Merge pull request #159 from revoltek/master

Rebase branch

.github/workflows/python.yml

@@ -0,0 +1,27 @@
+name: Python package
+
+on: [push]
+
+jobs:
+  build:
+
+    runs-on: ubuntu-latest
+    strategy:
+      matrix:
+        python-version: ["3.8", "3.9", "3.10", "3.11"]
+
+    steps:
+      - uses: actions/checkout@v4
+      - name: Set up Python ${{ matrix.python-version }}
+        uses: actions/setup-python@v5
+        with:
+          python-version: ${{ matrix.python-version }}
+      - name: Install dependencies
+        run: |
+          python -m pip install --upgrade pip
+          pip install flake8 pytest
+      - name: Install
+        run: pip install .
+      - name: Test
+        # We cannot yet use `pytest`; requires different test file names
+        run: python tools/losoto_test.py

bin/H5parm2parmdb.py

@@ -549,13 +549,13 @@ def makeTECparmdb(H, solset, TECsolTab, timewidths, freq, freqwidth):
                     # check whether this is clock or tec; if so, reshape properly to account for all freqs in the parmdb
                     # anyway these tables are freq-indep
                     if solType == "Clock":# or solType == "TEC" or solType == "RotationMeasure":
-                        # find freq-dimensionality 
+                        # find freq-dimensionality
                         nfreq = freqs.shape[0]
                         #print val.shape
                         # reshape such that all freq arrays are filled properly
-                        val = np.tile( val, np.append([nfreq], np.ones(len(val.shape),dtype=np.int) ) )
+                        val = np.tile( val, np.append([nfreq], np.ones(len(val.shape),dtype=int) ) )
                         #print val.shape
-                        weights = np.tile( weights, np.append([nfreq], np.ones(len(weights.shape),dtype=np.int) ) )
+                        weights = np.tile( weights, np.append([nfreq], np.ones(len(weights.shape),dtype=int) ) )
 
                     flags = np.zeros(shape=weights.shape, dtype=bool)
                     flags[np.where(weights == 0)] = True

bin/H5parm_collector.py

@@ -121,7 +121,7 @@
     logging.debug("Shape:"+str(allShape))
     allVals = np.empty( shape=allShape )
     allVals[:] = np.nan
-    allWeights = np.zeros( shape=allShape )#, dtype=np.float16 )
+    allWeights = np.zeros( shape=allShape )#, dtype=float )
 
     # fill arrays
     logging.info("Filling new table...")