def PlotTracesAsGrids(df, index, viewRange, saveDir=None, colorfy=False, dpi=300,
fig_size=None, adjustFigH=True, adjustFigW=True, nullRange=None,
annotation='Simple', setFont='default',gridSpec='Vertical',
scalebarAt='all', fontSize=10, linewidth=1.0, monoStim=False,
stimReflectCurrent=True):
"Export Multiple episodes arranged in a grid; default vertically"""
if not colorfy:
colorfy = ['k']
nchannels = len(viewRange.keys())
nepisodes = len(index)
if isinstance(gridSpec, str):
nrows, ncols = {
'ver': (nchannels*nepisodes, 1),
'hor': (1, nchannels*nepisodes),
'cha': (nchannels, nepisodes),
'epi': (nepisodes, nchannels)
}.get(gridSpec[:3].lower(), (None, None))
if nrows is None:
raise(ValueError('Unrecognized gridSpec: {}'.format(gridSpec)))
else:
raise(TypeError('Unrecognized type of argument: "gridSpec"'))
fig, _ = plt.subplots(nrows=nrows, ncols=ncols, sharex=True)
ax = fig.get_axes()
# text annotation area
textbox = []
viewRange_dict = {}
row, col = 0,0 # keep track of axis used
first_last_mat = [[],[]]
for n, i in enumerate(index):
zData = df['Data'][i]
ts = zData.Protocol.msPerPoint
channels = []
for c, m in enumerate(viewRange.keys()):
# Draw plots
X = zData.Time
Y = getattr(zData, m[0])[m[1]]
# null the trace
if nullRange is not None:
if isinstance(nullRange, list):
Y = Y - np.mean(spk_window(Y, ts, nullRange))
else: # a single number
Y = Y - Y[time2ind(nullRange, ts)]
# window the plot
X = spk_window(X, ts, viewRange[m][0])
Y = spk_window(Y, ts, viewRange[m][0])
# Stim channel reflects current channel
if stimReflectCurrent and m[0]=='Stimulus':
CurBase = spk_window(zData.Current[m[1]], ts, viewRange[m][0]) # use view range of stimulus on current
CurBase = np.mean(spk_window(CurBase, ts, [0,50]))
Y = Y + CurBase
# do the plot
ind = np.ravel_multi_index((row,col), (nrows, ncols), order='C')
if n == 0:
first_last_mat[0].append(ind)
elif n == len(index)-1:
first_last_mat[-1].append(ind)
if m[0] in ['Voltage', 'Current'] or not monoStim:
ax[ind].plot(X, Y, color=colorfy[n%len(colorfy)], lw=linewidth)
else:
ax[ind].plot(X, Y, color='k', lw=linewidth)
# View range
viewRange_dict[(row,col)] = list(m)+list(viewRange[m])
# Draw initial value
InitVal = "{0:0.0f}".format(Y[0])
if m[0] == 'Voltage':
InitVal += 'mV'
elif m[0] == 'Current':
InitVal += 'pA'
elif m[0] == 'Stimulus':
if stimReflectCurrent:
InitVal += 'pA'
else:
InitVal = ''
ax[ind].text(X[0]-0.03*(viewRange[m][0][1]-viewRange[m][0][0]), Y[0]-1, InitVal, ha='right', va='center', color=colorfy[n%len(colorfy)])
if m[1] not in channels:
channels.append(m[1])
# update axis
row, col = {
'ver': (row+1, col),
'hor': (row, col+1),
'cha': (row+1 if c<nrows-1 else 0, col+1 if c==nrows-1 else col),
'epi': (row+1 if c==ncols-1 else row, col+1 if c<ncols-1 else 0)
}.get(gridSpec[:3].lower())
if annotation.lower() != 'none':
final_notes = writeEpisodeNote(zData, viewRange[m][0], channels=channels, mode=annotation)
# Draw more annotations
textbox.append(TextArea(final_notes, minimumdescent=False, textprops=dict(color=colorfy[n%len(colorfy)])))
# Group all the episode annotation text
if annotation.lower() != 'none':
box = VPacker(children=textbox, align="left",pad=0, sep=2)
