1a16f90b-a2b4-48e1-87b0-09ef1ba1bd9c

Committed 05 Aug 2024 02:25AM UTC coverage: 48.631% (-4.6%) from 53.245%

Build # 1a16f90b-a2b4-48e1-87b0-09ef1ba1bd9c

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push

circleci

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web-flow

Commit Message

Merge pull request #674 from royagrace/update_tests

Update tests to get rid of extra files created when running tests

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9.68

/tools/RAiDER/models/plotWeather.py

"""
This set of functions is designed to for plotting WeatherModel
class objects. It is not designed to be used on its own apart
from this class.
"""

import os
from RAiDER.interpolator import RegularGridInterpolator as Interpolator
from mpl_toolkits.axes_grid1 import make_axes_locatable as mal
import numpy as np
import matplotlib.pyplot as plt
import matplotlib as mpl
mpl.use('Agg')


def plot_pqt(weatherObj, savefig=True, z1=500, z2=15000):
    '''
    Create a plot with pressure, temp, and humidity at two heights
    '''

    # Get the interpolator

    intFcn_p = Interpolator((weatherObj._xs, weatherObj._ys, weatherObj._zs), weatherObj._p.swapaxes(0, 1))
    intFcn_e = Interpolator((weatherObj._xs, weatherObj._ys, weatherObj._zs), weatherObj._e.swapaxes(0, 1))
    intFcn_t = Interpolator((weatherObj._xs, weatherObj._ys, weatherObj._zs), weatherObj._t.swapaxes(0, 1))

    # get the points needed
    XY = np.meshgrid(weatherObj._xs, weatherObj._ys)
    x = XY[0]
    y = XY[1]
    z1a = np.zeros(x.shape) + z1
    z2a = np.zeros(x.shape) + z2
    pts1 = np.stack((x.flatten(), y.flatten(), z1a.flatten()), axis=1)
    pts2 = np.stack((x.flatten(), y.flatten(), z2a.flatten()), axis=1)

    p1 = intFcn_p(pts1)
    e1 = intFcn_e(pts1)
    t1 = intFcn_t(pts1)
    p2 = intFcn_p(pts2)
    e2 = intFcn_e(pts2)
    t2 = intFcn_t(pts2)

    # Now get the data to plot
    plots = [p1 / 1e2, e1 / 1e2, t1 - 273.15, p2 / 1e2, e2 / 1e2, t2 - 273.15]
    # titles = ('P (hPa)', 'E (hPa)'.format(z1), 'T (C)', '', '', '')
    titles = ('P (hPa)', 'E (hPa)', 'T (C)', '', '', '')

    # setup the plot
    f = plt.figure(figsize=(18, 14))
    f.suptitle(f'{weatherObj._Name} Pressure/Humidity/Temperature at height {z1}m and {z2}m (values should drop as elevation increases)')

    xind = int(np.floor(weatherObj._xs.shape[0] / 2))
    yind = int(np.floor(weatherObj._ys.shape[0] / 2))

    # loop over each plot
    for ind, plot, title in zip(range(len(plots)), plots, titles):
        sp = f.add_subplot(3, 3, ind + 1)
        im = sp.imshow(np.reshape(plot, x.shape),
                       cmap='viridis',
                       extent=[np.nanmin(x), np.nanmax(x), np.nanmin(y), np.nanmax(y)],
                       origin='lower')
        sp.plot(x[yind, xind], y[yind, xind], 'ko')
        divider = mal(sp)
        cax = divider.append_axes("right", size="4%", pad=0.05)
        plt.colorbar(im, cax=cax)
        sp.set_title(title)
        if ind == 0:
            sp.set_ylabel('{} m\n'.format(z1))
        if ind == 3:
            sp.set_ylabel('{} m\n'.format(z2))

