Loading Pystare and Modules#

[1]:

import pystare

[2]:

import numpy
from pyhdf.SD import SD

Conversions#

[3]:

lat = numpy.array([30, 45, 60], dtype=numpy.double)
lon = numpy.array([45, 60, 10], dtype=numpy.double)

indices = pystare.from_latlon(lat, lon, 5)
indices

[3]:

array([4151504989081014885, 4161865161846704581, 3643626718498217157])

[4]:

lat, lon = pystare.to_latlon(indices)
lat, lon, level = pystare.to_latlonlevel(indices)
print(lat)
print(lon)
print(level)
pystare.to_latlonlevel(indices)

[30.00000012 45.00000003 59.99999986]
[44.99999991 60.00000013  9.9999999 ]
[5 5 5]

[4]:

(array([30.00000012, 45.00000003, 59.99999986]),
 array([44.99999991, 60.00000013,  9.9999999 ]),
 array([5, 5, 5], dtype=int32))

[7]:

hdf = SD('../tests/data/MOD05_L2.A2019336.0000.061.2019336211522.hdf')
lats = hdf.select('Latitude')[0:3, 0:3].astype('double')
lons = hdf.select('Longitude')[0:3, 0:3].astype('double')
pystare.from_latlon_2d(lats, lons, adapt_level=True)

[7]:

array([[4298473764500464809, 4298458168380511209, 4297394569014717897],
       [4298462872969244297, 4298459225563237225, 4297297422977447753],
       [4298462873435275369, 4298459227962358473, 4297297429637206121]])

[8]:

area = pystare.to_area(indices)
area

[8]:

array([0.0014197 , 0.00143268, 0.00130733])

Covers#

[9]:

import geopandas
path = geopandas.datasets.get_path('naturalearth_lowres')
world = geopandas.read_file(path)
de = world[world.name=='Poland']
geom = de.simplify(1).iloc[0]
lon, lat = geom.exterior.xy
lat = lat[::-1]
lon = lon[::-1]
geom

[9]:
../../_images/examples_notebooks_spatial_conversions_9_0.svg
[12]:

pystare.cover_from_hull(lat, lon, 4)#.size

[12]:

array([4251398048237748228, 4255901647865118724, 4258153447678803972,
       4539628424389459972, 4541880224203145220, 4546383823830515716])

[13]:

pystare.cover_from_ring(lat, lon, 5)#.size

[13]:

array([4252523948144590853, 4256464597818540037, 4257590497725382661,
       4258716397632225285, 4540191374342881285, 4542443174156566533,
       4543006124109987845, 4543569074063409157, 4546383823830515717,
       4547509723737358341, 4548072673690779653])

[14]:

pystare.to_vertices_latlon([4254212798004854789])

[14]:

(array([53.89745687, 56.8965353 , 56.93769843]),
 array([ 9.22866958, 13.23186479,  8.07137938]),
 array([55.93005351]),
 array([10.15342841]))

Overlay#

[15]:

intersected = pystare.intersection(indices, indices, multi_resolution=False)
print(indices)
print(intersected)
set(indices) == set(intersected)
pystare.to_level(intersected)

[4151504989081014885 4161865161846704581 3643626718498217157]
[3643412098542731269 4151192956528754693 4161326055690338309]

[15]:

array([5, 5, 5], dtype=int32)

[16]:

sids = numpy.array([4251398048237748227, 4269412446747230211, 4278419646001971203,])
pystare.intersects(sids, numpy.array([1251398048237748227, 4269412446747230210]), method=2)

[16]:

array([False,  True])

[17]:

sids1 = [4251398048237748227, 4269412446747230211, 4278419646001971203, 4539628424389459971]
sids2 = [4251398048237748228, 4255901647865118724, 4258153447678803972, 4539628424389459972]
pystare.intersection(sids1, sids2, multi_resolution=False)

[17]:

array([4251398048237748228, 4255901647865118724, 4258153447678803972,
       4539628424389459972])

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