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@rlcamp
Last active July 27, 2023 01:57
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using matplotlib to plot data vs unix time with yaxis_date is ungoogleable
#!/usr/bin/env python3
import sys
import os
def plot_image_vs_time(data, timestamps, x0, dx, xlabel, title=None):
import datetime
try:
import numpy
import matplotlib
except:
print('warning: plotting skipped, please "pip3 install matplotlib" or the equivalent on your OS')
exit()
matplotlib.use('pdf')
import matplotlib.pyplot
T, X = data.shape
if T < 2: raise RuntimeError('need multiple rows of pixels to plot')
if len(timestamps) != T: raise RuntimeError('need one timestamp per row of pixels')
dt_mean = (timestamps[T - 1] - timestamps[0]) / (T - 1)
fig, ax = matplotlib.pyplot.subplots()
# assumes that timestamps[0] and x0 specify the CENTRE of the oldest leftmost pixel
extent = [x0 - 0.5 * dx, x0 + (X - 0.5) * dx,
matplotlib.dates.date2num(datetime.datetime.utcfromtimestamp(timestamps[T - 1] + 0.5 * dt_mean)),
matplotlib.dates.date2num(datetime.datetime.utcfromtimestamp(timestamps[0] - 0.5 * dt_mean)) ]
# aspect is calculated from extent to force square pixels on screen
pos = ax.imshow(data, extent=extent, aspect=abs(extent[1] - extent[0]) * data.shape[0] / (abs(extent[3] - extent[2]) * data.shape[1]), vmin=0, vmax=255)
ax.yaxis_date()
ax.set(xlabel=xlabel)
if title:
ax.set(title=title)
ax.title.set_size(10)
if (sys.stdout.isatty()):
fig.savefig('/tmp/out.pdf', bbox_inches='tight')
os.system('open /tmp/out.pdf 2>/dev/null')
else: fig.savefig(sys.stdout.buffer, bbox_inches='tight')
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