def show_rvt_peak(r, fg):
"""
:param r:
:param fg:
:return:
"""
rvt_peak_plot = figure(fg)
rvt_peak_plot.clf()
# set(fg, 'KeyPressFcn', @afni_fig_interface) # Appears to be unnecessary to retain from MATLAB code
subplot(211)
plot(r['t'], real(r['x']),'g')
if r['rvt'].any():
subplot(211)
plot(r['t_mid_prd'], z_scale(r['rvt'], min(r['p_trace']), max(r['p_trace'])), 'k')
plot(r['tp_trace'], r['p_trace'], 'ro', r['tp_trace'], r['p_trace'],'r')
plot(r['tn_trace'], r['n_trace'], 'bo', r['tn_trace'], r['n_trace'],'b')
plot(r['t_mid_prd'], r['p_trace_mid_prd'], 'kx')
for i in range(len(r['prd'])):
text(r['t_mid_prd'][i], r['p_trace_mid_prd'][i], '%.2f' % r['prd'][i])
if r['tR']:
if r['p_trace_r'].any():
plot(r['tR'], r['p_trace_r'], 'm')
plot(r['tR'], r['n_trace_r'], 'y')
if r['rvtrs'].any():
plot(r['tR'], z_scale(r['rvtrs'], min(r['p_trace']), max(r['p_trace'])), 'k.')
xlabel('time (sec)')
title(r['v_name']) # , 'Interpreter', 'None')
subplot(413)
vn = real(r['x']) / (abs(r['x']) + spacing(1))
plot(r['t'], vn, 'g')
plot(r['t'], r['phase'] / 2 / pi, 'm')
if 'phase_r' in r:
plot(r['tR'], r['phase_r'] / 2 / pi, 'm-.')
xlabel('time (sec)')
title('Scaled by magnitude of analytical signal') # , 'Interpreter', 'None')
legend(['Scaled signal', 'phase'])
subplot(414)
plot(r['time_series_time'], r['phase_slice'][:, 0], 'ro') # This one isn't any different than the next plot line, check out why values are funky
plot(r['time_series_time'], r['phase_slice'][:, 1], 'bo')
plot(r['time_series_time'], r['phase_slice'][:, 1], 'b-')
plot(r['t'], r['phase'], 'k')
grid('on')
xlabel('time (sec)')
title('Phase sampled at slice acquisition time')
legend(['slice 0', 'slice 1', 'slice 1', 'original phase'])
# plotsign2(fg) # Another AFNI function, not crucial at the moment to making one figure
show()
def rvt_from_peakfinder(r):
if r['demo']:
quiet = 0
print "quiet = %s" % quiet
# Calculate RVT
if len(r['p_trace']) != len(r['n_trace']):
dd = abs(len(r['p_trace']) - len(r['n_trace']))
if dd > 1: # have not seen this yet, trap for it.
print 'Error RVT_from_PeakFinder:\n' \
' Peak trace lengths differ by %d\n' \
' This is unusual, please upload data\n' \
' sample to afni.nimh.nih.gov' % dd
# keyboard
return
else: # just a difference of 1, happens sometimes, seems ok to discard one sample
print 'Notice RVT_from_PeakFinder:\n' \
' Peak trace lengths differ by %d\n'\
' Clipping longer trace.' % dd
dm = min(len(r['p_trace']), len(r['n_trace']))
if len(r['p_trace']) != dm:
r['p_trace'] = r['p_trace'][0:dm]
r['tp_trace'] = r['tp_trace'][0:dm]
else:
r['n_trace'] = r['n_trace'][0:dm]
r['tn_trace'] = r['tn_trace'][0:dm]
r['rv'] = subtract(r['p_trace'], r['n_trace'])
# NEED TO consider which starts first and
# whether to initialize first two values by means
# and also, what to do when we are left with one
# incomplete pair at the end
nptrc = len(r['tp_trace'])
