Merge pull request #1552 from jamesmkrieger/pca_missed_quiet

add missed quiet check
prody · May 17, 2022 · 45cd0d8 · 45cd0d8
2 parents 9bc18a2 + a257f98
commit 45cd0d8
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Showing 3 changed files with 20 additions and 15 deletions.
diff --git a/prody/apps/prody_apps/prody_pca.py b/prody/apps/prody_apps/prody_pca.py
@@ -47,7 +47,6 @@ def prody_pca(coords, **kwargs):
     prefix = kwargs.get('prefix')
     nmodes = kwargs.get('nmodes')
     selstr = kwargs.get('select')
-    quiet = kwargs.pop('quiet', False)
     altloc = kwargs.get('altloc')
 
     ext = splitext(coords)[1].lower()
@@ -96,11 +95,11 @@ def prody_pca(coords, **kwargs):
                 raise ImportError('Please install threadpoolctl to control threads')
 
             with threadpool_limits(limits=nproc, user_api="blas"):
-                pca.buildCovariance(dcd, aligned=kwargs.get('aligned'), quiet=quiet)
+                pca.buildCovariance(dcd, aligned=kwargs.get('aligned'))
                 pca.calcModes(nmodes)
                 ensemble = dcd
         else:
-            pca.buildCovariance(dcd, aligned=kwargs.get('aligned'), quiet=quiet)
+            pca.buildCovariance(dcd, aligned=kwargs.get('aligned'))
             pca.calcModes(nmodes)
             ensemble = dcd
 
@@ -133,10 +132,10 @@ def prody_pca(coords, **kwargs):
                 raise ImportError('Please install threadpoolctl to control threads')
 
             with threadpool_limits(limits=nproc, user_api="blas"):
-                pca.buildCovariance(ensemble, aligned=kwargs.get('aligned'), quiet=quiet)
+                pca.buildCovariance(ensemble, aligned=kwargs.get('aligned'))
                 pca.calcModes(nmodes)
         else:
-            pca.buildCovariance(ensemble, aligned=kwargs.get('aligned'), quiet=quiet)
+            pca.buildCovariance(ensemble, aligned=kwargs.get('aligned'))
             pca.calcModes(nmodes)
 
     LOGGER.info('Writing numerical output.')
@@ -269,7 +268,7 @@ def addCommand(commands):
     subparser = commands.add_parser('pca',
         help='perform principal component analysis calculations')
 
-    subparser.add_argument('--quiet', help="suppress info messages to stderr",
+    subparser.add_argument('--quiet', help='suppress info messages to stderr',
         action=Quiet, nargs=0)
 
     subparser.add_argument('--examples', action=UsageExample, nargs=0,

diff --git a/prody/dynamics/pca.py b/prody/dynamics/pca.py
@@ -147,8 +147,9 @@ def buildCovariance(self, coordsets, **kwargs):
             if n_atoms < 3:
                 raise ValueError('coordsets must have more than 3 atoms')
             dof = n_atoms * 3
-            LOGGER.info('Covariance is calculated using {0} coordinate sets.'
-                        .format(len(coordsets)))
+            if not quiet:
+                LOGGER.info('Covariance is calculated using {0} coordinate sets.'
+                            .format(len(coordsets)))
             s = (n_confs, dof)
             if weights is None:
                 if coordsets.dtype == float:
@@ -158,13 +159,16 @@ def buildCovariance(self, coordsets, **kwargs):
                     cov = np.zeros((dof, dof))
                     coordsets = coordsets.reshape((n_confs, dof))
                     mean = coordsets.mean(0)
-                    LOGGER.progress('Building covariance', n_confs,
+                    if not quiet:
+                        LOGGER.progress('Building covariance', n_confs,
                                     '_prody_pca')
                     for i, coords in enumerate(coordsets.reshape(s)):
                         deviations = coords - mean
                         cov += np.outer(deviations, deviations)
-                        LOGGER.update(n_confs, label='_prody_pca')
-                    LOGGER.finish()
+                        if not quiet:
+                            LOGGER.update(n_confs, label='_prody_pca')
+                    if not quiet:
+                        LOGGER.finish()
                     cov /= n_confs
                     self._cov = cov
             else:
@@ -185,7 +189,8 @@ def buildCovariance(self, coordsets, **kwargs):
         self._trace = self._cov.trace()
         self._dof = dof
         self._n_atoms = n_atoms
-        LOGGER.report('Covariance matrix calculated in %2fs.', '_prody_pca')
+        if not quiet:
+            LOGGER.report('Covariance matrix calculated in %2fs.', '_prody_pca')
 
     def calcModes(self, n_modes=20, turbo=True):
         """Calculate principal (or essential) modes.  This method uses
@@ -255,10 +260,10 @@ def performSVD(self, coordsets):
                               coordsets._getCoords())
 
         n_confs = deviations.shape[0]
-        if n_confs < 3:
+        if n_confs <= 3:
             raise ValueError('coordsets must have more than 3 coordinate sets')
         n_atoms = deviations.shape[1]
-        if n_atoms < 3:
+        if n_atoms <= 3:
             raise ValueError('coordsets must have more than 3 atoms')
 
         dof = n_atoms * 3

diff --git a/prody/utilities/logger.py b/prody/utilities/logger.py
@@ -251,7 +251,8 @@ def progress(self, msg, steps, label=None, **kwargs):
 
         if not hasattr(self, '_verb'):
             self._verb = self._getverbosity()
-            self._setverbosity('progress')
+            if self._level < logging.WARNING:
+                self._setverbosity('progress')
         self._n_progress += 1
 
     def update(self, step, msg=None, label=None):