 

-../../../_images/11639a51dfc1d41ec01f43accb3e45b1faa111c6f5eb9fc82e857a79122f424f.png
+../../../_images/2d8418ff7d7ba045789f7f51b8fc1d460409d36286dc038781a0580b64cceeb7.png
diff --git a/examples/simulations/tutorials/using_ibip.html b/examples/simulations/tutorials/using_ibip.html index 2d46d79f2..ac12b69fe 100644 --- a/examples/simulations/tutorials/using_ibip.html +++ b/examples/simulations/tutorials/using_ibip.html @@ -42,7 +42,7 @@ - + @@ -2965,11 +2965,11 @@

Apply IBIP to image -
/tmp/ipykernel_8064/3299454374.py:1: DeprecationWarning: Call to deprecated function (or staticmethod) ibip. (The ibip function will be moved to the ``simulations`` module in a future version)
+
/tmp/ipykernel_8397/3299454374.py:1: DeprecationWarning: Call to deprecated function (or staticmethod) ibip. (The ibip function will be moved to the ``simulations`` module in a future version)
   out = ps.filters.ibip(im=im, inlets=bd, maxiter=15000)
 

 

-
+

@@ -2985,7 +2985,7 @@

Do some post-processing
-
+

@@ -3004,7 +3004,7 @@

Run standard MIO for comparison: - +

Comparing the invasion configurations between the MIO and IBIP algorithms below suggests that the methods produce similar results when trapping is turned off. In fact, it can be shown that the MIO result is a subset of the IBIP result.

@@ -3024,7 +3024,7 @@

Compare MIO and IBIP at Equal Saturations -../../../_images/920e92e31ed9fbdb584bec56b09bde0de040a2fc6ea6efaecb398a28fe579190.png +../../../_images/a9017714cba3e03019fb2d32f7722a72004af50778f9189a6f34adef4b7bb60a.png

The saturation fields can be compared directly by seeing which voxels are filled at each saturation in both methods. We must first find all the values of saturation that were obtained in the MIO result, which consists of discrete jumps (i.e. from s=0.33 to s=0.49) due to the pressure based nature of the simulations. Once we have a list of all unique saturation values, we can threshold the saturation fields from both simulations at these values and compare the configurations.

@@ -3055,7 +3055,7 @@

Compare MIO and IBIP at Equal Saturations -../../../_images/07d6fe6974c1124479501c346c086d1de81297dc1ba2f1b09faef2a2f3184467.png +../../../_images/128d88868a6b8496d4997659cca189f477869d36ef0fd60d7de5002d736f0979.png @@ -3070,11 +3070,11 @@

Comparing Capillary Pressure Curves -
/tmp/ipykernel_8064/1817964060.py:1: DeprecationWarning: Call to deprecated function (or staticmethod) pc_curve_from_ibip. (This function is deprecated, use pc_curve instead)
+
/tmp/ipykernel_8397/1817964060.py:1: DeprecationWarning: Call to deprecated function (or staticmethod) pc_curve_from_ibip. (This function is deprecated, use pc_curve instead)
   d = ps.metrics.pc_curve_from_ibip(im=im, seq=inv_seq, sizes=inv_size, voxel_size=1e-5);
 

 

-
+
@@ -3089,7 +3089,7 @@

Comparing Capillary Pressure Curves -../../../_images/337006e73c8e4bd08cc225828683826af9f316b4cfdcf1d8eac0c85386b5a555.png +../../../_images/4f0f274053e5ed035b47c624aac7bc749fd33d8a82c46d01f45066c7daeae4e9.png

The above capillary pressure curves are quite interesting. The MIO curve in red is the envelop of peak pressures obtained by the IPIP curve in green.

@@ -3119,7 +3119,7 @@

Compare results with trapping -../../../_images/9e1107deefd84d60bcf767f4265d34dd0c7519e3b33de891c0bed2561f560869.png +../../../_images/3adbad621eaf172ace0dcbf8cdba6aa6e8918ef43c0a24961ab62eab24a25ad6.png

The red color in the right image indicates regions that were invaded by the MIO algorithm, but not by the IBIP algorithm. The MIO will always underestimate trapping.

diff --git a/examples/tools/reference/align_image_with_openpnm.html b/examples/tools/reference/align_image_with_openpnm.html index 83f49fd8f..b3b5d2039 100644 --- a/examples/tools/reference/align_image_with_openpnm.html +++ b/examples/tools/reference/align_image_with_openpnm.html @@ -2916,7 +2916,7 @@

Create image and variables -../../../_images/11eb4acb803e400a0e84c3636cc984c23bf5e210d7eb9f4e70c83e23f294d622.png +../../../_images/2b9e030dfc981fb141254a080d0c8798712d20c17e0ac3a0f3399ffec9311e89.png @@ -2932,7 +2932,7 @@

Apply tool -../../../_images/3bb75d768ed41726f2cc35e6b061ce05be962e75c42a736d28012bf27cfd2188.png +../../../_images/e8adf99b0e4e3ff829d1c016135b53f423b1172d96daf886baa303bd2fb6288a.png diff --git a/examples/tools/reference/bbox_to_slices.html b/examples/tools/reference/bbox_to_slices.html index 27a11a53c..0ba60006e 100644 --- a/examples/tools/reference/bbox_to_slices.html +++ b/examples/tools/reference/bbox_to_slices.html @@ -2929,7 +2929,7 @@

Generate image for testing -../../../_images/e4ecb8cc1a03ece0a00c24978b59f258beb8af2770a2a6bae17ac212d2a90867.png +../../../_images/00f2c51452458ec474b535af176d7fac79377c5c134db44033a1112cadfa76fc.png @@ -2970,7 +2970,7 @@

Demonstration of function
Text(0.5, 1.0, '3D')
-../../../_images/5bcd47f5bcdafad70840682e8c83846f5aaea4660aaf0285be2f68fb1dc9407c.png +../../../_images/94a3297334f77a4b73714ff5ac75eec682f0f8b92d3226e0fe429e3f823460a7.png diff --git a/examples/tools/reference/extract_cylinder.html b/examples/tools/reference/extract_cylinder.html index 1a4150af4..0f7c6a97e 100644 --- a/examples/tools/reference/extract_cylinder.html +++ b/examples/tools/reference/extract_cylinder.html @@ -2930,7 +2930,7 @@

Apply tool and visualize -../../../_images/ef171219a8d59f52b148429c8939c606b6dda3d2296a5162553fb7fb6c651e2a.png +../../../_images/6b6f2a2df50fc85e98c148fdbf1e7512423351b12c679f49b571cc255fd9f4eb.png diff --git a/examples/tools/reference/extract_regions.html b/examples/tools/reference/extract_regions.html index 173de56e1..1edd47582 100644 --- a/examples/tools/reference/extract_regions.html +++ b/examples/tools/reference/extract_regions.html @@ -2919,7 +2919,7 @@

Generate image for testing -../../../_images/55060c32751df411493a1f1b98c64b478a7728f53a4f014832eea0cb25906585.png +../../../_images/55c8e800809e4b503118356a44fe6d7ef26ce081e4a44973777d16f09043f093.png @@ -2942,7 +2942,7 @@

Apply tool -../../../_images/09e47e5c81edbb1db3630cb8921ab48231a38d1f436419fd7422f918d18dbaed.png +../../../_images/1dab68c43befe5b5bdb59fd92bb26ab1feb46466d52f5e23e7c4a3c091efd9de.png diff --git a/examples/tools/reference/extract_subsection.html b/examples/tools/reference/extract_subsection.html index 3c1746a12..02af7b5ed 100644 --- a/examples/tools/reference/extract_subsection.html +++ b/examples/tools/reference/extract_subsection.html @@ -2916,10 +2916,10 @@

Generate image for testing -
<matplotlib.image.AxesImage at 0x7f54fbbd9430>
+
<matplotlib.image.AxesImage at 0x7fb1cb6a3f70>
 

 

-../../../_images/1068f6887930ffedddb4a3412a09f71a3633095fff273f5d35c9c69879ad4168.png
+../../../_images/520bbd8c1801278deb92012841c31423ac3b3c2cbdb5d183d3994bf46dacd703.png
@@ -2939,7 +2939,7 @@

Demonstration -../../../_images/2180f966b73298ea59f8d7c9936239e2c23d86c762ee9efd291a48d378d87d88.png +../../../_images/151e8d9f18938f171bf3d641c97d3732f5919437b6b9b38b51fcad674ff4ed6d.png diff --git a/examples/tools/reference/get_border.html b/examples/tools/reference/get_border.html index b0964ed6f..c1942e409 100644 --- a/examples/tools/reference/get_border.html +++ b/examples/tools/reference/get_border.html @@ -2953,7 +2953,7 @@

thickness -../../../_images/23a138c76d2ef7e1406bcadbc53814f568786b915c0444874b5cc083ad491a45.png +../../../_images/19473f37b55fc1386adaeaff1b945a6864106b3844f583e10db652025dc4d9ff.png @@ -2986,7 +2986,7 @@

mode#
-../../../_images/6c3222e7d754dea634670d87e912d1b6db19c2b5f38ad1fc6c40b61dfa37a5ab.png +../../../_images/0763ab0b9d2aed698600d647c72a5c5793fee2b0e46130f9aab490caa50897b4.png

For 2D images, the mode of ‘faces’ and ‘edges’ both return the same thing.

@@ -3015,7 +3015,7 @@

mode#
-../../../_images/a0f6f0d4e0998ec65deafa7582c002a2c8f47aa1ebbd72fa917fbc95b7c2792c.png +../../../_images/a39cd55b00196ffbaee8574c33efb778468ed1e4b88f0447587bc30b701a0ac5.png
@@ -3043,7 +3043,7 @@

return_indices
Text(0.5, 1.0, 'image with zeroed borders')
-../../../_images/825fecdbc6f9d9a1534e4b9aec40870f38de3a427f38801fae51874dfe7d088a.png +../../../_images/3729f794ed3ea65ea113f4b016be59992fb45825120ab66513c8ea4cff18e9e4.png diff --git a/examples/tools/reference/get_planes.html b/examples/tools/reference/get_planes.html index a05e719f2..c5f883d90 100644 --- a/examples/tools/reference/get_planes.html +++ b/examples/tools/reference/get_planes.html @@ -2918,7 +2918,7 @@

Generate image for testing -../../../_images/c9d2c3bd306f221bfed4d70f49f05954bbbbf5447a30afaeeeefbd3a7c2e5b94.png +../../../_images/a90fa12000471a06a692bf1839dc0b3b1537c16d423358a0a1cbd4f225ad1ba9.png @@ -2938,7 +2938,7 @@

Demonstrate function
-../../../_images/f8ab2b45a96b71b60ebc2b5337d6dae4a8c998a7c87aae50dd5a8e2ef9945e7a.png +../../../_images/a293af27614309425ebd7052d211b0f96e0572c497ee1dc64934fdc568075116.png
diff --git a/examples/tools/reference/insert_cylinder.html b/examples/tools/reference/insert_cylinder.html index 044316438..e202369ba 100644 --- a/examples/tools/reference/insert_cylinder.html +++ b/examples/tools/reference/insert_cylinder.html @@ -2918,7 +2918,7 @@

Generate image for testing -../../../_images/5f4f813882448f85d5e0c2120529e861bcccc2dd3841f5fc82e7c9a7dc82222c.png +../../../_images/a77fc4308e8c7bbd2b94dc3ac5b9d677bf6f229e60107a5a38f37a190093656e.png @@ -2935,7 +2935,7 @@

Demonstrate tool -../../../_images/3ddd43ed95491232af1d6cf630080ec80b6e7b35527500a8fc457aff062871c9.png +../../../_images/26144d035af76f9d5d500d1e5e237053d0ec4fe3a59bbddce6a1297edcb883fe.png diff --git a/examples/tools/reference/insert_sphere.html b/examples/tools/reference/insert_sphere.html index 523a132ed..b116899ce 100644 --- a/examples/tools/reference/insert_sphere.html +++ b/examples/tools/reference/insert_sphere.html @@ -2923,7 +2923,7 @@

Create image and variables -../../../_images/169d4942c6c194c5c8da5fe3ac0962ef5a216f382bace4d796b21db96e790340.png +../../../_images/71ceac3279fef2e106fd2302003bf7f12ac69faf67cb6167fcc4d7d5b73e0427.png @@ -2939,7 +2939,7 @@

Apply tool -../../../_images/adefba57e420c4fe6266be4cb3e99de8ed85a67957faa3409807feb4c766bc97.png +../../../_images/41d679374fb7dbb7aca38dac7fd6d589ca8b2188edbe78fbf52e678486dc98ea.png diff --git a/examples/tools/reference/make_contiguous.html b/examples/tools/reference/make_contiguous.html index aa1847bb4..b02416db5 100644 --- a/examples/tools/reference/make_contiguous.html +++ b/examples/tools/reference/make_contiguous.html @@ -2914,16 +2914,16 @@

Generate image for testing -
[[  8  -8  -9   6   0   8   4   8   6  -6]
- [  6   7   4   1   3   9  -2  -5  -9   3]
- [  9   1  -5  -5  -4  -8   7  -6  -4  -1]
- [  9  -5   5   6   3  -9   5   7   2  -5]
- [  5 -10  -2   9  -1   1  -2  -3   6   5]
- [-10  -3  -8  -5   4  -4   2   7  -1  -5]
- [ -5   5   4   5  -8   9   9   6   6   8]
- [  4  -9  -7  -3   9   2  -8   4  -6   1]
- [  7   7  -1   0   7   6   4  -4  -5   7]
- [ -4  -8  -4  -5  -4  -7   8   0   7  -4]]
+
[[  2   7   4   7  -4 -10  -4   7   2 -10]
+ [  4   3   3   5   7  -1   5   2  -6  -1]
+ [  6 -10 -10   1   4  -8  -8  -1   0  -8]
+ [  2   9   8   3   8 -10  -5  -1   8   7]
+ [  0  -4   3  -3   6   0   2   1  -8   3]
+ [ -8   0   4   5  -5   8   9  -9  -6  -5]
+ [  0   8   0   3   0  -8  -5 -10  -1   8]
+ [ -8   8   0  -1  -4   4   1  -7   6  -7]
+ [-10   0   4   5  -8  -9 -10  -4   9   2]
+ [ -2   2   3   7   5  -1  -6   6   9   4]]
@@ -2938,7 +2938,7 @@

Generate image for testing -../../../_images/51bf605f34faf2a1a972883df6314d8d3067b43bd35bb0370372ea8b14656728.png +../../../_images/5ee8e7c891dd6f82cd9fc715cbcb6e605b38edbbd39cfce3e8a876ff641ef761.png

@@ -2961,7 +2961,7 @@

Demonstrate function
-../../../_images/6ed017bac4f5b2fe3584649ac77b214e0e48e2fa0fe3f40930c6329898fb6da9.png +../../../_images/102da8d4f0ab8e4eb3a5408009da6e741f9627e3e17f9c595a50994ce47fbacb.png
diff --git a/examples/tools/reference/norm_to_uniform.html b/examples/tools/reference/norm_to_uniform.html index 123fed74a..3a27780b2 100644 --- a/examples/tools/reference/norm_to_uniform.html +++ b/examples/tools/reference/norm_to_uniform.html @@ -2928,7 +2928,7 @@

Generate image for testing -../../../_images/f7937b1185620eb7ba82cf62f81ded319f9a97a8dc06959935c5c122cf61a738.png +../../../_images/66fbe354f9ed66a4e1eae4dc40f7edfef7a5fd8f567926b54457d6d77cbe0ea1.png @@ -2948,7 +2948,7 @@

Demonstrate function
-../../../_images/f2d8bc688eadf180272d93e041d91fa8e4f5c4eb19cf72033f00b8ea73145238.png +../../../_images/d2d8b1c7f0e1a99e4a411fe6ce51587351900166e81764a9794113bf90ef6787.png
@@ -2967,7 +2967,7 @@

scale#
-../../../_images/1851a877f89f5d692ea317ea0a5bf3c0d3dd9e6ab088d34eb95b4547c78385b5.png +../../../_images/f2fcddfb1047b0ae6f54c9b56db51f0ebfce7334af7acc5f8ce91c18326a3244.png

diff --git a/examples/tools/reference/overlay.html b/examples/tools/reference/overlay.html index 18ccf8a29..de834ea5f 100644 --- a/examples/tools/reference/overlay.html +++ b/examples/tools/reference/overlay.html @@ -2927,16 +2927,16 @@

Create image and variables -
/tmp/ipykernel_8741/2366592848.py:3: DeprecationWarning: Call to deprecated function (or staticmethod) RSA. (This function has been renamed to rsa (lowercase to meet pep8))
+
/tmp/ipykernel_9070/2366592848.py:3: DeprecationWarning: Call to deprecated function (or staticmethod) RSA. (This function has been renamed to rsa (lowercase to meet pep8))
   im1 = ps.generators.RSA(im1, r=25, volume_fraction=0.5)
 

 

-
/tmp/ipykernel_8741/2366592848.py:4: DeprecationWarning: Call to deprecated function (or staticmethod) RSA. (This function has been renamed to rsa (lowercase to meet pep8))
+
/tmp/ipykernel_9070/2366592848.py:4: DeprecationWarning: Call to deprecated function (or staticmethod) RSA. (This function has been renamed to rsa (lowercase to meet pep8))
   im2 = ps.generators.RSA(im2, r=5, volume_fraction=0.5)
 

 

-../../../_images/ec9a97f80bf261c475842d4d06a786a03745f5ffa4c156aca81718b0d3cde5f6.png
-../../../_images/0002184cd2cf6a433dbe361948953ef50c1020a22c260eb54a52edc1750c498f.png
+../../../_images/c3781bd2b79a773fb3a6dadbe8c7c6272b89a90455687a195d222b130478b0ca.png
+../../../_images/53582683c02e1788757b2ed626dffa60827fcc801ef4b0c62c5519f4c8cf8c10.png
 

 

 
@@ -2952,7 +2952,7 @@ 
Apply tool
-../../../_images/1f7e5548aa77213b0e83164dd25d071661b1d5b22220af785430d4a7bea6d734.png
+../../../_images/62739cf769b195f8d028cb2090d234586f22113274f03ad9f8e0d05de417c6f9.png
@@ -2965,7 +2965,7 @@

Apply tool -../../../_images/0cf73ee7465ae49521f9bbe7c302883054c1cac5923e5f023051bb0803727f76.png +../../../_images/4c55d6553fe4fc6dc64a40a46f363f1cc2790a2e6c1ec9ffb1e1f2c37c74e3e3.png

diff --git a/examples/tools/reference/subdivide.html b/examples/tools/reference/subdivide.html index a08b01af2..431008fc8 100644 --- a/examples/tools/reference/subdivide.html +++ b/examples/tools/reference/subdivide.html @@ -2918,7 +2918,7 @@

Create image and variables -../../../_images/a5843937d12344df28e2397ee2651c20951bc1c789edff98a85af1f1b1ba9fb7.png +../../../_images/3a9149b62a238b432320c073b391b64f9a38025c5521fd509164669c94a2d198.png @@ -2948,7 +2948,7 @@

Apply tool -../../../_images/a3fe23edadc6b9ad833e98ee23341f4dc5408af06b62b9aa2c90076a895619ad.png +../../../_images/b830d8778943857c39b221229ba949366306a9999c39308a0bf9449b0f815b54.png diff --git a/examples/tools/reference/unpad.html b/examples/tools/reference/unpad.html index a4841bd0a..e814460f0 100644 --- a/examples/tools/reference/unpad.html +++ b/examples/tools/reference/unpad.html @@ -2915,7 +2915,7 @@

Generate image for testing -../../../_images/15180f8df1eec6b540789d2efea8811fbf2453e0a32601543a4448c179726695.png +../../../_images/b5c4494a32c4f7c04aa3240f024f365edc75951f45a7b8aa80b3bfcd5ec94502.png @@ -2947,7 +2947,7 @@

Apply tool +../../../_images/f5f607f6a171f9ac366c3afb1003ee100ceaf4b7c9b38e9690555590f7eb5168.png diff --git a/examples/visualization/reference/imshow.html b/examples/visualization/reference/imshow.html index 08a029b54..9c81daa94 100644 --- a/examples/visualization/reference/imshow.html +++ b/examples/visualization/reference/imshow.html @@ -2931,7 +2931,7 @@

im
-../../../_images/93151e2945f01c010c806e9c97ace1aebe10a8aa54516199e92589fe1a070f1f.png +../../../_images/994180a349ae6e1de12bd1a771fd8eddef690fe7fd14f8dd44c930de35bf603d.png
@@ -2945,7 +2945,7 @@

axis
-../../../_images/91dd4a8d2805c38920322c257ee32bab34c310b398102e1f5dac7d9b7ebae8fa.png +../../../_images/520f9da002571619618bfffe5f312295c7deeef15540a0c9c8c5cc803f379c10.png
@@ -2959,7 +2959,7 @@

ind
-../../../_images/11ae640f85fd19bef4a9e7b87d9de8c1b8482bea9a739b09b04e93465c7add75.png +../../../_images/0033ff955a0744d787eac581ebb926dc5fcc5c6a1e88a416ef31e80591bd6ad2.png
@@ -2973,7 +2973,7 @@

kwargs
-../../../_images/593d87b213c23501a5a2c81adde08e13aad0d257e01051c512393f075778c68c.png +../../../_images/f06cf16229a92c47454756b76f214f79ffc6721fa2b14e616b11591efb4217c5.png
diff --git a/examples/visualization/reference/prep_for_imshow.html b/examples/visualization/reference/prep_for_imshow.html index 7d6953d5a..48bf0c070 100644 --- a/examples/visualization/reference/prep_for_imshow.html +++ b/examples/visualization/reference/prep_for_imshow.html @@ -2955,7 +2955,7 @@

im
-../../../_images/e1cd5095e9f8d42e83aff54c97b851d6c5ac711d7ce0e0478109a0e25e47ae87.png +../../../_images/7bcc7255e3c30306ba0c90d591cec62b9e9f8f65bdf3af5992e15cc97d7d08df.png

The returned dict is passable to imshow as keyword arguments, with all the useful values set

@@ -2988,7 +2988,7 @@

im
-../../../_images/054bf8ebf5209c178eed884c131f16fa3a57553247c4b3b0abc5991afb2d87e7.png +../../../_images/9b89a2f24d611bdefd95845a35354a1d4b3d716d345836b763128f31a01d8f74.png
@@ -3007,7 +3007,7 @@

mask
-../../../_images/3fb50ce7465bdfccd1f1d29fdd03ec417b9e561e8a1771a887da3d81fa864bb9.png +../../../_images/7b8f1d50a7f099037f666b25c207650d939385c8c50e19f60bfab38bd7544be2.png
@@ -3028,7 +3028,7 @@

axis
-../../../_images/a6b853d756d4b226580947feb115c9859dc5b6c07f71fec16e8258c4673028fd.png +../../../_images/93ddfb40962073f4d48561a8a31b6f0303de6c4c9238d3f9cc21a8ee5f373a54.png
@@ -3049,7 +3049,7 @@

slice
-../../../_images/d36310b0db2522baac25a49ef27c1aca13de11aa11b1a56c31a5ee2e25f42917.png +../../../_images/78673d36abede959039a0a8e2ab0af334fdf1f76df730faa974dcce867e62bef.png
diff --git a/examples/visualization/reference/sem.html b/examples/visualization/reference/sem.html index 5e8c58fe1..c7c8a9222 100644 --- a/examples/visualization/reference/sem.html +++ b/examples/visualization/reference/sem.html @@ -42,7 +42,7 @@ - + @@ -2911,7 +2911,7 @@

sem
-../../../_images/4760afb8465ac306a2b318fd07ea3ac4593ae1deaf381b23ca9eeadf9c43df9c.png +../../../_images/7ad7c0c9199355a73dc0f826dc76f2181da65249545366fbfeb56d8da4e48bca.png
@@ -2936,7 +2936,7 @@

axis
-../../../_images/4aea01d6a2b3736c1f94c423bbc710ee66bd6b0f4cabfe4d4921dc07438d2108.png +../../../_images/d88c031287bdfb5fa6cf0a1f77d0cd9dc7b32d0e2bfae28ab7b05c8a60728cee.png

diff --git a/examples/visualization/reference/show_panels.html b/examples/visualization/reference/show_panels.html index 334dfd1d4..06861681f 100644 --- a/examples/visualization/reference/show_panels.html +++ b/examples/visualization/reference/show_panels.html @@ -2927,7 +2927,7 @@

im
-../../../_images/d6b5354df59dd1f785a44a630740ec3d10bd41488c04a3cea81ed45d206f6676.png +../../../_images/ec74152df55b0074af8c79f4e41ef2ff22e5c353d53eb39363058707ba62cc1c.png
@@ -2941,7 +2941,7 @@

rc
-../../../_images/b1fe9dd233938c37e5fb246a1c374d0c3c34efdb07f3a023c0c633e142c376cf.png +../../../_images/93ebd1578ba7fd966a4fd7c08c3a0033f32b83d965474c9ae5ec3087eebe9005.png
@@ -2955,7 +2955,7 @@

axis
-../../../_images/369125ae54723b1bb9b8f55c7d935911c2ad75091094cab91847882062c4d413.png +../../../_images/bdad4605b42a6611a6d3b4ae4bcda1126e70ee22fbd644162c991f318042fc4f.png
diff --git a/examples/visualization/reference/xray.html b/examples/visualization/reference/xray.html index 87b7b3b86..c62502574 100644 --- a/examples/visualization/reference/xray.html +++ b/examples/visualization/reference/xray.html @@ -42,7 +42,7 @@ - + @@ -2910,7 +2910,7 @@

xray
-../../../_images/8be3bf1f350df6a243d399e6ea5dfbacd6b34d116abb528aa4f233e56e5e5c14.png +../../../_images/fb9b4f3262b029798dba1a5320c8591d57b8be27f7d3414fa00f7459b1306708.png
@@ -2935,7 +2935,7 @@

axis
-../../../_images/2fa408036e0634bcfe082a78055051d993dc8314a8631e5953752097d6fa05a4.png +../../../_images/69f9c8fb45e937cafc2b619b1592a81cc6ba523a6e675941e0a85ad3ad970885.png

diff --git a/examples/visualization/tutorials/visualizing_tif_in_paraveiw.html b/examples/visualization/tutorials/visualizing_tif_in_paraveiw.html index f3fb27715..506481da3 100644 --- a/examples/visualization/tutorials/visualizing_tif_in_paraveiw.html +++ b/examples/visualization/tutorials/visualizing_tif_in_paraveiw.html @@ -42,7 +42,7 @@ - + @@ -2897,7 +2897,7 @@

Visualizing a tif image in Paraview -../../../_images/151b7f025e912a20c923261a6270cd6039b2f228fdfc4b856994ff546b5ba469.png +../../../_images/ecee8508b4440d2fff4e08c22077964f1400ffcec4cce33141bb739b991dce73.png

We can then save the ragions as a .tif format to be imported in Paraview.