r['rvt'] = r['rv'][0:nptrc - 1] / r['prd']
if r['p_trace_r'].any:
r['rvr'] = subtract(r['p_trace_r'], r['n_trace_r'])
# Debugging lines below
# with open('rvr.csv', 'w') as f:
# for i in r['rvr']:
# f.write("%s\n" % i)
# with open('prdR.csv', 'w') as f:
# for i in r['prdR']:
# f.write("%s\n" % i)
r['rvtr'] = numpy.ndarray(numpy.shape(r['rvr']))
divide(r['rvr'], r['prdR'], r['rvtr'])
# Smooth RVT so that we can resample it at volume_tr later
fnyq = r['phys_fs'] / 2 # nyquist of physio signal
fcut = 2 / r['volume_tr'] # cut below nyquist for volume_tr
w = float(r['frequency_cutoff']) / float(
fnyq) # cut off frequency normalized
b = firwin(numtaps=(r['fir_order'] + 1), cutoff=w, window='hamming')
v = r['rvtr']
around(v, 6, v)
# Debugging lines below
# with open('a.csv', 'w') as f:
# for i in v:
# f.write("%s\n" % i)
mv = mean(v)
# remove the mean
v = (v - mv)
# filter both ways to cancel phase shift
v = lfilter(b, 1, v)
if r['legacy_transform'] == 0:
v = numpy.flipud(
v
) # Turns out these don't do anything in the MATLAB version(Might be a major problem)
v = lfilter(b, 1, v)
if r['legacy_transform'] == 0:
v = numpy.flipud(
v
) # Turns out these don't do anything in the MATLAB version(Might be a major problem)
r['rvtrs'] = v + mv
# create RVT regressors
r['rvtrs_slc'] = zeros((len(r['rvt_shifts']), len(r['time_series_time'])))
for i in range(0, len(r['rvt_shifts'])):
shf = r['rvt_shifts'][i]
nsamp = int(round(shf * r['phys_fs']))
sind = add(range(0, len(r['t'])), nsamp)
print sind
sind[nonzero(sind < 0)] = 0
sind[nonzero(sind > (len(r['t']) - 1))] = len(r['t']) - 1
rvt_shf = interp1d(r['t'],
r['rvtrs'][sind],
r['interpolation_style'],
bounds_error=True)
rvt_shf_y = rvt_shf(r['time_series_time'])
subplot(111)
plot(r['time_series_time'], rvt_shf_y)
r['rvtrs_slc'][:][i] = rvt_shf_y
if r['quiet'] == 0 and r['show_graphs'] == 1:
print '--> Calculated RVT \n--> Created RVT regressors'
subplot(211)
plot(r['t_mid_prd'],
z_scale(r['rvt'], min(r['p_trace']), max(r['p_trace'])), 'k')
if any(r['p_trace_r']):
plot(r['tR'],
z_scale(r['rvtrs'], min(r['p_trace']), max(r['p_trace'])),
'm')
show()
if r['demo']:
# uiwait(msgbox('Press button to resume', 'Pausing', 'modal'))
pass
return r
def phase_base(amp_type, phasee):
"""
:type phasee: object
:param amp_type: if 0, it is a time-based phase estimation
if 1, it is an amplitude-based phase estimation
:param phasee: phasee information
:return:
"""
if amp_type == 0:
# Calculate the phase of the trace, with the peak to be the start of the phase
nptrc = len(phasee['tp_trace'])
phasee['phase'] = -2 * ones(size(phasee['t']))
i = 0
j = 0
while i <= (nptrc - 2):
while phasee['t'][j] < phasee['tp_trace'][i + 1]:
if phasee['t'][j] >= phasee['tp_trace'][i]:
# Note: Using a constant 244 period for each interval
# causes slope discontinuity within a period.
# One should resample period[i] so that it is
# estimated at each time in phasee['t'][j],
# dunno if that makes much of a difference in the end however.
if j == 10975:
pass
phasee['phase'][j] = (phasee['t'][j] - phasee['tp_trace'][i]) / phasee['prd'][i]\
+ phasee['zero_phase_offset']
if phasee['phase'][j] < 0:
phasee['phase'][j] = -phasee['phase'][j]
if phasee['phase'][j] > 1:
phasee['phase'][j] -= 1
j += 1
if i == 124:
pass
i += 1
# Remove the points flagged as unset
temp = nonzero(phasee['phase'] < -1)
phasee['phase'][temp] = 0.0
# Change phase to radians
phasee['phase'] = phasee['phase'] * 2 * pi
else: # phase based on amplitude
# at first scale to the max
mxamp = max(phasee['p_trace'])
phasee['phase_pol'] = []
gR = z_scale(phasee['v'], 0, mxamp) # Scale, per Glover 2000's paper
bins = arange(.01, 1.01, .01) * mxamp
hb_value = my_hist(gR,bins)
#hb_value = histogram(gR, bins)
if phasee['show_graphs'] == 1:
center = (bins[:-1] + bins[1:]) / 2
plt.bar(center, hb_value[:len(hb_value)-1])#, align='center')
plt.show()
#find the polarity of each time point in v
i = 0
itp = 0
inp = 0
tp = phasee['tp_trace'][0]
tn = phasee['tn_trace'][0]
while (i <= len(phasee['v'])) and (phasee['t'][i] < tp) and (phasee['t'][i] < tn):
phasee['phase_pol'].append(0)
i += 1
if tp < tn:
# Expiring phase (peak behind us)
cpol = -1
itp = 1
else:
# Inspiring phase (bottom behind us)
cpol = 1
inp = 1
phasee['phase_pol'] = zeros(size(phasee['v'])) # Not sure why you would replace the
# list that you created 10 lines prior to this
# Add a fake point to tptrace and tntrace to avoid ugly if statements
phasee['tp_trace'] = append(phasee['tp_trace'], phasee['t'][-1])
phasee['tn_trace'] = append(phasee['tn_trace'], phasee['t'][-1])
while i < len(phasee['v']):
phasee['phase_pol'][i] = cpol
if phasee['t'][i] == phasee['tp_trace'][itp]:
cpol = -1
itp = min((itp + 1), (len(phasee['tp_trace']) - 1))
elif phasee['t'][i] == phasee['tn_trace'][inp]:
cpol = 1
inp = min((inp + 1), (len(phasee['tn_trace']) - 1))
# cpol, inp, itp, i, R
i += 1
phasee['tp_trace'] = delete(phasee['tp_trace'], -1)
phasee['tn_trace'] = delete(phasee['tn_trace'], -1)
if phasee['show_graphs'] == 1:
#clf
plt.plot(phasee['t'], gR,'b')
ipositive = nonzero(phasee['phase_pol'] > 0)
ipositive = ipositive[0]
ipositive_x = []
for i in ipositive:
ipositive_x.append(phasee['t'][i])
ipositive_y = zeros(size(ipositive_x))
ipositive_y.fill(0.55 * mxamp)
plt.plot(ipositive_x, ipositive_y, 'r.')
inegative = nonzero(phasee['phase_pol'] < 0)
inegative = inegative[0]
inegative_x = []
for i in inegative:
inegative_x.append(phasee['t'][i])
inegative_y = zeros(size(inegative_x))
inegative_y.fill(0.45 * mxamp)
plt.plot(inegative_x, inegative_y, 'g.')
plt.show()
# Now that we have the polarity, without computing sign(dR/dt)
# as in Glover et al 2000, calculate the phase per eq. 3 of that paper
# First the sum in the numerator
for i, val in enumerate(gR):
gR[i] = (round(val / mxamp * 100) + 1)
gR = clip(gR, 0, 99)
shb = sum(hb_value)
hbsum = []
hbsum.append(float(hb_value[0]) / shb)
for i in range(1, 100):
hbsum.append(hbsum[i - 1] + (float(hb_value[i]) / shb))
for i in range(len(phasee['t'])):
phasee['phase'].append(pi * hbsum[int(gR[i]) - 1] * phasee['phase_pol'][i])
phasee['phase'] = array(phasee['phase'])
# Time series time vector
phasee['time_series_time'] = arange(0, (max(phasee['t']) - 0.5 * phasee['volume_tr']), phasee['volume_tr'])
phasee['phase_slice'] = zeros((len(phasee['time_series_time']), phasee['number_of_slices']))
phasee['phase_slice_reg'] = zeros((len(phasee['time_series_time']), 4, phasee['number_of_slices']))
for i_slice in range(phasee['number_of_slices']):
tslc = phasee['time_series_time'] + phasee['slice_offset'][i_slice]
for i in range(len(phasee['time_series_time'])):
imin = argmin(abs(tslc[i] - phasee['t']))
#mi = abs(tslc[i] - phasee['t']) # probably not needed
phasee['phase_slice'][i, i_slice] = phasee['phase'][imin]
# Make regressors for each slice
phasee['phase_slice_reg'][:, 0, i_slice] = sin(phasee['phase_slice'][:,i_slice])
phasee['phase_slice_reg'][:, 1, i_slice] = cos(phasee['phase_slice'][:,i_slice])
phasee['phase_slice_reg'][:, 2, i_slice] = sin(2 * phasee['phase_slice'][:,i_slice])
phasee['phase_slice_reg'][:, 3, i_slice] = cos(2 * phasee['phase_slice'][:,i_slice])
if phasee['quiet'] == 0 and phasee['show_graphs'] == 1:
print '--> Calculated phase'
plt.subplot(413)
a = divide(divide(phasee['phase'], 2), pi)
plt.plot(phasee['t'], divide(divide(phasee['phase'], 2), pi), 'm')
if 'phase_r' in phasee:
plt.plot(phasee['tR'], divide(divide(phasee['phase_r'], 2), pi), 'm-.')
