pert_zero_mean() - Code Metrics - Inspection of "Docstring checking" - Unidata/MetPy - Measure and Improve Code Quality continuously with Scrutinizer

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by Ryan

created 2016-11-28 06:27 UTC

pert_zero_mean() A

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# 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 `turbulence` module."""

import numpy as np
from numpy.testing import assert_almost_equal, assert_array_equal
import pytest

from metpy.calc.turbulence import friction_velocity, get_perturbation, kinematic_flux, tke


#
# TKE Tests
#
@pytest.fixture()
def uvw_and_known_tke():
    """Provide a set of u,v,w with a known tke value."""
    u = np.array([-2, -1, 0, 1, 2])
    v = -u
    w = 2 * u
    #  0.5 * sqrt(2 + 2 + 8)
    e_true = np.sqrt(12) / 2.
    return u, v, w, e_true


def test_no_tke_1d():
    """Test tke calculation where the expected value is 0."""
    observations = 5
    # given all the values are the same, there should not be any tke
    u = np.ones(observations)
    v = np.ones(observations)
    w = np.ones(observations)
    e_zero = 0
    assert_array_equal(e_zero, tke(u, v, w))


def test_no_tke_2d_axis_last():
    """Test 0 tke calculation with 2D arrays; calculation axis is last."""
    observations = 5
    instruments = 2
    # given all the values are the same, there should not be any tke
    u = np.ones((instruments, observations))
    v = np.ones((instruments, observations))
    w = np.ones((instruments, observations))
    e_zero = np.zeros(instruments)
    assert_array_equal(e_zero, tke(u, v, w, axis=-1))


def test_no_tke_2d_axis_first():
    """Test 0 tke calculation with 2D arrays; calculation axis is first."""
    observations = 5
    instruments = 2
    # given all the values are the same, there should not be any tke
    u = np.ones((observations, instruments))
    v = np.ones((observations, instruments))
    w = np.ones((observations, instruments))
    e_zero = np.zeros(instruments)
    assert_array_equal(e_zero, tke(u, v, w, axis=0))


def test_known_tke(uvw_and_known_tke):
    """Test basic behavior of tke with known values."""
    u, v, w, e_true = uvw_and_known_tke
    assert_array_equal(e_true, tke(u, v, w))


def test_known_tke_2d_axis_last(uvw_and_known_tke):
    """Test array with shape (3, 5) [pretend time axis is -1]."""
    u, v, w, e_true = uvw_and_known_tke
    u = np.array([u, u, u])
    v = np.array([v, v, v])
    w = np.array([w, w, w])
    e_true = e_true * np.ones(3)
    assert_array_equal(e_true, tke(u, v, w, axis=-1))


def test_known_tke_2d_axis_first(uvw_and_known_tke):
    """Test array with shape (5, 3) [pretend time axis is 0]."""
    u, v, w, e_true = uvw_and_known_tke
    u = np.array([u, u, u]).transpose()
    v = np.array([v, v, v]).transpose()
    w = np.array([w, w, w]).transpose()
    e_true = e_true * np.ones(3).transpose()
    assert_array_equal(e_true, tke(u, v, w, axis=0))
    assert_array_equal(e_true, tke(u, v, w, axis=0, perturbation=True))


#
# Perturbation tests
#
@pytest.fixture()
def pert_zero_mean():
    """Return time series with zero-mean and perturbations."""
    ts = np.array([-2, -1, 0, 1, 2])
    pert_true = ts.copy()
    return ts, pert_true


@pytest.fixture()
def pert_nonzero_mean():
    """Return time seres with non-zero-mean and perturbations."""
    ts = np.array([-2, 0, 2, 4, 6])
    # ts.mean() = 2
    pert_true = np.array([-4, -2, 0, 2, 4])
    return ts, pert_true


def test_no_perturbation_1d():
    """Test with uniform data in 1D."""
    observations = 5
    # given all the values are the same, there should not be perturbations
    ts = np.ones(observations)
    pert_zero = 0
    assert_array_equal(pert_zero, get_perturbation(ts))


def test_no_perturbation_2d_axis_last():
    """Test with uniform data in 2D along the last axis."""
    observations = 5
    instruments = 2
    # given all the values are the same, there should not be perturbations
    ts = np.ones((instruments, observations))
    pert_zero = np.zeros((instruments, observations))
    assert_array_equal(pert_zero, get_perturbation(ts, axis=-1))


def test_no_perturbation_2d_axis_first():
    """Test with uniform data in 2D along the first axis."""
    observations = 5
    instruments = 2
    # given all the values are the same, there should not be perturbations
    ts = np.ones((observations, instruments))
    pert_zero = np.zeros((observations, instruments))
    assert_array_equal(pert_zero, get_perturbation(ts, axis=0))


def test_known_perturbation_zero_mean_1d(pert_zero_mean):
    """Test with zero-mean data in 1D."""
    ts, pert_known = pert_zero_mean
    assert_array_equal(pert_known, get_perturbation(ts))