diff --git a/reports/examples/filters/reference/trim_floating_solid.err.log b/reports/examples/filters/reference/trim_floating_solid.err.log index de83eda11..5ac39800d 100644 --- a/reports/examples/filters/reference/trim_floating_solid.err.log +++ b/reports/examples/filters/reference/trim_floating_solid.err.log @@ -1,30 +1,30 @@ Traceback (most recent call last): - File "/opt/hostedtoolcache/Python/3.8.17/x64/lib/python3.8/site-packages/nbclient/client.py", line 778, in _async_poll_for_reply + File "/opt/hostedtoolcache/Python/3.8.18/x64/lib/python3.8/site-packages/nbclient/client.py", line 778, in _async_poll_for_reply msg = await ensure_async(self.kc.shell_channel.get_msg(timeout=new_timeout)) - File "/opt/hostedtoolcache/Python/3.8.17/x64/lib/python3.8/site-packages/jupyter_core/utils/__init__.py", line 182, in ensure_async + File "/opt/hostedtoolcache/Python/3.8.18/x64/lib/python3.8/site-packages/jupyter_core/utils/__init__.py", line 182, in ensure_async result = await obj - File "/opt/hostedtoolcache/Python/3.8.17/x64/lib/python3.8/site-packages/jupyter_client/channels.py", line 315, in get_msg + File "/opt/hostedtoolcache/Python/3.8.18/x64/lib/python3.8/site-packages/jupyter_client/channels.py", line 315, in get_msg raise Empty _queue.Empty During handling of the above exception, another exception occurred: Traceback (most recent call last): - File "/opt/hostedtoolcache/Python/3.8.17/x64/lib/python3.8/site-packages/jupyter_cache/executors/utils.py", line 58, in single_nb_execution + File "/opt/hostedtoolcache/Python/3.8.18/x64/lib/python3.8/site-packages/jupyter_cache/executors/utils.py", line 58, in single_nb_execution executenb( - File "/opt/hostedtoolcache/Python/3.8.17/x64/lib/python3.8/site-packages/nbclient/client.py", line 1305, in execute + File "/opt/hostedtoolcache/Python/3.8.18/x64/lib/python3.8/site-packages/nbclient/client.py", line 1305, in execute return NotebookClient(nb=nb, resources=resources, km=km, **kwargs).execute() - File "/opt/hostedtoolcache/Python/3.8.17/x64/lib/python3.8/site-packages/jupyter_core/utils/__init__.py", line 166, in wrapped + File "/opt/hostedtoolcache/Python/3.8.18/x64/lib/python3.8/site-packages/jupyter_core/utils/__init__.py", line 166, in wrapped return loop.run_until_complete(inner) - File "/opt/hostedtoolcache/Python/3.8.17/x64/lib/python3.8/asyncio/base_events.py", line 616, in run_until_complete + File "/opt/hostedtoolcache/Python/3.8.18/x64/lib/python3.8/asyncio/base_events.py", line 616, in run_until_complete return future.result() - File "/opt/hostedtoolcache/Python/3.8.17/x64/lib/python3.8/site-packages/nbclient/client.py", line 705, in async_execute + File "/opt/hostedtoolcache/Python/3.8.18/x64/lib/python3.8/site-packages/nbclient/client.py", line 705, in async_execute await self.async_execute_cell( - File "/opt/hostedtoolcache/Python/3.8.17/x64/lib/python3.8/site-packages/nbclient/client.py", line 1001, in async_execute_cell + File "/opt/hostedtoolcache/Python/3.8.18/x64/lib/python3.8/site-packages/nbclient/client.py", line 1001, in async_execute_cell exec_reply = await self.task_poll_for_reply - File "/opt/hostedtoolcache/Python/3.8.17/x64/lib/python3.8/site-packages/nbclient/client.py", line 802, in _async_poll_for_reply + File "/opt/hostedtoolcache/Python/3.8.18/x64/lib/python3.8/site-packages/nbclient/client.py", line 802, in _async_poll_for_reply error_on_timeout_execute_reply = await self._async_handle_timeout(timeout, cell) - File "/opt/hostedtoolcache/Python/3.8.17/x64/lib/python3.8/site-packages/nbclient/client.py", line 852, in _async_handle_timeout + File "/opt/hostedtoolcache/Python/3.8.18/x64/lib/python3.8/site-packages/nbclient/client.py", line 852, in _async_handle_timeout raise CellTimeoutError.error_from_timeout_and_cell( nbclient.exceptions.CellTimeoutError: A cell timed out while it was being executed, after 30 seconds. The message was: Cell execution timed out. diff --git a/reports/examples/general/denoising_and_segmenting_images.err.log b/reports/examples/general/denoising_and_segmenting_images.err.log index 101ff786e..2eb9ef0ce 100644 --- a/reports/examples/general/denoising_and_segmenting_images.err.log +++ b/reports/examples/general/denoising_and_segmenting_images.err.log @@ -1,17 +1,17 @@ Traceback (most recent call last): - File "/opt/hostedtoolcache/Python/3.8.17/x64/lib/python3.8/site-packages/jupyter_cache/executors/utils.py", line 58, in single_nb_execution + File "/opt/hostedtoolcache/Python/3.8.18/x64/lib/python3.8/site-packages/jupyter_cache/executors/utils.py", line 58, in single_nb_execution executenb( - File "/opt/hostedtoolcache/Python/3.8.17/x64/lib/python3.8/site-packages/nbclient/client.py", line 1305, in execute + File "/opt/hostedtoolcache/Python/3.8.18/x64/lib/python3.8/site-packages/nbclient/client.py", line 1305, in execute return NotebookClient(nb=nb, resources=resources, km=km, **kwargs).execute() - File "/opt/hostedtoolcache/Python/3.8.17/x64/lib/python3.8/site-packages/jupyter_core/utils/__init__.py", line 166, in wrapped + File "/opt/hostedtoolcache/Python/3.8.18/x64/lib/python3.8/site-packages/jupyter_core/utils/__init__.py", line 166, in wrapped return loop.run_until_complete(inner) - File "/opt/hostedtoolcache/Python/3.8.17/x64/lib/python3.8/asyncio/base_events.py", line 616, in run_until_complete + File "/opt/hostedtoolcache/Python/3.8.18/x64/lib/python3.8/asyncio/base_events.py", line 616, in run_until_complete return future.result() - File "/opt/hostedtoolcache/Python/3.8.17/x64/lib/python3.8/site-packages/nbclient/client.py", line 705, in async_execute + File "/opt/hostedtoolcache/Python/3.8.18/x64/lib/python3.8/site-packages/nbclient/client.py", line 705, in async_execute await self.async_execute_cell( - File "/opt/hostedtoolcache/Python/3.8.17/x64/lib/python3.8/site-packages/nbclient/client.py", line 1058, in async_execute_cell + File "/opt/hostedtoolcache/Python/3.8.18/x64/lib/python3.8/site-packages/nbclient/client.py", line 1058, in async_execute_cell await self._check_raise_for_error(cell, cell_index, exec_reply) - File "/opt/hostedtoolcache/Python/3.8.17/x64/lib/python3.8/site-packages/nbclient/client.py", line 914, in _check_raise_for_error + File "/opt/hostedtoolcache/Python/3.8.18/x64/lib/python3.8/site-packages/nbclient/client.py", line 914, in _check_raise_for_error raise CellExecutionError.from_cell_and_msg(cell, exec_reply_content) nbclient.exceptions.CellExecutionError: An error occurred while executing the following cell: ------------------ @@ -31,13 +31,13 @@ Cell In[8], line 1  2 im = (im - im.min())/(im.max() - im.min())  3 fig, ax = subplots(1, 3, figsize=[15, 5]) -File /opt/hostedtoolcache/Python/3.8.17/x64/lib/python3.8/site-packages/imageio/v2.py:522, in volread(uri, format, **kwargs) +File /opt/hostedtoolcache/Python/3.8.18/x64/lib/python3.8/site-packages/imageio/v2.py:522, in volread(uri, format, **kwargs)  520 imopen_args = decypher_format_arg(format)  521 imopen_args["legacy_mode"] = True --> 522 with imopen(uri, "rv", **imopen_args) as file:  523 return file.read(index=0, **kwargs) -File /opt/hostedtoolcache/Python/3.8.17/x64/lib/python3.8/site-packages/imageio/core/imopen.py:113, in imopen(uri, io_mode, plugin, extension, format_hint, legacy_mode, **kwargs) +File /opt/hostedtoolcache/Python/3.8.18/x64/lib/python3.8/site-packages/imageio/core/imopen.py:113, in imopen(uri, io_mode, plugin, extension, format_hint, legacy_mode, **kwargs)  111 request.format_hint = format_hint  112 else: --> 113 request = Request(uri, io_mode, format_hint=format_hint, extension=extension) @@ -45,14 +45,14 @@ File /opt/hostedtoolcache/Python/3.8.17/x64/lib/python3.8/site-packages/i  117 # fast-path based on plugin  118 # (except in legacy mode) -File /opt/hostedtoolcache/Python/3.8.17/x64/lib/python3.8/site-packages/imageio/core/request.py:247, in Request.__init__(self, uri, mode, extension, format_hint, **kwargs) +File /opt/hostedtoolcache/Python/3.8.18/x64/lib/python3.8/site-packages/imageio/core/request.py:247, in Request.__init__(self, uri, mode, extension, format_hint, **kwargs)  244 raise ValueError(f"Invalid Request.Mode: {mode}")  246 # Parse what was given --> 247 self._parse_uri(uri)  249 # Set extension  250 if extension is not None: -File /opt/hostedtoolcache/Python/3.8.17/x64/lib/python3.8/site-packages/imageio/core/request.py:407, in Request._parse_uri(self, uri) +File /opt/hostedtoolcache/Python/3.8.18/x64/lib/python3.8/site-packages/imageio/core/request.py:407, in Request._parse_uri(self, uri)  404 if is_read_request:  405 # Reading: check that the file exists (but is allowed a dir)  406 if not os.path.exists(fn): diff --git a/reports/examples/general/loading_images.err.log b/reports/examples/general/loading_images.err.log index ae30d5ed2..21c5dc2ee 100644 --- a/reports/examples/general/loading_images.err.log +++ b/reports/examples/general/loading_images.err.log @@ -1,17 +1,17 @@ Traceback (most recent call last): - File "/opt/hostedtoolcache/Python/3.8.17/x64/lib/python3.8/site-packages/jupyter_cache/executors/utils.py", line 58, in single_nb_execution + File "/opt/hostedtoolcache/Python/3.8.18/x64/lib/python3.8/site-packages/jupyter_cache/executors/utils.py", line 58, in single_nb_execution executenb( - File "/opt/hostedtoolcache/Python/3.8.17/x64/lib/python3.8/site-packages/nbclient/client.py", line 1305, in execute + File "/opt/hostedtoolcache/Python/3.8.18/x64/lib/python3.8/site-packages/nbclient/client.py", line 1305, in execute return NotebookClient(nb=nb, resources=resources, km=km, **kwargs).execute() - File "/opt/hostedtoolcache/Python/3.8.17/x64/lib/python3.8/site-packages/jupyter_core/utils/__init__.py", line 166, in wrapped + File "/opt/hostedtoolcache/Python/3.8.18/x64/lib/python3.8/site-packages/jupyter_core/utils/__init__.py", line 166, in wrapped return loop.run_until_complete(inner) - File "/opt/hostedtoolcache/Python/3.8.17/x64/lib/python3.8/asyncio/base_events.py", line 616, in run_until_complete + File "/opt/hostedtoolcache/Python/3.8.18/x64/lib/python3.8/asyncio/base_events.py", line 616, in run_until_complete return future.result() - File "/opt/hostedtoolcache/Python/3.8.17/x64/lib/python3.8/site-packages/nbclient/client.py", line 705, in async_execute + File "/opt/hostedtoolcache/Python/3.8.18/x64/lib/python3.8/site-packages/nbclient/client.py", line 705, in async_execute await self.async_execute_cell( - File "/opt/hostedtoolcache/Python/3.8.17/x64/lib/python3.8/site-packages/nbclient/client.py", line 1058, in async_execute_cell + File "/opt/hostedtoolcache/Python/3.8.18/x64/lib/python3.8/site-packages/nbclient/client.py", line 1058, in async_execute_cell await self._check_raise_for_error(cell, cell_index, exec_reply) - File "/opt/hostedtoolcache/Python/3.8.17/x64/lib/python3.8/site-packages/nbclient/client.py", line 914, in _check_raise_for_error + File "/opt/hostedtoolcache/Python/3.8.18/x64/lib/python3.8/site-packages/nbclient/client.py", line 914, in _check_raise_for_error raise CellExecutionError.from_cell_and_msg(cell, exec_reply_content) nbclient.exceptions.CellExecutionError: An error occurred while executing the following cell: ------------------ @@ -26,7 +26,7 @@ Cell In[4], line 2  1 fig, ax = subplots(figsize=[5, 5]) ----> 2 ax.imshow(seq[0]); -File /opt/hostedtoolcache/Python/3.8.17/x64/lib/python3.8/site-packages/skimage/io/collection.py:301, in ImageCollection.__getitem__(self, n) +File /opt/hostedtoolcache/Python/3.8.18/x64/lib/python3.8/site-packages/skimage/io/collection.py:301, in ImageCollection.__getitem__(self, n)  298 raise TypeError('slicing must be with an int or slice object')  300 if type(n) is int: --> 301 n = self._check_imgnum(n) @@ -34,7 +34,7 @@ File /opt/hostedtoolcache/Python/3.8.17/x64/lib/python3.8/site-packages/s  304 if ((self.conserve_memory and n != self._cached) or  305 (self.data[idx] is None)): -File /opt/hostedtoolcache/Python/3.8.17/x64/lib/python3.8/site-packages/skimage/io/collection.py:357, in ImageCollection._check_imgnum(self, n) +File /opt/hostedtoolcache/Python/3.8.18/x64/lib/python3.8/site-packages/skimage/io/collection.py:357, in ImageCollection._check_imgnum(self, n)  355 n = n % num  356 else: --> 357 raise IndexError(f"There are only {num} images in the collection") diff --git a/reports/examples/networks/reference/diffusive_size_factor_AI.err.log b/reports/examples/networks/reference/diffusive_size_factor_AI.err.log index b2aeb3130..e02514ce4 100644 --- a/reports/examples/networks/reference/diffusive_size_factor_AI.err.log +++ b/reports/examples/networks/reference/diffusive_size_factor_AI.err.log @@ -1,55 +1,37 @@ Traceback (most recent call last): - File "/opt/hostedtoolcache/Python/3.8.17/x64/lib/python3.8/site-packages/jupyter_cache/executors/utils.py", line 58, in single_nb_execution + File "/opt/hostedtoolcache/Python/3.8.18/x64/lib/python3.8/site-packages/nbclient/client.py", line 778, in _async_poll_for_reply + msg = await ensure_async(self.kc.shell_channel.get_msg(timeout=new_timeout)) + File "/opt/hostedtoolcache/Python/3.8.18/x64/lib/python3.8/site-packages/jupyter_core/utils/__init__.py", line 182, in ensure_async + result = await obj + File "/opt/hostedtoolcache/Python/3.8.18/x64/lib/python3.8/site-packages/jupyter_client/channels.py", line 315, in get_msg + raise Empty +_queue.Empty + +During handling of the above exception, another exception occurred: + +Traceback (most recent call last): + File "/opt/hostedtoolcache/Python/3.8.18/x64/lib/python3.8/site-packages/jupyter_cache/executors/utils.py", line 58, in single_nb_execution executenb( - File "/opt/hostedtoolcache/Python/3.8.17/x64/lib/python3.8/site-packages/nbclient/client.py", line 1305, in execute + File "/opt/hostedtoolcache/Python/3.8.18/x64/lib/python3.8/site-packages/nbclient/client.py", line 1305, in execute return NotebookClient(nb=nb, resources=resources, km=km, **kwargs).execute() - File "/opt/hostedtoolcache/Python/3.8.17/x64/lib/python3.8/site-packages/jupyter_core/utils/__init__.py", line 166, in wrapped + File "/opt/hostedtoolcache/Python/3.8.18/x64/lib/python3.8/site-packages/jupyter_core/utils/__init__.py", line 166, in wrapped return loop.run_until_complete(inner) - File "/opt/hostedtoolcache/Python/3.8.17/x64/lib/python3.8/asyncio/base_events.py", line 616, in run_until_complete + File "/opt/hostedtoolcache/Python/3.8.18/x64/lib/python3.8/asyncio/base_events.py", line 616, in run_until_complete return future.result() - File "/opt/hostedtoolcache/Python/3.8.17/x64/lib/python3.8/site-packages/nbclient/client.py", line 705, in async_execute + File "/opt/hostedtoolcache/Python/3.8.18/x64/lib/python3.8/site-packages/nbclient/client.py", line 705, in async_execute await self.async_execute_cell( - File "/opt/hostedtoolcache/Python/3.8.17/x64/lib/python3.8/site-packages/nbclient/client.py", line 1058, in async_execute_cell - await self._check_raise_for_error(cell, cell_index, exec_reply) - File "/opt/hostedtoolcache/Python/3.8.17/x64/lib/python3.8/site-packages/nbclient/client.py", line 914, in _check_raise_for_error - raise CellExecutionError.from_cell_and_msg(cell, exec_reply_content) -nbclient.exceptions.CellExecutionError: An error occurred while executing the following cell: ------------------- -path = "./sf-model-lib/diffusion" -path_train = os.path.join(path, 'g_train_original.hdf5') -path_weights = os.path.join(path, 'model_weights.h5') -g_train = h5py.File(path_train, 'r')['g_train'][()] -model = ps.networks.create_model() -model.load_weights(path_weights) ------------------- - - ---------------------------------------------------------------------------- -ModuleNotFoundError Traceback (most recent call last) -Cell In[4], line 5 - 3 path_weights = os.path.join(path, 'model_weights.h5') - 4 g_train = h5py.File(path_train, 'r')['g_train'][()] -----> 5 model = ps.networks.create_model() - 6 model.load_weights(path_weights) - -File ~/work/porespy/porespy/porespy/networks/_size_factors.py:612, in create_model() - 604 def create_model(): - 605  ''' - 606  Returns - 607  ------- - (...) - 610 - 611  ''' ---> 612 from tensorflow.keras.optimizers import Adam - 613 model = _resnet3d() - 614 model.compile(loss='mse', optimizer=Adam(lr=1e-4), metrics=['mse']) - -File /opt/hostedtoolcache/Python/3.8.17/x64/lib/python3.8/site-packages/tensorflow/__init__.py:38 - 35 import sys as _sys - 36 import typing as _typing ----> 38 from tensorflow.python.tools import module_util as _module_util - 39 from tensorflow.python.util.lazy_loader import LazyLoader as _LazyLoader - 41 # Make sure code inside the TensorFlow codebase can use tf2.enabled() at import. - -ModuleNotFoundError: No module named 'tensorflow.python' + File "/opt/hostedtoolcache/Python/3.8.18/x64/lib/python3.8/site-packages/nbclient/client.py", line 1001, in async_execute_cell + exec_reply = await self.task_poll_for_reply + File "/opt/hostedtoolcache/Python/3.8.18/x64/lib/python3.8/site-packages/nbclient/client.py", line 802, in _async_poll_for_reply + error_on_timeout_execute_reply = await self._async_handle_timeout(timeout, cell) + File "/opt/hostedtoolcache/Python/3.8.18/x64/lib/python3.8/site-packages/nbclient/client.py", line 852, in _async_handle_timeout + raise CellTimeoutError.error_from_timeout_and_cell( +nbclient.exceptions.CellTimeoutError: A cell timed out while it was being executed, after 30 seconds. +The message was: Cell execution timed out. +Here is a preview of the cell contents: +------------------- +['try:', ' import tensorflow as tf', 'except ImportError:', ' !pip install tensorflow', ''] +... +['', 'import os', '', 'if not os.path.exists("sf-model-lib"):', ' !git clone https://github.com/PMEAL/sf-model-lib'] +------------------- diff --git a/reports/examples/networks/tutorials/predicting_diffusive_size_factors_rock_sample.err.log b/reports/examples/networks/tutorials/predicting_diffusive_size_factors_rock_sample.err.log index 66888b986..d61026111 100644 --- a/reports/examples/networks/tutorials/predicting_diffusive_size_factors_rock_sample.err.log +++ b/reports/examples/networks/tutorials/predicting_diffusive_size_factors_rock_sample.err.log @@ -1,17 +1,17 @@ Traceback (most recent call last): - File "/opt/hostedtoolcache/Python/3.8.17/x64/lib/python3.8/site-packages/jupyter_cache/executors/utils.py", line 58, in single_nb_execution + File "/opt/hostedtoolcache/Python/3.8.18/x64/lib/python3.8/site-packages/jupyter_cache/executors/utils.py", line 58, in single_nb_execution executenb( - File "/opt/hostedtoolcache/Python/3.8.17/x64/lib/python3.8/site-packages/nbclient/client.py", line 1305, in execute + File "/opt/hostedtoolcache/Python/3.8.18/x64/lib/python3.8/site-packages/nbclient/client.py", line 1305, in execute return NotebookClient(nb=nb, resources=resources, km=km, **kwargs).execute() - File "/opt/hostedtoolcache/Python/3.8.17/x64/lib/python3.8/site-packages/jupyter_core/utils/__init__.py", line 166, in wrapped + File "/opt/hostedtoolcache/Python/3.8.18/x64/lib/python3.8/site-packages/jupyter_core/utils/__init__.py", line 166, in wrapped return loop.run_until_complete(inner) - File "/opt/hostedtoolcache/Python/3.8.17/x64/lib/python3.8/asyncio/base_events.py", line 616, in run_until_complete + File "/opt/hostedtoolcache/Python/3.8.18/x64/lib/python3.8/asyncio/base_events.py", line 616, in run_until_complete return future.result() - File "/opt/hostedtoolcache/Python/3.8.17/x64/lib/python3.8/site-packages/nbclient/client.py", line 705, in async_execute + File "/opt/hostedtoolcache/Python/3.8.18/x64/lib/python3.8/site-packages/nbclient/client.py", line 705, in async_execute await self.async_execute_cell( - File "/opt/hostedtoolcache/Python/3.8.17/x64/lib/python3.8/site-packages/nbclient/client.py", line 1058, in async_execute_cell + File "/opt/hostedtoolcache/Python/3.8.18/x64/lib/python3.8/site-packages/nbclient/client.py", line 1058, in async_execute_cell await self._check_raise_for_error(cell, cell_index, exec_reply) - File "/opt/hostedtoolcache/Python/3.8.17/x64/lib/python3.8/site-packages/nbclient/client.py", line 914, in _check_raise_for_error + File "/opt/hostedtoolcache/Python/3.8.18/x64/lib/python3.8/site-packages/nbclient/client.py", line 914, in _check_raise_for_error raise CellExecutionError.from_cell_and_msg(cell, exec_reply_content) nbclient.exceptions.CellExecutionError: An error occurred while executing the following cell: ------------------ diff --git a/reports/examples/networks/tutorials/using_diffusive_size_factor_AI_with_snow.err.log b/reports/examples/networks/tutorials/using_diffusive_size_factor_AI_with_snow.err.log index bc0aa3fb0..e02514ce4 100644 --- a/reports/examples/networks/tutorials/using_diffusive_size_factor_AI_with_snow.err.log +++ b/reports/examples/networks/tutorials/using_diffusive_size_factor_AI_with_snow.err.log @@ -1,30 +1,30 @@ Traceback (most recent call last): - File "/opt/hostedtoolcache/Python/3.8.17/x64/lib/python3.8/site-packages/nbclient/client.py", line 778, in _async_poll_for_reply + File "/opt/hostedtoolcache/Python/3.8.18/x64/lib/python3.8/site-packages/nbclient/client.py", line 778, in _async_poll_for_reply msg = await ensure_async(self.kc.shell_channel.get_msg(timeout=new_timeout)) - File "/opt/hostedtoolcache/Python/3.8.17/x64/lib/python3.8/site-packages/jupyter_core/utils/__init__.py", line 182, in ensure_async + File "/opt/hostedtoolcache/Python/3.8.18/x64/lib/python3.8/site-packages/jupyter_core/utils/__init__.py", line 182, in ensure_async result = await obj - File "/opt/hostedtoolcache/Python/3.8.17/x64/lib/python3.8/site-packages/jupyter_client/channels.py", line 315, in get_msg + File "/opt/hostedtoolcache/Python/3.8.18/x64/lib/python3.8/site-packages/jupyter_client/channels.py", line 315, in get_msg raise Empty _queue.Empty During handling of the above exception, another exception occurred: Traceback (most recent call last): - File "/opt/hostedtoolcache/Python/3.8.17/x64/lib/python3.8/site-packages/jupyter_cache/executors/utils.py", line 58, in single_nb_execution + File "/opt/hostedtoolcache/Python/3.8.18/x64/lib/python3.8/site-packages/jupyter_cache/executors/utils.py", line 58, in single_nb_execution executenb( - File "/opt/hostedtoolcache/Python/3.8.17/x64/lib/python3.8/site-packages/nbclient/client.py", line 1305, in execute + File "/opt/hostedtoolcache/Python/3.8.18/x64/lib/python3.8/site-packages/nbclient/client.py", line 1305, in execute return NotebookClient(nb=nb, resources=resources, km=km, **kwargs).execute() - File "/opt/hostedtoolcache/Python/3.8.17/x64/lib/python3.8/site-packages/jupyter_core/utils/__init__.py", line 166, in wrapped + File "/opt/hostedtoolcache/Python/3.8.18/x64/lib/python3.8/site-packages/jupyter_core/utils/__init__.py", line 166, in wrapped return loop.run_until_complete(inner) - File "/opt/hostedtoolcache/Python/3.8.17/x64/lib/python3.8/asyncio/base_events.py", line 616, in run_until_complete + File "/opt/hostedtoolcache/Python/3.8.18/x64/lib/python3.8/asyncio/base_events.py", line 616, in run_until_complete return future.result() - File "/opt/hostedtoolcache/Python/3.8.17/x64/lib/python3.8/site-packages/nbclient/client.py", line 705, in async_execute + File "/opt/hostedtoolcache/Python/3.8.18/x64/lib/python3.8/site-packages/nbclient/client.py", line 705, in async_execute await self.async_execute_cell( - File "/opt/hostedtoolcache/Python/3.8.17/x64/lib/python3.8/site-packages/nbclient/client.py", line 1001, in async_execute_cell + File "/opt/hostedtoolcache/Python/3.8.18/x64/lib/python3.8/site-packages/nbclient/client.py", line 1001, in async_execute_cell exec_reply = await self.task_poll_for_reply - File "/opt/hostedtoolcache/Python/3.8.17/x64/lib/python3.8/site-packages/nbclient/client.py", line 802, in _async_poll_for_reply + File "/opt/hostedtoolcache/Python/3.8.18/x64/lib/python3.8/site-packages/nbclient/client.py", line 802, in _async_poll_for_reply error_on_timeout_execute_reply = await self._async_handle_timeout(timeout, cell) - File "/opt/hostedtoolcache/Python/3.8.17/x64/lib/python3.8/site-packages/nbclient/client.py", line 852, in _async_handle_timeout + File "/opt/hostedtoolcache/Python/3.8.18/x64/lib/python3.8/site-packages/nbclient/client.py", line 852, in _async_handle_timeout raise CellTimeoutError.error_from_timeout_and_cell( nbclient.exceptions.CellTimeoutError: A cell timed out while it was being executed, after 30 seconds. 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195, 200, 201, 208, 231, 232, 238, 243, 253, 255, 256, 258, 263, 269, 279, 288, 322], "lot": [7, 32, 62, 125, 129], "help": [7, 48, 62, 90, 92, 113, 121, 123, 124, 137, 239, 241, 248, 253, 257], "get": [7, 40, 58, 59, 62, 63, 64, 70, 80, 86, 90, 92, 114, 125, 129, 168, 185, 213, 221, 222, 223, 225, 226, 235, 236, 238, 249], "start": [7, 25, 26, 50, 58, 59, 69, 78, 79, 84, 86, 87, 91, 92, 108, 111, 112, 113, 121, 124, 125, 129, 130, 131, 168, 185, 191, 201, 219, 240, 259, 262, 266, 275, 287, 288], "ar": [7, 21, 22, 23, 26, 28, 29, 30, 32, 33, 34, 36, 37, 38, 39, 40, 42, 44, 45, 46, 47, 48, 51, 52, 53, 54, 55, 56, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 70, 72, 75, 76, 80, 81, 82, 83, 84, 85, 86, 88, 90, 91, 92, 96, 98, 103, 106, 108, 110, 111, 112, 113, 114, 115, 117, 120, 121, 122, 123, 124, 126, 127, 129, 130, 131, 132, 133, 135, 140, 152, 154, 155, 156, 157, 158, 163, 166, 167, 168, 169, 170, 171, 172, 173, 174, 175, 176, 177, 179, 182, 185, 188, 189, 191, 192, 194, 196, 197, 198, 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130, 132, 133, 138, 167, 188, 192, 215, 221, 240, 248, 251, 252, 257, 268, 276, 281, 297, 310], "poros": [7, 8, 9, 10, 21, 22, 26, 28, 31, 32, 34, 39, 41, 44, 45, 46, 47, 48, 49, 51, 52, 53, 55, 56, 57, 60, 61, 65, 68, 70, 84, 85, 87, 91, 92, 95, 99, 100, 101, 107, 108, 111, 113, 115, 116, 117, 118, 119, 120, 121, 123, 124, 125, 126, 127, 129, 130, 131, 132, 133, 138, 153, 156, 159, 165, 174, 200, 210, 213, 220, 221, 231, 247, 250, 258, 263, 271], "profil": [7, 8, 10, 52, 91, 99, 107, 108, 240, 250, 258, 259], "along": [7, 8, 10, 22, 26, 35, 37, 58, 62, 83, 89, 92, 99, 108, 111, 120, 121, 131, 140, 155, 156, 158, 159, 163, 165, 169, 173, 182, 189, 190, 211, 214, 218, 223, 241, 244, 250, 259, 271, 276, 280, 281, 288, 300, 304, 306, 307, 312], "each": [7, 8, 10, 21, 22, 23, 24, 25, 32, 33, 34, 35, 36, 37, 38, 40, 43, 50, 58, 59, 61, 62, 66, 70, 73, 78, 82, 83, 87, 88, 89, 90, 94, 96, 97, 102, 103, 104, 105, 106, 111, 114, 118, 120, 121, 122, 124, 125, 127, 129, 130, 132, 133, 157, 158, 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300, 301, 303, 304, 306, 307, 310, 312], "us": [7, 8, 10, 11, 13, 14, 15, 24, 25, 27, 28, 29, 31, 32, 33, 36, 37, 40, 44, 45, 46, 47, 48, 50, 51, 52, 54, 56, 58, 59, 60, 61, 62, 66, 67, 68, 69, 70, 74, 75, 76, 79, 82, 85, 86, 88, 89, 90, 93, 94, 95, 97, 100, 103, 104, 105, 106, 107, 109, 110, 111, 112, 115, 116, 117, 118, 120, 121, 122, 123, 124, 125, 127, 129, 130, 132, 135, 137, 138, 140, 154, 156, 157, 158, 159, 160, 161, 162, 163, 165, 166, 167, 168, 171, 172, 174, 178, 179, 180, 181, 183, 184, 185, 188, 189, 190, 192, 194, 195, 198, 199, 200, 201, 202, 206, 207, 208, 210, 211, 212, 213, 214, 216, 217, 218, 220, 221, 222, 223, 224, 225, 226, 228, 232, 233, 235, 236, 237, 238, 239, 240, 241, 243, 244, 245, 246, 248, 249, 253, 254, 255, 256, 257, 258, 259, 260, 261, 262, 268, 269, 270, 271, 272, 273, 274, 275, 276, 279, 280, 282, 288, 289, 290, 296, 297, 299, 300, 301, 302, 303, 304, 305, 306, 307, 309, 311, 312, 322], "regionprops_3d": [7, 8, 9, 10, 100, 101, 251, 252], "analyz": 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284], "randomize_color": [7, 16, 17, 50, 60, 61, 114, 121, 124], "recombin": [7, 16, 17, 115, 126], "subdivid": [7, 16, 17, 297], "unpad": [7, 16, 17, 278], "tif": [7, 18, 20, 62, 124], "paraview": [7, 18, 20, 63, 124, 168, 229, 230, 234, 235, 236, 273], "bar": [7, 18, 19, 58, 59, 84, 90, 92, 97, 102, 111, 239, 241, 248, 253, 260], "imshow": [7, 18, 19, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 96, 97, 98, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 118, 119, 120, 121, 122, 124, 125, 126, 127, 129, 130, 131, 132, 133, 134, 135, 137, 138, 139, 140, 141, 142, 143, 145, 148, 149, 152, 153, 156, 157, 158, 159, 160, 161, 164, 165, 166, 304, 306, 307, 311, 312], "prep_for_imshow": [7, 18, 19], 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158, 166, 172, 175, 176, 178, 179, 181, 185, 186, 189, 192, 193, 196, 197, 198, 199, 200, 201, 202, 203, 205, 207, 210, 212, 213, 214, 215, 216, 217, 218, 220, 221, 222, 223, 224, 225, 226, 228, 230, 231, 232, 240, 242, 244, 254, 255, 259, 263, 268, 269, 270, 271, 276, 279, 286, 287, 289, 290, 303, 304, 306], "separ": [22, 61, 62, 121, 122, 123, 129, 169, 170, 201, 240, 260], "between": [22, 23, 46, 55, 59, 61, 63, 66, 67, 72, 73, 74, 76, 77, 79, 91, 103, 110, 111, 120, 121, 123, 126, 129, 130, 131, 132, 158, 164, 169, 192, 198, 199, 201, 202, 207, 212, 213, 216, 218, 219, 222, 223, 225, 226, 237, 240, 253, 254, 255, 260, 265, 268, 269, 270, 306, 311], "default": [22, 23, 26, 27, 29, 31, 32, 34, 36, 37, 38, 39, 40, 44, 45, 46, 47, 48, 58, 59, 63, 64, 66, 67, 68, 69, 70, 72, 74, 75, 76, 77, 79, 81, 83, 88, 89, 90, 91, 92, 96, 97, 99, 102, 103, 104, 105, 107, 108, 111, 116, 117, 118, 120, 121, 124, 127, 140, 143, 149, 154, 155, 156, 157, 158, 159, 163, 164, 165, 166, 168, 169, 170, 171, 172, 173, 175, 176, 178, 179, 182, 185, 188, 189, 192, 193, 198, 199, 200, 201, 205, 208, 209, 210, 211, 212, 213, 214, 215, 216, 217, 218, 220, 221, 222, 223, 224, 225, 226, 227, 228, 234, 237, 239, 241, 247, 248, 253, 254, 255, 256, 258, 260, 261, 262, 264, 265, 267, 268, 269, 270, 276, 280, 281, 285, 287, 289, 290, 292, 293, 295, 296, 302, 304, 306, 311], "decreas": [22, 