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test_declarative.py
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test_declarative.py
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# Copyright (c) 2019 MetPy Developers.
# Distributed under the terms of the BSD 3-Clause License.
# SPDX-License-Identifier: BSD-3-Clause
"""Test the simplified plotting interface."""
from datetime import datetime, timedelta
from io import BytesIO
import warnings
import matplotlib
import numpy as np
import pandas as pd
import pytest
from traitlets import TraitError
import xarray as xr
from metpy.cbook import get_test_data
from metpy.io import GiniFile
from metpy.io.metar import parse_metar_file
from metpy.plots import (BarbPlot, ContourPlot, FilledContourPlot, ImagePlot, MapPanel,
PanelContainer, PlotObs)
# Fixtures to make sure we have the right backend
from metpy.testing import needs_cartopy, set_agg_backend # noqa: F401, I202
from metpy.units import units
MPL_VERSION = matplotlib.__version__[:3]
@pytest.mark.mpl_image_compare(remove_text=True, tolerance=0.005)
@needs_cartopy
def test_declarative_image():
"""Test making an image plot."""
data = xr.open_dataset(GiniFile(get_test_data('NHEM-MULTICOMP_1km_IR_20151208_2100.gini')))
img = ImagePlot()
img.data = data.metpy.parse_cf('IR')
img.colormap = 'Greys_r'
panel = MapPanel()
panel.title = 'Test'
panel.plots = [img]
pc = PanelContainer()
pc.panel = panel
pc.draw()
assert panel.ax.get_title() == 'Test'
return pc.figure
@pytest.mark.mpl_image_compare(remove_text=True,
tolerance={'3.0': 0.256}.get(MPL_VERSION, 0.022))
@needs_cartopy
def test_declarative_contour():
"""Test making a contour plot."""
data = xr.open_dataset(get_test_data('narr_example.nc', as_file_obj=False))
contour = ContourPlot()
contour.data = data
contour.field = 'Temperature'
contour.level = 700 * units.hPa
contour.contours = 30
contour.linewidth = 1
contour.linecolor = 'red'
panel = MapPanel()
panel.area = 'us'
panel.proj = 'lcc'
panel.layers = ['coastline', 'borders', 'usstates']
panel.plots = [contour]
pc = PanelContainer()
pc.size = (8.0, 8)
pc.panels = [panel]
pc.draw()
return pc.figure
@pytest.mark.mpl_image_compare(remove_text=True,
tolerance={'3.0': 0.216}.get(MPL_VERSION, 0.022))
@needs_cartopy
def test_declarative_figsize():
"""Test having an all float figsize."""
data = xr.open_dataset(get_test_data('narr_example.nc', as_file_obj=False))
contour = ContourPlot()
contour.data = data
contour.field = 'Temperature'
contour.level = 700 * units.hPa
contour.contours = 30
contour.linewidth = 1
contour.linecolor = 'red'
panel = MapPanel()
panel.area = 'us'
panel.proj = 'lcc'
panel.layers = ['coastline', 'borders', 'usstates']
panel.plots = [contour]
pc = PanelContainer()
pc.size = (10.5, 10.5)
pc.panels = [panel]
pc.draw()
return pc.figure
@pytest.mark.mpl_image_compare(remove_text=True,
tolerance={'3.0': 0.328}.get(MPL_VERSION, 0.022))
@needs_cartopy
def test_declarative_contour_cam():
"""Test making a contour plot with CAM data."""
data = xr.open_dataset(get_test_data('CAM_test.nc', as_file_obj=False))
contour = ContourPlot()
contour.data = data
contour.field = 'PN'
contour.time = datetime.strptime('2020-11-29 00:00', '%Y-%m-%d %H:%M')
contour.level = 1000 * units.hPa
contour.linecolor = 'black'
contour.contours = list(range(0, 1200, 4))
panel = MapPanel()
panel.plots = [contour]
panel.layout = (1, 1, 1)
panel.layers = ['coastline', 'borders', 'states', 'land']
panel.plots = [contour]
pc = PanelContainer()
pc.panels = [panel]
pc.draw()
return pc.figure
@pytest.fixture
def fix_is_closed_polygon(monkeypatch):
"""Fix matplotlib.contour._is_closed_polygons for tests.
