fix py2 -> py3, fix broken import, remove deprecation warning

devutils/makesdist

@@ -1,8 +1,8 @@
 #!/usr/bin/env python
 
-'''Create source distribution tar.gz archive, where each file belongs
+"""Create source distribution tar.gz archive, where each file belongs
 to a root user and modification time is set to the git commit time.
-'''
+"""
 
 import sys
 import os
@@ -28,6 +28,7 @@ tarname = max(glob.glob(BASEDIR + '/dist/*.tar'), key=os.path.getmtime)
 tfin = tarfile.open(tarname)
 tfout = tarfile.open(tarname + '.gz', 'w:gz')
 
+
 def fixtarinfo(tinfo):
     tinfo.uid = tinfo.gid = 0
     tinfo.uname = tinfo.gname = 'root'

src/diffpy/srmise/applications/extract.py

@@ -434,7 +434,7 @@ def main():
         return
 
     if options.bcrystal is not None:
-        from diffpy.srmise.baselines import Polynomial
+        from diffpy.srmise.baselines.polynomial import Polynomial
 
         bl = Polynomial(degree=1)
         options.baseline = parsepars(bl, [options.bcrystal, "0c"])
@@ -445,27 +445,27 @@ def main():
         blext.read(options.bsrmise)
         options.baseline = blext.extracted.baseline
     elif options.bpoly0 is not None:
-        from diffpy.srmise.baselines import Polynomial
+        from diffpy.srmise.baselines.polynomial import Polynomial
 
         bl = Polynomial(degree=0)
         options.baseline = parsepars(bl, [options.bpoly0])
     elif options.bpoly1 is not None:
-        from diffpy.srmise.baselines import Polynomial
+        from diffpy.srmise.baselines.polynomial import Polynomial
 
         bl = Polynomial(degree=1)
         options.baseline = parsepars(bl, options.bpoly1)
     elif options.bpoly2 is not None:
-        from diffpy.srmise.baselines import Polynomial
+        from diffpy.srmise.baselines.polynomial import Polynomial
 
         bl = Polynomial(degree=2)
         options.baseline = parsepars(bl, options.bpoly2)
     elif options.bseq is not None:
-        from diffpy.srmise.baselines import FromSequence
+        from diffpy.srmise.baselines.fromsequence import FromSequence
 
         bl = FromSequence(options.bseq)
         options.baseline = bl.actualize([], "internal")
     elif options.bspherical is not None:
-        from diffpy.srmise.baselines import NanoSpherical
+        from diffpy.srmise.baselines.nanospherical import NanoSpherical
 
         bl = NanoSpherical()
         options.baseline = parsepars(bl, options.bspherical)

src/diffpy/srmise/applications/plot.py

@@ -22,8 +22,8 @@
 from matplotlib.ticker import MultipleLocator
 from mpl_toolkits.axes_grid1.inset_locator import inset_axes
 
-from diffpy.srmise import PDFPeakExtraction, PeakStability
-from diffpy.srmise.pdfpeakextraction import resample
+from diffpy.srmise.pdfpeakextraction import PDFPeakExtraction, resample
+from diffpy.srmise.peakstability import PeakStability
 
 # For a given figure, returns a label of interest
 labeldict = {}
@@ -92,14 +92,14 @@ def comparepositions(ppe, ip=None, **kwds):
     ep = [p for p in ep if p >= pmin and p <= pmax]
 
     if ip is not None:
-        xi = np.NaN + np.zeros(3 * len(ip))
+        xi = np.nan + np.zeros(3 * len(ip))
         xi[0::3] = ip
         xi[1::3] = ip
         yi = np.zeros_like(xi) + base
         yi[1::3] += yideal
         plt.plot(xi, yi, "b", lw=1.5, **ip_style)
 
-    xe = np.NaN + np.zeros(3 * len(ep))
+    xe = np.nan + np.zeros(3 * len(ep))
     xe[0::3] = ep
     xe[1::3] = ep
     ye = np.zeros_like(xe) + base
@@ -185,7 +185,7 @@ def makeplot(ppe_or_stability, ip=None, **kwds):
 
     if ppe.extracted is None:
         # Makeplot requires a ModelCluster, so whip one up.
-        from diffpy.srmise import ModelCluster
+        from diffpy.srmise.modelcluster import ModelCluster
 
         ppe.defaultvars()  # Make sure everything has some setting.  This
         # shouldn't have harmful side effects.