def test_known_perturbation_zero_mean_2d_axis_last(pert_zero_mean):
    """Test with zero-mean data in 2D along the last axis."""
    ts, pert_known = pert_zero_mean
    ts = np.array([ts, ts, ts])
    pert_known = np.array([pert_known, pert_known, pert_known])
    assert_array_equal(pert_known, get_perturbation(ts, axis=-1))


def test_known_perturbation_zero_mean_2d_axis_first(pert_zero_mean):
    """Test with zero-mean data in 2D along the first axis."""
    ts, pert_known = pert_zero_mean
    ts = np.array([ts, ts, ts]).transpose()
    pert_known = np.array([pert_known, pert_known, pert_known]).transpose()
    assert_array_equal(pert_known, get_perturbation(ts, axis=0))


def test_known_perturbation_nonzero_mean_1d(pert_nonzero_mean):
    """Test with non-zero-mean data in 1D."""
    ts, pert_known = pert_nonzero_mean
    assert_array_equal(pert_known, get_perturbation(ts))


def test_known_perturbation_nonzero_mean_2d_axis_last(pert_nonzero_mean):
    """Test with non-zero-mean data in 2D along the last axis."""
    ts, pert_known = pert_nonzero_mean
    ts = np.array([ts, ts, ts])
    pert_known = np.array([pert_known, pert_known, pert_known])
    assert_array_equal(pert_known, get_perturbation(ts, axis=-1))


def test_known_perturbation_nonzero_mean_2d_axis_first(pert_nonzero_mean):
    """Test with non-zero-mean data in 2D along the first axis."""
    ts, pert_known = pert_nonzero_mean
    ts = np.array([ts, ts, ts]).transpose()
    pert_known = np.array([pert_known, pert_known, pert_known]).transpose()
    assert_array_equal(pert_known, get_perturbation(ts, axis=0))


#
# Kinematic Flux Tests
#
@pytest.fixture()
def uvw_and_known_kf_zero_mean():
    """Return components and kinematic flux for zero-mean time series."""
    u = np.array([-2, -1, 0, 1, 2])
    v = -u
    w = 2 * u
    kf_true = {'uv': -2, 'uw': 4, 'vw': -4}
    return u, v, w, kf_true


@pytest.fixture()
def uvw_and_known_kf_nonzero_mean():
    """Return components and kinematic flux for non-zero-mean time series."""
    u = np.array([-2, -1, 0, 1, 5])
    v = -u
    w = 2 * u
    kf_true = {'uv': -5.84, 'uw': 11.68, 'vw': -11.68}
    return u, v, w, kf_true


def test_kf_1d_zero_mean(uvw_and_known_kf_zero_mean):
    """Test kinematic flux calculation in 1D with zero-mean time series."""
    u, v, w, kf_true = uvw_and_known_kf_zero_mean
    assert_array_equal(kinematic_flux(u, v, perturbation=False),
                       kf_true['uv'])
    assert_array_equal(kinematic_flux(u, w, perturbation=False),
                       kf_true['uw'])
    assert_array_equal(kinematic_flux(v, w, perturbation=False),
                       kf_true['vw'])

    # given u, v, and w have a zero mean, the kf computed with
    # perturbation=True and perturbation=False should be the same
    assert_array_equal(kinematic_flux(u, v, perturbation=False),
                       kinematic_flux(u, v, perturbation=True))
    assert_array_equal(kinematic_flux(u, w, perturbation=False),
                       kinematic_flux(u, w, perturbation=True))
    assert_array_equal(kinematic_flux(v, w, perturbation=False),
                       kinematic_flux(v, w, perturbation=True))


def test_kf_1d_nonzero_mean(uvw_and_known_kf_nonzero_mean):
    """Test kinematic flux calculation in 1D with non-zero-mean time series."""
    u, v, w, kf_true = uvw_and_known_kf_nonzero_mean
    assert_array_equal(kinematic_flux(u, v, perturbation=False),
                       kf_true['uv'])
    assert_array_equal(kinematic_flux(u, w, perturbation=False),
                       kf_true['uw'])
    assert_array_equal(kinematic_flux(v, w, perturbation=False),
                       kf_true['vw'])


def test_kf_2d_axis_last_zero_mean(uvw_and_known_kf_zero_mean):

