def plot(self, axis1, axis2, axis3=None, axis4=None):
# Display results
import framework.mypylab as pl
from framework.mynumpy import abs, db, mean, sin, cos, pi
self.interpolateData()
if VERBOSE:
print 'Start plotting...'
theta,rad = np.meshgrid(self.angles_intrp, self.ranges_intrp)
x = 1000 * rad * sin(theta)
y = 1000 * rad * cos(theta)
## Start Plotting
if (axis1 == 0): # stand alone plotting
pl.figure()
pl.subplot(1,2,1, aspect=1)
pl.pcolormesh(x, y, self.img_das_detected, cmap=pl.cm.gray, vmin=self.minDynRange.value, vmax=self.maxDynRange.value)
pl.gca().invert_yaxis()
else: # Plotting in given axis
axis1.pcolormesh(x, y, self.img_das_detected, cmap=pl.cm.gray, vmin=self.minDynRange.value, vmax=self.maxDynRange.value)
axis1.set_title('Delay-and-sum', fontsize='large')
axis1.set_xlabel('Width [mm]', fontsize='large')
axis1.set_ylabel('Depth [mm]', fontsize='large')
axis1.set_xlim(x.min(), x.max())
axis1.set_ylim(y.max(), y.min())
if (axis2 == 0):
ax = 0
pl.subplot(1,2,2, aspect=1)
pl.pcolormesh(x, y, self.img_cap_detected, cmap=pl.cm.gray, vmin=self.minDynRangeCapon.value, vmax=self.maxDynRangeCapon.value)
pl.gca().invert_yaxis()
pl.show()
else:
ax = axis2.pcolormesh(x, y, self.img_cap_detected, cmap=pl.cm.gray, vmin=self.minDynRangeCapon.value, vmax=self.maxDynRangeCapon.value)
if self.Nb.value > 0:
axis2.set_title('BS-Capon', fontsize='large')
else:
axis2.set_title('ES-Capon', fontsize='large')
axis2.set_xlabel('Width [mm]', fontsize='large')
axis2.set_ylabel('Depth [mm]', fontsize='large')
axis2.set_xlim(x.min(), x.max())
axis2.set_ylim(y.max(), y.min())
if axis3 is not None:
# plot axial profile
#profile_angle = np.arctan( self.profilePos[0] / self.profilePos[1] )
#if profile_angle < self.angles_intrp[-1] and profile_angle > self.angles_intrp[0]:
# range_slice_idx = round(self.angles_intrp.shape[0] * (profile_angle-self.angles_intrp[0]) / (self.angles_intrp[-1]-self.angles_intrp[0]))
# img_das_rslice = img_das_detected[:, range_slice_idx]
# img_cap_rslice = img_cap_detected[:, range_slice_idx]
#
# axis3.plot(y[:,range_slice_idx], img_das_rslice, label='DAS')
# axis3.plot(y[:,range_slice_idx], img_cap_rslice, '-r', label='Capon')
#
# axis3.set_ylim([self.minDynRange.value, self.maxDynRange.value])
#
# axis3.set_title('Radial intensity at %d degrees'%round(profile_angle*180/np.pi))
# axis3.set_xlabel('Depth [mm]')
# axis3.set_ylabel('Radial intensity [dB]')
# axis3.legend(loc=3, markerscale=0.5)
# Plot beampatterns and power spectrums
profile_range = np.sqrt( self.profilePos[0]**2 + self.profilePos[1]**2 ) / 1000.0
profile_angle = np.arctan( self.profilePos[0] / self.profilePos[1] )
if profile_range < self.ranges_intrp[-1] and profile_range > self.ranges_intrp[0] and profile_angle < self.angles_intrp[-1] and profile_angle > self.angles_intrp[0]:
range = round(self.ranges_intrp.shape[0] * (profile_range-self.ranges_intrp[0]) / (self.ranges_intrp[-1]-self.ranges_intrp[0]))
angle = round(self.angles_intrp.shape[0] * (profile_angle-self.angles_intrp[0]) / (self.angles_intrp[-1]-self.angles_intrp[0]))
spacing = 0.5
# plot beamspace data
x_data = self.Xd_i[angle / (2*self.Kx.value), range / (1*self.Ky.value), :]
das_beams = self.calcBeamPatternLinearArray(x_data, self.Nm, spacing, self.angles_intrp, self.angles_intrp[angle], takePowerAndNormalize=True)
axis3.plot(x[range,:], 10*np.log10(das_beams) + self.maxDynRange.value, label='DAS Sample Spectrum')
# make Capon beam pattern
w_capon = self.capon_weights[angle / (2*self.Kx.value), range / (1*self.Ky.value), :]
W_capon = self.calcBeamPatternLinearArray(w_capon, self.L.value, spacing, self.angles_intrp, self.angles_intrp[angle])
W_capon = abs(W_capon*W_capon.conj())
W_capon = W_capon / W_capon[angle]
axis3.plot(x[range,:], 10*np.log10(W_capon) + self.maxDynRange.value - 10 , label='Capon Beampattern')
# make DAS beam pattern for subarrays
W_das = self.calcBeamPatternLinearArray(self.das_w_sub, self.L.value, spacing, self.angles_intrp, self.angles_intrp[angle], takePowerAndNormalize=True)
axis3.plot(x[range,:], 10*np.log10(W_das) + self.maxDynRange.value - 10, label='DAS Beampattern')
