easy_vic_build.tools.plot_func.plot_utilities

Module easy_vic_build.tools.plot_func.plot_utilities.

Functions

format_lat(lat, pos)	Format latitude value as a string with direction (North/South).
format_lon(lon, pos)	Format longitude value as a string with direction (East/West).
get_NDVI_cmap()	Create a custom colormap for NDVI (Normalized Difference Vegetation Index) values.
get_UMD_LULC_cmap()	Create a colormap for UMD Land Use and Land Cover (LULC) classification.
get_colorbar(vmin, vmax, cmap[, figsize, ...])	Create a colorbar for visualizing data range using a given colormap.
plot_check_search(searched_grid_lat, ...[, ...])	Usage: i = 205 searched_grid_lon = [src_lon[l] for l in searched_grids_index[i][0]] searched_grid_lat = [src_lat[l] for l in searched_grids_index[i][1]] searched_grid_res = src_dlon target_grid_lat = [dst_lat[i]] target_grid_lon = [dst_lon[i]] target_grid_res = dst_dlon plot_check_search( searched_grid_lat, searched_grid_lon, target_grid_lat, target_grid_lon, searched_grid_res, target_grid_res, )
rotate_yticks(ax[, yticks_rotation])	Rotate the y-axis tick labels on a given axis.
set_ax_box_aspect(ax[, hw_factor])	Set the aspect ratio of the axis box.
set_boundary(ax, boundary_x_y)	Set the axis limits based on the given boundary values.
set_xyticks(ax, x_locator_interval, ...[, ...])	Set the x and y axis ticks with specified intervals and rotation.
zoom_center(ax, x_center, y_center[, ...])	Zoom into a specific region around a central point on the axis.

easy_vic_build.tools.plot_func.plot_utilities.get_colorbar(vmin, vmax, cmap, figsize=(2, 6), subplots_adjust={'left': 0.5}, cb_label='', cb_label_kwargs={}, cb_kwargs={})

Create a colorbar for visualizing data range using a given colormap.

Parameters:

• vmin (float) – The minimum value for the colormap normalization.

• vmax (float) – The maximum value for the colormap normalization.

• cmap (matplotlib.colors.Colormap) – The colormap to be used for the colorbar.

• figsize (tuple, optional) – The size of the figure (width, height). Default is (2, 6).

• subplots_adjust (dict, optional) – A dictionary to adjust the subplot layout. The default is {“left”: 0.5}. This allows fine control over the subplot positioning (e.g., “top”, “bottom”, “right”).

• cb_label (str, optional) – The label for the colorbar. Default is an empty string.

• cb_label_kwargs (dict, optional) – Additional keyword arguments to customize the colorbar label. Default is an empty dictionary.

• cb_kwargs (dict, optional) – Additional keyword arguments to customize the colorbar itself. This can include parameters like orientation (either ‘vertical’ or ‘horizontal’). Default is an empty dictionary.

Returns:

• fig (matplotlib.figure.Figure) – The figure containing the colorbar.

• ax (matplotlib.axes.Axes) – The axis object containing the colorbar.

• norm (matplotlib.colors.Normalize) – The normalization used for the colormap.

• sm (matplotlib.cm.ScalarMappable) – The scalar mappable object for the colorbar.

Notes

The function creates a colorbar using a given colormap and normalizes the values between vmin and vmax. The subplot layout can be adjusted via subplots_adjust, and the colorbar label can be set with cb_label and additional arguments provided through cb_label_kwargs.

easy_vic_build.tools.plot_func.plot_utilities.get_NDVI_cmap()

Create a custom colormap for NDVI (Normalized Difference Vegetation Index) values.

This function generates a colormap that represents NDVI values, ranging from 0 to 1, using a series of colors that reflect vegetation health. The colormap starts with a light brown color for low NDVI values and transitions to deep green for high NDVI values.

Returns:

A custom colormap designed for NDVI visualization, with color transitions at specified NDVI values.

Return type:

matplotlib.colors.LinearSegmentedColormap

Notes

The NDVI values are mapped to the following colors:

• NDVI = 0: Light brown (near white).

• NDVI = 0.15: Light brown.

• NDVI = 0.3: Dark brown and light green.

• NDVI = 0.65: Light green.

• NDVI = 1: Deep green.

This colormap can be used to visualize NDVI data in a meaningful way, where lower NDVI values represent less vegetation and higher NDVI values represent more vegetation.

easy_vic_build.tools.plot_func.plot_utilities.get_UMD_LULC_cmap()

Create a colormap for UMD Land Use and Land Cover (LULC) classification.

This function generates a colormap for the UMD LULC classes, which categorize land cover types such as water bodies, forests, grasslands, and urban areas. The colormap maps specific colors to each LULC class and returns the colormap, normalization, and other related information for visualization.

Returns:

• cmap (matplotlib.colors.ListedColormap) – A colormap object that maps LULC classes to specific colors.

• norm (matplotlib.colors.BoundaryNorm) – A normalization object that maps the LULC class values to the colormap.

• ticks (list of str) – A list of LULC class labels, corresponding to the categories.

• ticks_position (list of int) – A list of positions for each LULC class, used for tick placement in a colorbar.

• colorlist (list of str) – A list of hex color values representing the colors for each LULC class.

• colorlevel (numpy.ndarray) – An array of color boundaries that corresponds to the LULC class levels.

