#!/usr/bin/env python
import numpy as np
from diffpy.morph.morphapp import create_option_parser, single_morph
[docs]
def get_args(parser, params, kwargs):
inputs = []
for key, value in params.items():
if value is not None:
inputs.append(f"--{key}")
inputs.append(f"{value}")
for key, value in kwargs.items():
key = key.replace("_", "-")
if key == "exclude":
for param in value:
inputs.append(f"--{key}")
inputs.append(f"{param}")
else:
inputs.append(f"--{key}")
inputs.append(f"{value}")
(opts, pargs) = parser.parse_args(inputs)
return opts, pargs
def __get_morph_opts__(parser, scale, stretch, smear, plot, **kwargs):
# Check for Python-specific options
python_morphs = ["funcy", "funcx", "funcxy"]
pymorphs = {}
for pmorph in python_morphs:
if pmorph in kwargs:
pmorph_value = kwargs.pop(pmorph)
pymorphs.update({pmorph: pmorph_value})
# Special handling of parameters with dashes
kwargs_copy = kwargs.copy()
kwargs = {}
for key in kwargs_copy.keys():
new_key = key
if "_" in key:
new_key = key.replace("_", "-")
kwargs.update({new_key: kwargs_copy[key]})
# Special handling of store_true and store_false parameters
opts_storing_values = [
"verbose",
"pearson",
"addpearson",
"apply",
"reverse",
"diff",
"get-diff",
]
opts_to_ignore = ["multiple-morphs", "multiple-targets"]
for opt in opts_storing_values:
if opt in kwargs:
# Remove if user sets false in params
if not kwargs[opt]:
kwargs.pop(opt)
for opt in opts_to_ignore:
if opt in kwargs:
kwargs.pop(opt)
# Wrap the CLI
params = {
"scale": scale,
"stretch": stretch,
"smear": smear,
"noplot": True if not plot else None,
}
opts, _ = get_args(parser, params, kwargs)
if not len(pymorphs) > 0:
pymorphs = None
return opts, pymorphs
# Take in file names as input.
[docs]
def morph(
morph_file,
target_file,
scale=None,
stretch=None,
smear=None,
plot=False,
**kwargs,
):
"""Run diffpy.morph at Python level.
Parameters
----------
morph_file: str or numpy.array
Path-like object to the file to be morphed.
target_file: str or numpy.array
Path-like object to the target file.
scale: float, optional
Initial guess for the scaling parameter.
Refinement is done only for parameter that are not None.
stretch: float, optional
Initial guess for the stretching parameter.
smear: float, optional
Initial guess for the smearing parameter.
plot: bool
Show a plot of the morphed and target functions as well as the
difference curve (default: False).
kwargs: str, float, list, tuple, bool
See the diffpy.morph website for full list of options.
Returns
-------
morph_info: dict
Summary of morph parameters (e.g. scale, stretch, smear, rmin, rmax)
and results (e.g. Pearson, Rw).
morph_table: list
Function after morph where morph_table[:,0] is the abscissa and
morph_table[:,1] is the ordinate.
"""
pargs = [morph_file, target_file]
parser = create_option_parser()
opts, pymorphs = __get_morph_opts__(
parser, scale, stretch, smear, plot, **kwargs
)
return single_morph(
parser,
opts,
pargs,
stdout_flag=False,
python_wrap=True,
pymorphs=pymorphs,
)
# Take in array-like objects as input.
[docs]
def morph_arrays(
morph_table,
target_table,
scale=None,
stretch=None,
smear=None,
plot=False,
**kwargs,
):
"""Run diffpy.morph at Python level.
Parameters
----------
morph_table: numpy.array
Two-column array of (r, gr) for morphed function.
target_table: numpy.array
Two-column array of (r, gr) for target function.
scale: float, optional
Initial guess for the scaling parameter.
Refinement is done only for parameter that are not None.
stretch: float, optional
Initial guess for the stretching parameter.
smear: float, optional
Initial guess for the smearing parameter.
plot: bool
Show a plot of the morphed and target functions as well as the
difference curve (default: False).
kwargs: str, float, list, tuple, bool
See the diffpy.morph website for full list of options.
Returns
-------
morph_info: dict
Summary of morph parameters (e.g. scale, stretch, smear, rmin, rmax)
and results (e.g. Pearson, Rw).
morph_table: list
Function after morph where morph_table[:,0] is the abscissa and
morph_table[:,1] is the ordinate.
"""
morph_table = np.array(morph_table)
target_table = np.array(target_table)
x_morph = morph_table[:, 0]
y_morph = morph_table[:, 1]
x_target = target_table[:, 0]
y_target = target_table[:, 1]
pargs = ["Morph", "Target", x_morph, y_morph, x_target, y_target]
parser = create_option_parser()
opts, pymorphs = __get_morph_opts__(
parser, scale, stretch, smear, plot, **kwargs
)
return single_morph(
parser,
opts,
pargs,
stdout_flag=False,
python_wrap=True,
pymorphs=pymorphs,
)