test_hodograph_plot_arbitrary_layer() - Code Metrics - Inspection of "Merge pull request #482 from mwilson14/hodograph_c..." - Unidata/MetPy - Measure and Improve Code Quality continuously with Scrutinizer

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test_hodograph_plot_arbitrary_layer() A

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cc	1
dl	15
loc	15
rs	9.4285
c	2
b	0
f	0

# Copyright (c) 2008-2015 MetPy Developers.
# Distributed under the terms of the BSD 3-Clause License.
# SPDX-License-Identifier: BSD-3-Clause
"""Tests for the `skewt` module."""

import matplotlib
from matplotlib.gridspec import GridSpec
import matplotlib.pyplot as plt
import numpy as np
import pytest

from metpy.plots import Hodograph, SkewT
# Fixtures to make sure we have the right backend and consistent round
from metpy.testing import patch_round, set_agg_backend  # noqa: F401
from metpy.units import units

MPL_VERSION = matplotlib.__version__[:3]


@pytest.mark.mpl_image_compare(tolerance=0.021, remove_text=True)
def test_skewt_api():
    """Test the SkewT API."""
    fig = plt.figure(figsize=(9, 9))
    skew = SkewT(fig)

    # Plot the data using normal plotting functions, in this case using
    # log scaling in Y, as dictated by the typical meteorological plot
    p = np.linspace(1000, 100, 10)
    t = np.linspace(20, -20, 10)
    u = np.linspace(-10, 10, 10)
    skew.plot(p, t, 'r')
    skew.plot_barbs(p, u, u)

    # Add the relevant special lines
    skew.plot_dry_adiabats()
    skew.plot_moist_adiabats()
    skew.plot_mixing_lines()

    return fig


@pytest.mark.mpl_image_compare(tolerance=0, remove_text=True)
def test_skewt_subplot():
    """Test using SkewT on a sub-plot."""
    fig = plt.figure(figsize=(9, 9))
    SkewT(fig, subplot=(2, 2, 1))
    return fig


@pytest.mark.mpl_image_compare(tolerance=0, remove_text=True)
def test_skewt_gridspec():
    """Test using SkewT on a sub-plot."""
    fig = plt.figure(figsize=(9, 9))
    gs = GridSpec(1, 2)
    SkewT(fig, subplot=gs[0, 1])
    return fig


def test_skewt_with_grid_enabled():
    """Test using SkewT when gridlines are already enabled (#271)."""
    with plt.rc_context(rc={'axes.grid': True}):
        # Also tests when we don't pass in Figure
        SkewT()


@pytest.fixture()
def test_profile():
    """Return data for a test profile."""
    return np.linspace(1000, 100, 10), np.linspace(20, -20, 10), np.linspace(25, -30, 10)


@pytest.mark.mpl_image_compare(tolerance={'1.4': 1.71}.get(MPL_VERSION, 0.), remove_text=True)
def test_skewt_shade_cape_cin(test_profile):
    """Test shading CAPE and CIN on a SkewT plot."""
    p, t, tp = test_profile
    fig = plt.figure(figsize=(9, 9))
    skew = SkewT(fig)
    skew.plot(p, t, 'r')
    skew.plot(p, tp, 'k')
    skew.shade_cape(p, t, tp)
    skew.shade_cin(p, t, tp)
    return fig


@pytest.mark.mpl_image_compare(tolerance={'1.4': 1.70}.get(MPL_VERSION, 0.), remove_text=True)
def test_skewt_shade_area(test_profile):
    """Test shading areas on a SkewT plot."""
    p, t, tp = test_profile
    fig = plt.figure(figsize=(9, 9))
    skew = SkewT(fig)
    skew.plot(p, t, 'r')
    skew.plot(p, tp, 'k')
    skew.shade_area(p, t, tp)
    return fig


def test_skewt_shade_area_invalid(test_profile):
    """Test shading areas on a SkewT plot."""
    p, t, tp = test_profile
    fig = plt.figure(figsize=(9, 9))
    skew = SkewT(fig)
    skew.plot(p, t, 'r')
    skew.plot(p, tp, 'k')
    with pytest.raises(ValueError):
        skew.shade_area(p, t, tp, which='positve')


@pytest.mark.mpl_image_compare(tolerance={'1.4': 1.75}.get(MPL_VERSION, 0.), remove_text=True)
def test_skewt_shade_area_kwargs(test_profile):
    """Test shading areas on a SkewT plot with kwargs."""
    p, t, tp = test_profile
    fig = plt.figure(figsize=(9, 9))
    skew = SkewT(fig)
    skew.plot(p, t, 'r')
    skew.plot(p, tp, 'k')
    skew.shade_area(p, t, tp, facecolor='m')
    return fig