Needed because for Matplotlib<3.3, the internal matplotlib.contour._is_closed_polygon
uses strict floating point equality. This causes the test below to yield different
results for macOS vs. Linux/Windows.
"""
monkeypatch.setattr(matplotlib.contour, '_is_closed_polygon',
lambda X: np.allclose(X[0], X[-1], rtol=1e-10, atol=1e-13),
raising=False)
@pytest.mark.mpl_image_compare(remove_text=True,
tolerance={'3.0': 23.964}.get(MPL_VERSION, 0.0184))
@needs_cartopy
def test_declarative_contour_options(fix_is_closed_polygon):
"""Test making a contour plot."""
data = xr.open_dataset(get_test_data('narr_example.nc', as_file_obj=False))
contour = ContourPlot()
contour.data = data
contour.field = 'Temperature'
contour.level = 700 * units.hPa
contour.contours = 30
contour.linewidth = 1
contour.linecolor = 'red'
contour.linestyle = 'dashed'
contour.clabels = True
panel = MapPanel()
panel.area = 'us'
panel.proj = 'lcc'
panel.layers = ['coastline', 'borders', 'usstates']
panel.plots = [contour]
pc = PanelContainer()
pc.size = (8, 8)
pc.panels = [panel]
pc.draw()
return pc.figure
@pytest.mark.mpl_image_compare(remove_text=True,
tolerance={'3.0': 19.795}.get(MPL_VERSION, 0.0134))
@needs_cartopy
def test_declarative_contour_convert_units(fix_is_closed_polygon):
"""Test making a contour plot."""
data = xr.open_dataset(get_test_data('narr_example.nc', as_file_obj=False))
contour = ContourPlot()
contour.data = data
contour.field = 'Temperature'
contour.level = 700 * units.hPa
contour.contours = 30
contour.linewidth = 1
contour.linecolor = 'red'
contour.linestyle = 'dashed'
contour.clabels = True
contour.plot_units = 'degC'
panel = MapPanel()
panel.area = 'us'
panel.proj = 'lcc'
panel.layers = ['coastline', 'borders', 'usstates']
panel.plots = [contour]
pc = PanelContainer()
pc.size = (8, 8)
pc.panels = [panel]
pc.draw()
return pc.figure
@pytest.mark.mpl_image_compare(remove_text=True,
tolerance={'3.0': 0.051}.get(MPL_VERSION, 0))
@needs_cartopy
def test_declarative_events():
"""Test that resetting traitlets properly propagates."""
data = xr.open_dataset(get_test_data('narr_example.nc', as_file_obj=False))
contour = ContourPlot()
contour.data = data
contour.field = 'Temperature'
contour.level = 850 * units.hPa
contour.contours = 30
contour.linewidth = 1
contour.linecolor = 'red'
img = ImagePlot()
img.data = data
img.field = 'v_wind'
img.level = 700 * units.hPa
img.colormap = 'hot'
img.image_range = (3000, 5000)
panel = MapPanel()
panel.area = 'us'
panel.proj = 'lcc'
panel.layers = ['coastline', 'borders', 'states']
panel.plots = [contour, img]
pc = PanelContainer()
pc.size = (8, 8.0)
pc.panels = [panel]
pc.draw()
# Update some properties to make sure it regenerates the figure
contour.linewidth = 2
contour.linecolor = 'green'
contour.level = 700 * units.hPa
contour.field = 'Specific_humidity'
img.field = 'Geopotential_height'
img.colormap = 'plasma'
img.colorbar = 'horizontal'
return pc.figure
def test_no_field_error():
"""Make sure we get a useful error when the field is not set."""
