class GridGenerator(object):
"""
This class subdivides the geographical extent of the United States into an equal area grid.
Dependencies:
/geography_helper.py
/equal_area_globe_grid.py
/united_states_border.json
Usage:
Let X be the desired area in square miles of each equal area cell
>> GridGenerator(sqrt(X)).run()
Output:
/beautiful_grid.kml
"""
def __init__(self, cell_size_miles):
# input is desired square of each equal area cell, in miles
self._cell_size_miles = cell_size_miles
# ecapsulating longitude/latitude boxes for Mainland, Alaska, Hawaii, Puerto Rico
self._geo_reference = USABoundsReference().Geographies
# we'll store each cell's shape array here
self._shape_arrays = []
# a calculator that converts grid (column, row) to (longitude, latitude) and vice versa.
# formulas given by the National Snow and Ice Data Center (see EqualAreaGlobeGrid doc-string for more info)
self._proj_calc = EqualAreaGlobeGrid(self._cell_size_miles)
def run(self):
"""
Public run method - generates an equal area grid for the United States
"""
self._load_US_boundary()
self._create_equal_area_grid()
self._save_to_kml()
def _load_US_boundary(self):
"""
Loads a GeoJSON multipolygon created separately by merging the polygons provided here:
https://developers.google.com/kml/documentation/us_states.kml
"""
geojson_multipolygon_file = open("united_states_border.json", "r")
geojson_multipolygon = json.loads(geojson_multipolygon_file.read())
geojson_multipolygon_file.close()
# create a shapely multipolygon - this will be used to determine if a generated grid cell lies within the USA
self._US_boundary = MultiPolygon(geojson_multipolygon["coordinates"],
context_type="geojson")
def _create_equal_area_grid(self):
"""
For each region in the USA, calculate all equal area cells that either intersect, or are contained within
that region. Each cell follows the numbering convention:
Northwest Corner: (longitude_0, latitude_0)
Northeast Corner: (longitude_1, latitude_1)
Southeast Corner: (longitude_2, latitude_2)
Southwest Corner: (longitude_3, latitude_3)
"""
# loop over all boxes bounding the separate US geographical regions (Mainland, Alaska, Hawaii, Puerto Rico)
for region in self._geo_reference:
# start in the northwest corner of the bounding box
region_most_west_longitude = self._geo_reference[region]["west"]
region_most_north_latitude = self._geo_reference[region]["north"]
# get the starting grid column-row coordinate pair
self._r_0, self._s_0 = self._proj_calc.get_grid_coordinates(
region_most_west_longitude, region_most_north_latitude)
start_longitude, start_latitude = self._proj_calc.get_longitude_latitude(
self._r_0, self._s_0)
# just renaming to keep the crawl semantically consistent
latitude_crawl = start_latitude
# row index relative to s_0
s = 0
# crawl southward
while latitude_crawl > self._geo_reference[region]["south"]:
# column index relative to r_0
r = 0
# reset the starting longitude (western-most of the region on the grid)
longitude_crawl = start_longitude
# crawl eastward
while longitude_crawl < self._geo_reference[region]["east"]:
# generate a cell, and return the new starting longitude and latitude
longitude_crawl, latitude_crawl = self._generate_individual_cell(
r, s)
r += 1
s += 1
def _generate_individual_cell(self, r, s):
# northwest corner
longitude_0, latitude_0 = self._proj_calc.get_longitude_latitude(
self._r_0 + r, self._s_0 + s)
# northeast corner
longitude_1, latitude_1 = self._proj_calc.get_longitude_latitude(
self._r_0 + r + 1, self._s_0 + s)
# southeast corner
longitude_2, latitude_2 = self._proj_calc.get_longitude_latitude(
self._r_0 + r + 1, self._s_0 + s + 1)
# southwest corner
longitude_3, latitude_3 = self._proj_calc.get_longitude_latitude(
self._r_0 + r, self._s_0 + s + 1)
shape_array = [[longitude_0, latitude_0], [longitude_1, latitude_1],
[longitude_2, latitude_2], [longitude_3, latitude_3],
[longitude_0, latitude_0]]
# only add the shape array to the master list if it intersects or is contained within the USA
if self._shape_is_in_US(shape_array):
self._shape_arrays.append(shape_array)
return longitude_3, latitude_0
def _shape_is_in_US(self, shape_array):
# create shapely polygon out of the shape array
square = Polygon(shape_array)
# true if square either intersects the border of _US_boundary, or if it is included within the boundary
return self._US_boundary.intersects(square)
def _save_to_kml(self):
"""
Creates a KML file of this grid viewable in Google Maps and Google Earth.
See https://developers.google.com/kml/documentation/
"""
# call a helper method to convert this array of shape arrays to a KML file
kml_text = convert_arrays_of_geocos_to_kml(self._shape_arrays)
# save to a file in this directory
beautiful_grid_file = open("beautiful_grid.kml", "w")
beautiful_grid_file.write(kml_text)
beautiful_grid_file.close()
class GridGenerator(object):
"""
This class subdivides the geographical extent of the United States into an equal area grid.
