def get_geometry(stream, coordsys='lonlat', return_center=False,
verbose=False):
"""
Method to calculate the array geometry and the center coordinates in km
:param stream: Stream object, the trace.stats dict like class must
contain an :class:`~obspy.core.util.attribdict.AttribDict` with
'latitude', 'longitude' (in degrees) and 'elevation' (in km), or 'x',
'y', 'elevation' (in km) items/attributes. See param ``coordsys``
:param coordsys: valid values: 'lonlat' and 'xy', choose which stream
attributes to use for coordinates
:param return_center: Returns the center coordinates as extra tuple
:return: Returns the geometry of the stations as 2d :class:`numpy.ndarray`
The first dimension are the station indexes with the same order
as the traces in the stream object. The second index are the
values of [lat, lon, elev] in km
last index contains center [lat, lon, elev] in degrees and km if
return_center is true
"""
nstat = len(stream)
center_lat = 0.
center_lon = 0.
center_h = 0.
geometry = np.empty((nstat, 3))
if isinstance(stream, Stream):
for i, tr in enumerate(stream):
if coordsys == 'lonlat':
geometry[i, 0] = tr.stats.coordinates.longitude
geometry[i, 1] = tr.stats.coordinates.latitude
geometry[i, 2] = tr.stats.coordinates.elevation
elif coordsys == 'xy':
geometry[i, 0] = tr.stats.coordinates.x
geometry[i, 1] = tr.stats.coordinates.y
geometry[i, 2] = tr.stats.coordinates.elevation
elif isinstance(stream, np.ndarray):
geometry = stream.copy()
else:
raise TypeError('only Stream or numpy.ndarray allowed')
if verbose:
print(("coordys = " + coordsys))
if coordsys == 'lonlat':
center_lon = geometry[:, 0].mean()
center_lat = geometry[:, 1].mean()
center_h = geometry[:, 2].mean()
for i in np.arange(nstat):
x, y = utlGeoKm(center_lon, center_lat, geometry[i, 0],
geometry[i, 1])
geometry[i, 0] = x
geometry[i, 1] = y
geometry[i, 2] -= center_h
elif coordsys == 'xy':
geometry[:, 0] -= geometry[:, 0].mean()
geometry[:, 1] -= geometry[:, 1].mean()
geometry[:, 2] -= geometry[:, 2].mean()
else:
raise ValueError("Coordsys must be one of 'lonlat', 'xy'")
if return_center:
return np.c_[geometry.T,
np.array((center_lon, center_lat, center_h))].T
else:
return geometry
def get_geometry(stream, coordsys='lonlat', return_center=False,
verbose=False):
"""
Method to calculate the array geometry and the center coordinates in km
:param stream: Stream object, the trace.stats dict like class must
contain an :class:`~obspy.core.util.attribdict.AttribDict` with
'latitude', 'longitude' (in degrees) and 'elevation' (in km), or 'x',
'y', 'elevation' (in km) items/attributes. See param ``coordsys``
:param coordsys: valid values: 'lonlat' and 'xy', choose which stream
attributes to use for coordinates
:param return_center: Returns the center coordinates as extra tuple
:return: Returns the geometry of the stations as 2d :class:`numpy.ndarray`
The first dimension are the station indexes with the same order
as the traces in the stream object. The second index are the
values of [lat, lon, elev] in km
last index contains center [lat, lon, elev] in degrees and km if
return_center is true
"""
nstat = len(stream)
center_lat = 0.
center_lon = 0.
center_h = 0.
geometry = np.empty((nstat, 3))
if isinstance(stream, Stream):
for i, tr in enumerate(stream):
if coordsys == 'lonlat':
geometry[i, 0] = tr.stats.coordinates.longitude
geometry[i, 1] = tr.stats.coordinates.latitude
geometry[i, 2] = tr.stats.coordinates.elevation
elif coordsys == 'xy':
geometry[i, 0] = tr.stats.coordinates.x
geometry[i, 1] = tr.stats.coordinates.y
geometry[i, 2] = tr.stats.coordinates.elevation
elif isinstance(stream, np.ndarray):
geometry = stream.copy()
else:
raise TypeError('only Stream or numpy.ndarray allowed')
if verbose:
print("coordsys = " + coordsys)
if coordsys == 'lonlat':
center_lon = geometry[:, 0].mean()
center_lat = geometry[:, 1].mean()
center_h = geometry[:, 2].mean()
for i in np.arange(nstat):
x, y = utlGeoKm(center_lon, center_lat, geometry[i, 0],
geometry[i, 1])
geometry[i, 0] = x
geometry[i, 1] = y
geometry[i, 2] -= center_h
elif coordsys == 'xy':
geometry[:, 0] -= geometry[:, 0].mean()
geometry[:, 1] -= geometry[:, 1].mean()
geometry[:, 2] -= geometry[:, 2].mean()
else:
raise ValueError("Coordsys must be one of 'lonlat', 'xy'")
if return_center:
return np.c_[geometry.T,
np.array((center_lon, center_lat, center_h))].T
else:
return geometry
def plotarray(stcoord,
inunits='m',
plotunits='km',
sourcecoords=None,
stalabels=None):
"""
stcoord = stream or coords extracted in format from extract_coords
sourcecoords = lat,lon or x,y (should be in same units as stcoord)
inunits 'm' 'km' or 'deg'
"""
coords = []
tempcoords = []
if type(stcoord) is Stream:
if stalabels is None:
stalabels = []
for trace in stcoord:
if inunits == 'deg':
tempcoords.append(
np.array([
trace.stats.coordinates.longitude,
trace.stats.coordinates.latitude,
trace.stats.coordinates.elevation
]))
stalabels.append(trace.stats.station)
else:
tempcoords.append(
np.array([
trace.stats.coordinates.x, trace.stats.coordinates.y,
trace.stats.coordinates.elevation
]))
stalabels.append(trace.stats.station)
else:
tempcoords = stcoord
tempcoords = np.array(tempcoords)
if inunits == 'deg':
lons = np.array([coord[0] for coord in tempcoords])
lats = np.array([coord[1] for coord in tempcoords])
for coord in tempcoords:
x, y = utlGeoKm(lons.min(), lats.min(), coord[0], coord[1])
coords.append(np.array([x, y, coord[2]]))
if plotunits == 'm':
coords = np.array(coords) * 1000.