data = xr.open_dataset(get_test_data('narr_example.nc', as_file_obj=False))
contour = ContourPlot()
contour.data = data
contour.level = 700 * units.hPa
with pytest.raises(ValueError):
contour.draw()
def test_no_field_error_barbs():
"""Make sure we get a useful error when the field is not set."""
data = xr.open_dataset(get_test_data('narr_example.nc', as_file_obj=False))
barbs = BarbPlot()
barbs.data = data
barbs.level = 700 * units.hPa
with pytest.raises(TraitError):
barbs.draw()
def test_projection_object(ccrs, cfeature):
"""Test that we can pass a custom map projection."""
data = xr.open_dataset(get_test_data('narr_example.nc', as_file_obj=False))
contour = ContourPlot()
contour.data = data
contour.level = 700 * units.hPa
contour.field = 'Temperature'
panel = MapPanel()
panel.area = (-110, -60, 25, 55)
panel.projection = ccrs.Mercator()
panel.layers = [cfeature.LAKES]
panel.plots = [contour]
pc = PanelContainer()
pc.panel = panel
pc.draw()
return pc.figure
@pytest.mark.mpl_image_compare(remove_text=True, tolerance=0.016)
def test_colorfill(cfeature):
"""Test that we can use ContourFillPlot."""
data = xr.open_dataset(get_test_data('narr_example.nc', as_file_obj=False))
contour = FilledContourPlot()
contour.data = data
contour.level = 700 * units.hPa
contour.field = 'Temperature'
contour.colormap = 'coolwarm'
contour.colorbar = 'vertical'
panel = MapPanel()
panel.area = (-110, -60, 25, 55)
panel.layers = [cfeature.STATES]
panel.plots = [contour]
pc = PanelContainer()
pc.panel = panel
pc.size = (12, 8)
pc.draw()
return pc.figure
@pytest.mark.mpl_image_compare(remove_text=True, tolerance=0.016)
def test_colorfill_horiz_colorbar(cfeature):
"""Test that we can use ContourFillPlot."""
data = xr.open_dataset(get_test_data('narr_example.nc', as_file_obj=False))
contour = FilledContourPlot()
contour.data = data
contour.level = 700 * units.hPa
contour.field = 'Temperature'
contour.colormap = 'coolwarm'
contour.colorbar = 'horizontal'
panel = MapPanel()
panel.area = (-110, -60, 25, 55)
panel.layers = [cfeature.STATES]
panel.plots = [contour]
pc = PanelContainer()
pc.panel = panel
pc.size = (8, 8)
pc.draw()
return pc.figure
@pytest.mark.mpl_image_compare(remove_text=True,
tolerance={'3.0': 0.355}.get(MPL_VERSION, 0.016))
def test_colorfill_no_colorbar(cfeature):
"""Test that we can use ContourFillPlot."""
data = xr.open_dataset(get_test_data('narr_example.nc', as_file_obj=False))
contour = FilledContourPlot()
contour.data = data
contour.level = 700 * units.hPa
contour.field = 'Temperature'
contour.colormap = 'coolwarm'
contour.colorbar = None
panel = MapPanel()
panel.area = (-110, -60, 25, 55)
panel.layers = [cfeature.STATES]
panel.plots = [contour]
pc = PanelContainer()
pc.panel = panel
pc.size = (8, 8)
pc.draw()
return pc.figure
@pytest.mark.mpl_image_compare(remove_text=True, tolerance=1.23)
@needs_cartopy
def test_global():
"""Test that we can set global extent."""
data = xr.open_dataset(GiniFile(get_test_data('NHEM-MULTICOMP_1km_IR_20151208_2100.gini')))
img = ImagePlot()
img.data = data
img.field = 'IR'
img.colorbar = None
panel = MapPanel()
panel.area = 'global'
panel.plots = [img]
pc = PanelContainer()
pc.panel = panel
pc.draw()
return pc.figure
@pytest.mark.mpl_image_compare(remove_text=True)
@needs_cartopy
def test_latlon():
"""Test our handling of lat/lon information."""
