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#!/usr/bin/env python3
import sys
import yaml
import json
import matplotlib.pyplot as plt
import matplotlib as mpl
from matplotlib.colors import LinearSegmentedColormap
from metpy.units import units
# Define custom gpm and gpdm units. The default gpm in metpy is aliased to meter.
# We need the correct definition
units.define('_gpm = 9.80665 * J/kg')
units.define('_gpdm = 10 * _gpm')
# Define custom colormap
clcov_cmap = {
'red': (
(0.0, 0.0, 0.0),
(0.1, 0.9, 0.9),
(1.0, 0.3, 0.3),
),
'green': (
(0.0, 0.5, 0.5),
(0.1, 0.9, 0.9),
(1.0, 0.3, 0.3),
),
'blue': (
(0.0, 0.9, 0.9),
(0.1, 0.9, 0.9),
(1.0, 0.3, 0.3),
),
}
mpl.colormaps.register(LinearSegmentedColormap('clcov', clcov_cmap))
FILE = 'config.yaml'
if len(sys.argv) > 1:
FILE = sys.argv[1]
conf = None
with open(FILE, 'r') as f:
conf = yaml.safe_load(f)
index = []
for plotter in conf['plotter']:
modname = plotter['module']
del plotter['module']
if 'aggregator' in plotter:
aggname = plotter['aggregator']
del plotter['aggregator']
aggconf = conf['aggregator'][aggname]
classname = aggconf['module']
# We should prbly not delete it like in the plotter, since it is not a deepcopy
# and may be used again.
agg = __import__(classname, fromlist=[None])
# TODO: figure out a way to use **aggconf instead.
plotter['data'] = agg.load_data(aggname, aggconf)
mod = __import__(modname, fromlist=[None])
index.extend(mod.run(**plotter))
plt.close('all')
with open(conf['index'], 'w') as f:
f.write(json.dumps(index, indent=4))
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