def testGridDistances(self):
for i in range(100):
gsize = random.uniform(0., 1.) * 2. * 10.**random.uniform(4., 7.)
north_grid, east_grid = num.meshgrid(
num.linspace(-gsize / 2., gsize / 2., 11),
num.linspace(-gsize / 2., gsize / 2., 11))
north_grid = north_grid.flatten()
east_grid = east_grid.flatten()
lon = random.uniform(-180., 180.)
lat = random.uniform(-90., 90.)
lat_grid, lon_grid = orthodrome.ne_to_latlon(
lat, lon, north_grid, east_grid)
lat_grid_alt, lon_grid_alt = \
orthodrome.ne_to_latlon_alternative_method(
lat, lon, north_grid, east_grid)
for la, lo, no, ea in zip(lat_grid, lon_grid, north_grid,
east_grid):
a = orthodrome.Loc(lat=la, lon=lo)
b = orthodrome.Loc(lat=lat, lon=lon)
cd = orthodrome.cosdelta(a, b)
assert cd <= 1.0
d = num.arccos(cd) * earthradius
d2 = math.sqrt(no**2 + ea**2)
assert abs(d - d2) < 1.0e-3 or d2 < 10.
def testGridDistances(self):
for i in range(100):
w,h = 20,15
km = 1000.
gsize = random.uniform(0.,1.)*2.*10.**random.uniform(4.,7.)
north_grid, east_grid = num.meshgrid(num.linspace(-gsize/2.,gsize/2.,11) ,
num.linspace(-gsize/2.,gsize/2.,11) )
north_grid = north_grid.flatten()
east_grid = east_grid.flatten()
lat_delta = gsize/config.earthradius*r2d*2.
lon = random.uniform(-180.,180.)
lat = random.uniform(-90.,90.)
lat_grid, lon_grid = orthodrome.ne_to_latlon(lat, lon, north_grid, east_grid)
lat_grid_alt, lon_grid_alt = orthodrome.ne_to_latlon_alternative_method(lat, lon, north_grid, east_grid)
for la, lo, no, ea in zip(lat_grid, lon_grid, north_grid, east_grid):
a = Loc()
a.lat = la
a.lon = lo
b = Loc()
b.lat = lat
b.lon = lon
cd = orthodrome.cosdelta(a,b)
assert cd <= 1.0
d = num.arccos(cd)*config.earthradius
d2 = math.sqrt(no**2+ea**2)
assert not (abs(d-d2) > 1.0e-3 and d2 > 1.)
def testGridDistances(self):
for i in range(100):
w,h = 20,15
km = 1000.
gsize = random.uniform(0.,1.)*2.*10.**random.uniform(4.,7.)
north_grid, east_grid = num.meshgrid(num.linspace(-gsize/2.,gsize/2.,11) ,
num.linspace(-gsize/2.,gsize/2.,11) )
north_grid = north_grid.flatten()
east_grid = east_grid.flatten()
lat_delta = gsize/config.earthradius*r2d*2.
lon = random.uniform(-180.,180.)
lat = random.uniform(-90.,90.)
lat_grid, lon_grid = orthodrome.ne_to_latlon(lat, lon, north_grid, east_grid)
lat_grid_alt, lon_grid_alt = orthodrome.ne_to_latlon_alternative_method(lat, lon, north_grid, east_grid)
for la, lo, no, ea in zip(lat_grid, lon_grid, north_grid, east_grid):
a = Loc()
a.lat = la
a.lon = lo
b = Loc()
b.lat = lat
b.lon = lon
d = num.arccos(orthodrome.cosdelta(a,b))*config.earthradius
d2 = math.sqrt(no**2+ea**2)
if abs(d-d2) > 1.0e-3 and d2 > 1.:
print 'x',a.lat, a.lon, b.lat,b.lon
print 'y',d, d2, d-d2
def testGridDistances(self):
for i in range(100):
w, h = 20, 15
km = 1000.0
gsize = random.uniform(0.0, 1.0) * 2.0 * 10.0 ** random.uniform(4.0, 7.0)
north_grid, east_grid = num.meshgrid(
num.linspace(-gsize / 2.0, gsize / 2.0, 11), num.linspace(-gsize / 2.0, gsize / 2.0, 11)
)
north_grid = north_grid.flatten()
east_grid = east_grid.flatten()