else:
coords = np.array(coords)
if sourcecoords is not None:
sx, sy = utlGeoKm(lons.min(), lats.min(), sourcecoords[0],
sourcecoords[1])
elif inunits == 'm' and plotunits == 'km':
coords = np.array(tempcoords) / 1000.
if sourcecoords is not None:
sx, sy = sourcecoords / 1000.
elif inunits == 'km' and plotunits == 'm':
coords = np.array(tempcoords) * 1000.
if sourcecoords is not None:
sx, sy = sourcecoords * 1000.
else:
coords = np.array(tempcoords)
if sourcecoords is not None:
sx, sy = sourcecoords
fig = plt.figure()
ax = fig.add_subplot(111)
ax.plot([coord[0] for coord in coords], [coord[1] for coord in coords],
'o')
if stalabels is not None:
for coord, sta in zip(coords, stalabels):
ax.text(coord[0], coord[1], sta, fontsize=8)
if sourcecoords is not None:
ax.plot(sx, sy, '*k', markersize=20)
xcenter = np.array([coord[0] for coord in coords]).mean()
ycenter = np.array([coord[1] for coord in coords]).mean()
az = 180 * math.atan2((xcenter - sx), (ycenter - sy)) / math.pi
baz = az % -360 + 180
if baz < 0.0:
baz += 360
ax.set_title('Backazimuth %0.0f degrees' % baz)
else:
sx = None
sy = None
baz = None
az = None
plt.axis('equal')
ax.set_xlabel('x distance (%s)' % plotunits)
ax.set_ylabel('y distance (%s)' % plotunits)
plt.show()
# ADD AZIMUTH TO CENTER OF ARRAY
return coords, sx, sy, baz, az
def plotarray(stcoord, inunits='m', plotunits='km', sourcecoords=None, stalabels=None):
"""
stcoord = stream or coords extracted in format from extract_coords
sourcecoords = lat,lon or x,y (should be in same units as stcoord)
inunits 'm' 'km' or 'deg'
"""
coords = []
tempcoords = []
if type(stcoord) is Stream:
if stalabels is None:
stalabels = []
for trace in stcoord:
if inunits == 'deg':
tempcoords.append(np.array([trace.stats.coordinates.longitude, trace.stats.coordinates.latitude, trace.stats.coordinates.elevation]))
stalabels.append(trace.stats.station)
else:
tempcoords.append(np.array([trace.stats.coordinates.x, trace.stats.coordinates.y, trace.stats.coordinates.elevation]))
stalabels.append(trace.stats.station)
else:
tempcoords = stcoord
tempcoords = np.array(tempcoords)
if inunits == 'deg':
lons = np.array([coord[0] for coord in tempcoords])
lats = np.array([coord[1] for coord in tempcoords])
for coord in tempcoords:
x, y = utlGeoKm(lons.min(), lats.min(), coord[0], coord[1])
coords.append(np.array([x, y, coord[2]]))
if plotunits == 'm':
coords = np.array(coords)*1000.
else:
coords = np.array(coords)
if sourcecoords is not None:
sx, sy = utlGeoKm(lons.min(), lats.min(), sourcecoords[0], sourcecoords[1])
elif inunits == 'm' and plotunits == 'km':
coords = np.array(tempcoords)/1000.
if sourcecoords is not None:
sx, sy = sourcecoords/1000.
elif inunits == 'km' and plotunits == 'm':
coords = np.array(tempcoords)*1000.
if sourcecoords is not None:
sx, sy = sourcecoords*1000.
else:
coords = np.array(tempcoords)
if sourcecoords is not None:
sx, sy = sourcecoords
fig = plt.figure()
ax = fig.add_subplot(111)
ax.plot([coord[0] for coord in coords], [coord[1] for coord in coords], 'o')
if stalabels is not None:
for coord, sta in zip(coords, stalabels):
ax.text(coord[0], coord[1], sta, fontsize=8)
if sourcecoords is not None:
ax.plot(sx, sy, '*k', markersize=20)
xcenter = np.array([coord[0] for coord in coords]).mean()
ycenter = np.array([coord[1] for coord in coords]).mean()
az = 180 * math.atan2((xcenter-sx), (ycenter-sy)) / math.pi
baz = az % -360 + 180
if baz < 0.0:
baz += 360
ax.set_title('Backazimuth %0.0f degrees' % baz)
else:
sx = None
sy = None
baz = None
az = None
plt.axis('equal')
ax.set_xlabel('x distance (%s)' % plotunits)
ax.set_ylabel('y distance (%s)' % plotunits)
plt.show()
# ADD AZIMUTH TO CENTER OF ARRAY
return coords, sx, sy, baz, az
def utlGeoKm2(orig_lon, orig_lat, lon, lat):
return utlGeoKm(orig_lon, orig_lat, lon, lat)
