Morphfuncxy

news/morphfuncxy.rst

@@ -0,0 +1,24 @@
+**Added:**
+
+* morphfuncx added: apply a function to the grid of your morphed function; this function should maintain the monotonic increasing nature of the grid
+* morphfuncxy added: apply a general function which can modify both the ordinate and abscissa; useful when applying fourier transform or integration functions
+
+**Changed:**
+
+* <news item>
+
+**Deprecated:**
+
+* <news item>
+
+**Removed:**
+
+* <news item>
+
+**Fixed:**
+
+* <news item>
+
+**Security:**
+
+* <news item>

src/diffpy/morph/morph_api.py

@@ -209,7 +209,7 @@ def morph(
             refpars.append("baselineslope")
         elif k == "funcy":
             morph_inst = morph_cls()
-            morph_inst.function = rv_cfg.get("function", None)
+            morph_inst.function = rv_cfg.get("funcy_function", None)
             if morph_inst.function is None:
                 raise ValueError(
                     "Must provide a 'function' when using 'parameters'"

src/diffpy/morph/morph_io.py

@@ -79,32 +79,41 @@ def single_morph_output(
                 rw_pos + idx, (f"squeeze a{idx}", sq_dict[f"a{idx}"])
             )
         mr_copy = dict(morph_results_list)
-    funcy_function = None
-    if "function" in mr_copy:
-        funcy_function = mr_copy.pop("function")
-        print(funcy_function)
-    if "funcy" in mr_copy:
-        fy_dict = mr_copy.pop("funcy")
-        rw_pos = list(mr_copy.keys()).index("Rw")
-        morph_results_list = list(mr_copy.items())
-        for idx, key in enumerate(fy_dict):
-            morph_results_list.insert(
-                rw_pos + idx, (f"funcy {key}", fy_dict[key])
-            )
-        mr_copy = dict(morph_results_list)
+
+    # Handle special inputs (functional remove)
+    func_dicts = {
+        "funcxy": [None, None],
+        "funcx": [None, None],
+        "funcy": [None, None],
+    }
+    for func in func_dicts.keys():
+        if f"{func}_function" in mr_copy:
+            func_dicts[func][0] = mr_copy.pop(f"{func}_function")
+        if func in mr_copy:
+            func_dicts[func][1] = mr_copy.pop(func)
+            rw_pos = list(mr_copy.keys()).index("Rw")
+            morph_results_list = list(mr_copy.items())
+            for idx, key in enumerate(func_dicts[func][1]):
+                morph_results_list.insert(
+                    rw_pos + idx, (f"{func} {key}", func_dicts[func][1][key])
+                )
+            mr_copy = dict(morph_results_list)
+
     # Normal inputs
     morphs_out += "\n".join(
         f"# {key} = {mr_copy[key]:.6f}" for key in mr_copy.keys()
     )
-    # Special inputs (functional)
-    if funcy_function is not None:
-        morphs_in += '# funcy function =\n"""\n'
-        f_code, _ = inspect.getsourcelines(funcy_function)
-        n_leading = len(f_code[0]) - len(f_code[0].lstrip())
-        for idx, f_line in enumerate(f_code):
-            f_code[idx] = f_line[n_leading:]
-        morphs_in += "".join(f_code)
-        morphs_in += '"""\n'
+
+    # Handle special inputs (functional add)
+    for func in func_dicts.keys():
+        if func_dicts[func][0] is not None:
+            morphs_in += f'# {func} function =\n"""\n'
+            f_code, _ = inspect.getsourcelines(func_dicts[func][0])
+            n_leading = len(f_code[0]) - len(f_code[0].lstrip())
+            for idx, f_line in enumerate(f_code):
+                f_code[idx] = f_line[n_leading:]
+            morphs_in += "".join(f_code)
+            morphs_in += '"""\n'
 