59, 130, 133, 169, 197], "mean": [22, 31, 33, 36, 37, 53, 61, 77, 82, 86, 87, 91, 98, 99, 106, 120, 121, 129, 132, 133, 156, 163, 168, 169, 178, 180, 181, 187, 189, 197, 198, 210, 212, 213, 216, 217, 220, 221, 222, 223, 224, 225, 226, 228, 268, 270], "all": [22, 23, 32, 36, 37, 40, 48, 55, 58, 59, 60, 62, 63, 70, 71, 76, 80, 81, 82, 86, 103, 111, 112, 114, 115, 116, 117, 118, 120, 121, 124, 125, 126, 127, 129, 131, 132, 139, 155, 156, 158, 160, 164, 167, 168, 169, 170, 172, 174, 175, 176, 178, 179, 181, 188, 189, 191, 192, 193, 197, 198, 202, 203, 204, 205, 207, 210, 213, 216, 217, 218, 219, 222, 223, 225, 226, 233, 239, 241, 249, 250, 252, 254, 255, 257, 258, 264, 268, 269, 270, 279, 286, 287, 296, 300, 302, 303, 304, 306, 311], "touch": [22, 29, 58, 62, 121, 122, 169, 170, 176], "other": [22, 29, 36, 40, 62, 71, 95, 98, 107, 111, 114, 120, 121, 122, 123, 124, 126, 132, 155, 167, 169, 172, 177, 190, 200, 201, 202, 206, 233, 249, 268, 273, 287, 296, 302, 303], "automat": [22, 121, 124, 169, 170, 178, 193, 200, 248, 260, 269, 302, 303], "set": [22, 24, 36, 40, 47, 58, 61, 62, 64, 69, 70, 76, 77, 78, 79, 81, 83, 85, 87, 111, 112, 117, 119, 120, 121, 122, 124, 125, 129, 130, 131, 132, 154, 155, 156, 158, 169, 178, 179, 185, 188, 189, 192, 194, 202, 206, 210, 215, 224, 225, 226, 235, 236, 253, 268, 270, 275, 276, 287, 300, 302, 303, 304, 306], "argument": [22, 25, 26, 30, 32, 34, 36, 38, 39, 40, 44, 45, 46, 47, 67, 68, 69, 70, 74, 76, 82, 85, 87, 88, 91, 108, 114, 115, 116, 120, 121, 127, 130, 139, 154, 155, 156, 158, 169, 170, 171, 172, 178, 181, 185, 186, 192, 200, 201, 203, 210, 213, 225, 226, 230, 239, 241, 244, 245, 248, 253, 254, 255, 260, 261, 269, 278, 296, 302, 303, 306], "true": [22, 23, 27, 28, 29, 32, 35, 36, 38, 40, 51, 53, 55, 59, 62, 63, 64, 66, 69, 70, 71, 72, 73, 76, 77, 78, 79, 82, 83, 85, 90, 91, 92, 93, 96, 97, 98, 99, 102, 107, 108, 109, 113, 114, 118, 123, 124, 127, 128, 129, 130, 131, 132, 138, 141, 143, 157, 158, 169, 170, 171, 173, 174, 175, 176, 178, 179, 182, 185, 186, 188, 191, 192, 193, 194, 195, 196, 197, 198, 199, 200, 201, 202, 205, 207, 208, 210, 211, 212, 213, 214, 215, 216, 218, 220, 221, 222, 223, 225, 226, 228, 232, 239, 241, 243, 244, 247, 248, 249, 250, 253, 257, 259, 260, 269, 270, 271, 277, 279, 280, 281, 285, 288, 289, 292, 293, 295, 298, 300, 304, 305, 306, 307, 312], "x": [22, 23, 37, 42, 43, 53, 54, 55, 56, 58, 59, 63, 73, 77, 78, 82, 85, 86, 89, 90, 97, 111, 112, 121, 125, 131, 132, 133, 156, 158, 159, 163, 164, 165, 167, 170, 173, 202, 213, 215, 219, 233, 250, 264, 270, 276, 283, 285, 291, 296, 304, 312], "filter": [22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 44, 45, 46, 47, 48, 50, 51, 52, 53, 54, 55, 56, 57, 58, 60, 61, 63, 79, 84, 89, 90, 92, 93, 94, 95, 96, 97, 103, 104, 105, 111, 113, 114, 115, 116, 117, 118, 120, 121, 122, 124, 125, 127, 130, 131, 132, 154, 157, 158, 160, 162, 166, 167, 172, 174, 178, 186, 187, 189, 192, 200, 201, 253, 269, 289, 314, 317], "xx": 22, "3": [22, 23, 25, 26, 27, 29, 31, 33, 34, 36, 37, 38, 39, 40, 41, 45, 46, 48, 49, 51, 53, 57, 59, 62, 63, 64, 65, 66, 67, 68, 70, 71, 72, 75, 77, 78, 79, 80, 81, 82, 83, 85, 86, 87, 88, 89, 90, 92, 96, 97, 100, 101, 102, 104, 106, 110, 113, 114, 115, 116, 119, 121, 122, 123, 124, 125, 126, 127, 128, 132, 133, 138, 140, 141, 145, 149, 153, 155, 156, 159, 163, 165, 168, 170, 192, 202, 212, 213, 227, 232, 233, 261, 264, 269, 275, 278, 280, 281, 284, 287, 294, 295, 296, 305], "8": [22, 28, 29, 35, 37, 39, 53, 58, 59, 60, 62, 63, 64, 66, 67, 68, 70, 71, 72, 74, 76, 77, 78, 79, 82, 83, 85, 86, 87, 89, 104, 105, 110, 111, 113, 114, 115, 119, 121, 122, 123, 124, 125, 126, 129, 132, 133, 135, 137, 138, 139, 140, 141, 145, 148, 152, 153, 159, 164, 165, 168, 172, 174, 175, 176, 205, 224, 287], "set_titl": [22, 23, 24, 25, 26, 27, 28, 31, 33, 34, 35, 44, 45, 46, 47, 50, 52, 53, 54, 55, 56, 57, 60, 61, 67, 70, 72, 74, 75, 78, 79, 80, 83, 85, 87, 90, 91, 92, 97, 102, 104, 108, 113, 126, 133, 135, 140, 145, 153], "drawn": [22, 58, 75, 83, 89, 90, 92, 111, 129, 169, 219, 238, 239], "whether": [22, 26, 51, 53, 62, 70, 157, 166, 169, 170, 204, 225, 226, 228, 283, 292, 293, 295], "remov": [22, 28, 29, 32, 37, 41, 48, 51, 52, 53, 54, 55, 56, 57, 62, 78, 129, 131, 133, 153, 168, 169, 170, 175, 189, 193, 203, 204, 205, 206, 207, 208, 209, 228, 270, 271, 286, 301, 304], "edg": [22, 24, 29, 38, 40, 58, 59, 65, 67, 72, 76, 77, 79, 82, 83, 86, 110, 113, 120, 129, 133, 140, 154, 169, 170, 171, 172, 176, 177, 201, 211, 218, 222, 223, 225, 226, 228, 232, 257, 268, 270, 280, 301, 302], "return": [22, 40, 41, 48, 50, 53, 58, 59, 62, 63, 64, 66, 70, 73, 79, 82, 87, 88, 89, 90, 91, 92, 95, 96, 97, 102, 103, 104, 105, 107, 109, 113, 115, 116, 118, 120, 121, 123, 124, 125, 126, 129, 130, 131, 133, 135, 140, 152, 154, 156, 158, 167, 169, 170, 172, 173, 174, 175, 176, 177, 178, 179, 180, 181, 182, 185, 186, 187, 188, 190, 191, 192, 193, 194, 195, 196, 197, 198, 199, 200, 201, 202, 203, 204, 205, 206, 207, 208, 209, 210, 211, 212, 213, 214, 215, 217, 218, 219, 220, 221, 222, 223, 224, 225, 226, 227, 228, 231, 237, 238, 239, 240, 241, 242, 243, 244, 247, 248, 249, 250, 251, 252, 253, 254, 255, 256, 257, 258, 259, 260, 261, 262, 263, 264, 265, 267, 268, 269, 270, 271, 272, 273, 274, 275, 276, 277, 278, 279, 280, 281, 282, 283, 284, 285, 286, 287, 288, 289, 290, 291, 292, 293, 294, 295, 296, 297, 298, 299, 300, 302, 304, 306, 307, 309, 310, 311, 312, 313, 320], "uniqu": [22, 29, 38, 75, 96, 121, 122, 123, 129, 132, 169, 190, 198, 199, 201, 202, 296], "ly": [22, 122, 169, 241, 253], "same": [22, 36, 40, 55, 62, 64, 65, 68, 69, 70, 82, 85, 86, 111, 113, 120, 121, 122, 130, 131, 133, 140, 158, 169, 172, 174, 176, 177, 179, 180, 181, 185, 186, 188, 189, 191, 192, 193, 194, 195, 196, 197, 198, 199, 203, 206, 211, 215, 216, 223, 237, 251, 252, 257, 260, 261, 264, 265, 270, 279, 280, 285, 286, 287, 288, 296, 297, 301, 306], "otherwis": [22, 137, 169, 216, 217, 244, 247, 269, 270], "three": [23, 62, 96, 112, 133, 164, 170, 269, 281, 311], "seprat": 23, "plu": [23, 82, 114, 257], "y": [23, 37, 58, 73, 82, 86, 121, 125, 131, 132, 133, 156, 158, 164, 170, 202, 215, 219, 269, 285, 291, 296], "z": [23, 37, 82, 86, 133, 140, 155, 156, 164, 170, 189, 202, 213, 214, 215, 219, 235, 236, 285, 291, 296], "label": [23, 29, 30, 40, 44, 46, 47, 62, 85, 89, 93, 96, 98, 100, 101, 103, 104, 105, 106, 107, 109, 112, 113, 114, 115, 116, 118, 120, 121, 122, 123, 124, 125, 126, 129, 132, 133, 138, 166, 169, 170, 177, 179, 180, 181, 195, 200, 201, 202, 203, 206, 207, 211, 231, 233, 239, 243, 247, 249, 255, 256, 257, 260, 261, 263, 264, 265, 266, 268, 269, 275, 277, 280, 286, 296], "resepct": [23, 170], "inspect": [23, 26, 27, 28, 29, 30, 31, 32, 34, 36, 37, 38, 39, 40, 44, 45, 46, 47, 48, 51, 63, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 83, 88, 89, 90, 91, 93, 94, 95, 96, 97, 98, 102, 103, 104, 105, 107, 108, 109, 114, 115, 116, 124, 127, 128, 154, 156, 157, 158, 160, 161, 162, 164], "print": [23, 25, 28, 36, 48, 49, 50, 51, 58, 59, 60, 61, 72, 74, 79, 82, 83, 85, 86, 87, 88, 91, 93, 94, 95, 96, 98, 106, 113, 115, 117, 118, 120, 121, 123, 124, 125, 126, 129, 131, 133, 145, 152, 153, 156, 275, 278, 280, 287, 296, 299, 300], "signatur": [23, 26, 27, 28, 29, 30, 31, 32, 34, 36, 37, 38, 39, 40, 44, 45, 46, 47, 48, 51, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 83, 88, 89, 90, 91, 93, 94, 96, 97, 98, 102, 103, 104, 105, 107, 108, 109, 114, 115, 116, 121, 127, 128, 154, 156, 157, 158, 160, 161, 162, 164, 269], "take": [23, 25, 53, 62, 63, 76, 77, 86, 112, 115, 116, 120, 121, 123, 124, 126, 129, 130, 131, 162, 163, 185, 287, 290, 296, 309], "boolean": [23, 29, 35, 44, 46, 47, 55, 59, 63, 64, 76, 98, 99, 130, 138, 140, 156, 157, 158, 176, 178, 179, 180, 182, 192, 195, 200, 201, 203, 206, 207, 208, 210, 212, 213, 214, 215, 216, 218, 220, 221, 224, 227, 228, 239, 241, 247, 248, 253, 257, 259, 264, 265, 269, 270, 273, 277, 279, 281, 283, 285, 288, 289, 292, 293, 295, 305, 306], "indic": [23, 27, 28, 29, 32, 33, 36, 38, 47, 48, 51, 53, 55, 59, 62, 63, 69, 73, 76, 77, 79, 90, 95, 99, 102, 111, 115, 116, 120, 121, 122, 129, 131, 132, 140, 156, 157, 158, 163, 166, 169, 170, 173, 176, 177, 178, 179, 191, 192, 193, 194, 195, 196, 197, 198, 199, 200, 201, 202, 203, 206, 207, 212, 217, 222, 223, 225, 226, 232, 239, 242, 244, 249, 257, 258, 259, 262, 264, 266, 268, 269, 270, 271, 274, 275, 277, 280, 283, 285, 288, 289, 290, 292, 293, 295, 296, 300, 304, 305, 306], "phase": [23, 27, 28, 29, 32, 38, 49, 51, 54, 62, 79, 84, 85, 91, 92, 95, 96, 103, 104, 105, 107, 108, 109, 110, 111, 113, 115, 116, 117, 118, 122, 123, 124, 125, 126, 129, 130, 131, 132, 133, 156, 157, 173, 176, 177, 188, 190, 191, 192, 196, 197, 198, 199, 201, 202, 207, 222, 223, 231, 234, 240, 241, 244, 247, 248, 249, 259, 260, 263, 265, 266, 268, 269, 270, 271, 307, 312], "interest": [23, 34, 51, 92, 113, 131, 132, 156, 173, 176, 177, 180, 181, 188, 195, 202, 207, 244, 249, 251, 260, 269, 271, 273, 289, 304], "50": [23, 24, 52, 58, 62, 67, 71, 72, 77, 82, 83, 86, 87, 93, 94, 98, 99, 105, 112, 115, 117, 119, 121, 122, 126, 129, 132, 135, 137, 141, 142, 143, 156, 158, 159, 162, 165, 166], "12": [23, 24, 25, 26, 27, 28, 29, 30, 35, 36, 37, 38, 39, 40, 41, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 64, 65, 67, 68, 71, 75, 76, 77, 78, 80, 81, 82, 88, 89, 91, 95, 108, 115, 121, 123, 124, 125, 126, 127, 156, 159, 161, 165], "20": [23, 24, 37, 59, 65, 72, 73, 74, 76, 79, 82, 83, 88, 89, 100, 105, 106, 114, 115, 121, 124, 125, 126, 132, 139, 140, 142, 148, 152, 156, 158, 163, 166, 208, 221], "22": [23, 89, 100, 113, 115, 121, 124, 125, 126, 138], "differ": [23, 27, 31, 36, 46, 58, 59, 61, 63, 66, 70, 86, 87, 92, 96, 102, 111, 112, 116, 120, 121, 123, 124, 129, 130, 131, 132, 154, 160, 166, 172, 188, 190, 195, 213, 225, 226, 270, 296, 302], "integ": [23, 36, 53, 59, 88, 121, 195, 200, 201, 202, 247, 265, 269, 270, 286], "so": [23, 31, 32, 40, 46, 47, 48, 51, 53, 62, 63, 64, 71, 74, 75, 79, 80, 81, 85, 86, 91, 98, 106, 110, 111, 112, 113, 114, 117, 118, 120, 121, 124, 125, 129, 132, 133, 155, 156, 169, 170, 185, 189, 191, 194, 203, 206, 209, 210, 213, 221, 222, 223, 225, 226, 232, 239, 241, 248, 249, 252, 253, 254, 255, 260, 261, 264, 267, 268, 269, 270, 279, 287, 296, 303, 307, 309, 312], "thei": [23, 28, 32, 47, 56, 58, 66, 67, 76, 77, 83, 92, 95, 106, 111, 114, 115, 121, 122, 126, 129, 130, 132, 167, 168, 185, 188, 191, 192, 206, 208, 213, 225, 226, 239, 253, 257, 269, 296, 304], "isol": [23, 28, 29, 47, 57, 113, 120, 175, 176, 181, 194, 205, 209, 268], "threshold": [23, 36, 40, 62, 63, 64, 70, 87, 132, 166, 179, 188, 192, 209, 210, 216, 259, 305], "By": [23, 27, 37, 40, 67, 68, 70, 79, 83, 90, 92, 96, 97, 102, 103, 104, 105, 107, 116, 127, 132, 157, 158, 159, 163, 172, 179, 185, 189, 192, 213], "drown": 23, "orient": [23, 58, 67, 68, 100, 101, 106, 111, 113, 159, 165, 213, 214, 276], "maximum": [23, 34, 36, 52, 57, 66, 70, 74, 76, 77, 80, 113, 120, 121, 127, 156, 175, 176, 177, 178, 180, 187, 191, 197, 198, 199, 200, 201, 205, 220, 222, 223, 225, 226, 240, 260, 264, 268, 269, 279, 304], "number": [23, 25, 32, 36, 37, 38, 40, 44, 46, 47, 48, 49, 50, 58, 61, 62, 64, 67, 70, 74, 75, 76, 77, 78, 79, 80, 81, 83, 85, 86, 88, 89, 90, 92, 96, 97, 102, 103, 105, 107, 108, 110, 114, 118, 121, 124, 127, 130, 133, 158, 163, 172, 178, 188, 189, 190, 191, 192, 193, 194, 197, 198, 199, 201, 202, 208, 210, 211, 212, 213, 216, 218, 220, 221, 222, 223, 224, 225, 226, 227, 228, 231, 232, 237, 238, 239, 241, 247, 248, 253, 254, 256, 257, 258, 259, 260, 261, 263, 269, 275, 277, 280, 287, 300, 305], "adjust": [23, 62, 64, 74, 87, 91, 124, 132, 156, 160, 165, 179, 189, 213, 275, 287, 304, 308], "few": [23, 62, 63, 86, 106, 121, 122, 123, 124, 132, 138, 257, 317], "veri": [23, 45, 46, 62, 63, 75, 84, 87, 98, 106, 121, 129, 132, 140, 163, 213, 235, 236, 309], "need": [23, 28, 31, 51, 53, 62, 63, 85, 86, 91, 95, 106, 108, 110, 113, 115, 116, 121, 123, 125, 126, 129, 130, 137, 138, 163, 168, 172, 188, 213, 258], "c1": 23, "c3": 23, "30": [23, 60, 76, 80, 82, 94, 108, 115, 126, 131, 153, 162], "c2": 23, "pad": [24, 96, 114, 121, 122, 139, 153, 171, 172, 261, 269, 275, 279, 301], "befor": [24, 48, 54, 56, 62, 83, 86, 123, 124, 127, 129, 171, 182, 192, 206, 239, 241, 248, 253], "edt": [24, 31, 33, 34, 35, 42, 44, 45, 46, 47, 52, 54, 56, 102, 114, 118, 120, 121, 122, 129, 130, 132, 156, 253], "zero": [24, 59, 63, 71, 73, 92, 103, 104, 105, 120, 140, 149, 169, 177, 232, 254, 255, 268, 296], "300": [24, 59, 63, 66, 79, 87, 112, 124, 129], "volume_fract": [24, 59, 149, 225, 226], "figur": [24, 25, 33, 42, 43, 49, 50, 52, 54, 55, 56, 57, 62, 65, 68, 69, 80, 115, 119, 121, 122, 123, 125, 132, 134, 160, 302, 306, 310], "tmp": [24, 38, 59, 79, 84, 106, 121, 127, 132, 149], "ipykernel_2495": 24, "1290140162": 24, "py": [24, 38, 53, 59, 62, 63, 79, 84, 91, 106, 115, 119, 121, 122, 125, 126, 127, 131, 132, 133, 149], "deprecationwarn": [24, 38, 59, 79, 84, 106, 121, 127, 132, 149], "call": [24, 32, 33, 38, 41, 53, 58, 59, 62, 63, 72, 79, 82, 84, 94, 103, 104, 106, 113, 115, 121, 123, 124, 127, 129, 130, 132, 149, 168, 173, 180, 185, 210, 212, 213, 216, 220, 221, 222, 223, 224, 225, 226, 228, 242, 287], "deprec": [24, 38, 59, 79, 84, 106, 121, 126, 127, 132, 149, 245, 246], "staticmethod": [24, 38, 59, 79, 84, 106, 121, 127, 132, 149], "renam": [24, 38, 59, 79, 84, 106, 121, 149], "random_spher": [24, 38, 59, 62, 79, 84, 106, 121], "futur": [24, 38, 59, 79, 84, 106, 121, 127, 132], "version": [24, 38, 48, 59, 61, 62, 79, 80, 81, 84, 106, 111, 113, 118, 121, 127, 132, 175, 205, 257, 269, 282, 291, 320], "good": [24, 63, 121, 122, 213, 260], "case": [24, 40, 53, 62, 71, 76, 79, 82, 86, 95, 121, 122, 171, 172, 182, 195, 214, 217, 225, 226, 239, 251, 257, 301, 303], "skeletonize_3d": [24, 41, 171, 257, 301], "ha": [24, 32, 48, 62, 63, 72, 79, 80, 81, 85, 86, 87, 96, 98, 106, 110, 113, 119, 120, 121, 122, 125, 129, 130, 132, 137, 138, 139, 148, 149, 179, 183, 184, 185, 194, 200, 201, 213, 216, 222, 223, 225, 226, 237, 268, 270], "artifact": [24, 30, 59, 121, 124, 156, 172, 201, 300, 304], "reduc": [24, 48, 120, 121, 124, 130, 160, 202, 235, 236, 253], "pre": [24, 48, 122, 259], "morphologi": [24, 25, 27, 31, 41, 60, 96, 103, 104, 130, 171, 174, 210, 301], "amount": [24, 67, 79, 115, 121, 139, 164, 165, 171, 172, 177, 202, 204, 213, 218, 222, 223, 225, 226, 261, 279, 297, 300, 301, 311, 312], "x1": [24, 25, 33, 50, 53, 57, 73, 219], "x2": [24, 25, 33, 50, 53, 57], "100": [24, 28, 31, 32, 51, 57, 58, 62, 64, 67, 72, 74, 76, 77, 80, 81, 83, 86, 89, 90, 92, 97, 98, 100, 101, 102, 107, 109, 115, 117, 118, 119, 120, 121, 123, 124, 129, 132, 133, 135, 137, 139, 141, 142, 143, 149, 153, 155, 157, 174, 225, 226, 260], "": [24, 25, 27, 32, 37, 45, 46, 58, 59, 62, 63, 64, 69, 70, 72, 74, 79, 82, 84, 85, 86, 87, 90, 91, 92, 94, 96, 97, 98, 99, 102, 103, 104, 105, 106, 107, 110, 111, 113, 115, 116, 119, 120, 121, 122, 123, 124, 126, 129, 130, 131, 132, 138, 148, 152, 153, 154, 155, 156, 157, 158, 160, 162, 166, 167, 180, 181, 196, 197, 198, 199, 201, 210, 212, 213, 214, 215, 220, 221, 224, 225, 226, 228, 232, 235, 236, 239, 241, 249, 251, 253, 257, 258, 259, 266, 269, 275, 279, 286, 288, 296, 300, 302, 303, 305, 307, 308, 312], "morpholog": [24, 27, 36, 40, 130, 174, 188, 292, 293], "oper": [24, 25, 27, 33, 34, 36, 40, 50, 117, 121, 126, 132, 172, 174, 182, 292, 293, 300], "binary_open": [24, 59, 174], "x3": [24, 33, 53, 57], "footprint": [24, 121, 172], "tool": [24, 50, 51, 53, 59, 60, 61, 63, 79, 94, 114, 115, 121, 124, 129, 132, 135, 139, 140, 141, 145, 148, 162, 167, 170, 192, 202, 275, 278, 280, 287, 296, 300], "ps_disk": [24, 59, 79, 121, 148], "15": [24, 26, 27, 36, 37, 41, 48, 51, 59, 62, 65, 66, 68, 79, 89, 101, 114, 115, 121, 124, 125, 126, 133, 158], "x4": [24, 53], "With": [24, 86, 111, 113, 133], "place": [24, 59, 69, 71, 86, 171, 180, 211, 221, 280], "almost": [24, 107, 121, 132, 172], "alwai": [24, 25, 67, 77, 86, 132, 172, 174, 270], "mai": [24, 47, 48, 53, 74, 76, 121, 122, 123, 132, 154, 174, 177, 178, 194, 213, 218, 225, 226, 232, 257, 297, 302], "distanc": [24, 26, 30, 31, 33, 34, 35, 36, 37, 40, 48, 50, 52, 54, 56, 60, 76, 91, 92, 102, 108, 109, 111, 112, 113, 120, 121, 124, 129, 130, 133, 159, 172, 173, 177, 178, 187, 188, 189, 192, 194, 200, 201, 206, 208, 212, 213, 222, 232, 233, 241, 253, 257, 260, 268, 279, 287, 288], "transform": [24, 26, 27, 31, 33, 34, 35, 36, 40, 48, 50, 52, 54, 56, 60, 76, 102, 109, 111, 113, 115, 120, 121, 124, 126, 129, 130, 133, 172, 177, 178, 187, 188, 192, 194, 200, 201, 206, 208, 222, 232, 233, 253, 257, 260, 268, 279], "x5": 24, "10": [24, 27, 29, 34, 37, 50, 52, 57, 59, 60, 61, 62, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 79, 82, 83, 84, 85, 86, 87, 88, 89, 90, 92, 93, 94, 96, 97, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 113, 114, 115, 116, 117, 119, 121, 122, 123, 124, 125, 126, 130, 131, 133, 140, 145, 153, 154, 155, 156, 157, 158, 160, 162, 164, 166, 167, 220, 221, 237, 239, 241, 248, 253, 259, 305, 311], "x6": 24, "perform": [25, 27, 33, 36, 40, 50, 61, 76, 90, 91, 92, 97, 102, 108, 110, 118, 120, 122, 126, 129, 130, 167, 172, 174, 188, 192, 201, 202, 207, 232, 239, 241, 248, 253, 268, 269, 300, 322], "specfi": [25, 172], "one": [25, 37, 48, 61, 62, 71, 84, 86, 111, 116, 120, 121, 122, 123, 124, 126, 129, 130, 132, 133, 158, 172, 187, 189, 190, 213, 238, 254, 255, 257, 268, 269, 281, 286, 306], "chunk": [25, 36, 61, 115, 121, 126, 133, 172, 192, 202, 297], "time": [25, 37, 41, 50, 58, 61, 81, 85, 86, 115, 120, 123, 129, 133, 160, 172, 178, 179, 188, 192, 193, 200, 202, 210, 213, 215, 224, 227, 258], "save": [25, 50, 61, 115, 123, 126, 133, 157, 166, 172, 200, 305], "memori": [25, 50, 61, 172, 202, 300], "disk": [25, 27, 29, 31, 68, 96, 103, 104, 168, 174, 221, 225, 226, 254, 255, 293], "dilat": [25, 27, 36, 40, 59, 74, 79, 120, 174, 187, 188, 192, 228], "binary_dil": [25, 60, 172, 174], "structur": [25, 27, 29, 31, 51, 53, 59, 84, 87, 103, 104, 115, 126, 172, 174, 175, 178, 200, 201, 203, 205, 207, 216, 254, 255, 269, 289, 292, 293, 294, 295], "element": [25, 27, 29, 31, 36, 51, 59, 71, 89, 103, 104, 105, 110, 172, 174, 178, 200, 201, 207, 217, 237, 238, 242, 247, 254, 255, 264, 269, 281, 289, 292, 293, 294, 295], "divid": [25, 36, 50, 61, 78, 81, 98, 121, 130, 172, 178, 188, 192, 202, 210, 221, 224, 235, 236, 249, 300], "faster": [25, 40, 50, 85, 120, 124, 174, 178, 268, 269, 305], "input": [25, 27, 29, 35, 37, 74, 82, 89, 90, 92, 93, 94, 96, 97, 102, 103, 104, 105, 107, 109, 111, 121, 123, 124, 131, 157, 158, 161, 164, 172, 204, 208, 213, 225, 226, 230, 248, 296], "paus": [25, 50], "stop": [25, 50, 74, 80, 127, 231, 263, 275, 305], "second": [25, 50, 84, 86, 117, 123, 131, 157, 188, 192, 305], "fix": [25, 50, 54, 56, 62, 110], "fontdict": [25, 50, 53, 54, 55, 56, 57], "fontsiz": [25, 50, 53, 54, 55, 56, 57], "18": [25, 33, 50, 53, 54, 55, 56, 57, 71, 89, 100, 115, 121, 124, 125, 126, 133], "018918275833129883": 25, "027689456939697266": 25, "variant": [26, 185], "standard": [26, 37, 120, 121, 130, 153, 174, 180, 189, 200, 201, 221, 268, 269], "where": [26, 37, 38, 53, 58, 59, 71, 76, 82, 87, 95, 96, 97, 104, 105, 107, 108, 110, 113, 120, 121, 129, 130, 131, 132, 133, 140, 156, 157, 158, 189, 192, 201, 203, 210, 213, 215, 217, 218, 220, 221, 222, 223, 228, 229, 232, 234, 249, 253, 256, 257, 266, 268, 270, 275, 277, 279, 280, 281, 288, 291, 296], "comput": [26, 34, 36, 38, 39, 40, 50, 53, 61, 62, 70, 88, 98, 99, 108, 111, 120, 121, 123, 129, 130, 132, 156, 172, 181, 188, 192, 195, 200, 201, 222, 223, 225, 226, 239, 240, 243, 244, 250, 251, 252, 253, 256, 259, 268, 269, 271], "give": [26, 59, 70, 89, 90, 108, 123, 130, 140, 158, 211, 216, 218, 238, 239, 253, 280, 305], "rather": [26, 63, 85, 120, 121, 122, 130, 185, 225, 226, 249], "than": [26, 30, 36, 40, 48, 58, 59, 62, 68, 70, 72, 85, 90, 113, 117, 121, 122, 124, 126, 130, 132, 135, 174, 177, 178, 185, 188, 190, 191, 192, 197, 198, 204, 206, 208, 209, 225, 226, 239, 241, 248, 249, 253, 257, 260, 287, 305, 306], "radial": [26, 102, 241, 253], "both": [26, 32, 36, 38, 40, 44, 46, 47, 51, 52, 53, 55, 64, 86, 115, 116, 120, 124, 125, 126, 129, 130, 132, 140, 173, 178, 188, 191, 204, 213, 217, 218, 225, 226, 237, 239, 261, 269, 296], "should": [26, 31, 36, 37, 40, 58, 68, 69, 75, 76, 77, 86, 108, 117, 121, 122, 123, 124, 129, 135, 153, 156, 158, 168, 171, 172, 173, 186, 189, 191, 192, 193, 197, 198, 203, 214, 215, 217, 219, 221, 222, 223, 225, 226, 228, 239, 241, 248, 253, 259, 260, 269, 270, 285, 288, 292, 293, 295, 296, 301, 305, 306], "7": [26, 31, 32, 48, 52, 62, 71, 78, 85, 86, 87, 89, 100, 101, 115, 116, 117, 118, 120, 121, 123, 124, 125, 126, 127, 130, 133, 134, 135, 143, 145, 158, 159, 165], "dt": [26, 33, 34, 35, 36, 40, 42, 48, 49, 50, 52, 59, 60, 106, 113, 114, 121, 122, 124, 126, 129, 130, 132, 156, 177, 178, 188, 192, 200, 201, 202, 206, 208, 253], "f": [26, 31, 35, 45, 46, 47, 61, 62, 63, 67, 70, 72, 74, 75, 79, 80, 83, 85, 87, 110, 113, 115, 123, 126, 131, 145, 206, 224, 253], "comptut": 26, "end": [26, 59, 69, 73, 111, 112, 114, 117, 121, 133, 182, 193, 213, 219, 240, 261, 264, 269, 279, 284], "5": [26, 27, 28, 29, 31, 34, 36, 37, 38, 40, 41, 44, 45, 46, 47, 48, 49, 50, 51, 53, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 67, 68, 70, 71, 74, 75, 76, 77, 79, 80, 81, 82, 84, 85, 86, 87, 88, 89, 90, 91, 94, 95, 98, 99, 100, 101, 106, 108, 110, 112, 113, 114, 115, 116, 120, 121, 122, 123, 124, 125, 126, 129, 131, 132, 133, 135, 140, 145, 149, 154, 157, 158, 161, 163, 174, 189, 210, 216, 221, 224, 227, 254, 287, 296], "forward": [26, 92, 111, 112, 173], "revers": [26, 32, 173, 182, 265], "eros": [27, 36, 40, 59, 96, 174, 187, 192], "close": [27, 62, 76, 85, 87, 148, 174, 187, 206, 213, 222, 305], "fast": [27, 62, 120, 268, 269, 288], "fourier": [27, 109, 260], "convolut": [27, 103, 104, 289], "method": [27, 29, 36, 40, 50, 54, 56, 70, 85, 88, 89, 90, 92, 93, 94, 95, 96, 97, 102, 103, 104, 105, 107, 115, 116, 120, 123, 128, 130, 131, 132, 133, 154, 157, 158, 160, 161, 164, 166, 174, 182, 185, 188, 192, 220, 231, 232, 237, 256, 257, 259, 262, 263, 268, 269, 279, 288], "random": [27, 28, 29, 31, 32, 34, 35, 37, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 55, 60, 62, 64, 66, 67, 70, 71, 74, 75, 76, 77, 79, 85, 87, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 100, 101, 102, 103, 104, 105, 107, 108, 109, 111, 113, 115, 116, 117, 118, 119, 120, 121, 124, 125, 126, 129, 130, 131, 132, 133, 135, 138, 139, 140, 145, 148, 152, 154, 157, 158, 160, 162, 166, 210, 212, 213, 216, 220, 221, 222, 223, 224, 225, 226, 228, 230, 239, 241, 253, 258, 296], "seed": [27, 28, 29, 31, 32, 34, 35, 37, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 53, 55, 60, 61, 64, 66, 67, 74, 75, 76, 79, 83, 85, 87, 89, 90, 91, 93, 94, 95, 96, 97, 98, 100, 101, 102, 103, 104, 105, 107, 108, 109, 113, 115, 116, 117, 118, 119, 120, 121, 124, 125, 126, 129, 131, 132, 133, 135, 138, 154, 157, 158, 160, 162, 166, 210, 212, 213, 216, 220, 221, 222, 223, 224, 225, 226, 228, 296], "note": [27, 31, 40, 48, 53, 58, 59, 62, 63, 66, 68, 72, 74, 79, 83, 84, 91, 94, 95, 96, 97, 102, 103, 104, 105, 106, 112, 113, 115, 116, 120, 121, 122, 123, 125, 126, 129, 130, 132, 154, 158, 160, 161, 164, 166, 170, 171, 172, 174, 176, 178, 181, 182, 188, 189, 191, 192, 194, 195, 197, 198, 200, 201, 204, 206, 207, 210, 213, 216, 217, 218, 220, 225, 226, 229, 231, 232, 233, 234, 235, 236, 238, 239, 240, 241, 242, 244, 245, 248, 249, 253, 254, 255, 257, 258, 260, 263, 266, 267, 268, 270, 279, 280, 284, 288, 296, 300, 301, 304, 305, 309], "strucur": 27, "must": [27, 28, 31, 58, 59, 63, 67, 71, 75, 81, 94, 95, 97, 103, 113, 115, 118, 121, 122, 123, 126, 129, 130, 132, 154, 155, 172, 174, 182, 201, 203, 206, 222, 223, 225, 226, 232, 300], "respect": [27, 29, 50, 52, 53, 55, 61, 82, 95, 110, 133, 156, 197, 198, 202, 210, 212, 213, 220, 221, 224, 228, 231, 251, 263, 275, 287, 304], "im_open": 27, "im_diff": 27, "let": [27, 37, 44, 58, 59, 62, 63, 69, 79, 82, 84, 85, 86, 87, 90, 92, 94, 96, 97, 102, 103, 104, 106, 107, 113, 115, 116, 121, 124, 126, 129, 130, 157, 158, 160, 162, 166], "try": [27, 57, 62, 79, 94, 107, 115, 123, 126], "im_clos": [27, 96], "im_eros": 27, "im_dil": 27, "ani": [28, 29, 51, 59, 62, 68, 85, 86, 93, 96, 98, 107, 114, 115, 117, 120, 121, 126, 129, 130, 132, 154, 156, 168, 172, 175, 176, 178, 181, 185, 191, 194, 197, 198, 199, 202, 203, 205, 213, 230, 241, 269, 270, 273, 276, 304, 305], "connect": [28, 29, 40, 51, 55, 58, 103, 114, 115, 116, 118, 120, 121, 122, 129, 170, 175, 176, 188, 200, 201, 203, 205, 207, 262, 268, 269, 270], "often": [28, 123], "numer": [28, 58, 59, 62, 63, 121, 123, 124, 132, 177, 180, 181, 239, 266, 285, 288], "blind": [28, 175, 249], "consid": [28, 29, 53, 62, 103, 104, 105, 121, 124, 176, 179, 192, 206, 225, 226, 240, 241, 250, 254, 255, 305], "cluster": [28, 29, 51, 57, 76, 129, 209, 270], "im1": [28, 49, 51, 62, 64, 70, 72, 74, 75, 79, 82, 83, 84, 87, 101, 140, 141, 145, 148, 149, 153, 159, 160, 165, 291], "control": [28, 35, 36, 38, 40, 48, 64, 65, 66, 67, 70, 72, 74, 75, 77, 78, 79, 81, 82, 114, 120, 121, 127, 132, 155, 166, 173, 178, 188, 191, 192, 196, 197, 198, 199, 202, 206, 210, 213, 216, 222, 223, 225, 226, 244, 256, 268, 269, 287, 296, 311], "how": [28, 41, 51, 53, 59, 62, 63, 66, 67, 72, 75, 85, 86, 90, 108, 112, 120, 121, 122, 123, 124, 130, 131, 135, 140, 173, 180, 191, 196, 197, 198, 199, 206, 222, 223, 225, 226, 239, 244, 259, 268, 269, 287, 322], "group": [28, 168, 194], "option": [28, 29, 36, 40, 46, 47, 53, 58, 65, 67, 72, 82, 90, 95, 120, 121, 140, 154, 168, 172, 173, 174, 175, 176, 179, 180, 185, 186, 187, 188, 189, 191, 192, 193, 196, 197, 198, 199, 200, 201, 202, 205, 210, 211, 212, 213, 214, 215, 216, 218, 220, 221, 222, 223, 224, 225, 226, 228, 232, 235, 236, 237, 239, 240, 244, 255, 256, 259, 261, 262, 268, 269, 270, 280, 281, 286, 290, 302, 304, 306, 311], "while": [28, 61, 62, 80, 92, 120, 121, 129, 130, 156, 172, 175, 176, 192, 202, 205, 218, 266, 287], "26": [28, 29, 53, 58, 100, 115, 126, 149, 175, 176, 205], "im2": [28, 37, 49, 51, 62, 63, 64, 70, 72, 74, 75, 79, 82, 83, 84, 87, 101, 139, 140, 141, 148, 149, 159, 160, 165, 291], "flag": [28, 126, 192], "main": [28, 79, 121, 124, 125, 133, 175, 205, 217], "bodi": [28, 72, 202, 205, 218], "mi": [28, 74, 132], "lead": [28, 62, 78], "result": [28, 29, 32, 36, 37, 38, 40, 48, 49, 50, 53, 58, 59, 60, 61, 62, 63, 64, 82, 85, 86, 88, 89, 90, 91, 92, 95, 97, 102, 103, 104, 110, 111, 112, 113, 115, 116, 121, 123, 126, 127, 129, 130, 131, 133, 140, 161, 168, 171, 172, 173, 174, 182, 185, 188, 189, 190, 192, 195, 200, 201, 210, 211, 213, 216, 223, 225, 226, 237, 238, 239, 241, 244, 247, 248, 250, 253, 254, 257, 258, 259, 260, 265, 267, 269, 270, 271, 280, 283, 287, 302, 309, 312], "sinc": [28, 30, 32, 38, 58, 66, 67, 70, 95, 111, 112, 113, 115, 117, 120, 121, 122, 124, 125, 126, 129, 130, 133, 159, 165, 172, 175, 177, 188, 191, 197, 198, 200, 201, 205, 207, 213, 222, 223, 225, 226, 239, 241, 245, 248, 253, 267, 269, 270, 300], "just": [28, 30, 41, 45, 46, 58, 59, 62, 63, 70, 79, 86, 122, 124, 129, 130, 138, 168, 176, 177, 235, 236, 248, 298], "keep": [28, 55, 129, 168, 224], "largest": [28, 32, 36, 40, 59, 86, 97, 102, 111, 113, 120, 129, 175, 188, 191, 196, 198, 199, 205, 214, 231, 248, 257, 263, 268, 276], "For": [28, 34, 37, 59, 70, 93, 113, 115, 116, 121, 123, 124, 130, 131, 140, 154, 155, 166, 168, 175, 176, 186, 188, 189, 202, 205, 216, 218, 221, 235, 236, 239, 241, 244, 248, 250, 254, 260, 269, 274], "better": [28, 62, 90, 92, 97, 117, 120, 121, 130, 155, 239, 241, 248, 253, 268, 269], "recommend": [28, 120, 121, 129, 168, 189, 253], "trim_nonpercolation_path": 28, "detect": [29, 111, 170, 241], "region": [29, 32, 33, 34, 43, 46, 47, 48, 49, 50, 58, 60, 61, 62, 68, 78, 90, 92, 94, 97, 98, 100, 101, 106, 117, 118, 119, 121, 122, 123, 124, 125, 126, 129, 131, 132, 138, 158, 162, 166, 175, 176, 179, 180, 181, 188, 190, 195, 200, 201, 202, 205, 207, 225, 226, 239, 241, 242, 243, 248, 251, 252, 253, 254, 255, 256, 257, 261, 262, 266, 268, 269, 277, 279, 286, 289, 296, 310, 312], "specif": [29, 33, 70, 106, 111, 112, 123, 148, 167, 180, 185, 188, 192, 241, 253, 307, 312], "disconnect": [29, 131, 175, 176, 192, 205, 270, 271], "pixel": [29, 37, 38, 62, 83, 85, 89, 110, 113, 114, 125, 129, 131, 189, 190, 211, 213, 228, 280], "Then": [29, 45, 129, 166], "scikitimag": 29, "clear_bord": [29, 176], "includ": [29, 38, 49, 58, 62, 85, 86, 90, 92, 96, 97, 102, 104, 111, 113, 115, 116, 117, 118, 124, 126, 129, 130, 138, 166, 167, 172, 188, 190, 213, 225, 226, 228, 239, 241, 248, 253, 257, 259, 260, 269, 270, 275, 287, 299, 302, 304], "found": [29, 34, 38, 48, 54, 56, 69, 70, 71, 86, 107, 110, 115, 120, 121, 123, 126, 129, 131, 133, 177, 182, 188, 189, 200, 201, 232, 247, 252, 257, 268, 271, 280], "discon_voxel": 29, "sweep": 29, "subsequ": [29, 59, 111, 113, 121, 131, 301], "affect": [29, 36, 40], "accuraci": [29, 115, 123, 126, 179, 235, 236, 268, 269], "algorithm": [29, 40, 48, 50, 60, 61, 62, 75, 78, 93, 94, 103, 104, 113, 120, 121, 122, 123, 125, 126, 127, 129, 130, 132, 133, 157, 158, 167, 200, 201, 202, 206, 208, 213, 220, 225, 226, 243, 256, 257, 267, 268, 269, 270, 289, 305], "Their": 29, "correspond": [29, 37, 62, 89, 111, 112, 113, 120, 121, 132, 159, 165, 171, 185, 189, 202, 229, 231, 240, 247, 252, 263, 266, 268, 285], "squar": [29, 31, 53, 175, 176, 178, 205, 218, 227, 276], "cube": [29, 86, 93, 94, 103, 104, 105, 120, 231, 243, 254, 255, 256, 257, 263, 268, 269, 289], "ball": [29, 31, 225, 