#!/usr/bin/env python
##############################################################################
#
# diffpy.pdfmorph by DANSE Diffraction group
# Simon J. L. Billinge
# (c) 2008 Trustees of the Columbia University
# in the City of New York. All rights reserved.
#
# File coded by: Chris Farrow
#
# See AUTHORS.txt for a list of people who contributed.
# See LICENSE.txt for license information.
#
##############################################################################
"""Collection of plotting functions for PDFs."""
import matplotlib.pyplot as plt
import numpy
from bg_mpl_stylesheets.styles import all_styles
plt.style.use(all_styles["bg_style"])
# FIXME - make this return the figure object in the future, so several views
# can be composed.
[docs]
def plotPDFs(pairlist, labels=None, offset="auto", rmin=None, rmax=None):
"""Plots several PDFs on top of one another.
Parameters
----------
pairlist
Iterable of (r, gr) pairs to plot.
labels
Iterable of names for the pairs. If this is not the same length as the pairlist, a legend will not
be shown (default []).
offset
Offset to place between plots. PDFs will be sequentially shifted in the y-direction by the offset.
If offset is 'auto' (default), the optimal offset will be determined automatically.
rmin
The minimum r-value to plot. If this is None (default), the lower bound of the PDF is not altered.
rmax
The maximum r-value to plot. If this is None (default), the upper bound of the PDF is not altered.
"""
if labels is None:
labels = []
if offset == "auto":
offset = _find_offset(pairlist)
gap = len(pairlist) - len(labels)
labels = list(labels)
labels.extend([""] * gap)
for idx, pair in enumerate(pairlist):
r, gr = pair
plt.plot(r, gr + idx * offset, label=labels[idx])
plt.xlim(rmin, rmax)
if gap == 0:
plt.legend(loc=0)
plt.legend()
plt.xlabel(r"$r (\mathrm{\AA})$")
plt.ylabel(r"$G (\mathrm{\AA}^{-1})$")
plt.show()
return
[docs]
def comparePDFs(
pairlist,
labels=None,
rmin=None,
rmax=None,
show=True,
maglim=None,
mag=5,
rw=None,
legend=True,
l_width=1.5,
):
"""Plot two PDFs on top of each other and difference curve.
The second PDF will be shown as blue circles below and the first as a red line.
The difference curve will be in green and offset for clarity.
Parameters
----------
pairlist
Iterable of (r, gr) pairs to plot
labels
Iterable of names for the pairs. If this is not the same length as the pairlist, a legend will not
be shown (default []).
rmin
The minimum r-value to plot. If this is None (default), the lower bound of the PDF is not altered.
rmax
The maximum r-value to plot. If this is None (default), the upper bound of the PDF is not altered.
show
Show the plot (default True)
maglim
Point after which to magnify the signal by mag. If None (default), no magnification will take place.
mag
Magnification factor (default 5)
rw
Rw value to display on the plot, if any.
legend
Display the legend (default True).
"""
if labels is None:
labels = [2]
labeldata = None
labelfit = None
else:
labeldata = labels[1]
labelfit = labels[0]
rfit, grfit = pairlist[0]
rdat, grdat = pairlist[1]
# View min and max
rvmin = max(rfit[0], rdat[0])
rvmin = rmin or rvmin
rvmax = min(rfit[-1], rdat[-1])
rvmax = rmax or rvmax
gap = 2 - len(labels)
labels = list(labels)
labels.extend([""] * gap)
# Put gr1 on the same grid as rdat
gtemp = numpy.interp(rdat, rfit, grfit)
# Calculate the difference
diff = grdat - gtemp
# Put rw in the label
labeldiff = "difference" if len(labels) < 3 else labels[2]
if rw is not None:
labeldiff += " (Rw = %.3f)" % rw
# Magnify if necessary
if maglim is not None:
grfit = grfit.copy()
grfit[rfit > maglim] *= mag
sel = rdat > maglim
grdat = grdat.copy()
grdat[sel] *= mag
diff[sel] *= mag
gtemp[sel] *= mag
# Determine the offset for the difference curve.
sel = numpy.logical_and(rdat <= rvmax, rdat >= rvmin)
ymin = min(min(grdat[sel]), min(gtemp[sel]))
ymax = max(diff[sel])
offset = -1.1 * (ymax - ymin)
