# Copyright (C) 2021
# Smithsonian Astrophysical Observatory
# This program is free software; you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation; either version 3 of the License, or
# (at your option) any later version.
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
# You should have received a copy of the GNU General Public License along
# with this program; if not, write to the Free Software Foundation, Inc.,
# 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
'''Helper functions for plotting
This module contains a few helper functions for reformatting arrays in ways
that facilitate easier plotting.
import numpy as np
__all__ = ('intersperse', 'histogram_line')
[docs]def intersperse(a, b):
'''Interleave two arrays a and b
a, b : array
Two arrys to interleave. The numbe of elements in the two arrays cannot
differ by more than one.
out : array
array that interleaves the input arrays
>>> import numpy as np
>>> a = np.arange(5)
>>> b = np.arange(10, 14)
>>> intersperse(a, b)
array([ 0, 10, 1, 11, 2, 12, 3, 13, 4])
for interleaving arrays.
out = np.empty((a.size + b.size, ), dtype=a.dtype)
out[0::2] = a
out[1::2] = b
[docs]def histogram_line(xlo, xhi, y):
'''Manually create x, y arrays for draw histrogram line
Draw the data as a histogram, manually creating the lines
from the low to high edge of each bin. In the case on non-consequtive
bins, the line will have some nan values, so that disjoint lines are
In matplotlib, an alternative would be to create RectanglePatches,
one for each bin, but I don't want each bin to go down to 0. I do
not find the existing drawstyle options to be sufficient.
xlo, xhi : array
Lower and upper bin boundaries. Typically, ``xlo`` will contain the
lower boundary and ``xhi`` the upper boundary, but this function can
deal with situations where that is reversed. Both arrays have to be
monotonically increasing or decreasing.
y : array
Dependent values for each histrogram bin_hi
x, y2 : array
x and y arrays for plotting the histogram line.
if (len(xlo) != len(xhi)) or (len(y) != len(xlo)):
raise ValueError('All input arrays have to have the same length.')
# Deal with reversed order. Can happen when converting from energy
# to wavelength, or if input PHA is not ordered in increasing energy.
# But if both are happening at the same time, need to switch twice, which
# is a no-op. So, we get to use the elusive Python XOR operator.
if (xlo > xhi) ^ (xhi > xhi[-1]):
xlo, xhi = xhi, xlo
idxs, = np.where(xhi[:-1] != xlo[1:])
x = intersperse(xlo, xhi)
y2 = intersperse(y, y)
if idxs.size > 0:
idxs = 2 * (idxs + 1)
nans = [np.nan] * idxs.size
# ensure the arrays are floats so we can add nan values
x = np.insert(x.astype(np.float64), idxs, nans)
y2 = np.insert(y2.astype(np.float64), idxs, nans)
return x, y2