diff --git a/README.rst b/README.rst index a73b86efef..81583c97e6 100644 --- a/README.rst +++ b/README.rst @@ -184,6 +184,7 @@ The required dependencies to install Py-ART in addition to Python are: * `pooch `_ * `Cython `_ * `setuptools `_ +* `cmweather `_ A working C/C++ compiler is required for some optional modules. An easy method to install these dependencies is by using a diff --git a/continuous_integration/environment-ci.yml b/continuous_integration/environment-ci.yml index 4e02278263..3cc405dd57 100644 --- a/continuous_integration/environment-ci.yml +++ b/continuous_integration/environment-ci.yml @@ -25,6 +25,7 @@ dependencies: - setuptools - shapely - ruff + - cmweather - pip - pip: - cibuildwheel diff --git a/doc/environment.yml b/doc/environment.yml index 009e2ca6be..0c10630d2b 100644 --- a/doc/environment.yml +++ b/doc/environment.yml @@ -33,6 +33,7 @@ dependencies: - sphinx-copybutton - nbsphinx - pre_commit + - cmweather - pip - pip: - pooch diff --git a/doc/source/blog_posts/2022/hail-analysis-spc.ipynb b/doc/source/blog_posts/2022/hail-analysis-spc.ipynb index cd605ef686..223ec50d36 100644 --- a/doc/source/blog_posts/2022/hail-analysis-spc.ipynb +++ b/doc/source/blog_posts/2022/hail-analysis-spc.ipynb @@ -182,7 +182,7 @@ " ax=ax,\n", " embellish=False,\n", " add_grid_lines=True,\n", - " cmap=\"pyart_ChaseSpectral\",\n", + " cmap=\"ChaseSpectral\",\n", " vmin=-20,\n", " vmax=70,\n", ")\n", @@ -1064,7 +1064,7 @@ " projection=projection,\n", " resolution=\"10m\",\n", " gatefilter=gatefilter,\n", - " cmap=\"pyart_ChaseSpectral\",\n", + " cmap=\"ChaseSpectral\",\n", " colorbar_flag=False,\n", " lat_lines=[0, 0],\n", " lon_lines=[0, 0],\n", diff --git a/environment.yml b/environment.yml index 1a37c1c719..058b5fa452 100644 --- a/environment.yml +++ b/environment.yml @@ -15,6 +15,7 @@ dependencies: - xarray - xradar - pip + - cmweather - pip: - wheel - watchdog diff --git a/examples/mapping/plot_compare_two_radars_gatemapper.py b/examples/mapping/plot_compare_two_radars_gatemapper.py index fe57ea4557..a48e069838 100644 --- a/examples/mapping/plot_compare_two_radars_gatemapper.py +++ b/examples/mapping/plot_compare_two_radars_gatemapper.py @@ -169,7 +169,7 @@ disp1 = pyart.graph.RadarMapDisplay(radar_se) disp1.plot_ppi_map( "reflectivity_bias", - cmap="pyart_balance", + cmap="balance", title="Reflectivity Difference \n XSAPR Southwest - XSPAR Southeast", sweep=1, ax=ax, @@ -215,7 +215,7 @@ # Create a 1-1 comparison x, y = np.meshgrid((bins[:-1] + bins[1:]) / 2.0, (bins[:-1] + bins[1:]) / 2.0) -c = plt.pcolormesh(x, y, np.log10(hist.T), cmap="pyart_HomeyerRainbow") +c = plt.pcolormesh(x, y, np.log10(hist.T), cmap="HomeyerRainbow") # Add a colorbar and labels plt.colorbar(c, label="$log_{10}$ counts") diff --git a/examples/plotting/plot_choose_a_colormap.py b/examples/plotting/plot_choose_a_colormap.py index acc1e9880d..e0a1aa5230 100644 --- a/examples/plotting/plot_choose_a_colormap.py +++ b/examples/plotting/plot_choose_a_colormap.py @@ -21,7 +21,7 @@ ###################################### # **Plot the available colormaps** # -# Let's see which colormaps are available directly from Py-ART! +# Let's see which colormaps are available in Py-ART from the colormap package cmweather! # We use a helper function from matplotlib to plot this. # Setup some helper functions and ranges to visualize our colormaps, from matplotlib @@ -39,11 +39,11 @@ def plot_color_gradients(cmap_category, cmap_list): axs[0].set_title(cmap_category + " Colormaps", fontsize=14) for ax, cmap_name in zip(axs, cmap_list): - ax.imshow(gradient, aspect="auto", cmap=f"pyart_{cmap_name}") + ax.imshow(gradient, aspect="auto", cmap=f"{cmap_name}") ax.text( -0.01, 0.5, - f"pyart_{cmap_name}", + f"{cmap_name}", va="center", ha="right", fontsize=10, @@ -157,14 +157,10 @@ def plot_color_gradients(cmap_category, cmap_list): ###################################### # **Plot Using a Colormap from Py-ART** # -# Let's use one of our Py-ART's colorbars now! We need -# to remember to add the pyart_ string in front of the -# colormap, as shown below. +# Let's use one of our cmweather's colorbars now! # Setup a display to plot the data display = pyart.graph.RadarDisplay(radar) -# Start by plotting a regular matplotlib colormap (Spectral_r) -display.plot( - "reflectivity_horizontal", vmin=-32, vmax=64.0, cmap="pyart_HomeyerRainbow" -) +# Now let's plot with a CVD-friendly colormap (HomeyerRainbow) +display.plot("reflectivity_horizontal", vmin=-32, vmax=64.0, cmap="HomeyerRainbow") diff --git a/examples/plotting/plot_cross_section.py b/examples/plotting/plot_cross_section.py index aafa9e3b79..2820a270c2 100644 --- a/examples/plotting/plot_cross_section.py +++ b/examples/plotting/plot_cross_section.py @@ -53,7 +53,7 @@ display.plot_grid( "corrected_reflectivity_horizontal", ax=ax1, - cmap="pyart_HomeyerRainbow", + cmap="HomeyerRainbow", vmin=-20, vmax=70, ) @@ -71,7 +71,7 @@ start, end, x_axis="lat", - cmap="pyart_HomeyerRainbow", + cmap="HomeyerRainbow", vmin=-20, vmax=70, ) diff --git a/examples/plotting/plot_modify_colorbar.py b/examples/plotting/plot_modify_colorbar.py index 9451f897ca..4098b20b68 100644 --- a/examples/plotting/plot_modify_colorbar.py +++ b/examples/plotting/plot_modify_colorbar.py @@ -50,7 +50,7 @@ vmax=60, embellish=False, norm=None, - cmap="pyart_HomeyerRainbow", + cmap="HomeyerRainbow", ) # Add gridlines @@ -99,7 +99,7 @@ vmax=60, embellish=False, norm=None, - cmap="pyart_HomeyerRainbow", + cmap="HomeyerRainbow", ) # Add gridlines diff --git a/examples/plotting/plot_ppi_mdv.py b/examples/plotting/plot_ppi_mdv.py index 706495bf3a..4095440a5e 100644 --- a/examples/plotting/plot_ppi_mdv.py +++ b/examples/plotting/plot_ppi_mdv.py @@ -23,8 +23,6 @@ display = pyart.graph.RadarDisplay(radar) fig = plt.figure(figsize=[5, 5]) ax = fig.add_subplot(111) -display.plot( - "reflectivity", 0, vmin=-16.0, vmax=64, title="PPI", cmap="pyart_HomeyerRainbow" -) +display.plot("reflectivity", 0, vmin=-16.0, vmax=64, title="PPI", cmap="HomeyerRainbow") display.set_limits(ylim=[-150, 150], xlim=[-150, 150]) plt.show() diff --git a/examples/plotting/plot_rhi_cfradial_singlescan.py b/examples/plotting/plot_rhi_cfradial_singlescan.py index fcf9ea7c4e..ecc1b87503 100755 --- a/examples/plotting/plot_rhi_cfradial_singlescan.py +++ b/examples/plotting/plot_rhi_cfradial_singlescan.py @@ -39,7 +39,7 @@ mask_outside=True, title="RHI", axislabels=(xlabel, ylabel), - cmap="pyart_HomeyerRainbow", + cmap="HomeyerRainbow", colorbar_label=colorbar_label, ax=ax, ) diff --git a/examples/plotting/plot_rhi_data_overlay.py b/examples/plotting/plot_rhi_data_overlay.py index 2e6a901e29..be8646941e 100644 --- a/examples/plotting/plot_rhi_data_overlay.py +++ b/examples/plotting/plot_rhi_data_overlay.py @@ -29,9 +29,6 @@ ax = fig.add_subplot(111) # plot velocity -# cmap is the color ramp being used in this case blue to red no 18 -# https://github.com/ARM-DOE/pyart/blob/master/pyart/graph/cm.py -# for more information display.plot( "velocity", @@ -40,7 +37,7 @@ vmax=20.0, fig=fig, ax=ax, - cmap="pyart_BuDRd18", + cmap="balance", colorbar_label="Velocity (m/s)", ) diff --git a/examples/plotting/plot_rhi_two_panel.py b/examples/plotting/plot_rhi_two_panel.py index 9d6b84ae89..979001f22b 100755 --- a/examples/plotting/plot_rhi_two_panel.py +++ b/examples/plotting/plot_rhi_two_panel.py @@ -26,7 +26,7 @@ # Fields to plot and ranges fields_to_plot = ["reflectivity_horizontal", "mean_doppler_velocity"] ranges = [(-20, 20), (-17.0, 17.0)] -cmaps = ["pyart_HomeyerRainbow", "pyart_balance"] +cmaps = ["HomeyerRainbow", "balance"] # Plot the data nplots = len(fields_to_plot) diff --git a/examples/plotting/plot_three_panel_gridmapdisplay.py