     # Printing to terminal
     if stdout_flag:

src/diffpy/morph/morphapp.py

@@ -520,12 +520,26 @@ def single_morph(
 
     # Python-Specific Morphs
     if pymorphs is not None:
-        # funcy value is a tuple (function,{param_dict})
+        # funcxy/funcx/funcy value is a tuple (function,{param_dict})
+        if "funcxy" in pymorphs:
+            mfxy_function = pymorphs["funcxy"][0]
+            mfxy_params = pymorphs["funcxy"][1]
+            chain.append(morphs.MorphFuncxy())
+            config["funcxy_function"] = mfxy_function
+            config["funcxy"] = mfxy_params
+            refpars.append("funcxy")
+        if "funcx" in pymorphs:
+            mfx_function = pymorphs["funcx"][0]
+            mfx_params = pymorphs["funcx"][1]
+            chain.append(morphs.MorphFuncx())
+            config["funcx_function"] = mfx_function
+            config["funcx"] = mfx_params
+            refpars.append("funcx")
         if "funcy" in pymorphs:
             mfy_function = pymorphs["funcy"][0]
             mfy_params = pymorphs["funcy"][1]
             chain.append(morphs.MorphFuncy())
-            config["function"] = mfy_function
+            config["funcy_function"] = mfy_function
             config["funcy"] = mfy_params
             refpars.append("funcy")
 
@@ -692,6 +706,9 @@ def single_morph(
 
     # FOR FUTURE MAINTAINERS
     # Any new morph should have their input morph parameters updated here
+    # You should also update the IO in morph_io
+    # if you think there requires special handling
+
     # Input morph parameters
     morph_inputs = {
         "scale": scale_in,
@@ -705,11 +722,25 @@ def single_morph(
         for idx, _ in enumerate(squeeze_dict):
             morph_inputs.update({f"squeeze a{idx}": squeeze_dict[f"a{idx}"]})
     if pymorphs is not None:
+        if "funcxy" in pymorphs:
+            for funcxy_param in pymorphs["funcxy"][1].keys():
+                morph_inputs.update(
+                    {
+                        f"funcxy {funcxy_param}": pymorphs["funcxy"][1][
+                            funcxy_param
+                        ]
+                    }
+                )
         if "funcy" in pymorphs:
             for funcy_param in pymorphs["funcy"][1].keys():
                 morph_inputs.update(
                     {f"funcy {funcy_param}": pymorphs["funcy"][1][funcy_param]}
                 )
+        if "funcx" in pymorphs:
+            for funcy_param in pymorphs["funcx"][1].keys():
+                morph_inputs.update(
+                    {f"funcx {funcy_param}": pymorphs["funcx"][1][funcy_param]}
+                )
 
     # Output morph parameters
     morph_results = dict(config.items())

src/diffpy/morph/morphpy.py

@@ -26,7 +26,7 @@ def get_args(parser, params, kwargs):
 
 def __get_morph_opts__(parser, scale, stretch, smear, plot, **kwargs):
     # Check for Python-specific options
-    python_morphs = ["funcy"]
+    python_morphs = ["funcy", "funcx", "funcxy"]
     pymorphs = {}
     for pmorph in python_morphs:
         if pmorph in kwargs:

src/diffpy/morph/morphs/__init__.py

@@ -17,6 +17,8 @@
 
 from diffpy.morph.morphs.morph import Morph  # noqa: F401
 from diffpy.morph.morphs.morphchain import MorphChain  # noqa: F401
+from diffpy.morph.morphs.morphfuncx import MorphFuncx
+from diffpy.morph.morphs.morphfuncxy import MorphFuncxy
 from diffpy.morph.morphs.morphfuncy import MorphFuncy
 from diffpy.morph.morphs.morphishape import MorphISphere, MorphISpheroid
 from diffpy.morph.morphs.morphresolution import MorphResolutionDamping
@@ -42,6 +44,8 @@
     MorphShift,
     MorphSqueeze,
     MorphFuncy,
+    MorphFuncx,
+    MorphFuncxy,
 ]
 