# make total Capon beam pattern for the whole system (tx and rx)?
# plot selected direction/angle
axis3.plot([x[range,angle], x[range,angle]], [self.minDynRange.value, self.maxDynRange.value], label='Steering angle')
axis3.set_ylim([self.minDynRange.value, self.maxDynRange.value])
axis3.set_title('Beam pattern at %d degrees and %d mm range'%(round(profile_angle*180/np.pi), round(profile_range*1000)), fontsize='large')
axis3.set_xlabel('Width [mm]', fontsize='large')
axis3.set_ylabel('Intensity/Gain [dB]', fontsize='large')
if self.show_legends.value is 1:
axis3.legend(loc=3, markerscale=0.5)
if axis4 is not None:
profile_range = np.sqrt(self.profilePos[0]**2 + self.profilePos[1]**2) / 1000.0
if profile_range < self.ranges_intrp[-1] and profile_range > self.ranges_intrp[0]:
angle_slice_idx = round(self.ranges_intrp.shape[0] * (profile_range-self.ranges_intrp[0]) / (self.ranges_intrp[-1]-self.ranges_intrp[0]))
self.img_das_aslice = self.img_das_detected[angle_slice_idx, :]
self.img_cap_aslice = self.img_cap_detected[angle_slice_idx, :]
self.x_aslice = x[angle_slice_idx,:]
axis4.plot(self.x_aslice, self.img_das_aslice, label='DAS')
if (self.Nb.value > 0):
axis4.plot(self.x_aslice, self.img_cap_aslice, '-r', label='BS-Capon')
else:
axis4.plot(self.x_aslice, self.img_cap_aslice, '-r', label='ES-Capon')
axis4.set_ylim([self.minDynRange.value, self.maxDynRange.value])
axis4.set_title('Lateral intensity at %d mm range'%round(profile_range*1000), fontsize='large')
axis4.set_xlabel('Width [mm]', fontsize='large')
axis4.set_ylabel('Lateral intensity [dB]', fontsize='large')
if self.show_legends.value is 1:
axis4.legend(loc=3, markerscale=0.5)
if VERBOSE:
print 'done'
return ax
def plot_slices_invivo(legendOn=True):
datatag = 'Vingmed data cardiac 2STB 1'
#datatag = 'motion phantom 16x'
#datatag.append('Vingmed data liver 2STB 1')
#datatag.append('Vingmed data liver 2STB 2')
#datatag.append('Vingmed data cardiac 2STB 1')
#datatag.append('Vingmed data cardiac 4MLA 1')
multiFile = True
capon = CaponProcessor(datatag, multiFile)
capon.sliceRangeStart.mvToMin()
capon.sliceAngleStart.mvToMin()
capon.sliceRangeEnd.mvToMax()
capon.sliceAngleEnd.mvToMax()
# set parameters for capon processor
capon.image_idx.updateValue(0)
capon.Ky.updateValue(2) # incoherent interpolation in range
capon.Kx.updateValue(1) # in azimuth
#capon.L.updateValue()
capon.K.updateValue(2)
capon.minDynRange.updateValue(-20)
capon.maxDynRange.updateValue(20)
capon.minDynRangeCapon.updateValue(-20)
capon.maxDynRangeCapon.updateValue(20)
capon.show_legends.updateValue(1)
capon.apod.updateValue(0) #'Apodization: 0=uniform, 1=hamming'
# position profile
capon.profilePos = [-13.83174473246271, 96.50653026882506, 0.0]
ax = []
for i in range(4):
figure = pl.figure()
ax.append(figure.add_subplot(1, 1, 1))
Nbs = [0, 3]
for Nb in Nbs:
capon.Nb.updateValue(Nb)
if capon.Nb.value > 0:
capon.d.updateValue(d_BS)
else:
capon.d.updateValue(d_ES)
capon.processData()
capon.plot(ax[0], ax[1], ax[2], ax[3])
if Nb == 0:
x = capon.x_aslice
das_profile = capon.img_das_aslice
capon_profile = capon.img_cap_aslice
else:
capon_bs_profile = capon.img_cap_aslice