lat_delta = gsize / config.earthradius * r2d * 2.0
lon = random.uniform(-180.0, 180.0)
lat = random.uniform(-90.0, 90.0)
lat_grid, lon_grid = orthodrome.ne_to_latlon(lat, lon, north_grid, east_grid)
lat_grid_alt, lon_grid_alt = orthodrome.ne_to_latlon_alternative_method(lat, lon, north_grid, east_grid)
for la, lo, no, ea in zip(lat_grid, lon_grid, north_grid, east_grid):
a = Loc()
a.lat = la
a.lon = lo
b = Loc()
b.lat = lat
b.lon = lon
d = num.arccos(orthodrome.cosdelta(a, b)) * config.earthradius
d2 = math.sqrt(no ** 2 + ea ** 2)
if abs(d - d2) > 1.0e-3 and d2 > 1.0:
print "x", a.lat, a.lon, b.lat, b.lon
print "y", d, d2, d - d2
def export_geojson(self, filename):
import geojson
self._log.debug('Exporting GeoJSON Quadtree to %s', filename)
features = []
for lf in self.leaves:
llN, llE, urN, urE = (lf.llN, lf.llE, lf.urN, lf.urE)
if self.frame.isDegree():
llN += self.frame.llLat
llE += self.frame.llLon
urN += self.frame.llLat
urE += self.frame.llLon
coords = [(llE, llN), (urE, llN), (urE, urN), (llE, urN),
(llE, llN)]
if self.frame.isMeter():
coords_deg = []
for c in coords:
c_deg = od.ne_to_latlon_alternative_method(
self.frame.llLon, self.frame.llLat, *c)
coords_deg.append(c_deg)
coords = coords_deg
feature = geojson.Feature(
geometry=geojson.Polygon(coordinates=[coords]),
id=lf.id,
properties={
'mean': lf.mean,
'median': lf.median,
'std': lf.std,
'var': lf.var
})
features.append(feature)
collection = geojson.FeatureCollection(features)
with open(filename, 'w') as f:
geojson.dump(collection, f)
def plot_erroneous_ne_to_latlon():
import gmtpy
import random
import subprocess
import time
while True:
w, h = 20, 15
gsize = random.uniform(0., 1.) * 4. * 10.**random.uniform(4., 7.)
north_grid, east_grid = num.meshgrid(
num.linspace(-gsize / 2., gsize / 2., 11),
num.linspace(-gsize / 2., gsize / 2., 11))
north_grid = north_grid.flatten()
east_grid = east_grid.flatten()
lat_delta = gsize / earthradius * r2d * 2.
lon = random.uniform(-180., 180.)
lat = random.uniform(-90., 90.)
print(gsize / 1000.)
lat_grid, lon_grid = orthodrome.ne_to_latlon(lat, lon, north_grid,
east_grid)
lat_grid_alt, lon_grid_alt = \
orthodrome.ne_to_latlon_alternative_method(
lat, lon, north_grid, east_grid)
maxerrlat = num.max(num.abs(lat_grid - lat_grid_alt))
maxerrlon = num.max(num.abs(lon_grid - lon_grid_alt))
eps = 1.0e-8
if maxerrlon > eps or maxerrlat > eps:
print(lat, lon, maxerrlat, maxerrlon)
gmt = gmtpy.GMT(
config={
'PLOT_DEGREE_FORMAT': 'ddd.xxxF',
'PAPER_MEDIA': 'Custom_%ix%i' %
(w * gmtpy.cm, h * gmtpy.cm),
'GRID_PEN_PRIMARY': 'thinnest/0/50/0'
})
south = max(-85., lat - 0.5 * lat_delta)
north = min(85., lat + 0.5 * lat_delta)
lon_delta = lat_delta / math.cos(lat * d2r)
delta = lat_delta / 360. * earthradius * 2. * math.pi
scale_km = gmtpy.nice_value(delta / 10.) / 1000.
west = lon - 0.5 * lon_delta
east = lon + 0.5 * lon_delta
x, y = (west, east), (south, north)
xax = gmtpy.Ax(mode='min-max', approx_ticks=4.)
yax = gmtpy.Ax(mode='min-max', approx_ticks=4.)
