def plotRow(row):
p = main.text2wod(row['raw'][1:-1])
fig = plt.figure()
ax1 = fig.add_subplot(111)
im = ax1.scatter(p.z(),p.t(), c=row['leveltruth'][0], norm=matplotlib.colors.Normalize(vmin=1, vmax=10), cmap='tab10')
fig.colorbar(im, ax=ax1)
plt.xlabel('Depth [m]')
plt.ylabel('Temperature [C]')
plt.title(str(p.uid()))
range = plt.ylim()
plt.ylim(max(-10, range[0]), min(40, range[1]))
range = plt.ylim()
dom = plt.xlim()
plt.xlim(max(-10, dom[0]), min(10000, dom[1]))
dom = plt.xlim()
xmargin = (dom[1] - dom[0])*0.7 + dom[0]
yspace = (range[1] - range[0])*0.05
ymargin = (range[1] - range[0])*0.95 + range[0]
plt.text(xmargin,ymargin - 2*yspace, 'Lat: ' + str(p.latitude()))
plt.text(xmargin,ymargin - 3*yspace, 'Long: ' + str(p.longitude()))
plt.text(xmargin,ymargin - 4*yspace, 'Probe: ' + str(p.probe_type()))
plt.text(xmargin,ymargin - 5*yspace, 'Date: ' + str(p.year()) + '/' + str(p.month()) + '/' + str(p.day()) )
plt.text(xmargin,ymargin - 6*yspace, 'Originator: ' + str(p.originator_flag_type()))
if row['Truth'] and row['roc']:
dir = figdir+'/TP/'
elif row['Truth'] and not row['roc']:
dir = figdir+'/FN/'
elif not row['Truth'] and not row['roc']:
dir = figdir+'/TN/'
elif not row['Truth'] and row['roc']:
dir = figdir+'/FP/'
pylab.savefig(dir + str(p.uid()) + '.png', bbox_inches='tight')
plt.close()
def plotRow(row):
p = main.text2wod(row['raw'][1:-1])
fig = plt.figure()
ax1 = fig.add_subplot(111)
im = ax1.scatter(p.z(),p.t(), c=row['leveltruth'][0], norm=matplotlib.colors.Normalize(vmin=1, vmax=10), cmap='tab10')
fig.colorbar(im, ax=ax1)
plt.xlabel('Depth [m]')
plt.ylabel('Temperature [C]')
plt.title(str(p.uid()))
range = plt.ylim()
plt.ylim(max(-10, range[0]), min(40, range[1]))
range = plt.ylim()
dom = plt.xlim()
plt.xlim(max(-10, dom[0]), min(10000, dom[1]))
dom = plt.xlim()
xmargin = (dom[1] - dom[0])*0.7 + dom[0]
yspace = (range[1] - range[0])*0.05
ymargin = (range[1] - range[0])*0.95 + range[0]
plt.text(xmargin,ymargin - 2*yspace, 'Lat: ' + str(p.latitude()))
plt.text(xmargin,ymargin - 3*yspace, 'Long: ' + str(p.longitude()))
plt.text(xmargin,ymargin - 4*yspace, 'Probe: ' + str(p.probe_type()))
plt.text(xmargin,ymargin - 5*yspace, 'Date: ' + str(p.year()) + '/' + str(p.month()) + '/' + str(p.day()) )
plt.text(xmargin,ymargin - 6*yspace, 'Originator: ' + str(p.originator_flag_type()))
if row['Truth'] and row['roc']:
dir = figdir+'/TP/'
elif row['Truth'] and not row['roc']:
dir = figdir+'/FN/'
elif not row['Truth'] and not row['roc']:
dir = figdir+'/TN/'
elif not row['Truth'] and row['roc']:
dir = figdir+'/FP/'
pylab.savefig(dir + str(p.uid()) + '.png', bbox_inches='tight')
plt.close()
def plotPathology(row, figdir):
'''
look for a transition from all good to all bad, and plot that region
just do plotRow if no such transition is found.