plt.subplot(414)
plt.plot(phasee['time_series_time'], phasee['phase_slice'][:,1], 'ro',
phasee['time_series_time'], phasee['phase_slice'][:,2], 'bo',
phasee['time_series_time'], phasee['phase_slice'][:,2], 'b-')
plt.plot(phasee['t'], phasee['phase'], 'k')
#grid on
# title it
plt.title(phasee['v_name'])
plt.show()
# Need to implement this yet
#if phasee['Demo']:
#uiwait(msgbox('Press button to resume', 'Pausing', 'modal'))
return phasee
def rvt_from_peakfinder(r):
if r['demo']:
quiet = 0
print "quiet = %s" % quiet
# Calculate RVT
if len(r['p_trace']) != len(r['n_trace']):
dd = abs(len(r['p_trace']) - len(r['n_trace']))
if dd > 1: # have not seen this yet, trap for it.
print 'Error RVT_from_PeakFinder:\nPeak trace lengths differ by %d\nThis is unusual, please upload data' \
'\nsample to afni.nimh.nih.gov' % dd
# keyboard
return
else: # just a difference of 1, happens sometimes, seems ok to discard one sample
print 'Notice RVT_from_PeakFinder:\nPeak trace lengths differ by %d\nClipping longer trace.' % dd
dm = min(len(r['p_trace']), len(r['p_trace']))
if len(r['p_trace']) != dm:
r['p_trace'] = r['p_trace'][0:dm]
r['tp_trace'] = r['tp_trace'][0:dm]
else:
r['n_trace'] = r['n_trace'][0:dm]
r['tn_trace'] = r['tn_trace'][0:dm]
r['rv'] = subtract(r['p_trace'], r['n_trace'])
# NEED TO consider which starts first and
# whether to initialize first two values by means
# and also, what to do when we are left with one
# incomplete pair at the end
nptrc = len(r['tp_trace'])
r['rvt'] = r['rv'][0:nptrc - 1] / r['prd']
if r['p_trace_r'].any:
r['rvr'] = subtract(r['p_trace_r'], r['n_trace_r'])
# Debugging lines below
# with open('rvr.csv', 'w') as f:
# for i in r['rvr']:
# f.write("%s\n" % i)
# with open('prdR.csv', 'w') as f:
# for i in r['prdR']:
# f.write("%s\n" % i)
r['rvtr'] = numpy.ndarray(numpy.shape(r['rvr']))
divide(r['rvr'], r['prdR'], r['rvtr'])
# Smooth RVT so that we can resample it at volume_tr later
fnyq = r['phys_fs'] / 2 # nyquist of physio signal
fcut = 2 / r['volume_tr'] # cut below nyquist for volume_tr
w = float(r['frequency_cutoff']) / float(fnyq) # cut off frequency normalized
b = firwin(numtaps=(r['fir_order'] + 1), cutoff=w, window='hamming')
v = r['rvtr']
around(v, 6, v)
# Debugging lines below
# with open('a.csv', 'w') as f:
# for i in v:
# f.write("%s\n" % i)
mv = mean(v)
# remove the mean
v = (v - mv)
# filter both ways to cancel phase shift
v = lfilter(b, 1, v)
# v = numpy.flipud(v) # Turns out these don't do anything in the MATLAB version(Might be a major problem)
v = lfilter(b, 1, v)
# v = numpy.flipud(v) # Turns out these don't do anything in the MATLAB version(Might be a major problem)
r['rvtrs'] = v + mv
# create RVT regressors
r['rvtrs_slc'] = zeros((len(r['rvt_shifts']), len(r['time_series_time'])))
for i in range(0, len(r['rvt_shifts'])):
shf = r['rvt_shifts'][i]
nsamp = int(round(shf * r['phys_fs']))
sind = add(range(0, len(r['t'])), nsamp)
print sind
sind[nonzero(sind < 0)] = 0
sind[nonzero(sind > (len(r['t']) - 1))] = len(r['t']) - 1
rvt_shf = interp1d(r['t'], r['rvtrs'][sind], r['interpolation_style'], bounds_error=True)
rvt_shf_y = rvt_shf(r['time_series_time'])
subplot(111)
plot(r['time_series_time'], rvt_shf_y)
r['rvtrs_slc'][:][i] = rvt_shf_y
if r['quiet'] == 0 and r['show_graphs'] == 1:
print '--> Calculated RVT \n--> Created RVT regressors'
subplot(211)
