map_plotter.py

#!/usr/bin/python3
# Copyright 2018-2022 Francisco Pina Martins <f.pinamartins@gmail.com>
# This file is part of pyRona.
# pyRona is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.

# pyRona is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
# GNU General Public License for more details.

# You should have received a copy of the GNU General Public License
# along with pyRona.  If not, see <http://www.gnu.org/licenses/>.

import cartopy.crs as ccrs
import cartopy.feature as cfeature
import cartopy.io.shapereader as shpreader
from cartopy.mpl.gridliner import LONGITUDE_FORMATTER, LATITUDE_FORMATTER
import matplotlib.pyplot as plt
import numpy as np


def map_plotter(samples, latitudes, longitudes, out_filename, shapefile):
    """
    Plots a map with each sampling site coloured per its averag RONA value
    """
    def _define_map_edges(latitudes, longitudes, padding=0.10):
        """
        Defines the edges of the map to be drawn.
        Takes a list of latitudes and longitudes as input and returns the map
         edges
        """
        # Define padding for the map edges
        hpad = padding
        vpad = padding

        # Get map edges
        max_lon = np.max(longitudes)
        max_lon = max_lon + abs(max_lon * vpad)
        min_lon = np.min(longitudes)
        min_lon = min_lon - abs(min_lon * vpad)

        max_lat = np.max(latitudes)
        max_lat = max_lat + abs(max_lat * hpad)
        min_lat = np.min(latitudes)
        min_lat = min_lat - abs(min_lat * hpad)

        return([min_lat, max_lat, min_lon, max_lon])

    pop_names = samples

    fig = plt.figure(figsize=(22, 12), facecolor="none")
    map_area = plt.axes(projection=ccrs.PlateCarree())

    map_edges = _define_map_edges(latitudes, longitudes)

    map_area.set_extent(map_edges)
    map_area.coastlines(resolution='50m')
    #cfeature.BORDERS.scale = "100m"
    map_area.add_feature(cfeature.BORDERS)

    # Draw sampling sites
    dotplot = map_area.scatter(latitudes, longitudes, c="black", s=220,
                               #vmin=0, vmax=max(max_ronas),
                               transform=ccrs.PlateCarree(),
                               cmap='autumn_r', zorder=2)

    # Label the locations
    for label, x, y in zip(pop_names, latitudes, longitudes):
        map_area.annotate(label.strip().replace("_", " "), xy=(x, y),
                          xytext=(0, -28), textcoords='offset points',
                          ha='center', va='bottom', fontsize=17,
                          bbox=dict(boxstyle='round,pad=0.1',
                                    fc='lightgrey', edgecolor="none"))

    # Plot distribution shapefile
    # Based on https://techoverflow.net/2021/04/25/how-to-plot-shapefile-data-in-cartopy/
    my_distribution = shpreader.Reader(shapefile)
    dist = [loc for loc in my_distribution.records()]

    for area in dist:
        dist_feature = cfeature.ShapelyFeature([area.geometry],
                                               ccrs.PlateCarree(),
                                               facecolor="#61a40fff",
                                               edgecolor='black',
                                               lw=1)
        map_area.add_feature(dist_feature)


    # Control x and y ticks
    gridlines = map_area.gridlines(draw_labels=True)
    gridlines.xlines = False
    gridlines.ylines = False
    gridlines.ylabels_right = False
    gridlines.xlabels_top = False
    gridlines.xformatter = LONGITUDE_FORMATTER
    gridlines.yformatter = LATITUDE_FORMATTER
    gridlines.xlabel_style = {'size': 22}
    gridlines.ylabel_style = {'size': 22}

    # Control x and y labels
    map_area.text(-0.10, 0.55, 'Latitude', va='bottom', ha='center',
                  rotation='vertical', rotation_mode='anchor',
                  transform=map_area.transAxes, fontsize=28)
    map_area.text(0.5, -0.12, 'Longitude', va='bottom', ha='center',
                  rotation='horizontal', rotation_mode='anchor',
                  transform=map_area.transAxes, fontsize=28)

    # Sidebar settings
    #sidebar = fig.colorbar(dotplot)
    #sidebar.ax.tick_params(labelsize=20)
    #sidebar.set_label(label='RONA', size=30, weight='bold')

    # Save the map
    fig.savefig(out_filename)


def input_parser(input_filename):
    """
    Parses a csv with 3 columns: Sample_names, Latitude, Longitude
    Returns 3 lists, one for each column
    """
    input_handle = open(input_filename, 'r')
    input_handle.readline()  # Skip header
    samples = []
    lats = []
    longs = []
    for lines in input_handle:
        lines = lines.strip().split()
        samples.append(lines[0])
        lats.append(float(lines[2]))
        longs.append(float(lines[1]))

    return samples, lats, longs


if __name__ == "__main__":
    # Usage: python map_plotter.py sample_coords.csv map_file.svg shapefile.shp
    from sys import argv
    SAMPLES, LATS, LONGS = input_parser(argv[1])
    map_plotter(SAMPLES, LATS, LONGS, argv[2], argv[3])