Visualization

climate_resilience.visualize.get_site_markers(site: pandas.core.series.Series, icon_name: str, ipl_map: leafmap.leafmap.Map, feature: str) → None

Same as plot_site_on_map() but returns the marker instead of plotting it on the map. Also provides a tooltip at the markers showing the values and site ID.

Parameters

  • site (pd.Series) – Site to be plotted on the map.

  • icon_name (str) – Icon to be used as marker on the map.

  • ipl_map (leafmap.Map) – Map on which the site markers are added.

  • feature (str) – Feature based on which the markers are generated.

climate_resilience.visualize.plot_boxplot(data: pandas.core.frame.DataFrame, x_feature: str, y_feature: str, hue_feature: str, hue_order: Optional[List[str]] = None, colors: Optional[List[str]] = None, x_label: Optional[str] = None, y_label: Optional[str] = None, plot_title: str = 'Box Plot', figsize: Tuple[int] = (12, 6), output_filename: Optional[str] = None) → matplotlib.pyplot.axes

Create boxplot using the provided data.

Parameters

  • data (pd.DataFrame) – Data that is used to plot the boxplots.

  • x_feature (str) – Feature within the data that is plotted on the x-axis.

  • y_feature (str) – Feature within the data that is plotted on the y-axis.

  • hue_feature (str) – Feature within the data that is used as the third dimension categorical levels.

  • hue_order (List[str]) – The order in which the categorical levels are to be plotted. Defaults to None. Levels are infered from the data argument automatically if this argument is None.

  • colors (List[str]) – List of colors to be used for each categorical level. Defaults to None.

  • x_label (str, optional) – X-axis label. Defaults to None. The ‘x_feature’ argument is used if this argument is not provided.

  • y_label (str, optional) – Y-axis label. Defaults to None. The ‘y_feature’ argument is used if this argument is not provided.

  • plot_title (str, optional) – Title of the plot. Defaults to ‘Box Plot’.

  • figsize (Tuple[int], optional) – Figure canvas size. Defaults to (12,6).

  • output_filename (str, optional) – Name of the output PNG file. Defaults to None. The output file is not generated in this case.

Returns

Return the plot object axes. This object can be used to

further add plot components if required by the user.

Return type

plt.axes

climate_resilience.visualize.plot_histogram(sites: pandas.core.frame.DataFrame, features: List[str], n_bins: int = 10, bins: Optional[List[float]] = None, plot_title: str = 'Histogram', figsize: Tuple[int] = (12, 6), xlabels: Optional[List[str]] = None, colors: Optional[List[str]] = None) → Tuple[matplotlib.pyplot.figure, matplotlib.pyplot.axes]

Plot histogram between specified bins for the select features of the sites data frame.

Parameters

  • sites (pd.DataFrame) – Data Frame containing all the site information.

  • features (List[str]) – Features of interest.

  • n_bins (int) – Number of histogram bins. Will be ignored if ‘bins’ argument is passed. Defaults to 10.

  • bins (List[float]) – Custom bins for the histogram. Defaults to None. ‘n_bins’ argument is used in this case.

  • plot_title (str) – Title of the resulting plot.

  • figsize (Tuple[int]) – Size of the output plot. Format: (width, height).

  • xlabels (List[str]) – Custom labels in place of x-axis bin range values. Defaults to None. Original bin values are used in this case.

  • colors (List["str"]) – List of colors for each data vector. Must match the number features listed. Defaults to None. Matplotlib default colors are used in this case.

Returns

Returns the figure and axes for the

generated plot.

Return type

Tuple[plt.figure, plt.axes]

climate_resilience.visualize.plot_map(sites: pandas.core.frame.DataFrame, feature: str, colors: List[str], scale_range: Optional[List[float]] = None, icon_name: str = 'umbrella', map_center: List[float] = [39.0119, - 98.4842], map_zoom: int = 4, plot_colorbar: bool = True, colorbar_label: str = 'Colorbar', colorbar_min: Optional[float] = None, colorbar_max: Optional[float] = None, output_map_name: Optional[str] = None) → leafmap.leafmap.Map

Plot and mark each site on a map.

The markers that are generated in white color either lie outside the range specified in ‘scale_range’ OR have nan values.

Parameters

  • sites (pd.DataFrame) – Data Frame containing all the site information.

  • feature (str) – Feature of interest.

  • colors (List[str]) – List of colors to be used as markers. The scale_range is divided into number of colors specified.

  • scale_range (List[float], optional) – Range of the scale. Expects a min and max value to specify the range. Defaults to None. Min and Max value of the sites features are used in this case.

  • icon_name (str, optional) – Name of the Awesome icon that is used as marker for the sites on the map. Defaults to ‘umbrella’.

  • map_center (List[float], optional) – Marks the initial center coordinates of the map. Defaults to [39.0119, -98.4842].

  • map_zoom (int, optional) – Marks the intial zoom level in the map. Defaults to 4.

  • plot_colorbar (bool, optional) – Boolean flag to spacify if the colorbar is to be plotted in the map. Defaults to True.

  • colorbar_label (str, optional) – Caption for the colorbar. Defaults to ‘Colorbar’.

  • colorbar_min (float, optional) – Minimum value label in the color bar. Defaults to None. Values are taken from scale_range in this case.

  • colorbar_max (float, optional) – Maximum value label in the color bar. Defaults to None. Values are taken from scale_range in this case.

  • output_map_name (str, optional) – Name/Path of the output file. Must be an HTML file. Defaults to None. The output file is not generated in the default case.

Returns

Returns the map that is generated using all the specified

configurations.

Return type

leafmap.Map

climate_resilience.visualize.plot_site_on_map(site: pandas.core.series.Series, icon_name: str, ipl_map: leafmap.leafmap.Map, feature: str) → None

Plot a single site on the map. Also provides a tooltip at the markers showing the values and site ID.

Parameters

  • site (pd.Series) – Site to be plotted on the map.

  • icon_name (str) – Icon to be used as marker on the map.

  • ipl_map (leafmap.Map) – Map on which the site markers are added.

  • feature (str) – Feature based on which the markers are generated.