b/examples/plotting/plot_three_panel_gridmapdisplay.py index f256e8d392..3d42792997 100644 --- a/examples/plotting/plot_three_panel_gridmapdisplay.py +++ b/examples/plotting/plot_three_panel_gridmapdisplay.py @@ -49,14 +49,14 @@ vmax=vmax, ax=ax1, projection=projection, - cmap="pyart_HomeyerRainbow", + cmap="HomeyerRainbow", ) display.plot_crosshairs(lon=lon, lat=lat) # Panel 2: longitude slice ax2 = fig.add_axes(x_cut_panel_axes) display.plot_longitude_slice( - "REF", lon=lon, lat=lat, ax=ax2, vmin=vmin, vmax=vmax, cmap="pyart_HomeyerRainbow" + "REF", lon=lon, lat=lat, ax=ax2, vmin=vmin, vmax=vmax, cmap="HomeyerRainbow" ) ax2.set_ylim([0, 15]) @@ -65,7 +65,7 @@ # Panel 3: latitude slice ax3 = fig.add_axes(y_cut_panel_axes) display.plot_latitude_slice( - "REF", lon=lon, lat=lat, ax=ax3, vmin=vmin, vmax=vmax, cmap="pyart_HomeyerRainbow" + "REF", lon=lon, lat=lat, ax=ax3, vmin=vmin, vmax=vmax, cmap="HomeyerRainbow" ) ax3.set_ylim([0, 15]) ax3.set_xlim([-50, 50]) diff --git a/examples/plotting/radar-cross-section.ipynb b/examples/plotting/radar-cross-section.ipynb index e5389e7d99..e0988480f8 100644 --- a/examples/plotting/radar-cross-section.ipynb +++ b/examples/plotting/radar-cross-section.ipynb @@ -83,7 +83,7 @@ "display.plot_grid(\n", " \"corrected_reflectivity_horizontal\",\n", " ax=ax1,\n", - " cmap=\"pyart_HomeyerRainbow\",\n", + " cmap=\"HomeyerRainbow\",\n", " vmin=-20,\n", " vmax=70,\n", ")\n", @@ -98,7 +98,7 @@ " start,\n", " end,\n", " x_axis=\"lat\",\n", - " cmap=\"pyart_HomeyerRainbow\",\n", + " cmap=\"HomeyerRainbow\",\n", " vmin=-20,\n", " vmax=70,\n", ")" @@ -166,7 +166,7 @@ " start,\n", " end,\n", " x_axis=\"lon\",\n", - " cmap=\"pyart_HomeyerRainbow\",\n", + " cmap=\"HomeyerRainbow\",\n", " vmin=-20,\n", " vmax=70,\n", ")" @@ -297,7 +297,7 @@ "ds.corrected_reflectivity_horizontal.isel(z=0).plot(\n", " x=\"lon\",\n", " y=\"lat\",\n", - " cmap=\"pyart_HomeyerRainbow\",\n", + " cmap=\"HomeyerRainbow\",\n", " vmin=-20,\n", " vmax=60,\n", " ax=ax,\n", @@ -318,7 +318,7 @@ "fig = plt.figure()\n", "ax = plt.subplot(111)\n", "ds.corrected_reflectivity_horizontal.isel(z=0).plot(\n", - " x=\"lon\", y=\"lat\", cmap=\"pyart_HomeyerRainbow\", vmin=-20, vmax=60, ax=ax\n", + " x=\"lon\", y=\"lat\", cmap=\"HomeyerRainbow\", vmin=-20, vmax=60, ax=ax\n", ")\n", "ax.scatter(start[1], start[0], label=\"Start Point\", color=\"tab:blue\")\n", "ax.scatter(end[1], end[0], label=\"Start Point\", color=\"k\")\n", @@ -346,7 +346,7 @@ "fig = plt.figure(figsize=(10, 8))\n", "title = \"($^\\circ$N)\"\n", "cross.corrected_reflectivity_horizontal.plot(\n", - " cmap=\"pyart_HomeyerRainbow\",\n", + " cmap=\"HomeyerRainbow\",\n", " x=None,\n", " y=\"z\",\n", " vmin=-20,\n", @@ -437,7 +437,7 @@ " grid, \"corrected_reflectivity_horizontal\", start, end\n", ")\n", "cross.corrected_reflectivity_horizontal.plot(\n", - " cmap=\"pyart_HomeyerRainbow\",\n", + " cmap=\"HomeyerRainbow\",\n", " x=None,\n", " y=\"z\",\n", " vmin=-20,\n", diff --git a/examples/retrieve/hydrometeor-class.ipynb b/examples/retrieve/hydrometeor-class.ipynb index 5421256d03..fdbbfe509e 100644 --- a/examples/retrieve/hydrometeor-class.ipynb +++ b/examples/retrieve/hydrometeor-class.ipynb @@ -80,7 +80,7 @@ " vmax=60.0,\n", " ax=ax[0],\n", " colorbar_label=\"Raw Ref\",\n", - " cmap=\"pyart_HomeyerRainbow\",\n", + " cmap=\"HomeyerRainbow\",\n", ")\n", "display.plot_ppi(\n", " \"corrected_reflectivity_horizontal\",\n", @@ -88,7 +88,7 @@ " vmin=0,\n", " vmax=60.0,\n", " gatefilter=gtfilter,\n", - " cmap=\"pyart_HomeyerRainbow\",\n", + " cmap=\"HomeyerRainbow\",\n", " ax=ax[1],\n", " colorbar_label=\"Filtered Ref\",\n", ")\n", diff --git a/examples/retrieve/plot_composite_reflectivity.py b/examples/retrieve/plot_composite_reflectivity.py index 7f548fb6cc..015c9e9cc3 100644 --- a/examples/retrieve/plot_composite_reflectivity.py +++ b/examples/retrieve/plot_composite_reflectivity.py @@ -38,5 +38,5 @@ ax2 = plt.subplot(122) composite_display = pyart.graph.RadarDisplay(compz) composite_display.plot( - "composite_reflectivity", ax=ax2, vmin=-20, vmax=80, cmap="pyart_HomeyerRainbow" + "composite_reflectivity", ax=ax2, vmin=-20, vmax=80, cmap="HomeyerRainbow" ) diff --git a/pyart/default_config.py b/pyart/default_config.py index 0adf11a187..fbe5160a74 100644 --- a/pyart/default_config.py +++ b/pyart/default_config.py @@ -1410,54 +1410,54 @@ def spectrum_width_limit(container=None, selection=0): DEFAULT_FIELD_COLORMAP = { # field name : colormap - reflectivity: "pyart_HomeyerRainbow", - corrected_reflectivity: "pyart_HomeyerRainbow", - total_power: "pyart_HomeyerRainbow", - signal_to_noise_ratio: "pyart_Carbone17", - velocity: "pyart_BuDRd18", - corrected_velocity: "pyart_BuDRd18", - simulated_velocity: "pyart_BuDRd18", - eastward_wind_component: "pyart_BuDRd18", - northward_wind_component: "pyart_BuDRd18", - vertical_wind_component: "pyart_BuDRd18", - spectrum_width: "pyart_NWS_SPW", - normalized_coherent_power: "pyart_Carbone17", - differential_reflectivity: "pyart_RefDiff", - corrected_differential_reflectivity: "pyart_RefDiff", - clutter_filter_power_removed: "pyart_RefDiff", - cross_correlation_ratio: "pyart_RefDiff", - logarithmic_cross_correlation_ratio: "pyart_RefDiff", - differential_phase: "pyart_Wild25", - unfolded_differential_phase: "pyart_Wild25", - corrected_differential_phase: "pyart_Wild25", - specific_differential_phase: "pyart_Theodore16", - corrected_specific_differential_phase: "pyart_Theodore16", - linear_depolarization_ratio: "pyart_SCook18", - linear_depolarization_ratio_h: "pyart_SCook18", - linear_depolarization_ratio_v: "pyart_SCook18", - circular_depolarization_ratio: "pyart_SCook18", - rain_rate: "pyart_RRate11", - radar_estimated_rain_rate: "pyart_RRate11", - radar_echo_classification: "pyart_LangRainbow12", - specific_attenuation: "pyart_Carbone17", - differential_phase_texture: "pyart_BlueBrown11", - height: "pyart_SCook18", - interpolated_profile: "pyart_SCook18", - noisedBZ_hh: "pyart_HomeyerRainbow", - noisedBZ_vv: "pyart_HomeyerRainbow", + reflectivity: "HomeyerRainbow", + corrected_reflectivity: "HomeyerRainbow", + total_power: "HomeyerRainbow", + signal_to_noise_ratio: "Carbone17", + velocity: "BuDRd18", + corrected_velocity: "BuDRd18", + simulated_velocity: "BuDRd18", + eastward_wind_component: "BuDRd18", + northward_wind_component: "BuDRd18", + vertical_wind_component: "BuDRd18", + spectrum_width: "NWS_SPW", + normalized_coherent_power: "Carbone17", + differential_reflectivity: "RefDiff", + corrected_differential_reflectivity: "RefDiff", + clutter_filter_power_removed: "RefDiff", + cross_correlation_ratio: "RefDiff", + logarithmic_cross_correlation_ratio: "RefDiff", + differential_phase: "Wild25", + unfolded_differential_phase: "Wild25", + corrected_differential_phase: "Wild25", + specific_differential_phase: "Theodore16", + corrected_specific_differential_phase: "Theodore16", + linear_depolarization_ratio: "SCook18", + linear_depolarization_ratio_h: "SCook18", + linear_depolarization_ratio_v: "SCook18", + circular_depolarization_ratio: "SCook18", + rain_rate: "RRate11", + radar_estimated_rain_rate: "RRate11", + radar_echo_classification: "LangRainbow12", + specific_attenuation: "Carbone17", + differential_phase_texture: "BlueBrown11", + height: "SCook18", + interpolated_profile: "SCook18", + noisedBZ_hh: "HomeyerRainbow", + noisedBZ_vv: "HomeyerRainbow", # Additional reflectivity like fields - "CZ": "pyart_HomeyerRainbow", - "DZ": "pyart_HomeyerRainbow", - "AZ": "pyart_HomeyerRainbow", - "Z": "pyart_HomeyerRainbow", - "dbz": "pyart_HomeyerRainbow", - "DBZ": "pyart_HomeyerRainbow", - "dBZ": "pyart_HomeyerRainbow", - "DBZH": "pyart_HomeyerRainbow", - "DBZ_S": "pyart_HomeyerRainbow", - "DBZ_K": "pyart_HomeyerRainbow", - "reflectivity_horizontal": "pyart_HomeyerRainbow", - "corr_reflectivity": "pyart_HomeyerRainbow", + "CZ": "HomeyerRainbow", + "DZ": "HomeyerRainbow", + "AZ": "HomeyerRainbow", + "Z": "HomeyerRainbow", + "dbz": "HomeyerRainbow", + "DBZ": "HomeyerRainbow", + "dBZ": "HomeyerRainbow", + "DBZH": "HomeyerRainbow", + "DBZ_S": "HomeyerRainbow", + "DBZ_K": "HomeyerRainbow", + "reflectivity_horizontal": "HomeyerRainbow", + "corr_reflectivity": "HomeyerRainbow", } # map each field to a limit or a limit function diff --git a/pyart/graph/__init__.py b/pyart/graph/__init__.py index 8de2949cf6..1b482b7164 100644 --- a/pyart/graph/__init__.py +++ b/pyart/graph/__init__.py @@ -5,7 +5,7 @@ colormaps for plotting. Available colormaps, reversed versions (_r) are also provided, these -colormaps are available within matplotlib with names 'pyart_COLORMAP': +colormaps are available within matplotlib with names 'COLORMAP': * BlueBrown10 * BlueBrown11 @@ -54,7 +54,9 @@ """ -from . import cm, cm_colorblind # noqa +# Import colormaps from cmweather +import cmweather # noqa: F401 + from .convstrat_scheme_plot import plot_convstrat_scheme # noqa from .gridmapdisplay import GridMapDisplay # noqa from .gridmapdisplay_basemap import GridMapDisplayBasemap # noqa diff --git a/pyart/graph/_cm.py b/pyart/graph/_cm.py deleted file mode 100644 index 32529dd863..0000000000 --- a/pyart/graph/_cm.py +++ /dev/null @@ -1,1917 +0,0 @@ -""" -Data for radar related colormaps. - -""" - -# The data for the colormaps in this file were adapted from those found in -# ctables.py of the Deprecated_Metpy package by Patrick Marsh and Ryan May. -# https://github.com/pmarshwx/Deprecated_Metpy -# LangRainbow12 was developed separately by Timothy Lang - -# Standard National Weather Service Radar Colortables -_NWSRef_data = { - "blue": [ - (0.0, 0.92549019607843142, 0.92549019607843142), - (0.07142857, 0.96470588235294119, 0.96470588235294119), - (0.14285714, 0.96470588235294119, 0.96470588235294119), - (0.21428571, 0.0, 0.0), - (0.28571429, 0.0, 0.0), - (0.35714286, 0.0, 0.0), - (0.42857143, 0.0, 0.0), - (0.50000000, 0.0, 0.0), - (0.57142857, 0.0, 0.0), - (0.64285714, 0.0, 0.0), - (0.71428571, 0.0, 0.0), - (0.78571429, 0.0, 0.0), - (0.85714286, 1.0, 1.0), - (0.92857143, 0.78823529411764703, 0.78823529411764703), - (1.0, 0.0, 0.0), - ], - "green": [ - (0.0, 0.92549019607843142, 0.92549019607843142), - (0.07142857, 0.62745098039215685, 0.62745098039215685), - (0.14285714, 0.0, 0.0), - (0.21428571, 1.0, 1.0), - (0.28571429, 0.78431372549019607, 0.78431372549019607), - (0.35714286, 0.56470588235294117, 0.56470588235294117), - (0.42857143, 1.0, 1.0), - (0.50000000, 0.75294117647058822, 0.75294117647058822), - (0.57142857, 0.56470588235294117, 0.56470588235294117), - (0.64285714, 0.0, 0.0), - (0.71428571, 0.0, 0.0), - (0.78571429, 0.0, 0.0), - (0.85714286, 0.0, 0.0), - (0.92857143, 0.33333333333333331, 0.33333333333333331), - (1.0, 0.0, 0.0), - ], - "red": [ - (0.0, 0.0, 0.0), - (0.07142857, 0.0039215686274509803, 0.0039215686274509803), - (0.14285714, 0.0, 0.0), - (0.21428571, 0.0, 0.0), - (0.28571429, 0.0, 0.0), - (0.35714286, 0.0, 0.0), - (0.42857143, 1.0, 1.0), - (0.50000000, 0.90588235294117647, 0.90588235294117647), - (0.57142857, 1.0, 1.0), - (0.64285714, 1.0, 1.0), - (0.71428571, 0.83921568627450982, 0.83921568627450982), - (0.78571429, 0.75294117647058822, 0.75294117647058822), - (0.85714286, 1.0, 1.0), - (0.92857143, 0.59999999999999998, 0.59999999999999998), - (1.0, 0.0, 0.0), - ], -} - -_NWSVel_data = { - "blue": [ - (0.0, 0.62352941176470589, 0.62352941176470589), - (0.071428571428571425, 0.0, 0.0), - (0.14285714285714285, 0.0, 0.0), - (0.21428571428571427, 0.0, 0.0), - (0.2857142857142857, 0.0, 0.0), - (0.3571428571428571, 0.0, 0.0), - (0.42857142857142855, 0.0, 0.0), - (0.5, 0.46666666666666667, 0.46666666666666667), - (0.5714285714285714, 0.46666666666666667, 0.46666666666666667), - (0.64285714285714279, 0.0, 0.0), - (0.71428571428571419, 0.0, 0.0), - (0.7857142857142857, 0.0, 0.0), - (0.8571428571428571, 0.0, 0.0), - (0.92857142857142849, 0.0, 0.0), - (1.0, 0.0, 0.0), - ], - "green": [ - (0.0, 0.0, 0.0), - (0.071428571428571425, 1.0, 1.0), - (0.14285714285714285, 0.90980392156862744, 0.90980392156862744), - (0.21428571428571427, 0.78431372549019607, 0.78431372549019607), - (0.2857142857142857, 0.69019607843137254, 0.69019607843137254), - (0.3571428571428571, 0.56470588235294117, 0.56470588235294117), - (0.42857142857142855, 0.4392156862745098, 0.4392156862745098), - (0.5, 0.59215686274509804, 0.59215686274509804), - (0.5714285714285714, 0.46666666666666667, 0.46666666666666667), - (0.64285714285714279, 0.0, 0.0), - (0.71428571428571419, 0.0, 0.0), - (0.7857142857142857, 0.0, 0.0), - (0.8571428571428571, 0.0, 0.0), - (0.92857142857142849, 0.0, 0.0), - (1.0, 0.0, 0.0), - ], - "red": [ - (0.0, 0.56470588235294117, 0.56470588235294117), - (0.071428571428571425, 0.0, 0.0), - (0.14285714285714285, 0.0, 0.0), - (0.21428571428571427, 0.0, 0.0), - (0.2857142857142857, 0.0, 0.0), - (0.3571428571428571, 0.0, 0.0), - (0.42857142857142855, 0.0, 0.0), - (0.5, 0.46666666666666667, 0.46666666666666667), - (0.5714285714285714, 0.59215686274509804, 0.59215686274509804), - (0.64285714285714279, 0.50196078431372548, 0.50196078431372548), - (0.71428571428571419, 0.62745098039215685, 0.62745098039215685), - (0.7857142857142857, 0.72156862745098038, 0.72156862745098038), - (0.8571428571428571, 0.84705882352941175, 0.84705882352941175), - (0.92857142857142849, 0.93333333333333335, 0.93333333333333335), - (1.0, 1.0, 1.0), - ], -} - -_NWS_SPW_data = { - "blue": [ - (0.0, 0.62352941176470589, 0.62352941176470589), - (0.16666666666666666, 0.46274509803921571, 0.46274509803921571), - (0.33333333333333331, 0.61176470588235299, 0.61176470588235299), - (0.5, 0.0, 0.0), - (0.66666666666666663, 0.0, 0.0), - (0.83333333333333326, 0.0, 0.0), - (1.0, 0.0, 0.0), - ], - "green": [ - (0.0, 0.0, 0.0), - (0.16666666666666666, 0.46274509803921571, 0.46274509803921571), - (0.33333333333333331, 0.61176470588235299, 0.61176470588235299), - (0.5, 0.73333333333333328, 0.73333333333333328), - (0.66666666666666663, 0.0, 0.0), - (0.83333333333333326, 0.4392156862745098, 0.4392156862745098), - (1.0, 1.0, 1.0), - ], - "red": [ - (0.0, 0.56470588235294117, 0.56470588235294117), - (0.16666666666666666, 0.46274509803921571, 0.46274509803921571), - (0.33333333333333331, 0.61176470588235299, 0.61176470588235299), - (0.5, 0.0, 0.0), - (0.66666666666666663, 1.0, 1.0), - (0.83333333333333326, 0.81568627450980391, 0.81568627450980391), - (1.0, 1.0, 1.0), - ], -} - -# Colors maps from Patrick Marsh (http://www.pmarshwx.com/) -_RefDiff_data = { - "blue": [ - (0.0, 1.0, 1.0), - (0.1111111111111111, 1.0, 1.0), - (0.22222222222222221, 1.0, 1.0), - (0.33333333333333331, 0.0, 0.0), - (0.44444444444444442, 0.0, 0.0), - (0.55555555555555558, 0.0, 0.0), - (0.66666666666666663, 0.0, 0.0), - (0.77777777777777768, 0.0, 0.0), - (0.88888888888888884, 0.0, 0.0), - (1.0, 1.0, 1.0), - ], - "green": [ - (0.0, 0.0, 0.0), - (0.1111111111111111, 0.66666666666666663, 0.66666666666666663), - (0.22222222222222221, 1.0, 1.0), - (0.33333333333333331, 0.66666666666666663, 0.66666666666666663), - (0.44444444444444442, 1.0, 1.0), - (0.55555555555555558, 1.0, 1.0), - (0.66666666666666663, 0.66666666666666663, 0.66666666666666663), - (0.77777777777777768, 0.33333333333333331, 0.33333333333333331), - (0.88888888888888884, 0.0, 0.0), - (1.0, 0.0, 0.0), - ], - "red": [ - (0.0, 0.0, 0.0), - (0.1111111111111111, 0.0, 0.0), - (0.22222222222222221, 0.0, 0.0), - (0.33333333333333331, 0.0, 0.0), - (0.44444444444444442, 0.0, 0.0), - (0.55555555555555558, 1.0, 1.0), - (0.66666666666666663, 