.. DO NOT EDIT. .. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY. .. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE: .. "auto_examples/plot_custom_precipitation_range.py" .. LINE NUMBERS ARE GIVEN BELOW. .. only:: html .. note:: :class: sphx-glr-download-link-note :ref:`Go to the end ` to download the full example code. .. rst-class:: sphx-glr-example-title .. _sphx_glr_auto_examples_plot_custom_precipitation_range.py: Plot precipitation using custom colormap ============= This tutorial shows how to plot data using a custom colormap with a specific range of precipitation values. .. GENERATED FROM PYTHON SOURCE LINES 10-22 .. code-block:: Python import os from datetime import datetime import matplotlib.pyplot as plt import pysteps from pysteps import io, rcparams from pysteps.utils import conversion from pysteps.visualization import plot_precip_field from pysteps.datasets import download_pysteps_data, create_default_pystepsrc .. GENERATED FROM PYTHON SOURCE LINES 23-29 Download the data if it is not available ---------------------------------------- The following code block downloads datasets from the pysteps-data repository if it is not available on the disk. The dataset is used to demonstrate the plotting of precipitation data using a custom colormap. .. GENERATED FROM PYTHON SOURCE LINES 29-39 .. code-block:: Python # Check if the pysteps-data repository is available (it would be pysteps-data in pysteps) # Implies that you are running this script from the `pysteps/examples` folder if not os.path.exists(rcparams.data_sources["mrms"]["root_path"]): download_pysteps_data("pysteps_data") config_file_path = create_default_pystepsrc("pysteps_data") print(f"Configuration file has been created at {config_file_path}") .. GENERATED FROM PYTHON SOURCE LINES 40-45 Read precipitation field ------------------------ First thing, load a frame from Multi-Radar Multi-Sensor dataset and convert it to precipitation rate in mm/h. .. GENERATED FROM PYTHON SOURCE LINES 45-79 .. code-block:: Python # Define the dataset and the date for which you want to load data data_source = pysteps.rcparams.data_sources["mrms"] date = datetime(2019, 6, 10, 0, 2, 0) # Example date # Extract the parameters from the data source root_path = data_source["root_path"] path_fmt = data_source["path_fmt"] fn_pattern = data_source["fn_pattern"] fn_ext = data_source["fn_ext"] importer_name = data_source["importer"] importer_kwargs = data_source["importer_kwargs"] timestep = data_source["timestep"] # Find the frame in the archive for the specified date fns = io.find_by_date( date, root_path, path_fmt, fn_pattern, fn_ext, timestep, num_prev_files=1 ) # Read the frame from the archive importer = io.get_method(importer_name, "importer") R, _, metadata = io.read_timeseries(fns, importer, **importer_kwargs) # Convert the reflectivity data to rain rate R, metadata = conversion.to_rainrate(R, metadata) # Plot the first rainfall field from the loaded data plt.figure(figsize=(10, 5), dpi=300) plt.axis("off") plot_precip_field(R[0, :, :], geodata=metadata, axis="off") plt.tight_layout() plt.show() .. image-sg:: /auto_examples/images/sphx_glr_plot_custom_precipitation_range_001.png :alt: plot custom precipitation range :srcset: /auto_examples/images/sphx_glr_plot_custom_precipitation_range_001.png :class: sphx-glr-single-img .. rst-class:: sphx-glr-script-out .. code-block:: none /home/docs/checkouts/readthedocs.org/user_builds/pysteps/envs/v1.17.0/lib/python3.10/site-packages/pysteps/visualization/utils.py:439: UserWarning: cartopy package is required for the get_geogrid function but it is not installed. Ignoring geographical information. warnings.warn( .. GENERATED FROM PYTHON SOURCE LINES 80-97 Define the custom colormap -------------------------- Assume that the default colormap does not represent the precipitation values in the desired range. In this case, you can define a custom colormap that will be used to plot the precipitation data and pass the class instance to the `plot_precip_field` function. It essential for the custom colormap to have the following attributes: - `cmap`: The colormap object. - `norm`: The normalization object. - `clevs`: The color levels for the colormap. `plot_precip_field` can handle each of the classes defined in the `matplotlib.colors` https://matplotlib.org/stable/api/colors_api.html#colormaps There must be as many colors in the colormap as there are levels in the color levels. .. GENERATED FROM PYTHON SOURCE LINES 97-144 .. code-block:: Python # Define the custom colormap from matplotlib import colors class ColormapConfig: def __init__(self): self.cmap = None self.norm = None self.clevs = None self.build_colormap() def build_colormap(self): # Define the colormap boundaries and colors # color_list = ['lightgrey', 'lightskyblue', 'blue', 'yellow', 'orange', 'red', 'darkred'] color_list = ["blue", "navy", "yellow", "orange", "green", "brown", "red"] self.clevs = [0.1, 0.5, 1.5, 2.5, 4, 6, 10] # mm/hr # Create a ListedColormap object with the defined colors self.cmap = colors.ListedColormap(color_list) self.cmap.name = "Custom Colormap" # Set the color for values above the maximum level self.cmap.set_over("darkmagenta") # Set the color for values below the minimum level self.cmap.set_under("none") # Set the color for missing values self.cmap.set_bad("gray", alpha=0.5) # Create a BoundaryNorm object to normalize the data values to the colormap boundaries self.norm = colors.BoundaryNorm(self.clevs, self.cmap.N) # Create an instance of the ColormapConfig class config = ColormapConfig() # Plot the precipitation field using the custom colormap plt.figure(figsize=(10, 5), dpi=300) plt.axis("off") plot_precip_field(R[0, :, :], geodata=metadata, axis="off", colormap_config=config) plt.tight_layout() plt.show() .. image-sg:: /auto_examples/images/sphx_glr_plot_custom_precipitation_range_002.png :alt: plot custom precipitation range :srcset: /auto_examples/images/sphx_glr_plot_custom_precipitation_range_002.png :class: sphx-glr-single-img .. rst-class:: sphx-glr-script-out .. code-block:: none /home/docs/checkouts/readthedocs.org/user_builds/pysteps/envs/v1.17.0/lib/python3.10/site-packages/pysteps/visualization/utils.py:439: UserWarning: cartopy package is required for the get_geogrid function but it is not installed. Ignoring geographical information. warnings.warn( .. rst-class:: sphx-glr-timing **Total running time of the script:** (0 minutes 2.539 seconds) .. _sphx_glr_download_auto_examples_plot_custom_precipitation_range.py: .. only:: html .. container:: sphx-glr-footer sphx-glr-footer-example .. container:: sphx-glr-download sphx-glr-download-jupyter :download:`Download Jupyter notebook: plot_custom_precipitation_range.ipynb ` .. container:: sphx-glr-download sphx-glr-download-python :download:`Download Python source code: plot_custom_precipitation_range.py ` .. container:: sphx-glr-download sphx-glr-download-zip :download:`Download zipped: plot_custom_precipitation_range.zip ` .. only:: html .. rst-class:: sphx-glr-signature `Gallery generated by Sphinx-Gallery `_