@pytest.mark.mpl_image_compare(tolerance=0, remove_text=True)
def test_hodograph_api():
    """Basic test of Hodograph API."""
    fig = plt.figure(figsize=(9, 9))
    ax = fig.add_subplot(1, 1, 1)
    hodo = Hodograph(ax, component_range=60)
    hodo.add_grid(increment=5, color='k')
    hodo.plot([1, 10], [1, 10], color='red')
    hodo.plot_colormapped(np.array([1, 3, 5, 10]), np.array([2, 4, 6, 11]),
                          np.array([0.1, 0.3, 0.5, 0.9]), cmap='Greys')
    return fig


@pytest.mark.mpl_image_compare(tolerance=0, remove_text=True)
def test_hodograph_units():
    """Test passing unit-ed quantities to Hodograph."""
    fig = plt.figure(figsize=(9, 9))
    ax = fig.add_subplot(1, 1, 1)
    hodo = Hodograph(ax)
    u = np.arange(10) * units.kt
    v = np.arange(10) * units.kt
    hodo.plot(u, v)
    hodo.plot_colormapped(u, v, np.sqrt(u * u + v * v), cmap='Greys')
    return fig


def test_hodograph_alone():
    """Test to create Hodograph without specifying axes."""
    Hodograph()


@pytest.mark.mpl_image_compare(tolerance=0, remove_text=True)
def test_hodograph_plot_colormapped():
    """Test hodograph colored line with NaN values."""
    u = np.arange(5., 65., 5)
    v = np.arange(-5., -65., -5)
    u[3] = np.nan
    v[6] = np.nan
    fig = plt.figure(figsize=(9, 9))
    ax = fig.add_subplot(1, 1, 1)
    hodo = Hodograph(ax, component_range=80)
    hodo.add_grid(increment=20, color='k')
    hodo.plot_colormapped(u, v, np.hypot(u, v), cmap='Greys')

    return fig


@pytest.mark.mpl_image_compare(tolerance=0.021, remove_text=True)
def test_skewt_barb_color():
    """Test plotting colored wind barbs on the Skew-T."""
    fig = plt.figure(figsize=(9, 9))
    skew = SkewT(fig)

    p = np.linspace(1000, 100, 10)
    u = np.linspace(-10, 10, 10)
    skew.plot_barbs(p, u, u, c=u)

    return fig


@pytest.mark.mpl_image_compare(tolerance=0, remove_text=True)

def test_hodograph_plot_layers():
    """Test hodograph colored height layers with interpolation."""
    u = np.arange(5, 65, 5) * units('knot')
    v = np.arange(-5, -65, -5) * units('knot')
    h = [178, 213, 610, 656, 721, 914, 1060,
         1219, 1372, 1412, 1512, 1524] * units('meter')
    colors = ['red', 'green']
    levels = [0, 500, 1000] * units('meter')
    fig = plt.figure(figsize=(9, 9))
    ax = fig.add_subplot(1, 1, 1)
    hodo = Hodograph(ax, component_range=80)
    hodo.add_grid(increment=20, color='k')
    hodo.plot_colormapped(u, v, h, bounds=levels, colors=colors)

    return fig


@pytest.mark.mpl_image_compare(tolerance=0, remove_text=True)

def test_hodograph_plot_arbitrary_layer():
    """Test hodograph colored layers for arbitrary variables without interpolation."""
    u = np.arange(5, 65, 5) * units('knot')
    v = np.arange(-5, -65, -5) * units('knot')
    speed = np.sqrt(u ** 2 + v ** 2)
    colors = ['red', 'green', 'blue']
    levels = [0, 10, 20, 30] * units('knot')
    fig = plt.figure(figsize=(9, 9))
    ax = fig.add_subplot(1, 1, 1)
    hodo = Hodograph(ax, component_range=80)
    hodo.add_grid(increment=20, color='k')
    hodo.plot_colormapped(u, v, speed, bounds=levels, colors=colors)