1.0, 1.0), - (0.77777777777777768, 1.0, 1.0), - (0.88888888888888884, 1.0, 1.0), - (1.0, 1.0, 1.0), - ], -} - -# Colortables from SoloII -_Carbone11_data = { - 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(0.5, 0.90588235294117647, 0.90588235294117647), - (0.60000000000000009, 0.86274509803921573, 0.86274509803921573), - (0.70000000000000007, 0.69019607843137254, 0.69019607843137254), - (0.80000000000000004, 0.4392156862745098, 0.4392156862745098), - (0.90000000000000002, 0.4392156862745098, 0.4392156862745098), - (1.0, 0.12549019607843137, 0.12549019607843137), - ], - "red": [ - (0.0, 0.53725490196078429, 0.53725490196078429), - (0.10000000000000001, 0.46274509803921571, 0.46274509803921571), - (0.20000000000000001, 0.43137254901960786, 0.43137254901960786), - (0.30000000000000004, 0.12156862745098039, 0.12156862745098039), - (0.40000000000000002, 0.63529411764705879, 0.63529411764705879), - (0.5, 0.90588235294117647, 0.90588235294117647), - (0.60000000000000009, 0.96470588235294119, 0.96470588235294119), - (0.70000000000000007, 0.94117647058823528, 0.94117647058823528), - (0.80000000000000004, 0.63137254901960782, 0.63137254901960782), - (0.90000000000000002, 0.8901960784313725, 0.8901960784313725), - (1.0, 0.792156862745098, 0.792156862745098), - ], -} - -_Carbone17_data = { - "blue": [ - (0.0, 0.55686274509803924, 0.55686274509803924), - (0.0625, 0.61960784313725492, 0.61960784313725492), - (0.125, 0.88627450980392153, 0.88627450980392153), - (0.1875, 0.80784313725490198, 0.80784313725490198), - (0.25, 0.062745098039215685, 0.062745098039215685), - (0.3125, 0.12156862745098039, 0.12156862745098039), - (0.375, 0.42745098039215684, 0.42745098039215684), - (0.4375, 0.63137254901960782, 0.63137254901960782), - (0.5, 0.90588235294117647, 0.90588235294117647), - (0.5625, 0.047058823529411764, 0.047058823529411764), - (0.625, 0.10980392156862745, 0.10980392156862745), - (0.6875, 0.20784313725490197, 0.20784313725490197), - (0.75, 0.28627450980392155, 0.28627450980392155), - (0.8125, 0.3411764705882353, 0.3411764705882353), - (0.875, 0.46666666666666667, 0.46666666666666667), - (0.9375, 0.41568627450980394, 0.41568627450980394), - (1.0, 0.25098039215686274, 0.25098039215686274), - ], - "green": [ - (0.0, 0.062745098039215685, 0.062745098039215685), - (0.0625, 0.11764705882352941, 0.11764705882352941), - (0.125, 0.36078431372549019, 0.36078431372549019), - (0.1875, 0.68235294117647061, 0.68235294117647061), - (0.25, 0.54117647058823526, 0.54117647058823526), - (0.3125, 0.65098039215686276, 0.65098039215686276), - (0.375, 0.7686274509803922, 0.7686274509803922), - (0.4375, 0.81568627450980391, 0.81568627450980391), - (0.5, 0.90196078431372551, 0.90196078431372551), - (0.5625, 0.85882352941176465, 0.85882352941176465), - (0.625, 0.74901960784313726, 0.74901960784313726), - (0.6875, 0.63921568627450975, 0.63921568627450975), - (0.75, 0.53333333333333333, 0.53333333333333333), - (0.8125, 0.4392156862745098, 0.4392156862745098), - (0.875, 0.37254901960784315, 0.37254901960784315), - (0.9375, 0.27450980392156865, 0.27450980392156865), - (1.0, 0.15294117647058825, 0.15294117647058825), - ], - "red": [ - (0.0, 0.53725490196078429, 0.53725490196078429), - (0.0625, 0.29019607843137257, 0.29019607843137257), - (0.125, 0.45882352941176469, 0.45882352941176469), - (0.1875, 0.43529411764705883, 0.43529411764705883), - (0.25, 0.062745098039215685, 0.062745098039215685), - (0.3125, 0.12156862745098039, 0.12156862745098039), - (0.375, 0.42745098039215684, 0.42745098039215684), - (0.4375, 0.63137254901960782, 0.63137254901960782), - (0.5, 0.90588235294117647, 0.90588235294117647), - (0.5625, 0.98039215686274506, 0.98039215686274506), - (0.625, 0.98039215686274506, 0.98039215686274506), - (0.6875, 0.8784313725490196, 0.8784313725490196), - (0.75, 0.74901960784313726, 0.74901960784313726), - (0.8125, 0.62745098039215685, 0.62745098039215685), - (0.875, 0.87058823529411766, 0.87058823529411766), - (0.9375, 0.94117647058823528, 0.94117647058823528), - (1.0, 0.80784313725490198, 0.80784313725490198), - ], -} - -_RRate11_data = { - "blue": [ - (0.0, 0.50196078431372548, 0.50196078431372548), - (0.10000000000000001, 0.62745098039215685, 0.62745098039215685), - (0.20000000000000001, 0.93333333333333335, 0.93333333333333335), - (0.30000000000000004, 0.027450980392156862, 0.027450980392156862), - (0.40000000000000002, 0.34509803921568627, 0.34509803921568627), - (0.5, 0.92156862745098034, 0.92156862745098034), - (0.60000000000000009, 0.031372549019607843, 0.031372549019607843), - (0.70000000000000007, 0.15294117647058825, 0.15294117647058825), - (0.80000000000000004, 0.30588235294117649, 0.30588235294117649), - (0.90000000000000002, 0.43137254901960786, 0.43137254901960786), - (1.0, 0.23529411764705882, 0.23529411764705882), - ], - "green": [ - (0.0, 0.0, 0.0), - (0.10000000000000001, 0.17254901960784313, 0.17254901960784313), - (0.20000000000000001, 0.36078431372549019, 0.36078431372549019), - (0.30000000000000004, 0.52156862745098043, 0.52156862745098043), - (0.40000000000000002, 0.74509803921568629, 0.74509803921568629), - (0.5, 0.93333333333333335, 0.93333333333333335), - (0.60000000000000009, 0.85490196078431369, 0.85490196078431369), - (0.70000000000000007, 0.60784313725490191, 0.60784313725490191), - (0.80000000000000004, 0.38823529411764707, 0.38823529411764707), - (0.90000000000000002, 0.3843137254901961, 0.3843137254901961), - (1.0, 0.062745098039215685, 0.062745098039215685), - ], - "red": [ - (0.0, 0.50196078431372548, 0.50196078431372548), - (0.10000000000000001, 0.29803921568627451, 0.29803921568627451), - (0.20000000000000001, 0.42352941176470588, 0.42352941176470588), - (0.30000000000000004, 0.035294117647058823, 0.035294117647058823), - (0.40000000000000002, 0.36470588235294116, 0.36470588235294116), - (0.5, 0.94117647058823528, 0.94117647058823528), - (0.60000000000000009, 0.99215686274509807, 0.99215686274509807), - (0.70000000000000007, 0.93333333333333335, 0.93333333333333335), - (0.80000000000000004, 0.58823529411764708, 0.58823529411764708), - (0.90000000000000002, 0.93333333333333335, 0.93333333333333335), - (1.0, 0.83137254901960789, 0.83137254901960789), - ], -} - -_BlueBrown10_data = { - "blue": [ - (0.0, 0.75294117647058822, 0.75294117647058822), - (0.1111111111111111, 0.81176470588235294, 0.81176470588235294), - (0.22222222222222221, 0.87450980392156863, 0.87450980392156863), - (0.33333333333333331, 0.93725490196078431, 0.93725490196078431), - (0.44444444444444442, 1.0, 1.0), - (0.55555555555555558, 0.69411764705882351, 0.69411764705882351), - (0.66666666666666663, 0.60392156862745094, 0.60392156862745094), - (0.77777777777777768, 0.51372549019607838, 0.51372549019607838), - (0.88888888888888884, 0.42745098039215684, 0.42745098039215684), - (1.0, 0.33725490196078434, 0.33725490196078434), - ], - "green": [ - (0.0, 0.37647058823529411, 0.37647058823529411), - (0.1111111111111111, 0.51372549019607838, 0.51372549019607838), - (0.22222222222222221, 0.65098039215686276, 0.65098039215686276), - (0.33333333333333331, 0.78823529411764703, 0.78823529411764703), - (0.44444444444444442, 0.92941176470588238, 0.92941176470588238), - (0.55555555555555558, 0.90196078431372551, 0.90196078431372551), - (0.66666666666666663, 0.76078431372549016, 0.76078431372549016), - (0.77777777777777768, 0.62352941176470589, 0.62352941176470589), - (0.88888888888888884, 0.48627450980392156, 0.48627450980392156), - (1.0, 0.34509803921568627, 0.34509803921568627), - ], - "red": [ - (0.0, 0.0039215686274509803, 0.0039215686274509803), - (0.1111111111111111, 0.0039215686274509803, 0.0039215686274509803), - (0.22222222222222221, 0.0039215686274509803, 0.0039215686274509803), - (0.33333333333333331, 