data = xr.open_dataset(get_test_data('irma_gfs_example.nc', as_file_obj=False))
img = ImagePlot()
img.data = data
img.field = 'Temperature_isobaric'
img.level = 500 * units.hPa
img.time = datetime(2017, 9, 5, 15, 0, 0)
img.colorbar = None
contour = ContourPlot()
contour.data = data
contour.field = 'Geopotential_height_isobaric'
contour.level = img.level
contour.time = img.time
panel = MapPanel()
panel.projection = 'lcc'
panel.area = 'us'
panel.plots = [img, contour]
pc = PanelContainer()
pc.panel = panel
pc.draw()
return pc.figure
@pytest.mark.mpl_image_compare(remove_text=True,
tolerance={'3.0': 0.418}.get(MPL_VERSION, 0.37))
@needs_cartopy
def test_declarative_barb_options():
"""Test making a contour plot."""
data = xr.open_dataset(get_test_data('narr_example.nc', as_file_obj=False))
barb = BarbPlot()
barb.data = data
barb.level = 300 * units.hPa
barb.field = ['u_wind', 'v_wind']
barb.skip = (10, 10)
barb.color = 'blue'
barb.pivot = 'tip'
barb.barblength = 6.5
panel = MapPanel()
panel.area = 'us'
panel.projection = 'data'
panel.layers = ['coastline', 'borders', 'usstates']
panel.plots = [barb]
pc = PanelContainer()
pc.size = (8, 8)
pc.panels = [panel]
pc.draw()
return pc.figure
@pytest.mark.mpl_image_compare(remove_text=True,
tolerance={'3.0': 0.819}.get(MPL_VERSION, 0.612))
@needs_cartopy
def test_declarative_barb_earth_relative():
"""Test making a contour plot."""
import numpy as np
data = xr.open_dataset(get_test_data('NAM_test.nc', as_file_obj=False))
contour = ContourPlot()
contour.data = data
contour.field = 'Geopotential_height_isobaric'
contour.level = 300 * units.hPa
contour.linecolor = 'red'
contour.linestyle = '-'
contour.linewidth = 2
contour.contours = np.arange(0, 20000, 120).tolist()
barb = BarbPlot()
barb.data = data
barb.level = 300 * units.hPa
barb.time = datetime(2016, 10, 31, 12)
barb.field = ['u-component_of_wind_isobaric', 'v-component_of_wind_isobaric']
barb.skip = (5, 5)
barb.color = 'black'
barb.barblength = 6.5
barb.earth_relative = False
panel = MapPanel()
panel.area = (-124, -72, 20, 53)
panel.projection = 'lcc'
panel.layers = ['coastline', 'borders', 'usstates']
panel.plots = [contour, barb]
pc = PanelContainer()
pc.size = (8, 8)
pc.panels = [panel]
pc.draw()
return pc.figure
@pytest.mark.mpl_image_compare(remove_text=True,
tolerance={'3.0': 11.481}.get(MPL_VERSION, 0.00936))
@needs_cartopy
def test_declarative_gridded_scale():
"""Test making a contour plot."""
import numpy as np
data = xr.open_dataset(get_test_data('NAM_test.nc', as_file_obj=False))
contour = ContourPlot()
contour.data = data
contour.field = 'Geopotential_height_isobaric'
contour.level = 300 * units.hPa
contour.linewidth = 2
contour.contours = np.arange(0, 2000, 12).tolist()
contour.scale = 1e-1
contour.clabels = True
panel = MapPanel()
panel.area = (-124, -72, 20, 53)
panel.projection = 'lcc'
panel.layers = ['coastline', 'borders', 'usstates']
panel.plots = [contour]
pc = PanelContainer()
pc.size = (8, 8)
pc.panels = [panel]
pc.draw()
return pc.figure
@pytest.mark.mpl_image_compare(remove_text=True, tolerance=0.607)
@needs_cartopy
def test_declarative_global_gfs():
"""Test making a global contour plot using GFS."""
