def __init__(self, spatialreference, extent, nnodes=51, cliplat=0.0, lat_tick_interval=5, mapscale=1000000,
lon_minor_ticks=[12.5], lon_major_ticks=[25, 50, 75],
symmetrical=True, height = 4.0, fontsize=12, padding=1.0, outputname='scalebar.svg',
latlon=False):
nnodes = self._checknnodes(nnodes)
self.fontsize = fontsize
self.height = height
self.nnodes = nnodes
self.outputname = outputname
self.padding = padding
self._dwg = None
self.spatialreference = spatialreference.__str__()
self.mapscale = 1/float(mapscale)
(xmin, ymin, xmax, ymax) = extent
projstr = spatialreference.ExportToProj4()
semimajor = spatialreference.GetSemiMajor()
semiminor = spatialreference.GetSemiMinor()
self.name = emd.get_projection_name(spatialreference)
parallels = emd.get_standard_parallels(spatialreference)
#Create proj4 projection
proj = pyproj.Proj(projstr)
#Setup start and stop nodes
self.coords = np.empty((nnodes, 2))
self.coords[:,0] = xmin
self.coords[:,1] = np.linspace(ymin, ymax, self.nnodes)
if latlon:
#This is intentionally inverting lat/lon to match how GDAL returns image extents
lat = self.coords[:,1]
lon = np.empty(len(lat))
lon[:] = xmin
else:
#Convert to pixel grid to latlon grid
lon, lat = proj(self.coords[:,0], self.coords[:,1], inverse=True)
self.minlat = np.min(lat)
self.minlon = np.min(lon)
self.maxlat = np.max(lat)
self.maxlon = np.max(lon)
self.latlon_bounds = ((self.minlat, self.minlon),
(self.maxlat, self.maxlon))
#Parallels
if parallels[0] >= lat[0] and parallels[0] <= lat[1]:
p = parallels[0]
else:
p = parallels[1]
if 'Transverse_Mercator' in self.name:
clat = emd.get_latitude_of_origin(spatialreference)
clon = emd.get_central_meridian(spatialreference)
if clat > 0:
self.coords[:,1] = lat = np.linspace(np.min(lat), clat, self.nnodes)
else:
self.coords[:,1] = lat = np.linspace(np.max(lat), clat, self.nnodes)
distance = np.empty(len(lat))
k_naught = emd.get_scale_factor(spatialreference)
for i, l in enumerate(lat):
B = math.cos(math.radians(clon)) * math.sin(math.radians(clat) - math.radians(l))
distance[i] = k_naught / math.sqrt(1.0 - B ** 2.0)
distance = distance[::-1]
self.mask = self.coords[:,1] >= cliplat
elif 'Mercator' in self.name:
self.mask = lat >= cliplat
distance = 1.0 / np.cos(np.radians(lat[self.mask]))
distance = distance[::-1]
#elif 'Sinusoidal' in self.name:
elif (('Equirectangular' in self.name) or ('Equidistant_Cylindrical' in self.name) \
or ('Plate_Carree' in self.name) or ('Simple_Cylindrical' in self.name)):
p1 = parallels[0]
clon = emd.get_central_meridian(spatialreference)
if p1 > 0:
self.coords[:,1] = lat = np.linspace(np.min(lat), p1, self.nnodes)
else:
self.coords[:,1] = lat = np.linspace(np.max(lat), p1, self.nnodes)
distance = np.empty(len(lat))
for i, l in enumerate(lat):
distance[i] = math.cos(math.radians(p1))/math.cos(math.radians(l))
distance = distance[::-1]
self.mask = self.coords[:,1] >= cliplat
elif 'Lambert_Conformal' in self.name:
self.mask = lat >= cliplat
parallels.sort()
p1 = math.radians(parallels[0])
p2 = math.radians(parallels[1])
cp1 = math.cos(p1)
cp2 = math.cos(p2)
n = np.log(cp1 / cp2) / np.log( math.tan((math.pi / 4) + (math.radians(parallels[1] / 2))) / math.tan((math.pi / 4) + (math.radians(parallels[0] / 2)) ))
num = cp1 * np.tan(math.pi / 4 + math.radians(parallels[0] / 2)) ** n
den = np.cos(np.radians(lat)) * np.tan(math.pi / 4 + np.radians(lat / 2.0)) ** n
distance = num / den
distance = distance[::-1]
elif 'Stereographic' in self.name:
clat = emd.get_latitude_of_origin(spatialreference)
clon = emd.get_central_meridian(spatialreference)
if clat > 0:
self.coords[:,1] = lat = np.linspace(np.min(lat), clat, self.nnodes)
else:
self.coords[:,1] = lat = np.linspace(np.max(lat), clat, self.nnodes)
distance = np.empty(len(lat))
k_naught = emd.get_scale_factor(spatialreference)
for i, l in enumerate(lat):
distance[i] = (2 * k_naught) / (1.0 + math.sin(math.radians(clat)) * math.sin(math.radians(l)) +\
math.cos(math.radians(clat))*math.cos(math.radians(l))*math.cos(math.radians(180 - clon)))
distance = distance[::-1]
self.mask = self.coords[:,1] >= cliplat
lon_major_ticks = list(map(lambda x: x * 1000, lon_major_ticks)) #km to m
lon_minor_ticks = list(map(lambda x: x * 1000, lon_minor_ticks))
ticks = lon_major_ticks + lon_minor_ticks
ticks.sort()
ticks = ticks[::-1]
south = False
if lat[0] > lat[-1]:
south = True
#Vertical distance line logic
for l in ticks:
line_coords = ((l * 100) * self.mapscale) * distance
if self._dwg == None:
length = np.max(line_coords)
size = (length * 2, self.height)
self.createdrawing(size)
if symmetrical == True:
size = list(size)
size[0] /= 2
size = tuple(size)
self.createvertical(size)
#Check hemisphere
if south == True:
ytext = self.y[0]
else:
ytext = self.y[-1]
#Label the vertical
center = (size[0] + self.padding)* 0.995 # Offset left for font size
dist = self._dwg.text('0', (center * cm, (ytext + self.padding * 1.3) * cm))
self._dwg.add(dist)
nodes = list(zip(line_coords[::-1] + size[0], self.y[::-1]))
for i, start in enumerate(nodes[:-1]):
coords = self._pad_and_convert(start, nodes[i + 1])
self.drawline(coords, group=self.vertical)
if i == 0 and l in lon_major_ticks:
dist = self._dwg.text('{}km'.format(l / 1000), (coords[0][0], (ytext + self.padding * 1.3) * cm))
self._dwg.add(dist)
if symmetrical:
nline_coords = (line_coords * -1)
nodes = list(zip(nline_coords[::-1] + size[0], self.y[::-1]))
for i, start in enumerate(nodes[:-1]):
coords = self._pad_and_convert(start, nodes[i + 1])
self.drawline(coords, group=self.vertical)
if i == 0 and l in lon_major_ticks:
dist = self._dwg.text('{}km'.format(l / 1000), (coords[0][0], (ytext +self.padding * 1.3) * cm ))
self._dwg.add(dist)
#Compute the latrange and labels
latrange = lat[self.mask]
if latrange[0] > latrange[-1]: #Ghetto monotonic check for southern hemisphere...
ticks = np.arange(util.integerround(latrange[-2]), latrange[0] + lat_tick_interval, lat_tick_interval)
else:
ticks = np.arange(util.integerround(latrange[0] + lat_tick_interval) ,latrange[-2], lat_tick_interval)
ticks = labels = np.hstack((round(latrange[0], 1), ticks, round(latrange[-1], 1)))
horizontal_ticks = self._dwg.add(self._dwg.g(id='horizontal_tick', stroke='black'))
#Compute the y coordinate values in scalebar space
horizontals = self.height / (np.max(ticks) - np.min(ticks)) *(ticks - np.min(ticks))
horizontals = np.abs(horizontals - self.height)
for i, h in enumerate(horizontals):
x = [(size[0] + self.padding) * cm, (size[0] * 2 + self.padding) * cm]
y = [(h + self.padding) * cm] * 2
xy = list(zip(x, y))
line = self._dwg.line(start=xy[0], end=xy[1])
horizontal_ticks.add(line)
if i % 2 == 0:
ytext = y[1]
lat = self._dwg.text(u'{}\u00b0'.format(labels[i]), ((size[0] * 2 + 1.0) * cm, ytext))
self.text.add(lat)
if symmetrical:
x = [self.padding * cm, (size[0] + self.padding) * cm]
xy = list(zip(x, y))
line = self._dwg.line(start=xy[0], end=xy[1])
horizontal_ticks.add(line)
if i % 2 == 0:
lat = self._dwg.text(u'{}\u00b0'.format(labels[i]), (0.0 * cm, y[1]))
self.text.add(lat)
self._dwg.save()
def central_meridian(self):
if not getattr(self, '_central_meridian', None):
self._central_meridian = em.get_central_meridian(self.spatialreference)
