|
| 1 | +""" |
| 2 | +Tests for meca |
| 3 | +""" |
| 4 | +import os |
| 5 | +import pandas as pd |
| 6 | +import numpy as np |
| 7 | +import pytest |
| 8 | +from pygmt.helpers import GMTTempFile |
| 9 | + |
| 10 | +from .. import Figure |
| 11 | + |
| 12 | + |
| 13 | +TEST_DATA_DIR = os.path.join(os.path.dirname(__file__), "data") |
| 14 | + |
| 15 | + |
| 16 | +@pytest.mark.mpl_image_compare |
| 17 | +def test_meca_spec_dictionary(): |
| 18 | + """ |
| 19 | + Test supplying a dictionary containing a single focal mechanism to the |
| 20 | + `spec` argument. |
| 21 | + """ |
| 22 | + |
| 23 | + fig = Figure() |
| 24 | + |
| 25 | + # Right lateral strike slip focal mechanism |
| 26 | + fig.meca( |
| 27 | + dict(strike=0, dip=90, rake=0, magnitude=5), |
| 28 | + longitude=0, |
| 29 | + latitude=5, |
| 30 | + depth=0, |
| 31 | + scale="2.5c", |
| 32 | + region=[-1, 1, 4, 6], |
| 33 | + projection="M14c", |
| 34 | + frame=2, |
| 35 | + ) |
| 36 | + |
| 37 | + return fig |
| 38 | + |
| 39 | + |
| 40 | +@pytest.mark.mpl_image_compare |
| 41 | +def test_meca_spec_dict_list(): |
| 42 | + """ |
| 43 | + Test supplying a dictionary containing a list of focal mechanism to the |
| 44 | + `spec` argument. |
| 45 | + """ |
| 46 | + |
| 47 | + fig = Figure() |
| 48 | + |
| 49 | + # supply focal mechanisms as a dict of lists |
| 50 | + focal_mechanisms = dict( |
| 51 | + strike=[330, 350], dip=[30, 50], rake=[90, 90], magnitude=[3, 2] |
| 52 | + ) |
| 53 | + |
| 54 | + fig.meca( |
| 55 | + focal_mechanisms, |
| 56 | + longitude=[-124.3, -124.4], |
| 57 | + latitude=[48.1, 48.2], |
| 58 | + depth=[12.0, 11.0], |
| 59 | + region=[-125, -122, 47, 49], |
| 60 | + scale="2c", |
| 61 | + projection="M14c", |
| 62 | + ) |
| 63 | + |
| 64 | + return fig |
| 65 | + |
| 66 | + |
| 67 | +@pytest.mark.mpl_image_compare |
| 68 | +def test_meca_spec_dataframe(): |
| 69 | + """ |
| 70 | + Test supplying a pandas DataFrame containing focal mechanisms and |
| 71 | + locations to the `spec` argument. |
| 72 | + """ |
| 73 | + |
| 74 | + fig = Figure() |
| 75 | + |
| 76 | + # supply focal mechanisms to meca as a dataframe |
| 77 | + focal_mechanisms = dict( |
| 78 | + strike=[324, 353], |
| 79 | + dip=[20.6, 40], |
| 80 | + rake=[83, 90], |
| 81 | + magnitude=[3.4, 2.9], |
| 82 | + longitude=[-124, -124.4], |
| 83 | + latitude=[48.1, 48.2], |
| 84 | + depth=[12, 11.0], |
| 85 | + ) |
| 86 | + spec_dataframe = pd.DataFrame(data=focal_mechanisms) |
| 87 | + |
| 88 | + fig.meca(spec_dataframe, region=[-125, -122, 47, 49], scale="2c", projection="M14c") |
| 89 | + |
| 90 | + return fig |
| 91 | + |
| 92 | + |
| 93 | +@pytest.mark.mpl_image_compare |
| 94 | +def test_meca_spec_1d_array(): |
| 95 | + """ |
| 96 | + Test supplying a 1D numpy array containing focal mechanisms and |
| 97 | + locations to the `spec` argument. |
| 98 | + """ |
| 99 | + |
| 100 | + fig = Figure() |
| 101 | + |
| 102 | + # supply focal mechanisms to meca as a 1D numpy array, here we are using |
| 103 | + # the Harvard CMT zero trace convention but the focal mechanism |
| 104 | + # parameters may be specified any of the available conventions. Since we |
| 105 | + # are not using a dict or dataframe the convention and component should |
| 106 | + # be specified. |
| 107 | + focal_mechanism = [ |
| 108 | + -127.40, # longitude |
| 109 | + 40.87, # latitude |
| 110 | + 12, # depth |
| 111 | + -3.19, # mrr |
| 112 | + 0.16, # mtt |
| 113 | + 3.03, # mff |
| 114 | + -1.02, # mrt |
| 115 | + -3.93, # mrf |
| 116 | + -0.02, # mtf |
| 117 | + 23, # exponent |
| 118 | + 0, # plot_lon, 0 to plot at event location |
| 119 | + 0, # plot_lat, 0 to plot at event location |
| 120 | + ] |
| 121 | + focal_mech_array = np.asarray(focal_mechanism) |
| 122 | + |
| 123 | + fig.meca( |
