Visualize Data¶

In [1]:

import geolime as geo
from pyproj import CRS

geo.Project().set_crs(CRS("EPSG:20350"))

import geolime as geo from pyproj import CRS geo.Project().set_crs(CRS("EPSG:20350"))

In [3]:

dh = geo.datasets.load("rocklea_dome/dh_hyper.geo")

dh = geo.datasets.load("rocklea_dome/dh_hyper.geo")

In [4]:

gis_obj = geo.datasets.load('rocklea_dome/hyperspec_outline.shp')

gis_obj = geo.datasets.load('rocklea_dome/hyperspec_outline.shp')

Spatial Visualization¶

Visualize Data With No Coordinate Reference System (CRS)¶

XY Plot¶

In [5]:

geo.plot(dh, property="Fe_pct", agg_method="mean", width=400, height=650)

geo.plot(dh, property="Fe_pct", agg_method="mean", width=400, height=650)

Contour Plot¶

In [6]:

geo.contour_plot(dh, property="Fe_pct", fill_contour=True, width=400, height=650)

geo.contour_plot(dh, property="Fe_pct", fill_contour=True, width=400, height=650)

In [7]:

geo.contour_plot(dh, property="Fe_pct", fill_contour=False, width=400, height=650)

geo.contour_plot(dh, property="Fe_pct", fill_contour=False, width=400, height=650)

Visualize Data With Coordinate Reference System (CRS)¶

Using Plotly¶

Single GeoRefObject¶

In [8]:

geo.plot_2d(
    dh, 
    property="Fe_pct", 
    agg_method="mean", 
    width=400, 
    height=650
)

geo.plot_2d( dh, property="Fe_pct", agg_method="mean", width=400, height=650 )

Single GISObject¶

In [9]:

geo.plot_2d(
    gis_obj, 
    property="FID", 
    width=400, 
    height=650
)

geo.plot_2d( gis_obj, property="FID", width=400, height=650 )

Multiple GeoLime Objects¶

Note that the order of the list indicates the order of the layer on the map, ie: the first object defined is the most below one.

In [10]:

geo.plot_2d(
    [
        {"georef_object": gis_obj, "property": "FID"},
        {"georef_object": dh, "property": "Fe_pct", "agg_method":'sum'},
    ],
    width=400, 
    height=650,
    colorscale='viridis'
)

geo.plot_2d( [ {"georef_object": gis_obj, "property": "FID"}, {"georef_object": dh, "property": "Fe_pct", "agg_method":'sum'}, ], width=400, height=650, colorscale='viridis' )

Using Folium¶

In [11]:

dh.plot_2d("Fe_pct", "mean", interactive_map=True)

dh.plot_2d("Fe_pct", "mean", interactive_map=True)

Out[11]:

Make this Notebook Trusted to load map: File -> Trust Notebook

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Last update: 2023-10-23