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datastructure.py
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datastructure.py
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import sphereGIS
import random
import numpy
import math
import shapely
import geopandas
import pandas
import pyhdf.SD
def to_ecef(lon, lat):
lon = numpy.array(lon)
lat = numpy.array(lat)
x = numpy.cos(lon/360*math.pi*2) * numpy.cos(lat/360*math.pi*2)
y = numpy.sin(lon/360*math.pi*2) * numpy.cos(lat/360*math.pi*2)
z = numpy.sin(lat/360*math.pi*2)
return numpy.array([x, y, z]).transpose()
class SphereGeoDataFrame(geopandas.GeoDataFrame):
def __init__(self, *args, **kwargs):
super(SphereGeoDataFrame, self).__init__(*args, **kwargs)
self.bootstrap()
def bootstrap(self):
spherical_polygons = []
convex_hulls = []
for index, row in self.iterrows():
spherical_polygon = SphericalPolygon(row.geometry)
spherical_polygons.append(spherical_polygon)
convex_hulls.append(spherical_polygon.convex_nodes.as_polygon())
self['sphere_geom'] = spherical_polygons
self['convex_hull'] = convex_hulls
class SphericalPolygon:
def __init__(self, geom):
self.nodes = Nodes()
self.edges = Edges()
self.convex_nodes = Nodes()
self.convex_edges = Edges()
if geom:
self.from_geom(geom)
def from_geom(self, geom):
geom_type = geom.type
if geom_type == 'Polygon':
self.from_polygon(geom)
elif geom_type == 'MultiPolygon':
self.from_multipolygon(geom)
def from_polygon(self, geom):
self.nodes.from_lonlat(geom.exterior.xy[0], geom.exterior.xy[1])
self.edges.from_lonlat(geom.exterior.xy[0], geom.exterior.xy[1])
def from_multipolygon(self, geom):
for p in list(geom):
lon = p.exterior.xy[0]
lat = p.exterior.xy[1]
new_nodes = Nodes()
new_nodes.from_lonlat(lon, lat)
self.nodes.add(new_nodes)
new_edges = Edges()
new_edges.from_lonlat(lon, lat)
self.edges.add(new_edges)
def get_convex(self):
convex_node_indices = sphereGIS.lonlat2convex(self.nodes.lon, self.nodes.lat)
convex_lon = self.nodes.lon[convex_node_indices]
convex_lat = self.nodes.lat[convex_node_indices]
self.convex_nodes.from_lonlat(convex_lon, convex_lat)
self.convex_edges.from_lonlat(convex_lon, convex_lat)
def get_convex_indices(self):
x, y, z = self.nodes.as_ecef().transpose()
convex_node_indices = sphereGIS.lonlat2convex(self.nodes.lon, self.nodes.lat)
return convex_node_indices
class ConvexEdges:
pass
class Edges(ConvexEdges):
def __init__(self):
self.gcs = numpy.empty([0, 3], dtype=numpy.float)
self.left_gcs = numpy.empty([0, 3], dtype=numpy.float)
self.right_gcs = numpy.empty([0, 3], dtype=numpy.float)
def from_lonlat(self, lon, lat):
from_nodes = to_ecef(lon, lat)
to_nodes = numpy.roll(from_nodes, -1, axis=0) # Moving the first element to last
self.gcs = numpy.cross(from_nodes, to_nodes)
self.left_gcs = numpy.cross(self.gcs, from_nodes)
self.right_gcs = numpy.cross(to_nodes, self.gcs)
def add(self, other):
self.gcs = numpy.concatenate((self.gcs, other.gcs))
self.left_gcs = numpy.concatenate((self.left_gcs, other.left_gcs))
self.right_gcs = numpy.concatenate((self.right_gcs, other.right_gcs))
def __iter__(self):
return EdgeIterator(self)
class EdgeIterator:
def __init__(self, edges):
self._edges = edges
self._index = 0
def __next__(self):
pass
class Nodes:
def __init__(self):
self.lon = numpy.empty([0], dtype=numpy.float)
self.lat = numpy.empty([0], dtype=numpy.float)
def from_lonlat(self, lon, lat):
self.lon = numpy.array(lon)
self.lat = numpy.array(lat)
def drop_repetitive_unsorted(self):
# Dirty trick to get rid of duplicate points
self.lon, self.lat = zip(*(set(zip(self.lon, self.lat))))
def drop_repetitive(self):
# Even dirtier; this keeps the nodes in order.
self.lat, self.lon = zip(*list(dict.fromkeys(zip(self.lat, self.lon))))
def shuffle(self):
a = list(zip(self.lat, self.lon))
random.shuffle(a)
self.lat, self.lon = zip(*a)
def as_ecef(self):
return to_ecef(self.lon, self.lat)
def to_csv(self, name):
x, y, z = self.as_ecef().transpose()
df = pandas.DataFrame({'x':x, 'y': y, 'z': z})
df.to_csv(name, index=None, header=None)
def as_polygon(self):
return shapely.geometry.Polygon(zip(self.lon, self.lat))
def as_polygon_df(self):
geom = self.as_polygon()
gdf = geopandas.GeoDataFrame({'geom': [geom]})
gdf = gdf.set_geometry('geom')
return gdf
def as_point_df(self):
points = []
for lon, lat in zip(self.lon, self.lat):
points.append(shapely.geometry.Point(lon, lat))
gdf = geopandas.GeoDataFrame({'geom': points})
gdf = gdf.set_geometry('geom')
return gdf
def as_line_df(self):
# This will give surprising results for MultiPolygon
edges = shapely.geometry.LineString(zip(self.lon, self.lat))
gdf = geopandas.GeoDataFrame({'geom': [edges]})
gdf = gdf.set_geometry('geom')
return gdf
def add(self, other):
self.lon = numpy.concatenate((self.lon, other.lon))
self.lat = numpy.concatenate((self.lat, other.lat))
class Granule:
def __init__(self):
self.lat = None
self.lon = None
self.ecef = None
def intersects_convex(self, convex_edges):
dots = numpy.einsum('ji,mi->jm', self.ecef, convex_edges.gcs)
n_constraints = len(convex_edges.gcs)
inside_convex = numpy.where(numpy.sum(dots>0, axis=1)==n_constraints)[0]
return inside_convex
def inside_polygon(self, polygon):
inside_convex = self.intersects_convex(polygon.convex_edges)
lon_nodes = polygon.nodes.lon
lat_nodes = polygon.nodes.lat
candidate_lon = self.lon[inside_convex]
candidate_lat = self.lat[inside_convex]
mask = sphereGIS.intersects(candidate_lon, candidate_lat, lon_nodes, lat_nodes)
return inside_convex[numpy.where(mask)[0]]
class Mod09(Granule):
def __init__(self, fname):
hdf = pyhdf.SD.SD(fname)
self.lat = hdf.select('Latitude').get().flatten()
self.lon = hdf.select('Longitude').get().flatten()
self.ecef = to_ecef(self.lon, self.lat)