test_hodograph_plot_layers_different_units() - Code Metrics - Inspection of "Hodograph coloring units" - Unidata/MetPy - Measure and Improve Code Quality continuously with Scrutinizer

Completed

Pull Request — master (#572)

unknown

created 2017-10-19 17:03 UTC

test_hodograph_plot_layers_different_units() A

↳ Parent: Project

Complexity

Conditions

Size

Total Lines

Duplication

Lines	16
Ratio	100 %

Importance

Changes	2
Bugs	0	Features	0

Metric	Value
cc	1
c	2
b	0
f	0
dl	16
loc	16
rs	9.4285

# Copyright (c) 2015,2016,2017 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)
    skew.ax.set_xlim(-50, 50)
    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)
    skew.ax.set_xlim(-50, 50)
    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')
    skew.ax.set_xlim(-50, 50)
    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')
    ax.set_xlabel('')
    ax.set_ylabel('')
    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.zeros((6)) * units.knots
    v = np.array([0, 10, 20, 30, 40, 50]) * units.knots
    heights = np.array([0, 1000, 2000, 3000, 4000, 5000]) * units.m
    bounds = np.array([500, 1500, 2500, 3500, 4500]) * units.m
    colors = ['r', 'g', 'b', 'r']
    fig = plt.figure(figsize=(7, 7))
    ax1 = fig.add_subplot(1, 1, 1)
    h = Hodograph(ax1)
    h.add_grid(increment=10)
    h.plot_colormapped(u, v, heights, colors=colors, bounds=bounds)
    ax1.set_xlim(-50, 50)
    ax1.set_ylim(-5, 50)

