# ==== 3-points: Probe as pointer in static & dynamic acquisition
# Load file containing roto-translation from US image to global
matrix_pap = np.load('matrices_julie_PaP1.npz')
# Load file containing roto-translation from US image to global
matrix_dynamic = np.load('matrices_julie_dyn3.npz')
# Get roto-translation from US image to global reference frame
T_pap = matrix_pap['gTim']
# Get roto-translation from US image to global reference frame
T_dyn = matrix_dynamic['gTim']
# Get single points features from file
fea_pap = readFeaturesFile('feature_julie_PaP1.fea') # it must contain one point feature per US image
# Get single points features from file
fea_dyn = readFeaturesFile('feature_julie_dyn3.fea') # it must contain one point feature per US image
# Get metadata from dynamic trial files
timing_data = np.load('us_time_vector_julie_dyn3.npz')
usTimeVector = timing_data['usTimeVector'][0]
fcOpto = 120.
# Indicate u, v (50mm as depth)
u = 30./278
v = 50./463
# Calculate GLOBAL coordinates of muscle insertion - fem - STATIC
idxP1 = [135,145,155,165,175]
# ==== 3-points: Probe as pointer in static & dynamic acquisition
# Load file containing roto-translation from US image to global
matrix_pap = np.load('matrices_test4feb_PaP1.npz')
# Load file containing roto-translation from US image to global
matrix_dynamic = np.load('matrices_test4feb_dyn1.npz')
# Get roto-translation from US image to global reference frame
T_pap = matrix_pap['gTim']
# Get roto-translation from US image to global reference frame
T_dyn = matrix_dynamic['gTim']
# Get single points features from file
fea_pap = readFeaturesFile('PaP1.fea') # it must contain one point feature per US image
# Get single points features from file
fea_dyn = readFeaturesFile('dyn1.fea') # it must contain one point feature per US image
# Indicate u, v (50mm as depth)
u = 30./278
v = 50./463
# Calculate GLOBAL coordinates of muscle insertion - fem - STATIC
idxP1 = [214,216,218,220,222]
P1 = singlePointFeaturesTo3DPointsMatrix(fea_pap, u, v, idx=idxP1)
P1g = dot3(T_pap[idxP1,:,:], P1[...,None]).squeeze() # Np x 4
P1 = P1g.mean(axis=0)
# Calculate GLOBAL coordinates of tendon insertion - calc - STATIC
from Py3DFreeHandUS.segment import readFeaturesFile, singlePointFeaturesTo3DPointsMatrix
from Py3DFreeHandUS.kine import dot3
import numpy as np
if __name__ == "__main__":
# ---- METHOD 1: 6-points probing
# Load file containing roto-translation from US image to global
matrix = np.load('matrices_testwire_3points_15.npz')
# Get roto-translation from US image to global reference frame
T = matrix['gTim']
# Get single points features from file
fea = readFeaturesFile('testwire15.fea') # it must contain one point feature per US image
# Indicate u, v
u = 30./278
v = 50./463
# Calculate global coordinates of P1
idxP1 = range(79,84)
P1 = singlePointFeaturesTo3DPointsMatrix(fea, u, v, idx=idxP1)
print P1
P1g = dot3(T[idxP1,:,:], P1[...,None]).squeeze()[:,0:3] # Np x 3
P1 = P1g.mean(axis=0)
print P1g.std(axis=0)
# Calculate global coordinates of P2
idxP2 = range(142,147)
from Py3DFreeHandUS.kine import dot3
from Py3DFreeHandUS.muscles_analysis import MTJlengths
import numpy as np
if __name__ == "__main__":
# ---- METHOD 1: 3-points probing
# Load file containing roto-translation from US image to global
matrix = np.load('matrices_plantar_3points.npz')
# Get roto-translation from US image to global reference frame
T = matrix['gTim']
# Get single points features from file
fea = readFeaturesFile('plantar_position1.fea') # it must contain one point feature per US image
# Indicate u, v
u = 30./278
v = 50./463
# Calculate global coordinates of muscle insertion
idxP1 = [3,5,8,12,16]
P1 = singlePointFeaturesTo3DPointsMatrix(fea, u, v, idx=idxP1)
P1g = dot3(T[idxP1,:,:], P1[...,None]).squeeze()[:,0:3] # Np x 3
P1 = P1g.mean(axis=0)
# Calculate global coordinates of tendon insertion
idxP2 = [510,512,515,518,521]
P2 = singlePointFeaturesTo3DPointsMatrix(fea, u, v, idx=idxP2)
P2g = dot3(T[idxP2,:,:], P2[...,None]).squeeze()[:,0:3] # Np x 3