annotationbox = AnchoredOffsetbox(loc=3, child=box, frameon=False, bbox_to_anchor=[1, 1.1])
ax[-1].add_artist(annotationbox)
scalebar = [annotationbox]
else:
scalebar = []
# set axis
for c, vr in enumerate(viewRange_dict.items()):
l, r = vr
ind = np.ravel_multi_index(l, (nrows, ncols), order='C')
ax[ind].set_xlim(r[2])
ax[ind].set_ylim(r[3])
# Add scalebar
if scalebarAt.lower()=='all' or (scalebarAt.lower()=='first' and ind in first_last_mat[0]) or (scalebarAt.lower()=='last' and ind in first_last_mat[-1]):
scalebar.append(AddTraceScaleBar(xunit='ms', yunit='mV' if r[0]=='Voltage' else 'pA', ax=ax[ind]))
else: # including 'none'
TurnOffAxis(ax=ax[ind])
plt.subplots_adjust(hspace = .001)
# temp = 510 + c
temp = tic.MaxNLocator(3)
ax[ind].yaxis.set_major_locator(temp)
if (isinstance(setFont, str) and setFont.lower() in ['default', 'arial', 'helvetica']) or \
(isinstance(setFont, bool) and setFont):
SetFont(ax, fig, fontsize=fontSize, fontname=os.path.join(__location__,'../resources/Helvetica.ttf'))
else:
SetFont(ax, fig, fontsize=fontSize, fontname=setFont)
# save the figure
if adjustFigW:
fig_size = (fig_size[0]*ncols, fig_size[1])
if adjustFigH:
fig_size = (fig_size[0], fig_size[1]*nrows)
fig.set_size_inches(fig_size)
# plt.subplots_adjust(hspace=-0.8)
fig.savefig(saveDir, bbox_inches='tight', bbox_extra_artists=tuple(scalebar), dpi=dpi, transparent=True)
# Close the figure after save
plt.close(fig)
if '.svg' in saveDir:
svg2eps_ai(source_file=saveDir, target_file=saveDir.replace('.svg', '.eps'))
return(ax)
def PlotTracesConcatenated(df, index, viewRange, saveDir, colorfy=False, dpi=300,
fig_size=None, nullRange=None, hSpaceType='Fixed', hFixedSpace=0.10,
adjustFigW=True, adjustFigH=True, trimH=(None,None),
annotation='Simple', setFont='default', fontSize=10,
linewidth=1.0, monoStim=False, stimReflectCurrent=True):
"""Export traces arranged horizontally.
Good for an experiments acquired over multiple episodes.
trimH: (t1, t2) trim off the beginning of first episode by t1 seconds, and the
the end of the last episode by t2 seconds
"""
nchannels = len(viewRange.keys())
if not colorfy:
colorfy=['k']
fig, _= plt.subplots(nrows=nchannels, ncols=1, sharex=True)
ax = fig.get_axes()
# text annotation area
textbox = []
nullBase = dict()
currentTime = 0
maxWindow = max(df['Duration'])
for n, i in enumerate(index): #iterate over episodes
zData = df['Data'][i]
ts = zData.Protocol.msPerPoint
channels = []
for c, m in enumerate(viewRange.keys()): # iterate over channels/streams
# Draw plots
X = zData.Time + currentTime
Y = getattr(zData, m[0])[m[1]]
# null the trace
if nullRange is not None:
if n == 0: # calculate nullBase
if isinstance(nullRange, list):
nullBase[(m[0],m[1])] = np.mean(spk_window(Y, ts, nullRange))
else:
nullBase[(m[0],m[1])] = Y[time2ind(nullRange, ts)]
Y = Y - nullBase[(m[0],m[1])]
if n == 0 and trimH[0] is not None:
X = spk_window(X, ts, (trimH[0], None))
Y = spk_window(X, ts, (trimH[0], None))
elif n + 1 == len(index) and trimH[1] is not None:
X = spk_window(X, ts, (None, trimH[1]))
Y = spk_window(X, ts, (None, trimH[1]))
# Stim channel reflects current channel
if stimReflectCurrent and m[0]=='Stimulus':
