Minor fixes to code & edits of docs +++ textual feedback #45
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I went through the docs and executed the tutorials; I really enjoyed it. The only critical fix to make models run on my system is commit 'Run models whose absolute path contains a whitespace'. The rest are purely suggestions. @pabloitu Feel free to take what you need 😏
Further comments that require more elaboration follow below 🙂
I installed floatCSEP both via the latest version from github and the stable release from conde-forge; both install fine.
btw:
floatcsep/__init__.py
is at__version__ = "0.1.4"
installation instructions:
conda env create -n csep_env
expects anenvironment.yml
. So this can only be executed inside the floatCSEP folder; what you meant (in both cases) isconda create -n csep_env
(withoutenv
). To keep using the one withenv
at least for section Latest Version > 1. Usingconda
, you only have to reorder your commands, that is,create env
aftercd floatcsep
; this has a bonus: all dependencies are installed by conda, not pip. I did that in my PR and provided further suggestions. I guess this solves the issue of Toño.pycsep
manually, since it's already specified as dependency); I'd only mention theconda-forge
install option and link to the docs for alternative ways.markdown reports:
results
folder becomes "portable" and self-contained, that is, can be moved somewhere else or to other devices without breaking links..html
file, which can be viewed with a browser; either write out directly or convert from markdown using a separate package likemarkdown
orpygments
. However, those won't be consumed by GitHub.width=
parameter for the 'Input catalog' figures (I like 800). (I didn't touch the code because I didn't know how to do it for this figure table.)##
-heading, otherwise they hierarchically appear under "Authoritative Data".plots/figures:
Case D:
2020-01-01_2021-01-01/figures
(together with the test results). Also, it might we worthwhile to include them in the report (e.g., a section between input data and results:## Forecast(s)
).Case E:
use_db: False
is indeed muuuch slower (~10x).use_db: True
as the default in init ofTimeIndependentModel
?HDF5Serializer
will eventually be replaced bydbcsep
, correct?{timewindow}/forecasts
but (only) in2010-01-01_2022-01-01/figures
(i.e., only the last date and together with the test results). Again, it might we worthwhile to include them in the report.'viridis'
?case_e.py
file in the folder; does it have a purpose?Case F:
2016-11-20_2016-11-21/figures
). This made sense for time-independent models, but not so much for a T-D forecast. Also, it might we worthwhile to mention those outputs again in the doc of case F (and perhaps include them in the report).Case G:
build: venv
is incompatible with running floatCSEP in a conda env; this warning is printed and it doesn't findpymock
. In the following, I usebuild: conda
(using mamba, which it nicely detects) and assume thatbuild: venv
won't work inside an active conda env; not sure if it works on your system.build: venv
to use conda by default (since most users will work in a conda env per install instructions); if you do, don't forget to adapt the 'Important' box;conda remove -n pymock_<hash> --all
);build: venv
won't work when already working in a conda environment (if it is truly so).args_file
path into quotation marks (see commit)build: venv
, additionally also theactivate_script
path must be set in quotation marks (see commit)## Custom plots
).2012-06-13_2012-06-20/figures
) + it might we worthwhile to mention those outputs again in the doc of case G (and perhaps include them in the report).Case H:
misc:
floatcsep
,floatCSEP
, and floatCSEP in the docs; I'd homogenize it for "brand recognition" 😄