 # End of file

src/diffpy/morph/morphs/morphfuncx.py

@@ -0,0 +1,87 @@
+"""Class MorphFuncx -- apply a user-supplied python function to the
+x-axis."""
+
+from diffpy.morph.morphs.morph import LABEL_GR, LABEL_RA, Morph
+
+
+class MorphFuncx(Morph):
+    """Apply a custom function to the x-axis (grid) of the morph
+    function.
+
+    General morph function that applies a user-supplied function to the
+    x-coordinates of morph data to make it align with a target.
+
+    Notice: the function provided must preserve the monotonic
+    increase of the grid.
+    I.e. the function f applied on the grid x must ensure for all
+    indices i<j, f(x[i]) < f(x[j]).
+
+    Configuration Variables
+    -----------------------
+    function: callable
+        The user-supplied function that applies a transformation to the
+        x-coordinates of the data.
+
+    parameters: dict
+        A dictionary of parameters to pass to the function.
+
+    Returns
+    -------
+        A tuple (x_morph_out, y_morph_out, x_target_out, y_target_out)
+        where the target values remain the same and the morph data is
+        transformed according to the user-specified function and parameters
+        The morphed data is returned on the same grid as the unmorphed data
+
+    Example
+    -------
+    Import the funcx morph function:
+
+        >>> from diffpy.morph.morphs.morphfuncx import MorphFuncx
+
+    Define or import the user-supplied transformation function:
+
+        >>> import numpy as np
+        >>> def exp_function(x, y, scale, rate):
+        >>>     return abs(scale) * np.exp(rate * x)
+
+    Note that this transformation is monotonic increasing, so will preserve
+    the monotonic increasing nature of the provided grid.
+
+    Provide initial guess for parameters:
+
+        >>> parameters = {'scale': 1, 'rate': 1}
+
+    Run the funcy morph given input morph array (x_morph, y_morph)and target
+    array (x_target, y_target):
+
+        >>> morph = MorphFuncx()
+        >>> morph.funcx_function = exp_function
+        >>> morph.funcx = parameters
+        >>> x_morph_out, y_morph_out, x_target_out, y_target_out =
+        ... morph.morph(x_morph, y_morph, x_target, y_target)
+
+    To access parameters from the morph instance:
+
+        >>> x_morph_in = morph.x_morph_in
+        >>> y_morph_in = morph.y_morph_in
+        >>> x_target_in = morph.x_target_in
+        >>> y_target_in = morph.y_target_in
+        >>> parameters_out = morph.funcx
+    """
+
+    # Define input output types
+    summary = "Apply a Python function to the x-axis data"
+    xinlabel = LABEL_RA
+    yinlabel = LABEL_GR
+    xoutlabel = LABEL_RA
+    youtlabel = LABEL_GR
+    parnames = ["funcx_function", "funcx"]
+
+    def morph(self, x_morph, y_morph, x_target, y_target):
+        """Apply the user-supplied Python function to the x-coordinates
+        of the morph data."""
+        Morph.morph(self, x_morph, y_morph, x_target, y_target)
+        self.x_morph_out = self.funcx_function(
+            self.x_morph_in, self.y_morph_in, **self.funcx
+        )
+        return self.xyallout

