Deprecate: deprecate methods in RecipeOrganizer pt1

docs/examples/coreshellnp.py

@@ -76,8 +76,8 @@ def makeRecipe(stru1, stru2, datname):
     # very little to the PDF.
     from diffpy.srfit.pdf.characteristicfunctions import shellCF, sphericalCF
 
-    contribution.registerFunction(sphericalCF, name="f_CdS")
-    contribution.registerFunction(shellCF, name="f_ZnS")
+    contribution.register_function(sphericalCF, name="f_CdS")
+    contribution.register_function(shellCF, name="f_ZnS")
 
     # Write the fitting equation. We want to sum the PDFs from each phase and
     # multiply it by a scaling factor.

docs/examples/debyemodel.py

@@ -106,14 +106,14 @@ def makeRecipe():
     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
+    # to use the 'debye' function defined below. The 'register_function' method
     # will let us do this. Since we haven't told it otherwise,
-    # 'registerFunction' will extract the name of the function ('debye') and
+    # 'register_function' will extract the name of the function ('debye') and
     # the names of the arguments ('T', 'm', 'thetaD'). These arguments will
     # become Parameters of the FitContribution. Since we named the x-variable
     # 'T' above, the 'T' in the 'debye' equation will refer to this x-variable
     # whenever it is used.
-    contribution.registerFunction(debye)
+    contribution.register_function(debye)
 
     # Now we can create the fitting equation. We want to extend the 'debye'
     # equation by adding a vertical offset. We could wrap 'debye' in a new

docs/examples/debyemodelII.py

@@ -107,14 +107,14 @@ def plotResults(recipe):
     recipe.highT.profile.set_calculation_range(xmin="obs", xmax="obs")
     T = recipe.lowT.profile.x
     U = recipe.lowT.profile.y
-    # We can use a FitContribution's 'evaluateEquation' method to evaluate
+    # We can use a FitContribution's 'evaluate_equation' method to evaluate
     # expressions involving the Parameters and other aspects of the
     # FitContribution. Here we evaluate the fitting equation, which is always
     # accessed using the name "eq". We access it this way (rather than through
     # the Profile's ycalc attribute) because we changed the calculation range
     # above, and we therefore need to recalculate the profile.
-    lowU = recipe.lowT.evaluateEquation("eq")
-    highU = recipe.highT.evaluateEquation("eq")
+    lowU = recipe.lowT.evaluate_equation("eq")
+    highU = recipe.highT.evaluate_equation("eq")
 
     # Now we can plot this.
     import pylab

docs/examples/npintensity.py

@@ -231,7 +231,7 @@ def makeRecipe(strufile, datname):
 
     # This creates a callable equation named "bkgd" within the FitContribution,
     # and turns the polynomial coefficients into Parameters.
-    contribution.registerStringFunction(bkgdstr, "bkgd")
+    contribution.register_string_function(bkgdstr, "bkgd")
 
     # We will create the broadening function that we need by creating a python
     # function and registering it with the FitContribution.
@@ -247,7 +247,7 @@ def gaussian(q, q0, width):
 
     # This registers the python function and extracts the name and creates
     # Parameters from the arguments.
-    contribution.registerFunction(gaussian)
+    contribution.register_function(gaussian)
 
     # Center the Gaussian so it is not truncated.
     contribution.q0.value = x[len(x) // 2]
@@ -342,7 +342,7 @@ def plotResults(recipe):
 
     Imeas = recipe.bucky.profile.y
     Icalc = recipe.bucky.profile.ycalc
-    bkgd = recipe.bucky.evaluateEquation("bkgd")
+    bkgd = recipe.bucky.evaluate_equation("bkgd")
     diff = Imeas - Icalc
 
     import pylab

docs/examples/npintensityII.py

@@ -105,8 +105,8 @@ def makeRecipe(strufile, datname1, datname2):
     bkgdstr = "b0 + b1*q + b2*q**2 + b3*q**3 + b4*q**4 + b5*q**5 + b6*q**6 +\
                b7*q**7 +b8*q**8 + b9*q**9"
 
