Update dockerfile (#27)

* update libgl1 installation

* allow breaking of system packages

* check pip version for command line options

* use venv

* reformat files with Black

Dockerfile

@@ -10,26 +10,35 @@ ARG CC=gcc-9
 ARG CXX=g++-9
 
 RUN apt-get update && \
-    apt-get install -y autoconf automake libtool pkg-config libgl1-mesa-glx && \
+    apt-get install -y autoconf automake libtool pkg-config && \
     apt-get install -y gcc-9 g++-9 && \
     apt-get install -y cmake git wget && \
     apt-get install -y libarmadillo-dev && \
     apt-get install -y libcfitsio-dev && \
     apt-get install -y libfftw3-dev && \
+    apt-get install -y libgl1 && \
     apt-get install -y libgsl-dev && \
     apt-get install -y libsharp-dev && \
     apt-get install -y libhealpix-cxx-dev && \
     apt-get install -y healpy-data && \
-    apt-get install -y python3 python3-pip && \
+    apt-get install -y python3 python3-pip python3-venv && \
     apt-get clean
 
-ENV HEALPIX /usr/share/healpy
+ENV HEALPIX=/usr/share/healpy
 
-RUN python3 -m pip install jupyter
+RUN python3 -m venv /venv
+
+RUN source /venv/bin/activate && \
+    pip install --upgrade pip
+
+RUN source /venv/bin/activate && \
+    pip install jupyter
 
 COPY . /home
 
-RUN cd /home && \
-    python3 -m pip install .
+RUN source /venv/bin/activate && \
+    pip install /home
+
+RUN echo "source /venv/bin/activate" >> ~/.bashrc
 
-RUN echo -e '#!/bin/bash\njupyter notebook --port=8888 --no-browser --ip=0.0.0.0 --allow-root' > /usr/bin/notebook && chmod +x /usr/bin/notebook
+RUN echo -e '#!/bin/bash\nsource /venv/bin/activate\njupyter notebook --port=8888 --no-browser --ip=0.0.0.0 --allow-root' > /usr/bin/notebook && chmod +x /usr/bin/notebook

pycs/astro/wl/mass_mapping.py

@@ -913,9 +913,9 @@ def _prepare_data(self, InshearData, msg=None, niter=None, Nsigma=None):
             mask = (InshearData.Ncov != 0).astype(int)  # shape = (nx, ny)
         else:
             mask = InshearData.mask
-        InshearData.Ncov[InshearData.Ncov == 0] = (
-            1e9  # infinite value for no measurement
-        )
+        InshearData.Ncov[
+            InshearData.Ncov == 0
+        ] = 1e9  # infinite value for no measurement
         Ncv = InshearData.Ncov / 2.0  # shape = (nx, ny)
 
         # find the minimum noise variance
@@ -929,9 +929,9 @@ def _prepare_data(self, InshearData, msg=None, niter=None, Nsigma=None):
         eta = tau
         # compute signal coefficient
         Esn = eta / Ncv  # shape = (nx, ny)
-        Esn[Esn == np.inf] = (
-            0  # TODO: useless if we have set Ncv[mask == 0] = 1e9 before
-        )
+        Esn[
+            Esn == np.inf
+        ] = 0  # TODO: useless if we have set Ncv[mask == 0] = 1e9 before
 
         return gamma1, gamma2, nx, ny, eta, Esn, mask, ind, tau, niter, Nsigma
 

pycs/sparsity/sparse2d/mr_filter.py

@@ -16,6 +16,8 @@
 from datetime import datetime
 from astropy.io import fits
 import shlex
+
+
 ##
 #  Function that calls mr_filter to perform a wavelet filtering on the
 #  input data.
@@ -29,27 +31,26 @@
 #
 # %load_ext autoreload
 # %autoreload 2
-def mr_filter(data, opt=None, path='./', remove_files=True):
-
+def mr_filter(data, opt=None, path="./", remove_files=True):
     # Create a unique string using the current date and time.
     # print('mr_filter ', opt)
-    unique_string = datetime.now().strftime('%Y.%m.%d_%H.%M.%S')
-    result=0
+    unique_string = datetime.now().strftime("%Y.%m.%d_%H.%M.%S")
+    result = 0
     # Set the ouput file names.
-    file_name = path + 'mr_temp_' + unique_string
-    file_fits = file_name + '.fits'
-    file_out = file_name + '_out.fits'
+    file_name = path + "mr_temp_" + unique_string
+    file_fits = file_name + ".fits"
+    file_out = file_name + "_out.fits"
 