src/diffpy/morph/morphs/morphfuncxy.py

@@ -0,0 +1,85 @@
+"""Class MorphFuncxy -- apply a user-supplied python function to both
+the x and y axes."""
+
+from diffpy.morph.morphs.morph import LABEL_GR, LABEL_RA, Morph
+
+
+class MorphFuncxy(Morph):
+    """Apply a custom function to the morph function.
+
+    General morph function that applies a user-supplied function to the
+    morph data to make it align with a target.
+
+    This function may modify both the grid (x-axis) and function (y-axis)
+    of the morph data.
+
+    The user-provided function must return a two-column 1D function.
+
+    Configuration Variables
+    -----------------------
+    function: callable
+        The user-supplied function that applies a transformation to the
+        grid (x-axis) and morph function (y-axis).
+
+    parameters: dict
+        A dictionary of parameters to pass to the function.
+
+    Returns
+    -------
+        A tuple (x_morph_out, y_morph_out, x_target_out, y_target_out)
+        where the target values remain the same and the morph data is
+        transformed according to the user-specified function and parameters
+        The morphed data is returned on the same grid as the unmorphed data
+
+    Example (EDIT)
+    -------
+    Import the funcxy morph function:
+
+        >>> from diffpy.morph.morphs.morphfuncxy import MorphFuncxy
+
+    Define or import the user-supplied transformation function:
+
+        >>> import numpy as np
+        >>> def shift_function(x, y, hshift, vshift):
+        >>>     return x + hshift, y + vshift
+
+    Provide initial guess for parameters:
+
+        >>> parameters = {'hshift': 1, 'vshift': 1}
+
+    Run the funcy morph given input morph array (x_morph, y_morph)and target
+    array (x_target, y_target):
+
+        >>> morph = MorphFuncxy()
+        >>> morph.function = shift_function
+        >>> morph.funcy = parameters
+        >>> x_morph_out, y_morph_out, x_target_out, y_target_out =
+        ... morph.morph(x_morph, y_morph, x_target, y_target)
+
+    To access parameters from the morph instance:
+
+        >>> x_morph_in = morph.x_morph_in
+        >>> y_morph_in = morph.y_morph_in
+        >>> x_target_in = morph.x_target_in
+        >>> y_target_in = morph.y_target_in
+        >>> parameters_out = morph.funcxy
+    """
+
+    # Define input output types
+    summary = (
+        "Apply a Python function to the data (y-axis) and data grid (x-axis)"
+    )
+    xinlabel = LABEL_RA
+    yinlabel = LABEL_GR
+    xoutlabel = LABEL_RA
+    youtlabel = LABEL_GR
+    parnames = ["funcxy_function", "funcxy"]
+
+    def morph(self, x_morph, y_morph, x_target, y_target):
+        """Apply the user-supplied Python function to the y-coordinates
+        of the morph data."""
+        Morph.morph(self, x_morph, y_morph, x_target, y_target)
+        self.x_morph_out, self.y_morph_out = self.funcxy_function(
+            self.x_morph_in, self.y_morph_in, **self.funcxy
+        )
+        return self.xyallout

src/diffpy/morph/morphs/morphfuncy.py

@@ -34,6 +34,7 @@ class MorphFuncy(Morph):
 
     Define or import the user-supplied transformation function:
 
+        >>> import numpy as np
         >>> def sine_function(x, y, amplitude, frequency):
         >>>     return amplitude * np.sin(frequency * x) * y
 
@@ -45,7 +46,7 @@ class MorphFuncy(Morph):
     array (x_target, y_target):
 
         >>> morph = MorphFuncy()
-        >>> morph.function = sine_function
+        >>> morph.funcy_function = sine_function
         >>> morph.funcy = parameters
         >>> x_morph_out, y_morph_out, x_target_out, y_target_out =
         ... morph.morph(x_morph, y_morph, x_target, y_target)
@@ -65,13 +66,13 @@ class MorphFuncy(Morph):
     yinlabel = LABEL_GR
     xoutlabel = LABEL_RA
     youtlabel = LABEL_GR
-    parnames = ["function", "funcy"]
+    parnames = ["funcy_function", "funcy"]
 
     def morph(self, x_morph, y_morph, x_target, y_target):
         """Apply the user-supplied Python function to the y-coordinates
         of the morph data."""
         Morph.morph(self, x_morph, y_morph, x_target, y_target)
-        self.y_morph_out = self.function(
+        self.y_morph_out = self.funcy_function(
             self.x_morph_in, self.y_morph_in, **self.funcy
         )
         return self.xyallout