-    contribution1.registerStringFunction(bkgdstr, "bkgd")
-    contribution2.registerStringFunction(bkgdstr, "bkgd")
+    contribution1.register_string_function(bkgdstr, "bkgd")
+    contribution2.register_string_function(bkgdstr, "bkgd")
 
     # We will create the broadening function by registering a python function.
     pi = numpy.pi
@@ -119,8 +119,8 @@ def gaussian(q, q0, width):
             * exp(-0.5 * ((q - q0) / width) ** 2)
         )
 
-    contribution1.registerFunction(gaussian)
-    contribution2.registerFunction(gaussian)
+    contribution1.register_function(gaussian)
+    contribution2.register_function(gaussian)
     # Center the gaussian
     contribution1.q0.value = x[len(x) // 2]
     contribution2.q0.value = x[len(x) // 2]
@@ -196,11 +196,11 @@ def plotResults(recipe):
     # Plot this for fun.
     I1 = recipe.bucky1.profile.y
     Icalc1 = recipe.bucky1.profile.ycalc
-    bkgd1 = recipe.bucky1.evaluateEquation("bkgd")
+    bkgd1 = recipe.bucky1.evaluate_equation("bkgd")
     diff1 = I1 - Icalc1
     I2 = recipe.bucky2.profile.y
     Icalc2 = recipe.bucky2.profile.ycalc
-    bkgd2 = recipe.bucky2.evaluateEquation("bkgd")
+    bkgd2 = recipe.bucky2.evaluate_equation("bkgd")
     diff2 = I2 - Icalc2
     offset = 1.2 * max(I2) * numpy.ones_like(I2)
     I1 += offset

docs/examples/nppdfcrystal.py

@@ -59,7 +59,7 @@ def makeRecipe(ciffile, grdata):
     # Register the nanoparticle shape factor.
     from diffpy.srfit.pdf.characteristicfunctions import sphericalCF
 
-    pdfcontribution.registerFunction(sphericalCF, name="f")
+    pdfcontribution.register_function(sphericalCF, name="f")
 
     # Now we set up the fitting equation.
     pdfcontribution.set_equation("f * G")
@@ -91,10 +91,10 @@ def plotResults(recipe):
     diffzero = -0.8 * max(g) * numpy.ones_like(g)
     diff = g - gcalc + diffzero
 
-    gcryst = recipe.pdf.evaluateEquation("G")
+    gcryst = recipe.pdf.evaluate_equation("G")
     gcryst /= recipe.scale.value
 
-    fr = recipe.pdf.evaluateEquation("f")
+    fr = recipe.pdf.evaluate_equation("f")
     fr *= max(g) / fr[0]
 
     import pylab

docs/examples/nppdfsas.py

@@ -87,7 +87,7 @@ def makeRecipe(ciffile, grdata, iqdata):
 
     # Register the calculator with the pdf contribution and define the fitting
     # equation.
-    pdfcontribution.registerCalculator(cfcalculator)
+    pdfcontribution.register_calculator(cfcalculator)
     # The PDF for a nanoscale crystalline is approximated by
     # Gnano = f * Gcryst
     pdfcontribution.set_equation("f * G")
@@ -156,10 +156,10 @@ def plotResults(recipe):
     diffzero = -0.8 * max(g) * numpy.ones_like(g)
     diff = g - gcalc + diffzero
 
-    gcryst = recipe.pdf.evaluateEquation("G")
+    gcryst = recipe.pdf.evaluate_equation("G")
     gcryst /= recipe.scale.value
 
