Fixed bug in CUBEFIT that PSF parameters and positions of omitted layers were...

Fixed bug in CUBEFIT that PSF parameters and positions of omitted layers were set to NaN even when they were not fitted.
Accelerated polynomial fit of positions in POLYFIT.

bin/PampelMuse

@@ -58,7 +58,7 @@ the data into memory yet but just checks whether the file(s) are valid.
 
 Latest Git revision
 -------------------
-2022/06/14
+2022/06/20
 """
 import argparse
 import importlib
@@ -78,7 +78,7 @@ from pampelmuse.utils.fits import read_config_from_header
 
 __author__ = "Sebastian Kamann (s.kamann@ljmu.ac.uk)"
 __version__ = "1.0"
-__revision__ = 20220614
+__revision__ = 20220620
 
 
 logger = logging.getLogger(__name__)

pampelmuse/core/fit_cube.py

@@ -31,7 +31,7 @@ extraction for a data cube.
 
 Latest GIT revision
 -------------------
-2022/05/21
+2022/06/20
 """
 import collections
 import logging
@@ -45,7 +45,7 @@ from ..instruments.muse import MusePixtable
 
 
 __author__ = "Sebastian Kamann (s.kamann@ljmu.ac.uk)"
-__revision__ = 20220521
+__revision__ = 20220620
 
 
 logger = logging.getLogger(__name__)
@@ -420,14 +420,14 @@ class FitCube(object):
         # the parameters are fitted - all parameters of omitted layers are set to NaN. This is however not done for any
         # polynomial fits to the positions/parameters that may exist
         self.psf_attributes.interpolate()
-        if len(self.psf_parameters) > 0:
+        if any(self.psf_parameters.values()) > 0:
             self.psf_attributes.data.loc[omitted_indices, (slice(None), 'value')] = np.nan
             if self.psf_attributes.lut is not None:
                 self.psf_attributes.lut.loc[omitted_indices, 'value'] = np.nan
 
         if self.sources.transformation.valid:
             self.sources.transformation.interpolate()
-            if len(self.position_parameters) > 0:
+            if any(self.position_parameters.values()) > 0:
                 self.sources.transformation.data.loc[omitted_indices, (slice(None), 'value')] = np.nan
 
         # Load full coordinate array into memory because doing it per layer is quite slow.

pampelmuse/core/sources.py

@@ -37,7 +37,7 @@ memory but only on request.
 
 Latest Git revision
 -------------------
-2022/05/21
+2022/06/20
 """
 import collections
 import logging
@@ -59,7 +59,7 @@ except ImportError:
 
 
 __author__ = "Sebastian Kamann (s.kamann@ljmu.ac.uk)"
-__revision__ = 20220522
+__revision__ = 20220620
 
 
 logger = logging.getLogger(__name__)
@@ -1662,6 +1662,9 @@ class Sources(object):
             mask = pd.Series(False, index=self.wave)
 
         # determine 'mean' coordinate if option 'common_slope' selected
+        mean_x_fit = None
+        mean_y_fit = None
+        mean_mask = None
         if common_slope:
 
             # get mean coordinates along x and y for each available source
@@ -1685,7 +1688,11 @@ class Sources(object):
 
             order = 0  # all individual coordinates are now "fitted" with zeroth order polynomials
 
+        # x_fits = np.zeros((len(ids), self.wave.size), dtype=np.float64)
+        # y_fits = np.zeros_like(x_fits)
+
         # loop over selected sources and fir polynomials to x- and y-coordinates
+        import time
         for n, source_id in enumerate(ids, start=1):
 
             x = xy[(source_id, 'x', 'value')]
@@ -1710,8 +1717,10 @@ class Sources(object):
                     y_fit_i = fit_function.fit(self.wave[~mask_i], y[~mask_i], order)
 
                 # update IFS coordinates data frame
-                self.ifs_coordinates[(source_id, 'x', 'fit')] = x_fit_i(self.wave)
-                self.ifs_coordinates[(source_id, 'y', 'fit')] = y_fit_i(self.wave)
+                # self.ifs_coordinates[(source_id, 'x', 'fit')] = x_fit_i(self.wave)
+                # self.ifs_coordinates[(source_id, 'y', 'fit')] = y_fit_i(self.wave)
+                # x_fits[n - 1] = x_fit_i(self.wave)
+                # y_fits[n - 1] = y_fit_i(self.wave)
 
                 # update dictionary containing polynomial fits
                 self.ifs_coordinates_fitted[source_id] = True
@@ -1725,8 +1734,9 @@ class Sources(object):
             # log progress
             logging.debug("Polynomial fit to source #{0} [{1}/{2}]".format(source_id, n, len(ids)))
             if statusBar is not None:
-                statusBar.showMessage("Polynomial fit to source #{0} [{1}/{2}]".format(source_id, n, len(ids)),
-                                      5000)
+                statusBar.showMessage("Polynomial fit to source #{0} [{1}/{2}]".format(source_id, n, len(ids)), 5000)
+
+        self.load_ifs_coordinates(ids=ids)
 
     ##############################################################################
     #                             Output methods                                 #