     # Write the input data to a fits file.
     fits.writeto(file_fits, data)
 
-    cmd = 'mr_filter '
+    cmd = "mr_filter "
 
     if isinstance(opt, type(None)):
-        optF=' '
+        optF = " "
     else:
-        optF=opt
-    cmd = cmd + optF + ' ' + file_fits + ' '  + file_out
+        optF = opt
+    cmd = cmd + optF + " " + file_fits + " " + file_out
     # print 'CMD = ', cmd
     args = shlex.split(cmd)
     # print('args ', args)

pycs/sparsity/sparse2d/mr_gmca.py

@@ -19,6 +19,7 @@
 from pycs.misc.cosmostat_init import *
 from pycs.misc.cosmostat_init import writefits
 
+
 ##
 #  Function that calls mr_gmca to perform blind source separation on the
 #  input data.
@@ -32,20 +33,19 @@
 #
 # %load_ext autoreload
 # %autoreload 2
-def mr_gmca(data, opt=None, path='./', remove_files=True, verbose=False, FileOut=None):
-
+def mr_gmca(data, opt=None, path="./", remove_files=True, verbose=False, FileOut=None):
     # Create a unique string using the current date and time.
     # print('mr_filter ', opt)
-    prog="mr_gmca"
-    unique_string = datetime.now().strftime('%Y.%m.%d_%H.%M.%S')
-    result=0
+    prog = "mr_gmca"
+    unique_string = datetime.now().strftime("%Y.%m.%d_%H.%M.%S")
+    result = 0
     # Set the ouput file names.
-    file_name = path + 'mr_temp_' + unique_string
-    file_fits = file_name + '.fits'
+    file_name = path + "mr_temp_" + unique_string
+    file_fits = file_name + ".fits"
     if FileOut is not None:
         file_out = FileOut
     else:
-        file_out = file_name + '_out'
+        file_out = file_name + "_out"
 
     # Write the input data to a fits file.
     writefits(file_fits, data)
@@ -54,15 +54,15 @@ def mr_gmca(data, opt=None, path='./', remove_files=True, verbose=False, FileOut
     cmd = prog
 
     if isinstance(opt, type(None)):
-        optF=' '
+        optF = " "
     else:
-        optF= opt
+        optF = opt
     if verbose:
         optF = optF + " -v "
 
-    cmd = cmd + " " + optF + " "  + file_fits + " "   + file_out
+    cmd = cmd + " " + optF + " " + file_fits + " " + file_out
     if verbose:
-        print ('CMD = ', cmd)
+        print("CMD = ", cmd)
 
     args = shlex.split(cmd)
     # print('args ', args)
@@ -72,19 +72,18 @@ def mr_gmca(data, opt=None, path='./', remove_files=True, verbose=False, FileOut
     file_out_source = file_out + ".fits"
     file_out_mat = path + "xx_EstMixmat.fits"
     file_out_invmat = path + "xx_InvMixingMat.fits"
-    
+
     result = readfits(file_out_source)
     est_mixmat = readfits(file_out_mat)
-    est_invmixmat = readfits (file_out_invmat)
+    est_invmixmat = readfits(file_out_invmat)
 
-
     # Return the mr_transform results (and the output file names).
     if remove_files:
         remove(file_fits)
         remove(file_out_source)
         remove(file_out_mat)
         remove(file_out_invmat)
 
-        return result,est_mixmat,est_invmixmat
+        return result, est_mixmat, est_invmixmat
     else:
-        return result,est_mixmat,est_invmixmat
+        return result, est_mixmat, est_invmixmat