Notes

The UMD LULC classes and their corresponding colors are as follows:

0.0: Water -> Deep Blue 1.0: Evergreen Needleleaf Forest -> Dark Green 2.0: Evergreen Broadleaf Forest -> Light Green 3.0: Deciduous Needleleaf Forest -> Brownish 4.0: Deciduous Broadleaf Forest -> Orange 5.0: Mixed Forest -> Purple 6.0: Woodland -> Yellow-Green 7.0: Wooded Grassland -> Gray 8.0: Closed Shrubland -> Red 9.0: Open Shrubland -> Light Orange 10.0: Grassland -> Light Green 11.0: Cropland -> Golden Yellow 12.0: Bare Ground -> Light Brown 13.0: Urban and Built-up -> Bright Cyan

This colormap can be used for visualizing land cover data based on the UMD classification scheme.

easy_vic_build.tools.plot_func.plot_utilities.format_lon(lon, pos)

Format longitude value as a string with direction (East/West).

This function takes a longitude value and returns it as a string with one decimal place, followed by the corresponding directional suffix (’°E’ for positive values and ‘°W’ for negative values).

Parameters:

• lon (float) – The longitude value to be formatted.

• pos (float) – The position of the tick (not used in this function, but required by the formatter).

Returns:

The formatted longitude string, e.g., “45.0°E” or “90.0°W”.

Return type:

str

easy_vic_build.tools.plot_func.plot_utilities.format_lat(lat, pos)

Format latitude value as a string with direction (North/South).

This function takes a latitude value and returns it as a string with one decimal place, followed by the corresponding directional suffix (’°N’ for positive values and ‘°S’ for negative values).

Parameters:

• lat (float) – The latitude value to be formatted.

• pos (float) – The position of the tick (not used in this function, but required by the formatter).

Returns:

The formatted latitude string, e.g., “45.0°N” or “90.0°S”.

Return type:

str

easy_vic_build.tools.plot_func.plot_utilities.rotate_yticks(ax, yticks_rotation=0)

Rotate the y-axis tick labels on a given axis.

This function modifies the y-axis tick labels of the given axis object by setting their rotation angle and vertical alignment.

Parameters:

• ax (matplotlib.axes.Axes) – The axis object whose y-tick labels will be rotated.

• yticks_rotation (float, optional) – The angle of rotation for the y-tick labels in degrees (default is 0).

easy_vic_build.tools.plot_func.plot_utilities.set_xyticks(ax, x_locator_interval, y_locator_interval, yticks_rotation=0)

Set the x and y axis ticks with specified intervals and rotation.

This function configures the major tick locations and formatting for both the x and y axes. It also allows for rotation of the y-axis tick labels.

Parameters:

• ax (matplotlib.axes.Axes) – The axis object where the ticks and labels will be applied.

• x_locator_interval (float) – The interval between x-axis ticks.

• y_locator_interval (float) – The interval between y-axis ticks.

• yticks_rotation (float, optional) – The angle of rotation for the y-tick labels in degrees (default is 0).

easy_vic_build.tools.plot_func.plot_utilities.set_boundary(ax, boundary_x_y)

Set the axis limits based on the given boundary values.

This function adjusts the x and y axis limits of the provided axis object (ax) using the boundary values specified in boundary_x_y. The first two elements in boundary_x_y correspond to the x-axis limits, and the last two elements correspond to the y-axis limits.

Parameters:

• ax (matplotlib.axes.Axes) – The axis object for which the limits will be set.

• boundary_x_y (list or tuple of 4 floats) – The boundary values in the format [x_min, y_min, x_max, y_max], which define the x and y axis limits.

easy_vic_build.tools.plot_func.plot_utilities.zoom_center(ax, x_center, y_center, zoom_factor=2)

Zoom into a specific region around a central point on the axis.

This function zooms into the region centered at (x_center, y_center) by a factor specified by zoom_factor. The zooming is applied symmetrically, maintaining the aspect ratio of the plot.

Parameters:

• ax (matplotlib.axes.Axes) – The axis object to apply the zoom on.

• x_center (float) – The x-coordinate of the center point for zooming.

• y_center (float) – The y-coordinate of the center point for zooming.

• zoom_factor (float, optional) – The factor by which to zoom the plot. A value greater than 1 will zoom in (default is 2).

easy_vic_build.tools.plot_func.plot_utilities.set_ax_box_aspect(ax, hw_factor=1)

Set the aspect ratio of the axis box.

This function adjusts the aspect ratio of the axis box. The aspect ratio is set according to the value of hw_factor, where a value of 1 maintains a square aspect ratio. Values greater than 1 will stretch the plot horizontally, and values less than 1 will stretch it vertically.

Parameters:

• ax (matplotlib.axes.Axes) – The axis object for which the box aspect ratio will be set.

• hw_factor (float, optional) – The ratio of the width to the height of the axis box. A value of 1 maintains a square aspect ratio (default is 1).

easy_vic_build.tools.plot_func.plot_utilities.plot_check_search(searched_grid_lat, searched_grid_lon, target_grid_lat, target_grid_lon, searched_grid_res=None, target_grid_res=None)

Usage: i = 205 searched_grid_lon = [src_lon[l] for l in searched_grids_index[i][0]] searched_grid_lat = [src_lat[l] for l in searched_grids_index[i][1]] searched_grid_res = src_dlon target_grid_lat = [dst_lat[i]] target_grid_lon = [dst_lon[i]] target_grid_res = dst_dlon plot_check_search(

searched_grid_lat, searched_grid_lon, target_grid_lat, target_grid_lon, searched_grid_res, target_grid_res,

)