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Comrad/comrad/cli/worldmap.py
2020-09-29 14:09:56 +01:00

205 lines
5.8 KiB
Python

# Code from
# https://github.com/snorfalorpagus/ascii-world-map
import json
from functools import partial
from shutil import get_terminal_size
from shapely.geometry import shape, Point
from shapely import ops
import pyproj,math,os
import rtree
import warnings
warnings.filterwarnings(action='ignore')
# read the data into a list of shapely geometries
with open("data/world-countries2.json") as f:
data = json.load(f)
def print_map(countries=[]):
geoms_all = [
shape(feature["geometry"])
for feature in data["features"]
]
geoms = [
shape(feature["geometry"])
for feature in data["features"]
if not countries or feature.get('properties',{}).get('name',None) in countries
]
# transform the geometries into web mercator
wgs84 = pyproj.Proj(init="EPSG:4326")
webmerc = pyproj.Proj(proj="webmerc")
t = partial(pyproj.transform, wgs84, webmerc)
geoms = [ops.transform(t, geom) for geom in geoms]
geoms_all = [ops.transform(t, geom) for geom in geoms_all]
# create a spatial index of the geometries
def gen(geoms):
for n, geom in enumerate(geoms):
yield n, geom.bounds, geom
index = rtree.index.Index(gen(geoms))
index_all = rtree.index.Index(gen(geoms_all))
# get the window size
size = get_terminal_size(fallback=(80, 24))
columns = size.columns
lines = size.lines - 1 - 3 # allow for prompt at bottom
# calculate the projected extent and pixel size
# xmin, ymin = t(-180, -85)
# xmax, ymax = t(180, 85)
xmin, ymin = t(-180, -62)
xmax, ymax = t(180, 79)
pixel_width = (xmax - xmin) / columns
pixel_height = (ymax - ymin) / lines
land = "*"
water = " "
highlight=''
# stringl=[]
# os.system('cls' if os.name == 'nt' else 'clear')
for line in range(lines):
for col in range(columns):
# get the projected x, y of the pixel centroid
x = xmin + (col + 0.5) * pixel_width
y = ymax - (line + 0.5) * pixel_height
# check for a collision
objects = [n.object for n in index.intersection((x, y, x, y), objects=True)]
value = False
done=False
for geom in objects:
value = geom.intersects(Point(x, y))
if value:
print(highlight,end="")
# stringl+=[highlight]
done=True
break
if not done:
objects = [n.object for n in index_all.intersection((x, y, x, y), objects=True)]
for geom in objects:
value = geom.intersects(Point(x, y))
if value:
break
print(land if value else water, end="")
# stringl+=[land if value else water]
print("")
# stringl+=['\n']
# string = ''.join(stringl)
# print(string)
places = {
'Cambridge':(52.205338,0.121817),
'Sydney':(-33.868820,151.209290),
'New York':(40.712776,-74.005974),
'Hong Kong':(22.278300,114.174700),
'Cape Town':(33.9249, 18.4241),
'San Francisco':(-12.125640,-77.018967),
}
places_utm = {
'Honolulu':(618431.58,2357505.97),
'Tokyo':(394946.08,3946063.75),
'Ushuaia':(544808.23,3927028.51),
'Reykjavik':(459698.38,7111571.73)
}
def print_map_simple(places):
size = get_terminal_size(fallback=(80, 24))
columns = size.columns
lines = size.lines - 1 - 3 # allow for prompt at bottom
# calculate the projected extent and pixel size
# xmin, ymin = (-180, -85)
# xmax, ymax = (180, 85)
# pixel_width = (xmax - xmin) / columns
# pixel_height = (ymax - ymin) / lines
long_min,long_max = -180,180
# lat_min,lat_max = -85,85
lat_min,lat_max = -75,80
# utm_easting_min = 166640
# utm_easting_max = 833360
# utm_northing_min = 1110400
# utm_northing_max = 9334080
utm_easting_min = places_utm['Honolulu'][0]
utm_easting_max = places_utm['Tokyo'][0]
utm_northing_min = places_utm['Ushuaia'][1]
utm_northing_max = places_utm['Reykjavik'][1]
# import pyproj as proj
# setup your projections
# crs_wgs = proj.Proj(init='epsg:4326') # assuming you're using WGS84 geographic
# crs_bng = proj.Proj(init='epsg:27700') # use a locally appropriate projected CRS
import utm
normed = {}
for place,(lat,long) in places.items():
# wgs84 = pyproj.Proj(init="EPSG:4326")
# webmerc = pyproj.Proj(proj="webmerc")
# x, y = proj.transform(wgs84, webmerc, long, lat)
longx = (long - long_min) / (long_max - long_min)
laty = (lat - lat_min) / (lat_max - lat_min)
utm_easting,utm_northing,utm_zone_num,utm_zone_letter = utm.from_latlon(lat,long)
utmx = (utm_easting - utm_easting_min) / (utm_easting_max - utm_easting_min)
utmy = (utm_northing - utm_northing_min) / (utm_northing_max - utm_northing_min)
# norm = ( int(longx*columns), int(laty*lines) )
norm = ( int(utmx*columns), int(utmy*lines) )
# print(place,(utm_easting,utm_northing),(utmx,utmy),norm)
norm = (norm[0], lines - norm[1])
normed[norm] = place
p_i=None
place_now=None
for line in range(lines):
for col in range(columns):
if (col,line) in normed:
print('*',end="")
place=normed[(col,line)]
place_now=place
p_i=0
elif p_i is not None:
try:
print(place_now[p_i],end="")
p_i+=1
except IndexError:
place_now=None
p_i=None
else:
print(" ",end="")
print()
if __name__ == '__main__':
print_map() #['Brazil','Netherlands','Thailand'])
# print_map_simple(places)