-    fr = recipe.pdf.evaluateEquation("f")
+    fr = recipe.pdf.evaluate_equation("f")
     fr *= max(g) / fr[0]
 
     import pylab

docs/examples/threedoublepeaks.py

@@ -59,7 +59,7 @@ def makeRecipe():
     def gaussian(t, mu, sig):
         return 1 / (2 * pi * sig**2) ** 0.5 * exp(-0.5 * ((t - mu) / sig) ** 2)
 
-    contribution.registerFunction(gaussian, name="peakshape")
+    contribution.register_function(gaussian, name="peakshape")
 
     def delta(t, mu):
         """Calculate a delta-function.
@@ -70,12 +70,12 @@ def delta(t, mu):
         sig = t[1] - t[0]
         return gaussian(t, mu, sig)
 
-    contribution.registerFunction(delta)
+    contribution.register_function(delta)
 
     # Here is another one
     bkgdstr = "b0 + b1*t + b2*t**2 + b3*t**3 + b4*t**4 + b5*t**5 + b6*t**6"
 
-    contribution.registerStringFunction(bkgdstr, "bkgd")
+    contribution.register_string_function(bkgdstr, "bkgd")
 
     # Now define our fitting equation. We will hardcode the peak ratios.
     contribution.set_equation(
@@ -120,7 +120,7 @@ def peakloc(mu):
         l2 = 1.0
         return 180 / pi * arcsin(pi / 180 * l2 * sin(mu) / l1)
 
-    recipe.registerFunction(peakloc)
+    recipe.register_function(peakloc)
     recipe.constrain(contribution.mu12, "peakloc(mu11)")
     recipe.constrain(contribution.mu22, "peakloc(mu21)")
     recipe.constrain(contribution.mu32, "peakloc(mu31)")
@@ -134,7 +134,7 @@ def sig(sig0, dsig, mu):
         """Calculate the peak broadening with respect to position."""
         return sig0 * (1 - dsig * mu**2)
 
-    recipe.registerFunction(sig)
+    recipe.register_function(sig)
     recipe.fix("mu")
     # Now constrain the peak widths to this
     recipe.sig0.value = 0.001

news/recipeorg-dep1.rst

@@ -0,0 +1,37 @@
+**Added:**
+
+* Added ``iterate_over_parameters`` method.
+* Added ``register_calculator`` method.
+* Added ``register_function`` method.
+* Added ``register_string_function`` method.
+* Added ``evaluate_equation`` method.
+* Added ``is_constrained`` method.
+* Added ``get_constrained_parameters`` method.
+* Added ``clear_all_constraints`` method.
+
+**Changed:**
+
+* <news item>
+
+**Deprecated:**
+
+* Deprecated ``iterPars`` method. Use ``iterate_over_parameters`` instead.
+* Deprecated ``registerCalculator`` method. Use ``register_calculator`` instead.
+* Deprecated ``registerFunction`` method. Use ``register_function`` instead.
+* Deprecated ``registerStringFunction`` method. Use ``register_string_function`` instead.
+* Deprecated ``evaluateEquation`` method. Use ``evaluate_equation`` instead.
+* Deprecated ``isConstrained`` method. Use ``is_constrained`` instead.
+* Deprecated ``getConstrainedPars`` method. Use ``get_constrained_parameters`` instead.
+* Deprecated ``clearConstraints`` method. Use ``clear_all_constraints`` instead.
+
+**Removed:**
+
+* <news item>
+
+**Fixed:**
+
+* <news item>
+
+**Security:**
+
+* <news item>

src/diffpy/srfit/equation/builder.py

@@ -106,6 +106,16 @@
 
 _builders = {}
 
+EquationFactory_base = "diffpy.srfit.equation.builder.EquationFactory"
+removal_version = "4.0.0"
+
+registerFunction_dep_msg = build_deprecation_message(
+    EquationFactory_base,
+    "registerFunction",
+    "register_function",
+    removal_version,
+)
+
 
 class EquationFactory(object):
     """A Factory for equations.
@@ -208,23 +218,26 @@ def registerOperator(self, name, op):
         opbuilder = wrapOperator(name, op)
         return self.registerBuilder(name, opbuilder)
 
-    def registerFunction(self, name, func, argnames):
+    def register_function(self, name, func, argnames):
         """Register a named function with the factory.
 
