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fix lint and figure issues
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@kgoebber
kgoebber committed Jul 10, 2023
1 parent 5b6cf9e commit 357fbc8
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Showing 6 changed files with 46 additions and 64 deletions.
1 change: 1 addition & 0 deletions docs/_templates/overrides/metpy.calc.rst
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Expand Up @@ -205,6 +205,7 @@ Other
azimuth_range_to_lat_lon
find_bounding_indices
find_intersections
find_local_extrema
get_layer
get_layer_heights
get_perturbation
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7 changes: 3 additions & 4 deletions src/metpy/calc/tools.py
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Expand Up @@ -800,12 +800,11 @@ def find_local_extrema(var, nsize, extrema):
var_extrema: `xarray.DataArray`
The values of the local extrema with other values as NaNs
See Also
--------
plot_local_extrema
"""
from scipy.ndimage import maximum_filter, minimum_filter
if extrema not in ['max', 'min']:
raise ValueError('Invalid input for "extrema". Valid options are "max" or "min".')

if extrema == 'max':
extreme_val = maximum_filter(var.values, nsize, mode='nearest')
elif extrema == 'min':
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13 changes: 6 additions & 7 deletions src/metpy/plots/_util.py
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Expand Up @@ -290,7 +290,7 @@ def normalize(x):

def plot_local_extrema(ax, extreme_vals, symbol, plot_val=True, **kwargs):
"""Plot the local extreme (max/min) values of an array.
The behavior of the plotting will have the symbol horizontal/vertical alignment
be center/bottom and any value plotted will be center/top. The text size of plotted
values is 0.65 of the symbol size.
Expand All @@ -309,7 +309,7 @@ def plot_local_extrema(ax, extreme_vals, symbol, plot_val=True, **kwargs):
Returns
-------
Plots local extrema on the plot axes
Other Parameters
----------------
kwargs : `matplotlib.pyplot.Text` properties.
Expand All @@ -330,23 +330,22 @@ def plot_local_extrema(ax, extreme_vals, symbol, plot_val=True, **kwargs):
"""
defaultkwargs = {'size': 20, 'color': 'black', 'fontweight': 'bold',
'horizontalalignment': 'center', 'verticalalignment': 'center',
'transform': None}
'horizontalalignment': 'center', 'verticalalignment': 'center'}
kwargs = {**defaultkwargs, **kwargs}
if plot_val:
kwargs.pop('verticalalignment')
size = kwargs.pop('size')
textsize = size * .65

stack_vals = extreme_vals.stack(x=[extreme_vals.metpy.x.name, extreme_vals.metpy.y.name])
for extrema in stack_vals[stack_vals.notnull()]:
x = extrema[stack_vals.metpy.x.name].values
y = extrema[stack_vals.metpy.y.name].values
if plot_val:
ax.text(x, y, symbol, clip_on=True, clip_box=ax.bbox, size=size,
verticalalignment='bottom', **kwargs)
ax.text(x, y, f'{extrema.values:.0f}', clip_on=True, clip_box=ax.bbox, size=textsize,
verticalalignment='top', **kwargs)
ax.text(x, y, f'{extrema.values:.0f}', clip_on=True, clip_box=ax.bbox,
size=textsize, verticalalignment='top', **kwargs)
else:
ax.text(x, y, symbol, clip_on=True, clip_box=ax.bbox, size=size,
**kwargs)
53 changes: 27 additions & 26 deletions tests/calc/test_calc_tools.py
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Expand Up @@ -21,8 +21,7 @@
from metpy.calc.tools import (_delete_masked_points, _get_bound_pressure_height,
_greater_or_close, _less_or_close, _next_non_masked_element,
_remove_nans, azimuth_range_to_lat_lon, BASE_DEGREE_MULTIPLIER,
DIR_STRS, nominal_lat_lon_grid_deltas,
parse_grid_arguments, UND)
DIR_STRS, nominal_lat_lon_grid_deltas, parse_grid_arguments, UND)
from metpy.testing import (assert_almost_equal, assert_array_almost_equal, assert_array_equal,
get_test_data)
from metpy.units import units
Expand Down Expand Up @@ -481,42 +480,44 @@ def test_get_layer_heights_agl_bottom_no_interp():
def local_extrema_data():
"""Test data for local extrema finding."""
data = xr.DataArray(
np.array([[101628.24 , 101483.67 , 101366.06 , 101287.55 , 101233.45 ],
[101637.19 , 101515.555, 101387.164, 101280.32 , 101210.15 ],
[101581.78 , 101465.234, 101342. , 101233.22 , 101180.25 ],
[101404.31 , 101318.4 , 101233.18 , 101166.445, 101159.93 ],
[101280.586, 101238.445, 101195.234, 101183.34 , 101212.8 ]]),
name='mslp',
dims=('lat', 'lon'),
coords={'lat': xr.DataArray(np.array([45., 43., 41., 39., 37.]),
dims=('lat',), attrs={'units': 'degrees_north'}),
'lon': xr.DataArray(np.array([265., 267., 269., 271., 273.]),
dims=('lon',), attrs={'units': 'degrees_east'})
},
attrs={'units': 'Pa'}
np.array([[101628.24, 101483.67, 101366.06, 101287.55, 101233.45],
[101637.19, 101515.555, 101387.164, 101280.32, 101210.15],
[101581.78, 101465.234, 101342., 101233.22, 101180.25],
[101404.31, 101318.4, 101233.18, 101166.445, 101159.93],
[101280.586, 101238.445, 101195.234, 101183.34, 101212.8]]),
name='mslp',
dims=('lat', 'lon'),
coords={'lat': xr.DataArray(np.array([45., 43., 41., 39., 37.]),
dims=('lat',), attrs={'units': 'degrees_north'}),
'lon': xr.DataArray(np.array([265., 267., 269., 271., 273.]),
dims=('lon',), attrs={'units': 'degrees_east'})
},
attrs={'units': 'Pa'}
)
return data


