[pre-commit.ci] auto fixes from pre-commit hooks

Author: pre-commit-ci[bot]

doc/examples/fit_initial.py

@@ -10,14 +10,16 @@
 # See LICENSE.txt for license information.
 #
 ##############################################################################
-"""Example of peak fitting C60 PDF (unnormalized) with unreliable uncertainties.
-
-Peak fitting in SrMise means fitting a model of initial peaks, which may be
-specified manually or estimated with a clustering-based convenience function,
-just as with specifying initial peaks for peak extraction.  Unlike peak
-extraction, it does not attempt to add or remove peaks, apply termination
-ripples, or otherwise do anything beyond chi-square fitting using the specified
-grid."""
+"""Example of peak fitting C60 PDF (unnormalized) with unreliable
+uncertainties.
+
+Peak fitting in SrMise means fitting a model of initial peaks, which may
+be specified manually or estimated with a clustering-based convenience
+function, just as with specifying initial peaks for peak extraction.
+Unlike peak extraction, it does not attempt to add or remove peaks,
+apply termination ripples, or otherwise do anything beyond chi-square
+fitting using the specified grid.
+"""
 
 import matplotlib.pyplot as plt
 

doc/examples/multimodel_known_dG1.py

@@ -10,8 +10,8 @@
 # See LICENSE.txt for license information.
 #
 ##############################################################################
-"""Extract multiple models from crystalline PDF with known uncertainties for
-use in later AIC-driven multimodeling analysis.
+"""Extract multiple models from crystalline PDF with known uncertainties
+for use in later AIC-driven multimodeling analysis.
 
 The multimodel approach generates many models of varying complexity by assuming
 a range of experimental uncertainties are physically plausible.  This example

doc/examples/multimodel_known_dG2.py

@@ -10,7 +10,8 @@
 # See LICENSE.txt for license information.
 #
 ##############################################################################
-"""AIC-driven multimodel analysis of crystalline PDF with known uncertainties.
+"""AIC-driven multimodel analysis of crystalline PDF with known
+uncertainties.
 
 The multimodel approach generates many models of varying complexity by assuming
 a range of experimental uncertainties are physically plausible.  This example

doc/examples/multimodel_unknown_dG1.py

@@ -10,8 +10,8 @@
 # See LICENSE.txt for license information.
 #
 ##############################################################################
-"""Extract multiple models from nanoparticle PDF with unknown uncertainties for
-use in later AIC-driven multimodeling analysis.
+"""Extract multiple models from nanoparticle PDF with unknown
+uncertainties for use in later AIC-driven multimodeling analysis.
 
 The multimodel approach generates many models of varying complexity by assuming
 a range of experimental uncertainties are physically plausible.  This example

doc/examples/parameter_summary.py

@@ -25,7 +25,8 @@
 nyquist (whether to use Nyquist sampling)
 supersample (minimum amount to oversample during initial stages)
 cres (clustering resolution)
-initial_peaks (peaks already assumed to exist during extraction)"""
+initial_peaks (peaks already assumed to exist during extraction)
+"""
 
 import matplotlib.pyplot as plt
 

doc/examples/query_results.py

@@ -10,7 +10,8 @@
 # See LICENSE.txt for license information.
 #
 ##############################################################################
-"""Example of extracting multiple peaks and accessing results programmatically.
+"""Example of extracting multiple peaks and accessing results
+programmatically.
 
 This example shows how to extract a range of peaks from a simple crystalline
 PDF using a crystalline baseline obtained from an existing trial.  It shows

src/diffpy/__init__.py

@@ -12,7 +12,6 @@
 # See LICENSE.rst for license information.
 #
 ##############################################################################
-
 """Blank namespace package for module diffpy."""
 
 

src/diffpy/srmise/__init__.py

@@ -12,8 +12,8 @@
 # See LICENSE.rst for license information.
 #
 ##############################################################################
-
-"""Peak extraction and peak fitting tool for atomic pair distribution functions."""
+"""Peak extraction and peak fitting tool for atomic pair distribution
+functions."""
 
 # package version
 from diffpy.srmise.version import __version__

src/diffpy/srmise/applications/plot.py

@@ -11,7 +11,7 @@
 # See LICENSE.txt for license information.
 #
 ##############################################################################
-"""plot extracted peaks and comparison to ideal distances (if given)"""
+"""Plot extracted peaks and comparison to ideal distances (if given)"""
 
 import optparse
 import sys
@@ -175,7 +175,7 @@ def labelallsubplots():
 
 
 def makeplot(ppe_or_stability, ip=None, **kwds):
-    """Plot stuff"""
+    """Plot stuff."""
     if isinstance(ppe_or_stability, PeakStability):
         stability = ppe_or_stability
         ppe = stability.ppe
@@ -530,7 +530,8 @@ def on_draw(event):
 
 
 def readcompare(filename):
-    """Returns a list of distances read from filename, otherwise None."""
+    """Returns a list of distances read from filename, otherwise
+    None."""
 
     # TODO: Make this safer
     try:

src/diffpy/srmise/basefunction.py

@@ -11,7 +11,8 @@
 # See LICENSE.txt for license information.
 #
 ##############################################################################
-"""Defines BaseFunction, the base class for mathematical functions in srmise."""
+"""Defines BaseFunction, the base class for mathematical functions in
+srmise."""
 
 import logging
 import re
@@ -25,7 +26,8 @@
 
 
 class BaseFunction(object):
-    """Base class for mathematical functions which model numeric sequences.
+    """Base class for mathematical functions which model numeric
+    sequences.
 