CurBase = spk_window(zData.Current[m[1]], ts, viewRange[m][0]) # use view range of stimulus on current
CurBase = np.mean(spk_window(CurBase, ts, [0,50]))
Y = Y + CurBase
# do the plot
if m[0] in ['Voltage', 'Current'] or not monoStim: # temporary workaround
ax[c].plot(X, Y, color=colorfy[n%len(colorfy)], lw=linewidth)
else:
ax[c].plot(X, Y, color='k', lw=linewidth)
# Draw the initial value, only for the first plot
if n == 0:
InitVal = "{0:0.0f}".format(Y[0])
if m[0] == 'Voltage':
InitVal += 'mV'
elif m[0] == 'Current':
InitVal += 'pA'
elif m[0] == 'Stimulus':
if stimReflectCurrent:
InitVal += 'pA'
else:
InitVal = ''
ax[c].text(X[0]-0.03*(viewRange[m][0][1]-viewRange[m][0][0]), Y[0]-1, InitVal, ha='right', va='center', color=colorfy[n%len(colorfy)])
if m[1] not in channels:
channels.append(m[1])
if annotation.lower() != 'none':
final_notes = writeEpisodeNote(zData, viewRange[m][0], channels=channels, mode=annotation)
# Draw some annotations
textbox.append(TextArea(final_notes, minimumdescent=False, textprops=dict(color=colorfy[n%len(colorfy)])))
# Set some spacing for the next episode
if n+1 < len(index):
if hSpaceType.lower() == 'fixed':
currentTime = currentTime + (len(Y)-1)*ts + maxWindow * hFixedSpace / 100.0
elif hSpaceType.lower() in ['real time', 'realtime', 'rt']:
currentTime = currentTime + (df['Data'][index[n+1]].Protocol.WCtime - zData.Protocol.WCtime)*1000
# Group all the episodes annotation text
if annotation.lower() != 'none':
box = VPacker(children=textbox, align="left",pad=0, sep=2)
annotationbox = AnchoredOffsetbox(loc=3, child=box, frameon=False, bbox_to_anchor=[1, 1.1])
ax[-1].add_artist(annotationbox)
scalebar = [annotationbox]
else:
scalebar = []
# set axis
for c, vr in enumerate(viewRange.items()):
ax[c].set_ylim(vr[1][1])
# Add scalebar
scalebar.append(AddTraceScaleBar(xunit='ms', yunit='mV' if vr[0][0]=='Voltage' else 'pA', ax=ax[c]))
plt.subplots_adjust(hspace = .001)
temp = tic.MaxNLocator(3)
ax[c].yaxis.set_major_locator(temp)
# Set font
if (isinstance(setFont, str) and setFont.lower() in ['default', 'arial', 'helvetica']) or \
(isinstance(setFont, bool) and setFont):
SetFont(ax, fig, fontsize=fontSize, fontname=os.path.join(__location__,'../resources/Helvetica.ttf'))
else:
SetFont(ax, fig, fontsize=fontSize, fontname=setFont)
# figure out and set the figure size
if adjustFigW:
fig_size = (np.ptp(ax[0].get_xlim()) / maxWindow * fig_size[0], fig_size[1])
if adjustFigH:
fig_size = (fig_size[0], fig_size[1]*nchannels)
fig.set_size_inches(fig_size)
fig.savefig(saveDir, bbox_inches='tight', bbox_extra_artists=tuple(scalebar), dpi=dpi)
# Close the figure after save
plt.close(fig)
# Convert svg file to eps
if '.svg' in saveDir:
svg2eps_ai(source_file=saveDir, target_file=saveDir.replace('.svg', '.eps'))
return(ax)
def PlotTraces(df, index, viewRange, saveDir, colorfy=False, dpi=300, fig_size=None,
adjustFigH=True, adjustFigW=True, nullRange=None, annotation='Simple',
setFont='default', fontSize=10, linewidth=1.0, monoStim=False, stimReflectCurrent=True):
"""Export multiple traces overlapping each other"""