'''
p = main.text2wod(row['raw'][1:-1])
def cat(flag):
if flag == 3 or flag == 4:
return True
else:
return False
category = [cat(x) for x in row['leveltruth'][0]]
total = sum(category)
if sum(category[len(category) - total:]) != total:
plotRow(row, figdir)
return 0
z_transition = p.z()[len(category) - total]
t_transition = p.t()[len(category) - total]
fig = plt.figure()
ax1 = fig.add_subplot(111)
im = ax1.scatter(p.z(),
p.t(),
c=row['leveltruth'][0],
norm=matplotlib.colors.Normalize(vmin=1, vmax=10),
cmap='tab10')
fig.colorbar(im, ax=ax1)
plt.xlabel('Depth [m]')
plt.ylabel('Temperature [C]')
plt.title(str(p.uid()))
range = plt.ylim()
plt.ylim(t_transition - 1, t_transition + 1)
range = plt.ylim()
dom = plt.xlim()
plt.xlim(z_transition - 20, z_transition + 20)
dom = plt.xlim()
xmargin = (dom[1] - dom[0]) * 0.7 + dom[0]
yspace = (range[1] - range[0]) * 0.05
ymargin = (range[1] - range[0]) * 0.95 + range[0]
plt.text(xmargin, ymargin - 2 * yspace, 'Lat: ' + str(p.latitude()))
plt.text(xmargin, ymargin - 3 * yspace, 'Long: ' + str(p.longitude()))
plt.text(xmargin, ymargin - 4 * yspace, 'Probe: ' + str(p.probe_type()))
plt.text(
xmargin, ymargin - 5 * yspace,
'Date: ' + str(p.year()) + '/' + str(p.month()) + '/' + str(p.day()))
plt.text(xmargin, ymargin - 6 * yspace,
'Originator: ' + str(p.originator_flag_type()))
plt.text(xmargin, ymargin - 7 * yspace,
'Instrument: ' + str(probe_detail(p)))
pylab.savefig(figdir + '/' + str(p.uid()) + '.png', bbox_inches='tight')
plt.close()
def plotRow(row, figdir):
'''
generate a plot of the profile in QC table <row>
<row> must include the raw profile text and the per-level truth
fig saved as figdir/uid.png
row should have 'raw' and 'leveltuth' cols
'''
p = main.text2wod(row['raw'][1:-1])
fig = plt.figure()
ax1 = fig.add_subplot(111)
im = ax1.scatter(p.z(),
p.t(),
c=row['leveltruth'][0],
norm=matplotlib.colors.Normalize(vmin=1, vmax=10),
cmap='tab10')
fig.colorbar(im, ax=ax1)
plt.xlabel('Depth [m]')
plt.ylabel('Temperature [C]')
plt.title(str(p.uid()))
range = plt.ylim()
plt.ylim(max(-10, range[0]), min(40, range[1]))
range = plt.ylim()
dom = plt.xlim()
plt.xlim(max(-10, dom[0]), min(10000, dom[1]))
dom = plt.xlim()
xmargin = (dom[1] - dom[0]) * 0.7 + dom[0]
yspace = (range[1] - range[0]) * 0.05
ymargin = (range[1] - range[0]) * 0.95 + range[0]
plt.text(xmargin, ymargin - 2 * yspace, 'Lat: ' + str(p.latitude()))
plt.text(xmargin, ymargin - 3 * yspace, 'Long: ' + str(p.longitude()))
plt.text(xmargin, ymargin - 4 * yspace, 'Probe: ' + str(p.probe_type()))
plt.text(
xmargin, ymargin - 5 * yspace,
'Date: ' + str(p.year()) + '/' + str(p.month()) + '/' + str(p.day()))
plt.text(xmargin, ymargin - 6 * yspace,
'Originator: ' + str(p.originator_flag_type()))
plt.text(xmargin, ymargin - 7 * yspace,
'Instrument: ' + str(probe_detail(p)))
pylab.savefig(figdir + '/' + str(p.uid()) + '.png', bbox_inches='tight')
plt.close()
def aircraft_raw(raw):
trk = main.text2wod(raw)
return isAircraft(trk)
def assess_usability_raw(raw):
p = main.text2wod(raw)
return assess_usability(p)
def aircraft_raw(raw):
trk = main.text2wod(raw)
return isAircraft(trk)
def assess_usability_raw(raw):
p = main.text2wod(raw)
return assess_usability(p)