plot(r['t_mid_prd'], z_scale(r['rvt'], min(r['p_trace']), max(r['p_trace'])), 'k')
if any(r['p_trace_r']):
plot(r['tR'], z_scale(r['rvtrs'], min(r['p_trace']), max(r['p_trace'])), 'm')
show()
if r['demo']:
# uiwait(msgbox('Press button to resume', 'Pausing', 'modal'))
pass
return r
def phase_base(amp_type, phasee):
"""
:type phasee: object
:param amp_type: if 0, it is a time-based phase estimation
if 1, it is an amplitude-based phase estimation
:param phasee: phasee information
:return:
"""
if amp_type == 0:
# Calculate the phase of the trace, with the peak to be the start of the phase
nptrc = len(phasee['tp_trace'])
phasee['phase'] = -2 * ones(size(phasee['t']))
i = 0
j = 0
while i <= (nptrc - 2):
while phasee['t'][j] < phasee['tp_trace'][i + 1]:
if phasee['t'][j] >= phasee['tp_trace'][i]:
# Note: Using a constant 244 period for each interval
# causes slope discontinuity within a period.
# One should resample period[i] so that it is
# estimated at each time in phasee['t'][j],
# dunno if that makes much of a difference in the end however.
if j == 10975:
pass
phasee['phase'][j] = (phasee['t'][j] - phasee['tp_trace'][i]) / phasee['prd'][i]\
+ phasee['zero_phase_offset']
if phasee['phase'][j] < 0:
phasee['phase'][j] = -phasee['phase'][j]
if phasee['phase'][j] > 1:
phasee['phase'][j] -= 1
j += 1
if i == 124:
pass
i += 1
# Remove the points flagged as unset
temp = nonzero(phasee['phase'] < -1)
phasee['phase'][temp] = 0.0
# Change phase to radians
phasee['phase'] = phasee['phase'] * 2 * pi
else: # phase based on amplitude
# at first scale to the max
mxamp = max(phasee['p_trace'])
phasee['phase_pol'] = []
gR = z_scale(phasee['v'], 0, mxamp) # Scale, per Glover 2000's paper
bins = arange(.01, 1.01, .01) * mxamp
hb_value = my_hist(gR, bins)
#hb_value = histogram(gR, bins)
if phasee['show_graphs'] == 1:
center = (bins[:-1] + bins[1:]) / 2
plt.bar(center, hb_value[:len(hb_value) - 1]) #, align='center')
plt.show()
#find the polarity of each time point in v
i = 0
itp = 0
inp = 0
tp = phasee['tp_trace'][0]
tn = phasee['tn_trace'][0]
while (i <= len(phasee['v'])) and (phasee['t'][i] <
tp) and (phasee['t'][i] < tn):
phasee['phase_pol'].append(0)
i += 1
if tp < tn:
# Expiring phase (peak behind us)
cpol = -1
itp = 1
else:
# Inspiring phase (bottom behind us)
cpol = 1
inp = 1
phasee['phase_pol'] = zeros(size(
phasee['v'])) # Not sure why you would replace the
# list that you created 10 lines prior to this
# Add a fake point to tptrace and tntrace to avoid ugly if statements
phasee['tp_trace'] = append(phasee['tp_trace'], phasee['t'][-1])
phasee['tn_trace'] = append(phasee['tn_trace'], phasee['t'][-1])
while i < len(phasee['v']):
phasee['phase_pol'][i] = cpol
if phasee['t'][i] == phasee['tp_trace'][itp]:
cpol = -1
itp = min((itp + 1), (len(phasee['tp_trace']) - 1))
elif phasee['t'][i] == phasee['tn_trace'][inp]:
cpol = 1
inp = min((inp + 1), (len(phasee['tn_trace']) - 1))
# cpol, inp, itp, i, R
i += 1
phasee['tp_trace'] = delete(phasee['tp_trace'], -1)
phasee['tn_trace'] = delete(phasee['tn_trace'], -1)
if phasee['show_graphs'] == 1:
#clf
plt.plot(phasee['t'], gR, 'b')
ipositive = nonzero(phasee['phase_pol'] > 0)
ipositive = ipositive[0]
ipositive_x = []
for i in ipositive:
ipositive_x.append(phasee['t'][i])
ipositive_y = zeros(size(ipositive_x))
ipositive_y.fill(0.55 * mxamp)
plt.plot(ipositive_x, ipositive_y, 'r.')
