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# Authors: Denis A. Engemann <denis.engemann@gmail.com>
#
# simplified BSD-3 license
import numpy as np
from .constants import BTI
def bti_identity_trans(dtype='>f8'):
""" Get BTi identity transform
Parameters
----------
dtype : str | dtype object
The data format of the transform
Returns
-------
itrans : ndarray
The 4 x 4 transformation matrix.
"""
return np.array(BTI.T_IDENT, dtype=dtype)
def bti_to_vv_trans(adjust=None, translation=(0.0, 0.02, 0.11), dtype='>f8'):
""" Get the general Magnes3600WH to Neuromag coordinate transform
Parameters
----------
adjust : int | None
Degrees to tilt x-axis for sensor frame misalignment.
If None, no adjustment will be applied.
translation : array-like
The translation to place the origin of coordinate system
to the center of the head.
Returns
-------
m_nm_t : ndarray
4 x 4 rotation, translation, scaling matrix.
"""
flip_t = np.array(BTI.T_ROT_VV, dtype=dtype)
adjust_t = bti_identity_trans(dtype=dtype)
adjust = 0 if adjust is None else adjust
deg = np.deg2rad(np.float64(adjust))
adjust_t[[1, 2], [1, 2]] = np.cos(deg)
adjust_t[[1, 2], [2, 1]] = -np.sin(deg), np.sin(deg)
m_nm_t = np.ones([4, 4], dtype=dtype)
m_nm_t[BTI.T_ROT_IX] = np.dot(flip_t[BTI.T_ROT_IX],
adjust_t[BTI.T_ROT_IX])
m_nm_t[BTI.T_TRANS_IX] = np.matrix(translation, dtype=dtype).T
return m_nm_t
def bti_to_vv_coil_trans(ch_t, bti_t, nm_t, nm_default_scale=True):
""" transforms 4D coil position to fiff / Neuromag
"""
nm_coil_trans = apply_trans(inverse_trans(ch_t, bti_t), nm_t)
if nm_default_scale:
nm_coil_trans[3, :3] = 0.
return nm_coil_trans
def inverse_trans(x, t, rot=BTI.T_ROT_IX, trans=BTI.T_TRANS_IX,
scal=BTI.T_SCA_IX):
""" Undo a transform
"""
x = x.copy()
x[scal] *= t[scal]
x[rot] = np.dot(t[rot].T, x[rot])
x[trans] -= t[trans]
x[trans] = np.dot(t[rot].T, x[trans])
return x
def apply_trans(x, t, rot=BTI.T_ROT_IX, trans=BTI.T_TRANS_IX,
scal=BTI.T_SCA_IX):
""" Apply a transform
"""
x = x.copy()
x[rot] = np.dot(t[rot], x[rot])
x[trans] = np.dot(t[rot], x[trans])
x[trans] += t[trans]
x[scal] *= t[scal]
return x
def merge_trans(t1, t2, dtype='>f8'):
""" Merge two transforms
"""
t = bti_identity_trans(dtype=dtype)
t[BTI.T_ROT_IX] = np.dot(t1[BTI.T_ROT_IX], t2[BTI.T_ROT_IX])
t[BTI.T_TRANS_IX] = np.dot(t1[BTI.T_ROT_IX], t2[BTI.T_TRANS_IX])
t[BTI.T_TRANS_IX] += t1[BTI.T_TRANS_IX]
return t
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