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Pycode

Dataset card Data Studio Files Community
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:param data: a dictionary of fetched data where keys correspond to products
:param config: a config object
:param shape: the size of a composite image
:param lower_val: a tuple of lower values for RGB, any value below this is set to the low value
:param upper_val: a tuple of upper values for RGB, any value above this is set to the high value
:return: a (m,n,3) numpy array for a three color image where all values are between 0 and 1
""""""
order = {'red': 0, 'green': 1, 'blue': 2}
three_color = np.zeros((shape[0], shape[1], 3))
channel_colors = {color: config.default[color] for color in ['red', 'green', 'blue']}
for color, channel in channel_colors.items():
if data[channel][1] is None or \
abs((time - date_parser.parse(data[channel][0]['date-end'])).total_seconds()) > step.total_seconds()/2.0:
return np.zeros((shape[0], shape[1], 3))
three_color[:, :, order[color]] = data[channel][1]
# scale the image by the power
three_color[:, :, order[color]] = np.power(three_color[:, :, order[color]],
config.default[""{}_power"".format(color)])
# adjust the percentile thresholds
lower = lower_val[order[color]]
upper = upper_val[order[color]]
three_color[np.where(three_color[:, :, order[color]] < lower)] = lower
three_color[np.where(three_color[:, :, order[color]] > upper)] = upper
# image values must be between (0,1) so scale image
for color, index in order.items():
three_color[:, :, index] /= upper_val[order[color]]
return three_color"
103,"def main():
""""""
process the main task
""""""
args = get_args()
args.start = date_parser.parse(args.start)
args.end = date_parser.parse(args.end)
args.step = timedelta(args.step)
config = Config(args.config)
times = [args.start + i * args.step for i in range(int((args.end - args.start) / args.step))]
for i, time in enumerate(times):
make_plot(time, config, args.step)"
104,"def make_plot(time, config, step):
""""""
create a three color and all composite images for a given time
NOTE: channel mins and maxes are currently hardcoded since this is a very specific script
:param i: the index to save the file as
:param time:
:param config:
:return:
""""""
fig, ax = plt.subplots()
try:
result = Fetcher(time, products=config.products,
suvi_composite_path=config.suvi_composite_path).fetch(multithread=False)
if result:
arr = make_three_color(result, time, step, config, upper_val=(2.4, 2.4, 2.4))
else:
arr = np.zeros((1280, 1280, 3))
except ValueError:
arr = np.zeros((1280, 1280, 3))
ax.imshow(arr, origin='lower')
timestr = time.strftime(""%Y-%m-%d %H:%M:%S"")
fnextend = time.strftime(""%Y%m%d%H%M%S"")
ax.set_title(timestr)
ax.set_axis_off()
fig.savefig(""three_{}.png"".format(fnextend), bbox_inches='tight', dpi=300)
plt.close(fig)
channel_min = {'suvi-l2-ci094': 0,
'suvi-l2-ci131': 0,
'suvi-l2-ci171': 0,
'suvi-l2-ci195': 0,
'suvi-l2-ci284': 0,
'suvi-l2-ci304': 0}
channel_max = {'suvi-l2-ci094': 1,
'suvi-l2-ci131': 1,
'suvi-l2-ci171': 1.8,
'suvi-l2-ci195': 1.8,
'suvi-l2-ci284': 1.8,
'suvi-l2-ci304': 2.5}
for channel in channel_min:
fig, ax = plt.subplots()
if result[channel][1] is not None and \
abs((time - date_parser.parse(result[channel][0]['date-end'])).total_seconds()) < step.total_seconds()/2.0:
dat = np.power(result[channel][1], 0.25)
ax.set_title(date_parser.parse(result[channel][0]['date-obs']).strftime(""%Y-%m-%d %H:%M:%S""))
dat[np.isnan(dat)] = 0
else:
dat = np.zeros((1280, 1280))
ax.set_title(timestr)
ax.imshow(dat, vmin=channel_min[channel], vmax=channel_max[channel], cmap='gray', origin='lower')