fig = pl.figure()
ax = fig.add_subplot(1, 1, 1)
ax.plot(x, das_profile, c=(0.25, 0.25, 1.00), ls=':', lw=2.0, label='DAS')
ax.plot(x,
capon_profile,
c=(1.00, 0.25, 0.25),
ls='-.',
lw=2.0,
label='ES-Capon')
ax.plot(x,
capon_bs_profile,
c=(0.0, 0.0, 0.0),
ls='-',
lw=2.0,
label='BS-Capon')
ax.set_ylim([capon.minDynRange.value, capon.maxDynRange.value])
ax.set_title('Lateral intensity at %d mm range' % capon.profilePos[1],
fontsize='large')
ax.set_xlabel('Width [mm]', fontsize='large')
ax.set_ylabel('Lateral intensity [dB]', fontsize='large')
if legendOn:
ax.legend(loc=1, markerscale=0.5)
#fig.savefig('invivo_slice', bbox_inches='tight', pad_inches=0.5)
fig.savefig('invivo_slice.png',
dpi=300,
bbox_inches='tight',
pad_inches=0.5)
def runTradoffAnalysis():
datatag = 'motion phantom 16x 3.4 MHz 20dB30dB'
#filename = 'motion_phantom_16x'
#datatag.append('Vingmed data liver 2STB 1')
#datatag.append('Vingmed data liver 2STB 2')
#datatag.append('Vingmed data cardiac 2STB 1')
#datatag.append('Vingmed data cardiac 4MLA 1')
multiFile = True
capon = CaponProcessor(datatag, multiFile)
# set parameters for capon processor
capon.image_idx.updateValue(0)
capon.sliceRangeStart.updateValue(120) #(100)
capon.sliceAngleStart.updateValue(195) #(350)#200
capon.sliceRangeEnd.updateValue(145) #(120)#0
capon.sliceAngleEnd.updateValue(780) #(600)
capon.Ky.updateValue(4) # incoherent interpolation in range
capon.Kx.updateValue(4) # in azimuth
capon.Nb.updateValue(0)
#capon.L.updateValue()
capon.K.updateValue(2)
capon.minDynRange.updateValue(-20)
capon.maxDynRange.updateValue(35)
capon.minDynRangeCapon.updateValue(-20)
capon.maxDynRangeCapon.updateValue(35)
#capon.apod.updateValue(0) #'Apodization: 0=uniform, 1=hamming'
# position profile
#capon.profilePos = [0.0, 93.0, 0.0]
#Nb_L_range = range(32, 2, -1)
Nb_L_range = range(31, 0, -2)
fps = 25.0
p_depth = 90.0 #93.0 #mm
#p_depth += 0.2148 # add 1/4 of the pulse length
p_depth += 0.1388 #compensate for extra travel distance in elevation
frames = range(7, 30)
res_limit = 6.0
fig = pl.figure()
ax = fig.add_subplot(1, 1, 1)
for b in [True, False]:
resolution = []
if not b:
capon.L.resetValue()
capon.d.updateValue(-1) #1)
else:
capon.d.updateValue(-1) #1)
for v in Nb_L_range:
print 'Value is: ', v, ' b is:', b
if b:
capon.L.updateValue(v)
else:
capon.Nb.updateValue(v)
#capon.d.updateValue((1.0/30.0)*v - 61.0/30.0) # make d go from 0.1 at Nb=31 to 0.01 at Nb=1
resolution.append(
findResolution(capon,
frames,
res_limit,
p_depth,
fps,
highres=True))
if b:
ax.plot(Nb_L_range,
resolution,
c=(0.0, 0.0, 0.0),
ls='-',
marker='o',
lw=2.0,
label='Reducing subarrays')
else:
ax.plot(Nb_L_range,
resolution,
c=(0.2, 0.2, 0.2),
ls='-',
marker='s',
lw=2.0,
label='Reducing beamspace')
das_res = findResolution(capon,
frames,
res_limit,
p_depth,
fps,
highres=False)
ax.plot(Nb_L_range,
das_res * np.ones(len(Nb_L_range)),
c=(0.4, 0.4, 0.4),
ls='--',
lw=2.0,
label='Delay-and-sum')
#ax.set_ylim(ax.get_ylim()[0]-0.1, ax.get_ylim()[1]+0.1)
ax.set_ylim(ax.get_ylim()[0], ax.get_ylim()[1] + 0.1)
ax.set_xlim([Nb_L_range[0], Nb_L_range[-1]])
ax.set_title('Trading resolution for speed', fontsize='x-large')
