lint check, fix break import modules, remove unused import modules, r…

…emove some # (diffpy#33)

diffpy/srmise/applications/extract.py

@@ -419,25 +419,19 @@ def main():
     from diffpy.srmise.pdfpeakextraction import PDFPeakExtraction
     from diffpy.srmise.srmiseerrors import SrMiseDataFormatError, SrMiseFileError
 
-    if options.peakfunction is not None:
-        from diffpy.srmise import peaks
-
-        try:
-            options.peakfunction = eval("peaks." + options.peakfunction)
-        except Exception as err:
-            print(err)
-            print("Could not create peak function '%s'. Exiting." % options.peakfunction)
-            return
-
-    if options.modelevaluator is not None:
-        from diffpy.srmise import modelevaluators
-
-        try:
-            options.modelevaluator = eval("modelevaluators." + options.modelevaluator)
-        except Exception as err:
-            print(err)
-            print("Could not find ModelEvaluator '%s'. Exiting." % options.modelevaluator)
-            return
+    try:
+        options.peakfunction = eval("peaks." + options.peakfunction)
+    except Exception as err:
+        print(err)
+        print("Could not create peak function '%s'. Exiting." % options.peakfunction)
+        return
+
+    try:
+        options.modelevaluator = eval("modelevaluators." + options.modelevaluator)
+    except Exception as err:
+        print(err)
+        print("Could not find ModelEvaluator '%s'. Exiting." % options.modelevaluator)
+        return
 
     if options.bcrystal is not None:
         from diffpy.srmise.baselines import Polynomial
@@ -475,8 +469,6 @@ def main():
 
         bl = NanoSpherical()
         options.baseline = parsepars(bl, options.bspherical)
-    elif options.baseline is not None:
-        from diffpy.srmise import baselines
 
         try:
             options.baseline = eval("baselines." + options.baseline)

diffpy/srmise/modelevaluators/aic.py

@@ -16,7 +16,6 @@
 
 import numpy as np
 
-import diffpy.srmise.srmiselog
 from diffpy.srmise.modelevaluators.base import ModelEvaluator
 from diffpy.srmise.srmiseerrors import SrMiseModelEvaluatorError
 
@@ -72,7 +71,7 @@ def evaluate(self, fit, count_fixed=False, kshift=0):
             logger.warn("AIC.evaluate(): too few data to evaluate quality reliably.")
             n = self.minpoints(k)
 
-        if self.chisq == None:
+        if self.chisq is None:
             self.chisq = self.chi_squared(fit.value(), fit.y_cluster, fit.error_cluster)
 
         self.stat = self.chisq + self.parpenalty(k, n)
@@ -94,10 +93,12 @@ def parpenalty(self, k, n):
         return (2 * k) * fudgefactor
 
     def growth_justified(self, fit, k_prime):
-        """Returns whether adding k_prime parameters to the given model (ModelCluster) is justified given the current quality of the fit.
-        The assumption is that adding k_prime parameters will result in "effectively 0" chiSquared cost, and so adding it is justified
-        if the cost of adding these parameters is less than the current chiSquared cost.  The validity of this assumption (which
-        depends on an unknown chiSquared value) and the impact of the errors used should be examined more thoroughly in the future.
+        """Returns whether adding k_prime parameters to the given model (ModelCluster) is justified
+        given the current quality of the fit. The assumption is that adding k_prime parameters will
+        result in "effectively 0" chiSquared cost, and so adding it is justified if the cost of adding
+        these parameters is less than the current chiSquared cost.
+        The validity of this assumption (which depends on an unknown chiSquared value)
+        and the impact of the errors used should be examined more thoroughly in the future.
         """
 
         if self.chisq is None:

diffpy/srmise/pdfpeakextraction.py

@@ -16,20 +16,24 @@
 import os.path
 import re
 
-import matplotlib.pyplot as plt
 import numpy as np
 
+from diffpy.srmise import srmiselog
 from diffpy.srmise.modelcluster import ModelCluster, ModelCovariance
 
 # from diffpy.pdfgui.control.pdfdataset import PDFDataSet
 from diffpy.srmise.pdfdataset import PDFDataSet
 from diffpy.srmise.peakextraction import PeakExtraction
-from diffpy.srmise.srmiseerrors import *
+from diffpy.srmise.srmiseerrors import (
+    SrMiseDataFormatError,
+    SrMiseError,
+    SrMiseQmaxError,
+    SrMiseStaticOwnerError,
+    SrMiseUndefinedCovarianceError,
+)
 
 logger = logging.getLogger("diffpy.srmise")
 
-from diffpy.srmise import srmiselog
-
 
 class PDFPeakExtraction(PeakExtraction):
     """Class for peak extraction of peaks from the PDF.
@@ -454,7 +458,7 @@ def extract(self, **kwds):
         try:
             logger.info(str(cov))
             # logger.info("Correlations > .8:\n%s", "\n".join(str(c) for c in cov.correlationwarning(.8)))
-        except SrMiseUndefinedCovarianceError as e:
+        except SrMiseUndefinedCovarianceError:
             logger.warn("Covariance not defined for final model.  Fit may not have converged.")
             logger.info(str(ext))
 
@@ -527,7 +531,7 @@ def fit(self, **kwds):
         logger.info(str(ext))
         try:
             logger.info(str(cov))
-        except SrMiseUndefinedCovarianceError as e:
+        except SrMiseUndefinedCovarianceError:
             logger.warn("Covariance not defined for final model.  Fit may not have converged.")
 