    """Test kinematic flux calculation in 2D with zero-mean time series along last axis."""
    u, v, w, kf_true = uvw_and_known_kf_zero_mean
    u = np.array([u, u, u])
    v = np.array([v, v, v])
    w = np.array([w, w, w])
    for key in kf_true.keys():
        tmp = kf_true[key]
        kf_true[key] = np.array([tmp, tmp, tmp])
    assert_array_equal(kinematic_flux(u, v, perturbation=False, axis=-1),
                       kf_true['uv'])
    assert_array_equal(kinematic_flux(u, w, perturbation=False, axis=-1),
                       kf_true['uw'])
    assert_array_equal(kinematic_flux(v, w, perturbation=False, axis=-1),
                       kf_true['vw'])
    # given u, v, and w have a zero mean, the kf computed with
    # perturbation=True and perturbation=False should be the same
    assert_array_equal(kinematic_flux(u, v, perturbation=False, axis=-1),
                       kinematic_flux(u, v, perturbation=True, axis=-1))
    assert_array_equal(kinematic_flux(u, w, perturbation=False, axis=-1),
                       kinematic_flux(u, w, perturbation=True, axis=-1))
    assert_array_equal(kinematic_flux(v, w, perturbation=False, axis=-1),
                       kinematic_flux(v, w, perturbation=True, axis=-1))


def test_kf_2d_axis_last_nonzero_mean(uvw_and_known_kf_nonzero_mean):

    """Test kinematic flux calculation in 2D with non-zero-mean time series along last axis."""
    u, v, w, kf_true = uvw_and_known_kf_nonzero_mean
    u = np.array([u, u, u])
    v = np.array([v, v, v])
    w = np.array([w, w, w])
    for key in kf_true.keys():
        tmp = kf_true[key]
        kf_true[key] = np.array([tmp, tmp, tmp])
    assert_array_equal(kinematic_flux(u, v, perturbation=False, axis=-1),
                       kf_true['uv'])
    assert_array_equal(kinematic_flux(u, w, perturbation=False, axis=-1),
                       kf_true['uw'])
    assert_array_equal(kinematic_flux(v, w, perturbation=False, axis=-1),
                       kf_true['vw'])


def test_kf_2d_axis_first_zero_mean(uvw_and_known_kf_zero_mean):

    """Test kinematic flux calculation in 2D with zero-mean time series along first axis."""
    u, v, w, kf_true = uvw_and_known_kf_zero_mean
    u = np.array([u, u, u]).transpose()
    v = np.array([v, v, v]).transpose()
    w = np.array([w, w, w]).transpose()
    for key in kf_true.keys():
        tmp = kf_true[key]
        kf_true[key] = np.array([tmp, tmp, tmp]).transpose()
    assert_array_equal(kinematic_flux(u, v, perturbation=False, axis=0),
                       kf_true['uv'])
    assert_array_equal(kinematic_flux(u, w, perturbation=False, axis=0),
                       kf_true['uw'])
    assert_array_equal(kinematic_flux(v, w, perturbation=False, axis=0),
                       kf_true['vw'])
    # given u, v, and w have a zero mean, the kf computed with
    # perturbation=True and perturbation=False should be the same
    assert_array_equal(kinematic_flux(u, v, perturbation=False, axis=0),
                       kinematic_flux(u, v, perturbation=True, axis=0))
    assert_array_equal(kinematic_flux(u, w, perturbation=False, axis=0),
                       kinematic_flux(u, w, perturbation=True, axis=0))
    assert_array_equal(kinematic_flux(v, w, perturbation=False, axis=0),
                       kinematic_flux(v, w, perturbation=True, axis=0))


def test_kf_2d_axis_first_nonzero_mean(uvw_and_known_kf_nonzero_mean):

    """Test kinematic flux in 2D with non-zero-mean time series along first axis."""
    u, v, w, kf_true = uvw_and_known_kf_nonzero_mean
    u = np.array([u, u, u]).transpose()
    v = np.array([v, v, v]).transpose()
    w = np.array([w, w, w]).transpose()
    for key in kf_true.keys():
        tmp = kf_true[key]
        kf_true[key] = np.array([tmp, tmp, tmp]).transpose()
    assert_array_equal(kinematic_flux(u, v, perturbation=False, axis=0),
                       kf_true['uv'])
    assert_array_equal(kinematic_flux(u, w, perturbation=False, axis=0),
                       kf_true['uw'])
    assert_array_equal(kinematic_flux(v, w, perturbation=False, axis=0),
                       kf_true['vw'])


#
# Friction Velocity Tests
#
@pytest.fixture()
def uvw_and_known_u_star_zero_mean():
    """Return components and friction velocity for a zero-mean time series."""
    u = np.array([-2, -1, 0, 1, 2])
    v = -u
    w = 2 * u
    u_star_true = {'uw': 2.0, 'uwvw': 2.3784142300054421}
    return u, v, w, u_star_true


@pytest.fixture()
def uvw_and_known_u_star_nonzero_mean():
    """Return components and friction velocity for a non-zero-mean time series."""
    u = np.array([-2, -1, 0, 1, 5])
    v = -u
    w = 2 * u
    u_star_true = {'uw': 3.4176014981270124, 'uwvw': 4.0642360178166017}
    return u, v, w, u_star_true


def test_u_star_1d_zero_mean(uvw_and_known_u_star_zero_mean):
    """Test friction velocity in 1D with a zero-mean time series."""
    u, v, w, u_star_true = uvw_and_known_u_star_zero_mean
    assert_almost_equal(friction_velocity(u, w, perturbation=False),
                        u_star_true['uw'])
    assert_almost_equal(friction_velocity(u, w, v=v, perturbation=False),
                        u_star_true['uwvw'])


def test_u_star_1d_nonzero_mean(uvw_and_known_u_star_nonzero_mean):
    """Test friction velocity in 1D with a non-zero-mean time series."""
    u, v, w, u_star_true = uvw_and_known_u_star_nonzero_mean
    assert_almost_equal(friction_velocity(u, w, perturbation=False),
                        u_star_true['uw'])
    assert_almost_equal(friction_velocity(u, w, v=v, perturbation=False),
                        u_star_true['uwvw'])


def test_u_star_2d_axis_last_zero_mean(uvw_and_known_u_star_zero_mean):

