#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Tue Feb 25 05:46:36 2020
@author: deborahkhider
Contains all relevant mapping functions
"""
__all__=['map_all']
import cartopy.crs as ccrs
import cartopy.feature as cfeature
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
from .plotting import savefig, showfig
[docs]def set_proj(projection='Robinson', proj_default = True):
""" Set the projection for Cartopy.
Parameters
----------
projection : string
the map projection. Available projections:
'Robinson' (default), 'PlateCarree', 'AlbertsEqualArea',
'AzimuthalEquidistant','EquidistantConic','LambertConformal',
'LambertCylindrical','Mercator','Miller','Mollweide','Orthographic',
'Sinusoidal','Stereographic','TransverseMercator','UTM',
'InterruptedGoodeHomolosine','RotatedPole','OSGB','EuroPP',
'Geostationary','NearsidePerspective','EckertI','EckertII',
'EckertIII','EckertIV','EckertV','EckertVI','EqualEarth','Gnomonic',
'LambertAzimuthalEqualArea','NorthPolarStereo','OSNI','SouthPolarStereo'
proj_default : bool
If True, uses the standard projection attributes from Cartopy.
Enter new attributes in a dictionary to change them. Lists of attributes
can be found in the Cartopy documentation:
https://scitools.org.uk/cartopy/docs/latest/crs/projections.html#eckertiv
Returns
-------
proj : the Cartopy projection object
See Also
--------
pyleoclim.utils.mapping.map_all : mapping function making use of the projection
"""
if proj_default is not True and type(proj_default) is not dict:
raise TypeError('The default for the projections should either be provided'+
' as a dictionary or set to True')
# Set the projection
if projection == 'Robinson':
if proj_default is True:
proj = ccrs.Robinson()
else: proj = ccrs.Robinson(**proj_default)
elif projection == 'PlateCarree':
if proj_default is True:
proj = ccrs.PlateCarree()
else: proj = ccrs.PlateCarree(**proj_default)
elif projection == 'AlbersEqualArea':
if proj_default is True:
proj = ccrs.AlbersEqualArea()
else: proj = ccrs.AlbersEqualArea(**proj_default)
elif projection == 'AzimuthalEquidistant':
if proj_default is True:
proj = ccrs.AzimuthalEquidistant()
else: proj = ccrs.AzimuthalEquidistant(**proj_default)
elif projection == 'EquidistantConic':
if proj_default is True:
proj = ccrs.EquidistantConic()
else: proj = ccrs.EquidistantConic(**proj_default)
elif projection == 'LambertConformal':
if proj_default is True:
proj = ccrs.LambertConformal()
else: proj = ccrs.LambertConformal(**proj_default)
elif projection == 'LambertCylindrical':
if proj_default is True:
proj = ccrs.LambertCylindrical()
else: proj = ccrs.LambertCylindrical(**proj_default)
elif projection == 'Mercator':
if proj_default is True:
proj = ccrs.Mercator()
else: proj = ccrs.Mercator(**proj_default)
elif projection == 'Miller':
if proj_default is True:
proj = ccrs.Miller()
else: proj = ccrs.Miller(**proj_default)
elif projection == 'Mollweide':
if proj_default is True:
proj = ccrs.Mollweide()
else: proj = ccrs.Mollweide(**proj_default)
elif projection == 'Orthographic':
if proj_default is True:
proj = ccrs.Orthographic()
else: proj = ccrs.Orthographic(**proj_default)
elif projection == 'Sinusoidal':
if proj_default is True:
proj = ccrs.Sinusoidal()
else: proj = ccrs.Sinusoidal(**proj_default)
elif projection == 'Stereographic':
if proj_default is True:
proj = ccrs.Stereographic()
else: proj = ccrs.Stereographic(**proj_default)
