deprecate: deprecate setProfile

docs/examples/coreshellnp.py

@@ -68,7 +68,7 @@ def makeRecipe(stru1, stru2, datname):
     contribution = FitContribution("cdszns")
     contribution.addProfileGenerator(generator_cds)
     contribution.addProfileGenerator(generator_zns)
-    contribution.setProfile(profile, xname="r")
+    contribution.set_profile(profile, xname="r")
 
     # Set up the characteristic functions. We use a spherical CF for the core
     # and a spherical shell CF for the shell. Since this is set up as two

docs/examples/crystalpdf.py

@@ -75,7 +75,7 @@ def makeRecipe(ciffile, datname):
     # before.
     contribution = FitContribution("nickel")
     contribution.addProfileGenerator(generator)
-    contribution.setProfile(profile, xname="r")
+    contribution.set_profile(profile, xname="r")
 
     # Make the FitRecipe and add the FitContribution.
     recipe = FitRecipe()

docs/examples/crystalpdfall.py

@@ -48,7 +48,7 @@ def makeContribution(name, generator, profile):
     """Make a FitContribution and add a generator and profile."""
     contribution = FitContribution(name)
     contribution.addProfileGenerator(generator)
-    contribution.setProfile(profile, xname="r")
+    contribution.set_profile(profile, xname="r")
     return contribution
 
 

docs/examples/crystalpdfobjcryst.py

@@ -63,7 +63,7 @@ def makeRecipe(ciffile, datname):
     # The FitContribution
     contribution = FitContribution("nickel")
     contribution.addProfileGenerator(generator)
-    contribution.setProfile(profile, xname="r")
+    contribution.set_profile(profile, xname="r")
 
     # Make the FitRecipe and add the FitContribution.
     recipe = FitRecipe()

docs/examples/crystalpdftwodata.py

@@ -85,11 +85,11 @@ def makeRecipe(ciffile, xdatname, ndatname):
     # We associate the x-ray PDFGenerator and Profile in one FitContribution...
     xcontribution = FitContribution("xnickel")
     xcontribution.addProfileGenerator(xgenerator)
-    xcontribution.setProfile(xprofile, xname="r")
+    xcontribution.set_profile(xprofile, xname="r")
     # and the neutron objects in another.
     ncontribution = FitContribution("nnickel")
     ncontribution.addProfileGenerator(ngenerator)
-    ncontribution.setProfile(nprofile, xname="r")
+    ncontribution.set_profile(nprofile, xname="r")
 
     # This example is different than the previous ones in that we are composing
     # a residual function from other residuals (one for the x-ray contribution

docs/examples/crystalpdftwophase.py

@@ -74,7 +74,7 @@ def makeRecipe(niciffile, siciffile, datname):
     contribution = FitContribution("nisi")
     contribution.addProfileGenerator(generator_ni)
     contribution.addProfileGenerator(generator_si)
-    contribution.setProfile(profile, xname="r")
+    contribution.set_profile(profile, xname="r")
 
     # Write the fitting equation. We want to sum the PDFs from each phase and
     # multiply it by a scaling factor. We also want a certain phase scaling

docs/examples/debyemodel.py

@@ -102,7 +102,7 @@ def makeRecipe():
     # independent variable (the temperature) from the data to calculate the
     # theoretical signal, so give it an informative name ('T') that we can use
     # later.
-    contribution.setProfile(profile, xname="T")
+    contribution.set_profile(profile, xname="T")
 
     # We now need to create the fitting equation.  We tell the FitContribution
     # to use the 'debye' function defined below. The 'registerFunction' method

docs/examples/ellipsoidsas.py

@@ -58,7 +58,7 @@ def makeRecipe(datname):
     # before.
     contribution = FitContribution("ellipsoid")
     contribution.addProfileGenerator(generator)
-    contribution.setProfile(profile, xname="q")
+    contribution.set_profile(profile, xname="q")
 
     # We want to fit the log of the signal to the log of the data so that the
     # higher-Q information remains significant. There are no I(Q) uncertainty

docs/examples/gaussiangenerator.py

@@ -145,7 +145,7 @@ def makeRecipe():
     # set the fitting equation to "g", which calls the GaussianGenerator.
     contribution = FitContribution("g1")
     contribution.addProfileGenerator(generator)
-    contribution.setProfile(profile)
+    contribution.set_profile(profile)
 
     # The FitRecipe
     # Now we create the FitRecipe and add the FitContribution.

docs/examples/gaussianrecipe.py

@@ -114,7 +114,7 @@ def makeRecipe():
     # us access to the data held within the Profile. Here, we can tell it what
     # name we want to use for the independent variable. We tell it to use the
     # name "x".
-    contribution.setProfile(profile, xname="x")
+    contribution.set_profile(profile, xname="x")
 