         # Update calculated instance variables

diffpy/srmise/peaks/__init__.py

@@ -13,8 +13,3 @@
 ##############################################################################
 
 __all__ = ["base", "gaussian", "gaussianoverr", "terminationripples"]
-
-from base import Peak, Peaks
-from gaussian import Gaussian
-from gaussianoverr import GaussianOverR
-from terminationripples import TerminationRipples

diffpy/srmise/peaks/base.py

@@ -16,10 +16,9 @@
 
 import numpy as np
 
-import diffpy.srmise.srmiselog
 from diffpy.srmise.basefunction import BaseFunction
 from diffpy.srmise.modelparts import ModelPart, ModelParts
-from diffpy.srmise.srmiseerrors import *
+from diffpy.srmise.srmiseerrors import SrMiseDataFormatError, SrMiseScalingError
 
 logger = logging.getLogger("diffpy.srmise")
 
@@ -263,17 +262,16 @@ def factory(peakstr, ownerlist):
         peakstr: string representing peak
         ownerlist: List of BaseFunctions that owner is in
         """
-        from numpy import array
 
         data = peakstr.strip().splitlines()
 
         # dictionary of parameters
         pdict = {}
         for d in data:
-            l = d.split("=", 1)
-            if len(l) == 2:
+            parse_value = d.split("=", 1)
+            if len(parse_value) == 2:
                 try:
-                    pdict[l[0]] = eval(l[1])
+                    pdict[parse_value[0]] = eval(parse_value[1])
                 except Exception:
                     emsg = "Invalid parameter: %s" % d
                     raise SrMiseDataFormatError(emsg)

diffpy/srmise/peaks/terminationripples.py

@@ -281,7 +281,6 @@ def extend_grid(self, r, dr):
     from diffpy.srmise.modelevaluators import AICc
     from diffpy.srmise.peaks import Peaks
     from diffpy.srmise.peaks.gaussianoverr import GaussianOverR
-    from diffpy.srmise.peaks.terminationripples import TerminationRipples
 
     res = 0.01
     r = np.arange(2, 4, res)

diffpy/srmise/srmiselog.py

@@ -41,11 +41,10 @@
 import logging
 import os.path
 import re
-import sys
 
 from diffpy.srmise.srmiseerrors import SrMiseDataFormatError, SrMiseFileError, SrMiseLogError
 
-### Default settings ###
+# Default settings ###
 defaultformat = "%(message)s"
 defaultlevel = logging.INFO
 
@@ -57,7 +56,7 @@
     "critical": logging.CRITICAL,
 }
 
-### Set up logging to stdout ###
+# Set up logging to stdout ###
 logger = logging.getLogger("diffpy.srmise")
 logger.setLevel(defaultlevel)
 ch = logging.StreamHandler()
@@ -68,10 +67,10 @@
 
 logger.addHandler(ch)
 
-### Optional file logger ###
+# Optional file logger ###
 fh = None
 
-### Make updated plots as fitting progresses. ###
+# Make updated plots as fitting progresses. ###
 liveplots = False
 wait = False
 
@@ -144,7 +143,7 @@ def liveplotting(lp, w=False):
         raise ValueError(emsg)
 
 
-### TracePeaks.  Primary purpose is to enable creating movies. ###
+# TracePeaks.  Primary purpose is to enable creating movies. ###
 
 
 class TracePeaks(object):
@@ -345,7 +344,7 @@ def getfilter(self):
     filter = property(getfilter, setfilter)
 
 
-### End of class TracePeaks
+# End of class TracePeaks
 
 
 def settracer(**kwds):

doc/examples/extract_single_peak.py

@@ -27,26 +27,26 @@
 
 import matplotlib.pyplot as plt
 
-from diffpy.srmise import PDFPeakExtraction
 from diffpy.srmise.applications.plot import makeplot
 from diffpy.srmise.baselines import Polynomial
+from diffpy.srmise.pdfpeakextraction import PDFPeakExtraction
 
 
 def run(plot=True):
 
-    ## Initialize peak extraction
+    # Initialize peak extraction
     # Create peak extraction object
     ppe = PDFPeakExtraction()
 
     # Load the PDF from a file
     ppe.loadpdf("data/Ag_nyquist_qmax30.gr")
 
-    ## Set up extraction parameters.
-    # For convenience we add all parameters to a dictionary before passing them
+    # Set up extraction parameters.
+    # For convenience, we add all parameters to a dictionary before passing them
     # to the extraction object.
     #
     # The "rng" (range) parameter defines the region over which peaks will be
-    # extracted and fit.  For the well isolated nearest-neighbor silver peak,
+    # extracted and fit. For the well isolated nearest-neighbor silver peak,
     # which occurs near 2.9 angstroms, it is sufficient to perform extraction
     # between 2 and 3.5 angstroms.
     #
@@ -61,24 +61,24 @@ def run(plot=True):
     # Apply peak extraction parameters.
     ppe.setvars(**kwds)
 
-    ## Perform peak extraction
+    # Perform peak extraction
     ppe.extract()
 
-    ## Save output
+    # Save output
     # The write() method saves a file which preserves all aspects of peak
     # extraction and its results, by convention using the .srmise extension,
     # and which can later be read by diffpy.srmise.
     #
     # The writepwa() method saves a file intended as a human-readable summary.
     # In particular, it reports the position, width (as full-width at
-    # half-maximum), and area of of extracted peaks.  The reported values
+    # half-maximum), and area of extracted peaks.  The reported values
     # are for Gaussians in the radial distribution function (RDF) corresponding
     # to this PDF.
     ppe.write("output/extract_single_peak.srmise")
     ppe.writepwa("output/extract_single_peak.pwa")
 
-    ## Plot results.
-    # Display plot of extracted peak.  It is also possible to plot an existing
+    # Plot results.
+    # Display plot of extracted peak. It is also possible to plot an existing
     # .srmise file from the command line using
     #     srmise output/Ag_singlepeak.srmise --no-extract --plot
     # For additional plotting options, run "srmiseplot --help".