    # add plots that show each variable with height
    zdata = weatherObj._zs[:] / 1000
    sp = f.add_subplot(3, 3, 7)
    sp.plot(weatherObj._p[yind, xind, :] / 1e2, zdata)
    sp.set_ylabel('Height (km)')
    sp.set_xlabel('Pressure (hPa)')

    sp = f.add_subplot(3, 3, 8)
    sp.plot(weatherObj._e[yind, xind, :] / 100, zdata)
    sp.set_xlabel('E (hPa)')

    sp = f.add_subplot(3, 3, 9)
    sp.plot(weatherObj._t[yind, xind, :] - 273.15, zdata)
    sp.set_xlabel('Temp (C)')

    plt.subplots_adjust(top=0.95, bottom=0.1, left=0.1, right=0.95, hspace=0.2,
                        wspace=0.3)

    if savefig:
        wd   = os.path.dirname(os.path.dirname(weatherObj._out_name))
        f    = f'{weatherObj._Name}_weather_hgt{z1}_and_{z2}m.pdf'
        plt.savefig(os.path.join(wd, f))
    return f


def plot_wh(weatherObj, savefig=True, z1=500, z2=15000):
    '''
    Create a plot with wet refractivity and hydrostatic refractivity,
    at two different heights
    '''

    # Get the interpolator
    intFcn_w = Interpolator((weatherObj._xs, weatherObj._ys, weatherObj._zs), weatherObj._wet_refractivity.swapaxes(0, 1))
    intFcn_h = Interpolator((weatherObj._xs, weatherObj._ys, weatherObj._zs), weatherObj._hydrostatic_refractivity.swapaxes(0, 1))

    # get the points needed
    XY = np.meshgrid(weatherObj._xs, weatherObj._ys)
    x = XY[0]
    y = XY[1]
    z1a = np.zeros(x.shape) + z1
    z2a = np.zeros(x.shape) + z2
    pts1 = np.stack((x.flatten(), y.flatten(), z1a.flatten()), axis=1)
    pts2 = np.stack((x.flatten(), y.flatten(), z2a.flatten()), axis=1)

    w1 = intFcn_w(pts1)
    h1 = intFcn_h(pts1)
    w2 = intFcn_w(pts2)
    h2 = intFcn_h(pts2)

    # Now get the data to plot
    plots = [w1, h1, w2, h2]

    # titles
    titles = ('Wet refractivity {}'.format(z1),
              'Hydrostatic refractivity {}'.format(z1),
              '{}'.format(z2),
              '{}'.format(z2))

    # setup the plot
    f = plt.figure(figsize=(14, 10))
    f.suptitle(f'{weatherObj._Name} Wet and Hydrostatic refractivity at height {z1}m and {z2}m')

    # loop over each plot
    for ind, plot, title in zip(range(len(plots)), plots, titles):
        sp = f.add_subplot(2, 2, ind + 1)
        im = sp.imshow(np.reshape(plot, x.shape), cmap='viridis',
                       extent=[np.nanmin(x), np.nanmax(x), np.nanmin(y), np.nanmax(y)], origin='lower')
        divider = mal(sp)
        cax = divider.append_axes("right", size="4%", pad=0.05)
        plt.colorbar(im, cax=cax)
        sp.set_title(title)
        if ind == 0:
            sp.set_ylabel('{} m\n'.format(z1))
        if ind == 2:
            sp.set_ylabel('{} m\n'.format(z2))

    if savefig:
        wd   = os.path.dirname(os.path.dirname(weatherObj._out_name))
        f    = f'{weatherObj._Name}_refractivity_hgt{z1}_and_{z2}m.pdf'
        plt.savefig(os.path.join(wd, f))
    return f