inegative = nonzero(phasee['phase_pol'] < 0)
inegative = inegative[0]
inegative_x = []
for i in inegative:
inegative_x.append(phasee['t'][i])
inegative_y = zeros(size(inegative_x))
inegative_y.fill(0.45 * mxamp)
plt.plot(inegative_x, inegative_y, 'g.')
plt.show()
# Now that we have the polarity, without computing sign(dR/dt)
# as in Glover et al 2000, calculate the phase per eq. 3 of that paper
# First the sum in the numerator
for i, val in enumerate(gR):
gR[i] = (round(val / mxamp * 100) + 1)
gR = clip(gR, 0, 99)
shb = sum(hb_value)
hbsum = []
hbsum.append(float(hb_value[0]) / shb)
for i in range(1, 100):
hbsum.append(hbsum[i - 1] + (float(hb_value[i]) / shb))
for i in range(len(phasee['t'])):
phasee['phase'].append(pi * hbsum[int(gR[i]) - 1] *
phasee['phase_pol'][i])
phasee['phase'] = array(phasee['phase'])
# Time series time vector
phasee['time_series_time'] = arange(
0, (max(phasee['t']) - 0.5 * phasee['volume_tr']), phasee['volume_tr'])
phasee['phase_slice'] = zeros(
(len(phasee['time_series_time']), phasee['number_of_slices']))
phasee['phase_slice_reg'] = zeros(
(len(phasee['time_series_time']), 4, phasee['number_of_slices']))
for i_slice in range(phasee['number_of_slices']):
tslc = phasee['time_series_time'] + phasee['slice_offset'][i_slice]
for i in range(len(phasee['time_series_time'])):
imin = argmin(abs(tslc[i] - phasee['t']))
#mi = abs(tslc[i] - phasee['t']) # probably not needed
phasee['phase_slice'][i, i_slice] = phasee['phase'][imin]
# Make regressors for each slice
phasee['phase_slice_reg'][:, 0, i_slice] = sin(
phasee['phase_slice'][:, i_slice])
phasee['phase_slice_reg'][:, 1, i_slice] = cos(
phasee['phase_slice'][:, i_slice])
phasee['phase_slice_reg'][:, 2, i_slice] = sin(
2 * phasee['phase_slice'][:, i_slice])
phasee['phase_slice_reg'][:, 3, i_slice] = cos(
2 * phasee['phase_slice'][:, i_slice])
if phasee['quiet'] == 0 and phasee['show_graphs'] == 1:
print '--> Calculated phase'
plt.subplot(413)
a = divide(divide(phasee['phase'], 2), pi)
plt.plot(phasee['t'], divide(divide(phasee['phase'], 2), pi), 'm')
if 'phase_r' in phasee:
plt.plot(phasee['tR'], divide(divide(phasee['phase_r'], 2), pi),
'm-.')
plt.subplot(414)
plt.plot(phasee['time_series_time'], phasee['phase_slice'][:, 1], 'ro',
phasee['time_series_time'], phasee['phase_slice'][:, 2], 'bo',
phasee['time_series_time'], phasee['phase_slice'][:, 2], 'b-')
plt.plot(phasee['t'], phasee['phase'], 'k')
#grid on
# title it
plt.title(phasee['v_name'])
plt.show()
# Need to implement this yet
#if phasee['Demo']:
#uiwait(msgbox('Press button to resume', 'Pausing', 'modal'))
return phasee
