From ef4fbdaf1f94e379af11bbb50f2dfa3c176ddbfc Mon Sep 17 00:00:00 2001
From: AK <kutkin@gmail.com>
Date: Mon, 3 Jul 2023 14:47:40 +0000
Subject: [PATCH] fix matplotlib version
---
Dockerfile | 24 ++++++++++++------------
autocorrelations.py | 9 ++++++---
cluster.py | 5 +++--
3 files changed, 21 insertions(+), 17 deletions(-)
mode change 100644 => 100755 autocorrelations.py
diff --git a/Dockerfile b/Dockerfile
index 795026f..cc5bee0 100644
--- a/Dockerfile
+++ b/Dockerfile
@@ -4,7 +4,7 @@ FROM ubuntu:20.04 as builder
# It lives on the head of its dependencies.
# Install all build-time dependencies
-RUN export DEBIAN_FRONTEND=noninteractive && \
+RUN export DEBIAN_FRONTEND=noninteractive && \
apt-get update && \
apt-get install -y \
bison \
@@ -13,7 +13,7 @@ RUN export DEBIAN_FRONTEND=noninteractive && \
casacore-dev \
cmake \
flex \
- gfortran \
+ gfortran \
git \
libblas-dev \
libboost-date-time-dev \
@@ -61,7 +61,7 @@ RUN git clone --depth 1 --branch ${DYSCO_VERSION} \
cd dysco/build && \
cmake .. -DPORTABLE=${PORTABLE} && \
make install -j`nproc`
-
+
ARG IDG_VERSION=master
# IDG doesn't work with --depth 1, because it needs all branches to
# determine its version :-(
@@ -137,8 +137,8 @@ RUN git clone --depth 1 --branch ${WSCLEAN_VERSION} \
#ENV LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/local/karma/amd64_Linux_libc6.3/lib/
#ENV KARMABASE="/usr/local/karma/amd64_Linux_libc6.3"
-
-
+
+
# Do not use `pip` from the Debian repository, but fetch it from PyPA.
# This way, we are sure that the latest versions of `pip`, `setuptools`, and
# `wheel` are installed in /usr/local, the only directory we're going to copy
@@ -162,7 +162,7 @@ RUN \
make -j4 && \
cp bbs2model cluster editmodel render /usr/local/bin/ && \
cd
-
+
# Tom's stuff
ADD makemask /src/makemask
RUN cd /src/makemask && \
@@ -173,10 +173,10 @@ RUN cd /src/makemask && \
cp makeMaskFits makeNoiseMapFits makeCombMaskFits makeNoiseMapFitsLow /usr/local/bin/ && \
cd
-# gcc getMaxFits.c -o getMaxFits -lcfitsio -lm && \
+# gcc getMaxFits.c -o getMaxFits -lcfitsio -lm && \
# gcc locNoiseMed.c -o locNoiseMed -lcfitsio -lm && \
# gcc cookbook.c -o cookbook -lcfitsio -lm && \
-
+
#---------------------------------------------------------------------------
# The image will now be rebuilt without adding the sources, in order to
# reduce the size of the image.
@@ -199,7 +199,7 @@ ARG DP3_VERSION=master
ARG WSCLEAN_VERSION=master
-# Only install run-time required packages
+# Only install run-time required packages
RUN export DEBIAN_FRONTEND=noninteractive && \
apt-get update && \
apt-get install -y \
@@ -253,13 +253,13 @@ RUN wget -q -O /WSRT_Measures.ztar \
rm /WSRT_Measures.ztar
# Some python stuff
-RUN python3 -m pip install h5py pandas pyyaml astropy matplotlib scipy shapely bdsf ipython radio_beam scikit-learn
+RUN python3 -m pip install h5py pandas pyyaml astropy matplotlib==3.5.2 scipy shapely bdsf ipython radio_beam scikit-learn
# cd /src && \
# git clone https://github.com/lofar-astron/PyBDSF.git && \
# cd /src/PyBDSF && \
# python3 -m pip install . && \
-# cd
-
+# cd
+
# AImCal
ADD imcal.py /opt/imcal.py
ADD cluster.py /opt/cluster.py
diff --git a/autocorrelations.py b/autocorrelations.py
old mode 100644
new mode 100755
index d85452d..4940001
--- a/autocorrelations.py
+++ b/autocorrelations.py
@@ -27,9 +27,10 @@ def get_autocorr(tab, ant, avg='time', flagged=False):
data[q.getcol('FLAG')] = np.nan
if avg.lower() == 'time':
return abs(np.nanmean(data, axis=0))
- elif avg.lower().startswith('freq'):
+ elif avg.lower().startswith('freq') and len(data.shape)==3:
+ print(data.shape)
return abs(np.nanmean(data, axis=1))
- elif avg.lower().startswith('pol'):
+ elif avg.lower().startswith('pol') and len(data.shape)==3:
return abs(np.nanmean(data, axis=2))
else:
logging.error('Unknown average keywodr, must be time/freq/pol...')
@@ -99,8 +100,10 @@ def plot_autocorrs(ms, flagged=False):
antname = antnames[i]
avg_time = get_autocorr(tab, ant, avg='time', flagged=flagged) # TIME_AVG
avg_freq = get_autocorr(tab, ant, avg='freq', flagged=flagged) # FREQ_AVG
+ if not isinstance(avg_time, np.ndarray) or not isinstance(avg_freq, np.ndarray):
+ continue
med_time_avgs.append(np.nanmedian(avg_time, axis=0))
- med_freq_avgs.append(np.nanmedian(avg_freq, axis=0))
+ med_freq_avgs.append(np.nanmedian(avg_freq, axis=1))
for fig, res in zip ([fig1, fig2], [avg_time, avg_freq]):
ax = fig.add_subplot(ny, nx, i+1)
at = AnchoredText(antname, prop=dict(size=9), frameon=True, loc='upper left')
diff --git a/cluster.py b/cluster.py
index 9da0885..e175628 100755
--- a/cluster.py
+++ b/cluster.py
@@ -932,7 +932,7 @@ def main(img, resid, model, clustering_method='Voronoi', add_manual=False, nclus
# racen = f[0].header['CRVAL1']
# deccen = f[0].header['CRVAL2']
fig = plt.figure(figsize=[12,12])
- ax = fig.add_subplot(1,1,1, projection=wcs.celestial)
+ ax = fig.add_subplot(1,1,1, projection=wcs.celestial[0])
vmin, vmax = np.percentile(image_data, 5), np.percentile(image_data, 95)
ax.imshow(resid_data, vmin=vmin, vmax=vmax, origin='lower')#cmap='gray', vmin=2e-5, vmax=0.1)#, norm=LogNorm())
@@ -960,4 +960,5 @@ def main(img, resid, model, clustering_method='Voronoi', add_manual=False, nclus
### if __name__ == "__main__":
if __name__ == "__main__":
- main(img, resid, model, clustering_method='Voronoi', nclusters=6)
+ pass
+ # main(img, resid, model, clustering_method='Voronoi', nclusters=6)
--
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