     Attributes
     -------------
@@ -76,7 +78,7 @@ def __init__(
         base=None,
         Cache=None,
     ):
-        """Set parameterdict defined by subclass
+        """Set parameterdict defined by subclass.
 
         Parameters
         ----------
@@ -159,32 +161,50 @@ def __init__(
     # "Virtual" class methods ####
 
     def actualize(self, *args, **kwds):
-        """Create ModelPart instance of self with given parameters.  ("Virtual" method)"""
+        """Create ModelPart instance of self with given parameters.
+
+        ("Virtual" method)
+        """
         emsg = "actualize() must be implemented in a BaseFunction subclass."
         raise NotImplementedError(emsg)
 
     def estimate_parameters(self, *args, **kwds):
-        """Estimate BaseFunction parameters from supplied data. ("Virtual" method)"""
+        """Estimate BaseFunction parameters from supplied data.
+
+        ("Virtual" method)
+        """
         emsg = "estimate_parameters() must be implemented in a BaseFunction subclass."
         raise NotImplementedError(emsg)
 
     def _jacobianraw(self, *args, **kwds):
-        """Calculate the jacobian. ("Virtual" method)"""
+        """Calculate the jacobian.
+
+        ("Virtual" method)
+        """
         emsg = "_jacobianraw() must be implemented in a BaseFunction subclass."
         raise NotImplementedError(emsg)
 
     def _transform_derivativesraw(self, *args, **kwds):
-        """Convert BaseFunction parameters to another form. ("Virtual" method)"""
+        """Convert BaseFunction parameters to another form.
+
+        ("Virtual" method)
+        """
         emsg = "transform_parameters() must be implemented in a BaseFunction subclass."
         raise NotImplementedError(emsg)
 
     def _transform_parametersraw(self, *args, **kwds):
-        """Convert BaseFunction parameters to another form. ("Virtual" method)"""
+        """Convert BaseFunction parameters to another form.
+
+        ("Virtual" method)
+        """
         emsg = "transform_parameters() must be implemented in a BaseFunction subclass."
         raise NotImplementedError(emsg)
 
     def _valueraw(self, *args, **kwds):
-        """Calculate value of function. ("Virtual" method)"""
+        """Calculate value of function.
+
+        ("Virtual" method)
+        """
         emsg = "_valueraw must() be implemented in a BaseFunction subclass."
         raise NotImplementedError(emsg)
 
@@ -225,7 +245,8 @@ def jacobian(self, p, r, rng=None):
             return self._jacobianraw(p.pars, r, p.free)
 
     def transform_derivatives(self, pars, in_format=None, out_format=None):
-        """Return gradient matrix for pars converted from in_format to out_format.
+        """Return gradient matrix for pars converted from in_format to
+        out_format.
 
         Parameters
         ----------
@@ -266,7 +287,8 @@ def transform_derivatives(self, pars, in_format=None, out_format=None):
         return self._transform_derivativesraw(pars, in_format=in_format, out_format=out_format)
 
     def transform_parameters(self, pars, in_format=None, out_format=None):
-        """Return new sequence with pars converted from in_format to out_format.
+        """Return new sequence with pars converted from in_format to
+        out_format.
 
         Also restores parameters to a preferred range if it permits multiple
         values that correspond to the same physical result.
@@ -310,7 +332,8 @@ def transform_parameters(self, pars, in_format=None, out_format=None):
         return self._transform_parametersraw(pars, in_format=in_format, out_format=out_format)
 
     def value(self, p, r, rng=None):
-        """Calculate value of ModelPart over r, possibly restricted by range.
+        """Calculate value of ModelPart over r, possibly restricted by
+        range.
 
         Parameters
         ----------
@@ -345,7 +368,8 @@ def value(self, p, r, rng=None):
             return self._valueraw(p.pars, r)
 
     def pgradient(self, p, format):
-        """Return gradient matrix of parameterization in specified format wrt "internal" format at p.
+        """Return gradient matrix of parameterization in specified
+        format wrt "internal" format at p.
 
         Consider the "internal" parameterization given by (i0, i1, ..., in).
         Each parameter in a different format, say (o0, o1, ..., om), is a
@@ -373,7 +397,7 @@ def pgradient(self, p, format):
         return
 
     def getmodule(self):
-        """Return 'diffpy.srmise.basefunction'"""
+        """Return 'diffpy.srmise.basefunction'."""
         return "diffpy.srmise.basefunction"
 
     def writestr(self, baselist):
@@ -473,22 +497,25 @@ def factory(functionstr, baselist):
 
     @staticmethod
     def safefunctionlist(fs):
-        """Return list of BaseFunction instances where any dependencies occur earlier in list.
+        """Return list of BaseFunction instances where any dependencies
+        occur earlier in list.
 
         Any functions with hidden dependent functions (i.e. those not in fs)
         are included in the returned list.  This list provides an order that
         is guaranteed to be safe for saving/reinstantiating peak functions.
 
         Parameters
-        fs: List of BaseFunction instances."""
+        fs: List of BaseFunction instances.
+        """
         fsafe = []
         for f in fs:
             BaseFunction.safefunction(f, fsafe)
         return fsafe
 
     @staticmethod
     def safefunction(f, fsafe):
-        """Append BaseFunction instance f to fsafe, but adding dependent functions first.
+        """Append BaseFunction instance f to fsafe, but adding dependent
+        functions first.
 
         Does not handle circular dependencies.