| 124 | + focal_mech_array, |
| 125 | + convention="mt", |
| 126 | + component="full", |
| 127 | + region=[-128, -127, 40, 41], |
| 128 | + scale="2c", |
| 129 | + projection="M14c", |
| 130 | + ) |
| 131 | + |
| 132 | + return fig |
| 133 | + |
| 134 | + |
| 135 | +@pytest.mark.mpl_image_compare |
| 136 | +def test_meca_spec_2d_array(): |
| 137 | + """ |
| 138 | + Test supplying a 2D numpy array containing focal mechanisms and |
| 139 | + locations to the `spec` argument. |
| 140 | + """ |
| 141 | + |
| 142 | + fig = Figure() |
| 143 | + |
| 144 | + # supply focal mechanisms to meca as a 2D numpy array, here we are using |
| 145 | + # the GCMT convention but the focal mechanism parameters may be |
| 146 | + # specified any of the available conventions. Since we are not using a |
| 147 | + # dict or dataframe the convention and component should be specified. |
| 148 | + focal_mechanisms = [ |
| 149 | + [ |
| 150 | + -127.40, # longitude |
| 151 | + 40.87, # latitude |
| 152 | + 12, # depth |
| 153 | + 170, # strike1 |
| 154 | + 20, # dip1 |
| 155 | + -110, # rake1 |
| 156 | + 11, # strike2 |
| 157 | + 71, # dip2 |
| 158 | + -83, # rake2 |
| 159 | + 5.1, # mantissa |
| 160 | + 23, # exponent |
| 161 | + 0, # plot_lon, 0 means we want to plot at the event location |
| 162 | + 0, # plot_lat |
| 163 | + ], |
| 164 | + [-127.50, 40.88, 12.0, 168, 40, -115, 20, 54, -70, 4.0, 23, 0, 0], |
| 165 | + ] |
| 166 | + focal_mechs_array = np.asarray(focal_mechanisms) |
| 167 | + |
| 168 | + fig.meca( |
| 169 | + focal_mechs_array, |
| 170 | + convention="gcmt", |
| 171 | + region=[-128, -127, 40, 41], |
| 172 | + scale="2c", |
| 173 | + projection="M14c", |
| 174 | + ) |
| 175 | + |
| 176 | + return fig |
| 177 | + |
| 178 | + |
| 179 | +@pytest.mark.mpl_image_compare |
| 180 | +def test_meca_spec_file(): |
| 181 | + """ |
| 182 | + Test supplying a file containing focal mechanisms and locations to the |
| 183 | + `spec` argument. |
| 184 | + """ |
| 185 | + |
| 186 | + fig = Figure() |
| 187 | + |
| 188 | + focal_mechanism = [-127.43, 40.81, 12, -3.19, 1.16, 3.93, -1.02, -3.93, -1.02, 23] |
| 189 | + |
| 190 | + # writes temp file to pass to gmt |
| 191 | + with GMTTempFile() as temp: |
| 192 | + with open(temp.name, mode="w") as temp_file: |
| 193 | + temp_file.write(" ".join([str(x) for x in focal_mechanism])) |
| 194 | + # supply focal mechanisms to meca as a file |
| 195 | + fig.meca( |
| 196 | + temp.name, |
| 197 | + convention="mt", |
| 198 | + component="full", |
| 199 | + region=[-128, -127, 40, 41], |
| 200 | + scale="2c", |
| 201 | + projection="M14c", |
| 202 | + ) |
| 203 | + |
| 204 | + return fig |
| 205 | + |
| 206 | + |
| 207 | +@pytest.mark.mpl_image_compare |
| 208 | +def test_meca_loc_array(): |
| 209 | + """ |
| 210 | + Test supplying lists and np.ndarrays as the event location (longitude, |
| 211 | + latitude, and depth). |
| 212 | + """ |
| 213 | + |
| 214 | + fig = Figure() |
| 215 | + |
| 216 | + # specify focal mechanisms |
| 217 | + focal_mechanisms = dict( |
| 218 | + strike=[327, 350], dip=[41, 50], rake=[68, 90], magnitude=[3, 2] |
| 219 | + ) |
| 220 | + |
| 221 | + # longitude, latitude, and depth may be specified as an int, float, |
| 222 | + # list, or 1d numpy array |
| 223 | + longitude = np.array([-123.3, -124.4]) |
| 224 | + latitude = np.array([48.4, 48.2]) |
| 225 | + depth = [12.0, 11.0] # to test mixed data types as inputs |
| 226 | + |
| 227 | + scale = "2c" |
| 228 | + |
| 229 | + fig.meca( |
| 230 | + focal_mechanisms, |
| 231 | + scale, |
| 232 | + longitude, |
| 233 | + latitude, |
| 234 | + depth, |
| 235 | + region=[-125, -122, 47, 49], |
| 236 | + projection="M14c", |
| 237 | + ) |
| 238 | + |
| 239 | + return fig |
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