cleaning (#31)

* requirements

* clean out __init__

* replace ###

* ins not none in modelevaluators base

Author: sbillinge

diffpy/srmise/__init__.py

@@ -13,28 +13,5 @@
 
 """Tools for peak extraction from PDF."""
 
-__all__ = [
-    "basefunction",
-    "srmiseerrors",
-    "srmiselog",
-    "dataclusters",
-    "modelcluster",
-    "modelparts",
-    "pdfdataset",
-    "pdfpeakextraction",
-    "peakextraction",
-    "peakstability",
-    "multimodelselection",
-]
-
-from basefunction import BaseFunction
-from dataclusters import DataClusters
-from modelcluster import ModelCluster, ModelCovariance
-from modelparts import ModelPart, ModelParts
-from multimodelselection import MultimodelSelection
-from pdfdataset import PDFDataSet
-from pdfpeakextraction import PDFPeakExtraction
-from peakextraction import PeakExtraction
-from peakstability import PeakStability
 
 from diffpy.srmise.version import __version__

diffpy/srmise/modelevaluators/base.py

@@ -43,9 +43,6 @@
 
 import numpy as np
 
-import diffpy.srmise.srmiselog
-from diffpy.srmise.srmiseerrors import SrMiseModelEvaluatorError
-
 logger = logging.getLogger("diffpy.srmise")
 
 
@@ -68,9 +65,9 @@ def __lt__(self, other):
         """ """
 
         assert self.method == other.method  # Comparison between same types required
-        assert self.stat != None and other.stat != None  # The statistic must already be calculated
+        assert self.stat is not None and other.stat is not None  # The statistic must already be calculated
 
-        if self.higher_is_better:
+        if self.higher_is_better is not None:
             return self.stat < other.stat
         else:
             return other.stat < self.stat
@@ -79,9 +76,9 @@ def __le__(self, other):
         """ """
 
         assert self.method == other.method  # Comparison between same types required
-        assert self.stat != None and other.stat != None  # The statistic must already be calculated
+        assert self.stat is not None and other.stat is not None  # The statistic must already be calculated
 
-        if self.higher_is_better:
+        if self.higher_is_better is not None:
             return self.stat <= other.stat
         else:
             return other.stat <= self.stat
@@ -90,25 +87,25 @@ def __eq__(self, other):
         """ """
 
         assert self.method == other.method  # Comparison between same types required
-        assert self.stat != None and other.stat != None  # The statistic must already be calculated
+        assert self.stat is not None and other.stat is not None  # The statistic must already be calculated
 
         return self.stat == other.stat
 
     def __ne__(self, other):
         """ """
 
         assert self.method == other.method  # Comparison between same types required
-        assert self.stat != None and other.stat != None  # The statistic must already be calculated
+        assert self.stat is not None and other.stat is not None  # The statistic must already be calculated
 
         return self.stat != other.stat
 
     def __gt__(self, other):
         """ """
 
         assert self.method == other.method  # Comparison between same types required
-        assert self.stat != None and other.stat != None  # The statistic must already be calculated
+        assert self.stat is not None and other.stat is not None  # The statistic must already be calculated
 
-        if self.higher_is_better:
+        if self.higher_is_better is not None:
             return self.stat > other.stat
         else:
             return other.stat > self.stat
@@ -117,9 +114,9 @@ def __ge__(self, other):
         """ """
 
         assert self.method == other.method  # Comparison between same types required
-        assert self.stat != None and other.stat != None  # The statistic must already be calculated
+        assert self.stat is not None and other.stat is not None  # The statistic must already be calculated
 
-        if self.higher_is_better:
+        if self.higher_is_better is not None:
             return self.stat >= other.stat
         else:
             return other.stat >= self.stat

diffpy/srmise/modelparts.py

@@ -207,7 +207,7 @@ def fit(
 
         return
 
-    #### Notes on the fit f
+    # # Notes on the fit f
     # f[0] = solution
     # f[1] = Uses the fjac and ipvt optional outputs to construct an estimate of the jacobian around the solution.
     #        None if a singular matrix encountered (indicates very flat curvature in some direction).

