Merge pull request #313 from usnistgov/refactor_filtering

Refactor optimal filtering

VERSIONS.md

@@ -1,5 +1,10 @@
 ## Note on version numbers of Mass
 
+**0.8.6** November, 2024-
+
+* Completely refactor filter code to use modern Python and MASS practices, and less spaghetti (issue 312).
+  Some user code that involves filters might be broken.
+
 **0.8.5** November 15, 2024
 
 * Fix problem where numpy 2.0 was failing a regression test. Not a true regression, so we broaden the acceptance criteria (issue 295).

doc/gamma.rst

@@ -329,10 +329,10 @@ Fit for energy resolution with and without drift correction at the 80 keV line.
 
     energy:
     	20181018_144520 chan3  Ho166m_80 fwhm=60 ± 1.9
-    	20181018_144520 chan13 Ho166m_80 fwhm=62 ± 2.0
+    	20181018_144520 chan13 Ho166m_80 fwhm=62 ± 2.1
     energyNoDC:
-    	20181018_144520 chan3  Ho166m_80 fwhm=64 ± 2.4
-    	20181018_144520 chan13 Ho166m_80 fwhm=71 ± 2.6
+    	20181018_144520 chan3  Ho166m_80 fwhm=64 ± 2.3
+    	20181018_144520 chan13 Ho166m_80 fwhm=70 ± 2.6
 
 OFF vs Plain Comparision
 ------------------------
@@ -381,8 +381,8 @@ me know what you think about it.
 
     	chan   3 fwhm=60.0 ± 1.8 (off)
     	chan   3 fwhm=59.9 ± 1.8 (ljh)
-    	chan  13 fwhm=60.7 ± 1.9 (off)
-    	chan  13 fwhm=61.7 ± 1.9 (ljh)
+    	chan  13 fwhm=60.6 ± 1.9 (off)
+    	chan  13 fwhm=61.7 ± 2.0 (ljh)
 
 We also plot one fit from one channel for plain and off style.
 
@@ -413,9 +413,9 @@ from the previous section, not the apples to apples comparison where we used the
 .. testoutput::
   :options: +NORMALIZE_WHITESPACE
 
-    ch 3off   ngood=22112 ntot=22930
+    ch 3off   ngood=22113 ntot=22930
     ch 3plain ngood=21715 ntot=22930
-    ch 13off   ngood=21498 ntot=22406
+    ch 13off   ngood=21499 ntot=22406
     ch 13plain ngood=20423 ntot=22406
 
 

mass/core/channel_group.py

@@ -970,8 +970,7 @@ def plot_average_pulses(self, axis=None, channels=None, cmap=None, legend=True,
                 ltext = axis.get_legend().get_texts()
                 plt.setp(ltext, fontsize='small')
 
-    def plot_filters(self, axis=None, channels=None, cmap=None,
-                     filtname="filt_noconst", legend=True):
+    def plot_filters(self, axis=None, channels=None, cmap=None, legend=True):
         """Plot the optimal filters.
 
         Args:
@@ -996,7 +995,7 @@ def plot_filters(self, axis=None, channels=None, cmap=None,
             ds = self.channel[channum]
             if ds.filter is None:
                 continue
-            plt.plot(ds.filter.__dict__[filtname], label=f"Chan {ds.channum}",
+            plt.plot(ds.filter.values, label=f"Chan {ds.channum}",
                      color=cmap(float(ds_num) / len(channels)))
 
         plt.xlabel("Sample number")
@@ -1012,7 +1011,7 @@ def summarize_filters(self, filter_name='noconst', std_energy=5898.8):
         for i, ds in enumerate(self):
             try:
                 if ds.filter is not None:
-                    rms = ds.filter.variances[filter_name]**0.5
+                    rms = ds.filter.variance**0.5
                 else:
                     rms = ds.hdf5_group[f'filters/filt_{filter_name}'].attrs['variance']**0.5
                 v_dv = (1 / rms) / rms_fwhm
@@ -1136,11 +1135,11 @@ def plot_noise(self, axis=None, channels=None, cmap=None, scale_factor=1.0,
                 if include_dc:
                     freq[0] = freq[1] * 0.1
                     axis.plot(freq, yvalue, label=f'Chan {channum}',
-                            color=cmap(float(i) / nplot))
+                              color=cmap(float(i) / nplot))
                     fmin = min(fmin, freq[0] * 0.8)
                 else:
                     axis.plot(freq[1:], yvalue[1:], label=f'Chan {channum}',
-                            color=cmap(float(i) / nplot))
+                              color=cmap(float(i) / nplot))
                     fmin = min(fmin, freq[1] * 0.8)
                 fmax = max(fmax, freq[-1] * 1.2)
             except Exception:

mass/core/ljh2off.py

@@ -156,8 +156,8 @@ def multi_ljh2off_loop(ljhbases, h5_path, off_basename, max_channels, n_ignore_p
 
 def ljh2off_loop(ljhpath, h5_path, output_dir, max_channels, n_ignore_presamples, require_experiment_state=True,
                  show_progress=LOG.isEnabledFor(logging.WARN)):
-    basename, _channum = mass.ljh_util.ljh_basename_channum(ljhpath)
-    _ljhdir, file_basename = os.path.split(basename)
+    basename, _ = mass.ljh_util.ljh_basename_channum(ljhpath)
+    _, file_basename = os.path.split(basename)
     off_basename = os.path.join(output_dir, file_basename)
     ljh_filename_lists, off_filenames = multi_ljh2off_loop([basename], h5_path, off_basename,
                                                            max_channels, n_ignore_presamples, show_progress)