Dependencies:
/geography_helper.py
/equal_area_globe_grid.py
/united_states_border.json
Usage:
Let X be the desired area in square miles of each equal area cell
>> GridGenerator(sqrt(X)).run()
Output:
/beautiful_grid.kml
"""
def __init__(self, cell_size_miles):
# input is desired square of each equal area cell, in miles
self._cell_size_miles = cell_size_miles
# ecapsulating longitude/latitude boxes for Mainland, Alaska, Hawaii, Puerto Rico
self._geo_reference = USABoundsReference().Geographies
# we'll store each cell's shape array here
self._shape_arrays = []
# a calculator that converts grid (column, row) to (longitude, latitude) and vice versa.
# formulas given by the National Snow and Ice Data Center (see EqualAreaGlobeGrid doc-string for more info)
self._proj_calc = EqualAreaGlobeGrid(self._cell_size_miles)
def run(self):
"""
Public run method - generates an equal area grid for the United States
"""
self._load_US_boundary()
self._create_equal_area_grid()
self._save_to_kml()
def _load_US_boundary(self):
"""
Loads a GeoJSON multipolygon created separately by merging the polygons provided here:
https://developers.google.com/kml/documentation/us_states.kml
"""
geojson_multipolygon_file = open("united_states_border.json", "r")
geojson_multipolygon = json.loads(geojson_multipolygon_file.read())
geojson_multipolygon_file.close()
# create a shapely multipolygon - this will be used to determine if a generated grid cell lies within the USA
self._US_boundary = MultiPolygon(geojson_multipolygon["coordinates"], context_type = "geojson")
def _create_equal_area_grid(self):
"""
For each region in the USA, calculate all equal area cells that either intersect, or are contained within
that region. Each cell follows the numbering convention:
Northwest Corner: (longitude_0, latitude_0)
Northeast Corner: (longitude_1, latitude_1)
Southeast Corner: (longitude_2, latitude_2)
Southwest Corner: (longitude_3, latitude_3)
"""
# loop over all boxes bounding the separate US geographical regions (Mainland, Alaska, Hawaii, Puerto Rico)
for region in self._geo_reference:
# start in the northwest corner of the bounding box
region_most_west_longitude = self._geo_reference[region]["west"]
region_most_north_latitude = self._geo_reference[region]["north"]
# get the starting grid column-row coordinate pair
self._r_0, self._s_0 = self._proj_calc.get_grid_coordinates(region_most_west_longitude, region_most_north_latitude)
start_longitude, start_latitude = self._proj_calc.get_longitude_latitude(self._r_0, self._s_0)
# just renaming to keep the crawl semantically consistent
latitude_crawl = start_latitude
# row index relative to s_0
s = 0
# crawl southward
while latitude_crawl > self._geo_reference[region]["south"]:
# column index relative to r_0
r = 0
# reset the starting longitude (western-most of the region on the grid)
longitude_crawl = start_longitude
# crawl eastward
while longitude_crawl < self._geo_reference[region]["east"]:
# generate a cell, and return the new starting longitude and latitude
longitude_crawl, latitude_crawl = self._generate_individual_cell(r, s)
r += 1
s += 1
def _generate_individual_cell(self, r, s):
# northwest corner
longitude_0, latitude_0 = self._proj_calc.get_longitude_latitude(self._r_0 + r, self._s_0 + s)
# northeast corner
longitude_1, latitude_1 = self._proj_calc.get_longitude_latitude(self._r_0 + r + 1, self._s_0 + s)
# southeast corner
longitude_2, latitude_2 = self._proj_calc.get_longitude_latitude(self._r_0+ r + 1, self._s_0 + s + 1)
# southwest corner
longitude_3, latitude_3 = self._proj_calc.get_longitude_latitude(self._r_0 + r, self._s_0 + s + 1)
shape_array = [
[longitude_0, latitude_0],
[longitude_1, latitude_1],
[longitude_2, latitude_2],
[longitude_3, latitude_3],
[longitude_0, latitude_0]
]
# only add the shape array to the master list if it intersects or is contained within the USA
if self._shape_is_in_US(shape_array):
self._shape_arrays.append(shape_array)
return longitude_3, latitude_0
def _shape_is_in_US(self, shape_array):
# create shapely polygon out of the shape array
square = Polygon(shape_array)
# true if square either intersects the border of _US_boundary, or if it is included within the boundary
return self._US_boundary.intersects(square)
def _save_to_kml(self):
"""
Creates a KML file of this grid viewable in Google Maps and Google Earth.
See https://developers.google.com/kml/documentation/
"""
# call a helper method to convert this array of shape arrays to a KML file
kml_text = convert_arrays_of_geocos_to_kml(self._shape_arrays)
# save to a file in this directory
beautiful_grid_file = open("beautiful_grid.kml", "w")
beautiful_grid_file.write(kml_text)
beautiful_grid_file.close()