ax.set_xlabel('$L$ or $N_b$', fontsize='large')
ax.set_ylabel('Resolution [mm]', fontsize='large')
ax.legend(loc=2, markerscale=0.5)
fig.savefig('speed_res_trade.png',
dpi=300,
bbox_inches='tight',
pad_inches=0.5)
def process_and_plot_invivo_image(Nb=0):
datatag = 'Vingmed data cardiac 2STB 1'
multiFile = True
capon = CaponProcessor(datatag, multiFile)
# set parameters for capon processor
#capon.image_idx.updateValue(15)
capon.sliceRangeStart.mvToMin()
capon.sliceAngleStart.mvToMin()
capon.sliceRangeEnd.mvToMax()
capon.sliceAngleEnd.mvToMax()
capon.Ky.updateValue(2) # incoherent interpolation in range
capon.Kx.updateValue(1) # in azimuth
capon.Nb.updateValue(Nb)
if capon.Nb.value > 0:
capon.d.updateValue(d_BS)
else:
capon.d.updateValue(d_ES)
#capon.L.updateValue()
capon.K.updateValue(2)
capon.minDynRange.updateValue(-20)
capon.maxDynRange.updateValue(20)
capon.minDynRangeCapon.updateValue(-20)
capon.maxDynRangeCapon.updateValue(20)
capon.show_legends.updateValue(1)
capon.apod.updateValue(0) #'Apodization: 0=uniform, 1=hamming'
# position profile
capon.profilePos = [-13.83174473246271, 96.50653026882506, 0.0]
capon.processData()
fig = []
ax = []
filename = []
if Nb == 0:
filename = ['das_invivo', 'capon_invivo', 'ax1_invivo', 'ax2_invivo']
else:
filename = [
'das_invivo', 'capon_bs_invivo', 'ax1_bs_invivo', 'ax2_bs_invivo'
]
for i in range(4):
figure = pl.figure()
ax.append(figure.add_subplot(1, 1, 1))
fig.append(figure)
axc = capon.plot(ax[0], ax[1], ax[2], ax[3])
#for i in range(2):
#ax[i].invert_yaxis()
#fig[i].tight_layout()
from datetime import datetime
d = datetime.time(datetime.now())
for i in range(4):
if i is 1 and Nb is not 0:
colorBarFig = pl.figure()
cbar = colorBarFig.colorbar(
axc,
ticks=[capon.minDynRange.value, 0, capon.maxDynRange.value],
orientation='vertical') #, shrink=0.5)
cbar.ax.set_yticklabels([
r'$\leq$%d dB' % capon.minDynRange.value, '0 dB',
r'$\geq$%d dB' % capon.maxDynRange.value
])
colorBarFig.savefig('colorBarInvivo.png',
dpi=300,
bbox_inches='tight',
pad_inches=0.5)
if i < 2:
ax[i].set_aspect('equal') #, 'datalim')
#fig[i].savefig('%s_axes%d_%d%d%d%d'%(filename, i, d.hour, d.minute, d.second, d.microsecond), bbox_inches='tight', pad_inches=0.5)
fig[i].savefig('%s.png' % (filename[i]),
dpi=300,
bbox_inches='tight',
pad_inches=0.5)
def process_and_plot_invivo_image(Nb=0):
datatag = 'Vingmed data cardiac 2STB 1'
multiFile = True
capon = CaponProcessor(datatag, multiFile)
# set parameters for capon processor
#capon.image_idx.updateValue(15)
capon.sliceRangeStart.mvToMin()
capon.sliceAngleStart.mvToMin()
capon.sliceRangeEnd.mvToMax()
capon.sliceAngleEnd.mvToMax()
capon.Ky.updateValue(2) # incoherent interpolation in range
capon.Kx.updateValue(1) # in azimuth
capon.Nb.updateValue(Nb)
if capon.Nb.value > 0:
capon.d.updateValue(d_BS)
else:
capon.d.updateValue(d_ES)
#capon.L.updateValue()
capon.K.updateValue(2)
capon.minDynRange.updateValue(-20)
capon.maxDynRange.updateValue(20)
capon.minDynRangeCapon.updateValue(-20)
capon.maxDynRangeCapon.updateValue(20)
capon.show_legends.updateValue(1)
capon.apod.updateValue(0) #'Apodization: 0=uniform, 1=hamming'