diffpy/srmise/multimodelselection.py

@@ -527,7 +527,7 @@ def plot3dclassprobs(self, **kwds):
                 verts.append(np.concatenate([[p0], zip(xs, ys), [p1], [p0]]))
                 zlabels.append(i)
 
-        ### Define face colors
+        #  Define face colors
         fc = np.array([len(self.classes[z]) for z in zlabels])
         if class_size is "fraction":
             fc = fc / float(len(self.results))

diffpy/srmise/peakextraction.py

@@ -375,25 +375,25 @@ def readstr(self, datastring):
             baselinefunctions = header[res.end() :].strip()
             header = header[: res.start()]
 
-        ### Instantiating baseline functions
+        #  Instantiating baseline functions
         res = re.split(r"(?m)^#+ BaselineFunction \d+\s*(?:#.*\s+)*", baselinefunctions)
         for s in res[1:]:
             safebf.append(BaseFunction.factory(s, safebf))
 
-        ### Instantiating peak functions
+        #  Instantiating peak functions
         res = re.split(r"(?m)^#+ PeakFunction \d+\s*(?:#.*\s+)*", peakfunctions)
         for s in res[1:]:
             safepf.append(BaseFunction.factory(s, safepf))
 
-        ### Instantiating Baseline object
+        #  Instantiating Baseline object
         if re.match(r"^None$", baselineobject):
             self.baseline = None
         elif re.match(r"^\d+$", baselineobject):
             self.baseline = safebf[int(baselineobject)]
         else:
             self.baseline = Baseline.factory(baselineobject, safebf)
 
-        ### Instantiating initial peaks
+        #  Instantiating initial peaks
         if re.match(r"^None$", initial_peaks):
             self.initial_peaks = None
         else:
@@ -402,7 +402,7 @@ def readstr(self, datastring):
             for s in res[1:]:
                 self.initial_peaks.append(Peak.factory(s, safepf))
 
-        ### Instantiating srmise metatdata
+        #  Instantiating srmise metatdata
 
         # pf
         res = re.search(r"^pf=(.*)$", srmisemetadata, re.M)
@@ -426,10 +426,10 @@ def readstr(self, datastring):
         res = re.search(r"^Range=(.*)$", srmisemetadata, re.M)
         self.rng = eval(res.groups()[0].strip())
 
-        ### Instantiating other metadata
+        #  Instantiating other metadata
         self.readmetadata(metadata)
 
-        ### Instantiating start data
+        #  Instantiating start data
         # read actual data - x, y, dx, dy, plus effective_dy
         arrays = []
         if hasx:
@@ -478,7 +478,7 @@ def readstr(self, datastring):
         if hasedy:
             self.effective_dy = np.array(self.effective_dy)
 
-        ### Instantiating results
+        #  Instantiating results
         res = re.search(r"^#+ ModelCluster\s*(?:#.*\s+)*", results, re.M)
         if res:
             mc = results[res.end() :].strip()
@@ -638,7 +638,7 @@ def writestr(self):
                 line.append("%g" % self.effective_dy[i])
             lines.append(" ".join(line))
 
-        ### Calculated members
+        #  Calculated members
         lines.append("##### Results")
         lines.append("extraction_type=%s" % repr(self.extraction_type))
 
@@ -792,8 +792,8 @@ def extract_single(self, recursion_depth=1):
 
         stepcounter = 0
 
-        ############################
-        ### Main extraction loop ###
+        # #########################
+        #  Main extraction loop ###
         for step in dclusters:
 
             stepcounter += 1
@@ -839,7 +839,7 @@ def extract_single(self, recursion_depth=1):
             # three clusters can become adjacent at any given step.
             assert len(adjacent) <= 3
 
-            ### Update cluster fits ###
+            #  Update cluster fits ###
             # 1. Refit clusters adjacent to at least one other cluster.
             for a in adjacent:
                 mclusters[a].fit(justify=True)
@@ -922,7 +922,7 @@ def extract_single(self, recursion_depth=1):
                 near_peaks = Peaks([full_cluster.model[i] for i in near_peaks])
                 other_peaks = Peaks([full_cluster.model[i] for i in other_peaks])
 