data = xr.open_dataset(get_test_data('GFS_global.nc', as_file_obj=False))
cntr = ContourPlot()
cntr.data = data
cntr.time = datetime(2021, 1, 30, 12)
cntr.field = 'Geopotential_height_isobaric'
cntr.level = 300 * units.hPa
cntr.contours = np.arange(0, 100000, 120).tolist()
cntr.linecolor = 'darkblue'
cntr.linewidth = 1
panel = MapPanel()
panel.area = [-180, 180, 10, 90]
panel.projection = 'ps'
panel.layers = ['coastline']
panel.plots = [cntr]
pc = PanelContainer()
pc.size = (8, 8)
pc.panels = [panel]
pc.draw()
return pc.figure
@pytest.mark.mpl_image_compare(remove_text=True, tolerance=0.607)
@needs_cartopy
def test_declarative_barb_gfs():
"""Test making a contour plot."""
data = xr.open_dataset(get_test_data('GFS_test.nc', as_file_obj=False))
barb = BarbPlot()
barb.data = data
barb.level = 300 * units.hPa
barb.field = ['u-component_of_wind_isobaric', 'v-component_of_wind_isobaric']
barb.skip = (2, 2)
barb.earth_relative = False
panel = MapPanel()
panel.area = 'us'
panel.projection = 'data'
panel.layers = ['coastline', 'borders', 'usstates']
panel.plots = [barb]
pc = PanelContainer()
pc.size = (8, 8)
pc.panels = [panel]
pc.draw()
barb.level = 700 * units.hPa
return pc.figure
@pytest.mark.mpl_image_compare(remove_text=True, tolerance=0.466)
@needs_cartopy
def test_declarative_barb_gfs_knots():
"""Test making a contour plot."""
data = xr.open_dataset(get_test_data('GFS_test.nc', as_file_obj=False))
barb = BarbPlot()
barb.data = data
barb.level = 300 * units.hPa
barb.field = ['u-component_of_wind_isobaric', 'v-component_of_wind_isobaric']
barb.skip = (3, 3)
barb.earth_relative = False
barb.plot_units = 'knot'
panel = MapPanel()
panel.area = 'us'
panel.projection = 'data'
panel.layers = ['coastline', 'borders', 'usstates']
panel.plots = [barb]
pc = PanelContainer()
pc.size = (8, 8)
pc.panels = [panel]
pc.draw()
return pc.figure
@pytest.fixture()
def sample_obs():
"""Generate sample observational data for testing."""
return pd.DataFrame([('2020-08-05 12:00', 'KDEN', 1000, 1, 9),
('2020-08-05 12:01', 'KOKC', 1000, 2, 10),
('2020-08-05 12:00', 'KDEN', 500, 3, 11),
('2020-08-05 12:01', 'KOKC', 500, 4, 12),
('2020-08-06 13:00', 'KDEN', 1000, 5, 13),
('2020-08-06 12:59', 'KOKC', 1000, 6, 14),
('2020-08-06 13:00', 'KDEN', 500, 7, 15),
('2020-08-06 12:59', 'KOKC', 500, 8, 16)],
columns=['time', 'stid', 'pressure', 'temperature', 'dewpoint'])
def test_plotobs_subset_default_nolevel(sample_obs):
"""Test PlotObs subsetting with minimal config."""
obs = PlotObs()
obs.data = sample_obs
truth = pd.DataFrame([('2020-08-06 13:00', 'KDEN', 500, 7, 15),
('2020-08-06 12:59', 'KOKC', 500, 8, 16)],
columns=['time', 'stid', 'pressure', 'temperature', 'dewpoint'],
index=[6, 7])
pd.testing.assert_frame_equal(obs.obsdata, truth)
def test_plotobs_subset_level(sample_obs):
"""Test PlotObs subsetting based on level."""
obs = PlotObs()
obs.data = sample_obs
obs.level = 1000 * units.hPa
truth = pd.DataFrame([('2020-08-06 13:00', 'KDEN', 1000, 5, 13),
('2020-08-06 12:59', 'KOKC', 1000, 6, 14)],
columns=['time', 'stid', 'pressure', 'temperature', 'dewpoint'],
index=[4, 5])
pd.testing.assert_frame_equal(obs.obsdata, truth)
def test_plotobs_subset_level_no_units(sample_obs):
"""Test PlotObs subsetting based on unitless level."""
