def rotate_data(NSEMdata, rot_angle):
'''
Function that rotates clockwise by rotation angle
(- negative for a counter-clockwise rotation)
**Required**
:param SimPEG.EM.NSEM.Data NSEMdata: NSEM data object to process
:param float rot_angle: Rotation angel in degrees,
positive for clockwise rotation
'''
recData = NSEMdata.toRecArray('Complex')
impData = rec_to_ndarr(recData[['zxx', 'zxy', 'zyx', 'zyy']].copy(),
complex)
# Make the rotation matrix
# c,s,zxx,zxy,zyx,zyy = sympy.symbols('c,s,zxx,zxy,zyx,zyy')
# rotM = sympy.Matrix([[c,-s],[s, c]])
# zM = sympy.Matrix([[zxx,zxy],[zyx,zyy]])
# rotM*zM*rotM.T
# [c*(c*zxx - s*zyx) - s*(c*zxy - s*zyy), c*(c*zxy - s*zyy) + s*(c*zxx - s*zyx)],
# [c*(c*zyx + s*zxx) - s*(c*zyy + s*zxy), c*(c*zyy + s*zxy) + s*(c*zyx + s*zxx)]])
s = np.sin(-np.deg2rad(rot_angle))
c = np.cos(-np.deg2rad(rot_angle))
rotMat = np.array([[c, -s], [s, c]])
rotData = (rotMat.dot(impData.reshape(-1, 2, 2).dot(rotMat.T))).transpose(
1, 0, 2).reshape(-1, 4)
outRec = recData.copy()
for nr, comp in enumerate(['zxx', 'zxy', 'zyx', 'zyy']):
outRec[comp] = rotData[:, nr]
return Data.fromRecArray(outRec)
def resampleNSEMdataAtFreq(NSEMdata, freqs):
"""
Function to resample NSEMdata at set of frequencies
"""
# Make a rec array
NSEMrec = NSEMdata.toRecArray().data
# Find unique locations
uniLoc = np.unique(NSEMrec[['x','y','z']])
uniFreq = NSEMdata.survey.freqs
# Get the comps
dNames = NSEMrec.dtype
# Loop over all the locations and interpolate
for loc in uniLoc:
# Find the index of the station
ind = np.sqrt(np.sum((rec_to_ndarr(NSEMrec[['x','y','z']]) - rec_to_ndarr(loc))**2,axis=1)) < 1. # Find dist of 1 m accuracy
# Make a temporary recArray and interpolate all the components
tArrRec = np.concatenate((simpeg.mkvc(freqs,2),np.ones((len(freqs),1))*rec_to_ndarr(loc),np.nan*np.ones((len(freqs),12))),axis=1).view(dNames)
for comp in ['zxxr','zxxi','zxyr','zxyi','zyxr','zyxi','zyyr','zyyi','tzxr','tzxi','tzyr','tzyi']:
int1d = sciint.interp1d(NSEMrec[ind]['freq'],NSEMrec[ind][comp],bounds_error=False)
tArrRec[comp] = simpeg.mkvc(int1d(freqs),2)
# Join together
try:
outRecArr = recFunc.stack_arrays((outRecArr,tArrRec))
except NameError:
outRecArr = tArrRec
# Make the NSEMdata and return
return Data.fromRecArray(outRecArr)
def resampleNSEMdataAtFreq(NSEMdata, freqs):
"""
Function to resample NSEMdata at set of frequencies
"""
# Make a rec array
NSEMrec = NSEMdata.toRecArray().data
# Find unique locations
uniLoc = np.unique(NSEMrec[['x', 'y', 'z']])
uniFreq = NSEMdata.survey.freqs
# Get the comps
dNames = NSEMrec.dtype
# Loop over all the locations and interpolate
for loc in uniLoc:
# Find the index of the station
ind = np.sqrt(