src/diffpy/srmise/baselines/arbitrary.py

@@ -16,8 +16,8 @@
 
 import numpy as np
 
-from diffpy.srmise.baselines import Polynomial
 from diffpy.srmise.baselines.base import BaselineFunction
+from diffpy.srmise.baselines.polynomial import Polynomial
 from diffpy.srmise.srmiseerrors import SrMiseEstimationError
 
 logger = logging.getLogger("diffpy.srmise")
@@ -65,7 +65,7 @@ def __init__(self, npars, valuef, jacobianf=None, estimatef=None, Cache=None):
         # Define parameterdict
         # e.g. {"a_0":0, "a_1":1, "a_2":2, "a_3":3} if npars is 4.
         parameterdict = {}
-        for d in range(self.testnpars + 1):
+        for d in range(testnpars + 1):
             parameterdict["a_" + str(d)] = d
         formats = ["internal"]
         default_formats = {"default_input": "internal", "default_output": "internal"}

src/diffpy/srmise/baselines/base.py

@@ -170,8 +170,9 @@ def factory(baselinestr, ownerlist):
 
     from numpy.random import randn
 
-    from diffpy.srmise.modelevaluators import AICc
-    from diffpy.srmise.peaks import GaussianOverR, Peaks
+    from diffpy.srmise.modelevaluators.aicc import AICc
+    from diffpy.srmise.peaks.base import Peaks
+    from diffpy.srmise.peaks.gaussianoverr import GaussianOverR
 
     res = 0.01
     r = np.arange(2, 4, res)

src/diffpy/srmise/baselines/fromsequence.py

@@ -145,14 +145,14 @@ def _valueraw(self, pars, r):
             raise ValueError(emsg)
         try:
             if r[0] < self.minx or r[-1] > self.maxx:
-                logger.warn(
+                logger.warning(
                     "Warning: Evaluating interpolating function over %s, outside safe range of %s.",
                     [r[0], r[-1]],
                     [self.minx, self.maxx],
                 )
         except (IndexError, TypeError):
             if r < self.minx or r > self.maxx:
-                logger.warn(
+                logger.warning(
                     "Warning: Evaluating interpolating function at %s, outside safe range of %s.",
                     r,
                     [self.minx, self.maxx],
@@ -178,15 +178,15 @@ def readxy(self, filename):
 
         import re
 
-        res = re.search(r"^[^#]", datastring, re.M)
+        res = re.search(rb"^[^#]", datastring, re.M)
         if res:
             datastring = datastring[res.end() :].strip()
 
         x = []
         y = []
 
         try:
-            for line in datastring.split("\n"):
+            for line in datastring.split(b"\n"):
                 v = line.split()
                 x.append(float(v[0]))
                 y.append(float(v[1]))

src/diffpy/srmise/modelevaluators/aic.py

@@ -68,7 +68,7 @@ def evaluate(self, fit, count_fixed=False, kshift=0):
         n = fit.size
 
         if n < self.minpoints(k):
-            logger.warn("AIC.evaluate(): too few data to evaluate quality reliably.")
+            logger.warning("AIC.evaluate(): too few data to evaluate quality reliably.")
             n = self.minpoints(k)
 
         if self.chisq is None:
@@ -115,7 +115,7 @@ def growth_justified(self, fit, k_prime):
 
         # assert n >= self.minPoints(kActual) #check that AIC is defined for the actual fit
         if n < self.minpoints(k_actual):
-            logger.warn("AIC.growth_justified(): too few data to evaluate quality reliably.")
+            logger.warning("AIC.growth_justified(): too few data to evaluate quality reliably.")
             n = self.minpoints(k_actual)
 
         penalty = self.parpenalty(k_test, n) - self.parpenalty(k_actual, n)

src/diffpy/srmise/modelevaluators/aicc.py

@@ -68,7 +68,7 @@ def evaluate(self, fit, count_fixed=False, kshift=0):
         n = fit.size
 
         if n < self.minpoints(k):
-            logger.warn("AICc.evaluate(): too few data to evaluate quality reliably.")
+            logger.warning("AICc.evaluate(): too few data to evaluate quality reliably.")
             n = self.minpoints(k)
 
         if self.chisq is None:
@@ -117,7 +117,7 @@ def growth_justified(self, fit, k_prime):
 
         # assert n >= self.minPoints(kActual) #check that AICc is defined for the actual fit
         if n < self.minpoints(k_actual):
-            logger.warn("AICc.growth_justified(): too few data to evaluate quality reliably.")
+            logger.warning("AICc.growth_justified(): too few data to evaluate quality reliably.")
             n = self.minpoints(k_actual)
 
         penalty = self.parpenalty(k_test, n) - self.parpenalty(k_actual, n)