# position profile
capon.profilePos = [-13.83174473246271, 96.50653026882506, 0.0]
capon.processData()
fig = []
ax = []
filename = []
if Nb == 0:
filename = ['das_invivo', 'capon_invivo', 'ax1_invivo', 'ax2_invivo']
else:
filename = ['das_invivo', 'capon_bs_invivo', 'ax1_bs_invivo', 'ax2_bs_invivo']
for i in range(4):
figure = pl.figure()
ax.append(figure.add_subplot(1,1,1))
fig.append(figure)
axc = capon.plot(ax[0],ax[1],ax[2], ax[3])
#for i in range(2):
#ax[i].invert_yaxis()
#fig[i].tight_layout()
from datetime import datetime
d = datetime.time(datetime.now())
for i in range(4):
if i is 1 and Nb is not 0:
colorBarFig = pl.figure()
cbar = colorBarFig.colorbar(axc, ticks=[capon.minDynRange.value, 0, capon.maxDynRange.value], orientation='vertical')#, shrink=0.5)
cbar.ax.set_yticklabels([r'$\leq$%d dB'%capon.minDynRange.value, '0 dB', r'$\geq$%d dB'%capon.maxDynRange.value])
colorBarFig.savefig('colorBarInvivo.png', dpi=300, bbox_inches='tight', pad_inches=0.5)
if i < 2:
ax[i].set_aspect('equal')#, 'datalim')
#fig[i].savefig('%s_axes%d_%d%d%d%d'%(filename, i, d.hour, d.minute, d.second, d.microsecond), bbox_inches='tight', pad_inches=0.5)
fig[i].savefig('%s.png'%(filename[i]), dpi=300, bbox_inches='tight', pad_inches=0.5)
def runTradoffAnalysis():
datatag = 'motion phantom 16x 3.4 MHz 20dB30dB'
#filename = 'motion_phantom_16x'
#datatag.append('Vingmed data liver 2STB 1')
#datatag.append('Vingmed data liver 2STB 2')
#datatag.append('Vingmed data cardiac 2STB 1')
#datatag.append('Vingmed data cardiac 4MLA 1')
multiFile = True
capon = CaponProcessor(datatag, multiFile)
# set parameters for capon processor
capon.image_idx.updateValue(0)
capon.sliceRangeStart.updateValue(120)#(100)
capon.sliceAngleStart.updateValue(195)#(350)#200
capon.sliceRangeEnd.updateValue(145)#(120)#0
capon.sliceAngleEnd.updateValue(780)#(600)
capon.Ky.updateValue(4) # incoherent interpolation in range
capon.Kx.updateValue(4) # in azimuth
capon.Nb.updateValue(0)
#capon.L.updateValue()
capon.K.updateValue(2)
capon.minDynRange.updateValue(-20)
capon.maxDynRange.updateValue(35)
capon.minDynRangeCapon.updateValue(-20)
capon.maxDynRangeCapon.updateValue(35)
#capon.apod.updateValue(0) #'Apodization: 0=uniform, 1=hamming'
# position profile
#capon.profilePos = [0.0, 93.0, 0.0]
#Nb_L_range = range(32, 2, -1)
Nb_L_range = range(31, 0, -2)
fps = 25.0
p_depth = 90.0#93.0 #mm
#p_depth += 0.2148 # add 1/4 of the pulse length
p_depth += 0.1388#compensate for extra travel distance in elevation
frames = range(7, 30)
res_limit = 6.0
fig = pl.figure()
ax = fig.add_subplot(1,1,1)
for b in [True, False]:
resolution = []
if not b:
capon.L.resetValue()
capon.d.updateValue(-1)#1)
else:
capon.d.updateValue(-1)#1)
for v in Nb_L_range:
print 'Value is: ', v, ' b is:', b
if b:
capon.L.updateValue(v)
else:
capon.Nb.updateValue(v)
#capon.d.updateValue((1.0/30.0)*v - 61.0/30.0) # make d go from 0.1 at Nb=31 to 0.01 at Nb=1
resolution.append(findResolution(capon, frames, res_limit, p_depth, fps, highres=True))
if b:
ax.plot(Nb_L_range, resolution, c=(0.0,0.0,0.0), ls='-', marker='o', lw=2.0, label='Reducing subarrays')