-                ### Remove contribution of peaks outside neighborhood
+                #  Remove contribution of peaks outside neighborhood
                 # Define range of fitting/recursion to the interpeak range
                 # The adjusted error is passed unchanged.  This may introduce
                 # a few more peaks than is justified, but they can be pruned
@@ -985,7 +985,7 @@ def extract_single(self, recursion_depth=1):
                     # Incorporate best peaks from recursive search.
                     adj_cluster.augment(rec)
 
-                ### Select which model to use
+                #  Select which model to use
                 full_cluster.model = other_peaks
                 full_cluster.replacepeaks(adj_cluster.model)
                 full_cluster.fit(True)
@@ -1001,9 +1001,9 @@ def extract_single(self, recursion_depth=1):
                 logger.debug("\n".join(msg), mclusters[step.lastcluster_idx], full_cluster)
 
                 mclusters[step.lastcluster_idx] = full_cluster
-            ### End update cluster fits ###
+            #  End update cluster fits ###
 
-            ### Combine adjacent clusters ###
+            #  Combine adjacent clusters ###
 
             # Iterate in reverse order to preserve earlier indices
             for idx in adjacent[-1:0:-1]:
@@ -1065,7 +1065,7 @@ def extract_single(self, recursion_depth=1):
                 near_peaks = Peaks([new_cluster.model[i] for i in near_peaks])
                 other_peaks = Peaks([new_cluster.model[i] for i in other_peaks])
 
-                ### Remove contribution of peaks outside neighborhood
+                #  Remove contribution of peaks outside neighborhood
                 # Define range of fitting/recursion to the interpeak range
                 # The adjusted error is passed unchanged.  This may introduce
                 # a few more peaks than is justified, but they can be pruned
@@ -1075,7 +1075,7 @@ def extract_single(self, recursion_depth=1):
                 adj_y = y[adj_slice] - other_peaks.value(adj_x)
                 adj_error = dy[adj_slice]
 
-                #### Perform recursion on a version that is scaled at the
+                # # Perform recursion on a version that is scaled at the
                 # border, as well as on that is simply fit beforehand.  In
                 # many cases these lead to nearly identical results, but
                 # occasionally one works much better than the other.
@@ -1194,7 +1194,7 @@ def extract_single(self, recursion_depth=1):
                     # Incorporate best peaks from recursive search.
                     adj_cluster2.augment(rec2)
 
-                ### Select which model to use
+                #  Select which model to use
                 new_cluster.model = other_peaks
                 rej_cluster = ModelCluster(new_cluster)
                 q1 = adj_cluster1.quality(self.error_method)
@@ -1224,16 +1224,16 @@ def extract_single(self, recursion_depth=1):
                 mclusters[idx - 1] = new_cluster
                 del mclusters[idx]
 
-            ### End combine adjacent clusters loop ###
+            #  End combine adjacent clusters loop ###
 
             # Finally, combine clusters in dclusters
             if len(adjacent) > 0:
                 step.combine_clusters([adjacent])
 
             tracer.emit(*mclusters)
 
-        ### End main extraction loop ###
-        ################################
+        #  End main extraction loop ###
+        # #############################
 
         # Put initial peaks back in
         mclusters[0].addexternalpeaks(ip)

diffpy/srmise/peaks/base.py

@@ -91,13 +91,13 @@ def __init__(
             raise ValueError(emsg)
         BaseFunction.__init__(self, parameterdict, parformats, default_formats, metadict, base, Cache)
 
-    #### "Virtual" class methods ####
+    # # "Virtual" class methods ####
 
     def scale_at(self, peak, x, scale):
         emsg = "scale_at must be implemented in a PeakFunction subclass."
         raise NotImplementedError(emsg)
 
-    #### Methods required by BaseFunction ####
+    # # Methods required by BaseFunction ####
 
     def actualize(
         self,