def test_find_local_extrema(local_extrema_data):
"""Test find_local_extrema function for maximum."""
mslp_data = local_extrema_data
local_max = find_local_extrema(mslp_data, 3, 'max')
local_min = find_local_extrema(mslp_data, 3, 'min')
local_max = find_local_extrema(local_extrema_data, 3, 'max')
local_min = find_local_extrema(local_extrema_data, 3, 'min')

max_truth = np.array([[np.nan, np.nan, np.nan, np.nan, np.nan],
[101637.19, np.nan, np.nan, np.nan, np.nan],
[np.nan, np.nan, np.nan, np.nan, np.nan],
[np.nan, np.nan, np.nan, np.nan, np.nan],
[np.nan, np.nan, np.nan, np.nan, 101212.8]])
[101637.19, np.nan, np.nan, np.nan, np.nan],
[np.nan, np.nan, np.nan, np.nan, np.nan],
[np.nan, np.nan, np.nan, np.nan, np.nan],
[np.nan, np.nan, np.nan, np.nan, 101212.8]])
min_truth = np.array([[np.nan, np.nan, np.nan, np.nan, np.nan],
[np.nan, np.nan, np.nan, np.nan, np.nan],
[np.nan, np.nan, np.nan, np.nan, np.nan],
[np.nan, np.nan, np.nan, np.nan, 101159.93],
[np.nan, np.nan, np.nan, np.nan, np.nan]])
[np.nan, np.nan, np.nan, np.nan, np.nan],
[np.nan, np.nan, np.nan, np.nan, np.nan],
[np.nan, np.nan, np.nan, np.nan, 101159.93],
[np.nan, np.nan, np.nan, np.nan, np.nan]])
assert_array_almost_equal(local_max.data, max_truth)
assert_array_almost_equal(local_min.data, min_truth)

with pytest.raises(ValueError):
find_local_extrema(local_extrema_data, 3, 'large')


def test_lat_lon_grid_deltas_1d():
"""Test for lat_lon_grid_deltas for variable grid."""
Expand Down
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36 changes: 9 additions & 27 deletions tests/plots/test_util.py
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Expand Up @@ -5,8 +5,6 @@

from datetime import datetime

import cartopy.crs as ccrs
import cartopy.feature as cfeature
import matplotlib
import matplotlib.pyplot as plt
import numpy as np
Expand Down Expand Up @@ -166,34 +164,18 @@ def test_plot_extrema():
data = xr.open_dataset(get_test_data('GFS_test.nc', as_file_obj=False))

mslp = data.Pressure_reduced_to_MSL_msl.squeeze()
relmax2D = find_local_extrema(mslp, 10, 'max').metpy.convert_units('hPa')
relmin2D = find_local_extrema(mslp, 15, 'min').metpy.convert_units('hPa')
relmax2d = find_local_extrema(mslp, 10, 'max').metpy.convert_units('hPa')
relmin2d = find_local_extrema(mslp, 15, 'min').metpy.convert_units('hPa')

fig = plt.figure(1, figsize=(17., 11.))
ax = plt.subplot(111, projection=ccrs.LambertConformal(central_latitude=35,
central_longitude=-100))

# Set extent and plot map lines
ax.set_extent([-124., -70, 20., 60.], ccrs.PlateCarree())
ax.add_feature(cfeature.COASTLINE.with_scale('50m'),
edgecolor='grey', linewidth=0.75)
ax.add_feature(cfeature.STATES.with_scale('50m'),
edgecolor='grey', linewidth=0.5)

# Plot thickness with multiple colors
clevs = (np.arange(0, 5400, 60),
np.array([5400]),
np.arange(5460, 7000, 60))
fig = plt.figure(figsize=(8., 8.))
ax = fig.add_subplot(1, 1, 1)

# Plot MSLP
clevmslp = np.arange(800., 1120., 4)
cs2 = ax.contour(mslp.lon, mslp.lat, mslp.metpy.convert_units('hPa'),
clevmslp, colors='k', linewidths=1.25,
linestyles='solid', transform=ccrs.PlateCarree())
plt.clabel(cs2)
ax.contour(mslp.lon, mslp.lat, mslp.metpy.convert_units('hPa'),
clevmslp, colors='k', linewidths=1.25, linestyles='solid')

plot_local_extrema(ax, relmax2D, 'H', plot_val=False, color='tab:red',
transform=ccrs.PlateCarree())
plot_local_extrema(ax, relmin2D, 'L', color='tab:blue', transform=ccrs.PlateCarree())
plot_local_extrema(ax, relmax2d, 'H', plot_val=False, color='tab:red')
plot_local_extrema(ax, relmin2d, 'L', color='tab:blue')

return fig
return fig

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