else:
ax.plot(Nb_L_range, resolution, c=(0.2,0.2,0.2), ls='-', marker='s', lw=2.0, label='Reducing beamspace')
das_res = findResolution(capon, frames, res_limit, p_depth, fps, highres=False)
ax.plot(Nb_L_range, das_res*np.ones(len(Nb_L_range)), c=(0.4,0.4,0.4), ls='--', lw=2.0, label='Delay-and-sum')
#ax.set_ylim(ax.get_ylim()[0]-0.1, ax.get_ylim()[1]+0.1)
ax.set_ylim(ax.get_ylim()[0], ax.get_ylim()[1]+0.1)
ax.set_xlim([Nb_L_range[0], Nb_L_range[-1]])
ax.set_title('Trading resolution for speed', fontsize='x-large')
ax.set_xlabel('$L$ or $N_b$', fontsize='large')
ax.set_ylabel('Resolution [mm]', fontsize='large')
ax.legend(loc=2, markerscale=0.5)
fig.savefig('speed_res_trade.png', dpi=300, bbox_inches='tight', pad_inches=0.5)
def plot_slices_invivo(legendOn=True):
datatag = 'Vingmed data cardiac 2STB 1'
#datatag = 'motion phantom 16x'
#datatag.append('Vingmed data liver 2STB 1')
#datatag.append('Vingmed data liver 2STB 2')
#datatag.append('Vingmed data cardiac 2STB 1')
#datatag.append('Vingmed data cardiac 4MLA 1')
multiFile = True
capon = CaponProcessor(datatag, multiFile)
capon.sliceRangeStart.mvToMin()
capon.sliceAngleStart.mvToMin()
capon.sliceRangeEnd.mvToMax()
capon.sliceAngleEnd.mvToMax()
# set parameters for capon processor
capon.image_idx.updateValue(0)
capon.Ky.updateValue(2) # incoherent interpolation in range
capon.Kx.updateValue(1) # in azimuth
#capon.L.updateValue()
capon.K.updateValue(2)
capon.minDynRange.updateValue(-20)
capon.maxDynRange.updateValue(20)
capon.minDynRangeCapon.updateValue(-20)
capon.maxDynRangeCapon.updateValue(20)
capon.show_legends.updateValue(1)
capon.apod.updateValue(0) #'Apodization: 0=uniform, 1=hamming'
# position profile
capon.profilePos = [-13.83174473246271, 96.50653026882506, 0.0]
ax = []
for i in range(4):
figure = pl.figure()
ax.append(figure.add_subplot(1,1,1))
Nbs = [0, 3]
for Nb in Nbs:
capon.Nb.updateValue(Nb)
if capon.Nb.value > 0:
capon.d.updateValue(d_BS)
else:
capon.d.updateValue(d_ES)
capon.processData()
capon.plot(ax[0],ax[1],ax[2], ax[3])
if Nb == 0:
x = capon.x_aslice
das_profile = capon.img_das_aslice
capon_profile = capon.img_cap_aslice
else:
capon_bs_profile = capon.img_cap_aslice
fig = pl.figure()
ax = fig.add_subplot(1,1,1)
ax.plot(x, das_profile, c=(0.25,0.25,1.00), ls=':', lw=2.0, label='DAS')
ax.plot(x, capon_profile, c=(1.00,0.25,0.25), ls='-.', lw=2.0, label='ES-Capon')
ax.plot(x, capon_bs_profile, c=(0.0,0.0,0.0), ls='-', lw=2.0, label='BS-Capon')
ax.set_ylim([capon.minDynRange.value, capon.maxDynRange.value])
ax.set_title('Lateral intensity at %d mm range'%capon.profilePos[1], fontsize='large')
ax.set_xlabel('Width [mm]', fontsize='large')
ax.set_ylabel('Lateral intensity [dB]', fontsize='large')
if legendOn:
ax.legend(loc=1, markerscale=0.5)
#fig.savefig('invivo_slice', bbox_inches='tight', pad_inches=0.5)
fig.savefig('invivo_slice.png', dpi=300, bbox_inches='tight', pad_inches=0.5)
def plot(self, axis1, axis2, axis3=None, axis4=None):
# Display results
import framework.mypylab as pl
from framework.mynumpy import abs, db, mean, sin, cos, pi
self.interpolateData()
if VERBOSE:
print 'Start plotting...'