     # Now we need to create a fitting equation. We do that by writing out the
     # equation as a string. The FitContribution will turn this into a callable

docs/examples/interface.py

@@ -37,7 +37,7 @@ def main():
     # FitContribution operations
     # "<<"  -   Inject a parameter value
     c = FitContribution("g1")
-    c.setProfile(p)
+    c.set_profile(p)
     c.setEquation("A * exp(-0.5*(x-x0)**2/sigma**2)")
     c.A << 0.5
     c.x0 << 5

docs/examples/npintensity.py

@@ -204,7 +204,7 @@ def makeRecipe(strufile, datname):
     # use it in equations with this name.
     contribution = FitContribution("bucky")
     contribution.addProfileGenerator(generator)
-    contribution.setProfile(profile, xname="q")
+    contribution.set_profile(profile, xname="q")
 
     # Now we're ready to define the fitting equation for the FitContribution.
     # We need to modify the intensity calculation, and we'll do that from

docs/examples/npintensityII.py

@@ -89,10 +89,10 @@ def makeRecipe(strufile, datname1, datname2):
     # Create the FitContributions.
     contribution1 = FitContribution("bucky1")
     contribution1.addProfileGenerator(generator1)
-    contribution1.setProfile(profile1, xname="q")
+    contribution1.set_profile(profile1, xname="q")
     contribution2 = FitContribution("bucky2")
     contribution2.addProfileGenerator(generator2)
-    contribution2.setProfile(profile2, xname="q")
+    contribution2.set_profile(profile2, xname="q")
 
     # Now we're ready to define the fitting equation for each FitContribution.
     # The functions registered below will be independent, even though they take

docs/examples/nppdfcrystal.py

@@ -48,7 +48,7 @@ def makeRecipe(ciffile, grdata):
     pdfprofile.setCalculationRange(xmin=0.1, xmax=20)
 
     pdfcontribution = FitContribution("pdf")
-    pdfcontribution.setProfile(pdfprofile, xname="r")
+    pdfcontribution.set_profile(pdfprofile, xname="r")
 
     pdfgenerator = PDFGenerator("G")
     pdfgenerator.setQmax(30.0)

docs/examples/nppdfobjcryst.py

@@ -53,7 +53,7 @@ def makeRecipe(molecule, datname):
     # The FitContribution
     contribution = FitContribution("bucky")
     contribution.addProfileGenerator(generator)
-    contribution.setProfile(profile, xname="r")
+    contribution.set_profile(profile, xname="r")
 
     # Make a FitRecipe.
     recipe = FitRecipe()

docs/examples/nppdfsas.py

@@ -52,7 +52,7 @@ def makeRecipe(ciffile, grdata, iqdata):
     pdfprofile.setCalculationRange(xmin=0.1, xmax=20)
 
     pdfcontribution = FitContribution("pdf")
-    pdfcontribution.setProfile(pdfprofile, xname="r")
+    pdfcontribution.set_profile(pdfprofile, xname="r")
 
     pdfgenerator = PDFGenerator("G")
     pdfgenerator.setQmax(30.0)
@@ -71,7 +71,7 @@ def makeRecipe(ciffile, grdata, iqdata):
         sasprofile.dy[:] = 1
 
     sascontribution = FitContribution("sas")
-    sascontribution.setProfile(sasprofile)
+    sascontribution.set_profile(sasprofile)
 
     from sas.models.EllipsoidModel import EllipsoidModel
 

docs/examples/threedoublepeaks.py

@@ -50,7 +50,7 @@ def makeRecipe():
 
     # Create the contribution
     contribution = FitContribution("peaks")
-    contribution.setProfile(profile, xname="t")
+    contribution.set_profile(profile, xname="t")
     pi = numpy.pi
     exp = numpy.exp
 

news/dep-setprofile.rst

@@ -0,0 +1,23 @@
+**Added:**
+
+* <news item>
+
+**Changed:**
+
+* <news item>
+
+**Deprecated:**
+
+* Deprecate ``setProfile`` for removal in version 4.0.0.
+
+**Removed:**
+
+* <news item>
+
+**Fixed:**
+
+* <news item>
+
+**Security:**
+
+* <news item>