obs = PlotObs()
obs.data = sample_obs
obs.level = 1000
truth = pd.DataFrame([('2020-08-06 13:00', 'KDEN', 1000, 5, 13),
('2020-08-06 12:59', 'KOKC', 1000, 6, 14)],
columns=['time', 'stid', 'pressure', 'temperature', 'dewpoint'],
index=[4, 5])
pd.testing.assert_frame_equal(obs.obsdata, truth)
def test_plotobs_subset_time(sample_obs):
"""Test PlotObs subsetting for a particular time."""
obs = PlotObs()
obs.data = sample_obs
obs.level = None
obs.time = datetime(2020, 8, 6, 13)
truth = pd.DataFrame([('2020-08-06 13:00', 'KDEN', 500, 7, 15)],
columns=['time', 'stid', 'pressure', 'temperature', 'dewpoint'])
truth = truth.set_index(pd.to_datetime(truth['time']))
pd.testing.assert_frame_equal(obs.obsdata, truth)
def test_plotobs_subset_time_window(sample_obs):
"""Test PlotObs subsetting for a particular time with a window."""
# Test also using an existing index
sample_obs['time'] = pd.to_datetime(sample_obs['time'])
sample_obs.set_index('time')
obs = PlotObs()
obs.data = sample_obs
obs.level = None
obs.time = datetime(2020, 8, 5, 12)
obs.time_window = timedelta(minutes=30)
truth = pd.DataFrame([(datetime(2020, 8, 5, 12), 'KDEN', 500, 3, 11),
(datetime(2020, 8, 5, 12, 1), 'KOKC', 500, 4, 12)],
columns=['time', 'stid', 'pressure', 'temperature', 'dewpoint'])
truth = truth.set_index('time')
pd.testing.assert_frame_equal(obs.obsdata, truth)
def test_plotobs_subset_time_window_level(sample_obs):
"""Test PlotObs subsetting for a particular time with a window and a level."""
# Test also using an existing index
sample_obs['time'] = pd.to_datetime(sample_obs['time'])
sample_obs.set_index('time')
obs = PlotObs()
obs.data = sample_obs
obs.level = 1000 * units.hPa
obs.time = datetime(2020, 8, 5, 12)
obs.time_window = timedelta(minutes=30)
truth = pd.DataFrame([(datetime(2020, 8, 5, 12), 'KDEN', 1000, 1, 9),
(datetime(2020, 8, 5, 12, 1), 'KOKC', 1000, 2, 10)],
columns=['time', 'stid', 'pressure', 'temperature', 'dewpoint'])
truth = truth.set_index('time')
pd.testing.assert_frame_equal(obs.obsdata, truth)
@pytest.mark.mpl_image_compare(remove_text=True, tolerance=0)
def test_plotobs_units_with_formatter(ccrs):
"""Test using PlotObs with a field that both has units and a custom formatter."""
df = pd.read_csv(get_test_data('SFC_obs.csv', as_file_obj=False),
infer_datetime_format=True, parse_dates=['valid'])
df.units = {'alti': 'inHg'}
# Plot desired data
obs = PlotObs()
obs.data = df
obs.time = datetime(1993, 3, 12, 12)
obs.time_window = timedelta(minutes=15)
obs.level = None
obs.fields = ['alti']
obs.plot_units = ['hPa']
obs.locations = ['NE']
# Set a format for plotting MSLP
obs.formats = [lambda v: format(v * 10, '.0f')[-3:]]
obs.reduce_points = 0.75
# Panel for plot with Map features
panel = MapPanel()
panel.layout = (1, 1, 1)
panel.projection = 'lcc'
panel.area = 'in'
panel.plots = [obs]
# Bringing it all together
pc = PanelContainer()
pc.panels = [panel]
pc.size = (10, 10)
pc.draw()
return pc.figure
@pytest.mark.mpl_image_compare(remove_text=True,
tolerance={'3.0': 0.407}.get(MPL_VERSION, 0.022))
def test_declarative_sfc_obs(ccrs):
"""Test making a surface observation plot."""