    """Test friction velocity in 2D with a zero-mean time series along the last axis."""
    u, v, w, u_star_true = uvw_and_known_u_star_zero_mean
    u = np.array([u, u, u])
    v = np.array([v, v, v])
    w = np.array([w, w, w])
    for key in u_star_true.keys():
        tmp = u_star_true[key]
        u_star_true[key] = np.array([tmp, tmp, tmp])
    assert_almost_equal(friction_velocity(u, w, perturbation=False,
                        axis=-1), u_star_true['uw'])
    assert_almost_equal(friction_velocity(u, w, v=v, perturbation=False,
                        axis=-1), u_star_true['uwvw'])


def test_u_star_2d_axis_last_nonzero_mean(uvw_and_known_u_star_nonzero_mean):

    """Test friction velocity in 2D with a non-zero-mean time series along the last axis."""
    u, v, w, u_star_true = uvw_and_known_u_star_nonzero_mean
    u = np.array([u, u, u])
    v = np.array([v, v, v])
    w = np.array([w, w, w])
    for key in u_star_true.keys():
        tmp = u_star_true[key]
        u_star_true[key] = np.array([tmp, tmp, tmp])
    assert_almost_equal(friction_velocity(u, w, perturbation=False,
                        axis=-1), u_star_true['uw'])
    assert_almost_equal(friction_velocity(u, w, v=v, perturbation=False,
                        axis=-1), u_star_true['uwvw'])


def test_u_star_2d_axis_first_zero_mean(uvw_and_known_u_star_zero_mean):

    """Test friction velocity in 2D with a zero-mean time series along the first axis."""
    u, v, w, u_star_true = uvw_and_known_u_star_zero_mean
    u = np.array([u, u, u]).transpose()
    v = np.array([v, v, v]).transpose()
    w = np.array([w, w, w]).transpose()
    for key in u_star_true.keys():
        tmp = u_star_true[key]
        u_star_true[key] = np.array([tmp, tmp, tmp]).transpose()
    assert_almost_equal(friction_velocity(u, w, perturbation=False,
                        axis=0), u_star_true['uw'])
    assert_almost_equal(friction_velocity(u, w, v=v, perturbation=False,
                        axis=0), u_star_true['uwvw'])


def test_u_star_2d_axis_first_nonzero_mean(uvw_and_known_u_star_nonzero_mean):

    """Test friction velocity in 2D with a non-zero-mean time series along the first axis."""
    u, v, w, u_star_true = uvw_and_known_u_star_nonzero_mean
    u = np.array([u, u, u]).transpose()
    v = np.array([v, v, v]).transpose()
    w = np.array([w, w, w]).transpose()
    for key in u_star_true.keys():
        tmp = u_star_true[key]
        u_star_true[key] = np.array([tmp, tmp, tmp]).transpose()
    assert_almost_equal(friction_velocity(u, w, perturbation=False,
                        axis=0), u_star_true['uw'])
    assert_almost_equal(friction_velocity(u, w, v=v, perturbation=False,
                        axis=0), u_star_true['uwvw'])


