Fixed a few remaining references to mise.

Author: Ainamacar

Diff for: diffpy/srmise/modelcluster.py

@@ -23,7 +23,7 @@
 from scipy.optimize import leastsq
 from diffpy.srmise.peaks import Peak, Peaks
 from diffpy.srmise.modelparts import ModelParts
-from diffpy.srmise.srmiseerrors import MiseEstimationError, MiseFitError, MiseDataFormatError, MiseUndefinedCovarianceError
+from diffpy.srmise.srmiseerrors import SrMiseEstimationError, SrMiseFitError, SrMiseDataFormatError, SrMiseUndefinedCovarianceError
 from diffpy.srmise.baselines import Baseline
 import re
 import sys

Diff for: diffpy/srmise/modelevaluators/aic.py

@@ -12,11 +12,11 @@
 ##############################################################################
 
 import numpy as np
-from diffpy.srmise.mise.modelevaluators.base import ModelEvaluator
-from diffpy.srmise.mise.miseerrors import MiseModelEvaluatorError
+from diffpy.srmise.modelevaluators.base import ModelEvaluator
+from diffpy.srmise.srmiseerrors import SrMiseModelEvaluatorError
 
-import logging, diffpy.srmise.mise.miselog
-logger = logging.getLogger("mise.peakextraction")
+import logging, diffpy.srmise.srmiselog
+logger = logging.getLogger("diffpy.srmise")
 
 class AIC (ModelEvaluator):
     """Evaluate and compare models with the AIC statistic.
@@ -58,7 +58,7 @@ def evaluate(self, fit, count_fixed=False, kshift=0):
         k = fit.model.npars(count_fixed=count_fixed) + kshift
         if k < 0:
             emsg = "AIC not defined for negative number of parameters."
-            raise MiseModelEvaluatorError(emsg)
+            raise SrMiseModelEvaluatorError(emsg)
 
         # Number of data points included in the fit
         n = fit.size

Diff for: diffpy/srmise/modelevaluators/base.py

@@ -40,10 +40,10 @@
 ########################################################################
 
 import numpy as np
-from diffpy.srmise.mise.miseerrors import MiseModelEvaluatorError
+from diffpy.srmise.srmiseerrors import SrMiseModelEvaluatorError
 
-import logging, diffpy.srmise.mise.miselog
-logger = logging.getLogger("mise.peakextraction")
+import logging, diffpy.srmise.srmiselog
+logger = logging.getLogger("diffpy.srmise")
 
 class ModelEvaluator:
     """Class for evaluating the quality of a fit.  Comparison between different