# np.savez('R:/tmp.npz', df=df, index=index, viewRange=[viewRange], saveDir=saveDir, colorfy=colorfy)
# return
# set_trace()
# Start the figure
# viewRange= {(channel, stream):[[xmin,xmax],[ymin),ymax]]}
nchannels = len(viewRange.keys())
if not fig_size: # if not specified size, set to (4, 4*nchannels)
fig_size = (4, 4*nchannels)
if not colorfy:
colorfy=['k']
fig, _= plt.subplots(nrows=nchannels, ncols=1, sharex=True)
ax = fig.get_axes()
# text annotation area
textbox = []
for n, i in enumerate(index):
zData = df['Data'][i]
ts = zData.Protocol.msPerPoint
channels = []
for c, m in enumerate(viewRange.keys()):
# Draw plots
X = zData.Time
Y = getattr(zData, m[0])[m[1]]
# null the trace, but ignore arithmetic data since their data were already nulled
if nullRange is not None and zData.Protocol.acquireComment != 'PySynapse Arithmetic Data':
if isinstance(nullRange, list):
Y = Y - np.mean(spk_window(Y, ts, nullRange))
else: # a single number
Y = Y - Y[time2ind(nullRange, ts)]
# window the plot
X = spk_window(X, ts, viewRange[m][0])
Y = spk_window(Y, ts, viewRange[m][0])
# Stim channel reflects current channel
if stimReflectCurrent and m[0]=='Stimulus':
CurBase = spk_window(zData.Current[m[1]], ts, viewRange[m][0]) # use view range of stimulus on current
CurBase = np.mean(spk_window(CurBase, ts, [0,50]))
Y = Y + CurBase
# do the plot
if m[0] in ['Voltage', 'Current'] or not monoStim:
ax[c].plot(X, Y, color=colorfy[n%len(colorfy)], lw=linewidth)
else:
ax[c].plot(X, Y, color='k', lw=linewidth)
# Draw initial value
InitVal = "{0:0.0f}".format(Y[0])
if m[0] == 'Voltage':
InitVal += 'mV'
elif m[0] == 'Current':
InitVal += 'pA'
elif m[0] == 'Stimulus':
if stimReflectCurrent:
InitVal += 'pA'
else:
InitVal = ''
if m[1] not in channels:
channels.append(m[1])
#kkks = viewRange[m][0][1]-viewRange[m][0][0]
#set_trace()
ax[c].text(X[0]-0.03*(viewRange[m][0][1]-viewRange[m][0][0]), Y[0]-1, InitVal, ha='right', va='center', color=colorfy[n%len(colorfy)])
if annotation.lower() != 'none':
final_notes = writeEpisodeNote(zData, viewRange[m][0], channels=channels, mode=annotation)
# Draw more annotations
textbox.append(TextArea(final_notes, minimumdescent=False, textprops=dict(color=colorfy[n%len(colorfy)])))
# Group all the episode annotation text
if annotation.lower() != 'none':
box = VPacker(children=textbox, align="left",pad=0, sep=2)
annotationbox = AnchoredOffsetbox(loc=3, child=box, frameon=False, bbox_to_anchor=[1, 1.1])
ax[-1].add_artist(annotationbox)
scalebar = [annotationbox]
else:
scalebar = []
# set axis
for c, vr in enumerate(viewRange.items()):
l, r = vr
ax[c].set_xlim(r[0])
ax[c].set_ylim(r[1])
# Add scalebar
scalebar.append(AddTraceScaleBar(xunit='ms', yunit='mV' if l[0]=='Voltage' else 'pA', ax=ax[c]))
plt.subplots_adjust(hspace = .001)
# temp = 510 + c
temp = tic.MaxNLocator(3)
ax[c].yaxis.set_major_locator(temp)
if (isinstance(setFont, str) and setFont.lower() in ['default', 'arial', 'helvetica']) or \
(isinstance(setFont, bool) and setFont):
SetFont(ax, fig, fontsize=fontSize, fontname=os.path.join(__location__,'../resources/Helvetica.ttf'))
else:
SetFont(ax, fig, fontsize=fontSize, fontname=setFont)
# save the figure
if adjustFigH:
fig_size = (fig_size[0], fig_size[1]*nchannels)
fig.set_size_inches(fig_size)
