mirror of
https://github.com/ComradCollective/Comrad
synced 2024-11-19 15:25:34 +00:00
259 lines
7.3 KiB
Python
259 lines
7.3 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 curses,random,time
|
|
|
|
|
|
import warnings
|
|
warnings.filterwarnings(action='ignore')
|
|
|
|
|
|
|
|
# read the data into a list of shapely geometries
|
|
with open(os.path.join(os.path.dirname(__file__),"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':(37.774929,-122.419418),
|
|
'Honolulu':(21.306944,-157.858337),
|
|
'Tokyo':(35.689487,139.691711),
|
|
'Ushuaia':(-54.801910,-68.302948),
|
|
'Reykjavik':(64.126518,-21.817438)
|
|
|
|
}
|
|
|
|
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()
|
|
|
|
|
|
|
|
# print_map(['Brazil','Netherlands','Thailand'])
|
|
# print_map_simple(places)
|
|
|
|
def print_map(places):
|
|
curses.wrapper(run_print_map)
|
|
|
|
def run_print_map(stdscr):
|
|
curses.use_default_colors()
|
|
stdscr.addstr(0,0,'helloooooo')
|
|
stdscr.refresh()
|
|
|
|
rows, cols = stdscr.getmaxyx()
|
|
print(rows,cols)
|
|
rows = rows-10
|
|
cols = cols - 10
|
|
|
|
df = do_print_map(places,rows,cols)
|
|
for df_i,df_row in df.iterrows():
|
|
#try:
|
|
stdscr.addstr(df_row.y_win,df_row.x_win,'x '+df_row.place)
|
|
#except curses.error:
|
|
# pass
|
|
stdscr.getch()
|
|
|
|
|
|
def do_print_map(places,rows,cols):
|
|
normed = []
|
|
for place,(lat,long) in places.items():
|
|
wgs84 = pyproj.Proj(init="EPSG:4326")
|
|
webmerc = pyproj.Proj(proj="webmerc")
|
|
x, y = pyproj.transform(wgs84, webmerc, long, lat)
|
|
norm = {'place':place,'lat':lat,'long':long,'x':x,'y':y}
|
|
normed.append(norm)
|
|
|
|
import pandas as pd
|
|
df=pd.DataFrame(normed)
|
|
def do_norm(x,xcol): return (x - xcol.min()) / (xcol.max() - xcol.min())
|
|
df['x_norm'] = [do_norm(x,df['x']) for x in df['x']]
|
|
df['y_norm'] = [do_norm(y,df['y']) for y in df['y']]
|
|
df['x_win'] = [int(x*cols) for x in df['x_norm']]
|
|
df['y_win'] = [rows - int(y*rows) for y in df['y_norm']]
|
|
|
|
return df
|
|
|
|
|
|
if __name__ == '__main__':
|
|
|
|
# do_print_map(places,60,30)
|
|
print_map(places)
|