226, 267, 279, 292], "bt": 29, "paramet": [29, 62, 74, 81, 120, 160, 164, 169, 170, 171, 172, 173, 174, 175, 176, 177, 178, 179, 180, 181, 182, 186, 187, 188, 189, 190, 191, 192, 193, 194, 195, 196, 197, 198, 199, 200, 201, 202, 203, 204, 205, 206, 207, 208, 209, 210, 211, 212, 213, 214, 215, 216, 217, 218, 219, 220, 221, 222, 223, 224, 225, 226, 227, 228, 229, 230, 231, 232, 233, 234, 235, 236, 237, 238, 239, 240, 241, 242, 243, 244, 247, 248, 249, 250, 251, 252, 253, 254, 255, 256, 257, 258, 259, 260, 261, 262, 263, 264, 265, 266, 267, 268, 269, 270, 271, 273, 274, 275, 276, 277, 278, 279, 280, 281, 283, 284, 285, 286, 287, 288, 289, 290, 291, 292, 293, 294, 295, 296, 297, 298, 299, 300, 301, 302, 303, 304, 305, 306, 307, 309, 310, 311, 312], "closer": [30, 48, 54, 129, 177], "solid": [30, 44, 46, 47, 48, 51, 53, 54, 62, 63, 87, 100, 103, 104, 105, 106, 107, 109, 111, 113, 118, 121, 122, 123, 130, 156, 157, 158, 166, 173, 177, 179, 188, 191, 192, 196, 197, 198, 199, 205, 206, 219, 220, 231, 233, 234, 237, 241, 249, 253, 259, 263, 265, 269, 279, 304, 306, 307, 312], "These": [30, 52, 58, 69, 84, 114, 120, 121, 127, 129, 169, 170, 177, 185, 192, 253, 258, 268, 269, 305], "potenti": [30, 85, 114, 129, 177, 213, 253], "could": [30, 36, 62, 114, 120, 121, 124, 130, 156, 177, 186, 187, 188, 298], "lie": [30, 38, 48, 56, 62, 82, 111, 121, 124, 194, 213, 228], "beyond": [30, 82, 110, 132, 171, 177, 213, 217, 222, 223, 225, 226, 232, 275, 301, 305], "were": [30, 32, 47, 56, 59, 62, 63, 95, 111, 113, 115, 121, 126, 131, 132, 158, 177, 191, 208, 270, 297], "crop": [30, 137, 217], "onli": [30, 40, 53, 55, 59, 62, 63, 66, 71, 79, 82, 86, 94, 99, 112, 113, 115, 117, 120, 121, 123, 126, 129, 131, 132, 172, 175, 192, 201, 205, 206, 209, 217, 218, 221, 223, 225, 226, 241, 249, 267, 269, 270, 284, 285, 286, 296], "accept": [30, 37, 80, 81, 82, 86, 113, 121, 124, 154, 167, 173, 180, 189, 222, 225, 226, 229], "tranform": [30, 121, 129, 192], "distance_transform_edt": [30, 124], "dt2": [30, 52], "peak": [31, 35, 48, 49, 52, 60, 76, 122, 124, 132, 178, 182, 194, 200, 201, 204, 206, 208, 222, 232, 269], "watersh": [31, 34, 48, 60, 113, 114, 120, 121, 124, 125, 187, 200, 201, 206, 208, 257, 261, 268, 269], "segment": [31, 34, 48, 60, 61, 62, 63, 78, 94, 113, 114, 115, 116, 120, 121, 124, 125, 126, 200, 201, 202, 208, 261, 262, 268, 269], "11": [31, 59, 62, 71, 79, 86, 88, 89, 91, 115, 121, 123, 124, 125, 126], "sigma": [31, 33, 34, 37, 50, 53, 60, 61, 62, 95, 124, 129, 130, 178, 189, 200, 201, 202, 210, 244, 269, 270], "div": [31, 53, 61, 121, 152, 172, 178, 188, 192, 202, 210, 300], "pk": [31, 34, 35, 114], "search": [31, 35, 37, 38, 48, 63, 170, 189], "maxima": [31, 52, 120, 121, 178, 204, 268], "form": [31, 59, 66, 76, 77, 98, 133, 138, 185, 212, 242, 248, 274, 298], "handl": [31, 75, 86, 121, 171, 172, 181, 200, 201, 212, 222, 223, 225, 226, 261, 275, 282, 299, 302, 310], "depend": [31, 36, 40, 53, 72, 110, 115, 123, 126, 154, 168, 174, 188, 189, 192, 213, 269, 282, 302], "meant": [32, 106, 309], "defend": [32, 132, 270], "trap": [32, 179, 270], "dure": [32, 62, 85, 114, 121, 122, 244, 269], "ordinari": 32, "percol": [32, 127, 130, 131, 132, 157, 158, 175], "type": [32, 53, 63, 65, 115, 121, 123, 126, 168, 169, 170, 172, 173, 174, 176, 177, 178, 179, 180, 181, 182, 186, 187, 188, 190, 191, 192, 193, 194, 195, 196, 197, 198, 199, 200, 201, 202, 203, 204, 205, 206, 207, 208, 209, 210, 211, 212, 213, 214, 215, 216, 217, 218, 219, 220, 221, 222, 223, 224, 225, 226, 227, 228, 231, 237, 238, 239, 240, 241, 242, 243, 244, 247, 248, 249, 250, 251, 252, 253, 254, 255, 256, 257, 258, 259, 260, 261, 262, 263, 264, 265, 268, 269, 270, 271, 273, 274, 275, 276, 277, 278, 279, 280, 281, 282, 283, 284, 285, 286, 287, 288, 289, 290, 291, 292, 293, 294, 295, 296, 297, 298, 299, 300, 302, 304, 306, 307, 309, 310, 311, 312], "25": [32, 36, 37, 40, 46, 47, 52, 58, 62, 63, 65, 67, 68, 69, 71, 72, 73, 86, 87, 89, 115, 122, 123, 135, 148, 149, 158, 179, 188, 192, 231, 263, 270], "return_mask": [32, 132, 179], "inlet": [32, 91, 108, 129, 130, 131, 132, 157, 188, 192, 203, 207, 215, 270], "zeros_lik": [32, 40, 52, 55, 91, 108, 127, 129, 130, 132, 157], "sequenc": [32, 44, 45, 46, 47, 63, 127, 130, 132, 157, 179, 191, 196, 197, 199, 244], "wa": [32, 48, 58, 61, 62, 63, 81, 85, 86, 87, 91, 95, 98, 110, 115, 119, 120, 121, 122, 123, 124, 126, 130, 132, 139, 156, 157, 158, 177, 189, 191, 196, 197, 198, 200, 208, 210, 213, 244, 251, 266, 269, 270, 275, 281, 300, 306], "after": [32, 54, 56, 62, 85, 86, 90, 92, 97, 102, 103, 104, 121, 123, 124, 131, 185, 186, 187, 200, 213, 221, 239, 241, 248, 253, 257, 260, 267, 271, 317], "cutoff": 32, "output": [32, 48, 85, 108, 118, 132, 148, 156, 158, 160, 167, 168, 186, 187, 229, 232, 233, 234, 235, 236, 267, 296, 308], "howev": [32, 70, 86, 91, 98, 115, 117, 123, 126, 129, 132, 133, 166, 188, 201], "order": [32, 63, 70, 73, 115, 116, 182, 191, 201, 262, 270, 287, 309], "first": [32, 40, 58, 63, 72, 74, 85, 86, 92, 94, 103, 110, 111, 113, 115, 117, 126, 129, 130, 132, 133, 160, 162, 166, 168, 185, 189, 217, 225, 226, 248, 253, 257, 261, 275], "abov": [32, 46, 47, 48, 58, 59, 62, 63, 80, 82, 91, 111, 113, 114, 118, 121, 122, 123, 129, 130, 132, 148, 158, 168, 257, 304], "mask": [32, 104, 105, 106, 113, 124, 138, 179, 188, 192, 203, 207, 211, 214, 253, 259, 269, 270, 277, 279, 280, 303, 304], "treat": [32, 79, 121, 122, 191, 220, 257, 259], "d": [32, 63, 106, 110, 132, 261, 269, 294], "see": [32, 58, 59, 62, 63, 82, 86, 117, 118, 120, 121, 124, 129, 130, 132, 133, 140, 185, 192, 216, 237, 239, 244, 249, 253, 254, 255, 257, 260, 267, 270], "iter": [32, 67, 74, 78, 80, 85, 127, 185, 193, 206, 208, 213, 220, 223, 224, 225, 226, 227, 282, 300], "backward": [32, 173], "small": [32, 72, 85, 86, 90, 92, 97, 121, 122, 129, 132, 161, 210, 213, 218, 239, 241, 248, 253, 309], "step": [32, 36, 40, 48, 59, 60, 78, 95, 111, 115, 116, 120, 121, 122, 125, 126, 129, 131, 132, 168, 179, 188, 200, 245, 269], "taken": [32, 37, 60, 62, 66, 86, 121, 122, 129, 156, 158, 163, 180, 189, 278, 281, 304, 306], "occur": [32, 108, 121, 132, 178, 188, 192, 210, 288], "ibip": [32, 157, 158, 244], "unreason": 32, "slow": [32, 37, 62, 79, 120, 121, 129, 161, 258, 309], "even": [32, 62, 121], "via": [32, 63, 70, 120, 128, 168, 192, 268, 269], "being": [32, 36, 40, 48, 65, 68, 82, 86, 120, 121, 132, 155], "list": [32, 36, 40, 63, 66, 67, 68, 72, 73, 74, 75, 83, 103, 104, 106, 117, 118, 132, 135, 158, 171, 172, 178, 180, 181, 185, 188, 192, 201, 202, 210, 212, 213, 215, 218, 219, 220, 221, 225, 226, 228, 232, 240, 241, 251, 252, 254, 255, 257, 264, 269, 270, 274, 275, 277, 281, 283, 290, 297, 301, 305, 306], "statist": [33, 75, 180], "calcul": [33, 73, 85, 89, 93, 94, 96, 97, 98, 102, 103, 104, 105, 106, 107, 109, 110, 113, 115, 116, 120, 121, 122, 123, 126, 128, 129, 131, 133, 173, 178, 181, 188, 193, 213, 219, 231, 237, 242, 247, 248, 249, 250, 252, 254, 255, 256, 257, 258, 259, 260, 263, 268, 269, 271, 279, 304], "r_max": [33, 42, 50, 54, 56, 60, 61, 114, 178, 200, 201, 202, 269], "variou": [33, 62, 110, 113, 167, 180, 257, 302, 306], "max": [33, 52, 53, 59, 61, 62, 86, 95, 115, 120, 123, 126, 132, 133, 180, 188, 192, 201, 247, 290], "sum": [33, 34, 53, 67, 75, 87, 98, 99, 105, 120, 129, 132, 133, 180, 181, 239, 241, 249, 256, 258, 268], "suppli": [34, 46, 50, 71, 86, 118, 121, 129, 130, 178, 198, 199, 200, 201, 210, 217, 222, 223, 225, 226, 232, 238, 241, 269], "arrai": [34, 36, 38, 48, 49, 50, 53, 58, 59, 60, 63, 76, 79, 82, 84, 87, 88, 89, 95, 98, 104, 105, 115, 116, 120, 123, 124, 125, 126, 129, 131, 132, 133, 135, 140, 156, 161, 164, 166, 178, 180, 181, 191, 193, 194, 196, 198, 199, 200, 201, 203, 204, 206, 210, 211, 212, 213, 215, 218, 220, 221, 225, 226, 228, 229, 232, 234, 235, 236, 237, 238, 239, 242, 247, 248, 250, 253, 254, 256, 260, 262, 264, 265, 266, 268, 269, 270, 275, 278, 280, 283, 287, 288, 290, 292, 293, 294, 295, 300, 303, 309, 311], "instanc": [34, 36, 46, 47, 121, 129, 130, 155, 175, 185, 200, 205, 221, 250, 254, 269], "when": [34, 36, 37, 46, 47, 48, 62, 72, 79, 85, 98, 112, 121, 122, 124, 132, 140, 156, 157, 171, 172, 175, 179, 185, 190, 198, 199, 205, 207, 208, 213, 235, 236, 272, 282, 289, 297, 300, 301, 305], "those": [34, 58, 62, 95, 107, 129, 154, 160, 190, 276], "allow": [34, 39, 40, 62, 76, 77, 82, 87, 103, 104, 106, 121, 130, 178, 185, 188, 192, 200, 222, 223, 225, 226, 235, 236, 242, 249, 257, 269, 289], "Or": [34, 68, 95, 111, 129, 130], "amax": [34, 181], "color": [34, 47, 58, 121, 126, 130, 132, 133, 156, 157, 166, 251, 305, 307, 312], "within": [34, 74, 79, 92, 103, 104, 105, 111, 118, 120, 121, 188, 214, 222, 223, 225, 226, 241, 256, 260, 283], "gaussian_filt": [34, 53, 62, 121, 124, 178], "w": [34, 51, 114, 117, 119, 120, 122, 294], "marker": [34, 113, 114, 121, 124, 125, 200, 201, 206, 208, 269], "last": [35, 47, 53, 62, 63, 86, 115, 123, 129, 133, 303], "seen": [35, 40, 47, 48, 62, 82, 91, 113, 117, 125, 129, 158, 275, 296], "most": [35, 53, 62, 63, 115, 120, 121, 122, 123, 135, 287, 300], "distant": 35, "16": [35, 40, 67, 82, 86, 89, 100, 115, 120, 121, 124, 125, 126], "pk1": [35, 121], "pk2": [35, 121], "scan": [35, 129, 182], "would": [36, 58, 62, 69, 97, 120, 121, 123, 129, 130, 140, 156, 177, 223, 231, 254, 255, 263, 268, 269, 270, 300, 312], "center": [36, 68, 72, 120, 121, 124, 129, 133, 188, 194, 212, 213, 216, 217, 218, 232, 239, 241, 248, 253, 260, 268, 278, 285, 291], "hybrid": [36, 40, 188, 192], "either": [36, 40, 43, 61, 63, 78, 79, 80, 85, 94, 95, 97, 108, 120, 121, 185, 195, 203, 211, 225, 226, 239, 244, 248, 252, 260, 268, 269, 278, 280, 282, 283, 294, 295], "bin": [36, 37, 40, 58, 62, 63, 75, 87, 89, 111, 132, 148, 154, 179, 198, 199, 237, 239, 241, 248, 253, 260, 270, 302, 306], "draw": [36, 73, 89, 90, 129], "actual": [36, 40, 53, 59, 62, 63, 67, 69, 75, 80, 86, 113, 120, 121, 122, 129, 180, 208, 248, 257], "logarithm": [36, 90, 92, 97, 130, 237], "down": [36, 37, 59, 129, 132, 212], "custom": [36, 51, 90, 92, 97, 102, 107, 109, 117, 121, 124, 178, 200, 201, 239, 241, 244, 248, 253, 254, 258, 259, 269], "linear": [36, 111, 173, 241], "bimod": 36, "fft": [36, 40, 174, 188, 192], "mio": [36, 40, 188, 192], "select": [36, 40, 63, 123, 166, 229, 296], "speed": [36, 40, 61, 70, 120, 121, 123, 129, 172, 174, 188, 192, 222, 223, 225, 226, 300], "exactli": [36, 40, 58, 113], "ensur": [36, 40, 66, 76, 77, 84, 121, 122, 123, 163, 171, 206, 225, 226, 248, 275, 287, 301], "unit": [36, 40, 85, 86, 95, 120, 121, 213, 218, 239, 241, 248, 253, 259, 260, 267], "lt1": 36, "lt2": 36, "lt3": 36, "equal": [36, 85, 86, 115, 126, 129, 139, 158, 172, 190, 213, 287, 306], "process": [36, 37, 41, 61, 62, 63, 76, 77, 78, 84, 111, 120, 121, 122, 123, 124, 129, 167, 178, 188, 189, 192, 193, 200, 201, 202, 210, 216, 225, 226, 239, 241, 248, 249, 253, 269, 297], "dask": [36, 121, 172], "behind": [36, 121, 129], "scene": [36, 121, 129], "core": [36, 40, 53, 61, 62, 121, 126, 137, 172, 178, 188, 189, 192, 202, 210, 216, 249, 276, 279], "ident": [36, 40, 59, 188, 296], "regardless": [36, 40], "non": [37, 91, 95, 108, 123, 127, 129, 130, 131, 132, 169, 175, 188, 189, 192, 197, 198, 205, 232, 244, 259, 270, 279], "layer": [37, 62, 70, 86, 115, 126, 189, 211, 259, 261, 300], "stack": [37, 189], "nois": [37, 64, 70, 87, 148, 189, 210, 216], "util": [37, 115, 172, 260], "random_nois": 37, "75": [37, 48, 49, 64, 75, 85, 92, 115, 127, 158], "gaussian": [37, 48, 62, 87, 172, 178, 186, 187, 189, 200, 201, 210, 269], "24": [37, 48, 49, 50, 58, 59, 60, 88, 91, 95, 100, 113, 115, 126, 129, 131], "var": 37, "05": [37, 48, 49, 50, 70, 95, 126, 216, 221], "hist": [37, 40, 62, 63, 64, 70, 87, 89, 104, 113, 133, 148, 238], "flatten": [37, 52, 62, 63, 64, 70, 87, 133, 148, 300], "edgecolor": [37, 40, 58, 59, 62, 63, 64, 65, 68, 69, 87, 90, 92, 97, 102, 104, 111, 113, 133, 148, 154, 248, 302], "k": [37, 40, 58, 59, 62, 63, 64, 65, 68, 69, 87, 90, 92, 97, 102, 104, 111, 113, 115, 121, 133, 148, 248], "filtered_im": 37, "chang": [37, 64, 87, 110, 119, 121, 122, 125, 132, 154, 166, 168, 185, 204, 231, 263], "smaller": [37, 40, 57, 59, 62, 68, 70, 79, 86, 115, 123, 172, 192, 209, 216, 300], "slice": [37, 53, 62, 63, 106, 108, 112, 113, 122, 123, 124, 133, 135, 152, 155, 163, 166, 189, 257, 274, 275, 281, 286, 297, 300, 303, 304, 306], "tomographi": [37, 63, 167, 189, 276], "rotat": [37, 67, 121, 124, 140, 161, 189, 213, 214, 273, 309], "stage": [37, 121, 122, 123, 189, 200, 201, 269], "im_x": 37, "im_i": 37, "im_z": 37, "patch": [37, 124, 189], "denois": [37, 63, 189], "im_1": 37, "im_2": 37, "im_3": 37, "maxim": [37, 113, 189, 267], "cut": [37, 189], "off": [37, 58, 119, 122, 125, 132, 133, 189], "grai": [37, 189], "level": [37, 70, 123, 189], "higher": [37, 48, 78, 107, 108, 126, 129, 132, 179, 189, 210, 216, 305], "permiss": [37, 189], "smoother": [37, 108, 189], "expens": [37, 189], "blur": [37, 48, 62, 64, 87, 103, 104, 124, 172, 186, 187, 189, 210, 254, 255, 257, 289], "featur": [37, 70, 78, 106, 108, 113, 121, 122, 138, 163, 168, 178, 189, 195, 304, 307], "deviat": [37, 53, 123, 180, 189, 200, 201, 221, 269], "rule": [37, 48, 189], "thumb": [37, 189], "choos": [37, 90, 96, 105, 129, 166, 189, 192], "slightli": [37, 59, 70, 76, 98, 124, 132, 189], "matrix": [38, 76, 125, 279], "inclus": 38, "return_spher": [38, 79, 225, 226], "clearanc": [38, 84, 106, 121, 222, 223, 225, 226], "bd": [38, 65, 122, 132, 157], "ipykernel_3382": 38, "2381005276": 38, "intern": [38, 53, 113, 121, 122, 129], "corner": [38, 65, 76, 122, 140, 211, 217, 260, 280, 303, 304], "meet": [38, 74, 79, 120, 149, 268], "diagon": [38, 53, 175, 176, 205], "thicker": 38, "neighbor": [38, 48, 120, 121, 172, 175, 176, 205, 223, 233, 296], "bd1": 38, "bd2": 38, "capillari": [39, 95, 127, 129, 130, 191, 192, 244, 270], "pressur": [39, 95, 127, 129, 130, 191, 192, 196, 233, 244, 270], "map": [39, 44, 45, 46, 47, 91, 101, 102, 108, 115, 116, 118, 119, 120, 157, 166, 244, 265, 266, 268, 269, 305], "satur": [39, 44, 45, 46, 91, 95, 108, 129, 130, 157, 158, 191, 196, 197, 198, 240, 248, 259, 270, 305, 306], "drn": [39, 130], "voxel_s": [39, 44, 91, 95, 108, 112, 115, 119, 123, 124, 125, 129, 130, 132, 229, 235, 236, 239, 241, 244, 248, 253, 254, 255, 260, 262, 267, 268, 269, 270], "g": [39, 44, 61, 85, 91, 99, 108, 112, 113, 115, 121, 123, 125, 126, 129, 130, 132, 172, 185, 190, 215, 252, 270, 300], "satn": [39, 45, 46, 59, 91, 129, 132, 191, 196, 197, 198, 248, 259, 305, 306], "im_pc": [39, 129, 130, 270], "easi": [39, 45, 46, 62, 84, 86, 87], "desir": [39, 45, 46, 47, 48, 72, 74, 76, 79, 81, 118, 121, 178, 186, 187, 207, 212, 227, 234, 257, 259, 260, 292, 293, 294, 295, 299], "fluid": [39, 40, 45, 46, 91, 108, 120, 121, 127, 129, 130, 132, 188, 192, 233, 244, 259, 270], "configur": [39, 45, 46, 91, 129, 132, 188, 192, 270], "essenti": [40, 75, 86, 204, 207], "analzi": [40, 88], "access_limit": [40, 188, 192], "cumul": [40, 90, 92, 97, 102, 111, 239, 241, 248, 253], "analog": [40, 121], "densiti": [40, 90, 92, 97, 102, 239, 241, 248, 253, 260, 270], "set_xlabel": [40, 58, 59, 85, 88, 95, 107, 109, 110, 111, 112, 126, 129, 133, 148], "set_ylabel": [40, 58, 59, 85, 88, 95, 107, 109, 110, 111, 112, 126, 129, 133, 148], "state": [40, 111, 210, 212, 213, 220, 221, 224, 228, 230, 234, 241, 260], "enter": [40, 82, 132, 192, 270], "typic": [40, 65, 120, 121, 156, 167, 213, 300, 317], "physic": [40, 48, 67, 112, 121, 122, 124, 125, 126, 129, 167, 200, 201, 206, 208], "sizes1": 40, "sizes2": 40, "legend": [40, 85, 112, 132, 133], "As": [40, 48, 58, 103, 104, 113, 117, 123, 125, 126, 131, 158, 209, 275, 289, 296], "appear": [40, 63, 106, 122, 127, 132, 192, 312], "becaus": [40, 50, 56, 62, 63, 74, 86, 87, 91, 106, 113, 121, 122, 129, 132, 158, 161, 208, 222, 223, 225, 226, 252, 309], "cannot": [40, 113, 217, 260, 274], "reach": [40, 74, 85, 92, 129, 225, 226], "shield": [40, 129, 192], "ones": [40, 62, 71, 79, 86], "attribut": [40, 48, 58, 59, 63, 88, 91, 95, 106, 113, 121, 125, 129, 130, 131, 185, 200, 201, 237, 239, 241, 244, 248, 253, 254, 258, 259, 260, 269, 270, 271, 272, 275], "sizes3": 40, "fucntion": 40, "run": [40, 83, 115, 123, 126, 127, 216, 233, 267], "subdiv": 40, "divis": [40, 81, 92, 121, 224, 239, 241, 248, 253, 260, 300], "scalar": [40, 53, 64, 100, 106, 113, 120, 166, 171, 172, 178, 181, 188, 192, 201, 202, 206, 209, 210, 211, 213, 216, 217, 220, 225, 226, 229, 239, 240, 241, 248, 251, 252, 253, 254, 255, 259, 260, 261, 262, 267, 268, 269, 276, 277, 279, 280, 290, 292, 294, 295, 300, 305], "dangl": [41, 193], "branch": [41, 168, 193], "skeleton": [41, 106, 113, 171, 193, 257, 301], "requir": [41, 50, 58, 59, 61, 84, 86, 112, 114, 115, 121, 124, 126, 129, 130, 167, 168, 186, 206, 213, 215, 222, 223, 225, 226, 259], "mophologi": 41, "250": [41, 53, 62, 67, 132], "sk": 41, "sk1": 41, "repeat": [41, 59, 78, 85, 111, 129, 132, 192, 193, 213, 222, 223, 225, 226, 305], "equivalen": 41, 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"regions-to-network"], [120, "regions-to-network"]], "region_surface_areas": [[255, "region-surface-areas"], [104, "region-surface-areas"]], "radial_density_distribution": [[253, "radial-density-distribution"], [102, "radial-density-distribution"]], "mesh_surface_area": [[242, "mesh-surface-area"], [94, "mesh-surface-area"]], "Results": [[272, "results"]], "regionprops_3D": [[257, "regionprops-3d"], [106, "regionprops-3d"]], "find_h": [[240, "find-h"], [91, "find-h"]], "map_to_regions": [[266, "map-to-regions"], [119, "map-to-regions"]], "extract_regions": [[277, "extract-regions"], [138, "extract-regions"]], "extract_subsection": [[278, "extract-subsection"], [139, "extract-subsection"]], "find_outer_region": [[279, "find-outer-region"]], "pore_size_distribution": [[248, "pore-size-distribution"], [97, "pore-size-distribution"]], "add_boundary_regions": [[261, "add-boundary-regions"], [114, "add-boundary-regions"]], "mesh_volume": [[243, "mesh-volume"], [93, "mesh-volume"]], "prop_to_image": [[251, "prop-to-image"]], "tortuosity_fd": [[271, "tortuosity-fd"]], "maximal_ball_wrapper": [[267, "maximal-ball-wrapper"]], "bbox_to_slices": [[274, "bbox-to-slices"], [135, "bbox-to-slices"]], "generate_voxel_image": [[263, "generate-voxel-image"]], "pc_curve": [[244, "pc-curve"], [95, "pc-curve"]], "satn_profile": [[259, "satn-profile"], [108, "satn-profile"]], "drainage": [[270, "drainage"]], "label_boundaries": [[264, "label-boundaries"], [117, "label-boundaries"]], "lineal_path_distribution": [[241, "lineal-path-distribution"], [92, "lineal-path-distribution"]], "phase_fraction": [[247, "phase-fraction"], [96, "phase-fraction"]], "porosity_profile": [[250, "porosity-profile"], [99, "porosity-profile"]], "porosity": [[249, "porosity"], [74, "porosity"], [75, "porosity"], [67, "porosity"], [64, "porosity"], [98, "porosity"]], "pc_curve_from_ibip": [[245, "pc-curve-from-ibip"]], "representative_elementary_volume": [[258, "representative-elementary-volume"], [107, "representative-elementary-volume"]], "label_phases": [[265, "label-phases"], [118, "label-phases"]], "two_point_correlation": [[260, "two-point-correlation"], [109, "two-point-correlation"]], "rsa": [[226, "rsa"], [79, "rsa"]], "lattice_spheres": [[218, "lattice-spheres"], [72, "lattice-spheres"]], "sierpinski_foam": [[227, "sierpinski-foam"], [80, "sierpinski-foam"]], "to_stl": [[235, "to-stl"]], "cylinders": [[213, "cylinders"], [67, "cylinders"]], "boxcount": [[237, "boxcount"], [88, "boxcount"]], "snow_partitioning": [[200, "snow-partitioning"], [48, "snow-partitioning"]], "spheres_to_comsol": [[232, "spheres-to-comsol"]], "fractal_noise": [[216, "fractal-noise"], [70, "fractal-noise"]], "snow_partitioning_n": [[201, "snow-partitioning-n"], [49, "snow-partitioning-n"]], "dict_to_vtk": [[229, "dict-to-vtk"]], "blobs": [[210, "blobs"], [64, "blobs"]], "chord_counts": [[238, "chord-counts"], [89, "chord-counts"]], "trim_nearby_peaks": [[206, "trim-nearby-peaks"], [54, "trim-nearby-peaks"]], "trim_disconnected_blobs": [[203, "trim-disconnected-blobs"], [51, "trim-disconnected-blobs"]], "cylindrical_plug": [[214, "cylindrical-plug"], [68, "cylindrical-plug"]], "trim_extrema": [[204, "trim-extrema"], [52, "trim-extrema"]], "pseudo_gravity_packing": [[223, "pseudo-gravity-packing"], [77, "pseudo-gravity-packing"]], "to_vtk": [[236, "to-vtk"]], "trim_saddle_points": [[208, "trim-saddle-points"], [56, "trim-saddle-points"]], "pseudo_electrostatic_packing": [[222, "pseudo-electrostatic-packing"], [76, "pseudo-electrostatic-packing"]], "overlapping_spheres": [[220, "overlapping-spheres"], [74, "overlapping-spheres"]], "random_cantor_dust": [[224, "random-cantor-dust"], [78, "random-cantor-dust"]], "random_spheres": [[225, "random-spheres"]], "to_palabos": [[233, "to-palabos"]], "snow_partitioning_parallel": [[202, "snow-partitioning-parallel"], [50, "snow-partitioning-parallel"]], "borders": [[211, "borders"], [65, "borders"]], "trim_nonpercolating_paths": [[207, "trim-nonpercolating-paths"], [55, "trim-nonpercolating-paths"]], "trim_floating_solid": [[205, "trim-floating-solid"], [53, "trim-floating-solid"]], "bundle_of_tubes": [[212, "bundle-of-tubes"], [66, "bundle-of-tubes"]], "to_paraview": [[234, "to-paraview"]], "voronoi_edges": [[228, "voronoi-edges"], [83, "voronoi-edges"]], "line_segment": [[219, "line-segment"], [73, "line-segment"]], "chord_length_distribution": [[239, "chord-length-distribution"], [90, "chord-length-distribution"]], "faces": [[215, "faces"], [69, "faces"]], "openpnm_to_im": [[231, "openpnm-to-im"]], "trim_small_clusters": [[209, "trim-small-clusters"], [57, "trim-small-clusters"]], "insert_shape": [[217, "insert-shape"], [71, "insert-shape"]], "open_paraview": [[230, "open-paraview"]], "polydisperse_spheres": [[221, "polydisperse-spheres"], [75, "polydisperse-spheres"]], "size_to_satn": [[198, "size-to-satn"], [46, "size-to-satn"]], "reduce_peaks": [[194, "reduce-peaks"], [42, "reduce-peaks"]], "ibip": [[183, "ibip"], [127, "ibip"]], "region_size": [[195, "region-size"], [43, "region-size"]], "imagej_wrapper": [[187, "imagej-wrapper"]], "porosimetry": [[192, "porosimetry"], [40, "porosimetry"]], "mesh": [[162, "mesh"], [94, "mesh"]], "Installation": [[168, "installation"]], "Installing the dev version": [[168, "installing-the-dev-version"]], "The easy way": [[168, "the-easy-way"]], "The hard (but correct) way": [[168, "the-hard-but-correct-way"]], "Where\u2019s my conda prompt?": [[168, "where-s-my-conda-prompt"]], "show_panels": [[163, "show-panels"]], "rc": [[163, "rc"]], "size_to_seq": [[199, "size-to-seq"], [47, "size-to-seq"]], "imagej_plugin": [[186, "imagej-plugin"]], "Quantitative Image Analysis of Porous Materials": [[167, "quantitative-image-analysis-of-porous-materials"]], "What is PoreSpy? stars": [[167, "what-is-porespy-stars"]], "Capabilities": [[167, "capabilities"]], "Gallery": [[167, "gallery"]], "How To Cite": [[167, "how-to-cite"]], "Citation": [[167, null]], "seq_to_satn": [[197, "seq-to-satn"], [45, "seq-to-satn"]], "Visualizing a tif image in Paraview": [[166, "visualizing-a-tif-image-in-paraview"]], "prune_branches": [[193, "prune-branches"], [41, "prune-branches"]], "ibip_gpu": [[184, "ibip-gpu"]], "satn_to_seq": [[196, "satn-to-seq"], [44, "satn-to-seq"]], "seed": [[70, "seed"]], "frequency": [[70, "frequency"]], "octaves": [[70, "octaves"]], "gain": [[70, "gain"]], "uniform": [[70, "uniform"]], "distribution": [[66, "distribution"]], "Apply snow_partitioning_n filter": [[49, "apply-snow-partitioning-n-filter"]], "sites": [[76, "sites"]], "r": [[76, "r"], [67, "r"], [77, "r"], [68, "r"]], "clearance": [[76, "clearance"], [77, "clearance"], [79, "clearance"]], "protrusion": [[76, "protrusion"]], "maxiter": [[76, "maxiter"], [67, "maxiter"], [77, "maxiter"], [127, "maxiter"]], "radius": [[74, "radius"], [72, "radius"]], "max_iter": [[74, "max-iter"]], "tol": [[74, "tol"]], "peaks": [[56, "peaks"], [54, "peaks"], [42, "peaks"], [121, "peaks"]], "size": [[57, "size"], [46, "size"], [47, "size"]], "n": [[78, "n"], [81, "n"]], "f": [[78, "f"]], "p": [[78, "p"]], "iterations": [[41, "iterations"]], "Generate line segment:": [[73, "generate-line-segment"]], "inlets and outlets": [[55, "inlets-and-outlets"]], "satn": [[44, "satn"], [157, "satn"], [158, "satn"], [108, "satn"]], "sigma": [[48, "sigma"]], "inlets": [[40, "inlets"], [127, "inlets"]], "access limited": [[40, "access-limited"]], "thickness": [[65, "thickness"], [140, "thickness"]], "im and inlets": [[51, "im-and-inlets"]], "value": [[71, "value"]], "center and corner": [[71, "center-and-corner"]], "SNOW partitioning": [[60, "snow-partitioning"]], "dist": [[75, "dist"]], "nbins": [[75, "nbins"]], "r_min": [[75, "r-min"]], "ncylinders": [[67, "ncylinders"]], "phi_max and theta_max": [[67, "phi-max-and-theta-max"]], "length": [[67, "length"]], "Converting Greyscale Images to Binary": [[62, "converting-greyscale-images-to-binary"]], "The Noise Problem": [[62, "the-noise-problem"]], "Noise Filtering": [[62, "noise-filtering"]], "Non-Edge Preserving Filters": [[62, "non-edge-preserving-filters"]], "Edge Preserving Filters": [[62, "edge-preserving-filters"]], "Applying Non-Local Means to a Stack": [[62, "applying-non-local-means-to-a-stack"]], "im_or_shape": [[79, "im-or-shape"]], "volume_fraction and n_max": [[79, "volume-fraction-and-n-max"]], "Apply reduce_peaks filter": [[42, "apply-reduce-peaks-filter"]], "inlet and outlet": [[69, "inlet-and-outlet"]], "Local thickness": [[59, "local-thickness"]], "Generate Test Image": [[59, "generate-test-image"]], "Apply Local Thickness Filter": [[59, "apply-local-thickness-filter"]], "Extracting PSD as a Histogram": [[59, "extracting-psd-as-a-histogram"]], "PoreSpy Implementation": [[59, "porespy-implementation"]], "Apply region_size filter": [[43, "apply-region-size-filter"]], "Opening and Preparing Images": [[63, "opening-and-preparing-images"]], "Opening a Folder of 2D tif Images": [[63, "opening-a-folder-of-2d-tif-images"]], "Using ImageJ": [[63, "using-imagej"]], "Directly in Python": [[63, "directly-in-python"]], "Convert to Binary": [[63, "convert-to-binary"]], "Opening a 3D Stack": [[63, "opening-a-3d-stack"]], "Saving a 3D Image": [[63, "saving-a-3d-image"]], "2D conn": [[53, "d-conn"]], "Applying chords to 2D and 3D images": [[58, "applying-chords-to-2d-and-3d-images"]], "Demonstration on 2D Image": [[58, "demonstration-on-2d-image"]], "Application to 3D images": [[58, "application-to-3d-images"]], "SNOW partitioning parallel": [[61, "snow-partitioning-parallel"]], "Create a random image of overlapping spheres": [[61, "create-a-random-image-of-overlapping-spheres"]], "Apply SNOW_partitioning_parallel on the binary image": [[61, "apply-snow-partitioning-parallel-on-the-binary-image"]], "offset": [[72, "offset"]], "lattice": [[72, "lattice"]], "blobiness": [[64, "blobiness"]], "Reproducing Images": [[64, "reproducing-images"]], "Generate image for testing": [[140, "generate-image-for-testing"], [135, "generate-image-for-testing"], [142, "generate-image-for-testing"], [138, "generate-image-for-testing"], [145, "generate-image-for-testing"], [148, "generate-image-for-testing"], [139, "generate-image-for-testing"], [141, "generate-image-for-testing"], [153, "generate-image-for-testing"]], "Demonstrate function": [[140, "demonstrate-function"], [145, "demonstrate-function"], [148, "demonstrate-function"], [141, "demonstrate-function"]], "return_indices": [[140, "return-indices"]], "extend_slice [WIP]": [[136, "extend-slice-wip"]], "Create image and variables": [[134, "create-image-and-variables"], [152, "create-image-and-variables"], [143, "create-image-and-variables"], [149, "create-image-and-variables"]], "Apply tool": [[134, "apply-tool"], [138, "apply-tool"], [152, "apply-tool"], [143, "apply-tool"], [149, "apply-tool"], [153, "apply-tool"]], "Image-based invasion percoalation": [[132, "image-based-invasion-percoalation"]], "Generate test image": [[132, "generate-test-image"], [133, "generate-test-image"]], "Apply IBIP to image": [[132, "apply-ibip-to-image"]], "Do some post-processing": [[132, "do-some-post-processing"]], "Run standard MIO for comparison:": [[132, "run-standard-mio-for-comparison"]], "Compare MIO and IBIP at Equal Saturations": [[132, "compare-mio-and-ibip-at-equal-saturations"]], "Comparing Capillary Pressure Curves": [[132, "comparing-capillary-pressure-curves"]], "Compare results with trapping": [[132, "compare-results-with-trapping"]], "Make a movie of the invasion": [[132, "make-a-movie-of-the-invasion"]], "cmap": [[157, "cmap"]], "c_under": [[157, "c-under"]], "c_over": [[157, "c-over"]], "v_under": [[157, "v-under"]], "v_over": [[157, "v-over"]], "fps": [[157, "fps"]], "repeat": [[157, "repeat"]], "SNOW network extraction": [[125, "snow-network-extraction"]], "Demonstration of function": [[135, "demonstration-of-function"]], "Demonstrate tool": [[142, "demonstrate-tool"]], "Basics of Peforming Drainage Simulations with and without Gravity": [[130, "basics-of-peforming-drainage-simulations-with-and-without-gravity"]], "mask": [[156, "mask"]], "slice": [[156, "slice"], [158, "slice"]], "scale": [[148, "scale"]], "ind": [[155, "ind"]], "kwargs": [[155, "kwargs"]], "regions": [[120, "regions"], [114, "regions"], [104, "regions"], [93, "regions"], [103, "regions"], [115, "regions"], [116, "regions"], [105, "regions"]], "phases": [[120, "phases"], [121, "phases"]], "voxel_size": [[120, "voxel-size"], [121, "voxel-size"], [97, "voxel-size"], [92, "voxel-size"], [102, "voxel-size"], [104, "voxel-size"], [103, "voxel-size"], [90, "voxel-size"], [116, "voxel-size"]], "accuracy": [[120, "accuracy"], [121, "accuracy"]], "Predicting