theta, rad = np.meshgrid(self.angles_intrp, self.ranges_intrp)
x = 1000 * rad * sin(theta)
y = 1000 * rad * cos(theta)
## Start Plotting
if (axis1 == 0): # stand alone plotting
pl.figure()
pl.subplot(1, 2, 1, aspect=1)
pl.pcolormesh(x,
y,
self.img_das_detected,
cmap=pl.cm.gray,
vmin=self.minDynRange.value,
vmax=self.maxDynRange.value)
pl.gca().invert_yaxis()
else: # Plotting in given axis
axis1.pcolormesh(x,
y,
self.img_das_detected,
cmap=pl.cm.gray,
vmin=self.minDynRange.value,
vmax=self.maxDynRange.value)
axis1.set_title('Delay-and-sum', fontsize='large')
axis1.set_xlabel('Width [mm]', fontsize='large')
axis1.set_ylabel('Depth [mm]', fontsize='large')
axis1.set_xlim(x.min(), x.max())
axis1.set_ylim(y.max(), y.min())
if (axis2 == 0):
ax = 0
pl.subplot(1, 2, 2, aspect=1)
pl.pcolormesh(x,
y,
self.img_cap_detected,
cmap=pl.cm.gray,
vmin=self.minDynRangeCapon.value,
vmax=self.maxDynRangeCapon.value)
pl.gca().invert_yaxis()
pl.show()
else:
ax = axis2.pcolormesh(x,
y,
self.img_cap_detected,
cmap=pl.cm.gray,
vmin=self.minDynRangeCapon.value,
vmax=self.maxDynRangeCapon.value)
if self.Nb.value > 0:
axis2.set_title('BS-Capon', fontsize='large')
else:
axis2.set_title('ES-Capon', fontsize='large')
axis2.set_xlabel('Width [mm]', fontsize='large')
axis2.set_ylabel('Depth [mm]', fontsize='large')
axis2.set_xlim(x.min(), x.max())
axis2.set_ylim(y.max(), y.min())
if axis3 is not None:
# plot axial profile
#profile_angle = np.arctan( self.profilePos[0] / self.profilePos[1] )
#if profile_angle < self.angles_intrp[-1] and profile_angle > self.angles_intrp[0]:
# range_slice_idx = round(self.angles_intrp.shape[0] * (profile_angle-self.angles_intrp[0]) / (self.angles_intrp[-1]-self.angles_intrp[0]))
# img_das_rslice = img_das_detected[:, range_slice_idx]
# img_cap_rslice = img_cap_detected[:, range_slice_idx]
#
# axis3.plot(y[:,range_slice_idx], img_das_rslice, label='DAS')
# axis3.plot(y[:,range_slice_idx], img_cap_rslice, '-r', label='Capon')
#
# axis3.set_ylim([self.minDynRange.value, self.maxDynRange.value])
#
# axis3.set_title('Radial intensity at %d degrees'%round(profile_angle*180/np.pi))
# axis3.set_xlabel('Depth [mm]')
# axis3.set_ylabel('Radial intensity [dB]')
# axis3.legend(loc=3, markerscale=0.5)
# Plot beampatterns and power spectrums
profile_range = np.sqrt(self.profilePos[0]**2 +
self.profilePos[1]**2) / 1000.0
profile_angle = np.arctan(self.profilePos[0] / self.profilePos[1])
if profile_range < self.ranges_intrp[
-1] and profile_range > self.ranges_intrp[
0] and profile_angle < self.angles_intrp[
-1] and profile_angle > self.angles_intrp[0]:
range = round(self.ranges_intrp.shape[0] *
(profile_range - self.ranges_intrp[0]) /
(self.ranges_intrp[-1] - self.ranges_intrp[0]))
angle = round(self.angles_intrp.shape[0] *
(profile_angle - self.angles_intrp[0]) /