1	"""
2	This set of functions is designed to for plotting WeatherModel
3	class objects. It is not designed to be used on its own apart
4	from this class.
5	"""
6
7	import os	1✔
8	from RAiDER.interpolator import RegularGridInterpolator as Interpolator	1✔
9	from mpl_toolkits.axes_grid1 import make_axes_locatable as mal	1✔
10	import numpy as np	1✔
11	import matplotlib.pyplot as plt	1✔
12	import matplotlib as mpl	1✔
13	mpl.use('Agg')	1✔
14
15
16	def plot_pqt(weatherObj, savefig=True, z1=500, z2=15000):	1✔
17	'''
18	Create a plot with pressure, temp, and humidity at two heights
19	'''
20
21	# Get the interpolator
22
23	intFcn_p = Interpolator((weatherObj._xs, weatherObj._ys, weatherObj._zs), weatherObj._p.swapaxes(0, 1))	×
24	intFcn_e = Interpolator((weatherObj._xs, weatherObj._ys, weatherObj._zs), weatherObj._e.swapaxes(0, 1))	×
25	intFcn_t = Interpolator((weatherObj._xs, weatherObj._ys, weatherObj._zs), weatherObj._t.swapaxes(0, 1))	×
26
27	# get the points needed
28	XY = np.meshgrid(weatherObj._xs, weatherObj._ys)	×
29	x = XY[0]	×
30	y = XY[1]	×
31	z1a = np.zeros(x.shape) + z1	×
32	z2a = np.zeros(x.shape) + z2	×
33	pts1 = np.stack((x.flatten(), y.flatten(), z1a.flatten()), axis=1)	×
34	pts2 = np.stack((x.flatten(), y.flatten(), z2a.flatten()), axis=1)	×
35
36	p1 = intFcn_p(pts1)	×
37	e1 = intFcn_e(pts1)	×
38	t1 = intFcn_t(pts1)	×
39	p2 = intFcn_p(pts2)	×
40	e2 = intFcn_e(pts2)	×
41	t2 = intFcn_t(pts2)	×
42
43	# Now get the data to plot
44	plots = [p1 / 1e2, e1 / 1e2, t1 - 273.15, p2 / 1e2, e2 / 1e2, t2 - 273.15]	×
45	# titles = ('P (hPa)', 'E (hPa)'.format(z1), 'T (C)', '', '', '')
46	titles = ('P (hPa)', 'E (hPa)', 'T (C)', '', '', '')	×
47
48	# setup the plot
49	f = plt.figure(figsize=(18, 14))	×
50	f.suptitle(f'{weatherObj._Name} Pressure/Humidity/Temperature at height {z1}m and {z2}m (values should drop as elevation increases)')	×
51
52	xind = int(np.floor(weatherObj._xs.shape[0] / 2))	×
53	yind = int(np.floor(weatherObj._ys.shape[0] / 2))	×
54
55	# loop over each plot
56	for ind, plot, title in zip(range(len(plots)), plots, titles):	×
57	sp = f.add_subplot(3, 3, ind + 1)	×
58	im = sp.imshow(np.reshape(plot, x.shape),	×
59	cmap='viridis',
60	extent=[np.nanmin(x), np.nanmax(x), np.nanmin(y), np.nanmax(y)],
61	origin='lower')
62	sp.plot(x[yind, xind], y[yind, xind], 'ko')	×
63	divider = mal(sp)	×
64	cax = divider.append_axes("right", size="4%", pad=0.05)	×
65	plt.colorbar(im, cax=cax)	×
66	sp.set_title(title)	×
67	if ind == 0:	×
68	sp.set_ylabel('{} m\n'.format(z1))	×
69	if ind == 3:	×
70	sp.set_ylabel('{} m\n'.format(z2))	×
71
72	# add plots that show each variable with height
73	zdata = weatherObj._zs[:] / 1000	×
74	sp = f.add_subplot(3, 3, 7)	×
75	sp.plot(weatherObj._p[yind, xind, :] / 1e2, zdata)	×
76	sp.set_ylabel('Height (km)')	×