data = pd.read_csv(get_test_data('SFC_obs.csv', as_file_obj=False),
infer_datetime_format=True, parse_dates=['valid'])
obs = PlotObs()
obs.data = data
obs.time = datetime(1993, 3, 12, 12)
obs.time_window = timedelta(minutes=15)
obs.level = None
obs.fields = ['tmpf']
obs.colors = ['black']
# Panel for plot with Map features
panel = MapPanel()
panel.layout = (1, 1, 1)
panel.projection = ccrs.PlateCarree()
panel.area = 'in'
panel.layers = ['states']
panel.plots = [obs]
# Bringing it all together
pc = PanelContainer()
pc.size = (10, 10)
pc.panels = [panel]
pc.draw()
return pc.figure
@pytest.mark.mpl_image_compare(remove_text=True,
tolerance={'3.0': 8.09}.get(MPL_VERSION, 0.022))
@needs_cartopy
def test_declarative_sfc_text():
"""Test making a surface observation plot with text."""
data = pd.read_csv(get_test_data('SFC_obs.csv', as_file_obj=False),
infer_datetime_format=True, parse_dates=['valid'])
obs = PlotObs()
obs.data = data
obs.time = datetime(1993, 3, 12, 12)
obs.time_window = timedelta(minutes=15)
obs.level = None
obs.fields = ['station']
obs.colors = ['black']
obs.formats = ['text']
# Panel for plot with Map features
panel = MapPanel()
panel.layout = (1, 1, 1)
panel.projection = 'lcc'
panel.area = 'in'
panel.layers = ['states']
panel.plots = [obs]
# Bringing it all together
pc = PanelContainer()
pc.size = (10, 10)
pc.panels = [panel]
pc.draw()
return pc.figure
@pytest.mark.mpl_image_compare(remove_text=True,
tolerance={'3.0': 0.407}.get(MPL_VERSION, 0.022))
def test_declarative_sfc_obs_changes(ccrs):
"""Test making a surface observation plot, changing the field."""
data = pd.read_csv(get_test_data('SFC_obs.csv', as_file_obj=False),
infer_datetime_format=True, parse_dates=['valid'])
obs = PlotObs()
obs.data = data
obs.time = datetime(1993, 3, 12, 12)
obs.level = None
obs.fields = ['tmpf']
obs.colors = ['black']
obs.time_window = timedelta(minutes=15)
# Panel for plot with Map features
panel = MapPanel()
panel.layout = (1, 1, 1)
panel.projection = ccrs.PlateCarree()
panel.area = 'in'
panel.layers = ['states']
panel.plots = [obs]
panel.title = f'Surface Observations for {obs.time}'
# Bringing it all together
pc = PanelContainer()
pc.size = (10, 10)
pc.panels = [panel]
pc.draw()
obs.fields = ['dwpf']
obs.colors = ['green']
return pc.figure
@pytest.mark.mpl_image_compare(remove_text=True,
tolerance={'3.0': 0.352}.get(MPL_VERSION, 0.00586))
def test_declarative_colored_barbs(ccrs):
"""Test making a surface plot with a colored barb (gh-1274)."""
data = pd.read_csv(get_test_data('SFC_obs.csv', as_file_obj=False),
infer_datetime_format=True, parse_dates=['valid'])
obs = PlotObs()
obs.data = data
obs.time = datetime(1993, 3, 12, 13)
obs.level = None
obs.vector_field = ('uwind', 'vwind')
obs.vector_field_color = 'red'
obs.reduce_points = .5
# Panel for plot with Map features
panel = MapPanel()
panel.layout = (1, 1, 1)
panel.projection = ccrs.PlateCarree()
panel.area = 'NE'
panel.layers = ['states']
panel.plots = [obs]
# Bringing it all together
pc = PanelContainer()
pc.size = (10, 10)
pc.panels = [panel]
pc.draw()
return pc.figure
@pytest.mark.mpl_image_compare(remove_text=True,
tolerance={'3.1': 9.771,
'3.0': 9.409}.get(MPL_VERSION, 0.00651))
def test_declarative_sfc_obs_full(ccrs):
"""Test making a full surface observation plot."""