scaler = gmtpy.ScaleGuru(data_tuples=[(x, y)], axes=(xax, yax))
scaler['R'] = '-Rg'
layout = gmt.default_layout()
mw = 2.5 * gmtpy.cm
layout.set_fixed_margins(mw, mw, mw / gmtpy.golden_ratio,
mw / gmtpy.golden_ratio)
widget = layout.get_widget()
# widget['J'] = ('-JT%g/%g' % (lon, lat)) + '/%(width)gp'
widget['J'] = (
'-JE%g/%g/%g' % (lon, lat, min(lat_delta/2., 180.)))\
+ '/%(width)gp'
aspect = gmtpy.aspect_for_projection(*(widget.J() + scaler.R()))
widget.set_aspect(aspect)
gmt.psbasemap(B='5g5',
L=('x%gp/%gp/%g/%g/%gk' %
(widget.width() / 2., widget.height() / 7., lon,
lat, scale_km)),
*(widget.JXY() + scaler.R()))
gmt.psxy(in_columns=(lon_grid, lat_grid),
S='x10p',
W='1p/200/0/0',
*(widget.JXY() + scaler.R()))
gmt.psxy(in_columns=(lon_grid_alt, lat_grid_alt),
S='c10p',
W='1p/0/0/200',
*(widget.JXY() + scaler.R()))
gmt.save('orthodrome.pdf')
subprocess.call(['xpdf', '-remote', 'ortho', '-reload'])
time.sleep(2)
else:
print('ok', gsize, lat, lon)
def plot_erroneous_ne_to_latlon():
import gmtpy
import random
import subprocess
import time
while True:
w, h = 20, 15
gsize = random.uniform(0., 1.)*4.*10.**random.uniform(4., 7.)
north_grid, east_grid = num.meshgrid(
num.linspace(-gsize/2., gsize/2., 11),
num.linspace(-gsize/2., gsize/2., 11))
north_grid = north_grid.flatten()
east_grid = east_grid.flatten()
lat_delta = gsize/earthradius*r2d*2.
lon = random.uniform(-180., 180.)
lat = random.uniform(-90., 90.)
print(gsize/1000.)
lat_grid, lon_grid = orthodrome.ne_to_latlon(
lat, lon, north_grid, east_grid)
lat_grid_alt, lon_grid_alt = \
orthodrome.ne_to_latlon_alternative_method(
lat, lon, north_grid, east_grid)
maxerrlat = num.max(num.abs(lat_grid-lat_grid_alt))
maxerrlon = num.max(num.abs(lon_grid-lon_grid_alt))
eps = 1.0e-8
if maxerrlon > eps or maxerrlat > eps:
print(lat, lon, maxerrlat, maxerrlon)
gmt = gmtpy.GMT(
config={
'PLOT_DEGREE_FORMAT': 'ddd.xxxF',
'PAPER_MEDIA': 'Custom_%ix%i' % (w*gmtpy.cm, h*gmtpy.cm),
'GRID_PEN_PRIMARY': 'thinnest/0/50/0'})
south = max(-85., lat - 0.5*lat_delta)
north = min(85., lat + 0.5*lat_delta)
lon_delta = lat_delta/math.cos(lat*d2r)
delta = lat_delta/360.*earthradius*2.*math.pi
scale_km = gmtpy.nice_value(delta/10.)/1000.
west = lon - 0.5*lon_delta
east = lon + 0.5*lon_delta
x, y = (west, east), (south, north)
xax = gmtpy.Ax(mode='min-max', approx_ticks=4.)
yax = gmtpy.Ax(mode='min-max', approx_ticks=4.)
scaler = gmtpy.ScaleGuru(data_tuples=[(x, y)], axes=(xax, yax))
scaler['R'] = '-Rg'
layout = gmt.default_layout()
mw = 2.5*gmtpy.cm
layout.set_fixed_margins(
mw, mw, mw/gmtpy.golden_ratio, mw/gmtpy.golden_ratio)
widget = layout.get_widget()
# widget['J'] = ('-JT%g/%g' % (lon, lat)) + '/%(width)gp'
widget['J'] = (
'-JE%g/%g/%g' % (lon, lat, min(lat_delta/2., 180.)))\
+ '/%(width)gp'
aspect = gmtpy.aspect_for_projection(*(widget.J() + scaler.R()))
widget.set_aspect(aspect)
gmt.psbasemap(
B='5g5',
L=('x%gp/%gp/%g/%g/%gk' % (
widget.width()/2., widget.height()/7.,
lon, lat, scale_km)),
*(widget.JXY()+scaler.R()))
gmt.psxy(
in_columns=(lon_grid, lat_grid),
S='x10p', W='1p/200/0/0', *(widget.JXY()+scaler.R()))
gmt.psxy(
in_columns=(lon_grid_alt, lat_grid_alt),
S='c10p', W='1p/0/0/200', *(widget.JXY()+scaler.R()))
gmt.save('orthodrome.pdf')
subprocess.call(['xpdf', '-remote', 'ortho', '-reload'])
time.sleep(2)
else:
print('ok', gsize, lat, lon)