diffusive size factors of a rock sample": [[123, "predicting-diffusive-size-factors-of-a-rock-sample"]], "Import libaries and the AI model path": [[123, "import-libaries-and-the-ai-model-path"]], "Reading image of the rock sample": [[123, "reading-image-of-the-rock-sample"]], "Additional info: steps to create a subsection of the rock sample": [[123, "additional-info-steps-to-create-a-subsection-of-the-rock-sample"]], "Segmentation of the image": [[123, "segmentation-of-the-image"]], "Size factor prediction": [[123, "size-factor-prediction"]], "Determining tortuosity using geometric domain decomposition": [[133, "determining-tortuosity-using-geometric-domain-decomposition"]], "Run the function on the image": [[133, "run-the-function-on-the-image"]], "Extracting info from the DataFrame": [[133, "extracting-info-from-the-dataframe"]], "**kwargs": [[158, "kwargs"], [154, "kwargs"]], "Using AI based diffusive size factors for extracted networks": [[126, "using-ai-based-diffusive-size-factors-for-extracted-networks"]], "Trained model and supplementary materials": [[126, "trained-model-and-supplementary-materials"], [115, "trained-model-and-supplementary-materials"]], "Create test image": [[126, "create-test-image"]], "Extract the network": [[126, "extract-the-network"]], "Apply diffusive_size_factor_AI": [[126, "apply-diffusive-size-factor-ai"]], "Compare with finite difference method": [[126, "compare-with-finite-difference-method"]], "SNOW network extraction (advanced)": [[124, "snow-network-extraction-advanced"]], "Generate artificial image": [[124, "generate-artificial-image"]], "Step-by-step application of the SNOW algorithm": [[124, "step-by-step-application-of-the-snow-algorithm"]], "tortuosity_gdd": [[128, "tortuosity-gdd"]], "recombine [WIP]": [[151, "recombine-wip"]], "mesh_region [WIP]": [[147, "mesh-region-wip"]], "randomize_colors [WIP]": [[150, "randomize-colors-wip"]], "results": [[154, "results"]], "Generate Image for Testing": [[137, "generate-image-for-testing"]], "Apply tool and visualize": [[137, "apply-tool-and-visualize"]], "marching_map [WIP]": [[146, "marching-map-wip"]], "isolate_object [WIP]": [[144, "isolate-object-wip"]], "Demonstration": [[139, "demonstration"]], "phase_alias": [[121, "phase-alias"]], "boundary_width": [[121, "boundary-width"]], "sigma and r_max": [[121, "sigma-and-r-max"]], "parallelization": [[121, "parallelization"]], "Finding the Tortuosity (\\tau) of an Image Using tortuosity_fd": [[131, "finding-the-tortuosity-tau-of-an-image-using-tortuosity-fd"]], "Algortihm Description": [[131, "algortihm-description"]], "Importing Packages": [[131, "importing-packages"]], "Generating the image:": [[131, "generating-the-image"]], "Running the algorithm": [[131, "running-the-algorithm"]], "Calling Values From The Output": [[131, "calling-values-from-the-output"]], "Adding boundary pores": [[122, "adding-boundary-pores"]], "Create image": [[122, "create-image"]], "Details of Drainage Simulations with and without Gravity": [[129, "details-of-drainage-simulations-with-and-without-gravity"]], "Creating Multiscale Images": [[84, "creating-multiscale-images"]], "Using blobs of different blobiness": [[84, "using-blobs-of-different-blobiness"]], "Using rsa to insert non-overlapping spheres into blobs": [[84, "using-rsa-to-insert-non-overlapping-spheres-into-blobs"]], "Summary": [[84, "summary"]], "log": [[97, "log"], [92, "log"], [102, "log"], [90, "log"]], "sierpinski_foam2": [[81, "sierpinski-foam2"]], "Measuring fractal dimension by box-counting": [[110, "measuring-fractal-dimension-by-box-counting"]], "Theory": [[110, "theory"]], "Box Counting Method": [[110, "box-counting-method"]], "Mathematical Definition": [[110, "mathematical-definition"]], "Example": [[110, "example"]], "normed": [[96, "normed"]], "Generating fibrous mats": [[85, "generating-fibrous-mats"]], "s": [[108, "s"]], "span": [[108, "span"]], "spheres_from_coords": [[82, "spheres-from-coords"]], "df": [[82, "df"]], "smooth": [[82, "smooth"]], "Create image and extract network": [[119, "create-image-and-extract-network"]], "Plot the pore network": [[119, "plot-the-pore-network"]], "Making blobs": [[87, "making-blobs"]], "props_to_image": [[101, "props-to-image"]], "pc": [[95, "pc"]], "npoints": [[107, "npoints"]], "The lineal path function": [[111, "the-lineal-path-function"]], "network": [[118, "network"], [117, "network"]], "alias": [[118, "alias"]], "Generating Sphere Packings from Digital Rocks Portal": [[86, "generating-sphere-packings-from-digital-rocks-portal"]], "Finney Packing": [[86, "finney-packing"]], "Bidisperse Sphere Packs": [[86, "bidisperse-sphere-packs"]], "srange": [[91, "srange"]], "dmin and n": [[80, "dmin-and-n"]], "ndim": [[80, "ndim"]], "max_size": [[80, "max-size"]], "Using regionprops_3d to analyze properties of each pore": [[113, "using-regionprops-3d-to-analyze-properties-of-each-pore"]], "Generating a test image": [[113, "generating-a-test-image"]], "Segementing void space into regions for individual analysis": [[113, "segementing-void-space-into-regions-for-individual-analysis"]], "Applying regionsprops_3d": [[113, "applying-regionsprops-3d"]], "Listing all available properties": [[113, "listing-all-available-properties"]], "Analyze properties for a single region": [[113, "analyze-properties-for-a-single-region"]], "Extracting one property for all regions as an array": [[113, "extracting-one-property-for-all-regions-as-an-array"]], "Creating a composite image of region images": [[113, "creating-a-composite-image-of-region-images"]], "Creating a colorized image based on region properties": [[113, "creating-a-colorized-image-based-on-region-properties"]], "verts, faces": [[94, "verts-faces"]], "areas": [[103, "areas"]], "model , g_train": [[115, "model-g-train"]], "throat_conns": [[115, "throat-conns"], [116, "throat-conns"]], "Compare with finite difference": [[115, "compare-with-finite-difference"]], "Apply on one conduit": [[115, "apply-on-one-conduit"]], "normalization": [[90, "normalization"]], "Obtaining the porosity profile along each principle axis": [[112, "obtaining-the-porosity-profile-along-each-principle-axis"]], "diffusive_size_factor_DNS": [[116, "diffusive-size-factor-dns"]], "flat_faces": [[83, "flat-faces"]], "r radius": [[83, "r-radius"]], "ncells": [[83, "ncells"]]}, "indexentries": {"apply_chords() (in module porespy.filters)": [[169, "porespy.filters.apply_chords"]], "apply_chords_3d() (in module porespy.filters)": [[170, "porespy.filters.apply_chords_3D"]], "apply_padded() (in module porespy.filters)": [[171, "porespy.filters.apply_padded"]], "chunked_func() (in module porespy.filters)": [[172, "porespy.filters.chunked_func"]], "distance_transform_lin() (in module porespy.filters)": [[173, "porespy.filters.distance_transform_lin"]], "fftmorphology() (in module porespy.filters)": [[174, "porespy.filters.fftmorphology"]], "fill_blind_pores() (in module porespy.filters)": [[175, "porespy.filters.fill_blind_pores"]], "find_disconnected_voxels() (in module porespy.filters)": [[176, "porespy.filters.find_disconnected_voxels"]], "find_dt_artifacts() (in module porespy.filters)": [[177, "porespy.filters.find_dt_artifacts"]], "find_peaks() (in module porespy.filters)": [[178, "porespy.filters.find_peaks"]], "find_trapped_regions() (in module porespy.filters)": [[179, "porespy.filters.find_trapped_regions"]], "flood() (in module porespy.filters)": [[180, "porespy.filters.flood"]], "flood_func() (in module porespy.filters)": [[181, "porespy.filters.flood_func"]], "hold_peaks() (in module porespy.filters)": [[182, "porespy.filters.hold_peaks"]], "ibip() (in module porespy.filters)": [[183, "porespy.filters.ibip"]], "ibip_gpu() (in module porespy.filters)": [[184, "porespy.filters.ibip_gpu"]], "imagej": [[185, "module-imagej"]], "module": [[185, "module-imagej"], [313, "module-porespy.filters"], [314, "module-porespy.filters.imagej"], [315, "module-porespy.generators"], [316, "module-porespy.io"], [317, "module-porespy.metrics"], [318, "module-porespy.networks"], [319, "module-porespy.simulations"], [320, "module-porespy.tools"], [321, "module-porespy.visualization"], [322, "module-porespy"]], "imagej_plugin() (in module porespy.filters.imagej)": [[186, "porespy.filters.imagej.imagej_plugin"]], "imagej_wrapper() (in module porespy.filters.imagej)": [[187, "porespy.filters.imagej.imagej_wrapper"]], "local_thickness() (in module porespy.filters)": [[188, "porespy.filters.local_thickness"]], "nl_means_layered() (in module porespy.filters)": [[189, "porespy.filters.nl_means_layered"]], "nphase_border() (in module porespy.filters)": [[190, "porespy.filters.nphase_border"]], "pc_to_satn() (in module porespy.filters)": [[191, "porespy.filters.pc_to_satn"]], "porosimetry() (in module porespy.filters)": [[192, "porespy.filters.porosimetry"]], "prune_branches() (in module porespy.filters)": [[193, "porespy.filters.prune_branches"]], "reduce_peaks() (in module porespy.filters)": [[194, "porespy.filters.reduce_peaks"]], "region_size() (in module porespy.filters)": [[195, "porespy.filters.region_size"]], "satn_to_seq() (in module porespy.filters)": [[196, "porespy.filters.satn_to_seq"]], "seq_to_satn() (in module porespy.filters)": [[197, "porespy.filters.seq_to_satn"]], "size_to_satn() (in module porespy.filters)": [[198, "porespy.filters.size_to_satn"]], "size_to_seq() (in module porespy.filters)": [[199, "porespy.filters.size_to_seq"]], "snow_partitioning() (in module porespy.filters)": [[200, "porespy.filters.snow_partitioning"]], "snow_partitioning_n() (in module porespy.filters)": [[201, "porespy.filters.snow_partitioning_n"]], "snow_partitioning_parallel() (in module porespy.filters)": [[202, "porespy.filters.snow_partitioning_parallel"]], "trim_disconnected_blobs() (in module porespy.filters)": [[203, "porespy.filters.trim_disconnected_blobs"]], "trim_extrema() (in module porespy.filters)": [[204, "porespy.filters.trim_extrema"]], "trim_floating_solid() (in module porespy.filters)": [[205, "porespy.filters.trim_floating_solid"]], "trim_nearby_peaks() (in module porespy.filters)": [[206, "porespy.filters.trim_nearby_peaks"]], "trim_nonpercolating_paths() (in module porespy.filters)": [[207, "porespy.filters.trim_nonpercolating_paths"]], "trim_saddle_points() (in module porespy.filters)": [[208, "porespy.filters.trim_saddle_points"]], "trim_small_clusters() (in module porespy.filters)": [[209, "porespy.filters.trim_small_clusters"]], "blobs() (in module porespy.generators)": [[210, "porespy.generators.blobs"]], "borders() (in module porespy.generators)": [[211, "porespy.generators.borders"]], "bundle_of_tubes() (in module porespy.generators)": [[212, "porespy.generators.bundle_of_tubes"]], "cylinders() (in module porespy.generators)": [[213, "porespy.generators.cylinders"]], "cylindrical_plug() (in module porespy.generators)": [[214, "porespy.generators.cylindrical_plug"]], "faces() (in module porespy.generators)": [[215, "porespy.generators.faces"]], "fractal_noise() (in module porespy.generators)": [[216, "porespy.generators.fractal_noise"]], "insert_shape() (in module porespy.generators)": [[217, "porespy.generators.insert_shape"]], "lattice_spheres() (in module porespy.generators)": [[218, "porespy.generators.lattice_spheres"]], "line_segment() (in module porespy.generators)": [[219, "porespy.generators.line_segment"]], "overlapping_spheres() (in module porespy.generators)": [[220, "porespy.generators.overlapping_spheres"]], "polydisperse_spheres() (in module porespy.generators)": [[221, "porespy.generators.polydisperse_spheres"]], "pseudo_electrostatic_packing() (in module porespy.generators)": [[222, "porespy.generators.pseudo_electrostatic_packing"]], "pseudo_gravity_packing() (in module porespy.generators)": [[223, "porespy.generators.pseudo_gravity_packing"]], "random_cantor_dust() (in module porespy.generators)": [[224, "porespy.generators.random_cantor_dust"]], "random_spheres() (in module porespy.generators)": [[225, "porespy.generators.random_spheres"]], "rsa() (in module porespy.generators)": [[226, "porespy.generators.rsa"]], "sierpinski_foam() (in module porespy.generators)": [[227, "porespy.generators.sierpinski_foam"]], "voronoi_edges() (in module porespy.generators)": [[228, "porespy.generators.voronoi_edges"]], "dict_to_vtk() (in module porespy.io)": [[229, "porespy.io.dict_to_vtk"]], "open_paraview() (in module porespy.io)": [[230, "porespy.io.open_paraview"]], "openpnm_to_im() (in module porespy.io)": [[231, "porespy.io.openpnm_to_im"]], "spheres_to_comsol() (in module porespy.io)": [[232, "porespy.io.spheres_to_comsol"]], "to_palabos() (in module porespy.io)": [[233, "porespy.io.to_palabos"]], "to_paraview() (in module porespy.io)": [[234, "porespy.io.to_paraview"]], "to_stl() (in module porespy.io)": [[235, "porespy.io.to_stl"]], "to_vtk() (in module porespy.io)": [[236, "porespy.io.to_vtk"]], "boxcount() (in module porespy.metrics)": [[237, "porespy.metrics.boxcount"]], "chord_counts() (in module porespy.metrics)": [[238, "porespy.metrics.chord_counts"]], "chord_length_distribution() (in module porespy.metrics)": [[239, "porespy.metrics.chord_length_distribution"]], "find_h() (in module porespy.metrics)": [[240, "porespy.metrics.find_h"]], "lineal_path_distribution() (in module porespy.metrics)": [[241, "porespy.metrics.lineal_path_distribution"]], "mesh_surface_area() (in module porespy.metrics)": [[242, "porespy.metrics.mesh_surface_area"]], "mesh_volume() (in module porespy.metrics)": [[243, "porespy.metrics.mesh_volume"]], "pc_curve() (in module porespy.metrics)": [[244, "porespy.metrics.pc_curve"]], "pc_curve_from_ibip() (in module porespy.metrics)": [[245, "porespy.metrics.pc_curve_from_ibip"]], "pc_curve_from_mio() (in module porespy.metrics)": [[246, "porespy.metrics.pc_curve_from_mio"]], "phase_fraction() (in module porespy.metrics)": [[247, "porespy.metrics.phase_fraction"]], "pore_size_distribution() (in module porespy.metrics)": [[248, "porespy.metrics.pore_size_distribution"]], "porosity() (in module porespy.metrics)": [[249, "porespy.metrics.porosity"]], "porosity_profile() (in module porespy.metrics)": [[250, "porespy.metrics.porosity_profile"]], "prop_to_image() (in module porespy.metrics)": [[251, "porespy.metrics.prop_to_image"]], "props_to_dataframe() (in module porespy.metrics)": [[252, "porespy.metrics.props_to_DataFrame"]], "radial_density_distribution() (in module porespy.metrics)": [[253, "porespy.metrics.radial_density_distribution"]], "region_interface_areas() (in module porespy.metrics)": [[254, "porespy.metrics.region_interface_areas"]], "region_surface_areas() (in module porespy.metrics)": [[255, "porespy.metrics.region_surface_areas"]], "region_volumes() (in module porespy.metrics)": [[256, "porespy.metrics.region_volumes"]], "regionprops_3d() (in module porespy.metrics)": [[257, "porespy.metrics.regionprops_3D"]], "representative_elementary_volume() (in module porespy.metrics)": [[258, "porespy.metrics.representative_elementary_volume"]], "satn_profile() (in module porespy.metrics)": [[259, "porespy.metrics.satn_profile"]], "two_point_correlation() (in module porespy.metrics)": [[260, "porespy.metrics.two_point_correlation"]], "add_boundary_regions() (in module porespy.networks)": [[261, "porespy.networks.add_boundary_regions"]], "diffusive_size_factor_ai() (in module porespy.networks)": [[262, "porespy.networks.diffusive_size_factor_AI"]], "generate_voxel_image() (in module porespy.networks)": [[263, "porespy.networks.generate_voxel_image"]], "label_boundaries() (in module porespy.networks)": [[264, "porespy.networks.label_boundaries"]], "label_phases() (in module porespy.networks)": [[265, "porespy.networks.label_phases"]], "map_to_regions() (in module porespy.networks)": [[266, "porespy.networks.map_to_regions"]], "maximal_ball_wrapper() (in module porespy.networks)": [[267, "porespy.networks.maximal_ball_wrapper"]], "regions_to_network() (in module porespy.networks)": [[268, "porespy.networks.regions_to_network"]], "snow2() (in module porespy.networks)": [[269, "porespy.networks.snow2"]], "drainage() (in module porespy.simulations)": [[270, "porespy.simulations.drainage"]], "tortuosity_fd() (in module porespy.simulations)": [[271, "porespy.simulations.tortuosity_fd"]], "results (class in porespy.tools)": [[272, "porespy.tools.Results"]], "align_image_with_openpnm() (in module porespy.tools)": [[273, "porespy.tools.align_image_with_openpnm"]], "bbox_to_slices() (in module porespy.tools)": [[274, "porespy.tools.bbox_to_slices"]], "extend_slice() (in module porespy.tools)": [[275, "porespy.tools.extend_slice"]], "extract_cylinder() (in module porespy.tools)": [[276, "porespy.tools.extract_cylinder"]], "extract_regions() (in module porespy.tools)": [[277, "porespy.tools.extract_regions"]], "extract_subsection() (in module porespy.tools)": [[278, "porespy.tools.extract_subsection"]], "find_outer_region() (in module porespy.tools)": [[279, "porespy.tools.find_outer_region"]], "get_border() (in module porespy.tools)": [[280, "porespy.tools.get_border"]], "get_planes() (in module porespy.tools)": [[281, "porespy.tools.get_planes"]], "get_tqdm() (in module porespy.tools)": [[282, "porespy.tools.get_tqdm"]], "in_hull() (in module porespy.tools)": [[283, "porespy.tools.in_hull"]], "insert_cylinder() (in module porespy.tools)": [[284, "porespy.tools.insert_cylinder"]], "insert_sphere() (in module porespy.tools)": [[285, "porespy.tools.insert_sphere"]], "isolate_object() (in module porespy.tools)": [[286, "porespy.tools.isolate_object"]], "make_contiguous() (in module porespy.tools)": [[287, "porespy.tools.make_contiguous"]], "marching_map() (in module porespy.tools)": [[288, "porespy.tools.marching_map"]], "mesh_region() (in module porespy.tools)": [[289, "porespy.tools.mesh_region"]], "norm_to_uniform() (in module porespy.tools)": [[290, "porespy.tools.norm_to_uniform"]], "overlay() (in module porespy.tools)": [[291, "porespy.tools.overlay"]], "ps_ball() (in module porespy.tools)": [[292, "porespy.tools.ps_ball"]], "ps_disk() (in module porespy.tools)": [[293, "porespy.tools.ps_disk"]], "ps_rect() (in module porespy.tools)": [[294, "porespy.tools.ps_rect"]], "ps_round() (in module porespy.tools)": [[295, "porespy.tools.ps_round"]], "randomize_colors() (in module porespy.tools)": [[296, "porespy.tools.randomize_colors"]], "recombine() (in module porespy.tools)": [[297, "porespy.tools.recombine"]], "sanitize_filename() (in module porespy.tools)": [[298, "porespy.tools.sanitize_filename"]], "show_docstring() (in module porespy.tools)": [[299, "porespy.tools.show_docstring"]], "subdivide() (in module porespy.tools)": [[300, "porespy.tools.subdivide"]], "unpad() (in module porespy.tools)": [[301, "porespy.tools.unpad"]], "bar() (in module porespy.visualization)": [[302, "porespy.visualization.bar"]], "imshow() (in module porespy.visualization)": [[303, "porespy.visualization.imshow"]], "prep_for_imshow() (in module porespy.visualization)": [[304, "porespy.visualization.prep_for_imshow"]], "satn_to_movie() (in module porespy.visualization)": [[305, "porespy.visualization.satn_to_movie"]], "satn_to_panels() (in module porespy.visualization)": [[306, "porespy.visualization.satn_to_panels"]], "sem() (in module porespy.visualization)": [[307, "porespy.visualization.sem"]], "set_mpl_style() (in module porespy.visualization)": [[308, "porespy.visualization.set_mpl_style"]], "show_3d() (in module porespy.visualization)": [[309, "porespy.visualization.show_3D"]], "show_mesh() (in module porespy.visualization)": [[310, "porespy.visualization.show_mesh"]], "show_planes() (in module porespy.visualization)": [[311, "porespy.visualization.show_planes"]], "xray() (in module porespy.visualization)": [[312, "porespy.visualization.xray"]], "porespy.filters": [[313, "module-porespy.filters"]], "porespy.filters.imagej": [[314, "module-porespy.filters.imagej"]], "porespy.generators": [[315, "module-porespy.generators"]], "porespy.io": [[316, "module-porespy.io"]], "porespy.metrics": [[317, "module-porespy.metrics"]], "porespy.networks": [[318, "module-porespy.networks"]], "porespy.simulations": [[319, "module-porespy.simulations"]], "porespy.tools": [[320, "module-porespy.tools"]], "porespy.visualization": [[321, "module-porespy.visualization"]], "porespy": [[322, "module-porespy"]]}}) \ No newline at end of file +Search.setIndex({"docnames": ["_examples/filters/index", "_examples/filters/reference", "_examples/filters/tutorials", "_examples/general/index", "_examples/generators/index", "_examples/generators/reference", "_examples/generators/tutorials", "_examples/index", "_examples/metrics/index", "_examples/metrics/reference", "_examples/metrics/tutorials", "_examples/networks/index", "_examples/networks/reference", "_examples/networks/tutorials", "_examples/simulations/index", "_examples/simulations/tutorials", "_examples/tools/index", "_examples/tools/reference", "_examples/visualization/index", "_examples/visualization/reference", "_examples/visualization/tutorials", "basic_usage", "examples/filters/reference/apply_chords", "examples/filters/reference/apply_chords_3D", "examples/filters/reference/apply_padded", "examples/filters/reference/chunked_func", "examples/filters/reference/distance_transform_lin", "examples/filters/reference/fftmorphology", "examples/filters/reference/fill_blind_pores", "examples/filters/reference/find_disconnected_voxels", "examples/filters/reference/find_dt_artifacts", "examples/filters/reference/find_peaks", "examples/filters/reference/find_trapped_regions", "examples/filters/reference/flood", "examples/filters/reference/flood_func", "examples/filters/reference/hold_peaks", "examples/filters/reference/local_thickness", "examples/filters/reference/nl_means_layered", "examples/filters/reference/nphase_border", "examples/filters/reference/pc_to_satn", "examples/filters/reference/porosimetry", "examples/filters/reference/prune_branches", "examples/filters/reference/reduce_peaks", "examples/filters/reference/region_size", "examples/filters/reference/satn_to_seq", "examples/filters/reference/seq_to_satn", "examples/filters/reference/size_to_satn", "examples/filters/reference/size_to_seq", "examples/filters/reference/snow_partitioning", "examples/filters/reference/snow_partitioning_n", "examples/filters/reference/snow_partitioning_parallel", "examples/filters/reference/trim_disconnected_blobs", "examples/filters/reference/trim_extrema", "examples/filters/reference/trim_floating_solid", "examples/filters/reference/trim_nearby_peaks", "examples/filters/reference/trim_nonpercolating_paths", "examples/filters/reference/trim_saddle_points", "examples/filters/reference/trim_small_clusters", "examples/filters/tutorials/adding_chords", "examples/filters/tutorials/local_thickness", "examples/filters/tutorials/snow_partitioning", "examples/filters/tutorials/snow_partitioning_parallel", "examples/general/denoising_and_segmenting_images", "examples/general/loading_images", "examples/generators/reference/blobs", "examples/generators/reference/borders", "examples/generators/reference/bundle_of_tubes", "examples/generators/reference/cylinders", "examples/generators/reference/cylindrical_plug", "examples/generators/reference/faces", "examples/generators/reference/fractal_noise", "examples/generators/reference/insert_shape", "examples/generators/reference/lattice_spheres", "examples/generators/reference/line_segment", "examples/generators/reference/overlapping_spheres", "examples/generators/reference/polydisperse_spheres", "examples/generators/reference/pseudo_electrostatic_packing", "examples/generators/reference/pseudo_gravity_packing", "examples/generators/reference/random_cantor_dust", "examples/generators/reference/rsa", "examples/generators/reference/sierpinski_foam", "examples/generators/reference/sierpinski_foam2", "examples/generators/reference/spheres_from_coords", "examples/generators/reference/voronoi_edges", "examples/generators/tutorials/Creating_Multiscale_Images", "examples/generators/tutorials/cylinders", "examples/generators/tutorials/generate_spheres_packings", "examples/generators/tutorials/making_blobs", "examples/metrics/reference/boxcount", "examples/metrics/reference/chord_counts", "examples/metrics/reference/chord_length_distribution", "examples/metrics/reference/find_h", "examples/metrics/reference/lineal_path_distribution", "examples/metrics/reference/mesh__volume", "examples/metrics/reference/mesh_surface_area", "examples/metrics/reference/pc_curve", "examples/metrics/reference/phase_fraction", "examples/metrics/reference/pore_size_distribution", "examples/metrics/reference/porosity", "examples/metrics/reference/porosity_profile", "examples/metrics/reference/props_to_DataFrame", "examples/metrics/reference/props_to_image", "examples/metrics/reference/radial_density_distribution", "examples/metrics/reference/region_interface_areas", "examples/metrics/reference/region_surface_areas", "examples/metrics/reference/region_volumes", "examples/metrics/reference/regionprops_3D", "examples/metrics/reference/representative_elementary_volume", "examples/metrics/reference/satn_profile", "examples/metrics/reference/two_point_correlation", "examples/metrics/tutorials/computing_fractal_dim", "examples/metrics/tutorials/lineal_path_function", "examples/metrics/tutorials/porosity_profiles", "examples/metrics/tutorials/regionprops_3d", "examples/networks/reference/add_boundary_regions", "examples/networks/reference/diffusive_size_factor_AI", "examples/networks/reference/diffusive_size_factor_DNS", "examples/networks/reference/label_boundaries", "examples/networks/reference/label_phases", "examples/networks/reference/map_to_regions", "examples/networks/reference/regions_to_network", "examples/networks/reference/snow2", "examples/networks/tutorials/adding_boundary_pores", "examples/networks/tutorials/predicting_diffusive_size_factors_rock_sample", "examples/networks/tutorials/snow_advanced", "examples/networks/tutorials/snow_basic", "examples/networks/tutorials/using_diffusive_size_factor_AI_with_snow", "examples/simulations/reference/ibip", "examples/simulations/reference/tortuosity_gdd", "examples/simulations/tutorials/drainage_with_gravity_advanced", "examples/simulations/tutorials/drainage_with_gravity_basic", "examples/simulations/tutorials/finding_tortuosity_from_image", "examples/simulations/tutorials/using_ibip", "examples/simulations/tutorials/using_tortuosity_gdd", "examples/tools/reference/align_image_with_openpnm", "examples/tools/reference/bbox_to_slices", "examples/tools/reference/extend_slice", "examples/tools/reference/extract_cylinder", "examples/tools/reference/extract_regions", "examples/tools/reference/extract_subsection", "examples/tools/reference/get_border", "examples/tools/reference/get_planes", "examples/tools/reference/insert_cylinder", "examples/tools/reference/insert_sphere", "examples/tools/reference/isolate_object", 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28, 29, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 102, 103, 104, 105, 106, 107, 108, 109, 110, 112, 113, 114, 115, 116, 118, 120, 121, 122, 123, 124, 125, 126, 127, 129, 130, 132, 133, 135, 139, 140, 148, 154, 155, 156, 157, 158, 161, 163, 164, 165, 166, 169, 170, 171, 172, 173, 174, 175, 176, 177, 178, 179, 180, 181, 182, 185, 186, 187, 188, 189, 191, 192, 193, 194, 196, 197, 198, 199, 200, 201, 202, 203, 204, 205, 206, 207, 208, 209, 210, 211, 212, 213, 214, 215, 216, 217, 218, 219, 220, 221, 222, 223, 224, 225, 226, 227, 228, 229, 231, 232, 233, 234, 235, 236, 237, 238, 239, 240, 241, 242, 243, 244, 248, 250, 251, 253, 254, 255, 257, 258, 259, 260, 261, 262, 263, 264, 265, 266, 267, 268, 269, 270, 271, 273, 274, 275, 276, 279, 280, 281, 282, 283, 285, 286, 289, 290, 292, 293, 294, 295, 296, 297, 300, 301, 302, 303, 304, 305, 306, 309, 312], "best": [7, 86, 125, 168], "wai": [7, 21, 62, 69, 84, 110, 121, 125, 129, 130, 131, 172, 188, 192, 195, 201, 222, 223, 225, 226, 320], "learn": [7, 85, 86, 113, 115, 126], "openpnm": [7, 48, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 131, 133, 231, 263, 268, 269, 273], "like": [7, 21, 35, 58, 59, 62, 63, 76, 86, 88, 91, 106, 108, 113, 114, 120, 121, 129, 132, 138, 175, 192, 194, 203, 205, 215, 265, 270, 272, 276], "anyth": [7, 34, 63, 71], "i": [7, 21, 22, 23, 24, 25, 27, 28, 29, 31, 32, 34, 36, 37, 40, 41, 43, 46, 47, 48, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 66, 67, 68, 69, 70, 72, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 102, 103, 104, 105, 106, 108, 110, 111, 112, 113, 115, 116, 117, 118, 120, 121, 122, 123, 124, 125, 126, 129, 130, 131, 132, 133, 137, 138, 152, 154, 155, 156, 157, 158, 159, 160, 161, 162, 163, 164, 165, 166, 168, 169, 170, 171, 172, 173, 175, 176, 177, 178, 179, 180, 181, 182, 185, 188, 189, 191, 192, 193, 194, 195, 197, 198, 199, 200, 201, 203, 204, 205, 206, 207, 208, 209, 210, 211, 212, 213, 214, 215, 216, 217, 218, 220, 221, 222, 223, 224, 225, 226, 227, 228, 229, 230, 231, 232, 234, 235, 236, 237, 238, 239, 240, 241, 244, 245, 246, 247, 248, 249, 250, 251, 252, 253, 254, 255, 256, 257, 258, 259, 260, 261, 262, 263, 264, 265, 266, 267, 268, 269, 270, 273, 274, 275, 276, 279, 280, 281, 282, 284, 285, 286, 287, 288, 289, 290, 296, 299, 300, 301, 302, 303, 304, 306, 309, 312, 313, 314, 315, 316, 317, 318, 319, 320, 321, 322], "experi": [7, 40, 59, 62, 70, 130, 132, 189, 192, 244, 312], "In": [7, 28, 32, 47, 53, 59, 62, 63, 65, 70, 71, 72, 76, 79, 81, 82, 85, 86, 95, 98, 106, 107, 110, 111, 115, 116, 118, 121, 122, 123, 124, 125, 129, 130, 131, 132, 138, 166, 172, 177, 182, 186, 191, 201, 