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 `turbulence` module."""
5
6		import numpy as np
7		from numpy.testing import assert_almost_equal, assert_array_equal
8		import pytest
9
10		from metpy.calc.turbulence import friction_velocity, get_perturbation, kinematic_flux, tke
11
12
13		#
14		# TKE Tests
15		#
16		@pytest.fixture()
17		def uvw_and_known_tke():
18		"""Provide a set of u,v,w with a known tke value."""
19		u = np.array([-2, -1, 0, 1, 2])
20		v = -u
21		w = 2 * u
22		# 0.5 * sqrt(2 + 2 + 8)
23		e_true = np.sqrt(12) / 2.
24		return u, v, w, e_true
25
26
27		def test_no_tke_1d():
28		"""Test tke calculation where the expected value is 0."""
29		observations = 5
30		# given all the values are the same, there should not be any tke
31		u = np.ones(observations)
32		v = np.ones(observations)
33		w = np.ones(observations)
34		e_zero = 0
35		assert_array_equal(e_zero, tke(u, v, w))
36
37
38		def test_no_tke_2d_axis_last():
39		"""Test 0 tke calculation with 2D arrays; calculation axis is last."""
40		observations = 5
41		instruments = 2
42		# given all the values are the same, there should not be any tke
43		u = np.ones((instruments, observations))
44		v = np.ones((instruments, observations))
45		w = np.ones((instruments, observations))
46		e_zero = np.zeros(instruments)
47		assert_array_equal(e_zero, tke(u, v, w, axis=-1))
48
49
50		def test_no_tke_2d_axis_first():
51		"""Test 0 tke calculation with 2D arrays; calculation axis is first."""
52		observations = 5
53		instruments = 2
54		# given all the values are the same, there should not be any tke
55		u = np.ones((observations, instruments))
56		v = np.ones((observations, instruments))
57		w = np.ones((observations, instruments))
58		e_zero = np.zeros(instruments)
59		assert_array_equal(e_zero, tke(u, v, w, axis=0))
60
61
62		def test_known_tke(uvw_and_known_tke):
63		"""Test basic behavior of tke with known values."""
64		u, v, w, e_true = uvw_and_known_tke
65		assert_array_equal(e_true, tke(u, v, w))
66
67
68		def test_known_tke_2d_axis_last(uvw_and_known_tke):
69		"""Test array with shape (3, 5) [pretend time axis is -1]."""
70		u, v, w, e_true = uvw_and_known_tke
71		u = np.array([u, u, u])
72		v = np.array([v, v, v])
73		w = np.array([w, w, w])
74		e_true = e_true * np.ones(3)
75		assert_array_equal(e_true, tke(u, v, w, axis=-1))
76
77
78		def test_known_tke_2d_axis_first(uvw_and_known_tke):
79		"""Test array with shape (5, 3) [pretend time axis is 0]."""
80		u, v, w, e_true = uvw_and_known_tke
81		u = np.array([u, u, u]).transpose()
82		v = np.array([v, v, v]).transpose()
83		w = np.array([w, w, w]).transpose()
84		e_true = e_true * np.ones(3).transpose()
85		assert_array_equal(e_true, tke(u, v, w, axis=0))
86		assert_array_equal(e_true, tke(u, v, w, axis=0, perturbation=True))
87
88
89		#
90		# Perturbation tests
91		#
92		@pytest.fixture()
93		def pert_zero_mean():
94		"""Return time series with zero-mean and perturbations."""
95		ts = np.array([-2, -1, 0, 1, 2])
96		pert_true = ts.copy()
97		return ts, pert_true
98
99
100		@pytest.fixture()
101		def pert_nonzero_mean():
102		"""Return time seres with non-zero-mean and perturbations."""
103		ts = np.array([-2, 0, 2, 4, 6])
104		# ts.mean() = 2
105		pert_true = np.array([-4, -2, 0, 2, 4])
106		return ts, pert_true
107
108
109		def test_no_perturbation_1d():
110		"""Test with uniform data in 1D."""
111		observations = 5
112		# given all the values are the same, there should not be perturbations
113		ts = np.ones(observations)
114		pert_zero = 0
115		assert_array_equal(pert_zero, get_perturbation(ts))
116
117
118		def test_no_perturbation_2d_axis_last():
119		"""Test with uniform data in 2D along the last axis."""
120		observations = 5
121		instruments = 2
122		# given all the values are the same, there should not be perturbations
123		ts = np.ones((instruments, observations))
124		pert_zero = np.zeros((instruments, observations))
125		assert_array_equal(pert_zero, get_perturbation(ts, axis=-1))
126
127
128		def test_no_perturbation_2d_axis_first():
129		"""Test with uniform data in 2D along the first axis."""
130		observations = 5
131		instruments = 2
132		# given all the values are the same, there should not be perturbations
133		ts = np.ones((observations, instruments))
134		pert_zero = np.zeros((observations, instruments))
135		assert_array_equal(pert_zero, get_perturbation(ts, axis=0))
136
137
138		def test_known_perturbation_zero_mean_1d(pert_zero_mean):
139		"""Test with zero-mean data in 1D."""