data = pd.read_csv(get_test_data('SFC_obs.csv', as_file_obj=False),
infer_datetime_format=True, parse_dates=['valid'])
obs = PlotObs()
obs.data = data
obs.time = datetime(1993, 3, 12, 13)
obs.time_window = timedelta(minutes=15)
obs.level = None
obs.fields = ['tmpf', 'dwpf', 'emsl', 'cloud_cover', 'wxsym']
obs.locations = ['NW', 'SW', 'NE', 'C', 'W']
obs.colors = ['red', 'green', 'black', 'black', 'blue']
obs.formats = [None, None, lambda v: format(10 * v, '.0f')[-3:], 'sky_cover',
'current_weather']
obs.vector_field = ('uwind', 'vwind')
obs.reduce_points = 1
# Panel for plot with Map features
panel = MapPanel()
panel.layout = (1, 1, 1)
panel.area = (-124, -72, 20, 53)
panel.area = 'il'
panel.projection = ccrs.PlateCarree()
panel.layers = ['coastline', 'borders', 'states']
panel.plots = [obs]
# Bringing it all together
pc = PanelContainer()
pc.size = (10, 10)
pc.panels = [panel]
pc.draw()
return pc.figure
@pytest.mark.mpl_image_compare(remove_text=True, tolerance=0.08)
@needs_cartopy
def test_declarative_upa_obs():
"""Test making a full upperair observation plot."""
data = pd.read_csv(get_test_data('UPA_obs.csv', as_file_obj=False))
obs = PlotObs()
obs.data = data
obs.time = datetime(1993, 3, 14, 0)
obs.level = 500 * units.hPa
obs.fields = ['temperature', 'dewpoint', 'height']
obs.locations = ['NW', 'SW', 'NE']
obs.formats = [None, None, lambda v: format(v, '.0f')[:3]]
obs.vector_field = ('u_wind', 'v_wind')
obs.vector_field_length = 7
obs.reduce_points = 0
# Panel for plot with Map features
panel = MapPanel()
panel.layout = (1, 1, 1)
panel.area = (-124, -72, 20, 53)
panel.projection = 'lcc'
panel.layers = ['coastline', 'borders', 'states', 'land']
panel.plots = [obs]
# Bringing it all together
pc = PanelContainer()
pc.size = (15, 10)
pc.panels = [panel]
pc.draw()
obs.level = 300 * units.hPa
return pc.figure
@pytest.mark.mpl_image_compare(remove_text=True, tolerance=0.08)
@needs_cartopy
def test_declarative_upa_obs_convert_barb_units():
"""Test making a full upperair observation plot."""
data = pd.read_csv(get_test_data('UPA_obs.csv', as_file_obj=False))
data.units = ''
data.units = {'pressure': 'hPa', 'height': 'meters', 'temperature': 'degC',
'dewpoint': 'degC', 'direction': 'degrees', 'speed': 'knots',
'station': None, 'time': None, 'u_wind': 'knots', 'v_wind': 'knots',
'latitude': 'degrees', 'longitude': 'degrees'}
obs = PlotObs()
obs.data = data
obs.time = datetime(1993, 3, 14, 0)
obs.level = 500 * units.hPa
obs.fields = ['temperature', 'dewpoint', 'height']
obs.locations = ['NW', 'SW', 'NE']
obs.formats = [None, None, lambda v: format(v, '.0f')[:3]]
obs.vector_field = ('u_wind', 'v_wind')
obs.vector_field_length = 7
obs.vector_plot_units = 'm/s'
obs.reduce_points = 0