0.0039215686274509803, 0.0039215686274509803), - (0.44444444444444442, 0.0078431372549019607, 0.0078431372549019607), - (0.55555555555555558, 1.0, 1.0), - (0.66666666666666663, 0.90196078431372551, 0.90196078431372551), - (0.77777777777777768, 0.80392156862745101, 0.80392156862745101), - (0.88888888888888884, 0.70588235294117652, 0.70588235294117652), - (1.0, 0.60784313725490191, 0.60784313725490191), - ], -} - -_BlueBrown11_data = { - "blue": [ - (0.0, 0.75294117647058822, 0.75294117647058822), - (0.10000000000000001, 0.81176470588235294, 0.81176470588235294), - (0.20000000000000001, 0.87450980392156863, 0.87450980392156863), - (0.30000000000000004, 0.93725490196078431, 0.93725490196078431), - (0.40000000000000002, 1.0, 1.0), - 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(0.090909090909090912, 0.187, 0.187), - (0.18181818181818182, 0.379, 0.379), - (0.27272727272727271, 0.60799999999999998, 0.60799999999999998), - (0.36363636363636365, 0.68799999999999994, 0.68799999999999994), - (0.45454545454545459, 0.85499999999999998, 0.85499999999999998), - (0.54545454545454541, 0.99299999999999999, 0.99299999999999999), - (0.63636363636363635, 0.97299999999999998, 0.97299999999999998), - (0.72727272727272729, 0.93999999999999995, 0.93999999999999995), - (0.81818181818181823, 0.89300000000000002, 0.89300000000000002), - (0.90909090909090917, 0.66700000000000004, 0.66700000000000004), - (1.0, 0.47999999999999998, 0.47999999999999998), - ], - "red": [ - (0.0, 0.20000000000000001, 0.20000000000000001), - (0.090909090909090912, 0.40000000000000002, 0.40000000000000002), - (0.18181818181818182, 0.59999999999999998, 0.59999999999999998), - (0.27272727272727271, 0.80000000000000004, 0.80000000000000004), - (0.36363636363636365, 0.84999999999999998, 0.84999999999999998), - (0.45454545454545459, 0.94999999999999996, 0.94999999999999996), - (0.54545454545454541, 0.80000000000000004, 0.80000000000000004), - (0.63636363636363635, 0.59999999999999998, 0.59999999999999998), - (0.72727272727272729, 0.40000000000000002, 0.40000000000000002), - (0.81818181818181823, 0.20000000000000001, 0.20000000000000001), - (0.90909090909090917, 0.0, 0.0), - (1.0, 0.0, 0.0), - ], -} - -_GrMg16_data = { - "blue": [ - (0.0, 0.0, 0.0), - (0.066666666666666666, 0.0, 0.0), - (0.13333333333333333, 0.0, 0.0), - (0.20000000000000001, 0.0, 0.0), - (0.26666666666666666, 0.316, 0.316), - (0.33333333333333331, 0.52600000000000002, 0.52600000000000002), - (0.40000000000000002, 0.73699999999999999, 0.73699999999999999), - (0.46666666666666667, 1.0, 1.0), - (0.53333333333333333, 1.0, 1.0), - (0.59999999999999998, 1.0, 1.0), - (0.66666666666666663, 1.0, 1.0), - (0.73333333333333328, 1.0, 1.0), - (0.80000000000000004, 0.94699999999999995, 0.94699999999999995), - (0.8666666666666667, 0.73699999999999999, 0.73699999999999999), - (0.93333333333333335, 0.52600000000000002, 0.52600000000000002), - (1.0, 0.316, 0.316), - ], - "green": [ - (0.0, 0.316, 0.316), - (0.066666666666666666, 0.52600000000000002, 0.52600000000000002), - (0.13333333333333333, 0.73699999999999999, 0.73699999999999999), - (0.20000000000000001, 0.94699999999999995, 0.94699999999999995), - (0.26666666666666666, 1.0, 1.0), - (0.33333333333333331, 1.0, 1.0), - (0.40000000000000002, 1.0, 1.0), - (0.46666666666666667, 1.0, 1.0), - (0.53333333333333333, 0.94699999999999995, 0.94699999999999995), - (0.59999999999999998, 0.73699999999999999, 0.73699999999999999), - (0.66666666666666663, 0.52600000000000002, 0.52600000000000002), - (0.73333333333333328, 0.316, 0.316), - (0.80000000000000004, 0.0, 0.0), - (0.8666666666666667, 0.0, 0.0), - (0.93333333333333335, 0.0, 0.0), - (1.0, 0.0, 0.0), - ], - "red": [ - (0.0, 0.0, 0.0), - (0.066666666666666666, 0.0, 0.0), - (0.13333333333333333, 0.0, 0.0), - (0.20000000000000001, 0.0, 0.0), - (0.26666666666666666, 0.316, 0.316), - (0.33333333333333331, 0.52600000000000002, 0.52600000000000002), - (0.40000000000000002, 0.73699999999999999, 0.73699999999999999), - (0.46666666666666667, 1.0, 1.0), - (0.53333333333333333, 1.0, 1.0), - (0.59999999999999998, 1.0, 1.0), - (0.66666666666666663, 1.0, 1.0), - (0.73333333333333328, 1.0, 1.0), - (0.80000000000000004, 0.94699999999999995, 0.94699999999999995), - (0.8666666666666667, 0.73699999999999999, 0.73699999999999999), - (0.93333333333333335, 0.52600000000000002, 0.52600000000000002), - (1.0, 0.316, 0.316), - ], -} - -_BrBu10_data = { - "blue": [ - (0.0, 0.0, 0.0), - (0.1111111111111111, 0.20999999999999999, 0.20999999999999999), - (0.22222222222222221, 0.47999999999999998, 0.47999999999999998), - (0.33333333333333331, 0.59499999999999997, 0.59499999999999997), - (0.44444444444444442, 0.80800000000000005, 0.80800000000000005), - (0.55555555555555558, 1.0, 1.0), - (0.66666666666666663, 1.0, 1.0), - (0.77777777777777768, 1.0, 1.0), - (0.88888888888888884, 1.0, 1.0), - (1.0, 0.80000000000000004, 0.80000000000000004), - ], - "green": [ - (0.0, 0.187, 0.187), - (0.1111111111111111, 0.379, 0.379), - (0.22222222222222221, 0.60799999999999998, 0.60799999999999998), - (0.33333333333333331, 0.68799999999999994, 0.68799999999999994), - (0.44444444444444442, 0.85499999999999998, 0.85499999999999998), - (0.55555555555555558, 0.99299999999999999, 0.99299999999999999), - (0.66666666666666663, 0.97299999999999998, 0.97299999999999998), - (0.77777777777777768, 0.93999999999999995, 0.93999999999999995), - (0.88888888888888884, 0.89300000000000002, 0.89300000000000002), - (1.0, 0.66700000000000004, 0.66700000000000004), - ], - "red": [ - (0.0, 0.40000000000000002, 0.40000000000000002), - (0.1111111111111111, 0.59999999999999998, 0.59999999999999998), - (0.22222222222222221, 0.80000000000000004, 0.80000000000000004), - (0.33333333333333331, 0.84999999999999998, 0.84999999999999998), - (0.44444444444444442, 0.94999999999999996, 0.94999999999999996), - (0.55555555555555558, 0.80000000000000004, 0.80000000000000004), - (0.66666666666666663, 0.59999999999999998, 0.59999999999999998), - (0.77777777777777768, 0.40000000000000002, 0.40000000000000002), - (0.88888888888888884, 0.20000000000000001, 0.20000000000000001), - (1.0, 0.0, 0.0), - ], -} - -_Bu10_data = { - "blue": [ - (0.0, 1.0, 1.0), - (0.1111111111111111, 1.0, 1.0), - (0.22222222222222221, 1.0, 1.0), - (0.33333333333333331, 1.0, 1.0), - (0.44444444444444442, 1.0, 1.0), - (0.55555555555555558, 1.0, 1.0), - (0.66666666666666663, 1.0, 1.0), - (0.77777777777777768, 1.0, 1.0), - (0.88888888888888884, 1.0, 1.0), - (1.0, 1.0, 1.0), - ], - "green": [ - (0.0, 1.0, 1.0), - (0.1111111111111111, 0.98299999999999998, 0.98299999999999998), - (0.22222222222222221, 0.94999999999999996, 0.94999999999999996), - (0.33333333333333331, 0.90000000000000002, 0.90000000000000002), - (0.44444444444444442, 0.83299999999999996, 0.83299999999999996), - (0.55555555555555558, 0.75, 0.75), - (0.66666666666666663, 0.65000000000000002, 0.65000000000000002), - (0.77777777777777768, 0.53300000000000003, 0.53300000000000003), - (0.88888888888888884, 0.40000000000000002, 0.40000000000000002), - (1.0, 0.25, 0.25), - ], - "red": [ - (0.0, 0.90000000000000002, 0.90000000000000002), - (0.1111111111111111, 0.80000000000000004, 0.80000000000000004), - (0.22222222222222221, 0.69999999999999996, 0.69999999999999996), - (0.33333333333333331, 0.59999999999999998, 0.59999999999999998), - (0.44444444444444442, 0.5, 0.5), - (0.55555555555555558, 0.40000000000000002, 0.40000000000000002), - (0.66666666666666663, 0.29999999999999999, 0.29999999999999999), - (0.77777777777777768, 0.20000000000000001, 0.20000000000000001), - (0.88888888888888884, 0.10000000000000001, 0.10000000000000001), - (1.0, 0.0, 0.0), - ], -} - -_BuDOr12_data = { - "blue": [ - (0.0, 0.59999999999999998, 