    return fig


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

def test_hodograph_plot_layers_different_units():
    """Test hodograph colored height layers with interpolation and different units."""
    u = np.zeros((6)) * units.knots
    v = np.array([0, 10, 20, 30, 40, 50]) * units.knots
    heights = np.array([0, 1, 2, 3, 4, 5]) * units.km
    bounds = np.array([500, 1500, 2500, 3500, 4500]) * units.m
    colors = ['r', 'g', 'b', 'r']
    fig = plt.figure(figsize=(7, 7))
    ax1 = fig.add_subplot(1, 1, 1)
    h = Hodograph(ax1)
    h.add_grid(increment=10)
    h.plot_colormapped(u, v, heights, colors=colors, bounds=bounds)
    ax1.set_xlim(-50, 50)
    ax1.set_ylim(-5, 50)
    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) 2015,2016,2017 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	View Code Duplication	@pytest.mark.mpl_image_compare(tolerance={'1.4': 1.71}.get(MPL_VERSION, 0.), remove_text=True)
		0 ignored issues – show Duplication introduced 2017-09-13 15:36 UTC by Report Bug Copy Issue Report This code seems to be duplicated in your project. Loading history...
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		skew.ax.set_xlim(-50, 50)
83		return fig
84
85
86	View Code Duplication	@pytest.mark.mpl_image_compare(tolerance={'1.4': 1.70}.get(MPL_VERSION, 0.), remove_text=True)
		0 ignored issues – show Duplication introduced 2017-09-14 01:54 UTC by Report Bug Copy Issue Report This code seems to be duplicated in your project. Loading history...
87		def test_skewt_shade_area(test_profile):
88		"""Test shading areas on a SkewT plot."""
89		p, t, tp = test_profile
90		fig = plt.figure(figsize=(9, 9))
91		skew = SkewT(fig)
92		skew.plot(p, t, 'r')
93		skew.plot(p, tp, 'k')
94		skew.shade_area(p, t, tp)
95		skew.ax.set_xlim(-50, 50)
96		return fig
97
98
99		def test_skewt_shade_area_invalid(test_profile):
100		"""Test shading areas on a SkewT plot."""
101		p, t, tp = test_profile
102		fig = plt.figure(figsize=(9, 9))
103		skew = SkewT(fig)
104		skew.plot(p, t, 'r')
105		skew.plot(p, tp, 'k')
106		with pytest.raises(ValueError):
107		skew.shade_area(p, t, tp, which='positve')
108
109
110	View Code Duplication	@pytest.mark.mpl_image_compare(tolerance={'1.4': 1.75}.get(MPL_VERSION, 0.), remove_text=True)
		0 ignored issues – show Duplication introduced 2017-09-13 15:36 UTC by Report Bug Copy Issue Report This code seems to be duplicated in your project. Loading history...
111		def test_skewt_shade_area_kwargs(test_profile):
112		"""Test shading areas on a SkewT plot with kwargs."""
113		p, t, tp = test_profile
114		fig = plt.figure(figsize=(9, 9))
115		skew = SkewT(fig)
116		skew.plot(p, t, 'r')
117		skew.plot(p, tp, 'k')
118		skew.shade_area(p, t, tp, facecolor='m')
119		skew.ax.set_xlim(-50, 50)
120		return fig
121
122
123		@pytest.mark.mpl_image_compare(tolerance=0, remove_text=True)
124		def test_hodograph_api():
125		"""Basic test of Hodograph API."""
126		fig = plt.figure(figsize=(9, 9))
127		ax = fig.add_subplot(1, 1, 1)
128		hodo = Hodograph(ax, component_range=60)
129		hodo.add_grid(increment=5, color='k')
130		hodo.plot([1, 10], [1, 10], color='red')
131		hodo.plot_colormapped(np.array([1, 3, 5, 10]), np.array([2, 4, 6, 11]),
132		np.array([0.1, 0.3, 0.5, 0.9]), cmap='Greys')
133		return fig
134
135
136		@pytest.mark.mpl_image_compare(tolerance=0, remove_text=True)
137		def test_hodograph_units():
138		"""Test passing unit-ed quantities to Hodograph."""
139		fig = plt.figure(figsize=(9, 9))
140		ax = fig.add_subplot(1, 1, 1)
141		hodo = Hodograph(ax)
142		u = np.arange(10) * units.kt
143		v = np.arange(10) * units.kt
144		hodo.plot(u, v)
145		hodo.plot_colormapped(u, v, np.sqrt(u * u + v * v), cmap='Greys')
146		ax.set_xlabel('')
147		ax.set_ylabel('')
148		return fig
149
150
151		def test_hodograph_alone():
152		"""Test to create Hodograph without specifying axes."""
153		Hodograph()
154
155
156		@pytest.mark.mpl_image_compare(tolerance=0, remove_text=True)
157		def test_hodograph_plot_colormapped():
158		"""Test hodograph colored line with NaN values."""
159		u = np.arange(5., 65., 5)
160		v = np.arange(-5., -65., -5)
161		u[3] = np.nan
162		v[6] = np.nan
163		fig = plt.figure(figsize=(9, 9))
164		ax = fig.add_subplot(1, 1, 1)
165		hodo = Hodograph(ax, component_range=80)
166		hodo.add_grid(increment=20, color='k')
167		hodo.plot_colormapped(u, v, np.hypot(u, v), cmap='Greys')
168
169		return fig
170
171
172		@pytest.mark.mpl_image_compare(tolerance=0.021, remove_text=True)
173		def test_skewt_barb_color():
174		"""Test plotting colored wind barbs on the Skew-T."""
175		fig = plt.figure(figsize=(9, 9))
176		skew = SkewT(fig)
177
178		p = np.linspace(1000, 100, 10)
179		u = np.linspace(-10, 10, 10)
180		skew.plot_barbs(p, u, u, c=u)
181
182		return fig
183
184
185	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...
186		def test_hodograph_plot_layers():
187		"""Test hodograph colored height layers with interpolation."""
188		u = np.zeros((6)) * units.knots
189		v = np.array([0, 10, 20, 30, 40, 50]) * units.knots
190		heights = np.array([0, 1000, 2000, 3000, 4000, 5000]) * units.m
191		bounds = np.array([500, 1500, 2500, 3500, 4500]) * units.m
192		colors = ['r', 'g', 'b', 'r']
193		fig = plt.figure(figsize=(7, 7))
194		ax1 = fig.add_subplot(1, 1, 1)
195		h = Hodograph(ax1)
196		h.add_grid(increment=10)
197		h.plot_colormapped(u, v, heights, colors=colors, bounds=bounds)
198		ax1.set_xlim(-50, 50)
199		ax1.set_ylim(-5, 50)
200
201		return fig
202
203
204	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...
205		def test_hodograph_plot_layers_different_units():
206		"""Test hodograph colored height layers with interpolation and different units."""
207		u = np.zeros((6)) * units.knots
208		v = np.array([0, 10, 20, 30, 40, 50]) * units.knots
209		heights = np.array([0, 1, 2, 3, 4, 5]) * units.km
210		bounds = np.array([500, 1500, 2500, 3500, 4500]) * units.m
211		colors = ['r', 'g', 'b', 'r']
212		fig = plt.figure(figsize=(7, 7))
213		ax1 = fig.add_subplot(1, 1, 1)
214		h = Hodograph(ax1)
215		h.add_grid(increment=10)
216		h.plot_colormapped(u, v, heights, colors=colors, bounds=bounds)
217		ax1.set_xlim(-50, 50)
218		ax1.set_ylim(-5, 50)
219		return fig
220
221
222		@pytest.mark.mpl_image_compare(tolerance=0, remove_text=True)
223		def test_hodograph_plot_arbitrary_layer():
224		"""Test hodograph colored layers for arbitrary variables without interpolation."""
225		u = np.arange(5, 65, 5) * units('knot')
226		v = np.arange(-5, -65, -5) * units('knot')
227		speed = np.sqrt(u 2 + v 2)
228		colors = ['red', 'green', 'blue']
229		levels = [0, 10, 20, 30] * units('knot')
230		fig = plt.figure(figsize=(9, 9))
231		ax = fig.add_subplot(1, 1, 1)
232		hodo = Hodograph(ax, component_range=80)
233		hodo.add_grid(increment=20, color='k')
234		hodo.plot_colormapped(u, v, speed, bounds=levels, colors=colors)
235
236		return fig
237

Unidata / MetPy

Pull Request — master (#572)

test_hodograph_plot_layers_different_units() A

Complexity

Size

Duplication

Importance

Duplication Side-by-Side

Filter issues like