         This will register a builder for the function.
 
-        Attributes
+        Parameters
         ----------
-        name
+        name : str
             The name of the function
-        func
-            A callable python object
-        argnames
+        func : callable
+            The callable python object
+        argnames : list of str
             The argument names for func. If these names do not
             correspond to builders, then new constants with value 0
             will be created for each name.
 
-        Returns the registered builder.
+        Returns
+        -------
+        registered_builder : OperatorBuilder
+            The registered builder.
         """
         for n in argnames:
             if n not in self.builders:
@@ -234,8 +247,19 @@ def registerFunction(self, name, func, argnames):
             builder = self.builders[argname]
             argliteral = builder.literal
             opbuilder.literal.addLiteral(argliteral)
+        registered_builder = self.registerBuilder(name, opbuilder)
+        return registered_builder
 
-        return self.registerBuilder(name, opbuilder)
+    @deprecated(registerFunction_dep_msg)
+    def registerFunction(self, name, func, argnames):
+        """This function has been deprecated and will be removed in
+        version 4.0.0.
+
+        Please use
+        diffpy.srfit.equation.builder.EquationFactory.register_function
+        instead.
+        """
+        return self.register_function(name, func, argnames)
 
     def registerBuilder(self, name, builder):
         """Register builder in this module so it can be used in

src/diffpy/srfit/fitbase/calculator.py

@@ -20,7 +20,7 @@
 overloaded to accept external arguments. Calculators are used to wrap
 registered functions so that the function's Parameters are contained in
 an object specific to the function.  A custom Calculator can be added to
-another RecipeOrganizer with the 'registerCalculator' method.
+another RecipeOrganizer with the 'register_calculator' method.
 """
 
 __all__ = ["Calculator"]

src/diffpy/srfit/fitbase/fitcontribution.py

@@ -283,8 +283,8 @@ def set_equation(self, eqstr, ns={}):
         eqstr
             A string representation of the equation. Any Parameter
             registered by addParameter or setProfile, or function
-            registered by setCalculator, registerFunction or
-            registerStringFunction can be can be used in the equation
+            registered by setCalculator, register_function or
+            register_string_function can be can be used in the equation
             by name. Other names will be turned into Parameters of this
             FitContribution.
         ns

src/diffpy/srfit/fitbase/fitrecipe.py

@@ -195,7 +195,7 @@ class FitRecipe(_fitrecipe_interface, RecipeOrganizer):
         lambda self: [
             v.name
             for v in self._parameters.values()
-            if not (self.is_free(v) or self.isConstrained(v))
+            if not (self.is_free(v) or self.is_constrained(v))
         ],
         doc="names of the fixed refinable variables",
     )
@@ -204,7 +204,7 @@ class FitRecipe(_fitrecipe_interface, RecipeOrganizer):
             [
                 v.value
                 for v in self._parameters.values()
-                if not (self.is_free(v) or self.isConstrained(v))
+                if not (self.is_free(v) or self.is_constrained(v))
             ]
         ),
         doc="values of the fixed refinable variables",
@@ -622,7 +622,7 @@ def __verify_parameters(self):
 
         # Get all parameters with a value of None
         badpars = []
-        for par in self.iterPars():
+        for par in self.iterate_over_parameters():
             try:
                 par.getValue()
             except ValueError:

src/diffpy/srfit/fitbase/parameterset.py

@@ -156,7 +156,7 @@ def setConst(self, const=True):
             Flag indicating if the parameter is constant (default
             True).
         """
-        for par in self.iterPars():
+        for par in self.iterate_over_parameters():
             par.setConst(const)
 
         return