    return fig


1		# Copyright (c) 2008-2015 MetPy Developers.
2		# Distributed under the terms of the BSD 3-Clause License.
3		# SPDX-License-Identifier: BSD-3-Clause
4		"""Tests for the `skewt` module."""
5
6		import matplotlib
7		from matplotlib.gridspec import GridSpec
8		import matplotlib.pyplot as plt
9		import numpy as np
10		import pytest
11
12		from metpy.plots import Hodograph, SkewT
13		# Fixtures to make sure we have the right backend and consistent round
14		from metpy.testing import patch_round, set_agg_backend # noqa: F401
15		from metpy.units import units
16
17		MPL_VERSION = matplotlib.__version__[:3]
18
19
20		@pytest.mark.mpl_image_compare(tolerance=0.021, remove_text=True)
21		def test_skewt_api():
22		"""Test the SkewT API."""
23		fig = plt.figure(figsize=(9, 9))
24		skew = SkewT(fig)
25
26		# Plot the data using normal plotting functions, in this case using
27		# log scaling in Y, as dictated by the typical meteorological plot
28		p = np.linspace(1000, 100, 10)
29		t = np.linspace(20, -20, 10)
30		u = np.linspace(-10, 10, 10)
31		skew.plot(p, t, 'r')
32		skew.plot_barbs(p, u, u)
33
34		# Add the relevant special lines
35		skew.plot_dry_adiabats()
36		skew.plot_moist_adiabats()
37		skew.plot_mixing_lines()
38
39		return fig
40
41
42		@pytest.mark.mpl_image_compare(tolerance=0, remove_text=True)
43		def test_skewt_subplot():
44		"""Test using SkewT on a sub-plot."""
45		fig = plt.figure(figsize=(9, 9))
46		SkewT(fig, subplot=(2, 2, 1))
47		return fig
48
49
50		@pytest.mark.mpl_image_compare(tolerance=0, remove_text=True)
51		def test_skewt_gridspec():
52		"""Test using SkewT on a sub-plot."""
53		fig = plt.figure(figsize=(9, 9))
54		gs = GridSpec(1, 2)
55		SkewT(fig, subplot=gs[0, 1])
56		return fig
57
58
59		def test_skewt_with_grid_enabled():
60		"""Test using SkewT when gridlines are already enabled (#271)."""
61		with plt.rc_context(rc={'axes.grid': True}):
62		# Also tests when we don't pass in Figure
63		SkewT()
64
65
66		@pytest.fixture()
67		def test_profile():
68		"""Return data for a test profile."""
69		return np.linspace(1000, 100, 10), np.linspace(20, -20, 10), np.linspace(25, -30, 10)
70
71
72		@pytest.mark.mpl_image_compare(tolerance={'1.4': 1.71}.get(MPL_VERSION, 0.), remove_text=True)
73		def test_skewt_shade_cape_cin(test_profile):
74		"""Test shading CAPE and CIN on a SkewT plot."""
75		p, t, tp = test_profile
76		fig = plt.figure(figsize=(9, 9))
77		skew = SkewT(fig)
78		skew.plot(p, t, 'r')
79		skew.plot(p, tp, 'k')
80		skew.shade_cape(p, t, tp)
81		skew.shade_cin(p, t, tp)
82		return fig
83
84
85		@pytest.mark.mpl_image_compare(tolerance={'1.4': 1.70}.get(MPL_VERSION, 0.), remove_text=True)
86		def test_skewt_shade_area(test_profile):
87		"""Test shading areas on a SkewT plot."""
88		p, t, tp = test_profile
89		fig = plt.figure(figsize=(9, 9))
90		skew = SkewT(fig)
91		skew.plot(p, t, 'r')
92		skew.plot(p, tp, 'k')
93		skew.shade_area(p, t, tp)
94		return fig
95
96
97		def test_skewt_shade_area_invalid(test_profile):
98		"""Test shading areas on a SkewT plot."""
99		p, t, tp = test_profile
100		fig = plt.figure(figsize=(9, 9))
101		skew = SkewT(fig)
102		skew.plot(p, t, 'r')
103		skew.plot(p, tp, 'k')
104		with pytest.raises(ValueError):
105		skew.shade_area(p, t, tp, which='positve')
106
107
108		@pytest.mark.mpl_image_compare(tolerance={'1.4': 1.75}.get(MPL_VERSION, 0.), remove_text=True)
109		def test_skewt_shade_area_kwargs(test_profile):
110		"""Test shading areas on a SkewT plot with kwargs."""
111		p, t, tp = test_profile
112		fig = plt.figure(figsize=(9, 9))
113		skew = SkewT(fig)
114		skew.plot(p, t, 'r')
115		skew.plot(p, tp, 'k')
116		skew.shade_area(p, t, tp, facecolor='m')
117		return fig
118
119