elif projection == 'TransverseMercator':
if proj_default is True:
proj = ccrs.TransverseMercator()
else: proj = ccrs.TransverseMercator(**proj_default)
elif projection == 'TransverseMercator':
if proj_default is True:
proj = ccrs.TransverseMercator()
else: proj = ccrs.TransverseMercator(**proj_default)
elif projection == 'UTM':
if proj_default is True:
proj = ccrs.UTM()
else: proj = ccrs.UTM(**proj_default)
elif projection == 'UTM':
if proj_default is True:
proj = ccrs.UTM()
else: proj = ccrs.UTM(**proj_default)
elif projection == 'InterruptedGoodeHomolosine':
if proj_default is True:
proj = ccrs.InterruptedGoodeHomolosine()
else: proj = ccrs.InterruptedGoodeHomolosine(**proj_default)
elif projection == 'RotatedPole':
if proj_default is True:
proj = ccrs.RotatedPole()
else: proj = ccrs.RotatedPole(**proj_default)
elif projection == 'OSGB':
if proj_default is True:
proj = ccrs.OSGB()
else: proj = ccrs.OSGB(**proj_default)
elif projection == 'EuroPP':
if proj_default is True:
proj = ccrs.EuroPP()
else: proj = ccrs.EuroPP(**proj_default)
elif projection == 'Geostationary':
if proj_default is True:
proj = ccrs.Geostationary()
else: proj = ccrs.Geostationary(**proj_default)
elif projection == 'NearsidePerspective':
if proj_default is True:
proj = ccrs.NearsidePerspective()
else: proj = ccrs.NearsidePerspective(**proj_default)
elif projection == 'EckertI':
if proj_default is True:
proj = ccrs.EckertI()
else: proj = ccrs.EckertI(**proj_default)
elif projection == 'EckertII':
if proj_default is True:
proj = ccrs.EckertII()
else: proj = ccrs.EckertII(**proj_default)
elif projection == 'EckertIII':
if proj_default is True:
proj = ccrs.EckertIII()
else: proj = ccrs.EckertIII(**proj_default)
elif projection == 'EckertIV':
if proj_default is True:
proj = ccrs.EckertIV()
else: proj = ccrs.EckertIV(**proj_default)
elif projection == 'EckertV':
if proj_default is True:
proj = ccrs.EckertV()
else: proj = ccrs.EckertV(**proj_default)
elif projection == 'EckertVI':
if proj_default is True:
proj = ccrs.EckertVI()
else: proj = ccrs.EckertVI(**proj_default)
elif projection == 'EqualEarth':
if proj_default is True:
proj = ccrs.EqualEarth()
else: proj = ccrs.EqualEarth(**proj_default)
elif projection == 'Gnomonic':
if proj_default is True:
proj = ccrs.Gnomonic()
else: proj = ccrs.Gnomonic(**proj_default)
elif projection == 'LambertAzimuthalEqualArea':
if proj_default is True:
proj = ccrs.LambertAzimuthalEqualArea()
else: proj = ccrs.LambertAzimuthalEqualArea(**proj_default)
elif projection == 'NorthPolarStereo':
if proj_default is True:
proj = ccrs.NorthPolarStereo()
else: proj = ccrs.NorthPolarStereo(**proj_default)
elif projection == 'OSNI':
if proj_default is True:
proj = ccrs.OSNI()
else: proj = ccrs.OSNI(**proj_default)
elif projection == 'OSNI':
if proj_default is True:
proj = ccrs.SouthPolarStereo()
else: proj = ccrs.SouthPolarStereo(**proj_default)
else:
raise ValueError('Invalid projection type')
return proj
[docs]def map_all(lat, lon, criteria, marker=None, color =None,
projection = 'Robinson', proj_default = True,
background = True,borders = False, rivers = False, lakes = False,
figsize = None, ax = None, scatter_kwargs=None, legend=True,
lgd_kwargs=None,savefig_settings=None, mute=False):
""" Map the location of all lat/lon according to some criteria
Map the location of all lat/lon according to some criteria. Based on functions defined in the Cartopy package.