140		ts, pert_known = pert_zero_mean
141		assert_array_equal(pert_known, get_perturbation(ts))
142
143
144		def test_known_perturbation_zero_mean_2d_axis_last(pert_zero_mean):
145		"""Test with zero-mean data in 2D along the last axis."""
146		ts, pert_known = pert_zero_mean
147		ts = np.array([ts, ts, ts])
148		pert_known = np.array([pert_known, pert_known, pert_known])
149		assert_array_equal(pert_known, get_perturbation(ts, axis=-1))
150
151
152		def test_known_perturbation_zero_mean_2d_axis_first(pert_zero_mean):
153		"""Test with zero-mean data in 2D along the first axis."""
154		ts, pert_known = pert_zero_mean
155		ts = np.array([ts, ts, ts]).transpose()
156		pert_known = np.array([pert_known, pert_known, pert_known]).transpose()
157		assert_array_equal(pert_known, get_perturbation(ts, axis=0))
158
159
160		def test_known_perturbation_nonzero_mean_1d(pert_nonzero_mean):
161		"""Test with non-zero-mean data in 1D."""
162		ts, pert_known = pert_nonzero_mean
163		assert_array_equal(pert_known, get_perturbation(ts))
164
165
166		def test_known_perturbation_nonzero_mean_2d_axis_last(pert_nonzero_mean):
167		"""Test with non-zero-mean data in 2D along the last axis."""
168		ts, pert_known = pert_nonzero_mean
169		ts = np.array([ts, ts, ts])
170		pert_known = np.array([pert_known, pert_known, pert_known])
171		assert_array_equal(pert_known, get_perturbation(ts, axis=-1))
172
173
174		def test_known_perturbation_nonzero_mean_2d_axis_first(pert_nonzero_mean):
175		"""Test with non-zero-mean data in 2D along the first axis."""
176		ts, pert_known = pert_nonzero_mean
177		ts = np.array([ts, ts, ts]).transpose()
178		pert_known = np.array([pert_known, pert_known, pert_known]).transpose()
179		assert_array_equal(pert_known, get_perturbation(ts, axis=0))
180
181
182		#
183		# Kinematic Flux Tests
184		#
185		@pytest.fixture()
186		def uvw_and_known_kf_zero_mean():
187		"""Return components and kinematic flux for zero-mean time series."""
188		u = np.array([-2, -1, 0, 1, 2])
189		v = -u
190		w = 2 * u
191		kf_true = {'uv': -2, 'uw': 4, 'vw': -4}
192		return u, v, w, kf_true
193
194
195		@pytest.fixture()
196		def uvw_and_known_kf_nonzero_mean():
197		"""Return components and kinematic flux for non-zero-mean time series."""
198		u = np.array([-2, -1, 0, 1, 5])
199		v = -u
200		w = 2 * u
201		kf_true = {'uv': -5.84, 'uw': 11.68, 'vw': -11.68}
202		return u, v, w, kf_true
203
204
205		def test_kf_1d_zero_mean(uvw_and_known_kf_zero_mean):
206		"""Test kinematic flux calculation in 1D with zero-mean time series."""
207		u, v, w, kf_true = uvw_and_known_kf_zero_mean
208		assert_array_equal(kinematic_flux(u, v, perturbation=False),
209		kf_true['uv'])
210		assert_array_equal(kinematic_flux(u, w, perturbation=False),
211		kf_true['uw'])
212		assert_array_equal(kinematic_flux(v, w, perturbation=False),
213		kf_true['vw'])
214
215		# given u, v, and w have a zero mean, the kf computed with
216		# perturbation=True and perturbation=False should be the same
217		assert_array_equal(kinematic_flux(u, v, perturbation=False),
218		kinematic_flux(u, v, perturbation=True))
219		assert_array_equal(kinematic_flux(u, w, perturbation=False),
220		kinematic_flux(u, w, perturbation=True))
221		assert_array_equal(kinematic_flux(v, w, perturbation=False),
222		kinematic_flux(v, w, perturbation=True))
223
224
225		def test_kf_1d_nonzero_mean(uvw_and_known_kf_nonzero_mean):
226		"""Test kinematic flux calculation in 1D with non-zero-mean time series."""
227		u, v, w, kf_true = uvw_and_known_kf_nonzero_mean
228		assert_array_equal(kinematic_flux(u, v, perturbation=False),
229		kf_true['uv'])
230		assert_array_equal(kinematic_flux(u, w, perturbation=False),
231		kf_true['uw'])
232		assert_array_equal(kinematic_flux(v, w, perturbation=False),
233		kf_true['vw'])
234
235
236	View Code Duplication	def test_kf_2d_axis_last_zero_mean(uvw_and_known_kf_zero_mean):
		0 ignored issues – show Duplication introduced 2016-11-28 06:28 UTC by Report Bug Copy Issue Report This code seems to be duplicated in your project. Loading history...
237		"""Test kinematic flux calculation in 2D with zero-mean time series along last axis."""
238		u, v, w, kf_true = uvw_and_known_kf_zero_mean
239		u = np.array([u, u, u])
240		v = np.array([v, v, v])
241		w = np.array([w, w, w])
242		for key in kf_true.keys():
243		tmp = kf_true[key]
244		kf_true[key] = np.array([tmp, tmp, tmp])
245		assert_array_equal(kinematic_flux(u, v, perturbation=False, axis=-1),
246		kf_true['uv'])
