fix: rows in dataframe

features/rt-cetsa-intensity-extraction-tool/pyproject.toml

@@ -21,6 +21,9 @@ bfio = "^2.3.6"
 bump2version = "^1.0.1"
 pre-commit = "^3.1.0"
 pytest = "^7.2.1"
+scikit-image = "0.22.0"
+tifffile = "^2024.5.10"
+polus_images_segmentation_rt_cetsa_plate_extraction = { path = "../../segmentation/rt-cetsa-plate-extraction-tool", develop = true }
 
 [build-system]
 requires = ["poetry-core"]

features/rt-cetsa-intensity-extraction-tool/src/polus/images/features/rt_cetsa_intensity_extraction/__init__.py

@@ -96,9 +96,6 @@ def index_to_battleship(x: int, y: int, size: PlateSize) -> str:
         row = "A"
     row = row + string.ascii_uppercase[y % 26]
 
-    # TODO: uncomment this when we are ready to deploy, this is the standard notation
-    # if size.value >= 96:
-
     return f"{row}{x+1}"
 
 
@@ -122,6 +119,7 @@ def build_df(
 
     # sort intensities by temperature
     intensities.sort(key=lambda x: x[0])
+    rows: list[list[float]] = [[a, *b] for a, b in intensities]
 
     # build header
     header = ["Temperature"]
@@ -134,7 +132,7 @@ def build_df(
         header.append(index_to_battleship(x, y, plate_size))
 
     # build DataFrame
-    df = pandas.DataFrame(intensities, columns=header)
+    df = pandas.DataFrame(rows, columns=header)
 
     # Set the temperature as the index
     df.set_index("Temperature", inplace=True)

features/rt-cetsa-intensity-extraction-tool/tests/__init__.py

@@ -0,0 +1 @@
+"""Tests for the tool."""

features/rt-cetsa-intensity-extraction-tool/tests/test_plate.py

@@ -0,0 +1,79 @@
+import pathlib
+import numpy
+from skimage.draw import disk
+from skimage.transform import rotate
+from tifffile import imwrite
+
+from polus.images.features.rt_cetsa_intensity_extraction import build_df
+from polus.images.segmentation.rt_cetsa_plate_extraction import extract_plate
+
+
+def gen_plate(
+    size: tuple[int, int],
+    radius: int,
+    trim: int,
+    angle: int,
+    inp_dir: pathlib.Path,
+) -> numpy.ndarray:
+    """Generate a plate image."""
+
+    # Calculate the size of the plate
+    well_size = 2 * (radius + trim)
+    plate_size = (size[0] * well_size, size[1] * well_size)
+    plate = numpy.zeros(plate_size, dtype=numpy.uint8)
+
+    # Generate the wells
+    x_centers = numpy.arange(radius + trim, plate_size[0], well_size)
+    y_centers = numpy.arange(radius + trim, plate_size[1], well_size)
+    for xc in x_centers:
+        for yc in y_centers:
+            rr, cc = disk((xc, yc), radius)
+            plate[rr, cc] = 1
+
+    # Add noise to the wells
+    rng = numpy.random.default_rng()
+    noise = rng.poisson(16, size=plate.shape).astype(numpy.uint8)
+    plate *= noise
+
+    background = rng.poisson(2, size=plate.shape).astype(numpy.uint8)
+    plate += background
+
+    # Rotate the plate
+    plate = rotate(plate, -angle, resize=True, cval=0)
+
+    # Pad the plate with zeros
+    pad = trim * min(size)
+    plate = numpy.pad(plate, pad_width=pad, mode="constant", constant_values=0)
+
+    return plate
+
+
+def test_tool():
+    data_dir = pathlib.Path(__file__).parent.parent / "data"
+    inp_dir = data_dir / "input"
+    out_dir = data_dir / "output"
+
+    size = (16, 24)
+    radius = 20
+    trim = 5
+    angle = 15
+
+    paths = []
+    for i in range(1, 4):
+        p_path = inp_dir / f"plate_{i}.tif"
+        m_path = inp_dir / f"mask_{i}.tif"
+
+        plate = gen_plate(size, radius, trim, angle, inp_dir)
+        imwrite(p_path, plate)
+
+        plate, mask = extract_plate(p_path)
+        imwrite(p_path, plate)
+        imwrite(m_path, mask)
+
+        paths.append((p_path, m_path))
+
+    df = build_df(paths)
+    path = out_dir / "intensities.csv"
+    df.to_csv(path)
+
+    assert path.exists()