Parameters
----------
lat : list
a list of latitudes.
lon : list
a list of longitudes.
criteria : list
a list of unique criteria for plotting purposes. For instance,
a map by the types of archive present in the dataset or proxy
observations. Should have the same length as lon/lat.
marker : list
a list of possible markers for each criterion. If None, will use pyleoclim default
color : list
a list of possible colors for each criterion. If None, will use pyleoclim default
projection : string
the map projection. Available projections:
'Robinson' (default), 'PlateCarree', 'AlbertsEqualArea',
'AzimuthalEquidistant','EquidistantConic','LambertConformal',
'LambertCylindrical','Mercator','Miller','Mollweide','Orthographic',
'Sinusoidal','Stereographic','TransverseMercator','UTM',
'InterruptedGoodeHomolosine','RotatedPole','OSGB','EuroPP',
'Geostationary','NearsidePerspective','EckertI','EckertII',
'EckertIII','EckertIV','EckertV','EckertVI','EqualEarth','Gnomonic',
'LambertAzimuthalEqualArea','NorthPolarStereo','OSNI','SouthPolarStereo'
proj_default : bool
If True, uses the standard projection attributes.
Enter new attributes in a dictionary to change them. Lists of attributes
can be found in the Cartopy documentation:
https://scitools.org.uk/cartopy/docs/latest/crs/projections.html#eckertiv
background : bool
If True, uses a shaded relief background (only one
available in Cartopy)
borders : bool
Draws the countries border. Defaults is off (False).
rivers : bool
Draws major rivers. Default is off (False).
lakes : bool
Draws major lakes.
Default is off (False).
figsize : list
the size for the figure
ax: axis,optional
Return as axis instead of figure (useful to integrate plot into a subplot)
scatter_kwargs : dict
Dictionary of arguments available in matplotlib.pyplot.scatter (https://matplotlib.org/3.2.1/api/_as_gen/matplotlib.pyplot.scatter.html).
legend : bool
Whether the draw a legend on the figure
lgd_kwargs : dict
Dictionary of arguments for matplotlib.pyplot.legend (https://matplotlib.org/3.2.1/api/_as_gen/matplotlib.pyplot.legend.html)
savefig_settings : dict
Dictionary of arguments for matplotlib.pyplot.saveFig.
- "path" must be specified; it can be any existed or non-existed path,
with or without a suffix; if the suffix is not given in "path", it will follow "format"
- "format" can be one of {"pdf", "eps", "png", "ps"}
mute : bool
if True, the plot will not show;
recommend to set to true when more modifications are going to be made on ax
Returns
-------
ax: The figure, or axis if ax specified
See Also
--------
pyleoclim.utils.mapping.set_proj : Set the projection for Cartopy-based maps
"""
#Take care of duplicate legends
def legend_without_duplicate_labels(ax):
handles, labels = ax.get_legend_handles_labels()
unique = [(h, l) for i, (h, l) in enumerate(zip(handles, labels)) if l not in labels[:i]]
ax.legend(*zip(*unique),**lgd_kwargs)
#Check that the lists have the same length and convert to numpy arrays
if len(lat)!=len(lon) or len(lat)!=len(criteria) or len(lon)!=len(criteria):
raise ValueError("Latitude, Longitude, and criteria list must be the same" +\
"length")
# Check that the default is set to True or in dictionary format
if proj_default is not True and type(proj_default) is not dict:
raise TypeError('The default for the projections should either be provided'+
' as a dictionary or set to True')
# handle dict defaults
savefig_settings={} if savefig_settings is None else savefig_settings.copy()
scatter_kwargs = {} if scatter_kwargs is None else scatter_kwargs.copy()
lgd_kwargs = {} if lgd_kwargs is None else lgd_kwargs.copy()
if marker!=None:
if 'marker' in scatter_kwargs.keys():
print('marker has been set as a parameter to the map_all function, overriding scatter_kwargs')
del scatter_kwargs['marker']
if type(marker) == list and len(marker)!=len(criteria):
raise ValueError('The marker vector should have the same length as the lat/lon/criteria vector')
if color!=None:
if 'facecolor' in scatter_kwargs.keys():
print('facecolor has been set as a parameter to the map_all function, overriding scatter_kwargs')
del scatter_kwargs['facecolor']
if type(color) == list and len(color)!=len(criteria):
raise ValueError('The color vector should have the same length as the lon/lat/criteria vector')
# Prepare scatter information
if 's' in scatter_kwargs.keys():
if type(scatter_kwargs['s']) == list and len(scatter_kwargs['s']) !=len(criteria):
raise ValueError('If s is a list, it should have the same length as lon/lat/criteria')
else:
scatter_kwargs['s'] = None
if 'edgecolors' in scatter_kwargs.keys():
if type(scatter_kwargs['edgecolors']) == list and len(scatter_kwargs['edgecolors']) !=len(criteria):
raise ValueError('If edgecolors is a list, it should have the same length as lon/lat/criteria')
else:
scatter_kwargs['edgecolors'] = None
color_data=pd.DataFrame({'criteria':criteria,'color':color,'marker':marker,
's': scatter_kwargs['s'], 'edgecolors': scatter_kwargs['edgecolors']})
#delete extra scatter_kwargs
del scatter_kwargs['s']
del scatter_kwargs['edgecolors']
# get the projection:
proj = set_proj(projection=projection, proj_default=proj_default)
data_crs = ccrs.PlateCarree()
# Make the figure
if ax is None:
fig, ax = plt.subplots(figsize=figsize,subplot_kw=dict(projection=proj))
# draw the coastlines
ax.add_feature(cfeature.COASTLINE)
# Background
if background is True:
ax.stock_img()
#Other extra information
if borders is True:
ax.add_feature(cfeature.BORDERS)
if lakes is True:
ax.add_feature(cfeature.LAKES)
if rivers is True:
ax.add_feature(cfeature.RIVERS)
# Get the indexes by criteria
for index, crit in enumerate(criteria):
ax.scatter(np.array(lon)[index],np.array(lat)[index],
zorder = 10,
label = crit,
transform=data_crs,
marker = color_data['marker'].iloc[index],
color = color_data['color'].iloc[index],
s = color_data['s'].iloc[index],
edgecolors= color_data['edgecolors'].iloc[index],
**scatter_kwargs)
if legend == True:
#ax.legend(**lgd_kwargs)
legend_without_duplicate_labels(ax)
else:
ax.legend().remove()
if 'fig' in locals():
if 'path' in savefig_settings:
savefig(fig, settings=savefig_settings)
else:
if not mute:
showfig(fig)
return fig, ax
else:
return ax
[docs]def dist_sphere(lat1,lon1,lat2,lon2):
"""Uses the harversine formula to calculate distance on a sphere
Parameters
----------
lat1: float
Latitude of the first point, in radians
lon1: float
Longitude of the first point, in radians
lat2: float
Latitude of the second point, in radians
lon2: float
Longitude of the second point, in radians
Returns
-------
dist: float
The distance between the two point in km
"""
R = 6371 #km. Earth's radius
dlat = lat2-lat1
dlon = lon2-lon1
a = np.sin(dlat/2)**2+np.cos(lat1)*np.cos(lat2)*np.sin(dlon/2)**2
c = 2*np.arctan2(np.sqrt(a),np.sqrt(1-a))
dist =R*c
return float(dist)
[docs]def compute_dist(lat_r, lon_r, lat_c, lon_c):
""" Computes the distance in (km) between a reference point and an array
of other coordinates.
Parameters
----------
lat_r: float
The reference latitude, in deg
lon_r: float
The reference longitude, in deg
lat_c: list
A list of latitudes for the comparison points, in deg
lon_c: list
A list of longitudes for the comparison points, in deg
See also
--------
pyleoclim.utils.mapping.dist_sphere: calculate distance on a sphere
Returns
-------
dist: list
A list of distances in km.
"""
dist = []
for idx, val in enumerate (lat_c):
lat1 = np.radians(lat_r)
lon1 = np.radians(lon_r)
lat2 = np.radians(val)
lon2 = np.radians(lon_c[idx])
dist.append(dist_sphere(lat1,lon1,lat2,lon2))
return dist
[docs]def within_distance(distance, radius):
""" Returns the index of the records that are within a certain distance
Parameters:
-----------
distance: list
A list containing the distance
radius: float
The radius to be considered
Returns
-------
idx: list
a list of index
"""
idx = [idx for idx,val in enumerate(distance) if val <= radius]
return idx