# Scale the x-limit based on the r-extent of the signal. This gives a nice
# density of PDF peaks.
rlim = rvmax - rvmin
scale = rlim / 25.0
# Set a reasonable minimum of .8 and maximum of 1
scale = min(1, max(scale, 0.8))
figsize = [13.5, 4.5]
figsize[0] *= scale
fig = plt.figure(1, figsize=figsize)
# Get the margins based on the figure size
lm = 0.12 / scale
bm = 0.20 / scale
rm = 0.02 / scale
tm = 0.15 / scale
axes = plt.Axes(fig, [lm, bm, 1 - lm - rm, 1 - bm - tm])
fig.add_axes(axes)
plt.minorticks_on()
plt.plot(rdat, grdat, linewidth=l_width, label=labeldata)
plt.plot(rfit, grfit, linewidth=l_width, label=labelfit)
plt.plot(rdat, offset * numpy.ones_like(diff), linewidth=3, color="black")
diff += offset
plt.plot(rdat, diff, linewidth=l_width, label=labeldiff)
if maglim is not None:
# Add a line for the magnification cutoff
plt.axvline(maglim, 0, 1, linestyle="--", color="black", linewidth=1.5, dashes=(14, 7))
# FIXME - look for a place to put the maglim
xpos = (rvmax * 0.85 + maglim) / 2 / (rvmax - rvmin)
if xpos <= 0.9:
plt.figtext(xpos, 0.7, "x%.1f" % mag, backgroundcolor="w")
# Get a tight view
plt.xlim(rvmin, rvmax)
ymin = min(diff[sel])
ymax = max(max(grdat[sel]), max(gtemp[sel]))
yspan = ymax - ymin
# Give a small border to the plot
gap = 0.05 * yspan
ymin -= gap
ymax += gap
plt.ylim(ymin, ymax)
# Make labels and legends
plt.xlabel(r"r ($\mathrm{\AA})$")
plt.ylabel(r"G $(\mathrm{\AA}^{-1})$")
if legend:
plt.legend(
bbox_to_anchor=(0.005, 1.02, 0.99, 0.10),
loc=3,
ncol=3,
mode="expand",
borderaxespad=0,
)
if show:
plt.show()
return
[docs]
def plot_param(target_labels, param_list, param_name=None, field=None):
"""
Plot Rw values for multiple morphs.
Parameters
----------
target_labels: list
Names (or field if --sort-by given) of each file acting as target for the morph.
param_list: list
Contains the values of some parameter corresponding to each file.
param_name: str
Name of the parameter.
field: list or None
When not None and entries in field are numerical, a line chart of Rw versus field is made.
When None (default) or values are non-numerical, it plots a bar chart of Rw values per file.
"""
# ensure all entries in target_labels are distinct for plotting
unique_labels = set()
for idx in range(len(target_labels)):
item = target_labels[idx]
# if repeat found, add additional label
if item in unique_labels:
counter = 1
new_name = f"{item} ({counter})"
while new_name in unique_labels:
counter += 1
new_name = f"{item} ({counter})"
item = new_name
target_labels[idx] = item
unique_labels.update({item})
# Check if numerical field
numerical = True
if field is None:
numerical = False
else:
for item in target_labels:
if type(item) is not float:
numerical = False
if numerical:
# Plot the parameter against a numerical field
plt.plot(target_labels, param_list, linestyle="-", marker="o")
if param_name is not None:
plt.ylabel(rf"{param_name}")
plt.xlabel(rf"{field}")
plt.minorticks_on()
# Create bar chart for each file
else:
# Ensure file names do not crowd
bar_size = 1 # FIXME: depends on resolution
max_len = bar_size
for item in target_labels:
max_len = max(max_len, len(item))
angle = numpy.arccos(bar_size / max_len)
angle *= 180 / numpy.pi # Convert to degrees
plt.xticks(rotation=angle)
# Plot Rw for each file
plt.bar(target_labels, param_list)
if param_name is not None:
plt.ylabel(rf"{param_name}")
if field is None:
plt.xlabel(r"Target File")
else:
plt.xlabel(rf"{field}")
# Show plot
plt.tight_layout()
plt.show()
return
[docs]
def truncatePDFs(r, gr, rmin=None, rmax=None):
"""Truncate a PDF to specified bounds.
Parameters
----------
r
r-values of the PDF.
gr
PDF g(r) values.
rmin
The minimum r-value. If this is None (default), the lower bound of the PDF is not altered.
rmax
The maximum r-value. If this is None (default), the upper bound of the PDF is not altered.
Returns
-------
r, gr
Returns the truncated r, gr.
"""
if rmin is not None:
sel = r >= rmin
gr = gr[sel]
r = r[sel]
if rmax is not None:
sel = r <= rmax
gr = gr[sel]
r = r[sel]
return r, gr
def _find_offset(pairlist):
"""Find an optimal offset between PDFs."""
maxlist = [max(p[1]) for p in pairlist]
minlist = [min(p[1]) for p in pairlist]
difflist = numpy.subtract(maxlist[:-1], minlist[1:])
offset = 1.1 * max(difflist)
return offset