def test_plot_matrix(data):
"Plot the data passing in a matrix and specifying columns"
fig = Figure()
fig.plot(
data=data,
region=[10, 70, -5, 10],
projection="M10i",
style="cc",
color="#aaaaaa",
B="a",
columns="0,1,2+s0.005",
)
return fig
def test_plot_projection(data):
"Plot the data in green squares with a projection"
fig = Figure()
fig.plot(
x=data[:, 0],
y=data[:, 1],
region="g",
projection="R270/4i",
style="s0.2c",
color="green",
frame="ag",
)
return fig
def test_plot_colors_sizes_proj(data, region):
"Plot the data using z as sizes and colors with a projection"
fig = Figure()
fig.coast(region=region, projection="M10i", frame="af", water="skyblue")
fig.plot(
x=data[:, 0],
y=data[:, 1],
color=data[:, 2],
sizes=0.5 * data[:, 2],
style="cc",
cmap="copper",
)
return fig
def test_legend_default_position():
"""
Test using the default legend position.
"""
fig = Figure()
fig.basemap(region=[-1, 1, -1, 1], frame=True)
fig.plot(x=[0], y=[0], style="p10p", label="Default")
fig.legend()
return fig
def test_plot_matrix_color(data):
"""
Plot the data passing in a matrix and using a colormap.
"""
fig = Figure()
fig.plot(
data=data,
region=[10, 70, -5, 10],
projection="X10c",
style="c0.5c",
cmap="rainbow",
frame="a",
)
return fig
def test_plot_lines_with_arrows():
"""Plot lines with arrows.
The test is slightly different from test_plot_vectors().
Here the vectors are plotted as lines, with arrows at the end.
The test also check if the API crashes.
See https://github.com/GenericMappingTools/pygmt/issues/406.
"""
fig = Figure()
fig.basemap(region=[-2, 2, -2, 2], frame=True)
fig.plot(x=[-1.0, -1.0], y=[-1.0, 1.0], pen="1p,black+ve0.2c")
fig.plot(x=[1.0, 1.0], y=[-1.0, 1.0], pen="1p,black+ve0.2c")
return fig
def test_plot_sizes(data, region):
"Plot the data using z as sizes"
fig = Figure()
fig.plot(
x=data[:, 0],
y=data[:, 1],
sizes=0.5 * data[:, 2],
region=region,
projection="X4i",
style="cc",
color="blue",
frame="af",
)
return fig
def test_geopandas_plot_non_default_circle():
"""
Check the default behavior of plotting geopandas DataFrame with Point
geometry in 2d.
"""
point = shapely.geometry.Point(1, 2)
gdf = gpd.GeoDataFrame(geometry=[point])
fig = Figure()
fig.plot(data=gdf,
region=[0, 2, 1, 3],
projection="X2c",
frame=True,
style="c0.2c")
return fig
def test_plot_matrix(data, color):
"""
Plot the data passing in a matrix and specifying columns.
"""
fig = Figure()
fig.plot(
data=data,
region=[10, 70, -5, 10],
projection="M15c",
style="cc",
color=color,
frame="a",
incols="0,1,2+s0.5",
)
return fig
def test_plot_from_file(region):
"""
Plot using the data file name instead of loaded data.
"""
fig = Figure()
fig.plot(
data=POINTS_DATA,
region=region,
projection="X10c",
style="d1c",
color="yellow",
frame=True,
incols=[0, 1],
)
return fig
def test_plot_red_circles(data, region):
"""
Plot the data in red circles passing in vectors.
"""
fig = Figure()
fig.plot(
x=data[:, 0],
y=data[:, 1],
region=region,
projection="X10c",
style="c0.2c",
color="red",
frame="afg",
)
return fig
def test_plot_colors_sizes(data, region):
"Plot the data using z as sizes and colors"
fig = Figure()
fig.plot(
x=data[:, 0],
y=data[:, 1],
color=data[:, 2],
sizes=0.5 * data[:, 2],
region=region,
projection="X3i",
style="cc",
cmap="copper",
frame="af",
)
return fig
def test_makecpt_plot_points(points, region):
"""
Use static color palette table to change color of points.
"""
fig = Figure()
makecpt(cmap="rainbow")
fig.plot(
x=points[:, 0],
y=points[:, 1],
color=points[:, 2],
region=region,
style="c1c",
cmap=True,
)
return fig
def test_plot_colors(data, region):
"""
Plot the data using z as colors.
"""
fig = Figure()
fig.plot(
x=data[:, 0],
y=data[:, 1],
color=data[:, 2],
region=region,
projection="X10c",
style="c0.5c",
cmap="cubhelix",
frame="af",
)
return fig
def test_plot_dataframe_incols():
"""
Make sure that the incols parameter works for pandas.DataFrame.
See https://github.com/GenericMappingTools/pygmt/issues/1440.
"""
data = pd.DataFrame(data={
"col1": [-0.5, 0, 0.5],
"col2": [-0.75, 0, 0.75]
})
fig = Figure()
fig.plot(data=data,
frame=True,
region=[-1, 1, -1, 1],
projection="X5c",
incols=[1, 0])
return fig
def test_legend_position():
"""
Try positioning with each of the four legend coordinate systems.
"""
fig = Figure()
fig.basemap(region=[-2, 2, -2, 2], frame=True)
positions = ["jTR+jTR", "g0/1", "n0.2/0.2", "x4i/2i/2i"]
for i, position in enumerate(positions):
fig.plot(x=[0], y=[0], style="p10p", label=i)
fig.legend(position=position, box=True)
return fig
def test_plot_vectors():
"Plot vectors"
azimuth = np.array([0, 45, 90, 135, 180, 225, 270, 310])
lengths = np.linspace(0.1, 1, len(azimuth))
lon = np.sin(np.deg2rad(azimuth))
lat = np.cos(np.deg2rad(azimuth))
fig = Figure()
fig.plot(
x=lon,
y=lat,
direction=(azimuth, lengths),
region="-2/2/-2/2",
projection="X4i",
style="V0.2c+e",
color="black",
frame="af",
)
return fig
def test_plot_ogrgmt_file_multipoint_default_style(func):
"""
Make sure that OGR/GMT files with MultiPoint geometry are plotted as
squares and not as line (default GMT style).
"""
with GMTTempFile(suffix=".gmt") as tmpfile:
gmt_file = """# @VGMT1.0 @GMULTIPOINT
# @R1/1/1/1UB
# FEATURE_DATA
1 2
"""
with open(tmpfile.name, "w", encoding="utf8") as file:
file.write(gmt_file)
fig = Figure()
fig.plot(data=func(tmpfile.name),
region=[0, 2, 1, 3],
projection="X2c",
frame=True)
return fig
def test_plot_datetime():
"""
Test various datetime input data.
"""
fig = Figure()
fig.basemap(
projection="X15c/5c",
region=[
np.array("2010-01-01T00:00:00", dtype=np.datetime64),
pd.Timestamp("2020-01-01"),
0,
10,
],
frame=True,
)
# numpy.datetime64 types
x = np.array(
["2010-06-01", "2011-06-01T12", "2012-01-01T12:34:56"], dtype="datetime64"
)
y = [1.0, 2.0, 3.0]
fig.plot(x, y, style="c0.2c", pen="1p")
# pandas.DatetimeIndex
x = pd.date_range("2013", freq="YS", periods=3)
y = [4, 5, 6]
fig.plot(x, y, style="t0.2c", pen="1p")
# xarray.DataArray
x = xr.DataArray(data=pd.date_range(start="2015-03", freq="QS", periods=3))
y = [7.5, 6, 4.5]
fig.plot(x, y, style="s0.2c", pen="1p")
# raw datetime strings
x = ["2016-02-01", "2017-03-04T00:00"]
y = [7, 8]
fig.plot(x, y, style="a0.2c", pen="1p")
# the Python built-in datetime and date
x = [datetime.date(2018, 1, 1), datetime.datetime(2019, 1, 1)]
y = [8.5, 9.5]
fig.plot(x, y, style="i0.2c", pen="1p")
return fig
def test_plot_transparency():
"""
Plot the data with a constant transparency.
"""
x = np.arange(1, 10)
y = np.arange(1, 10)
fig = Figure()
fig.plot(
x=x,
y=y,
region=[0, 10, 0, 10],
projection="X10c",
frame=True,
style="c0.2c",
color="blue",
transparency=80.0,
)
return fig
def test_plot_varying_transparency():
"""
Plot the data using z as transparency.
"""
x = np.arange(1, 10)
y = np.arange(1, 10)
z = np.arange(1, 10) * 10
fig = Figure()
fig.plot(
x=x,
y=y,
region=[0, 10, 0, 10],
projection="X10c",
frame=True,
style="c0.2c",
color="blue",
transparency=z,
)
return fig
def test_plot_varying_intensity():
"""
Plot the data with array-like intensity.
"""
x = np.arange(-1, 1.1, 0.1)
y = np.zeros(x.size)
intensity = x
fig = Figure()
fig.plot(
x=x,
y=y,
region=[-1.1, 1.1, -0.5, 0.5],
projection="X10c/2c",
frame=["S", "xaf+lIntensity"],
style="c0.25c",
color="blue",
intensity=intensity,
)
return fig
def test_plot_deprecate_columns_to_incols(region):
"""
Make sure that the old parameter "columns" is supported and it reports a
warning.
Modified from the test_plot_from_file() test.
"""
fig = Figure()
with pytest.warns(expected_warning=FutureWarning) as record:
fig.plot(
data=POINTS_DATA,
region=region,
projection="X10c",
style="d1c",
color="yellow",
frame=True,
columns=[0, 1],
)
assert len(record) == 1 # check that only one warning was raised
return fig
def test_plot_ogrgmt_file_multipoint_non_default_style():
"""
Make sure that non-default style can be set for plotting OGR/GMT file.
"""
with GMTTempFile(suffix=".gmt") as tmpfile:
gmt_file = """# @VGMT1.0 @GPOINT
# @R1/1/1/1UB
# FEATURE_DATA
1 2
"""
with open(tmpfile.name, "w", encoding="utf8") as file:
file.write(gmt_file)
fig = Figure()
fig.plot(
data=tmpfile.name,
region=[0, 2, 1, 3],
projection="X2c",
frame=True,
style="c0.2c",
)
return fig
def test_plot_deprecate_sizes_to_size(data, region):
"""
Make sure that the old parameter "sizes" is supported and it reports a
warning.
Modified from the test_plot_sizes() test.
"""
fig = Figure()
with pytest.warns(expected_warning=FutureWarning) as record:
fig.plot(
x=data[:, 0],
y=data[:, 1],
sizes=0.5 * data[:, 2],
region=region,
projection="X10c",
style="cc",
color="blue",
frame="af",
)
assert len(record) == 1 # check that only one warning was raised
return fig
def test_legend_entries():
"""
Test different marker types/shapes.
"""
fig_ref, fig_test = Figure(), Figure()
# Use single-character arguments for the reference image
fig_ref = Figure()
fig_ref.basemap(J="x1i", R="0/7/3/7", B="")
fig_ref.plot(
data="@Table_5_11.txt",
S="c0.15i",
G="lightgreen",
W="faint",
l="Apples",
)
fig_ref.plot(data="@Table_5_11.txt", W="1.5p,gray", l='"My lines"')
fig_ref.plot(data="@Table_5_11.txt", S="t0.15i", G="orange", l="Oranges")
fig_ref.legend(D="JTR+jTR")
fig_test.basemap(projection="x1i", region=[0, 7, 3, 7], frame=True)
fig_test.plot(
data="@Table_5_11.txt",
style="c0.15i",
color="lightgreen",
pen="faint",
label="Apples",
)
fig_test.plot(data="@Table_5_11.txt", pen="1.5p,gray", label='"My lines"')
fig_test.plot(
data="@Table_5_11.txt", style="t0.15i", color="orange", label="Oranges"
)
fig_test.legend(position="JTR+jTR")
return fig_ref, fig_test
def test_plot_fail_size_color(data):
"Should raise an exception if array sizes and color are used with matrix"
fig = Figure()
with pytest.raises(GMTInvalidInput):
fig.plot(
data=data,
region=region,
projection="X4i",
style="c0.2c",
color=data[:, 2],
frame="afg",
)
with pytest.raises(GMTInvalidInput):
fig.plot(
data=data,
region=region,
projection="X4i",
style="cc",
sizes=data[:, 2],
color="red",
frame="afg",
)
def test_plot_scalar_xy():
"Plot symbols given scalar x, y coordinates"
fig = Figure()
fig.basemap(region=[-2, 2, -2, 2], frame=True)
fig.plot(x=-1.5, y=1.5, style="c1c")
fig.plot(x=0, y=0, style="t1c")
fig.plot(x=1.5, y=-1.5, style="s1c")
return fig
def test_plot_fail_1d_array_with_data(data):
"""
Should raise an exception if array color, size, intensity and transparency
are used with matrix.
"""
fig = Figure()
kwargs = dict(data=data, region=region, projection="X10c", frame="afg")
with pytest.raises(GMTInvalidInput):
fig.plot(style="c0.2c", color=data[:, 2], **kwargs)
with pytest.raises(GMTInvalidInput):
fig.plot(style="cc", size=data[:, 2], color="red", **kwargs)
with pytest.raises(GMTInvalidInput):
fig.plot(style="c0.2c", color="red", intensity=data[:, 2], **kwargs)
with pytest.raises(GMTInvalidInput):
fig.plot(style="c0.2c", color="red", transparency=data[:, 2] * 100, **kwargs)
def test_plot_projection(data):
"""
Plot the data in green squares with a projection.
"""
fig_ref, fig_test = Figure(), Figure()
fig_ref.plot(
data=POINTS_DATA,
R="g",
J="R270/4i",
S="s0.2c",
G="green",
B="ag",
)
fig_test.plot(
x=data[:, 0],
y=data[:, 1],
region="g",
projection="R270/4i",
style="s0.2c",
color="green",
frame="ag",
)
return fig_ref, fig_test