0.59999999999999998), - (0.090909090909090912, 0.80000000000000004, 0.80000000000000004), - (0.18181818181818182, 1.0, 1.0), - (0.27272727272727271, 1.0, 1.0), - (0.36363636363636365, 1.0, 1.0), - (0.45454545454545459, 1.0, 1.0), - (0.54545454545454541, 0.80000000000000004, 0.80000000000000004), - (0.63636363636363635, 0.59999999999999998, 0.59999999999999998), - (0.72727272727272729, 0.40000000000000002, 0.40000000000000002), - (0.81818181818181823, 0.20000000000000001, 0.20000000000000001), - (0.90909090909090917, 0.0, 0.0), - (1.0, 0.0, 0.0), - ], - "green": [ - (0.0, 0.56000000000000005, 0.56000000000000005), - (0.090909090909090912, 0.76800000000000002, 0.76800000000000002), - (0.18181818181818182, 0.97999999999999998, 0.97999999999999998), - (0.27272727272727271, 0.98999999999999999, 0.98999999999999999), - (0.36363636363636365, 0.997, 0.997), - (0.45454545454545459, 1.0, 1.0), - (0.54545454545454541, 0.90000000000000002, 0.90000000000000002), - (0.63636363636363635, 0.79300000000000004, 0.79300000000000004), - (0.72727272727272729, 0.68000000000000005, 0.68000000000000005), - (0.81818181818181823, 0.56000000000000005, 0.56000000000000005), - (0.90909090909090917, 0.34699999999999998, 0.34699999999999998), - (1.0, 0.25, 0.25), - ], - "red": [ - (0.0, 0.12, 0.12), - (0.090909090909090912, 0.32000000000000001, 0.32000000000000001), - (0.18181818181818182, 0.59999999999999998, 0.59999999999999998), - (0.27272727272727271, 0.69999999999999996, 0.69999999999999996), - (0.36363636363636365, 0.80000000000000004, 0.80000000000000004), - (0.45454545454545459, 0.90000000000000002, 0.90000000000000002), - (0.54545454545454541, 1.0, 1.0), - (0.63636363636363635, 1.0, 1.0), - (0.72727272727272729, 1.0, 1.0), - (0.81818181818181823, 1.0, 1.0), - (0.90909090909090917, 0.80000000000000004, 0.80000000000000004), - (1.0, 0.59999999999999998, 0.59999999999999998), - ], -} - -_StepSeq25_data = { - "blue": [ - (0.0, 0.059999999999999998, 0.059999999999999998), - (0.041666666666666664, 0.17499999999999999, 0.17499999999999999), - (0.083333333333333329, 0.32000000000000001, 0.32000000000000001), - (0.125, 0.495, 0.495), - (0.16666666666666666, 0.69999999999999996, 0.69999999999999996), - (0.20833333333333331, 0.059999999999999998, 0.059999999999999998), - (0.25, 0.17499999999999999, 0.17499999999999999), - (0.29166666666666663, 0.32000000000000001, 0.32000000000000001), - (0.33333333333333331, 0.495, 0.495), - (0.375, 0.69999999999999996, 0.69999999999999996), - (0.41666666666666663, 0.059999999999999998, 0.059999999999999998), - (0.45833333333333331, 0.17499999999999999, 0.17499999999999999), - (0.5, 0.32000000000000001, 0.32000000000000001), - (0.54166666666666663, 0.495, 0.495), - (0.58333333333333326, 0.69999999999999996, 0.69999999999999996), - (0.625, 0.59999999999999998, 0.59999999999999998), - (0.66666666666666663, 0.69999999999999996, 0.69999999999999996), - (0.70833333333333326, 0.80000000000000004, 0.80000000000000004), - (0.75, 0.90000000000000002, 0.90000000000000002), - (0.79166666666666663, 1.0, 1.0), - (0.83333333333333326, 0.59999999999999998, 0.59999999999999998), - (0.875, 0.69999999999999996, 0.69999999999999996), - (0.91666666666666663, 0.80000000000000004, 0.80000000000000004), - (0.95833333333333326, 0.90000000000000002, 0.90000000000000002), - (1.0, 1.0, 1.0), - ], - "green": [ - (0.0, 0.059999999999999998, 0.059999999999999998), - 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(0.55555555555555558, 0.80000000000000004, 0.80000000000000004), - (0.66666666666666663, 0.59999999999999998, 0.59999999999999998), - (0.77777777777777768, 0.40000000000000002, 0.40000000000000002), - (0.88888888888888884, 0.20000000000000001, 0.20000000000000001), - (1.0, 0.0, 0.0), - ], - "green": [ - (0.0, 0.33300000000000002, 0.33300000000000002), - (0.1111111111111111, 0.59999999999999998, 0.59999999999999998), - (0.22222222222222221, 0.80000000000000004, 0.80000000000000004), - (0.33333333333333331, 0.93300000000000005, 0.93300000000000005), - (0.44444444444444442, 1.0, 1.0), - (0.55555555555555558, 1.0, 1.0), - (0.66666666666666663, 0.93300000000000005, 0.93300000000000005), - (0.77777777777777768, 0.80000000000000004, 0.80000000000000004), - (0.88888888888888884, 0.59999999999999998, 0.59999999999999998), - (1.0, 0.33300000000000002, 0.33300000000000002), - ], - "red": [ - (0.0, 0.0, 0.0), - (0.1111111111111111, 0.20000000000000001, 0.20000000000000001), - (0.22222222222222221, 0.40000000000000002, 0.40000000000000002), - (0.33333333333333331, 0.59999999999999998, 0.59999999999999998), - (0.44444444444444442, 0.80000000000000004, 0.80000000000000004), - (0.55555555555555558, 1.0, 1.0), - (0.66666666666666663, 1.0, 1.0), - (0.77777777777777768, 1.0, 1.0), - (0.88888888888888884, 1.0, 1.0), - (1.0, 1.0, 1.0), - ], -} - -_BuDRd12_data = { - "blue": [ - (0.0, 0.84999999999999998, 0.84999999999999998), - (0.090909090909090912, 1.0, 1.0), - (0.18181818181818182, 1.0, 1.0), - (0.27272727272727271, 1.0, 1.0), - (0.36363636363636365, 1.0, 1.0), - (0.45454545454545459, 1.0, 1.0), - (0.54545454545454541, 0.75, 0.75), - (0.63636363636363635, 0.59999999999999998, 0.59999999999999998), - (0.72727272727272729, 0.45000000000000001, 0.45000000000000001), - (0.81818181818181823, 0.37, 0.37), - (0.90909090909090917, 0.19600000000000001, 0.19600000000000001), - (1.0, 0.13, 0.13), - ], - "green": [ - (0.0, 0.042999999999999997, 0.042999999999999997), - (0.090909090909090912, 0.30599999999999999, 0.30599999999999999), - (0.18181818181818182, 0.63, 0.63), - (0.27272727272727271, 0.85299999999999998, 0.85299999999999998), - (0.36363636363636365, 0.97299999999999998, 0.97299999999999998), - (0.45454545454545459, 1.0, 1.0), - (0.54545454545454541, 1.0, 1.0), - (0.63636363636363635, 0.88, 0.88), - (0.72727272727272729, 0.67900000000000005, 0.67900000000000005), - (0.81818181818181823, 0.42999999999999999, 0.42999999999999999), - (0.90909090909090917, 0.14999999999999999, 0.14999999999999999), - (1.0, 0.0, 0.0), - ], - "red": [ - (0.0, 0.16400000000000001, 0.16400000000000001), - (0.090909090909090912, 0.14999999999999999, 0.14999999999999999), - (0.18181818181818182, 0.25, 0.25), - (0.27272727272727271, 0.45000000000000001, 0.45000000000000001), - (0.36363636363636365, 0.67000000000000004, 0.67000000000000004), - (0.45454545454545459, 0.88, 0.88), - (0.54545454545454541, 1.0, 1.0), - (0.63636363636363635, 1.0, 1.0), - (0.72727272727272729, 1.0, 1.0), - (0.81818181818181823, 0.96999999999999997, 0.96999999999999997), - (0.90909090909090917, 0.84999999999999998, 0.84999999999999998), - (1.0, 0.65000000000000002, 0.65000000000000002), - ], -} - -# LangRainbow12 developed to be friendlier to color blindness and B&W printing -# than most rainbow color scales. -_LangRainbow12_data = { - "blue": [ - (0.0, 0.97000000000000008, 0.97000000000000008), - (0.090909090909090912, 0.95599999999999996, 0.95599999999999996), - (0.18181818181818182, 0.94500000000000006, 0.94500000000000006), - (0.27272727272727271, 0.93700000000000006, 0.93700000000000006), - (0.36363636363636365, 0.93199999999999994, 0.93199999999999994), - (0.45454545454545459, 0.92999999999999994, 0.92999999999999994), - (0.54545454545454541, 0.14900000000000002, 0.14900000000000002), - (0.63636363636363635, 0.060000000000000053, 0.060000000000000053), - (0.72727272727272729, 0.042000000000000037, 0.042000000000000037), - (0.81818181818181823, 0.027000000000000024, 0.027000000000000024), - (0.90909090909090917, 0.015000000000000013, 0.015000000000000013), - (1.0, 0.0060000000000000053, 0.0060000000000000053), - ], - "green": [ - (0.0, 0.82999999999999996, 0.82999999999999996), - (0.090909090909090912, 0.7240000000000002, 