211, 217, 222, 223, 225, 226, 239, 280], "thi": [7, 22, 23, 24, 25, 28, 29, 30, 31, 32, 34, 36, 37, 38, 40, 41, 44, 45, 46, 47, 48, 49, 51, 54, 55, 57, 58, 59, 61, 62, 63, 66, 67, 68, 69, 70, 71, 72, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 102, 103, 104, 105, 106, 107, 108, 110, 111, 112, 113, 114, 115, 116, 117, 120, 121, 122, 123, 124, 125, 126, 129, 130, 131, 132, 133, 137, 138, 139, 148, 149, 153, 154, 155, 156, 157, 158, 159, 160, 161, 162, 163, 164, 165, 166, 168, 169, 170, 171, 172, 174, 175, 176, 177, 178, 180, 181, 182, 183, 184, 185, 186, 188, 189, 192, 193, 195, 197, 198, 200, 201, 204, 205, 206, 207, 209, 210, 211, 212, 213, 215, 216, 220, 221, 222, 223, 224, 225, 226, 228, 230, 232, 235, 236, 237, 239, 241, 242, 244, 245, 246, 248, 249, 251, 252, 253, 254, 255, 257, 258, 259, 260, 261, 262, 266, 267, 268, 269, 270, 271, 272, 273, 274, 275, 276, 279, 280, 284, 286, 287, 288, 296, 300, 301, 302, 303, 304, 306, 309, 311, 313, 314, 315, 316, 317, 318, 319, 320, 321], "page": [7, 168, 239, 253], "you": [7, 21, 59, 63, 67, 70, 79, 80, 86, 114, 121, 123, 124, 125, 139, 140, 155, 156, 160, 166, 167, 168, 181, 185, 235, 236, 239, 241, 248, 252, 253, 269, 302, 322], "can": [7, 21, 22, 23, 24, 28, 32, 33, 34, 36, 37, 40, 43, 46, 47, 48, 51, 53, 58, 59, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 75, 76, 77, 78, 79, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 101, 102, 103, 104, 105, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 135, 138, 140, 148, 155, 156, 157, 158, 159, 160, 161, 162, 166, 168, 169, 170, 172, 174, 175, 181, 185, 188, 192, 200, 202, 203, 205, 211, 213, 214, 215, 216, 217, 220, 221, 222, 223, 225, 226, 227, 229, 232, 233, 234, 235, 236, 238, 239, 240, 241, 244, 245, 248, 249, 251, 252, 253, 255, 257, 258, 260, 267, 268, 269, 273, 274, 275, 276, 278, 279, 280, 283, 296, 300, 303, 304, 305, 309, 311, 317], "find": [7, 14, 15, 29, 31, 32, 42, 48, 54, 62, 86, 90, 91, 92, 107, 113, 121, 124, 125, 126, 129, 132, 138, 178, 179, 188, 190, 192, 195, 200, 201, 208, 231, 232, 238, 243, 253, 255, 256, 258, 263, 269, 279, 288, 322], "lot": [7, 32, 62, 125, 129], "help": [7, 48, 62, 90, 92, 113, 121, 123, 124, 137, 239, 241, 248, 253, 257], "get": [7, 40, 58, 59, 62, 63, 64, 70, 80, 86, 90, 92, 114, 125, 129, 168, 185, 213, 221, 222, 223, 225, 226, 235, 236, 238, 249], "start": [7, 25, 26, 50, 58, 59, 69, 78, 79, 84, 86, 87, 91, 92, 108, 111, 112, 113, 121, 124, 125, 129, 130, 131, 168, 185, 191, 201, 219, 240, 259, 262, 266, 275, 287, 288], "ar": [7, 21, 22, 23, 26, 28, 29, 30, 32, 33, 34, 36, 37, 38, 39, 40, 42, 44, 45, 46, 47, 48, 51, 52, 53, 54, 55, 56, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 70, 72, 75, 76, 80, 81, 82, 83, 84, 85, 86, 88, 90, 91, 92, 96, 98, 103, 106, 108, 110, 111, 112, 113, 114, 115, 117, 120, 121, 122, 123, 124, 126, 127, 129, 130, 131, 132, 133, 135, 140, 152, 154, 155, 156, 157, 158, 163, 166, 167, 168, 169, 170, 171, 172, 173, 174, 175, 176, 177, 179, 182, 185, 188, 189, 191, 192, 194, 196, 197, 198, 199, 200, 201, 202, 204, 205, 206, 207, 208, 209, 210, 211, 213, 216, 217, 218, 222, 223, 225, 226, 228, 229, 230, 231, 232, 235, 236, 239, 244, 247, 249, 250, 253, 254, 256, 257, 259, 260, 263, 265, 266, 268, 269, 270, 271, 279, 280, 281, 283, 285, 287, 296, 302, 303, 304, 305, 306, 307, 317], "categor": 7, "follow": [7, 21, 32, 58, 59, 62, 63, 67, 68, 69, 86, 87, 88, 97, 107, 111, 115, 118, 120, 121, 126, 129, 130, 132, 133, 148, 167, 168, 178, 192, 200, 201, 237, 239, 241, 244, 248, 253, 254, 257, 258, 259, 269, 270, 271, 304], "categori": 7, "measur": [7, 8, 10, 33, 88, 89, 94, 111, 120, 121, 173, 180, 242, 244, 257, 259, 268, 289, 310], "fractal": [7, 8, 10, 78, 80, 81, 88, 216, 237], "dimens": [7, 8, 10, 67, 68, 71, 86, 88, 122, 123, 129, 212, 217, 227, 231, 235, 236, 237, 263, 275, 300], "box": [7, 8, 10, 63, 85, 88, 107, 135, 237, 257, 258, 274, 277], "count": [7, 8, 10, 58, 88, 90, 99, 111, 115, 120, 132, 148, 222, 223, 225, 226, 237, 239, 247, 268, 269], "lineal": [7, 8, 10, 92], "path": [7, 8, 10, 55, 62, 92, 115, 126, 131, 175, 186, 187, 207, 229, 230, 232, 233, 234, 235, 236, 241, 267, 288], "function": [7, 8, 10, 21, 23, 24, 25, 28, 29, 30, 31, 32, 33, 34, 37, 38, 40, 41, 44, 45, 46, 47, 48, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 67, 68, 69, 70, 72, 74, 76, 79, 80, 82, 84, 85, 86, 87, 88, 90, 91, 92, 94, 95, 97, 98, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 112, 113, 114, 115, 116, 117, 118, 120, 121, 122, 123, 124, 125, 126, 127, 129, 130, 131, 132, 138, 149, 154, 155, 156, 158, 161, 162, 163, 167, 168, 171, 172, 174, 176, 178, 180, 181, 183, 184, 185, 186, 188, 189, 192, 195, 201, 203, 204, 207, 210, 212, 213, 216, 220, 221, 222, 223, 224, 225, 226, 228, 238, 239, 240, 241, 242, 244, 245, 246, 248, 249, 252, 253, 257, 258, 260, 261, 264, 265, 266, 267, 269, 272, 274, 275, 279, 282, 284, 286, 288, 289, 296, 299, 300, 302, 306, 307, 310, 312], "obtain": [7, 8, 10, 45, 46, 59, 63, 79, 85, 87, 92, 108, 115, 120, 121, 123, 126, 130, 132, 133, 138, 167, 188, 192, 215, 221, 240, 248, 251, 252, 257, 268, 276, 281, 297, 310], "poros": [7, 8, 9, 10, 21, 22, 26, 28, 31, 32, 34, 39, 41, 44, 45, 46, 47, 48, 49, 51, 52, 53, 55, 56, 57, 60, 61, 65, 68, 70, 84, 85, 87, 91, 92, 95, 99, 100, 101, 107, 108, 111, 113, 115, 116, 117, 118, 119, 120, 121, 123, 124, 125, 126, 127, 129, 130, 131, 132, 133, 138, 153, 156, 159, 165, 174, 200, 210, 213, 220, 221, 231, 247, 250, 258, 263, 271], "profil": [7, 8, 10, 52, 91, 99, 107, 108, 240, 250, 258, 259], "along": [7, 8, 10, 22, 26, 35, 37, 58, 62, 83, 89, 92, 99, 108, 111, 120, 121, 131, 140, 155, 156, 158, 159, 163, 165, 169, 173, 182, 189, 190, 211, 214, 218, 223, 241, 244, 250, 259, 271, 276, 280, 281, 288, 300, 304, 306, 307, 312], "each": [7, 8, 10, 21, 22, 23, 24, 25, 32, 33, 34, 35, 36, 37, 38, 40, 43, 50, 58, 59, 61, 62, 66, 70, 73, 78, 82, 83, 87, 88, 89, 90, 94, 96, 97, 102, 103, 104, 105, 106, 111, 114, 118, 120, 121, 122, 124, 125, 127, 129, 130, 132, 133, 157, 158, 160, 164, 166, 169, 171, 172, 173, 177, 179, 180, 181, 182, 185, 188, 189, 191, 195, 196, 197, 198, 199, 201, 202, 204, 206, 218, 221, 222, 223, 224, 225, 226, 228, 229, 231, 235, 236, 237, 238, 239, 240, 241, 242, 244, 247, 248, 250, 251, 252, 253, 254, 255, 256, 257, 258, 259, 260, 261, 263, 264, 266, 268, 269, 270, 275, 281, 288, 296, 300, 301, 306, 311, 322], "principl": [7, 8, 10, 21, 23, 170, 201, 270, 281], "axi": [7, 8, 10, 23, 24, 25, 27, 28, 29, 30, 31, 32, 33, 34, 36, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 62, 63, 64, 65, 66, 67, 69, 70, 71, 72, 73, 74, 75, 76, 78, 79, 80, 81, 82, 83, 84, 86, 88, 89, 90, 91, 92, 93, 94, 96, 97, 98, 102, 103, 104, 105, 107, 109, 111, 114, 115, 116, 117, 119, 121, 122, 125, 126, 127, 131, 132, 133, 134, 135, 137, 138, 139, 140, 141, 142, 143, 145, 148, 149, 152, 153, 157, 161, 164, 166, 169, 171, 173, 182, 189, 190, 202, 213, 214, 215, 218, 223, 250, 257, 259, 261, 264, 269, 270, 271, 276, 281, 300, 301, 303, 304, 306, 307, 310, 312], "us": [7, 8, 10, 11, 13, 14, 15, 24, 25, 27, 28, 29, 31, 32, 33, 36, 37, 40, 44, 45, 46, 47, 48, 50, 51, 52, 54, 56, 58, 59, 60, 61, 62, 66, 67, 68, 69, 70, 74, 75, 76, 79, 82, 85, 86, 88, 89, 90, 93, 94, 95, 97, 100, 103, 104, 105, 106, 107, 109, 110, 111, 112, 115, 116, 117, 118, 120, 121, 122, 123, 124, 125, 127, 129, 130, 132, 135, 137, 138, 140, 154, 156, 157, 158, 159, 160, 161, 162, 163, 165, 166, 167, 168, 171, 172, 174, 178, 179, 180, 181, 183, 184, 185, 188, 189, 190, 192, 194, 195, 198, 199, 200, 201, 202, 206, 207, 208, 210, 211, 212, 213, 214, 216, 217, 218, 220, 221, 222, 223, 224, 225, 226, 228, 232, 233, 235, 236, 237, 238, 239, 240, 241, 243, 244, 245, 246, 248, 249, 253, 254, 255, 256, 257, 258, 259, 260, 261, 262, 268, 269, 270, 271, 272, 273, 274, 275, 276, 279, 280, 282, 288, 289, 290, 296, 297, 299, 300, 301, 302, 303, 304, 305, 306, 307, 309, 311, 312, 322], "regionprops_3d": [7, 8, 9, 10, 100, 101, 251, 252], "analyz": [7, 8, 10, 21, 32, 51, 80, 81, 84, 102, 110, 118, 120, 124, 129, 131, 167, 179, 253, 268, 271], "properti": [7, 8, 10, 80, 81, 106, 120, 121, 124, 125, 126, 129, 167, 229, 239, 241, 251, 252, 253, 268, 269], "pore": [7, 8, 10, 11, 13, 21, 28, 40, 48, 55, 58, 59, 64, 66, 79, 84, 94, 97, 103, 104, 105, 114, 117, 118, 120, 121, 123, 124, 125, 126, 130, 131, 133, 156, 167, 171, 175, 178, 188, 190, 192, 200, 201, 202, 206, 208, 210, 212, 213, 218, 220, 221, 225, 226, 228, 231, 233, 234, 239, 248, 249, 253, 254, 255, 262, 263, 264, 265, 266, 268, 269, 273, 313, 318], "boxcount": [7, 8, 9, 110], "chord_count": [7, 8, 9, 90], "chord_length_distribut": [7, 8, 9, 58, 302], "find_h": [7, 8, 9], "lineal_path_distribut": [7, 8, 9, 111], "mesh_volum": [7, 8, 9, 105], "mesh_surface_area": [7, 8, 9, 104, 257], "pc_curv": [7, 8, 9, 129, 132, 245, 246], "phase_fract": [7, 8, 9, 249], "pore_size_distribut": [7, 8, 9, 21, 59, 84, 102, 154], "porosity_profil": [7, 8, 9, 112], "props_to_datafram": [7, 8, 9, 113, 251], "props_to_imag": [7, 8, 9], "radial_density_distribut": [7, 8, 9, 154], "region_interface_area": [7, 8, 9], "region_surface_area": [7, 8, 9, 94, 103, 254], "region_volum": [7, 8, 9, 117, 118, 120, 121, 124, 125, 126, 268], "representative_elementary_volum": [7, 8, 9], "satn_profil": [7, 8, 9, 91, 240], "two_point_correl": [7, 8, 9], "ad": [7, 11, 13, 58, 59, 63, 67, 70, 71, 74, 75, 79, 85, 106, 113, 114, 117, 118, 121, 123, 129, 153, 168, 213, 215, 217, 222, 223, 225, 226, 239, 241, 244, 248, 249, 253, 254, 258, 264, 265, 269, 270, 301], "boundari": [7, 11, 13, 28, 30, 92, 113, 114, 117, 121, 125, 177, 179, 190, 192, 217, 228, 261, 264, 269, 271, 275], "predict": [7, 11, 13, 115, 116, 126, 213, 231, 262, 263], "diffus": [7, 11, 13, 115, 116, 131, 133, 262], "size": [7, 11, 13, 21, 32, 34, 37, 43, 44, 45, 48, 49, 50, 58, 59, 60, 62, 64, 66, 67, 70, 72, 74, 75, 78, 80, 81, 84, 86, 87, 88, 90, 92, 97, 98, 102, 103, 104, 107, 110, 112, 115, 116, 120, 121, 127, 129, 131, 132, 133, 139, 172, 176, 178, 179, 180, 181, 188, 189, 192, 193, 195, 196, 198, 199, 206, 209, 210, 211, 212, 213, 214, 216, 218, 220, 221, 223, 224, 227, 228, 229, 235, 236, 237, 239, 241, 244, 248, 251, 253, 258, 259, 260, 262, 267, 268, 278, 279, 286, 287, 288, 289, 294, 296, 313], "factor": [7, 11, 13, 78, 115, 116, 131, 262], "sampl": [7, 11, 13, 62, 63, 107, 112, 132, 165, 189, 192, 258, 279], "extract": [7, 11, 13, 28, 40, 48, 100, 107, 114, 115, 116, 117, 118, 120, 121, 122, 123, 137, 138, 156, 158, 167, 171, 200, 201, 206, 208, 255, 257, 258, 262, 266, 268, 269, 276, 277, 278, 281, 286, 300, 306], "advanc": [7, 11, 13, 61, 132, 258, 269], "ai": [7, 11, 13, 115], "base": [7, 11, 13, 14, 15, 21, 33, 36, 40, 62, 70, 90, 92, 97, 102, 105, 115, 117, 121, 123, 124, 125, 127, 130, 157, 158, 167, 168, 174, 180, 181, 200, 201, 206, 208, 239, 241, 248, 253, 264, 265, 269, 270, 282, 287], "train": [7, 11, 13, 123, 262], 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270, 289], "common": [21, 59, 115, 167, 223, 290], "we": [21, 25, 32, 50, 53, 58, 59, 60, 62, 63, 69, 70, 82, 84, 85, 86, 87, 89, 90, 91, 92, 93, 94, 96, 97, 102, 103, 104, 105, 106, 107, 109, 112, 113, 115, 116, 117, 118, 120, 121, 122, 123, 124, 126, 129, 130, 131, 132, 138, 156, 157, 158, 166, 168, 188], "have": [21, 22, 33, 40, 62, 63, 68, 69, 71, 76, 77, 79, 82, 83, 84, 95, 98, 106, 107, 110, 114, 115, 116, 117, 118, 120, 121, 123, 124, 126, 129, 130, 132, 158, 168, 169, 172, 174, 177, 186, 189, 191, 196, 198, 199, 200, 206, 216, 218, 225, 226, 239, 249, 253, 269, 292, 293, 295, 296, 297, 298, 302], "mani": [21, 40, 41, 58, 59, 62, 63, 67, 75, 79, 85, 113, 122, 124, 129, 138, 163, 167, 172, 181, 192, 209], "more": [21, 25, 37, 38, 41, 50, 62, 70, 72, 85, 86, 87, 90, 98, 112, 113, 117, 121, 123, 129, 130, 133, 138, 156, 166, 171, 174, 179, 189, 190, 216, 239, 241, 244, 248, 253, 254, 255, 257, 259, 260, 270, 301, 312], "exampl": [21, 59, 63, 80, 81, 85, 111, 112, 113, 115, 116, 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74, 75, 76, 77, 79, 85, 97, 121, 152, 172, 202, 213, 218, 220, 221, 222, 223, 225, 226, 232, 248, 259, 297, 300], "analysi": [21, 63, 110, 179, 232, 241, 253, 269, 322], "histogram": [21, 40, 62, 63, 87, 89, 90, 92, 97, 102, 104, 111, 113, 154, 189, 238, 239, 253], "valu": [21, 22, 23, 24, 27, 28, 29, 31, 33, 34, 37, 38, 40, 44, 45, 46, 47, 48, 51, 52, 55, 58, 59, 62, 63, 64, 66, 67, 68, 69, 70, 72, 74, 76, 79, 80, 81, 82, 86, 87, 88, 90, 92, 93, 95, 96, 97, 98, 99, 100, 101, 102, 104, 105, 107, 110, 111, 112, 113, 115, 116, 119, 120, 121, 123, 124, 125, 126, 129, 130, 132, 133, 135, 143, 148, 149, 154, 156, 157, 158, 166, 169, 170, 171, 172, 173, 176, 177, 178, 179, 180, 181, 182, 185, 188, 189, 190, 191, 192, 193, 194, 195, 196, 197, 198, 199, 202, 204, 206, 207, 208, 210, 211, 212, 213, 215, 216, 217, 218, 220, 221, 222, 223, 224, 225, 226, 227, 228, 229, 232, 233, 234, 239, 240, 241, 244, 247, 248, 249, 250, 251, 252, 253, 259, 260, 265, 266, 268, 269, 270, 271, 272, 275, 276, 277, 279, 280, 285, 286, 287, 288, 289, 290, 296, 300, 301, 302, 304, 305, 306, 313], "provid": [21, 23, 31, 34, 36, 51, 60, 70, 71, 85, 94, 95, 106, 111, 118, 121, 123, 129, 130, 132, 156, 172, 179, 181, 188, 192, 193, 195, 200, 201, 202, 204, 210, 212, 213, 214, 216, 220, 221, 224, 225, 226, 228, 231, 237, 240, 244, 254, 255, 257, 259, 263, 267, 269, 270, 283, 286, 289], "inform": [21, 59, 62, 86, 90, 92, 95, 97, 102, 113, 115, 120, 121, 123, 125, 126, 167, 189, 216, 235, 236, 253, 257, 268], "about": [21, 58, 59, 63, 85, 86, 113, 120, 121, 124, 189, 213, 317], "distribut": [21, 40, 58, 59, 62, 64, 70, 75, 84, 87, 90, 91, 92, 97, 102, 108, 111, 112, 115, 126, 133, 148, 168, 169, 170, 174, 210, 212, 216, 221, 239, 241, 248, 253, 262, 290], "lt": [21, 36, 84, 126], "less": [21, 37, 48, 62, 70, 72, 90, 106, 189, 191, 197, 198, 216, 222, 223, 225, 226, 231, 239, 263, 287, 305], "applic": [21, 37, 96, 123, 186, 187], "span": [21, 63, 91, 110, 188, 192, 207, 221, 248, 259, 260, 290], "space": 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270, 271, 274, 275, 279, 311], "It": [21, 24, 32, 52, 58, 59, 63, 64, 72, 78, 80, 81, 82, 84, 86, 87, 89, 90, 98, 110, 112, 117, 120, 121, 122, 129, 140, 148, 168, 178, 189, 203, 215, 304, 309], "possibl": [21, 32, 40, 59, 63, 70, 74, 76, 77, 79, 84, 86, 87, 111, 113, 117, 120, 121, 132, 168, 177, 178, 191, 200, 201, 214, 221, 222, 269], "gain": [21, 216], "anisotropi": [21, 58, 64, 111, 241], "look": [21, 62, 63, 86, 113, 121, 124, 140, 156, 168, 172, 272, 276, 307, 312], "length": [21, 58, 71, 80, 81, 85, 88, 89, 90, 92, 110, 111, 112, 120, 121, 123, 126, 133, 164, 169, 170, 213, 229, 232, 235, 236, 238, 239, 241, 247, 254, 255, 262, 268, 269, 283], "cr": 21, "sub": [21, 71, 84, 124, 125, 138, 200, 217, 251, 300], "modul": [21, 58, 59, 113, 115, 123, 126, 127, 130, 132, 167, 178, 183, 184, 313, 314, 315, 316, 317, 318, 319, 320, 321], "contain": [21, 44, 45, 46, 47, 49, 51, 59, 62, 77, 79, 82, 86, 89, 90, 95, 96, 102, 103, 104, 105, 107, 109, 114, 115, 117, 118, 120, 121, 124, 125, 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248, 253, 259, 260, 270, 283, 284, 288, 289, 304, 306, 307, 312], "correl": [21, 87, 109, 148, 260], "data": [21, 58, 62, 63, 86, 90, 91, 92, 94, 95, 97, 102, 107, 109, 110, 111, 115, 120, 121, 123, 125, 126, 132, 154, 157, 158, 162, 166, 167, 200, 201, 229, 235, 236, 238, 239, 241, 244, 248, 252, 253, 254, 258, 259, 260, 262, 268, 269, 270, 276, 290, 304], "two_point_correlation_fft": 21, "fig": [21, 22, 23, 24, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 44, 45, 46, 47, 48, 49, 51, 52, 53, 55, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 101, 102, 103, 104, 105, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 119, 121, 122, 124, 125, 126, 127, 129, 130, 131, 132, 133, 135, 137, 138, 139, 140, 141, 142, 143, 145, 148, 149, 152, 153, 156, 157, 158, 159, 160, 161, 162, 163, 164, 165, 166, 302, 306, 310], "plot": [21, 50, 52, 58, 59, 85, 87, 88, 89, 90, 91, 92, 95, 97, 99, 102, 103, 104, 107, 108, 109, 110, 111, 112, 115, 121, 123, 126, 129, 130, 132, 166, 238, 239, 241, 248, 253, 258], "bo": 21, "ylabel": [21, 89, 91, 95, 103, 108, 115, 123, 130, 132], "probabl": [21, 59, 62, 78, 86, 90, 92, 97, 102, 109, 117, 188, 239, 241, 248, 253, 260], "xlabel": [21, 89, 91, 95, 103, 108, 115, 123, 130, 132], "suit": 21, "produc": [21, 28, 41, 46, 47, 48, 62, 64, 70, 86, 87, 95, 97, 120, 124, 130, 132, 157, 158, 195, 207, 216, 221, 222, 223, 225, 226, 233, 239, 241, 244, 248, 253, 269, 305, 306], "pass": [21, 24, 31, 32, 34, 44, 46, 47, 48, 58, 59, 82, 85, 89, 90, 92, 111, 115, 116, 120, 121, 122, 124, 129, 155, 156, 158, 165, 171, 172, 181, 185, 192, 203, 207, 222, 223, 225, 226, 238, 239, 241, 242, 244, 248, 252, 253, 254, 255, 258, 260, 264, 265, 268, 269, 302, 303, 304], "through": [21, 24, 32, 66, 86, 120, 123, 124, 131, 132, 163, 165, 185, 212, 244, 268, 312], "mip": 21, "log": [21, 59, 110, 132, 154, 239, 241, 248, 253], "fals": [21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 62, 63, 64, 65, 66, 67, 68, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 86, 88, 89, 90, 91, 92, 93, 94, 96, 97, 102, 103, 104, 105, 107, 108, 109, 114, 115, 116, 121, 123, 126, 127, 129, 130, 131, 132, 134, 135, 137, 138, 139, 140, 141, 142, 143, 145, 148, 149, 152, 153, 154, 157, 158, 159, 161, 164, 165, 166, 169, 175, 176, 178, 179, 182, 188, 190, 197, 198, 199, 200, 205, 211, 214, 225, 226, 228, 235, 236, 239, 241, 249, 253, 276, 280, 281, 285, 292, 293, 295, 298, 300, 304, 306], "now": [21, 32, 58, 59, 62, 63, 79, 84, 85, 89, 90, 92, 94, 97, 102, 111, 112, 113, 115, 118, 119, 120, 121, 123, 126, 129, 130, 157, 158, 160, 166, 168], "show": [21, 55, 58, 59, 62, 85, 97, 121, 122, 129, 130, 132, 155, 156, 164, 166, 303, 304, 311], "intrus": [21, 192], "curv": [21, 95, 108, 110, 127, 129, 130, 244], "r": [21, 24, 31, 34, 38, 51, 58, 59, 60, 61, 62, 72, 74, 79, 82, 84, 85, 86, 95, 99, 100, 101, 106, 107, 108, 109, 112, 113, 114, 115, 117, 118, 120, 121, 122, 123, 124, 126, 129, 130, 131, 132, 133, 137, 142, 143, 149, 154, 159, 165, 167, 168, 178, 192, 213, 214, 218, 220, 222, 223, 225, 226, 228, 248, 253, 260, 269, 276, 279, 284, 285, 292, 293, 295], "cdf": [21, 58, 59, 90, 92, 97, 102, 111, 154, 239, 241, 248, 253, 302], "volum": [21, 40, 59, 62, 79, 85, 93, 98, 100, 105, 106, 107, 113, 117, 118, 120, 121, 124, 125, 126, 127, 132, 213, 220, 222, 223, 225, 226, 243, 251, 252, 254, 255, 256, 257, 258, 259, 268, 269], "fraction": [21, 40, 59, 62, 64, 79, 85, 96, 111, 112, 132, 197, 198, 213, 220, 222, 223, 224, 225, 226, 244, 247, 249, 253, 260, 278], "invad": [21, 32, 40, 47, 95, 129, 130, 132, 157, 158, 188, 191, 192, 196, 197, 198, 244, 270, 306], "add": [22, 23, 24, 62, 63, 67, 75, 76, 77, 79, 80, 83, 117, 130, 167, 169, 170, 213, 218, 223, 225, 226, 261, 269, 301], "void": [22, 23, 28, 38, 40, 47, 51, 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50, 58, 59, 62, 63, 64, 66, 70, 73, 79, 82, 87, 88, 89, 90, 91, 92, 95, 96, 97, 102, 103, 104, 105, 107, 109, 113, 115, 116, 118, 120, 121, 123, 124, 125, 126, 129, 130, 131, 133, 135, 140, 152, 154, 156, 158, 167, 169, 170, 172, 173, 174, 175, 176, 177, 178, 179, 180, 181, 182, 185, 186, 187, 188, 190, 191, 192, 193, 194, 195, 196, 197, 198, 199, 200, 201, 202, 203, 204, 205, 206, 207, 208, 209, 210, 211, 212, 213, 214, 215, 217, 218, 219, 220, 221, 222, 223, 224, 225, 226, 227, 228, 231, 237, 238, 239, 240, 241, 242, 243, 244, 247, 248, 249, 250, 251, 252, 253, 254, 255, 256, 257, 258, 259, 260, 261, 262, 263, 264, 265, 267, 268, 269, 270, 271, 272, 273, 274, 275, 276, 277, 278, 279, 280, 281, 282, 283, 284, 285, 286, 287, 288, 289, 290, 291, 292, 293, 294, 295, 296, 297, 298, 299, 300, 302, 304, 306, 307, 309, 310, 311, 312, 313, 320], "uniqu": [22, 29, 38, 75, 96, 121, 122, 123, 129, 132, 169, 190, 198, 199, 201, 202, 296], "ly": [22, 122, 169, 241, 253], "same": [22, 36, 40, 55, 62, 64, 65, 68, 69, 70, 82, 85, 86, 111, 113, 120, 121, 122, 130, 131, 133, 140, 158, 169, 172, 174, 176, 177, 179, 180, 181, 185, 186, 188, 189, 191, 192, 193, 194, 195, 196, 197, 198, 199, 203, 206, 211, 215, 216, 223, 237, 251, 252, 257, 260, 261, 264, 265, 270, 279, 280, 285, 286, 287, 288, 296, 297, 301, 306], "otherwis": [22, 137, 169, 216, 217, 244, 247, 269, 270], "three": [23, 62, 96, 112, 133, 164, 170, 269, 281, 311], "seprat": 23, "plu": [23, 82, 114, 257], "y": [23, 37, 58, 73, 82, 86, 121, 125, 131, 132, 133, 156, 158, 164, 170, 202, 215, 219, 269, 285, 291, 296], "z": [23, 37, 82, 86, 133, 140, 155, 156, 164, 170, 189, 202, 213, 214, 215, 219, 235, 236, 285, 291, 296], "label": [23, 29, 30, 40, 44, 46, 47, 62, 85, 89, 93, 96, 98, 100, 101, 103, 104, 105, 106, 107, 109, 112, 113, 114, 115, 116, 118, 120, 121, 122, 123, 124, 125, 126, 129, 132, 133, 138, 166, 169, 170, 177, 179, 180, 181, 195, 200, 201, 202, 203, 206, 207, 211, 231, 233, 239, 243, 247, 249, 255, 256, 257, 260, 261, 263, 264, 265, 266, 268, 269, 275, 277, 280, 286, 296], "resepct": [23, 170], "inspect": [23, 26, 27, 28, 29, 30, 31, 32, 34, 36, 37, 38, 39, 40, 44, 45, 46, 47, 48, 51, 63, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 83, 88, 89, 90, 91, 93, 94, 95, 96, 97, 98, 102, 103, 104, 105, 107, 108, 109, 114, 115, 116, 124, 127, 128, 154, 156, 157, 158, 160, 161, 162, 164], "print": [23, 25, 28, 36, 48, 49, 50, 51, 58, 59, 60, 61, 72, 74, 79, 82, 83, 85, 86, 87, 88, 91, 93, 94, 95, 96, 98, 106, 113, 115, 117, 118, 120, 121, 123, 124, 125, 126, 129, 131, 133, 145, 152, 153, 156, 275, 278, 280, 287, 296, 299, 300], "signatur": [23, 26, 27, 28, 29, 30, 31, 32, 34, 36, 37, 38, 39, 40, 44, 45, 46, 47, 48, 51, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 83, 88, 89, 90, 91, 93, 94, 96, 97, 98, 102, 103, 104, 105, 107, 108, 109, 114, 115, 116, 121, 127, 128, 154, 156, 157, 158, 160, 161, 162, 164, 269], "take": [23, 25, 53, 62, 63, 76, 77, 86, 112, 115, 116, 120, 121, 123, 124, 126, 129, 130, 131, 162, 163, 185, 287, 290, 296, 309], "boolean": [23, 29, 35, 44, 46, 47, 55, 59, 63, 64, 76, 98, 99, 130, 138, 140, 156, 157, 158, 176, 178, 179, 180, 182, 192, 195, 200, 201, 203, 206, 207, 208, 210, 212, 213, 214, 215, 216, 218, 220, 221, 224, 227, 228, 239, 241, 247, 248, 253, 257, 259, 264, 265, 269, 270, 273, 277, 279, 281, 283, 285, 288, 289, 292, 293, 295, 305, 306], "indic": [23, 27, 28, 29, 32, 33, 36, 38, 47, 48, 51, 53, 55, 59, 62, 63, 69, 73, 76, 77, 79, 90, 95, 99, 102, 111, 115, 116, 120, 121, 122, 129, 131, 132, 140, 156, 157, 158, 163, 166, 169, 170, 173, 176, 177, 178, 179, 191, 192, 193, 194, 195, 196, 197, 198, 199, 200, 201, 202, 203, 206, 207, 212, 217, 222, 223, 225, 226, 232, 239, 242, 244, 249, 257, 258, 259, 262, 264, 266, 268, 269, 270, 271, 274, 275, 277, 280, 283, 285, 288, 289, 290, 292, 293, 295, 296, 300, 304, 305, 306], "phase": [23, 27, 28, 29, 32, 38, 49, 51, 54, 62, 79, 84, 85, 91, 92, 95, 96, 103, 104, 105, 107, 108, 109, 110, 111, 113, 115, 116, 117, 118, 122, 123, 124, 125, 126, 129, 130, 131, 132, 133, 156, 157, 173, 176, 177, 188, 190, 191, 192, 196, 197, 198, 199, 201, 202, 207, 222, 223, 231, 234, 240, 241, 244, 247, 248, 249, 259, 260, 263, 265, 266, 268, 269, 270, 271, 307, 312], "interest": [23, 34, 51, 92, 113, 131, 132, 156, 173, 176, 177, 180, 181, 188, 195, 202, 207, 244, 249, 251, 260, 269, 271, 273, 289, 304], "50": [23, 24, 48, 49, 50, 52, 58, 62, 67, 71, 72, 77, 82, 83, 86, 87, 93, 94, 98, 99, 105, 112, 117, 119, 121, 122, 126, 129, 132, 135, 137, 141, 142, 143, 156, 158, 159, 162, 165, 166], "12": [23, 24, 25, 26, 27, 28, 29, 30, 35, 36, 37, 38, 39, 40, 41, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 64, 65, 67, 68, 71, 75, 76, 77, 78, 80, 81, 82, 88, 89, 91, 95, 108, 115, 121, 123, 124, 125, 126, 127, 156, 159, 161, 165], "20": [23, 24, 37, 59, 65, 72, 73, 74, 76, 79, 82, 83, 88, 89, 100, 105, 106, 114, 115, 121, 124, 125, 126, 132, 139, 140, 142, 148, 152, 156, 158, 163, 166, 208, 221], "22": [23, 89, 100, 113, 115, 121, 124, 125, 126, 129, 138], "differ": [23, 27, 31, 36, 46, 58, 59, 61, 63, 66, 70, 86, 87, 92, 96, 102, 111, 112, 116, 120, 121, 123, 124, 129, 130, 131, 132, 154, 160, 166, 172, 188, 190, 195, 213, 225, 226, 270, 296, 302], "integ": [23, 36, 59, 88, 121, 195, 200, 201, 202, 247, 265, 269, 270, 286], "so": [23, 31, 32, 40, 46, 47, 48, 51, 53, 62, 63, 64, 71, 74, 75, 79, 80, 81, 85, 86, 91, 98, 106, 110, 111, 112, 113, 114, 117, 118, 120, 121, 124, 125, 129, 132, 133, 155, 156, 169, 170, 185, 189, 191, 194, 203, 206, 209, 210, 213, 221, 222, 223, 225, 226, 232, 239, 241, 248, 249, 252, 253, 254, 255, 260, 261, 264, 267, 268, 269, 270, 279, 287, 296, 303, 307, 309, 312], "thei": [23, 28, 32, 47, 56, 58, 66, 67, 76, 77, 83, 92, 95, 106, 111, 114, 115, 121, 122, 126, 129, 130, 132, 167, 168, 185, 188, 191, 192, 206, 208, 213, 225, 226, 239, 253, 257, 269, 296, 304], "isol": [23, 28, 29, 47, 57, 113, 120, 175, 176, 181, 194, 205, 209, 268], "threshold": [23, 36, 40, 62, 63, 64, 70, 87, 132, 166, 179, 188, 192, 209, 210, 216, 259, 305], "By": [23, 27, 37, 40, 67, 68, 70, 79, 83, 90, 92, 96, 97, 102, 103, 104, 105, 107, 116, 127, 132, 157, 158, 159, 163, 172, 179, 185, 189, 192, 213], "drown": 23, "orient": [23, 58, 67, 68, 100, 101, 106, 111, 113, 159, 165, 213, 214, 276], "maximum": [23, 34, 36, 52, 57, 66, 70, 74, 76, 77, 80, 113, 120, 121, 127, 156, 175, 176, 177, 178, 180, 187, 191, 197, 198, 199, 200, 201, 205, 220, 222, 223, 225, 226, 240, 260, 264, 268, 269, 279, 304], "number": [23, 25, 32, 36, 37, 38, 40, 44, 46, 47, 48, 49, 50, 58, 61, 62, 64, 67, 70, 74, 75, 76, 77, 78, 79, 80, 81, 83, 85, 86, 88, 89, 90, 92, 96, 97, 102, 103, 105, 107, 108, 110, 114, 118, 121, 124, 127, 130, 133, 158, 163, 172, 178, 188, 189, 190, 191, 192, 193, 194, 197, 198, 199, 201, 202, 208, 210, 211, 212, 213, 216, 218, 220, 221, 222, 223, 224, 225, 226, 227, 228, 231, 232, 237, 238, 239, 241, 247, 248, 253, 254, 256, 257, 258, 259, 260, 261, 263, 269, 275, 277, 280, 287, 300, 305], "adjust": [23, 62, 64, 74, 87, 91, 124, 132, 156, 160, 165, 179, 189, 213, 275, 287, 304, 308], "few": [23, 62, 63, 86, 106, 121, 122, 123, 124, 132, 138, 257, 317], "veri": [23, 45, 46, 62, 63, 75, 84, 87, 98, 106, 121, 129, 132, 140, 163, 213, 235, 236, 309], "need": [23, 28, 31, 51, 62, 63, 85, 86, 91, 95, 106, 108, 110, 113, 115, 116, 121, 123, 125, 126, 129, 130, 137, 138, 163, 168, 172, 188, 213, 258], "c1": 23, "c3": [23, 126], "30": [23, 76, 80, 82, 94, 108, 115, 126, 153, 162], "c2": 23, "pad": [24, 96, 114, 121, 122, 139, 153, 171, 172, 261, 269, 275, 279, 301], "befor": [24, 48, 54, 56, 62, 83, 86, 123, 124, 127, 129, 171, 182, 192, 206, 239, 241, 248, 253], "edt": [24, 31, 33, 34, 35, 42, 44, 45, 46, 47, 52, 54, 56, 102, 114, 118, 120, 121, 122, 129, 130, 132, 156, 253], "zero": [24, 59, 63, 71, 73, 92, 103, 104, 105, 120, 140, 149, 169, 177, 232, 254, 255, 268, 296], "300": [24, 59, 63, 66, 79, 87, 112, 124, 129], "volume_fract": [24, 59, 149, 225, 226], "figur": [24, 25, 33, 42, 43, 49, 50, 52, 54, 55, 56, 57, 62, 65, 68, 69, 80, 115, 122, 123, 132, 134, 160, 302, 306, 310], "tmp": [24, 38, 59, 79, 84, 106, 121, 127, 132, 149], "ipykernel_2781": 24, "1290140162": 24, "py": [24, 38, 53, 59, 62, 63, 79, 84, 91, 106, 115, 121, 126, 127, 131, 132, 133, 149], "deprecationwarn": [24, 38, 59, 79, 84, 106, 121, 127, 132, 149], "call": [24, 32, 33, 38, 41, 53, 58, 59, 62, 63, 72, 79, 82, 84, 94, 103, 104, 106, 113, 121, 123, 124, 127, 129, 130, 132, 149, 168, 173, 180, 185, 210, 212, 213, 216, 220, 221, 222, 223, 224, 225, 226, 228, 242, 287], "deprec": [24, 38, 59, 79, 84, 106, 115, 121, 126, 127, 132, 149, 245, 246], "staticmethod": [24, 38, 59, 79, 84, 106, 121, 127, 132, 149], "renam": [24, 38, 59, 79, 84, 106, 121, 149], "random_spher": [24, 38, 59, 62, 79, 84, 106, 121], "futur": [24, 38, 59, 79, 84, 106, 121, 127, 132], "version": [24, 38, 48, 59, 61, 62, 79, 80, 81, 84, 106, 111, 113, 118, 121, 127, 132, 175, 205, 257, 269, 282, 291, 320], "good": [24, 63, 121, 122, 213, 260], "case": [24, 40, 53, 62, 71, 76, 79, 82, 86, 95, 121, 122, 171, 172, 182, 195, 214, 217, 225, 226, 239, 251, 257, 301, 303], "skeletonize_3d": [24, 41, 171, 257, 301], "ha": [24, 32, 48, 62, 63, 72, 79, 80, 81, 85, 86, 87, 96, 98, 106, 110, 113, 120, 121, 125, 129, 130, 132, 137, 138, 139, 148, 149, 179, 183, 184, 185, 194, 200, 201, 213, 216, 222, 223, 225, 226, 237, 268, 270], "artifact": [24, 30, 59, 121, 124, 156, 172, 201, 300, 304], "reduc": [24, 48, 120, 121, 124, 130, 160, 202, 235, 236, 253], "pre": [24, 48, 122, 259], "morphologi": [24, 25, 27, 31, 41, 60, 96, 103, 104, 130, 171, 174, 210, 301], "amount": [24, 67, 79, 115, 121, 139, 164, 165, 171, 172, 177, 202, 204, 213, 218, 222, 223, 225, 226, 261, 279, 297, 300, 301, 311, 312], "x1": [24, 25, 33, 50, 53, 57, 73, 219], "x2": [24, 25, 33, 50, 53, 57], "100": [24, 28, 31, 32, 51, 57, 58, 62, 64, 67, 72, 74, 76, 77, 80, 81, 83, 86, 89, 90, 92, 97, 98, 100, 101, 102, 107, 109, 115, 117, 118, 119, 120, 121, 123, 124, 129, 132, 133, 135, 137, 139, 141, 142, 143, 149, 153, 155, 157, 174, 225, 226, 260], "": [24, 25, 27, 32, 37, 45, 46, 58, 59, 62, 63, 64, 69, 70, 72, 74, 79, 82, 84, 85, 86, 87, 90, 91, 92, 94, 96, 97, 98, 99, 102, 103, 104, 105, 106, 107, 110, 111, 113, 115, 116, 119, 120, 121, 122, 123, 124, 126, 129, 130, 131, 132, 138, 148, 152, 153, 154, 155, 156, 157, 158, 160, 162, 166, 167, 180, 181, 196, 197, 198, 199, 201, 210, 212, 213, 214, 215, 220, 221, 224, 225, 226, 228, 232, 235, 236, 239, 241, 249, 251, 253, 257, 258, 259, 266, 269, 275, 279, 286, 288, 296, 300, 302, 303, 305, 307, 308, 312], "morpholog": [24, 27, 36, 40, 130, 