plot_by_bands#
- geetools.ee_image.ImageAccessor.plot_by_bands(type, regions, reducer='mean', bands=[], regionId='system:index', labels=[], colors=[], ax=None, scale=10000, crs=None, crsTransform=None, tileScale=1)#
Plot the reduced values for each bands.
Each band will be plotted using the
labelsas x-axis label defauting to band names if not provided. If nobandsare provided, all bands will be plotted. If noregionIdare provided, the “system;index” property will be used.Warning
This method is client-side.
- Parameters:
type (str) – The type of plot to use. Defaults to “bar”. can be any type of plot from the python lib matplotlib.pyplot. If the one you need is missing open an issue!
regions (ee.FeatureCollection) – The regions to compute the reducer in.
reducer (str | ee.Reducer) – The name of the reducer or a reducer object to use. Default is “mean”.
bands (list) – The bands to compute the reducer on. Default to all bands.
regionId (str) – The property used to label region. Defaults to “system:index”.
labels (list) – The labels to use for the output dictionary. Default to the band names.
colors (list) – The colors to use for the plot. Default to the default matplotlib colors.
ax (matplotlib.axes.Axes | None) – The matplotlib axis to plot the data on. If None, a new figure is created.
scale (int) – The scale to use for the computation. Default is 10000m.
crs (str | None) – The projection to work in. If unspecified, the projection of the image’s first band is used. If specified in addition to scale, rescaled to the specified scale.
crsTransform (list | None) – The list of CRS transform values. This is a row-major ordering of the 3x2 transform matrix. This option is mutually exclusive with ‘scale’, and replaces any transform already set on the projection.
tileScale (float) – A scaling factor between 0.1 and 16 used to adjust aggregation tile size; setting a larger tileScale (e.g., 2 or 4) uses smaller tiles and may enable computations that run out of memory with the default.
- Returns:
The matplotlib axis with the plot.
- Return type:
See also
byRegions: Compute a reducer in each region of the image for eah band.byBands: Compute a reducer for each band of the image in each region.plot_by_regions: Plot the reduced values for each region.:docstring:`ee.Image.geetools.plot_hist
Examples
import ee, geetools ee.Initialize() ecoregions = ee.FeatureCollection("projects/google/charts_feature_example").select(["label", "value","warm"]) normClim = ee.ImageCollection('OREGONSTATE/PRISM/Norm91m').toBands() normClim.plot_by_bands(ecoregions, ee.Reducer.mean(), scale=10000)