return self._central_meridian
def __init__(self, spatialreference, extent, nnodes=51, cliplat=0.0, lat_tick_interval=5, mapscale=1000000,
lon_minor_ticks=[12.5], lon_major_ticks=[25, 50, 75],
symmetrical=True, height = 4.0, fontsize=12, padding=1.0, outputname='scalebar.svg',
latlon=False):
nnodes = self._checknnodes(nnodes)
self.fontsize = fontsize
self.height = height
self.nnodes = nnodes
self.outputname = outputname
self.padding = padding
self._dwg = None
self.spatialreference = spatialreference.__str__()
self.mapscale = 1/float(mapscale)
(xmin, ymin, xmax, ymax) = extent
projstr = spatialreference.ExportToProj4()
semimajor = spatialreference.GetSemiMajor()
semiminor = spatialreference.GetSemiMinor()
self.name = emd.get_projection_name(spatialreference)
parallels = emd.get_standard_parallels(spatialreference)
#Create proj4 projection
proj = pyproj.Proj(projstr)
#Setup start and stop nodes
self.coords = np.empty((nnodes, 2))
self.coords[:,0] = xmin
self.coords[:,1] = np.linspace(ymin, ymax, self.nnodes)
if latlon:
#This is intentionally inverting lat/lon to match how GDAL returns image extents
lat = self.coords[:,1]
lon = np.empty(len(lat))
lon[:] = xmin
else:
#Convert to pixel grid to latlon grid
lon, lat = proj(self.coords[:,0], self.coords[:,1], inverse=True)
self.minlat = np.min(lat)
self.minlon = np.min(lon)
self.maxlat = np.max(lat)
self.maxlon = np.max(lon)
self.latlon_bounds = ((self.minlat, self.minlon),
(self.maxlat, self.maxlon))
#Parallels
if parallels[0] >= lat[0] and parallels[0] <= lat[1]:
p = parallels[0]
else:
p = parallels[1]
if 'Transverse_Mercator' in self.name:
clat = emd.get_latitude_of_origin(spatialreference)
clon = emd.get_central_meridian(spatialreference)
if clat > 0:
self.coords[:,1] = lat = np.linspace(np.min(lat), clat, self.nnodes)
else:
self.coords[:,1] = lat = np.linspace(np.max(lat), clat, self.nnodes)
distance = np.empty(len(lat))
k_naught = emd.get_scale_factor(spatialreference)
for i, l in enumerate(lat):
B = math.cos(math.radians(clon)) * math.sin(math.radians(clat) - math.radians(l))
distance[i] = k_naught / math.sqrt(1.0 - B ** 2.0)
distance = distance[::-1]
self.mask = self.coords[:,1] >= cliplat
elif 'Mercator' in self.name:
self.mask = lat >= cliplat
distance = 1.0 / np.cos(np.radians(lat[self.mask]))
distance = distance[::-1]
#elif 'Sinusoidal' in self.name:
elif (('Equirectangular' in self.name) or ('Equidistant_Cylindrical' in self.name) \
or ('Plate_Carree' in self.name) or ('Simple_Cylindrical' in self.name)):
p1 = parallels[0]
clon = emd.get_central_meridian(spatialreference)
if p1 > 0:
self.coords[:,1] = lat = np.linspace(np.min(lat), p1, self.nnodes)
else:
self.coords[:,1] = lat = np.linspace(np.max(lat), p1, self.nnodes)
distance = np.empty(len(lat))
for i, l in enumerate(lat):
distance[i] = math.cos(math.radians(p1))/math.cos(math.radians(l))
distance = distance[::-1]
self.mask = self.coords[:,1] >= cliplat
elif 'Lambert_Conformal' in self.name:
self.mask = lat >= cliplat
parallels.sort()
p1 = math.radians(parallels[0])
p2 = math.radians(parallels[1])
cp1 = math.cos(p1)
cp2 = math.cos(p2)
n = np.log(cp1 / cp2) / np.log( math.tan((math.pi / 4) + (math.radians(parallels[1] / 2))) / math.tan((math.pi / 4) + (math.radians(parallels[0] / 2)) ))
num = cp1 * np.tan(math.pi / 4 + math.radians(parallels[0] / 2)) ** n
den = np.cos(np.radians(lat)) * np.tan(math.pi / 4 + np.radians(lat / 2.0)) ** n
distance = num / den
distance = distance[::-1]
elif 'Stereographic' in self.name:
clat = emd.get_latitude_of_origin(spatialreference)
clon = emd.get_central_meridian(spatialreference)
if clat > 0:
self.coords[:,1] = lat = np.linspace(np.min(lat), clat, self.nnodes)
else:
self.coords[:,1] = lat = np.linspace(np.max(lat), clat, self.nnodes)
distance = np.empty(len(lat))
k_naught = emd.get_scale_factor(spatialreference)
for i, l in enumerate(lat):
distance[i] = (2 * k_naught) / (1.0 + math.sin(math.radians(clat)) * math.sin(math.radians(l)) +\
math.cos(math.radians(clat))*math.cos(math.radians(l))*math.cos(math.radians(180 - clon)))
distance = distance[::-1]
self.mask = self.coords[:,1] >= cliplat
lon_major_ticks = map(lambda x: x * 1000, lon_major_ticks) #km to m
lon_minor_ticks = map(lambda x: x * 1000, lon_minor_ticks)
ticks = lon_major_ticks + lon_minor_ticks
ticks.sort()
ticks = ticks[::-1]
south = False
if lat[0] > lat[-1]:
south = True
#Vertical distance line logic
for l in ticks:
line_coords = ((l * 100) * self.mapscale) * distance
if self._dwg == None:
length = np.max(line_coords)
size = (length * 2, self.height)
self.createdrawing(size)
if symmetrical == True:
size = list(size)
size[0] /= 2
size = tuple(size)
self.createvertical(size)
#Check hemisphere
if south == True:
ytext = self.y[0]
else:
ytext = self.y[-1]
#Label the vertical
center = (size[0] + self.padding)* 0.995 # Offset left for font size
dist = self._dwg.text('0', (center * cm, (ytext + self.padding * 1.3) * cm))
self._dwg.add(dist)
nodes = zip(line_coords[::-1] + size[0], self.y[::-1])
for i, start in enumerate(nodes[:-1]):
coords = self._pad_and_convert(start, nodes[i + 1])
self.drawline(coords, group=self.vertical)
if i == 0 and l in lon_major_ticks:
dist = self._dwg.text('{}km'.format(l / 1000), (coords[0][0], (ytext + self.padding * 1.3) * cm))
self._dwg.add(dist)
if symmetrical:
nline_coords = (line_coords * -1)
nodes = zip(nline_coords[::-1] + size[0], self.y[::-1])
for i, start in enumerate(nodes[:-1]):
coords = self._pad_and_convert(start, nodes[i + 1])
self.drawline(coords, group=self.vertical)
if i == 0 and l in lon_major_ticks:
dist = self._dwg.text('{}km'.format(l / 1000), (coords[0][0], (ytext +self.padding * 1.3) * cm ))
self._dwg.add(dist)
#Compute the latrange and labels
latrange = lat[self.mask]
if latrange[0] > latrange[-1]: #Ghetto monotonic check for southern hemisphere...
ticks = np.arange(util.integerround(latrange[-2]), latrange[0] + lat_tick_interval, lat_tick_interval)
else:
ticks = np.arange(util.integerround(latrange[0] + lat_tick_interval) ,latrange[-2], lat_tick_interval)
ticks = labels = np.hstack((round(latrange[0], 1), ticks, round(latrange[-1], 1)))
horizontal_ticks = self._dwg.add(self._dwg.g(id='horizontal_tick', stroke='black'))
#Compute the y coordinate values in scalebar space
horizontals = self.height / (np.max(ticks) - np.min(ticks)) *(ticks - np.min(ticks))
horizontals = np.abs(horizontals - self.height)
for i, h in enumerate(horizontals):
x = [(size[0] + self.padding) * cm, (size[0] * 2 + self.padding) * cm]
y = [(h + self.padding) * cm] * 2
xy = zip(x, y)
line = self._dwg.line(start=xy[0], end=xy[1])
horizontal_ticks.add(line)
if i % 2 == 0:
ytext = y[1]
lat = self._dwg.text(u'{}\u00b0'.format(labels[i]), ((size[0] * 2 + 1.0) * cm, ytext))
self.text.add(lat)
if symmetrical:
x = [self.padding * cm, (size[0] + self.padding) * cm]
xy = zip(x, y)
line = self._dwg.line(start=xy[0], end=xy[1])
horizontal_ticks.add(line)
if i % 2 == 0:
lat = self._dwg.text(u'{}\u00b0'.format(labels[i]), (0.0 * cm, y[1]))
self.text.add(lat)
self._dwg.save()
def central_meridian(self):
if not getattr(self, '_central_meridian', None):
self._central_meridian = em.get_central_meridian(
self.spatialreference)
return self._central_meridian