0.7240000000000002), - (0.18181818181818182, 0.64799999999999991, 0.64799999999999991), - (0.27272727272727271, 0.67660000000000009, 0.67660000000000009), - (0.36363636363636365, 0.76879999999999971, 0.76879999999999971), - (0.45454545454545459, 0.92999999999999983, 0.92999999999999983), - (0.54545454545454541, 0.93100000000000005, 0.93100000000000005), - (0.63636363636363635, 0.75929999999999997, 0.75929999999999997), - (0.72727272727272729, 0.54600000000000004, 0.54600000000000004), - (0.81818181818181823, 0.35999999999999999, 0.35999999999999999), - (0.90909090909090917, 0.20500000000000002, 0.20500000000000002), - (1.0, 0.08415600000000005, 0.08415600000000005), - ], - "red": [ - (0.0, 0.89999999999999991, 0.89999999999999991), - (0.090909090909090912, 0.77039999999999997, 0.77039999999999997), - (0.18181818181818182, 0.61499999999999999, 0.61499999999999999), - (0.27272727272727271, 0.50300000000000011, 0.50300000000000011), - (0.36363636363636365, 0.38800000000000012, 0.38800000000000012), - (0.45454545454545459, 0.27000000000000024, 0.27000000000000024), - (0.54545454545454541, 0.93099999999999983, 0.93099999999999983), - (0.63636363636363635, 0.89999999999999991, 0.89999999999999991), - (0.72727272727272729, 0.79800000000000004, 0.79800000000000004), - (0.81818181818181823, 0.69299999999999995, 0.69299999999999995), - (0.90909090909090917, 0.58500000000000008, 0.58500000000000008), - (1.0, 0.4740000000000002, 0.4740000000000002), - ], -} - -datad = { - "NWSRef": _NWSRef_data, - "NWSVel": _NWSVel_data, - "NWS_SPW": _NWS_SPW_data, - "RefDiff": _RefDiff_data, - "Carbone11": _Carbone11_data, - "Carbone17": _Carbone17_data, - "RRate11": _RRate11_data, - "BlueBrown10": _BlueBrown10_data, - "BlueBrown11": _BlueBrown11_data, - "Theodore16": _Theodore16_data, - "EWilson17": _EWilson17_data, - "Wild25": _Wild25_data, - "SCook18": _SCook18_data, - "PD17": _PD17_data, - "Gray5": _Gray5_data, - "Gray9": _Gray9_data, - "SymGray12": _SymGray12_data, - "Carbone42": _Carbone42_data, - "BrBu12": _BrBu12_data, - "GrMg16": _GrMg16_data, - "BrBu10": _BrBu10_data, - "Bu10": _Bu10_data, - "BuDOr12": _BuDOr12_data, - "StepSeq25": _StepSeq25_data, - "RdYlBu11b": _RdYlBu11b_data, - "Bu7": _Bu7_data, - "BuOr12": _BuOr12_data, - "BuGr14": _BuGr14_data, - "BuDRd18": _BuDRd18_data, - "BuDOr18": _BuDOr18_data, - "BuOr8": _BuOr8_data, - "Cat12": _Cat12_data, - "BuGy8": _BuGy8_data, - "BuOrR14": _BuOrR14_data, - "BuOr10": _BuOr10_data, - "BuDRd12": _BuDRd12_data, - "LangRainbow12": _LangRainbow12_data, -} diff --git a/pyart/graph/_cm_colorblind.py b/pyart/graph/_cm_colorblind.py deleted file mode 100644 index 8b078ea58e..0000000000 --- a/pyart/graph/_cm_colorblind.py +++ /dev/null @@ -1,64 +0,0 @@ -""" -Data for colorblind friendly radar colormaps - -""" -import os - -import numpy as np - - -def yuv_rainbow_24(nc): - path1 = np.linspace(0.8 * np.pi, 1.8 * np.pi, nc) - path2 = np.linspace(-0.33 * np.pi, 0.33 * np.pi, nc) - - y = np.concatenate( - [np.linspace(0.3, 0.85, nc * 2 // 5), np.linspace(0.9, 0.0, nc - nc * 2 // 5)] - ) - u = 0.40 * np.sin(path1) - v = 0.55 * np.sin(path2) + 0.1 - - rgb_from_yuv = np.array([[1, 0, 1.13983], [1, -0.39465, -0.58060], [1, 2.03211, 0]]) - cmap_dict = {"blue": [], "green": [], "red": []} - for i in range(len(y)): - yuv = np.array([y[i], u[i], v[i]]) - rgb = rgb_from_yuv.dot(yuv) - red_tuple = (i / (len(y) - 1.0), rgb[0], rgb[0]) - green_tuple = (i / (len(y) - 1.0), rgb[1], rgb[1]) - blue_tuple = (i / (len(y) - 1.0), rgb[2], rgb[2]) - cmap_dict["blue"].append(blue_tuple) - cmap_dict["red"].append(red_tuple) - cmap_dict["green"].append(green_tuple) - - return cmap_dict - - -# balance colormap from cmocean project -# courtesy Kristen Thyng - -# Thyng, K. M., Greene, C. A., Hetland, R. D., Zimmerle, H. M., & DiMarco, S. F. (2016). -# True colors of oceanography. Oceanography, 29(3), 10. - -data_dir = os.path.split(__file__)[0] -bal_rgb_vals = np.genfromtxt(os.path.join(data_dir, "balance-rgb.txt")) - - -# "Spectral"-like colormaps for radar reflectivity -# ChaseSpectral developed by Randy Chase with assistance from Sam Gardner and Jonathan Thielen -# SpectralExtended developed by Jonathan Thielen based on ChaseSpectral - -chase_spectral_rgb_vals = np.genfromtxt( - os.path.join(data_dir, "chase-spectral-rgb.txt") -) -spectral_ext_rgb_vals = np.genfromtxt( - os.path.join(data_dir, "spectral-extended-rgb.txt") -) - - -# HomeyerRainbow developed by Cameron Homeyer with assistance from Bobby Jackson - -datad = { - "HomeyerRainbow": yuv_rainbow_24(15), - "balance": bal_rgb_vals, - "ChaseSpectral": chase_spectral_rgb_vals, - "SpectralExtended": spectral_ext_rgb_vals, -} diff --git a/pyart/graph/balance-rgb.txt b/pyart/graph/balance-rgb.txt deleted file mode 100644 index 5d41696c83..0000000000 --- a/pyart/graph/balance-rgb.txt +++ /dev/null @@ -1,256 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-colormaps are available within matplotlib with names 'pyart_COLORMAP': - - * BlueBrown10 - * BlueBrown11 - * BrBu10 - * BrBu12 - * Bu10 - * Bu7 - * BuDOr12 - * BuDOr18 - * BuDRd12 - * BuDRd18 - * BuGr14 - * BuGy8 - * BuOr10 - * BuOr12 - * BuOr8 - * BuOrR14 - * Carbone11 - * Carbone17 - * Carbone42 - * Cat12 - * EWilson17 - * GrMg16 - * Gray5 - * Gray9 - * NWSRef - * NWSVel - * NWS_SPW - * PD17 - * RRate11 - * RdYlBu11b - * RefDiff - * SCook18 - * StepSeq25 - * SymGray12 - * Theodore16 - * Wild25 - * LangRainbow12 - -""" - -# This file was adapted from the cm.py file of the matplotlib project, -# http://matplotlib.org/. -# Copyright (c) 2012-2013 Matplotlib Development Team; All Rights Reserved - -import warnings - -import matplotlib as mpl -import matplotlib.colors as colors - -from ._cm import datad - -cmap_d = dict() - -# reverse all the colormaps. -# reversed colormaps have '_r' appended to the name. - - -def _reverser(f): - """perform reversal.""" - - def freversed(x): - """f specific reverser.""" - return f(1 - x) - - return freversed - - -def revcmap(data): - """Can only handle specification *data* in dictionary format.""" - data_r = {} - for key, val in data.items(): - if callable(val): - valnew = _reverser(val) - # This doesn't work: lambda x: val(1-x) - # The same "val" (the first one) is used - # each time, so the colors are identical - # and the result is shades of gray. - else: - # Flip x and exchange the y values facing x = 0 and x = 1. - valnew = [(1.0 - x, y1, y0) for x, y0, y1 in reversed(val)] - data_r[key] = valnew - return data_r - - -def _reverse_cmap_spec(spec): - """Reverses cmap specification *spec*, can handle both dict and tuple - type specs.""" - with warnings.catch_warnings(): - warnings.simplefilter("ignore", FutureWarning) - if isinstance(spec, dict) and "red" in spec.keys(): - return revcmap(spec) - else: - revspec = list(reversed(spec)) - if len(revspec[0]) == 2: # e.g., (1, (1.0, 0.0, 1.0)) - revspec = [(1.0 - a, b) for a, b in revspec] - return revspec - - -def _generate_cmap(name, lutsize): - """Generates the requested cmap from it's name *name*. The lut size is - *lutsize*.""" - - spec = datad[name] - - # Generate the colormap object. - if isinstance(spec, dict) and "red" in spec.keys(): - return colors.LinearSegmentedColormap(name, spec, lutsize) - else: - return colors.LinearSegmentedColormap.from_list(name, spec, lutsize) - - -LUTSIZE = mpl.rcParams["image.lut"] - -# need this list because datad is changed in loop -_cmapnames = list(datad.keys()) - -# Generate the reversed specifications ... - -for cmapname in _cmapnames: - spec = datad[cmapname] - spec_reversed = _reverse_cmap_spec(spec) - datad[cmapname + "_r"] = spec_reversed - -# Precache the cmaps with ``lutsize = LUTSIZE`` ... - -# Use datad.keys() to also add the reversed ones added