Segmented Plot

example_usage.py

import ephem
from segmented_plot import segment_plot
import matplotlib.pyplot

base_date = ephem.Date(b'2014/11/25')
date_range = numpy.array(range(-182, 2*356))

fig, ax = matplotlib.pyplot.subplots()

for (planet, style) in [(ephem.Moon, {'color': '0.9'}),
                        (ephem.Sun,  {'color': 'y', 'lw': '3'}),
                        (ephem.Mars,  {'color': 'r'}),
                        (ephem.Jupiter,  {'color': 'g'})]:
    segment_plot(numpy.array([12*ep.ra/numpy.pi for ep in [planet(base_date + d) for d in date_range]]),
                date_range,
                ax, lims=[0, 24], thresh=0.95,
                **style)

ax.set(xlim=[0, 24])
ax.set(ylim=[min(date_range), max(date_range)])

Segmented Plot as Func.md

This file sets the title of this gist.

This gist gives an example of how to implement SO question 27138751 by defining a 'segment_plot' function.

segmented_plot.py

from __future__ import division

from matplotlib.pyplot import gca
import numpy


def unlink_wrap(dat, lims=lims, thresh=thresh):
    jump = numpy.nonzero(numpy.abs(numpy.diff(dat)) > ((lims[1] - lims[0]) * thresh))[0]
    lasti = 0
    for ind in jump:
        yield slice(lasti, ind + 1)
        lasti = ind + 1
    yield slice(lasti, len(dat))


def pad_segments(x, y, slc):
    x_values = x[slc]
    y_values = y[slc]
    if slc.stop < len(x):
        x_values = numpy.concatenate((x_values, [x[slc.stop + 1] + 24]))
        y_values = numpy.concatenate((y_values, [y[slc.stop + 1]]))
    if slc.start > 0:
        x_values = numpy.concatenate(([x[slc.start - 1] - 24], x_values))
        y_values = numpy.concatenate(([y[slc.start - 1]], y_values))
    return x_values, y_values


def segment_plot(x, y, ax=None, lims=[0, 24], thresh=0.95, **kwargs):
    if ax is None:
        ax = gca()

    for slc in unlink_wrap(x, lims=lims, thresh=thresh):
        x_vals, y_vals = pad_segments(x, y, slc)
        ax.plot(x_vals, y_vals, **kwargs)