247		assert_array_equal(kinematic_flux(u, w, perturbation=False, axis=-1),
248		kf_true['uw'])
249		assert_array_equal(kinematic_flux(v, w, perturbation=False, axis=-1),
250		kf_true['vw'])
251		# given u, v, and w have a zero mean, the kf computed with
252		# perturbation=True and perturbation=False should be the same
253		assert_array_equal(kinematic_flux(u, v, perturbation=False, axis=-1),
254		kinematic_flux(u, v, perturbation=True, axis=-1))
255		assert_array_equal(kinematic_flux(u, w, perturbation=False, axis=-1),
256		kinematic_flux(u, w, perturbation=True, axis=-1))
257		assert_array_equal(kinematic_flux(v, w, perturbation=False, axis=-1),
258		kinematic_flux(v, w, perturbation=True, axis=-1))
259
260
261	View Code Duplication	def test_kf_2d_axis_last_nonzero_mean(uvw_and_known_kf_nonzero_mean):
		0 ignored issues – show Duplication introduced 2016-11-28 06:28 UTC by Report Bug Copy Issue Report This code seems to be duplicated in your project. Loading history...
262		"""Test kinematic flux calculation in 2D with non-zero-mean time series along last axis."""
263		u, v, w, kf_true = uvw_and_known_kf_nonzero_mean
264		u = np.array([u, u, u])
265		v = np.array([v, v, v])
266		w = np.array([w, w, w])
267		for key in kf_true.keys():
268		tmp = kf_true[key]
269		kf_true[key] = np.array([tmp, tmp, tmp])
270		assert_array_equal(kinematic_flux(u, v, perturbation=False, axis=-1),
271		kf_true['uv'])
272		assert_array_equal(kinematic_flux(u, w, perturbation=False, axis=-1),
273		kf_true['uw'])
274		assert_array_equal(kinematic_flux(v, w, perturbation=False, axis=-1),
275		kf_true['vw'])
276
277
278	View Code Duplication	def test_kf_2d_axis_first_zero_mean(uvw_and_known_kf_zero_mean):
		0 ignored issues – show Duplication introduced 2016-11-28 06:28 UTC by Report Bug Copy Issue Report This code seems to be duplicated in your project. Loading history...
279		"""Test kinematic flux calculation in 2D with zero-mean time series along first axis."""
280		u, v, w, kf_true = uvw_and_known_kf_zero_mean
281		u = np.array([u, u, u]).transpose()
282		v = np.array([v, v, v]).transpose()
283		w = np.array([w, w, w]).transpose()
284		for key in kf_true.keys():
285		tmp = kf_true[key]
286		kf_true[key] = np.array([tmp, tmp, tmp]).transpose()
287		assert_array_equal(kinematic_flux(u, v, perturbation=False, axis=0),
288		kf_true['uv'])
289		assert_array_equal(kinematic_flux(u, w, perturbation=False, axis=0),
290		kf_true['uw'])
291		assert_array_equal(kinematic_flux(v, w, perturbation=False, axis=0),
292		kf_true['vw'])
293		# given u, v, and w have a zero mean, the kf computed with
294		# perturbation=True and perturbation=False should be the same
295		assert_array_equal(kinematic_flux(u, v, perturbation=False, axis=0),
296		kinematic_flux(u, v, perturbation=True, axis=0))
297		assert_array_equal(kinematic_flux(u, w, perturbation=False, axis=0),
298		kinematic_flux(u, w, perturbation=True, axis=0))
299		assert_array_equal(kinematic_flux(v, w, perturbation=False, axis=0),
300		kinematic_flux(v, w, perturbation=True, axis=0))
301
302
303	View Code Duplication	def test_kf_2d_axis_first_nonzero_mean(uvw_and_known_kf_nonzero_mean):
		0 ignored issues – show Duplication introduced 2016-11-28 06:28 UTC by Report Bug Copy Issue Report This code seems to be duplicated in your project. Loading history...
304		"""Test kinematic flux in 2D with non-zero-mean time series along first axis."""
305		u, v, w, kf_true = uvw_and_known_kf_nonzero_mean
306		u = np.array([u, u, u]).transpose()
307		v = np.array([v, v, v]).transpose()
308		w = np.array([w, w, w]).transpose()
309		for key in kf_true.keys():
310		tmp = kf_true[key]
311		kf_true[key] = np.array([tmp, tmp, tmp]).transpose()
312		assert_array_equal(kinematic_flux(u, v, perturbation=False, axis=0),
313		kf_true['uv'])
314		assert_array_equal(kinematic_flux(u, w, perturbation=False, axis=0),
315		kf_true['uw'])
316		assert_array_equal(kinematic_flux(v, w, perturbation=False, axis=0),
317		kf_true['vw'])
318
319
320		#
321		# Friction Velocity Tests
322		#
323		@pytest.fixture()
324		def uvw_and_known_u_star_zero_mean():
325		"""Return components and friction velocity for a zero-mean time series."""
326		u = np.array([-2, -1, 0, 1, 2])
327		v = -u
328		w = 2 * u
329		u_star_true = {'uw': 2.0, 'uwvw': 2.3784142300054421}
330		return u, v, w, u_star_true
331
332
333		@pytest.fixture()
334		def uvw_and_known_u_star_nonzero_mean():
335		"""Return components and friction velocity for a non-zero-mean time series."""
