def rti_plot(data, extent, tick_locs, tick_labels, log_scale, zscale, title):
# set to log scaling
if log_scale:
RTId = 10.0 * numpy.log10(data)
else:
RTId = data
zscale_low, zscale_high = zscale
if zscale_low == 0 and zscale_high == 0:
if log_scale:
zscale_low = numpy.median(
numpy.min(RTId[numpy.where(RTId.real != -numpy.Inf)])) - 3.0
zscale_high = numpy.median(numpy.max(RTId)) + 10.0
else:
zscale_low = numpy.median(numpy.min(RTId))
zscale_high = numpy.median(numpy.max(RTId))
vmin = zscale_low
vmax = zscale_high
fig = plt.figure()
ax = fig.add_subplot(1, 1, 1)
img = ax.imshow(RTId, origin='lower',
extent=extent, interpolation='none', vmin=vmin, vmax=vmax, aspect='auto')
# plot dates
ax.set_xticks(tick_locs)
ax.set_xticklabels(tick_labels, rotation=-45, fontsize=10)
cb = fig.colorbar(img, ax=ax)
ax.set_xlabel('time (seconds)', fontsize=12)
ax.set_ylabel('range (km)', fontsize=12)
ax.set_title(title)
return fig
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