in the section above: -for cmapname in datad.keys(): - cmap_d[cmapname] = _generate_cmap(cmapname, LUTSIZE) - -locals().update(cmap_d) - -# register the colormaps so that can be accessed with the names pyart_XXX -for name, cmap in cmap_d.items(): - full_name = "pyart_" + name - # Matplotlib 3.6.0 colormap registering changed. - try: - mpl.colormaps.register(name=full_name, cmap=cmap, force=True) - except AttributeError: - mpl.cm.register_cmap(name=full_name, cmap=cmap) diff --git a/pyart/graph/cm_colorblind.py b/pyart/graph/cm_colorblind.py deleted file mode 100644 index 4a6d23c0fb..0000000000 --- a/pyart/graph/cm_colorblind.py +++ /dev/null @@ -1,68 +0,0 @@ -""" -Colorblind friendly radar colormaps - -Available colormaps, reversed versions are also provided, these -colormaps are available within matplotlib with names pyart_COLORMAP': - - * HomeyerRainbow - * balance - * ChaseSpectral - * SpectralExtended -""" - -import warnings - -import matplotlib as mpl -import matplotlib.colors as colors - -from ._cm_colorblind import datad -from .cm import _reverse_cmap_spec - - -def _generate_cmap(name, lutsize): - """Generates the requested cmap from it's name *name*. The lut size is - *lutsize*.""" - - spec = datad[name] - # Generate the colormap object. - with warnings.catch_warnings(): - warnings.simplefilter("ignore", FutureWarning) - if isinstance(spec, dict) and "red" in spec.keys(): - return colors.LinearSegmentedColormap(name, spec, lutsize) - else: - return colors.LinearSegmentedColormap.from_list(name, spec, lutsize) - - -cmap_d = dict() - -# reverse all the colormaps. -# reversed colormaps have '_r' appended to the name. - -LUTSIZE = mpl.rcParams["image.lut"] - -# need this list because datad is changed in loop -_cmapnames = list(datad.keys()) - -# Generate the reversed specifications ... - -for cmapname in _cmapnames: - spec = datad[cmapname] - spec_reversed = _reverse_cmap_spec(spec) - datad[cmapname + "_r"] = spec_reversed - -# Precache the cmaps with ``lutsize = LUTSIZE`` ... - -# Use datad.keys() to also add the reversed ones added in the section above: -for cmapname in datad.keys(): - cmap_d[cmapname] = _generate_cmap(cmapname, LUTSIZE) - -locals().update(cmap_d) - -# register the colormaps so that can be accessed with the names pyart_XXX -for name, cmap in cmap_d.items(): - full_name = "pyart_" + name - # Matplotlib 3.6.0 colormap registering changed. - try: - mpl.colormaps.register(name=full_name, cmap=cmap, force=True) - except AttributeError: - mpl.cm.register_cmap(name=full_name, cmap=cmap) diff --git a/pyart/graph/spectral-extended-rgb.txt b/pyart/graph/spectral-extended-rgb.txt deleted file mode 100644 index 8e9f793f2c..0000000000 --- a/pyart/graph/spectral-extended-rgb.txt +++ /dev/null @@ -1,180 +0,0 @@ -7.959147299103611073e-02 6.647558492714741862e-02 1.045726997595241847e-01 -8.073045518328400560e-02 6.761264811292452825e-02 1.061401083833245218e-01 -8.290153602823913115e-02 6.982558504352573414e-02 1.092585259199206349e-01 -8.591114534445465356e-02 7.300325551098113541e-02 1.138945127963576776e-01 -8.951109590787198478e-02 7.700278999126289325e-02 1.199968319554120255e-01 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-1.977615140884450007e-01 0.000000000000000000e+00 2.503076628606556997e-01 -1.929046655677319477e-01 0.000000000000000000e+00 2.462736956007085531e-01 -1.890760172775479975e-01 0.000000000000000000e+00 2.428711469817661506e-01 -1.862414647995699057e-01 0.000000000000000000e+00 2.402115163945445220e-01 -1.843709148334545522e-01 0.000000000000000000e+00 2.383851520678009206e-01 -1.834417329885095482e-01 0.000000000000000000e+00 2.374555838818699360e-01 diff --git a/requirements.txt b/requirements.txt index b2f16d96e0..8afcdbdb07 100644 --- a/requirements.txt +++ b/requirements.txt @@ -10,3 +10,4 @@ open_radar_data xradar pandas xarray!=0.21.0 +cmweather diff --git a/tests/graph/test_cm.py b/tests/graph/test_cm.py deleted file mode 100644 index 562ef1a976..0000000000 --- a/tests/graph/test_cm.py +++ /dev/null @@ -1,47 +0,0 @@ -""" Unit Tests for Py-ART's graph/cm.py module. """ - - -import matplotlib - -from pyart.graph import cm - - -def test_colormaps_exist(): - assert isinstance(cm.NWSRef, matplotlib.colors.Colormap) - assert isinstance(cm.NWSRef_r, matplotlib.colors.Colormap) - - -def test_colormaps_registered(): - cmap = matplotlib.colormaps.get_cmap("pyart_NWSRef") - assert isinstance(cmap, matplotlib.colors.Colormap) - - cmap = matplotlib.colormaps.get_cmap("pyart_NWSRef_r") - assert isinstance(cmap, matplotlib.colors.Colormap) - - -def test_tuple_spec(): - # None of the Py-ART colormaps use the tuple spec, so for coverage in the - # unit tests ddefine a colormap using a tuple - - # data borrowed from matplotlib's lib/matplotlib/_cm.py - _seismic_data = ( - (0.0, 0.0, 0.3), - (0.0, 0.0, 1.0), - (1.0, 1.0, 1.0), - (1.0, 0.0, 0.0), - (0.5, 0.0, 0.0), - ) - cm._reverse_cmap_spec(_seismic_data) - - spec = ((0, 1), (0, 1)) - cm._reverse_cmap_spec(spec) - - cm.datad["foo"] = _seismic_data - cm._generate_cmap("foo", 1) - assert isinstance(cm.NWSRef_r, matplotlib.colors.Colormap) - - -def test_revcmap_callable(): - # reversing a callable is not exercised in Py-ART - data_r = cm.revcmap({"foo": lambda x: x}) - assert data_r["foo"](0) == 1 diff --git a/tests/graph/test_cm_colorblind.py b/tests/graph/test_cm_colorblind.py deleted file mode 100644 index 5060ff0143..0000000000 --- a/tests/graph/test_cm_colorblind.py +++ /dev/null @@ -1,43 +0,0 @@ -""" Unit Tests for Py-ART's graph/cm_colorblind.py module. """ - - -import matplotlib - -from pyart.graph import cm_colorblind - - -def test_colormaps_exist(): - assert isinstance(cm_colorblind.HomeyerRainbow, matplotlib.colors.Colormap) - assert isinstance(cm_colorblind.HomeyerRainbow_r, matplotlib.colors.Colormap) - assert isinstance(cm_colorblind.balance, matplotlib.colors.Colormap) - assert isinstance(cm_colorblind.balance_r, matplotlib.colors.Colormap) - assert isinstance(cm_colorblind.ChaseSpectral, matplotlib.colors.Colormap) - assert isinstance(cm_colorblind.ChaseSpectral_r, matplotlib.colors.Colormap) - assert isinstance(cm_colorblind.SpectralExtended, matplotlib.colors.Colormap) - assert isinstance(cm_colorblind.SpectralExtended_r, matplotlib.colors.Colormap) - - -def test_colormaps_registered(): - cmap = matplotlib.colormaps.get_cmap("pyart_HomeyerRainbow") - assert isinstance(cmap, matplotlib.colors.Colormap) - - cmap = matplotlib.colormaps.get_cmap("pyart_HomeyerRainbow_r") - assert isinstance(cmap, matplotlib.colors.Colormap) - - cmap = matplotlib.colormaps.get_cmap("pyart_balance") - assert isinstance(cmap, matplotlib.colors.Colormap) - - cmap = matplotlib.colormaps.get_cmap("pyart_balance_r") - assert isinstance(cmap, matplotlib.colors.Colormap) - - cmap = matplotlib.colormaps.get_cmap("pyart_ChaseSpectral") - assert isinstance(cmap, matplotlib.colors.Colormap) - - cmap = matplotlib.colormaps.get_cmap("pyart_ChaseSpectral_r") - assert isinstance(cmap, matplotlib.colors.Colormap) - - cmap = matplotlib.colormaps.get_cmap("pyart_SpectralExtended") - assert isinstance(cmap, matplotlib.colors.Colormap) - - cmap = matplotlib.colormaps.get_cmap("pyart_SpectralExtended_r") - assert isinstance(cmap, matplotlib.colors.Colormap) diff --git a/tests/graph/test_common.py b/tests/graph/test_common.py index 47ce7a7293..7951f57f25 100644 --- a/tests/graph/test_common.py +++ b/tests/graph/test_common.py @@ -33,7 +33,7 @@ def test_parse_ax_fig(): def test_parse_cmap(): assert common.parse_cmap("jet", "foo") == "jet" - assert common.parse_cmap(None, "reflectivity") == "pyart_HomeyerRainbow" + assert common.parse_cmap(None, "reflectivity") == "HomeyerRainbow" def test_parse_vmin_vmax():