336		u = np.array([-2, -1, 0, 1, 5])
337		v = -u
338		w = 2 * u
339		u_star_true = {'uw': 3.4176014981270124, 'uwvw': 4.0642360178166017}
340		return u, v, w, u_star_true
341
342
343		def test_u_star_1d_zero_mean(uvw_and_known_u_star_zero_mean):
344		"""Test friction velocity in 1D with a zero-mean time series."""
345		u, v, w, u_star_true = uvw_and_known_u_star_zero_mean
346		assert_almost_equal(friction_velocity(u, w, perturbation=False),
347		u_star_true['uw'])
348		assert_almost_equal(friction_velocity(u, w, v=v, perturbation=False),
349		u_star_true['uwvw'])
350
351
352		def test_u_star_1d_nonzero_mean(uvw_and_known_u_star_nonzero_mean):
353		"""Test friction velocity in 1D with a non-zero-mean time series."""
354		u, v, w, u_star_true = uvw_and_known_u_star_nonzero_mean
355		assert_almost_equal(friction_velocity(u, w, perturbation=False),
356		u_star_true['uw'])
357		assert_almost_equal(friction_velocity(u, w, v=v, perturbation=False),
358		u_star_true['uwvw'])
359
360
361	View Code Duplication	def test_u_star_2d_axis_last_zero_mean(uvw_and_known_u_star_zero_mean):
		0 ignored issues – show Duplication introduced 2016-11-28 06:28 UTC by Report Bug Copy Issue Report This code seems to be duplicated in your project. Loading history...
362		"""Test friction velocity in 2D with a zero-mean time series along the last axis."""
363		u, v, w, u_star_true = uvw_and_known_u_star_zero_mean
364		u = np.array([u, u, u])
365		v = np.array([v, v, v])
366		w = np.array([w, w, w])
367		for key in u_star_true.keys():
368		tmp = u_star_true[key]
369		u_star_true[key] = np.array([tmp, tmp, tmp])
370		assert_almost_equal(friction_velocity(u, w, perturbation=False,
371		axis=-1), u_star_true['uw'])
372		assert_almost_equal(friction_velocity(u, w, v=v, perturbation=False,
373		axis=-1), u_star_true['uwvw'])
374
375
376	View Code Duplication	def test_u_star_2d_axis_last_nonzero_mean(uvw_and_known_u_star_nonzero_mean):
		0 ignored issues – show Duplication introduced 2016-11-28 06:28 UTC by Report Bug Copy Issue Report This code seems to be duplicated in your project. Loading history...
377		"""Test friction velocity in 2D with a non-zero-mean time series along the last axis."""
378		u, v, w, u_star_true = uvw_and_known_u_star_nonzero_mean
379		u = np.array([u, u, u])
380		v = np.array([v, v, v])
381		w = np.array([w, w, w])
382		for key in u_star_true.keys():
383		tmp = u_star_true[key]
384		u_star_true[key] = np.array([tmp, tmp, tmp])
385		assert_almost_equal(friction_velocity(u, w, perturbation=False,
386		axis=-1), u_star_true['uw'])
387		assert_almost_equal(friction_velocity(u, w, v=v, perturbation=False,
388		axis=-1), u_star_true['uwvw'])
389
390
391	View Code Duplication	def test_u_star_2d_axis_first_zero_mean(uvw_and_known_u_star_zero_mean):
		0 ignored issues – show Duplication introduced 2016-11-28 06:28 UTC by Report Bug Copy Issue Report This code seems to be duplicated in your project. Loading history...
392		"""Test friction velocity in 2D with a zero-mean time series along the first axis."""
393		u, v, w, u_star_true = uvw_and_known_u_star_zero_mean
394		u = np.array([u, u, u]).transpose()
395		v = np.array([v, v, v]).transpose()
396		w = np.array([w, w, w]).transpose()
397		for key in u_star_true.keys():
398		tmp = u_star_true[key]
399		u_star_true[key] = np.array([tmp, tmp, tmp]).transpose()
400		assert_almost_equal(friction_velocity(u, w, perturbation=False,
401		axis=0), u_star_true['uw'])
402		assert_almost_equal(friction_velocity(u, w, v=v, perturbation=False,
403		axis=0), u_star_true['uwvw'])
404
405
406	View Code Duplication	def test_u_star_2d_axis_first_nonzero_mean(uvw_and_known_u_star_nonzero_mean):
		0 ignored issues – show Duplication introduced 2016-11-28 06:28 UTC by Report Bug Copy Issue Report This code seems to be duplicated in your project. Loading history...
407		"""Test friction velocity in 2D with a non-zero-mean time series along the first axis."""
408		u, v, w, u_star_true = uvw_and_known_u_star_nonzero_mean
409		u = np.array([u, u, u]).transpose()
410		v = np.array([v, v, v]).transpose()
411		w = np.array([w, w, w]).transpose()
412		for key in u_star_true.keys():
413		tmp = u_star_true[key]
414		u_star_true[key] = np.array([tmp, tmp, tmp]).transpose()
415		assert_almost_equal(friction_velocity(u, w, perturbation=False,
416		axis=0), u_star_true['uw'])
417		assert_almost_equal(friction_velocity(u, w, v=v, perturbation=False,
418		axis=0), u_star_true['uwvw'])
419

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