174, 188, 292, 293], "oper": [24, 25, 27, 33, 34, 36, 40, 50, 115, 117, 121, 126, 132, 172, 174, 182, 292, 293, 300], "binary_open": [24, 59, 174], "x3": [24, 33, 53, 57], "footprint": [24, 121, 172], "tool": [24, 50, 51, 53, 59, 60, 61, 63, 79, 94, 114, 121, 124, 129, 132, 135, 139, 140, 141, 145, 148, 162, 167, 170, 192, 202, 275, 278, 280, 287, 296, 300], "ps_disk": [24, 59, 79, 121, 148], "15": [24, 26, 27, 36, 37, 41, 48, 51, 59, 62, 65, 66, 68, 79, 89, 101, 114, 115, 121, 124, 125, 126, 133, 158], "x4": [24, 53], "With": [24, 86, 111, 113, 133], "place": [24, 59, 69, 71, 86, 171, 180, 211, 221, 280], "almost": [24, 107, 121, 132, 172], "alwai": [24, 25, 67, 77, 86, 132, 172, 174, 270], "mai": [24, 47, 48, 53, 74, 76, 121, 122, 123, 132, 154, 174, 177, 178, 194, 213, 218, 225, 226, 232, 257, 297, 302], "distanc": [24, 26, 30, 31, 33, 34, 35, 36, 37, 40, 48, 50, 52, 54, 56, 60, 76, 91, 92, 102, 108, 109, 111, 112, 113, 120, 121, 124, 129, 130, 133, 159, 172, 173, 177, 178, 187, 188, 189, 192, 194, 200, 201, 206, 208, 212, 213, 222, 232, 233, 241, 253, 257, 260, 268, 279, 287, 288], "transform": [24, 26, 27, 31, 33, 34, 35, 36, 40, 48, 50, 52, 54, 56, 60, 76, 102, 109, 111, 113, 115, 120, 121, 124, 126, 129, 130, 133, 172, 177, 178, 187, 188, 192, 194, 200, 201, 206, 208, 222, 232, 233, 253, 257, 260, 268, 279], "x5": 24, "10": [24, 27, 29, 34, 37, 49, 50, 52, 57, 59, 60, 61, 62, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 79, 82, 83, 84, 85, 86, 87, 88, 89, 90, 92, 93, 94, 96, 97, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 113, 114, 115, 116, 117, 119, 121, 122, 123, 124, 125, 126, 130, 131, 133, 140, 145, 153, 154, 155, 156, 157, 158, 160, 162, 164, 166, 167, 220, 221, 237, 239, 241, 248, 253, 259, 305, 311], "x6": 24, "perform": [25, 27, 33, 36, 40, 50, 61, 76, 90, 91, 92, 97, 102, 108, 110, 115, 118, 120, 122, 126, 129, 130, 167, 172, 174, 188, 192, 201, 202, 207, 232, 239, 241, 248, 253, 268, 269, 300, 322], "specfi": [25, 172], "one": [25, 37, 48, 61, 62, 71, 84, 86, 111, 116, 120, 121, 122, 123, 124, 126, 129, 130, 132, 133, 158, 172, 187, 189, 190, 213, 238, 254, 255, 257, 268, 269, 281, 286, 306], "chunk": [25, 36, 61, 115, 121, 126, 133, 172, 192, 202, 297], "time": [25, 37, 41, 50, 58, 61, 81, 85, 86, 115, 120, 123, 129, 133, 160, 172, 178, 179, 188, 192, 193, 200, 202, 210, 213, 215, 224, 227, 258], "save": [25, 50, 61, 115, 123, 126, 133, 157, 166, 172, 200, 305], "memori": [25, 50, 61, 172, 202, 300], "disk": [25, 27, 29, 31, 68, 96, 103, 104, 168, 174, 221, 225, 226, 254, 255, 293], "dilat": [25, 27, 36, 40, 59, 74, 79, 120, 174, 187, 188, 192, 228], "binary_dil": [25, 60, 172, 174], "structur": [25, 27, 29, 31, 51, 53, 59, 84, 87, 103, 104, 115, 126, 172, 174, 175, 178, 200, 201, 203, 205, 207, 216, 254, 255, 269, 289, 292, 293, 294, 295], "element": [25, 27, 29, 31, 36, 51, 59, 71, 89, 103, 104, 105, 110, 172, 174, 178, 200, 201, 207, 217, 237, 238, 242, 247, 254, 255, 264, 269, 281, 289, 292, 293, 294, 295], "divid": [25, 36, 50, 61, 78, 81, 98, 121, 130, 172, 178, 188, 192, 202, 210, 221, 224, 235, 236, 249, 300], "faster": [25, 40, 50, 85, 120, 124, 174, 178, 268, 269, 305], "input": [25, 27, 29, 35, 37, 74, 82, 89, 90, 92, 93, 94, 96, 97, 102, 103, 104, 105, 107, 109, 111, 121, 123, 124, 131, 157, 158, 161, 164, 172, 204, 208, 213, 225, 226, 230, 248, 296], "paus": [25, 50], "stop": [25, 50, 74, 80, 127, 231, 263, 275, 305], "second": [25, 50, 84, 86, 117, 123, 131, 157, 188, 192, 305], "fix": [25, 50, 54, 56, 62, 110], "fontdict": [25, 50, 53, 54, 55, 56, 57], "fontsiz": [25, 50, 53, 54, 55, 56, 57], "18": [25, 33, 50, 53, 54, 55, 56, 57, 62, 63, 71, 89, 100, 115, 121, 124, 125, 126, 133], "02565741539001465": 25, "02136993408203125": 25, "variant": [26, 185], "standard": [26, 37, 120, 121, 130, 153, 174, 180, 189, 200, 201, 221, 268, 269], "where": [26, 37, 38, 58, 59, 71, 76, 82, 87, 95, 96, 97, 104, 105, 107, 108, 110, 113, 120, 121, 129, 130, 131, 132, 133, 140, 156, 157, 158, 189, 192, 201, 203, 210, 213, 215, 217, 218, 220, 221, 222, 223, 228, 229, 232, 234, 249, 253, 256, 257, 266, 268, 270, 275, 277, 279, 280, 281, 288, 291, 296], "comput": [26, 34, 36, 38, 39, 40, 50, 61, 62, 70, 88, 98, 99, 108, 111, 120, 121, 123, 129, 130, 132, 156, 172, 181, 188, 192, 195, 200, 201, 222, 223, 225, 226, 239, 240, 243, 244, 250, 251, 252, 253, 256, 259, 268, 269, 271], "give": [26, 59, 70, 89, 90, 108, 123, 130, 140, 158, 211, 216, 218, 238, 239, 253, 280, 305], "rather": [26, 63, 85, 120, 121, 122, 130, 185, 225, 226, 249], "than": [26, 30, 36, 40, 48, 58, 59, 62, 68, 70, 72, 85, 90, 113, 117, 121, 122, 124, 126, 130, 132, 135, 174, 177, 178, 185, 188, 190, 191, 192, 197, 198, 204, 206, 208, 209, 225, 226, 239, 241, 248, 249, 253, 257, 260, 287, 305, 306], "radial": [26, 102, 241, 253], "both": [26, 32, 36, 38, 40, 44, 46, 47, 51, 52, 53, 55, 64, 86, 115, 116, 120, 124, 125, 126, 129, 130, 132, 140, 173, 178, 188, 191, 204, 213, 217, 218, 225, 226, 237, 239, 261, 269, 296], "should": [26, 31, 36, 37, 40, 58, 68, 69, 75, 76, 77, 86, 108, 117, 121, 122, 123, 124, 129, 135, 153, 156, 158, 168, 171, 172, 173, 186, 189, 191, 192, 193, 197, 198, 203, 214, 215, 217, 219, 221, 222, 223, 225, 226, 228, 239, 241, 248, 253, 259, 260, 269, 270, 285, 288, 292, 293, 295, 296, 301, 305, 306], "7": [26, 31, 32, 48, 52, 62, 71, 78, 85, 86, 87, 89, 100, 101, 115, 116, 117, 118, 120, 121, 123, 124, 125, 126, 127, 130, 133, 134, 135, 143, 145, 158, 159, 165], "dt": [26, 33, 34, 35, 36, 40, 42, 48, 49, 50, 52, 59, 60, 106, 113, 114, 121, 122, 124, 126, 129, 130, 132, 156, 177, 178, 188, 192, 200, 201, 202, 206, 208, 253], "f": [26, 31, 35, 45, 46, 47, 61, 62, 63, 67, 70, 72, 74, 75, 79, 80, 83, 85, 87, 110, 113, 115, 123, 126, 131, 145, 206, 224, 253], "comptut": 26, "end": [26, 59, 69, 73, 111, 112, 114, 117, 121, 133, 182, 193, 213, 219, 240, 261, 264, 269, 279, 284], "5": [26, 27, 28, 29, 31, 34, 36, 37, 38, 40, 41, 44, 45, 46, 47, 48, 49, 50, 51, 53, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 67, 68, 70, 71, 74, 75, 76, 77, 79, 80, 81, 82, 84, 85, 86, 87, 88, 89, 90, 91, 94, 95, 98, 99, 100, 101, 106, 108, 110, 112, 113, 114, 115, 116, 120, 121, 122, 123, 124, 125, 126, 129, 131, 132, 133, 135, 140, 145, 149, 154, 157, 158, 161, 163, 174, 189, 210, 216, 221, 224, 227, 254, 287, 296], "forward": [26, 92, 111, 112, 173], "revers": [26, 32, 173, 182, 265], "eros": [27, 36, 40, 59, 96, 174, 187, 192], "close": [27, 62, 76, 85, 87, 148, 174, 187, 206, 213, 222, 305], "fast": [27, 62, 120, 268, 269, 288], "fourier": [27, 109, 260], "convolut": [27, 103, 104, 289], "method": [27, 29, 36, 40, 50, 54, 56, 70, 85, 88, 89, 90, 92, 93, 94, 95, 96, 97, 102, 103, 104, 105, 107, 115, 116, 120, 123, 128, 130, 131, 132, 133, 154, 157, 158, 160, 161, 164, 166, 174, 182, 185, 188, 192, 220, 231, 232, 237, 256, 257, 259, 262, 263, 268, 269, 279, 288], "random": [27, 28, 29, 31, 32, 34, 35, 37, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 55, 60, 62, 64, 66, 67, 70, 71, 74, 75, 76, 77, 79, 85, 87, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 100, 101, 102, 103, 104, 105, 107, 108, 109, 111, 113, 115, 116, 117, 118, 119, 120, 121, 124, 125, 126, 129, 130, 131, 132, 133, 135, 138, 139, 140, 145, 148, 152, 154, 157, 158, 160, 162, 166, 210, 212, 213, 216, 220, 221, 222, 223, 224, 225, 226, 228, 230, 239, 241, 253, 258, 296], "seed": [27, 28, 29, 31, 32, 34, 35, 37, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 53, 55, 60, 61, 64, 66, 67, 74, 75, 76, 79, 83, 85, 87, 89, 90, 91, 93, 94, 95, 96, 97, 98, 100, 101, 102, 103, 104, 105, 107, 108, 109, 113, 115, 116, 117, 118, 119, 120, 121, 124, 125, 126, 129, 131, 132, 133, 135, 138, 154, 157, 158, 160, 162, 166, 210, 212, 213, 216, 220, 221, 222, 223, 224, 225, 226, 228, 296], "note": [27, 31, 40, 48, 58, 59, 62, 63, 66, 68, 72, 74, 79, 83, 84, 91, 94, 95, 96, 97, 102, 103, 104, 105, 106, 112, 113, 115, 116, 120, 121, 122, 123, 125, 126, 129, 130, 132, 154, 158, 160, 161, 164, 166, 170, 171, 172, 174, 176, 178, 181, 182, 188, 189, 191, 192, 194, 195, 197, 198, 200, 201, 204, 206, 207, 210, 213, 216, 217, 218, 220, 225, 226, 229, 231, 232, 233, 234, 235, 236, 238, 239, 240, 241, 242, 244, 245, 248, 249, 253, 254, 255, 257, 258, 260, 263, 266, 267, 268, 270, 279, 280, 284, 288, 296, 300, 301, 304, 305, 309], "strucur": 27, "must": [27, 28, 31, 58, 59, 63, 67, 71, 75, 81, 94, 95, 97, 103, 113, 115, 118, 121, 122, 123, 126, 129, 130, 132, 154, 155, 172, 174, 182, 201, 203, 206, 222, 223, 225, 226, 232, 300], "respect": [27, 29, 50, 52, 53, 55, 61, 82, 95, 110, 133, 156, 197, 198, 202, 210, 212, 213, 220, 221, 224, 228, 231, 251, 263, 275, 287, 304], "im_open": 27, "im_diff": 27, "let": [27, 37, 44, 58, 59, 62, 63, 69, 79, 82, 84, 85, 86, 87, 90, 92, 94, 96, 97, 102, 103, 104, 106, 107, 113, 115, 116, 121, 124, 126, 129, 130, 157, 158, 160, 162, 166], "try": [27, 57, 62, 79, 94, 107, 115, 123, 126], "im_clos": [27, 96], "im_eros": 27, "im_dil": 27, "ani": [28, 29, 51, 59, 62, 68, 85, 86, 93, 96, 98, 107, 114, 115, 117, 120, 121, 126, 129, 130, 132, 154, 156, 168, 172, 175, 176, 178, 181, 185, 191, 194, 197, 198, 199, 202, 203, 205, 213, 230, 241, 269, 270, 273, 276, 304, 305], "connect": [28, 29, 40, 51, 55, 58, 103, 114, 115, 116, 118, 120, 121, 122, 129, 170, 175, 176, 188, 200, 201, 203, 205, 207, 262, 268, 269, 270], "often": [28, 123], "numer": [28, 58, 59, 62, 63, 121, 123, 124, 132, 177, 180, 181, 239, 266, 285, 288], "blind": [28, 175, 249], "consid": [28, 29, 53, 62, 103, 104, 105, 121, 124, 176, 179, 192, 206, 225, 226, 240, 241, 250, 254, 255, 305], "cluster": [28, 29, 51, 57, 76, 129, 209, 270], "im1": [28, 49, 51, 62, 64, 70, 72, 74, 75, 79, 82, 83, 84, 87, 101, 140, 141, 145, 148, 149, 153, 159, 160, 165, 291], "control": [28, 35, 36, 38, 40, 48, 64, 65, 66, 67, 70, 72, 74, 75, 77, 78, 79, 81, 82, 114, 120, 121, 127, 132, 155, 166, 173, 178, 188, 191, 192, 196, 197, 198, 199, 202, 206, 210, 213, 216, 222, 223, 225, 226, 244, 256, 268, 269, 287, 296, 311], "how": [28, 41, 51, 53, 59, 62, 63, 66, 67, 72, 75, 85, 86, 90, 108, 112, 120, 121, 122, 123, 124, 130, 131, 135, 140, 173, 180, 191, 196, 197, 198, 199, 206, 222, 223, 225, 226, 239, 244, 259, 268, 269, 287, 322], "group": [28, 168, 194], "option": [28, 29, 36, 40, 46, 47, 53, 58, 65, 67, 72, 82, 90, 95, 120, 121, 140, 154, 168, 172, 173, 174, 175, 176, 179, 180, 185, 186, 187, 188, 189, 191, 192, 193, 196, 197, 198, 199, 200, 201, 202, 205, 210, 211, 212, 213, 214, 215, 216, 218, 220, 221, 222, 223, 224, 225, 226, 228, 232, 235, 236, 237, 239, 240, 244, 255, 256, 259, 261, 262, 268, 269, 270, 280, 281, 286, 290, 302, 304, 306, 311], "while": [28, 61, 62, 80, 92, 120, 121, 129, 130, 156, 172, 175, 176, 192, 202, 205, 218, 266, 287], "26": [28, 29, 53, 58, 100, 115, 126, 149, 175, 176, 205], "im2": [28, 37, 49, 51, 62, 63, 64, 70, 72, 74, 75, 79, 82, 83, 84, 87, 101, 139, 140, 141, 148, 149, 159, 160, 165, 291], "flag": [28, 115, 126, 192], "main": [28, 79, 121, 124, 125, 133, 175, 205, 217], "bodi": [28, 72, 202, 205, 218], "mi": [28, 74, 132], "lead": [28, 62, 78], "result": [28, 29, 32, 36, 37, 38, 40, 48, 49, 50, 53, 58, 59, 60, 61, 62, 63, 64, 82, 85, 86, 88, 89, 90, 91, 92, 95, 97, 102, 103, 104, 110, 111, 112, 113, 115, 116, 121, 123, 126, 127, 129, 130, 131, 133, 140, 161, 168, 171, 172, 173, 174, 182, 185, 188, 189, 190, 192, 195, 200, 201, 210, 211, 213, 216, 223, 225, 226, 237, 238, 239, 241, 244, 247, 248, 250, 253, 254, 257, 258, 259, 260, 265, 267, 269, 270, 271, 280, 283, 287, 302, 309, 312], "sinc": [28, 30, 32, 38, 58, 66, 67, 70, 95, 111, 112, 113, 115, 117, 120, 121, 122, 124, 125, 126, 129, 130, 133, 159, 165, 172, 175, 177, 188, 191, 197, 198, 200, 201, 205, 207, 213, 222, 223, 225, 226, 239, 241, 245, 248, 253, 267, 269, 270, 300], "just": [28, 30, 41, 45, 46, 58, 59, 62, 63, 70, 79, 86, 122, 124, 129, 130, 138, 168, 176, 177, 235, 236, 248, 298], "keep": [28, 55, 129, 168, 224], "largest": [28, 32, 36, 40, 59, 86, 97, 102, 111, 113, 120, 129, 175, 188, 191, 196, 198, 199, 205, 214, 231, 248, 257, 263, 268, 276], "For": [28, 34, 37, 59, 70, 93, 113, 115, 116, 121, 123, 124, 130, 131, 140, 154, 155, 166, 168, 175, 176, 186, 188, 189, 202, 205, 216, 218, 221, 235, 236, 239, 241, 244, 248, 250, 254, 260, 269, 274], "better": [28, 62, 90, 92, 97, 117, 120, 121, 130, 155, 239, 241, 248, 253, 268, 269], "recommend": [28, 120, 121, 129, 168, 189, 253], "trim_nonpercolation_path": 28, "detect": [29, 111, 170, 241], "region": [29, 32, 33, 34, 43, 46, 47, 48, 49, 50, 58, 60, 61, 62, 68, 78, 90, 92, 94, 97, 98, 100, 101, 106, 117, 118, 119, 121, 122, 123, 124, 125, 126, 129, 131, 132, 138, 158, 162, 166, 175, 176, 179, 180, 181, 188, 190, 195, 200, 201, 202, 205, 207, 225, 226, 239, 241, 242, 243, 248, 251, 252, 253, 254, 255, 256, 257, 261, 262, 266, 268, 269, 277, 279, 286, 289, 296, 310, 312], "specif": [29, 33, 70, 106, 111, 112, 123, 148, 167, 180, 185, 188, 192, 241, 253, 307, 312], "disconnect": [29, 131, 175, 176, 192, 205, 270, 271], "pixel": [29, 37, 38, 62, 83, 85, 89, 110, 113, 114, 125, 129, 131, 189, 190, 211, 213, 228, 280], "Then": [29, 45, 129, 166], "scikitimag": 29, "clear_bord": [29, 176], "includ": [29, 38, 49, 58, 62, 85, 86, 90, 92, 96, 97, 102, 104, 111, 113, 115, 116, 117, 118, 124, 126, 129, 130, 138, 166, 167, 172, 188, 190, 213, 225, 226, 228, 239, 241, 248, 253, 257, 259, 260, 269, 270, 275, 287, 299, 302, 304], "found": [29, 34, 38, 48, 54, 56, 69, 70, 71, 86, 107, 110, 115, 120, 121, 123, 126, 129, 131, 133, 177, 182, 188, 189, 200, 201, 232, 247, 252, 257, 268, 271, 280], "discon_voxel": 29, "sweep": 29, "subsequ": [29, 59, 111, 113, 121, 131, 301], "affect": [29, 36, 40], "accuraci": [29, 115, 123, 126, 179, 235, 236, 268, 269], "algorithm": [29, 40, 48, 50, 60, 61, 62, 75, 78, 93, 94, 103, 104, 113, 120, 121, 122, 123, 125, 126, 127, 129, 130, 132, 133, 157, 158, 167, 200, 201, 202, 206, 208, 213, 220, 225, 226, 243, 256, 257, 267, 268, 269, 270, 289, 305], "Their": 29, "correspond": [29, 37, 62, 89, 111, 112, 113, 120, 121, 132, 159, 165, 171, 185, 189, 202, 229, 231, 240, 247, 252, 263, 266, 268, 285], "squar": [29, 31, 53, 175, 176, 178, 205, 218, 227, 276], "cube": [29, 86, 93, 94, 103, 104, 105, 120, 231, 243, 254, 255, 256, 257, 263, 268, 269, 289], "ball": [29, 31, 225, 226, 267, 279, 292], "bt": 29, "paramet": [29, 62, 74, 81, 120, 160, 164, 169, 170, 171, 172, 173, 174, 175, 176, 177, 178, 179, 180, 181, 182, 186, 187, 188, 189, 190, 191, 192, 193, 194, 195, 196, 197, 198, 199, 200, 201, 202, 203, 204, 205, 206, 207, 208, 209, 210, 211, 212, 213, 214, 215, 216, 217, 218, 219, 220, 221, 222, 223, 224, 225, 226, 227, 228, 229, 230, 231, 232, 233, 234, 235, 236, 237, 238, 239, 240, 241, 242, 243, 244, 247, 248, 249, 250, 251, 252, 253, 254, 255, 256, 257, 258, 259, 260, 261, 262, 263, 264, 265, 266, 267, 268, 269, 270, 271, 273, 274, 275, 276, 277, 278, 279, 280, 281, 283, 284, 285, 286, 287, 288, 289, 290, 291, 292, 293, 294, 295, 296, 297, 298, 299, 300, 301, 302, 303, 304, 305, 306, 307, 309, 310, 311, 312], "closer": [30, 48, 54, 129, 177], "solid": [30, 44, 46, 47, 48, 51, 53, 54, 62, 63, 87, 100, 103, 104, 105, 106, 107, 109, 111, 113, 118, 121, 122, 123, 130, 156, 157, 158, 166, 173, 177, 179, 188, 191, 192, 196, 197, 198, 199, 205, 206, 219, 220, 231, 233, 234, 237, 241, 249, 253, 259, 263, 265, 269, 279, 304, 306, 307, 312], "These": [30, 52, 58, 69, 84, 114, 120, 121, 127, 129, 169, 170, 177, 185, 192, 253, 258, 268, 269, 305], "potenti": [30, 85, 114, 129, 177, 213, 253], "could": [30, 36, 62, 114, 120, 121, 124, 130, 156, 177, 186, 187, 188, 298], "lie": [30, 38, 48, 56, 62, 82, 111, 121, 124, 194, 213, 228], "beyond": [30, 82, 110, 132, 171, 177, 213, 217, 222, 223, 225, 226, 232, 275, 301, 305], "were": [30, 32, 47, 56, 59, 62, 63, 95, 111, 113, 115, 121, 126, 131, 132, 158, 177, 191, 208, 270, 297], "crop": [30, 137, 217], "onli": [30, 40, 53, 55, 59, 62, 63, 66, 71, 79, 82, 86, 94, 99, 112, 113, 115, 117, 120, 121, 123, 126, 129, 131, 132, 172, 175, 192, 201, 205, 206, 209, 217, 218, 221, 223, 225, 226, 241, 249, 267, 269, 270, 284, 285, 286, 296], "accept": [30, 37, 80, 81, 82, 86, 113, 121, 124, 154, 167, 173, 180, 189, 222, 225, 226, 229], "tranform": [30, 121, 129, 192], "distance_transform_edt": [30, 124], "dt2": [30, 52], "peak": [31, 35, 48, 49, 52, 60, 76, 122, 124, 132, 178, 182, 194, 200, 201, 204, 206, 208, 222, 232, 269], "watersh": [31, 34, 48, 60, 113, 114, 120, 121, 124, 125, 187, 200, 201, 206, 208, 257, 261, 268, 269], "segment": [31, 34, 48, 60, 61, 62, 63, 78, 94, 113, 114, 115, 116, 120, 121, 124, 125, 126, 200, 201, 202, 208, 261, 262, 268, 269], "11": [31, 59, 62, 71, 79, 86, 89, 115, 121, 123, 124, 125, 126], "sigma": [31, 33, 34, 37, 50, 53, 60, 61, 62, 95, 124, 129, 130, 178, 189, 200, 201, 202, 210, 244, 269, 270], "div": [31, 53, 61, 121, 152, 172, 178, 188, 192, 202, 210, 300], "pk": [31, 34, 35, 114], "search": [31, 35, 37, 38, 48, 63, 170, 189], "maxima": [31, 52, 120, 121, 178, 204, 268], "form": [31, 59, 66, 76, 77, 98, 133, 138, 185, 212, 242, 248, 274, 298], "handl": [31, 75, 86, 121, 171, 172, 181, 200, 201, 212, 222, 223, 225, 226, 261, 275, 282, 299, 302, 310], "depend": [31, 36, 40, 53, 72, 110, 115, 123, 126, 154, 168, 174, 188, 189, 192, 213, 269, 282, 302], "meant": [32, 106, 309], "defend": [32, 132, 270], "trap": [32, 179, 270], "dure": [32, 62, 85, 114, 121, 122, 244, 269], "ordinari": 32, "percol": [32, 127, 130, 131, 132, 157, 158, 175], "type": [32, 63, 65, 115, 121, 123, 126, 168, 169, 170, 172, 173, 174, 176, 177, 178, 179, 180, 181, 182, 186, 187, 188, 190, 191, 192, 193, 194, 195, 196, 197, 198, 199, 200, 201, 202, 203, 204, 205, 206, 207, 208, 209, 210, 211, 212, 213, 214, 215, 216, 217, 218, 219, 220, 221, 222, 223, 224, 225, 226, 227, 228, 231, 237, 238, 239, 240, 241, 242, 243, 244, 247, 248, 249, 250, 251, 252, 253, 254, 255, 256, 257, 258, 259, 260, 261, 262, 263, 264, 265, 268, 269, 270, 271, 273, 274, 275, 276, 277, 278, 279, 280, 281, 282, 283, 284, 285, 286, 287, 288, 289, 290, 291, 292, 293, 294, 295, 296, 297, 298, 299, 300, 302, 304, 306, 307, 309, 310, 311, 312], "25": [32, 36, 37, 40, 46, 47, 52, 58, 62, 63, 65, 67, 68, 69, 71, 72, 73, 86, 87, 89, 122, 123, 126, 135, 148, 149, 158, 179, 188, 192, 231, 263, 270], "return_mask": [32, 132, 179], "inlet": [32, 91, 108, 129, 130, 131, 132, 157, 188, 192, 203, 207, 215, 270], "zeros_lik": [32, 40, 52, 55, 91, 108, 127, 129, 130, 132, 157], "sequenc": [32, 44, 45, 46, 47, 63, 127, 130, 132, 157, 179, 191, 196, 197, 199, 244], "wa": [32, 48, 58, 61, 62, 63, 81, 85, 86, 87, 91, 95, 98, 110, 115, 119, 120, 121, 122, 123, 124, 126, 130, 132, 139, 156, 157, 158, 177, 189, 191, 196, 197, 198, 200, 208, 210, 213, 244, 251, 266, 269, 270, 275, 281, 300, 306], "after": [32, 54, 56, 62, 85, 86, 90, 92, 97, 102, 103, 104, 121, 123, 124, 131, 185, 186, 187, 200, 213, 221, 239, 241, 248, 253, 257, 260, 267, 271, 317], "cutoff": 32, "output": [32, 48, 85, 108, 118, 132, 148, 156, 158, 160, 167, 168, 186, 187, 229, 232, 233, 234, 235, 236, 267, 296, 308], "howev": [32, 70, 86, 91, 98, 115, 117, 123, 126, 129, 132, 133, 166, 188, 201], "order": [32, 63, 70, 73, 115, 116, 182, 191, 201, 262, 270, 287, 309], "first": [32, 40, 58, 63, 72, 74, 85, 86, 92, 94, 103, 110, 111, 113, 115, 117, 126, 129, 130, 132, 133, 160, 162, 166, 168, 185, 189, 217, 225, 226, 248, 253, 257, 261, 275], "abov": [32, 46, 47, 48, 58, 59, 62, 63, 80, 82, 91, 111, 113, 114, 118, 121, 122, 123, 129, 130, 132, 148, 158, 168, 257, 304], "mask": [32, 104, 105, 106, 113, 124, 138, 179, 188, 192, 203, 207, 211, 214, 253, 259, 269, 270, 277, 279, 280, 303, 304], "treat": [32, 79, 121, 122, 191, 220, 257, 259], "d": [32, 63, 106, 110, 132, 261, 269, 294], "see": [32, 58, 59, 62, 63, 82, 86, 117, 118, 120, 121, 124, 129, 130, 132, 133, 140, 185, 192, 216, 237, 239, 244, 249, 253, 254, 255, 257, 260, 267, 270], "iter": [32, 67, 74, 78, 80, 85, 127, 185, 193, 206, 208, 213, 220, 223, 224, 225, 226, 227, 282, 300], "backward": [32, 173], "small": [32, 72, 85, 86, 90, 92, 97, 121, 122, 129, 132, 161, 210, 213, 218, 239, 241, 248, 253, 309], "step": [32, 36, 40, 48, 59, 60, 78, 95, 111, 115, 116, 120, 121, 122, 125, 126, 129, 131, 132, 168, 179, 188, 200, 245, 269], "taken": [32, 37, 60, 62, 66, 86, 121, 122, 129, 156, 158, 163, 180, 189, 278, 281, 304, 306], "occur": [32, 108, 121, 132, 178, 188, 192, 210, 288], "ibip": [32, 157, 158, 244], "unreason": 32, "slow": [32, 37, 62, 79, 120, 121, 129, 161, 258, 309], "even": [32, 62, 121], "via": [32, 63, 70, 120, 128, 168, 192, 268, 269], "being": [32, 36, 40, 48, 65, 68, 82, 86, 120, 121, 132, 155], "list": [32, 36, 40, 63, 66, 67, 68, 72, 73, 74, 75, 83, 103, 104, 106, 117, 118, 132, 135, 158, 171, 172, 178, 180, 181, 185, 188, 192, 201, 202, 210, 212, 213, 215, 218, 219, 220, 221, 225, 226, 228, 232, 240, 241, 251, 252, 254, 255, 257, 264, 269, 270, 274, 275, 277, 281, 283, 290, 297, 301, 305, 306], "statist": [33, 75, 180], "calcul": [33, 73, 85, 89, 93, 94, 96, 97, 98, 102, 103, 104, 105, 106, 107, 109, 110, 113, 115, 116, 120, 121, 122, 123, 126, 128, 129, 131, 133, 173, 178, 181, 188, 193, 213, 219, 231, 237, 242, 247, 248, 249, 250, 252, 254, 255, 256, 257, 258, 259, 260, 263, 268, 269, 271, 279, 304], "r_max": [33, 42, 50, 54, 56, 60, 61, 114, 178, 200, 201, 202, 269], "variou": [33, 62, 110, 113, 167, 180, 257, 302, 306], "max": [33, 52, 53, 59, 61, 62, 86, 95, 115, 120, 123, 126, 132, 133, 180, 188, 192, 201, 247, 290], "sum": [33, 34, 67, 75, 87, 98, 99, 105, 120, 129, 132, 133, 180, 181, 239, 241, 249, 256, 258, 268], "suppli": [34, 46, 50, 71, 86, 118, 121, 129, 130, 178, 198, 199, 200, 201, 210, 217, 222, 223, 225, 226, 232, 238, 241, 269], "arrai": [34, 36, 38, 48, 49, 50, 58, 59, 60, 63, 76, 79, 82, 84, 87, 88, 89, 95, 98, 104, 105, 115, 116, 120, 123, 124, 125, 126, 129, 131, 132, 133, 135, 140, 156, 161, 164, 166, 178, 180, 181, 191, 193, 194, 196, 198, 199, 200, 201, 203, 204, 206, 210, 211, 212, 213, 215, 218, 220, 221, 225, 226, 228, 229, 232, 234, 235, 236, 237, 238, 239, 242, 247, 248, 250, 253, 254, 256, 260, 262, 264, 265, 266, 268, 269, 270, 275, 278, 280, 283, 287, 288, 290, 292, 293, 294, 295, 300, 303, 309, 311], "instanc": [34, 36, 46, 47, 121, 129, 130, 155, 175, 185, 200, 205, 221, 250, 254, 269], "when": [34, 36, 37, 46, 47, 48, 62, 72, 79, 85, 98, 112, 121, 122, 124, 132, 140, 156, 157, 171, 172, 175, 179, 185, 190, 198, 199, 205, 207, 208, 213, 235, 236, 272, 282, 289, 297, 300, 301, 305], "those": [34, 58, 62, 95, 107, 129, 154, 160, 190, 276], "allow": [34, 39, 40, 62, 76, 77, 82, 87, 103, 104, 106, 121, 130, 178, 185, 188, 192, 200, 222, 223, 225, 226, 235, 236, 242, 249, 257, 269, 289], "Or": [34, 68, 95, 111, 129, 130], "amax": [34, 181], "color": [34, 47, 58, 121, 126, 130, 132, 133, 156, 157, 166, 251, 305, 307, 312], "within": [34, 74, 79, 92, 103, 104, 105, 111, 118, 120, 121, 188, 214, 222, 223, 225, 226, 241, 256, 260, 283], "gaussian_filt": [34, 53, 62, 121, 124, 178], "w": [34, 51, 114, 117, 119, 120, 122, 294], "marker": [34, 113, 114, 121, 124, 125, 200, 201, 206, 208, 269], "last": [35, 47, 53, 62, 63, 86, 123, 129, 133, 303], "seen": [35, 40, 47, 48, 62, 82, 91, 113, 117, 125, 129, 158, 275, 296], "most": [35, 53, 62, 63, 120, 121, 122, 123, 135, 287, 300], "distant": 35, "16": [35, 40, 67, 82, 86, 89, 100, 115, 120, 121, 124, 125, 126], "pk1": [35, 121], "pk2": [35, 121], "scan": [35, 129, 182], "would": [36, 58, 62, 69, 97, 120, 121, 123, 129, 130, 140, 156, 177, 223, 231, 254, 255, 263, 268, 269, 270, 300, 312], "center": [36, 68, 72, 120, 121, 124, 129, 133, 188, 194, 212, 213, 216, 217, 218, 232, 239, 241, 248, 253, 260, 268, 278, 285, 291], "hybrid": [36, 40, 188, 192], "either": [36, 40, 43, 61, 63, 78, 79, 80, 85, 94, 95, 97, 108, 120, 121, 185, 195, 203, 211, 225, 226, 239, 244, 248, 252, 260, 268, 269, 278, 280, 282, 283, 294, 295], "bin": [36, 37, 40, 58, 62, 63, 75, 87, 89, 111, 132, 148, 154, 179, 198, 199, 237, 239, 241, 248, 253, 260, 270, 302, 306], "draw": [36, 73, 89, 90, 129], "actual": [36, 40, 53, 59, 62, 63, 67, 69, 75, 80, 86, 113, 120, 121, 122, 129, 180, 208, 248, 257], "logarithm": [36, 90, 92, 97, 130, 237], "down": [36, 37, 59, 129, 132, 212], "custom": [36, 51, 90, 92, 97, 102, 107, 109, 117, 121, 124, 178, 200, 201, 239, 241, 244, 248, 253, 254, 258, 259, 269], "linear": [36, 111, 173, 241], "bimod": 36, "fft": [36, 40, 174, 188, 192], "mio": [36, 40, 188, 192], "select": [36, 40, 63, 123, 166, 229, 296], "speed": [36, 40, 61, 70, 120, 121, 123, 129, 172, 174, 188, 192, 222, 223, 225, 226, 300], "exactli": [36, 40, 58, 113], "ensur": [36, 40, 66, 76, 77, 84, 121, 122, 123, 163, 171, 206, 225, 226, 248, 275, 287, 301], "unit": [36, 40, 85, 86, 95, 120, 121, 213, 218, 239, 241, 248, 253, 259, 260, 267], "lt1": 36, "lt2": 36, "lt3": 36, "equal": [36, 85, 86, 115, 126, 129, 139, 158, 172, 190, 213, 287, 306], "process": [36, 37, 41, 61, 62, 63, 76, 77, 78, 84, 111, 120, 121, 122, 123, 124, 129, 167, 178, 188, 189, 192, 193, 200, 201, 202, 210, 216, 225, 226, 239, 241, 248, 249, 253, 269, 297], "dask": [36, 121, 172], "behind": [36, 121, 129], "scene": [36, 121, 129], "core": [36, 40, 61, 62, 115, 121, 126, 137, 172, 178, 188, 189, 192, 202, 210, 216, 249, 276, 279], "ident": [36, 40, 59, 188, 296], "regardless": [36, 40], "non": [37, 91, 95, 108, 123, 127, 129, 130, 131, 132, 169, 175, 188, 189, 192, 197, 198, 205, 232, 244, 259, 270, 279], "layer": [37, 62, 70, 86, 115, 126, 189, 211, 259, 261, 300], "stack": [37, 189], "nois": [37, 64, 70, 87, 148, 189, 210, 216], "util": [37, 172, 260], "random_nois": 37, "75": [37, 48, 49, 64, 75, 85, 92, 127, 158], "gaussian": [37, 48, 62, 87, 172, 178, 186, 187, 189, 200, 201, 210, 269], "24": [37, 88, 91, 100, 113, 115, 126], "var": 37, "05": [37, 59, 70, 126, 216, 221], "hist": [37, 40, 62, 63, 64, 70, 87, 89, 104, 113, 133, 148, 238], "flatten": [37, 52, 62, 63, 64, 70, 87, 133, 148, 300], "edgecolor": [37, 40, 58, 59, 62, 63, 64, 65, 68, 69, 87, 90, 92, 97, 102, 104, 111, 113, 133, 148, 154, 248, 302], "k": [37, 40, 58, 59, 62, 63, 64, 65, 68, 69, 87, 90, 92, 97, 102, 104, 111, 113, 115, 121, 133, 148, 248], "filtered_im": 37, "chang": [37, 64, 87, 110, 132, 154, 166, 168, 185, 204, 231, 263], "smaller": [37, 40, 57, 59, 62, 68, 70, 79, 86, 115, 123, 172, 192, 209, 216, 300], "slice": [37, 53, 62, 63, 106, 108, 112, 113, 122, 123, 124, 133, 135, 152, 155, 163, 166, 189, 257, 274, 275, 281, 286, 297, 300, 303, 304, 306], "tomographi": [37, 63, 167, 189, 276], "rotat": [37, 67, 121, 124, 140, 161, 189, 213, 214, 273, 309], "stage": [37, 121, 122, 123, 189, 200, 201, 269], "im_x": 37, "im_i": 37, "im_z": 37, "patch": [37, 124, 189], "denois": [37, 63, 189], "im_1": 37, "im_2": 37, "im_3": 37, "maxim": [37, 113, 189, 267], "cut": [37, 189], "off": [37, 58, 119, 122, 125, 132, 133, 189], "grai": [37, 189], "level": [37, 70, 123, 189], "higher": [37, 48, 78, 107, 108, 126, 129, 132, 179, 189, 210, 216, 305], "permiss": [37, 189], "smoother": [37, 108, 189], "expens": [37, 189], "blur": [37, 48, 62, 64, 87, 103, 104, 124, 172, 186, 187, 189, 210, 254, 255, 257, 289], "featur": [37, 70, 78, 106, 108, 113, 121, 122, 138, 163, 168, 178, 189, 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196, 198, 199, 204, 223, 225, 226, 244, 279], "caus": [47, 70, 112, 121, 266, 271, 300], "fact": [47, 62, 85, 86, 90, 92, 97, 102, 103, 104, 112, 132, 213, 239, 248, 253, 260, 266, 267], "them": [47, 58, 61, 63, 73, 74, 76, 77, 79, 84, 86, 100, 115, 120, 121, 122, 123, 126, 129, 132, 200, 201, 221, 229, 233, 268, 269, 287, 322], "outlin": [48, 62, 111, 118, 120, 122, 166, 268], "paper": [48, 121, 130], "review": [48, 124, 125, 200, 201, 206, 208], "e": [48, 58, 59, 62, 64, 66, 74, 78, 84, 87, 98, 99, 110, 113, 115, 120, 122, 123, 124, 125, 126, 132, 133, 167, 168, 172, 173, 176, 178, 185, 188, 190, 200, 201, 206, 208, 215, 217, 239, 252, 261, 267, 268, 269, 270, 281, 282, 290, 300, 304], "name": [48, 58, 59, 63, 86, 113, 118, 120, 121, 123, 168, 185, 186, 187, 229, 230, 239, 241, 244, 248, 253, 254, 257, 258, 260, 268, 269, 289, 298, 302, 305], "saddl": [48, 56, 124, 208], "anoth": [48, 65, 84, 85, 92, 113, 118, 206, 238, 290, 302], "obain": 48, "combin": [48, 60, 115, 120, 121, 123, 126, 129, 130, 201, 269, 277], "itermedi": 48, "modifi": [48, 291, 320], "present": [48, 71, 106, 120, 155, 163, 177, 191, 197, 198, 285], "new": [48, 59, 63, 79, 81, 114, 115, 121, 126, 130, 131, 132, 153, 166, 168, 180, 185, 194, 222, 223, 225, 226, 239, 241, 253, 261, 264, 265, 290], "aggress": [48, 86], "trim": [48, 51, 52, 55, 57, 58, 124, 131, 138, 177, 188, 192, 193, 203, 204, 206, 209, 270, 277], "though": [48, 59, 62, 79, 86, 129, 165, 172, 191], "much": [48, 62, 67, 86, 120, 129, 135, 213, 231, 263, 268, 269], "easier": [48, 50, 86, 129], "object": [48, 58, 59, 63, 66, 75, 85, 88, 90, 91, 92, 95, 97, 102, 103, 106, 107, 109, 113, 115, 117, 121, 125, 127, 129, 130, 131, 133, 135, 152, 154, 166, 185, 200, 201, 212, 213, 221, 231, 232, 237, 239, 241, 244, 248, 253, 254, 258, 260, 263, 269, 270, 271, 272, 274, 275, 283, 286, 297, 299, 300, 302, 306], "attach": [48, 53, 121, 129, 130, 205], "thu": [48, 49, 50, 58, 59, 60, 88, 90, 91, 95, 111, 121, 129, 131, 239, 249], "sep": [48, 49, 50, 58, 59, 60, 88, 91, 95, 129, 131], "14": [48, 49, 50, 58, 59, 60, 88, 89, 91, 95, 113, 115, 121, 123, 124, 125, 126, 129, 130, 131, 133], "04": [48, 49, 50, 58, 59, 60, 88, 91, 95, 115, 126, 129, 131], "01": [48, 74, 91, 115, 126, 220, 240], "2023": [48, 49, 50, 58, 59, 60, 88, 91, 95, 115, 126, 129, 