(self.angles_intrp[-1] - self.angles_intrp[0]))
spacing = 0.5
# plot beamspace data
x_data = self.Xd_i[angle / (2 * self.Kx.value),
range / (1 * self.Ky.value), :]
das_beams = self.calcBeamPatternLinearArray(
x_data,
self.Nm,
spacing,
self.angles_intrp,
self.angles_intrp[angle],
takePowerAndNormalize=True)
axis3.plot(x[range, :],
10 * np.log10(das_beams) + self.maxDynRange.value,
label='DAS Sample Spectrum')
# make Capon beam pattern
w_capon = self.capon_weights[angle / (2 * self.Kx.value),
range / (1 * self.Ky.value), :]
W_capon = self.calcBeamPatternLinearArray(
w_capon, self.L.value, spacing, self.angles_intrp,
self.angles_intrp[angle])
W_capon = abs(W_capon * W_capon.conj())
W_capon = W_capon / W_capon[angle]
axis3.plot(x[range, :],
10 * np.log10(W_capon) + self.maxDynRange.value -
10,
label='Capon Beampattern')
# make DAS beam pattern for subarrays
W_das = self.calcBeamPatternLinearArray(
self.das_w_sub,
self.L.value,
spacing,
self.angles_intrp,
self.angles_intrp[angle],
takePowerAndNormalize=True)
axis3.plot(x[range, :],
10 * np.log10(W_das) + self.maxDynRange.value - 10,
label='DAS Beampattern')
# make total Capon beam pattern for the whole system (tx and rx)?
# plot selected direction/angle
axis3.plot([x[range, angle], x[range, angle]],
[self.minDynRange.value, self.maxDynRange.value],
label='Steering angle')
axis3.set_ylim([self.minDynRange.value, self.maxDynRange.value])
axis3.set_title(
'Beam pattern at %d degrees and %d mm range' % (round(
profile_angle * 180 / np.pi), round(profile_range * 1000)),
fontsize='large')
axis3.set_xlabel('Width [mm]', fontsize='large')
axis3.set_ylabel('Intensity/Gain [dB]', fontsize='large')
if self.show_legends.value is 1:
axis3.legend(loc=3, markerscale=0.5)
if axis4 is not None:
profile_range = np.sqrt(self.profilePos[0]**2 +
self.profilePos[1]**2) / 1000.0
if profile_range < self.ranges_intrp[
-1] and profile_range > self.ranges_intrp[0]:
angle_slice_idx = round(
self.ranges_intrp.shape[0] *
(profile_range - self.ranges_intrp[0]) /
(self.ranges_intrp[-1] - self.ranges_intrp[0]))
self.img_das_aslice = self.img_das_detected[angle_slice_idx, :]
self.img_cap_aslice = self.img_cap_detected[angle_slice_idx, :]
self.x_aslice = x[angle_slice_idx, :]
axis4.plot(self.x_aslice, self.img_das_aslice, label='DAS')
if (self.Nb.value > 0):
axis4.plot(self.x_aslice,
self.img_cap_aslice,
'-r',
label='BS-Capon')
else:
axis4.plot(self.x_aslice,
self.img_cap_aslice,
'-r',
label='ES-Capon')
axis4.set_ylim(
[self.minDynRange.value, self.maxDynRange.value])
axis4.set_title('Lateral intensity at %d mm range' %
round(profile_range * 1000),
fontsize='large')
axis4.set_xlabel('Width [mm]', fontsize='large')
axis4.set_ylabel('Lateral intensity [dB]', fontsize='large')
if self.show_legends.value is 1:
axis4.legend(loc=3, markerscale=0.5)
if VERBOSE:
print 'done'
return ax
