Metadata-Version: 2.1
Name: EOmaps
Version: 2.1.1
Summary: A library to create interactive maps of geographical datasets.
Home-page: https://github.com/raphaelquast/maps
Author: Raphael Quast
Author-email: raphael.quast@geo.tuwien.ac.at
Maintainer: Raphael Quast
Maintainer-email: raphael.quast@geo.tuwien.ac.at
License: GNU General Public License v3 or later (GPLv3+)
Description: [![tests](https://github.com/raphaelquast/EOmaps/actions/workflows/testMaps.yml/badge.svg?branch=master)](https://github.com/raphaelquast/EOmaps/actions/workflows/testMaps.yml)
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        [![pypi](https://img.shields.io/pypi/v/eomaps)](https://pypi.org/project/eomaps/)
        [![Documentation Status](https://readthedocs.org/projects/eomaps/badge/?version=latest)](https://eomaps.readthedocs.io/en/latest/?badge=latest)
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        # EOmaps
        
        ### ... a library to create interactive maps of geographical datasets
        
        <ol type="none">
          <li>🌍 A simple interface to visualize geographical datasets ... a pandas DataFrame is all you need!</li>
          <ul type="none">
            <li>⬥ applicable also for large datasets with ~ 1M datapoints!  </li>
          </ul>
          <li>🌎 Quickly turn your maps into powerful interactive data-analysis widgets!</li>
          <ul type="none">
            <li>⬥ compare multiple data-layers, WebMaps etc. with only a few lines of code! </li>
            <li>⬥ use callback functions to interact with the data (or an underlying database) </li>
          </ul>
        </ol>
        
        
        #### 🛸 checkout the [documentation](https://eomaps.readthedocs.io/en/latest) for more details and [examples](https://eomaps.readthedocs.io/en/latest/EOmaps_examples.html) 🛸
        
        ## 🔨 installation
        
        Installing EOmaps can be done via `pip`.  
        However, to make sure all dependencies are correctly installed, make sure to have a look at the [installation instructions](https://eomaps.readthedocs.io/en/latest/general.html#installation) in the documentation!
        
        <br/>
        
        <p align="center">
        <img src="https://github.com/raphaelquast/EOmaps/blob/dev/docs/_static/fig2.gif?raw=true" alt="EOmaps example image 1">
        <img src="https://github.com/raphaelquast/EOmaps/blob/dev/docs/_static/fig6.gif?raw=true" alt="EOmaps example image 2">
        </p>
        
        
        ## 🌳 basic usage
        - A pandas DataFrame is all you need as input!
          - plots of large (>1M datapoints) irregularly sampled datasets are generated in a few seconds!
          - Represent your data as shapes with actual geographic dimensions
          - Re-project the data to any crs supported by `cartopy`
        - Add annotations, overlays, WebMap-layers etc. to the maps
        - ... and get a nice colorbar with a colored histogram on top!
        
        ```python
        import pandas as pd
        from eomaps import Maps
        
        # the data you want to plot
        data = pd.DataFrame(dict(lat=[...], lon=[...], value=[...]))
        
        # initialize Maps object
        m = Maps()
        # set the data
        m.set_data(data=data, xcoord="lon", ycoord="lat", parameter="value", crs=4326)
        # set the shapes that you want to use to represent the data-points
        m.set_shape.geod_circles(radius=10000) # (e.g. geodetic circles with 10km radius)
        # set the appearance of the plot
        m.set_plot_specs(crs=Maps.CRS.Orthographic(), cmap="viridis")
        # (optionally) classify the data
        m.set_classify_specs(scheme=Maps.CLASSIFIERS.Quantiles, k=5)
        # plot the map
        m.plot_map()
        ```
        #### attach callback functions to interact with the plot
        
        - Many pre-defined functions for common tasks are available!
          - display coordinates and values, add markers, compare data-layers etc.
          - ... or define your own function and attach it to the plot!
        - Maps objects can be interactively connected to analyze relations between datasets!
        
        ```python
        # get a nice annotation if you click on a datapoint
        m.cb.pick.attach.annotate()
        # draw a marker if you click on a datapoint
        m.cb.pick.attach.mark(facecolor="r", edgecolor="g", shape="rectangles", radius=1, radius_crs=4326)
        
        # show the data-layer `1` in a inset-rectangle (size=20% width of the axes) if you click on the map
        m.cb.click.attach.peek_layer(how=0.2, layer=1)
        #attach some custom function to interact with the map
        m.cb.click.attach(<... a custom function ...>)
        
        # show the data-layer `1` if you press "a" on the keyboard and the layer `0` if you press "q"
        m.cb.keypress.attach.switch_layer(layer=0, key="q")
        m.cb.keypress.attach.switch_layer(layer=1, key="a")
        ```
        #### add additional layers and overlays
        ```python
        m.add_wms(...)             # add WebMapService layers
        m.add_wms(...)             # add WebMapTileService layers
        m.add_gdf(...)             # add geo-dataframes
        m.add_overlay(...)         # add overlay-layers from NaturalEarth
        
        m.add_annotation(...)      # add static annotations
        m.add_marker(...)          # add static markers
        ```
        #### save the figure
        ```python
        m.savefig("oooh_what_a_nice_figure.png", dpi=300)  
        ```
        ## advanced usage
        #### connect Maps-objects to get multiple interactive layers of data!
        ```python
        m = Maps()
        ...
        m.plot_map()
        
        m2 = Maps(parent=m) # connect Maps to get multiple interactive data-layers
        m2.set_data(...)
        m2.set_shape(...)
        ...
        m2.plot_map(layer=2)         # plot another layer of data
        m2.cb.attach.peek_layer(layer=2, how=0.25)
        ```
        #### plot grids of maps
        ```python
        from eomaps import MapsGrid
        mgrid = MapsGrid(2, 2, connect=True)
        
        for m in mgrid:
           m.plot_specs.plot_crs = 3857
        
        mgrid.ax_0_0.plot_map()
        mgrid.ax_0_1.plot_map()
        mgrid.ax_1_0.plot_map()
        mgrid.ax_1_1.plot_map()
        
        mgrid.parent.join_limits(*mgrid.children)   # join limits
        ```
        
Keywords: visualization,plotting,maps,geographical data
Platform: UNKNOWN
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering :: Visualization
Classifier: License :: OSI Approved :: GNU General Public License v3 or later (GPLv3+)
Classifier: Programming Language :: Python :: 3.7
Description-Content-Type: text/markdown