131], "kernel": [48, 70, 178], "realli": [48, 70, 124], "shown": [48, 53, 61, 62, 63, 81, 92, 111, 115, 125, 126, 132, 166, 303], "suitabl": [48, 121, 124, 125, 156, 189, 214, 238, 299, 300, 307, 312], "snow1": 48, "snow3": 48, "miss": [48, 122, 206], "skip": 48, "similar": [49, 50, 62, 80, 81, 85, 89, 106, 107, 110, 115, 116, 132, 133, 192, 258, 270], "except": [49, 50, 62, 81, 115, 123, 126, 185, 188, 192, 199, 215, 261, 269, 270, 286], "arbitrari": [49, 111, 185, 201, 277, 287], "astyp": [49, 98, 115, 116, 118, 120, 121, 166], "int": [49, 63, 66, 67, 71, 72, 74, 75, 79, 83, 98, 118, 120, 121, 129, 132, 145, 158, 169, 170, 171, 173, 175, 176, 178, 179, 182, 188, 189, 192, 193, 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168, 174, 189], "minima": [52, 204], "extrema": [52, 117, 204, 264], "minimum": [52, 145, 156, 173, 180, 187, 240, 264, 304], "primari": 53, "float": [53, 67, 74, 75, 132, 178, 182, 189, 200, 202, 204, 210, 213, 220, 221, 224, 229, 231, 242, 243, 244, 249, 263, 269, 270, 293], "investig": [53, 121, 201, 269], "im2d": [53, 140], "im3d": [53, 63, 135, 140], "keyboardinterrupt": 53, "traceback": [53, 62, 63, 123], "recent": [53, 62, 63, 113, 123, 130], "cell": [53, 62, 63, 83, 123, 218, 228], "file": [53, 62, 63, 82, 86, 115, 123, 124, 126, 157, 168, 229, 230, 232, 233, 234, 235, 236, 267, 298, 305], "_imgen": 53, "1117": 53, "1115": 53, "els": [53, 62, 63, 98, 118], "1116": 53, "scale": [53, 62, 66, 70, 75, 78, 80, 81, 84, 86, 90, 92, 97, 102, 103, 104, 110, 112, 115, 116, 126, 201, 216, 221, 239, 241, 248, 253, 260, 267, 269, 270, 290], "1118": 53, "1119": 53, "_func": [53, 91], "965": 53, "963": 53, "964": 53, "min": [53, 62, 145, 180, 188, 192, 237, 290], "std": 53, "966": 53, "erfc": 53, "sqrt": 53, "967": 53, "neighbour": [53, 103], "similarli": [53, 123, 261], "appar": 53, "adjac": [53, 254], "therefor": [53, 115, 116, 121, 126, 132], "nearbi": [54, 124, 206], "reli": 54, "nonpercol": [55, 207], "55": [55, 74], "mistakenli": [56, 208], "identifi": [56, 62, 121, 123, 132, 176, 179, 181, 190, 197, 198, 199, 208, 233, 239, 257, 279], "ridg": [56, 208], "detetmin": 56, "vari": [57, 129], "sp": [58, 87, 115, 116, 123, 126, 278], "thing": [58, 70, 86, 121, 122, 140, 168, 306], "sort": [58, 62, 172], "probe": [58, 269], "anisotrop": [58, 111, 210], "400": [58, 111, 112, 119, 121, 125], "easili": [58, 84, 85, 168, 213, 300], "done": [58, 59, 61, 62, 63, 106, 113, 115, 121, 129, 131, 132, 133, 172, 200, 245], "crds_x": 58, "crds_y": 58, "shorter": [58, 305], "skew": [58, 169, 170], "behavior": [58, 165, 181, 225, 226], "kept": [58, 113, 175, 205, 206], "trim_edg": [58, 169, 170], "sometim": [58, 84, 123, 130], "below": [58, 59, 61, 62, 63, 81, 111, 113, 120, 123, 132, 140, 216, 268, 304], "sz_x": 58, "sz_y": 58, "although": [58, 62, 82, 121, 195, 309], "quantit": [58, 63], "To": [58, 59, 66, 79, 86, 115, 120, 126, 129, 138, 157, 158, 166, 168, 201, 216, 222, 223, 225, 226, 248, 269, 305], "metric": [58, 59, 74, 84, 85, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 115, 123, 126, 129, 130, 132, 154, 167, 252, 257, 302, 310], "submodul": [58, 221, 302, 310, 317], "data_x": 58, "data_i": 58, "lump": [58, 59], "togeth": [58, 59, 61, 63, 84, 113, 123, 130, 257], "advantag": [58, 59], "access": [58, 59, 63, 106, 113, 129, 168, 185, 192, 216, 223, 249, 300, 314], "pdf": [58, 59, 90, 92, 97, 102, 104, 154, 239, 241, 248, 253, 260, 302], "autocomplet": [58, 59], "your": [58, 59, 123, 129, 157, 168], "id": [58, 59, 86], "support": [58, 59, 63, 70, 113, 157, 245, 272], "51": [58, 149], "47": [58, 100, 115, 126], "l": [58, 72, 90, 92, 111, 131, 133, 239, 241], "relfreq": [58, 239, 241], 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86, 113, 122, 124, 125, 131, 132, 155, 156, 159, 165, 305], "cm": [58, 59, 60, 67, 86, 113, 122, 124, 125, 131, 132, 155, 156, 159, 165], "twilight": [58, 159], "crd": 58, "explain": [59, 61, 110, 115, 121, 129], "closest": 59, "unlik": 59, "unaffect": 59, "effect": [59, 62, 72, 84, 121, 129, 130, 131, 192, 202, 213, 222, 223, 225, 226, 235, 236, 270], "limit": [59, 66, 75, 76, 77, 79, 111, 225, 226], "approach": [59, 70, 74, 79, 86, 111, 121, 122, 123, 132, 168, 174, 188, 260], "imagej": [59, 167, 168, 186, 187, 188], "ll": [59, 62, 63, 70, 79, 82, 84, 86, 112, 113, 122, 124, 129, 130, 322], "fun": 59, "ipykernel_5443": 59, "1607336354": 59, "simpli": [59, 120, 121, 239, 242, 268, 269, 274, 283], "foreground": [59, 84, 173, 188, 192, 203], "thk": 59, "jet": [59, 113], "doe": [59, 62, 63, 68, 76, 77, 80, 81, 86, 98, 111, 114, 118, 120, 121, 129, 140, 157, 161, 164, 172, 178, 188, 192, 195, 210, 225, 226, 268, 269, 275], "u": [59, 86, 121, 123, 129, 130], "52": [59, 60, 100, 122, 123, 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"Apply reduce_peaks filter": [[42, "apply-reduce-peaks-filter"]], "blobiness": [[64, "blobiness"]], "Reproducing Images": [[64, "reproducing-images"]], "2D conn": [[53, "d-conn"]], "Local thickness": [[59, "local-thickness"]], "Generate Test Image": [[59, "generate-test-image"]], "Apply Local Thickness Filter": [[59, "apply-local-thickness-filter"]], "Extracting PSD as a Histogram": [[59, "extracting-psd-as-a-histogram"]], "PoreSpy Implementation": [[59, "porespy-implementation"]], "Converting Greyscale Images to Binary": [[62, "converting-greyscale-images-to-binary"]], "The Noise Problem": [[62, "the-noise-problem"]], "Noise Filtering": [[62, "noise-filtering"]], "Non-Edge Preserving Filters": [[62, "non-edge-preserving-filters"]], "Edge Preserving Filters": [[62, "edge-preserving-filters"]], "Applying Non-Local Means to a Stack": [[62, "applying-non-local-means-to-a-stack"]], "SNOW partitioning parallel": [[61, "snow-partitioning-parallel"]], "Create a random image of overlapping spheres": [[61, "create-a-random-image-of-overlapping-spheres"]], "Apply SNOW_partitioning_parallel on the binary image": [[61, "apply-snow-partitioning-parallel-on-the-binary-image"]], "n": [[78, "n"], [81, "n"]], "f": [[78, "f"]], "p": [[78, "p"]], "sigma": [[48, "sigma"]], "seed": [[70, "seed"]], "frequency": [[70, "frequency"]], "octaves": [[70, "octaves"]], "gain": [[70, "gain"]], "uniform": [[70, "uniform"]], "inlets": [[40, "inlets"], [127, "inlets"]], "access limited": [[40, "access-limited"]], "inlets and outlets": [[55, "inlets-and-outlets"]], "value": [[71, "value"]], "center and corner": [[71, "center-and-corner"]], "Apply region_size filter": [[43, "apply-region-size-filter"]], "max_iter": [[74, "max-iter"]], "tol": [[74, "tol"]], "Predicting diffusive size factors of a rock sample": [[123, "predicting-diffusive-size-factors-of-a-rock-sample"]], "Import libaries and the AI model path": [[123, "import-libaries-and-the-ai-model-path"]], "Reading image of the rock sample": [[123, "reading-image-of-the-rock-sample"]], "Additional info: steps to create a subsection of the rock sample": [[123, "additional-info-steps-to-create-a-subsection-of-the-rock-sample"]], "Segmentation of the image": [[123, "segmentation-of-the-image"]], "Size factor prediction": [[123, "size-factor-prediction"]], "Generate image for testing": [[145, "generate-image-for-testing"], [148, "generate-image-for-testing"], [141, "generate-image-for-testing"], [142, "generate-image-for-testing"], [138, "generate-image-for-testing"], [139, "generate-image-for-testing"], [135, "generate-image-for-testing"], [153, "generate-image-for-testing"], [140, "generate-image-for-testing"]], "Demonstrate function": [[145, "demonstrate-function"], [148, "demonstrate-function"], [141, "demonstrate-function"], [140, "demonstrate-function"]], "scale": [[148, "scale"]], "mesh_region [WIP]": [[147, "mesh-region-wip"]], "Details of Drainage Simulations with and without Gravity": [[129, "details-of-drainage-simulations-with-and-without-gravity"]], "Basics of Peforming Drainage Simulations with and without Gravity": [[130, "basics-of-peforming-drainage-simulations-with-and-without-gravity"]], "extend_slice [WIP]": [[136, "extend-slice-wip"]], "ind": [[155, "ind"]], "kwargs": [[155, "kwargs"]], "Create image and variables": [[143, "create-image-and-variables"], [149, "create-image-and-variables"], [152, "create-image-and-variables"], [134, "create-image-and-variables"]], "Apply tool": [[143, "apply-tool"], [138, "apply-tool"], [149, "apply-tool"], [153, "apply-tool"], [152, "apply-tool"], [134, "apply-tool"]], "phases": [[121, "phases"], [120, "phases"]], "phase_alias": [[121, "phase-alias"]], "boundary_width": [[121, "boundary-width"]], "accuracy": [[121, "accuracy"], [120, "accuracy"]], "voxel_size": [[121, "voxel-size"], [120, "voxel-size"], [102, "voxel-size"], [116, "voxel-size"], [90, "voxel-size"], [104, "voxel-size"], [92, "voxel-size"], [103, "voxel-size"], [97, "voxel-size"]], "sigma and r_max": [[121, "sigma-and-r-max"]], "parallelization": [[121, "parallelization"]], "Generate Image for Testing": [[137, "generate-image-for-testing"]], "Apply tool and visualize": [[137, "apply-tool-and-visualize"]], "isolate_object [WIP]": [[144, "isolate-object-wip"]], "Finding the Tortuosity (\\tau) of an Image Using tortuosity_fd": [[131, "finding-the-tortuosity-tau-of-an-image-using-tortuosity-fd"]], "Algortihm Description": [[131, "algortihm-description"]], "Importing Packages": [[131, "importing-packages"]], "Generating the image:": [[131, "generating-the-image"]], "Running the algorithm": [[131, "running-the-algorithm"]], "Calling Values From The Output": [[131, "calling-values-from-the-output"]], "Demonstrate tool": [[142, "demonstrate-tool"]], "regions": [[120, "regions"], [115, "regions"], [116, "regions"], [104, "regions"], [114, "regions"], [93, "regions"], [103, "regions"], [105, "regions"]], "Demonstration": [[139, "demonstration"]], "marching_map [WIP]": [[146, "marching-map-wip"]], "Determining tortuosity using geometric domain decomposition": [[133, "determining-tortuosity-using-geometric-domain-decomposition"]], "Generate test image": [[133, "generate-test-image"], [132, "generate-test-image"]], "Run the function on the image": [[133, "run-the-function-on-the-image"]], "Extracting info from the DataFrame": [[133, "extracting-info-from-the-dataframe"]], "Demonstration of function": [[135, "demonstration-of-function"]], "Using AI based diffusive size factors for extracted networks": [[126, "using-ai-based-diffusive-size-factors-for-extracted-networks"]], "Trained model and supplementary materials": [[126, "trained-model-and-supplementary-materials"], [115, "trained-model-and-supplementary-materials"]], "Create test image": [[126, "create-test-image"]], "Extract the network": [[126, "extract-the-network"]], "Apply diffusive_size_factor_AI": [[126, "apply-diffusive-size-factor-ai"]], "Compare with finite difference method": [[126, "compare-with-finite-difference-method"]], "Adding boundary pores": [[122, "adding-boundary-pores"]], "Create image": [[122, "create-image"]], "SNOW network extraction (advanced)": [[124, "snow-network-extraction-advanced"]], "Generate artificial image": [[124, "generate-artificial-image"]], "Step-by-step application of the SNOW algorithm": [[124, "step-by-step-application-of-the-snow-algorithm"]], "randomize_colors [WIP]": [[150, "randomize-colors-wip"]], "results": [[154, "results"]], "**kwargs": [[154, "kwargs"], [158, "kwargs"]], "recombine [WIP]": [[151, "recombine-wip"]], "return_indices": [[140, "return-indices"]], "slice": [[158, "slice"], [156, "slice"]], "Image-based invasion percoalation": [[132, "image-based-invasion-percoalation"]], "Apply IBIP to image": [[132, "apply-ibip-to-image"]], "Do some post-processing": [[132, "do-some-post-processing"]], "Run standard MIO for comparison:": [[132, "run-standard-mio-for-comparison"]], "Compare MIO and IBIP at Equal Saturations": [[132, "compare-mio-and-ibip-at-equal-saturations"]], "Comparing Capillary Pressure Curves": [[132, "comparing-capillary-pressure-curves"]], "Compare results with trapping": [[132, "compare-results-with-trapping"]], "Make a movie of the invasion": [[132, "make-a-movie-of-the-invasion"]], "SNOW network extraction": [[125, "snow-network-extraction"]], "mask": [[156, "mask"]], "cmap": [[157, "cmap"]], "c_under": [[157, "c-under"]], "c_over": [[157, "c-over"]], "v_under": [[157, "v-under"]], "v_over": [[157, "v-over"]], "fps": [[157, "fps"]], "repeat": [[157, "repeat"]], "tortuosity_gdd": [[128, "tortuosity-gdd"]], "log": [[102, "log"], [90, "log"], [92, "log"], [97, "log"]], "model , g_train": [[115, "model-g-train"]], "throat_conns": [[115, "throat-conns"], [116, "throat-conns"]], "Compare with finite difference": [[115, "compare-with-finite-difference"]], "Apply on one conduit": [[115, "apply-on-one-conduit"]], "Creating Multiscale Images": [[84, "creating-multiscale-images"]], "Using blobs of different blobiness": [[84, "using-blobs-of-different-blobiness"]], "Using rsa to insert non-overlapping spheres into blobs": [[84, "using-rsa-to-insert-non-overlapping-spheres-into-blobs"]], "Summary": [[84, "summary"]], "diffusive_size_factor_DNS": [[116, "diffusive-size-factor-dns"]], "props_to_image": [[101, "props-to-image"]], "Measuring fractal dimension by box-counting": [[110, "measuring-fractal-dimension-by-box-counting"]], "Theory": [[110, "theory"]], "Box Counting Method": [[110, "box-counting-method"]], "Mathematical Definition": [[110, "mathematical-definition"]], "Example": [[110, "example"]], "Create image and extract network": [[119, "create-image-and-extract-network"]], "Plot the pore network": [[119, "plot-the-pore-network"]], "normalization": [[90, "normalization"]], "sierpinski_foam2": [[81, "sierpinski-foam2"]], "normed": [[96, "normed"]], "network": [[118, "network"], [117, "network"]], "alias": [[118, "alias"]], "npoints": [[107, "npoints"]], "Obtaining the porosity profile along each principle axis": [[112, "obtaining-the-porosity-profile-along-each-principle-axis"]], "Using regionprops_3d to analyze properties of each pore": [[113, "using-regionprops-3d-to-analyze-properties-of-each-pore"]], "Generating a test image": [[113, "generating-a-test-image"]], "Segementing void space into regions for individual analysis": [[113, "segementing-void-space-into-regions-for-individual-analysis"]], "Applying regionsprops_3d": [[113, "applying-regionsprops-3d"]], "Listing all available properties": [[113, "listing-all-available-properties"]], "Analyze properties for a single region": [[113, "analyze-properties-for-a-single-region"]], "Extracting one property for all regions as an array": [[113, "extracting-one-property-for-all-regions-as-an-array"]], "Creating a composite image of region images": [[113, "creating-a-composite-image-of-region-images"]], "Creating a colorized image based on region properties": [[113, "creating-a-colorized-image-based-on-region-properties"]], "Generating fibrous mats": [[85, "generating-fibrous-mats"]], "The lineal path function": [[111, "the-lineal-path-function"]], "flat_faces": [[83, "flat-faces"]], "r radius": [[83, "r-radius"]], "ncells": [[83, "ncells"]], "Generating Sphere Packings from Digital Rocks Portal": [[86, "generating-sphere-packings-from-digital-rocks-portal"]], "Finney Packing": [[86, "finney-packing"]], "Bidisperse Sphere Packs": [[86, "bidisperse-sphere-packs"]], "verts, faces": [[94, "verts-faces"]], "spheres_from_coords": [[82, "spheres-from-coords"]], "df": [[82, "df"]], "smooth": [[82, "smooth"]], "pc": [[95, "pc"]], "srange": [[91, "srange"]], "areas": [[103, "areas"]], "dmin and n": [[80, "dmin-and-n"]], "ndim": [[80, "ndim"]], "max_size": [[80, "max-size"]], "s": [[108, "s"]], "span": [[108, "span"]], "Making blobs": [[87, "making-blobs"]]}, "indexentries": {"apply_chords() (in module porespy.filters)": [[169, "porespy.filters.apply_chords"]], "apply_chords_3d() (in module porespy.filters)": [[170, "porespy.filters.apply_chords_3D"]], "apply_padded() (in module porespy.filters)": [[171, "porespy.filters.apply_padded"]], "chunked_func() (in module porespy.filters)": [[172, "porespy.filters.chunked_func"]], "distance_transform_lin() (in module porespy.filters)": [[173, "porespy.filters.distance_transform_lin"]], "fftmorphology() (in module porespy.filters)": [[174, "porespy.filters.fftmorphology"]], "fill_blind_pores() (in module porespy.filters)": [[175, "porespy.filters.fill_blind_pores"]], "find_disconnected_voxels() (in module porespy.filters)": [[176, "porespy.filters.find_disconnected_voxels"]], "find_dt_artifacts() (in module porespy.filters)": [[177, "porespy.filters.find_dt_artifacts"]], "find_peaks() (in module porespy.filters)": [[178, "porespy.filters.find_peaks"]], "find_trapped_regions() (in module porespy.filters)": [[179, "porespy.filters.find_trapped_regions"]], "flood() (in module porespy.filters)": [[180, "porespy.filters.flood"]], "flood_func() (in module porespy.filters)": [[181, "porespy.filters.flood_func"]], "hold_peaks() (in module porespy.filters)": [[182, "porespy.filters.hold_peaks"]], "ibip() (in module porespy.filters)": [[183, "porespy.filters.ibip"]], "ibip_gpu() (in module porespy.filters)": [[184, "porespy.filters.ibip_gpu"]], "imagej": [[185, "module-imagej"]], "module": [[185, "module-imagej"], [313, "module-porespy.filters"], [314, "module-porespy.filters.imagej"], [315, "module-porespy.generators"], [316, "module-porespy.io"], [317, "module-porespy.metrics"], [318, "module-porespy.networks"], [319, "module-porespy.simulations"], [320, "module-porespy.tools"], [321, "module-porespy.visualization"], [322, "module-porespy"]], "imagej_plugin() (in module porespy.filters.imagej)": [[186, "porespy.filters.imagej.imagej_plugin"]], "imagej_wrapper() (in module porespy.filters.imagej)": [[187, "porespy.filters.imagej.imagej_wrapper"]], "local_thickness() (in module porespy.filters)": [[188, "porespy.filters.local_thickness"]], "nl_means_layered() (in module porespy.filters)": [[189, "porespy.filters.nl_means_layered"]], "nphase_border() (in module porespy.filters)": [[190, "porespy.filters.nphase_border"]], "pc_to_satn() (in module porespy.filters)": [[191, "porespy.filters.pc_to_satn"]], "porosimetry() (in module porespy.filters)": [[192, "porespy.filters.porosimetry"]], "prune_branches() (in module porespy.filters)": [[193, "porespy.filters.prune_branches"]], "reduce_peaks() (in module porespy.filters)": [[194, "porespy.filters.reduce_peaks"]], "region_size() (in module porespy.filters)": [[195, "porespy.filters.region_size"]], "satn_to_seq() (in module porespy.filters)": [[196, "porespy.filters.satn_to_seq"]], "seq_to_satn() (in module porespy.filters)": [[197, "porespy.filters.seq_to_satn"]], "size_to_satn() (in module porespy.filters)": [[198, "porespy.filters.size_to_satn"]], "size_to_seq() (in module porespy.filters)": [[199, "porespy.filters.size_to_seq"]], "snow_partitioning() (in module porespy.filters)": [[200, "porespy.filters.snow_partitioning"]], "snow_partitioning_n() (in module porespy.filters)": [[201, "porespy.filters.snow_partitioning_n"]], "snow_partitioning_parallel() (in module porespy.filters)": [[202, "porespy.filters.snow_partitioning_parallel"]], "trim_disconnected_blobs() (in module porespy.filters)": [[203, "porespy.filters.trim_disconnected_blobs"]], "trim_extrema() (in module porespy.filters)": [[204, "porespy.filters.trim_extrema"]], "trim_floating_solid() (in module porespy.filters)": [[205, "porespy.filters.trim_floating_solid"]], "trim_nearby_peaks() (in module porespy.filters)": [[206, "porespy.filters.trim_nearby_peaks"]], "trim_nonpercolating_paths() (in module porespy.filters)": [[207, "porespy.filters.trim_nonpercolating_paths"]], "trim_saddle_points() (in module porespy.filters)": [[208, "porespy.filters.trim_saddle_points"]], "trim_small_clusters() (in module porespy.filters)": [[209, "porespy.filters.trim_small_clusters"]], "blobs() (in module porespy.generators)": [[210, "porespy.generators.blobs"]], "borders() (in module porespy.generators)": [[211, "porespy.generators.borders"]], "bundle_of_tubes() (in module porespy.generators)": [[212, "porespy.generators.bundle_of_tubes"]], "cylinders() (in module porespy.generators)": [[213, "porespy.generators.cylinders"]], "cylindrical_plug() (in module porespy.generators)": [[214, "porespy.generators.cylindrical_plug"]], "faces() (in module porespy.generators)": [[215, "porespy.generators.faces"]], "fractal_noise() (in module porespy.generators)": [[216, "porespy.generators.fractal_noise"]], "insert_shape() (in module porespy.generators)": [[217, "porespy.generators.insert_shape"]], "lattice_spheres() (in module porespy.generators)": [[218, "porespy.generators.lattice_spheres"]], "line_segment() (in module porespy.generators)": [[219, "porespy.generators.line_segment"]], "overlapping_spheres() (in module porespy.generators)": [[220, "porespy.generators.overlapping_spheres"]], "polydisperse_spheres() (in module porespy.generators)": [[221, "porespy.generators.polydisperse_spheres"]], "pseudo_electrostatic_packing() (in module porespy.generators)": [[222, "porespy.generators.pseudo_electrostatic_packing"]], "pseudo_gravity_packing() (in module porespy.generators)": [[223, "porespy.generators.pseudo_gravity_packing"]], "random_cantor_dust() (in module porespy.generators)": [[224, "porespy.generators.random_cantor_dust"]], "random_spheres() (in module porespy.generators)": [[225, "porespy.generators.random_spheres"]], "rsa() (in module porespy.generators)": [[226, "porespy.generators.rsa"]], "sierpinski_foam() (in module porespy.generators)": [[227, "porespy.generators.sierpinski_foam"]], "voronoi_edges() (in module porespy.generators)": [[228, "porespy.generators.voronoi_edges"]], "dict_to_vtk() (in module porespy.io)": [[229, "porespy.io.dict_to_vtk"]], "open_paraview() (in module porespy.io)": [[230, "porespy.io.open_paraview"]], "openpnm_to_im() (in module porespy.io)": [[231, "porespy.io.openpnm_to_im"]], "spheres_to_comsol() (in module porespy.io)": [[232, "porespy.io.spheres_to_comsol"]], "to_palabos() (in module porespy.io)": [[233, "porespy.io.to_palabos"]], "to_paraview() (in module porespy.io)": [[234, "porespy.io.to_paraview"]], "to_stl() (in module porespy.io)": [[235, "porespy.io.to_stl"]], "to_vtk() (in module porespy.io)": [[236, "porespy.io.to_vtk"]], "boxcount() (in module porespy.metrics)": [[237, "porespy.metrics.boxcount"]], "chord_counts() (in module porespy.metrics)": [[238, "porespy.metrics.chord_counts"]], "chord_length_distribution() (in module porespy.metrics)": [[239, "porespy.metrics.chord_length_distribution"]], "find_h() (in module porespy.metrics)": [[240, "porespy.metrics.find_h"]], "lineal_path_distribution() (in module porespy.metrics)": [[241, "porespy.metrics.lineal_path_distribution"]], "mesh_surface_area() (in module porespy.metrics)": [[242, "porespy.metrics.mesh_surface_area"]], "mesh_volume() (in module porespy.metrics)": [[243, "porespy.metrics.mesh_volume"]], "pc_curve() (in module porespy.metrics)": [[244, "porespy.metrics.pc_curve"]], "pc_curve_from_ibip() (in module porespy.metrics)": [[245, "porespy.metrics.pc_curve_from_ibip"]], "pc_curve_from_mio() (in module porespy.metrics)": [[246, "porespy.metrics.pc_curve_from_mio"]], "phase_fraction() (in module porespy.metrics)": [[247, "porespy.metrics.phase_fraction"]], "pore_size_distribution() (in module porespy.metrics)": [[248, "porespy.metrics.pore_size_distribution"]], "porosity() (in module porespy.metrics)": [[249, "porespy.metrics.porosity"]], "porosity_profile() (in module porespy.metrics)": [[250, "porespy.metrics.porosity_profile"]], "prop_to_image() (in module porespy.metrics)": [[251, "porespy.metrics.prop_to_image"]], "props_to_dataframe() (in module porespy.metrics)": [[252, "porespy.metrics.props_to_DataFrame"]], "radial_density_distribution() (in module porespy.metrics)": [[253, "porespy.metrics.radial_density_distribution"]], "region_interface_areas() (in module porespy.metrics)": [[254, "porespy.metrics.region_interface_areas"]], "region_surface_areas() (in module porespy.metrics)": [[255, "porespy.metrics.region_surface_areas"]], "region_volumes() (in module porespy.metrics)": [[256, "porespy.metrics.region_volumes"]], "regionprops_3d() (in module porespy.metrics)": [[257, "porespy.metrics.regionprops_3D"]], "representative_elementary_volume() (in module porespy.metrics)": [[258, "porespy.metrics.representative_elementary_volume"]], "satn_profile() (in module porespy.metrics)": [[259, "porespy.metrics.satn_profile"]], "two_point_correlation() (in module porespy.metrics)": [[260, "porespy.metrics.two_point_correlation"]], "add_boundary_regions() (in module porespy.networks)": [[261, "porespy.networks.add_boundary_regions"]], "diffusive_size_factor_ai() (in module porespy.networks)": [[262, "porespy.networks.diffusive_size_factor_AI"]], "generate_voxel_image() (in module porespy.networks)": [[263, "porespy.networks.generate_voxel_image"]], "label_boundaries() (in module porespy.networks)": [[264, "porespy.networks.label_boundaries"]], "label_phases() (in module porespy.networks)": [[265, "porespy.networks.label_phases"]], "map_to_regions() (in module porespy.networks)": [[266, "porespy.networks.map_to_regions"]], "maximal_ball_wrapper() (in module porespy.networks)": [[267, "porespy.networks.maximal_ball_wrapper"]], "regions_to_network() (in module porespy.networks)": [[268, "porespy.networks.regions_to_network"]], "snow2() (in module porespy.networks)": [[269, "porespy.networks.snow2"]], "drainage() (in module porespy.simulations)": [[270, "porespy.simulations.drainage"]], "tortuosity_fd() (in module porespy.simulations)": [[271, "porespy.simulations.tortuosity_fd"]], "results (class in porespy.tools)": [[272, "porespy.tools.Results"]], "align_image_with_openpnm() (in module porespy.tools)": [[273, "porespy.tools.align_image_with_openpnm"]], "bbox_to_slices() (in module porespy.tools)": [[274, "porespy.tools.bbox_to_slices"]], "extend_slice() (in module porespy.tools)": [[275, "porespy.tools.extend_slice"]], "extract_cylinder() (in module porespy.tools)": [[276, "porespy.tools.extract_cylinder"]], "extract_regions() (in module porespy.tools)": [[277, "porespy.tools.extract_regions"]], "extract_subsection() (in module porespy.tools)": [[278, "porespy.tools.extract_subsection"]], "find_outer_region() (in module porespy.tools)": [[279, "porespy.tools.find_outer_region"]], "get_border() (in module porespy.tools)": [[280, "porespy.tools.get_border"]], "get_planes() (in module porespy.tools)": [[281, "porespy.tools.get_planes"]], "get_tqdm() (in module porespy.tools)": [[282, "porespy.tools.get_tqdm"]], "in_hull() (in module porespy.tools)": [[283, "porespy.tools.in_hull"]], "insert_cylinder() (in module porespy.tools)": [[284, "porespy.tools.insert_cylinder"]], "insert_sphere() (in module porespy.tools)": [[285, "porespy.tools.insert_sphere"]], "isolate_object() (in module porespy.tools)": [[286, "porespy.tools.isolate_object"]], "make_contiguous() (in module porespy.tools)": [[287, "porespy.tools.make_contiguous"]], "marching_map() (in module porespy.tools)": [[288, "porespy.tools.marching_map"]], "mesh_region() (in module porespy.tools)": [[289, "porespy.tools.mesh_region"]], "norm_to_uniform() (in module porespy.tools)": [[290, "porespy.tools.norm_to_uniform"]], "overlay() (in module porespy.tools)": [[291, "porespy.tools.overlay"]], "ps_ball() (in module porespy.tools)": [[292, "porespy.tools.ps_ball"]], "ps_disk() (in module porespy.tools)": [[293, "porespy.tools.ps_disk"]], "ps_rect() (in module porespy.tools)": [[294, "porespy.tools.ps_rect"]], "ps_round() (in module porespy.tools)": [[295, "porespy.tools.ps_round"]], "randomize_colors() (in module porespy.tools)": [[296, "porespy.tools.randomize_colors"]], "recombine() (in module porespy.tools)": [[297, "porespy.tools.recombine"]], "sanitize_filename() (in module porespy.tools)": [[298, "porespy.tools.sanitize_filename"]], "show_docstring() (in module porespy.tools)": [[299, "porespy.tools.show_docstring"]], "subdivide() (in module porespy.tools)": [[300, "porespy.tools.subdivide"]], "unpad() (in module porespy.tools)": [[301, "porespy.tools.unpad"]], "bar() (in module porespy.visualization)": [[302, "porespy.visualization.bar"]], "imshow() (in module porespy.visualization)": [[303, "porespy.visualization.imshow"]], "prep_for_imshow() (in module porespy.visualization)": [[304, "porespy.visualization.prep_for_imshow"]], "satn_to_movie() (in module porespy.visualization)": [[305, "porespy.visualization.satn_to_movie"]], "satn_to_panels() (in module porespy.visualization)": [[306, "porespy.visualization.satn_to_panels"]], "sem() (in module porespy.visualization)": [[307, "porespy.visualization.sem"]], "set_mpl_style() (in module porespy.visualization)": [[308, "porespy.visualization.set_mpl_style"]], "show_3d() (in module porespy.visualization)": [[309, "porespy.visualization.show_3D"]], "show_mesh() (in module porespy.visualization)": [[310, "porespy.visualization.show_mesh"]], "show_planes() (in module porespy.visualization)": [[311, "porespy.visualization.show_planes"]], "xray() (in module porespy.visualization)": [[312, "porespy.visualization.xray"]], "porespy.filters": [[313, "module-porespy.filters"]], "porespy.filters.imagej": [[314, "module-porespy.filters.imagej"]], "porespy.generators": [[315, "module-porespy.generators"]], "porespy.io": [[316, "module-porespy.io"]], "porespy.metrics": [[317, "module-porespy.metrics"]], "porespy.networks": [[318, "module-porespy.networks"]], "porespy.simulations": [[319, "module-porespy.simulations"]], "porespy.tools": [[320, "module-porespy.tools"]], "porespy.visualization": [[321, "module-porespy.visualization"]], "porespy": [[322, "module-porespy"]]}}) \ No newline at end of file