Newer
Older
from matplotlib import pyplot as plt
import numpy as np
import matplotlib
import matplotlib.patches as patches
import cartopy.crs as ccrs
import cartopy.feature as cfeature
from datetime import datetime
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
# plots the wave state (all wavetroughs given specific timestep in a set) ts: pb2.Timestep
def plot_wavetroughs(ts, fig_name, cv=None):
fig, ax = plt.subplots(nrows=1, ncols=1, figsize=(8, 4), subplot_kw=dict(projection=ccrs.PlateCarree()))
x_ticks = [-100, -95, -85, -75, -65, -55, -45, -35, -25, -15, -5, 5, 15, 25, 35]
y_ticks = [0, 10, 20, 30]
extent = [-100, -45, -35, 35]
if cv is not None:
levelfc = np.asarray([0, 0.5, 1, 2, 3]) * 1e-5
cv.plot.contourf(levels=levelfc, vmin=0, extend='max', cmap='Blues')
# generate plot per pressure level, per time step
# colors per time step
# min_time = wave_thr_list[0].time.astype('float64')
# max_time = wave_thr_list[-1].time.astype('float64')
# cmap = matplotlib.cm.get_cmap('rainbow')
# color_wgts = np.linspace(0.0, 1.0, len(wave_thr_list))
# colors = ['red', 'yellow', 'green', 'blue', 'purple']
vt = ts.valid_time
for obj_idx, obj in enumerate(ts.objects):
# time64 = wave.time.astype('float64')
# time_weight = (time64 - min_time) / (max_time - min_time) if max_time > min_time else 1.0
line_pts = obj.properties.line_pts
line = patches.Path([[p.lon, p.lat] for p in line_pts])
patch = patches.PathPatch(line, linewidth=2, facecolor='none', edgecolor='red') # cmap(time_weight)
ax.add_patch(patch)
ax.coastlines()
ax.add_feature(cfeature.BORDERS.with_scale('50m'))
ax.set_extent(extent, crs=ccrs.PlateCarree())
yt1 = ax.set_yticks(y_ticks, crs=ccrs.PlateCarree())
xt1 = ax.set_xticks(x_ticks, crs=ccrs.PlateCarree())
figure_name = fig_name.replace(':', '_') + '_aew_troughs.png'
plt.savefig(figure_name, format='png')
plt.figure().clear()
plt.close()
plt.cla()
plt.clf()
return figure_name
def plot_timesteps_from_desc(object_desc, cv=None):
# plot for each set for each timestep everything detected.
from enstools.feature.util.data_utils import get_subset_by_description
for set_idx, od_set in enumerate(object_desc.sets):
fn = "set_" + str(set_idx) # TODO better to_string
cv_set = get_subset_by_description(cv, od_set)
for ts in od_set.timesteps:
cv_st = cv_set.sel(time=ts.valid_time).cv
fnt = fn + "_" + ts.valid_time
print(fnt)
# ts.validTime / .objects
fout_name = plot_wavetroughs(ts, fnt, cv=cv_st)
print(fout_name)
return None
def plot_track_from_graph(track_desc, fig_name_prefix, cv=None):
nodes = [node.this_node for node in track_desc.nodes]
fig, ax = plt.subplots(nrows=1, ncols=1, figsize=(8, 4), subplot_kw=dict(projection=ccrs.PlateCarree()))
x_ticks = [-100, -95, -85, -75, -65, -55, -45, -35, -25, -15, -5, 5, 15, 25, 35]
y_ticks = [0, 10, 20, 30]
extent = [-100, -45, -35, 35]
if cv is not None:
cv = cv.isel(time=0)
levelfc = np.asarray([0, 0.5, 1, 2, 3]) * 1e-5
cv.plot.contourf(levels=levelfc, vmin=0, extend='max', cmap='Blues')
# generate plot per pressure level, per time step
# colors per time step
min_time = datetime.strptime(nodes[0].time, '%Y-%m-%dT%H:%M:%S').timestamp()
max_time = datetime.strptime(nodes[-1].time, '%Y-%m-%dT%H:%M:%S').timestamp()
cmap = matplotlib.cm.get_cmap('rainbow')
color_wgts = np.linspace(0.0, 1.0, len(nodes))
colors = ['red', 'yellow', 'green', 'blue', 'purple']
for node_idx, node in enumerate(nodes):
obj = node.object
time_d = datetime.strptime(node.time, '%Y-%m-%dT%H:%M:%S').timestamp()
time_weight = (time_d - min_time) / (max_time - min_time) if max_time > min_time else 1.0
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
line_pts = obj.properties.line_pts
line = patches.Path([[p.lon, p.lat] for p in line_pts])
patch = patches.PathPatch(line, linewidth=2, facecolor='none', edgecolor=cmap(time_weight))
ax.add_patch(patch)
ax.coastlines()
ax.add_feature(cfeature.BORDERS.with_scale('50m'))
ax.set_extent(extent, crs=ccrs.PlateCarree())
yt1 = ax.set_yticks(y_ticks, crs=ccrs.PlateCarree())
xt1 = ax.set_xticks(x_ticks, crs=ccrs.PlateCarree())
figure_name = fig_name_prefix.replace(':', '_') + '_troughs.png'
plt.title(nodes[0].time + " - " + nodes[-1].time)
plt.savefig(figure_name, format='png')
plt.figure().clear()
plt.close()
plt.cla()
plt.clf()
return figure_name
return None
def plot_tracks_from_graph(graph_desc, ds=None):
from enstools.feature.util.data_utils import get_subset_by_description
for set_idx, od_set in enumerate(graph_desc.sets):
cv_set = get_subset_by_description(ds, od_set)
for set_tr, track in enumerate(od_set.tracks):
fn = os.path.expanduser('~') + "/phd/data/aew/plots/set_" + str(set_idx) + "_track_" + str(set_tr)
plot_track_from_graph(track, fn, cv_set.cv)