requirements/conda.txt

@@ -2,3 +2,4 @@ matplotlib-base
 numpy
 scipy
 bg-mpl-stylesheets
+diffpy.utils

requirements/pip.txt

@@ -2,3 +2,4 @@ matplotlib
 numpy
 scipy
 bg-mpl-stylesheets
+diffpy.utils

src/diffpy/srfit/fitbase/fitcontribution.py

@@ -29,6 +29,17 @@
 from diffpy.srfit.fitbase.parameterset import ParameterSet
 from diffpy.srfit.fitbase.profile import Profile
 from diffpy.srfit.fitbase.recipeorganizer import equationFromString
+from diffpy.utils._deprecator import build_deprecation_message, deprecated
+
+base = "diffpy.srfit.fitbase.FitContribution"
+removal_version = "4.0.0"
+
+setprofile_dep_msg = build_deprecation_message(
+    base,
+    "setProfile",
+    "set_profile",
+    removal_version,
+)
 
 
 class FitContribution(ParameterSet):
@@ -97,7 +108,7 @@ def __init__(self, name):
         self._manage(self._generators)
         return
 
-    def setProfile(self, profile, xname=None, yname=None, dyname=None):
+    def set_profile(self, profile, xname=None, yname=None, dyname=None):
         """Assign the Profile for this FitContribution.
 
         Attributes
@@ -149,14 +160,25 @@ def setProfile(self, profile, xname=None, yname=None, dyname=None):
 
         # If we have ProfileGenerators, set their Profiles.
         for gen in self._generators.values():
-            gen.setProfile(profile)
+            gen.set_profile(profile)
 
         # If we have _eq, but not _reseq, set the residual
         if self._eq is not None and self._reseq is None:
             self.setResidualEquation("chiv")
 
         return
 
+    @deprecated(setprofile_dep_msg)
+    def setProfile(self, profile, xname=None, yname=None, dyname=None):
+        """This function has been deprecated and will be removed in version
+        4.0.0.
+
+        Please use diffpy.srfit.fitbase.FitContribution.set_profile instead.
+        """
+        return self.set_profile(
+            profile, xname=xname, yname=yname, dyname=dyname
+        )
+
     def addProfileGenerator(self, gen, name=None):
         """Add a ProfileGenerator to be used by this FitContribution.
 
@@ -192,7 +214,7 @@ def addProfileGenerator(self, gen, name=None):
 
         # If we have a profile, set the profile of the generator.
         if self.profile is not None:
-            gen.setProfile(self.profile)
+            gen.set_profile(self.profile)
 
         # Make this our equation if we don't have one. This will set the
         # residual equation if necessary.

src/diffpy/srfit/fitbase/profilegenerator.py

@@ -153,7 +153,7 @@ def operation(self):
         y = self.__call__(self.profile.x)
         return y
 
-    def setProfile(self, profile):
+    def set_profile(self, profile):
         """Assign the profile.
 
         Attributes

src/diffpy/srfit/fitbase/simplerecipe.py

@@ -93,7 +93,7 @@ def __init__(self, name="fit", conclass=FitContribution):
         self.fithooks[0].verbose = 3
         contribution = conclass("contribution")
         self.profile = Profile()
-        contribution.setProfile(self.profile)
+        contribution.set_profile(self.profile)
         self.addContribution(contribution)
         self.results = FitResults(self, update=False)
 

src/diffpy/srfit/pdf/pdfcontribution.py

@@ -93,7 +93,7 @@ def __init__(self, name):
         self._meta = {}
         # Add the profile
         profile = Profile()
-        self.setProfile(profile, xname="r")
+        self.set_profile(profile, xname="r")
 
         # Need a parameter for the overall scale, in the case that this is a
         # multi-phase fit.

tests/conftest.py

@@ -154,7 +154,7 @@ def build_recipe_one_contribution():
     y = sin(x)
     profile.setObservedProfile(x, y)
     contribution = FitContribution("c1")
-    contribution.setProfile(profile)
+    contribution.set_profile(profile)
     contribution.setEquation("A*sin(k*x + c)")
     recipe = FitRecipe()
     recipe.addContribution(contribution)
@@ -172,14 +172,14 @@ def build_recipe_two_contributions():
     y1 = sin(x)
     profile1.setObservedProfile(x, y1)
     contribution1 = FitContribution("c1")
-    contribution1.setProfile(profile1)
+    contribution1.set_profile(profile1)
     contribution1.setEquation("A*sin(k*x + c)")
 
     profile2 = Profile()
     y2 = 0.5 * sin(2 * x)
     profile2.setObservedProfile(x, y2)
     contribution2 = FitContribution("c2")
-    contribution2.setProfile(profile2)
+    contribution2.set_profile(profile2)
     contribution2.setEquation("B*sin(m*x + d)")
     recipe = FitRecipe()
     recipe.addContribution(contribution1)