77	sp.set_xlabel('Pressure (hPa)')	×
78
79	sp = f.add_subplot(3, 3, 8)	×
80	sp.plot(weatherObj._e[yind, xind, :] / 100, zdata)	×
81	sp.set_xlabel('E (hPa)')	×
82
83	sp = f.add_subplot(3, 3, 9)	×
84	sp.plot(weatherObj._t[yind, xind, :] - 273.15, zdata)	×
85	sp.set_xlabel('Temp (C)')	×
86
87	plt.subplots_adjust(top=0.95, bottom=0.1, left=0.1, right=0.95, hspace=0.2,	×
88	wspace=0.3)
89
90	if savefig:	×
91	wd = os.path.dirname(os.path.dirname(weatherObj._out_name))	×
92	f = f'{weatherObj._Name}_weather_hgt{z1}_and_{z2}m.pdf'	×
93	plt.savefig(os.path.join(wd, f))	×
94	return f	×
95
96
97	def plot_wh(weatherObj, savefig=True, z1=500, z2=15000):	1✔
98	'''
99	Create a plot with wet refractivity and hydrostatic refractivity,
100	at two different heights
101	'''
102
103	# Get the interpolator
104	intFcn_w = Interpolator((weatherObj._xs, weatherObj._ys, weatherObj._zs), weatherObj._wet_refractivity.swapaxes(0, 1))	×
105	intFcn_h = Interpolator((weatherObj._xs, weatherObj._ys, weatherObj._zs), weatherObj._hydrostatic_refractivity.swapaxes(0, 1))	×
106
107	# get the points needed
108	XY = np.meshgrid(weatherObj._xs, weatherObj._ys)	×
109	x = XY[0]	×
110	y = XY[1]	×
111	z1a = np.zeros(x.shape) + z1	×
112	z2a = np.zeros(x.shape) + z2	×
113	pts1 = np.stack((x.flatten(), y.flatten(), z1a.flatten()), axis=1)	×
114	pts2 = np.stack((x.flatten(), y.flatten(), z2a.flatten()), axis=1)	×
115
116	w1 = intFcn_w(pts1)	×
117	h1 = intFcn_h(pts1)	×
118	w2 = intFcn_w(pts2)	×
119	h2 = intFcn_h(pts2)	×
120
121	# Now get the data to plot
122	plots = [w1, h1, w2, h2]	×
123
124	# titles
125	titles = ('Wet refractivity {}'.format(z1),	×
126	'Hydrostatic refractivity {}'.format(z1),
127	'{}'.format(z2),
128	'{}'.format(z2))
129
130	# setup the plot
131	f = plt.figure(figsize=(14, 10))	×
132	f.suptitle(f'{weatherObj._Name} Wet and Hydrostatic refractivity at height {z1}m and {z2}m')	×
133
134	# loop over each plot
135	for ind, plot, title in zip(range(len(plots)), plots, titles):	×
136	sp = f.add_subplot(2, 2, ind + 1)	×
137	im = sp.imshow(np.reshape(plot, x.shape), cmap='viridis',	×
138	extent=[np.nanmin(x), np.nanmax(x), np.nanmin(y), np.nanmax(y)], origin='lower')
139	divider = mal(sp)	×
140	cax = divider.append_axes("right", size="4%", pad=0.05)	×
141	plt.colorbar(im, cax=cax)	×
142	sp.set_title(title)	×
143	if ind == 0:	×
144	sp.set_ylabel('{} m\n'.format(z1))	×
145	if ind == 2:	×
146	sp.set_ylabel('{} m\n'.format(z2))	×
147
148	if savefig:	×
149	wd = os.path.dirname(os.path.dirname(weatherObj._out_name))	×
150	f = f'{weatherObj._Name}_refractivity_hgt{z1}_and_{z2}m.pdf'	×
151	plt.savefig(os.path.join(wd, f))	×
152	return f	×

dbekaert / RAiDER / 1a16f90b-a2b4-48e1-87b0-09ef1ba1bd9c

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