np.sum((rec_to_ndarr(NSEMrec[['x', 'y', 'z']]) - rec_to_ndarr(loc))
**2,
axis=1)) < 1. # Find dist of 1 m accuracy
# Make a temporary recArray and interpolate all the components
tArrRec = np.concatenate(
(simpeg.mkvc(freqs, 2), np.ones(
(len(freqs), 1)) * rec_to_ndarr(loc), np.nan * np.ones(
(len(freqs), 12))),
axis=1).view(dNames)
for comp in [
'zxxr', 'zxxi', 'zxyr', 'zxyi', 'zyxr', 'zyxi', 'zyyr', 'zyyi',
'tzxr', 'tzxi', 'tzyr', 'tzyi'
]:
int1d = sciint.interp1d(NSEMrec[ind]['freq'],
NSEMrec[ind][comp],
bounds_error=False)
tArrRec[comp] = simpeg.mkvc(int1d(freqs), 2)
# Join together
try:
outRecArr = recFunc.stack_arrays((outRecArr, tArrRec))
except NameError:
outRecArr = tArrRec
# Make the NSEMdata and return
return Data.fromRecArray(outRecArr)
def rotateData(NSEMdata, rotAngle):
'''
Function that rotates clockwist by rotAngle (- negative for a counter-clockwise rotation)
'''
recData = NSEMdata.toRecArray('Complex')
impData = rec_to_ndarr(recData[['zxx', 'zxy', 'zyx', 'zyy']], complex)
# Make the rotation matrix
# c,s,zxx,zxy,zyx,zyy = sympy.symbols('c,s,zxx,zxy,zyx,zyy')
# rotM = sympy.Matrix([[c,-s],[s, c]])
# zM = sympy.Matrix([[zxx,zxy],[zyx,zyy]])
# rotM*zM*rotM.T
# [c*(c*zxx - s*zyx) - s*(c*zxy - s*zyy), c*(c*zxy - s*zyy) + s*(c*zxx - s*zyx)],
# [c*(c*zyx + s*zxx) - s*(c*zyy + s*zxy), c*(c*zyy + s*zxy) + s*(c*zyx + s*zxx)]])
s = np.sin(-np.deg2rad(rotAngle))
c = np.cos(-np.deg2rad(rotAngle))
rotMat = np.array([[c, -s], [s, c]])
rotData = (rotMat.dot(impData.reshape(-1, 2, 2).dot(rotMat.T))).transpose(
1, 0, 2).reshape(-1, 4)
outRec = recData.copy()
for nr, comp in enumerate(['zxx', 'zxy', 'zyx', 'zyy']):
outRec[comp] = rotData[:, nr]
return Data.fromRecArray(outRec)
def rotateData(NSEMdata, rotAngle):
'''
Function that rotates clockwist by rotAngle (- negative for a counter-clockwise rotation)
'''
recData = NSEMdata.toRecArray('Complex')
impData = rec_to_ndarr(recData[['zxx','zxy','zyx','zyy']],complex)
# Make the rotation matrix
# c,s,zxx,zxy,zyx,zyy = sympy.symbols('c,s,zxx,zxy,zyx,zyy')
# rotM = sympy.Matrix([[c,-s],[s, c]])
# zM = sympy.Matrix([[zxx,zxy],[zyx,zyy]])
# rotM*zM*rotM.T
# [c*(c*zxx - s*zyx) - s*(c*zxy - s*zyy), c*(c*zxy - s*zyy) + s*(c*zxx - s*zyx)],
# [c*(c*zyx + s*zxx) - s*(c*zyy + s*zxy), c*(c*zyy + s*zxy) + s*(c*zyx + s*zxx)]])
s = np.sin(-np.deg2rad(rotAngle))
c = np.cos(-np.deg2rad(rotAngle))
rotMat = np.array([[c,-s],[s,c]])
rotData = (rotMat.dot(impData.reshape(-1,2,2).dot(rotMat.T))).transpose(1,0,2).reshape(-1,4)
outRec = recData.copy()
for nr,comp in enumerate(['zxx','zxy','zyx','zyy']):
outRec[comp] = rotData[:,nr]
return Data.fromRecArray(outRec)