120		@pytest.mark.mpl_image_compare(tolerance=0, remove_text=True)
121		def test_hodograph_api():
122		"""Basic test of Hodograph API."""
123		fig = plt.figure(figsize=(9, 9))
124		ax = fig.add_subplot(1, 1, 1)
125		hodo = Hodograph(ax, component_range=60)
126		hodo.add_grid(increment=5, color='k')
127		hodo.plot([1, 10], [1, 10], color='red')
128		hodo.plot_colormapped(np.array([1, 3, 5, 10]), np.array([2, 4, 6, 11]),
129		np.array([0.1, 0.3, 0.5, 0.9]), cmap='Greys')
130		return fig
131
132
133		@pytest.mark.mpl_image_compare(tolerance=0, remove_text=True)
134		def test_hodograph_units():
135		"""Test passing unit-ed quantities to Hodograph."""
136		fig = plt.figure(figsize=(9, 9))
137		ax = fig.add_subplot(1, 1, 1)
138		hodo = Hodograph(ax)
139		u = np.arange(10) * units.kt
140		v = np.arange(10) * units.kt
141		hodo.plot(u, v)
142		hodo.plot_colormapped(u, v, np.sqrt(u * u + v * v), cmap='Greys')
143		return fig
144
145
146		def test_hodograph_alone():
147		"""Test to create Hodograph without specifying axes."""
148		Hodograph()
149
150
151		@pytest.mark.mpl_image_compare(tolerance=0, remove_text=True)
152		def test_hodograph_plot_colormapped():
153		"""Test hodograph colored line with NaN values."""
154		u = np.arange(5., 65., 5)
155		v = np.arange(-5., -65., -5)
156		u[3] = np.nan
157		v[6] = np.nan
158		fig = plt.figure(figsize=(9, 9))
159		ax = fig.add_subplot(1, 1, 1)
160		hodo = Hodograph(ax, component_range=80)
161		hodo.add_grid(increment=20, color='k')
162		hodo.plot_colormapped(u, v, np.hypot(u, v), cmap='Greys')
163
164		return fig
165
166
167		@pytest.mark.mpl_image_compare(tolerance=0.021, remove_text=True)
168		def test_skewt_barb_color():
169		"""Test plotting colored wind barbs on the Skew-T."""
170		fig = plt.figure(figsize=(9, 9))
171		skew = SkewT(fig)
172
173		p = np.linspace(1000, 100, 10)
174		u = np.linspace(-10, 10, 10)
175		skew.plot_barbs(p, u, u, c=u)
176
177		return fig
178
179
180	View Code Duplication	@pytest.mark.mpl_image_compare(tolerance=0, remove_text=True)
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181		def test_hodograph_plot_layers():
182		"""Test hodograph colored height layers with interpolation."""
183		u = np.arange(5, 65, 5) * units('knot')
184		v = np.arange(-5, -65, -5) * units('knot')
185		h = [178, 213, 610, 656, 721, 914, 1060,
186		1219, 1372, 1412, 1512, 1524] * units('meter')
187		colors = ['red', 'green']
188		levels = [0, 500, 1000] * units('meter')
189		fig = plt.figure(figsize=(9, 9))
190		ax = fig.add_subplot(1, 1, 1)
191		hodo = Hodograph(ax, component_range=80)
192		hodo.add_grid(increment=20, color='k')
193		hodo.plot_colormapped(u, v, h, bounds=levels, colors=colors)
194
195		return fig
196
197
198	View Code Duplication	@pytest.mark.mpl_image_compare(tolerance=0, remove_text=True)
		0 ignored issues – show Duplication introduced 2017-04-03 17:12 UTC by Report Bug Copy Issue Report This code seems to be duplicated in your project. Loading history...
199		def test_hodograph_plot_arbitrary_layer():
200		"""Test hodograph colored layers for arbitrary variables without interpolation."""
201		u = np.arange(5, 65, 5) * units('knot')
202		v = np.arange(-5, -65, -5) * units('knot')
203		speed = np.sqrt(u 2 + v 2)
204		colors = ['red', 'green', 'blue']
205		levels = [0, 10, 20, 30] * units('knot')
206		fig = plt.figure(figsize=(9, 9))
207		ax = fig.add_subplot(1, 1, 1)
208		hodo = Hodograph(ax, component_range=80)
209		hodo.add_grid(increment=20, color='k')
210		hodo.plot_colormapped(u, v, speed, bounds=levels, colors=colors)
211
212		return fig
213

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test_hodograph_plot_arbitrary_layer() A

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