Merge pull request #144 from revoltek/RAP-313_numpy-fixes

Type fixes for NumPy 1.24

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

losoto/_version.py

@@ -4,7 +4,7 @@
 """
 
 # Version number
-__version__ = '2.4'
+__version__ = '2.4.1'
 
 # H5parm version
 __h5parmVersion__ = '1.0'

losoto/operations/_fitClockTEC.py

@@ -501,7 +501,7 @@ def getClockTECFitStation(
                 except np.linalg.LinAlgError:
                     logging.debug("Init parmaters failed   t=%d st=%s flags=%d" % (itm,stationname,datatmpist.count()) + str(sol[:]))
                     sol[:] = [-10.,]*sol.shape[0]
-                    
+
                 #logging.debug("Getting init par for station %d:%s "%(itm,stationname)+str(sol))
 
         #now do the real fitting
@@ -527,7 +527,7 @@ def getClockTECFitStation(
             except np.linalg.LinAlgError:
                 logging.debug("Fit failed   t=%d st=%s flags=%d" % (itm,stationname,datatmpist.count()) + str(sol[:]))
                 sol[:] = [-10.,]*sol.shape[0]
-               
+
         # calculate chi2 per station
 
         residual = data[itm] - np.dot(A, sol)
@@ -632,7 +632,7 @@ def correctWraps(
     lonlat = np.concatenate((lons, lats)).reshape((2, ) + lons.shape)
     # refine (is it needed/helpful for LBA? the offsets seem to make sense for LBA)
     myselect=np.sqrt(np.sum(lonlat**2,axis=0))>0.5
-    
+
 
     for nr_iter in range(2):
         # recreate best TEC at the moment
@@ -740,7 +740,7 @@ def doFit(
     indices = np.arange(nF)
 
     if flagBadChannels:
-        mymask=np.zeros((nF), dtype=np.bool)
+        mymask=np.zeros((nF), dtype=bool)
         for nr_iter in range(2):
             rms = np.ma.std(np.ma.std(refdata, axis=0), axis=1)
             freqselect = rms < flagcut * np.average(rms)

losoto/operations/flagextend.py

@@ -22,11 +22,11 @@ def _flag(weights, coord, axesToExt, selection, percent=50, size=[0], maxCycles=
         Flag data if surreounded by other flagged data
         weights = the weights to convert into flags
         percent = percent of surrounding flagged point to extend the flag
-        
+
         return: flags array and final rms
         """
         def extendFlag(flags, percent):
-            #flags = flags.astype(np.int)
+            #flags = flags.astype(int)
             if float(np.sum( flags ))/len(flags) > percent/100.:
                 return 1
             else:
@@ -59,8 +59,8 @@ def percentFlagged(w):
                     % (removeKeys(coord, axesToExt), initPercent, percentFlagged(weights)))
 
         outQueue.put([weights, selection])
-        
-            
+
+
 def run( soltab, axesToExt, size, percent=50., maxCycles=3, ncpu=0 ):
     """
     This operation for LoSoTo implement a extend flag procedure

losoto/operations/prefactor_bandpass.py

@@ -80,8 +80,8 @@ def _savitzky_golay(y, window_size, order, deriv=0, rate=1):
     from math import factorial
 
     try:
-        window_size = np.abs(np.int(window_size))
-        order = np.abs(np.int(order))
+        window_size = np.abs(int(window_size))
+        order = np.abs(int(order))
     except ValueError as msg:
         raise ValueError("window_size and order have to be of type int")
     if window_size % 2 != 1 or window_size < 1: