def test_grdcontour_file():
"""
Plot a contour image using grid file input.
"""
fig = Figure()
fig.grdcontour(
"@earth_relief_01d_g",
interval="1000",
limit="0",
pen="0.5p,black",
region=[-180, 180, -70, 70],
projection="M10i",
)
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_contour_vec(region):
"""
Plot an x-centered gaussian kernel with different y scale.
"""
fig = Figure()
x, y = np.meshgrid(
np.linspace(region[0], region[1]), np.linspace(region[2], region[3])
)
x = x.flatten()
y = y.flatten()
z = (x - 0.5 * (region[0] + region[1])) ** 2 + 4 * y ** 2
z = np.exp(-z / 10 ** 2 * np.log(2))
fig.contour(x=x, y=y, z=z, projection="X10c", region=region, frame="a", pen=True)
return fig
def test_grdcontour_slice(grid):
"""
Plot an contour image using an xarray grid that has been sliced.
"""
fig_ref, fig_test = Figure(), Figure()
grid_ = grid.sel(lat=slice(-30, 30))
kwargs = dict(interval="1000", projection="M6i")
fig_ref.grdcontour(
grid="@earth_relief_01d_g", region=[-180, 180, -30, 30], **kwargs
)
fig_test.grdcontour(grid=grid_, **kwargs)
return fig_ref, fig_test
def test_grdimage_over_dateline(xrgrid):
"""
Ensure no gaps are plotted over the 180 degree international dateline.
Specifically checking that `xrgrid.gmt.gtype = 1` sets `GMT_GRID_IS_GEO`,
and that `xrgrid.gmt.registration = 0` sets `GMT_GRID_NODE_REG`. Note that
there would be a gap over the dateline if a pixel registered grid is used.
See also https://github.com/GenericMappingTools/pygmt/issues/375.
"""
fig = Figure()
assert xrgrid.gmt.registration == 0 # gridline registration
xrgrid.gmt.gtype = 1 # geographic coordinate system
fig.grdimage(grid=xrgrid, region="g", projection="A0/0/1c")
return fig
def test_histogram(table):
"""
Tests plotting a histogram using a list of integers.
"""
fig = Figure()
fig.histogram(
table=table,
projection="X10c/10c",
region=[0, 9, 0, 6],
series=1,
frame="a",
fill="green",
)
return fig
def test_grdview_on_a_plane_styled_with_facadepen(xrgrid):
"""
Run grdview by passing in a grid and plotting it on a z-plane with styled
lines for the frontal facade.
"""
fig = Figure()
fig.grdview(
grid=xrgrid,
plane=-4000,
perspective=[225, 30],
zscale=0.005,
facadepen="0.5p,blue,dash",
)
return fig
def test_extract_region_two_figures():
"Extract region should handle multiple figures existing at the same time"
# Make two figures before calling extract_region to make sure that it's
# getting from the current figure, not the last figure.
fig1 = Figure()
region1 = np.array([0, 10, -20, -10])
fig1.coast(region=region1, projection="M6i", frame=True, land="black")
fig2 = Figure()
fig2.basemap(region="US.HI+r5", projection="M6i", frame=True)
# Activate the first figure and extract the region from it
# Use in a different session to avoid any memory problems.
with clib.Session() as lib:
lib.call_module("figure", "{} -".format(fig1._name))
with clib.Session() as lib:
wesn1 = lib.extract_region()
npt.assert_allclose(wesn1, region1)
# Now try it with the second one
with clib.Session() as lib:
lib.call_module("figure", "{} -".format(fig2._name))
with clib.Session() as lib:
wesn2 = lib.extract_region()
npt.assert_allclose(wesn2, np.array([-165.0, -150.0, 15.0, 25.0]))
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_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_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_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_coast_dcw_continent():
"""
Test passing a continent code to dcw.
"""
fig_ref, fig_test = Figure(), Figure()
# Use single-character arguments for the reference image
fig_ref.coast(R="-10/15/25/44", J="M15c", B="a", G="brown", E="=AF+gbisque+pblue")
fig_test.coast(
region=[-10, 15, 25, 44],
frame="a",
projection="M15c",
land="brown",
dcw="=AF+gbisque+pblue",
)
return fig_ref, fig_test
def test_grdcontour_labels(grid):
"""Plot a contour image using a xarray grid
with contour labels and alternate colors
"""
fig_ref, fig_test = Figure(), Figure()
kwargs = dict(
interval="1000",
annotation="5000",
projection="W0/6i",
pen=["a1p,red", "c0.5p,black"],
label_placement="d3i",
)
fig_ref.grdcontour("@earth_relief_01d_g", **kwargs)
fig_test.grdcontour(grid, **kwargs)
return fig_ref, fig_test
def test_grdview_with_perspective_and_zaxis_frame(xrgrid, region):
"""
Run grdview by passing in a grid and plotting an annotated vertical z-axis
frame on a Transverse Mercator (T) projection.
"""
fig = Figure()
projection = f"T{(region[0]+region[1])/2}/{abs((region[2]+region[3])/2)}"
fig.grdview(
grid=xrgrid,
projection=projection,
perspective=[225, 30],
zscale=0.005,
frame=["xaf", "yaf", "zaf"],
)
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_projection(data):
"""
Plot the data in green squares with a projection.
"""
fig = Figure()
fig.plot(
x=data[:, 0],
y=data[:, 1],
region="g",
projection="R270/10c",
style="s0.2c",
color="green",
frame="ag",
)
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_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_text_round_clearance(region, projection):
"""
Print text with round rectangle box clearance
"""
fig = Figure()
fig.text(
region=region,
projection=projection,
x=1.2,
y=1.2,
text="clearance around text",
clearance="90%+tO",
pen="default,black,dashed",
)
return fig
def test_grdimage_central_meridians_and_standard_parallels(
grid, proj_type, lon0, lat0):
"""
Test that plotting a grid with different central meridians (lon0) and
standard_parallels (lat0) using Cylindrical Equidistant (Q) and General
Stereographic (S) projection systems work.
"""
fig_ref, fig_test = Figure(), Figure()
fig_ref.grdimage("@earth_relief_01d_g",
projection=f"{proj_type}{lon0}/{lat0}/15c",
cmap="geo")
fig_test.grdimage(grid,
projection=f"{proj_type}{lon0}/{lat0}/15c",
cmap="geo")
return fig_ref, fig_test
def test_inset_context_manager():
"""
Test that the inset context manager works and, once closed, plotting
elements are added to the larger figure.
"""
fig = Figure()
fig.basemap(region=[-74, -69.5, 41, 43], projection="M9c", frame=True)
with fig.inset(position="jBL+w3c+o0.2c", margin=0, box="+pblack"):
fig.basemap(region=[-80, -65, 35, 50], projection="M3c", frame="afg")
fig.basemap(
rose="jTR+w3c") # Pass rose argument with basemap after the inset
return fig
def test_config_format_date_map():
"""
Test that setting FORMAT_DATE_MAP config changes how the output date string
is plotted.
Note the space in 'o dd', this acts as a regression test for
https://github.com/GenericMappingTools/pygmt/issues/247.
"""
fig = Figure()
with config(FORMAT_DATE_MAP="o dd"):
fig.basemap(
region=["1969-7-21T", "1969-7-23T", 0, 1],
projection="X2.5c/0.1c",
frame=["sxa1D", "S"],
)
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],
size=0.5 * data[:, 2],
region=region,
projection="X10c",
style="cc",
color="blue",
frame="af",
)
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_coast():
"Simple plot from the GMT docs"
fig = Figure()
fig.coast(
R="-30/30/-40/40",
J="m0.1i",
B=5,
I="1/1p,blue",
N="1/0.25p,-",
W="0.25p,white",
G="green",
S="blue",
D="c",
A=10000,
)
return fig
def test_text_justify_parsed_from_textfile():
"""
Print text justified based on a column from textfile, using justify=True
boolean operation. Loosely based on "All great-circle paths lead to Rome"
gallery example at
https://gmt.soest.hawaii.edu/doc/latest/gallery/ex23.html
"""
fig = Figure()
fig.text(
region="g",
projection="H90/9i",
justify=True,
textfiles=CITIES_DATA,
D="j0.45/0+vred", # draw red-line from xy point to text label (city name)
)
return fig
def test_plot3d_red_circles_zsize(data, region):
"Plot the 3D data in red circles passing in vectors and setting zsize = 6c"
fig = Figure()
fig.plot3d(
x=data[:, 0],
y=data[:, 1],
z=data[:, 2],
zsize="6c",
perspective=[225, 30],
region=region,
projection="X10c",
style="c0.2c",
color="red",
frame=["afg", "zafg"],
)
return fig
def test_text_nonstr_text():
"""
Input text is in non-string type (e.g., int, float)
"""
fig = Figure()
fig.text(
region=[0, 10, 0, 10],
projection="X10c",
frame=True,
x=[1, 2, 3, 4],
y=[1, 2, 3, 4],
text=[1, 2, 3.0, 4.0],
)
return fig
def test_grdcontour_labels(grid):
"""
Plot a contour image using a xarray grid with contour labels and alternate
colors.
"""
fig = Figure()
fig.grdcontour(
grid=grid,
interval=50,
annotation=200,
projection="M10c",
pen=["a1p,red", "c0.5p,black"],
label_placement="d6c",
frame=True,
)
return fig