# plt.subplots_adjust(hspace=-0.8)
fig.savefig(saveDir, bbox_inches='tight', bbox_extra_artists=tuple(scalebar), dpi=dpi, transparent=True)
# Close the figure after save
plt.close(fig)
# Convert from svg to eps
if '.svg' in saveDir:
svg2eps_ai(source_file=saveDir, target_file=saveDir.replace('.svg', '.eps'))
return(ax)
def PlotTracesAsGrids(df, index, viewRange, saveDir=None, colorfy=False, artists=None, dpi=300,
fig_size=None, adjustFigH=True, adjustFigW=True, nullRange=None,
annotation='Simple', setFont='default',gridSpec='Vertical',
scalebarAt='all', fontSize=10, linewidth=1.0, monoStim=False,
stimReflectCurrent=True):
"Export Multiple episodes arranged in a grid; default vertically"""
if not colorfy:
colorfy = ['k']
nchannels = len(viewRange.keys())
nepisodes = len(index)
if isinstance(gridSpec, str):
nrows, ncols = {
'ver': (nchannels*nepisodes, 1),
'hor': (1, nchannels*nepisodes),
'cha': (nchannels, nepisodes),
'epi': (nepisodes, nchannels)
}.get(gridSpec[:3].lower(), (None, None))
if nrows is None:
raise(ValueError('Unrecognized gridSpec: {}'.format(gridSpec)))
else:
raise(TypeError('Unrecognized type of argument: "gridSpec"'))
fig, _ = plt.subplots(nrows=nrows, ncols=ncols, sharex=True)
ax = fig.get_axes()
# text annotation area
textbox = []
viewRange_dict = {}
row, col = 0,0 # keep track of axis used
first_last_mat = [[],[]]
for n, i in enumerate(index):
zData = df['Data'][i]
ts = zData.Protocol.msPerPoint
channels = []
for c, m in enumerate(viewRange.keys()):
# Draw plots
X = zData.Time
Y = getattr(zData, m[0])[m[1]]
# null the trace
if nullRange is not None:
if isinstance(nullRange, list):
Y = Y - np.mean(spk_window(Y, ts, nullRange))
else: # a single number
Y = Y - Y[time2ind(nullRange, ts)]
# window the plot
X = spk_window(X, ts, viewRange[m][0])
Y = spk_window(Y, ts, viewRange[m][0])
# Stim channel reflects current channel
if stimReflectCurrent and m[0]=='Stimulus':
CurBase = spk_window(zData.Current[m[1]], ts, viewRange[m][0]) # use view range of stimulus on current
CurBase = np.mean(spk_window(CurBase, ts, [0,50]))
Y = Y + CurBase
# do the plot
ind = np.ravel_multi_index((row,col), (nrows, ncols), order='C')
if n == 0:
first_last_mat[0].append(ind)
elif n == len(index)-1:
first_last_mat[-1].append(ind)
if m[0] in ['Voltage', 'Current'] or not monoStim:
ax[ind].plot(X, Y, color=colorfy[n%len(colorfy)], lw=linewidth, solid_joinstyle='bevel', solid_capstyle='butt')
else:
ax[ind].plot(X, Y, color='k', lw=linewidth, solid_joinstyle='bevel', solid_capstyle='butt')
# View range
viewRange_dict[(row,col)] = list(m)+list(viewRange[m])
# Draw initial value
InitVal = "{0:0.0f}".format(Y[0])
if m[0] == 'Voltage':
InitVal += 'mV'
elif m[0] == 'Current':
InitVal += 'pA'
elif m[0] == 'Stimulus':
if stimReflectCurrent:
InitVal += 'pA'
else:
InitVal = ''
ax[ind].text(X[0]-0.03*(viewRange[m][0][1]-viewRange[m][0][0]), Y[0]-1, InitVal, ha='right', va='center', color=colorfy[n%len(colorfy)])
if m[1] not in channels:
channels.append(m[1])
# update axis
row, col = {
'ver': (row+1, col),
'hor': (row, col+1),
'cha': (row+1 if c<nrows-1 else 0, col+1 if c==nrows-1 else col),
'epi': (row+1 if c==ncols-1 else row, col+1 if c<ncols-1 else 0)
}.get(gridSpec[:3].lower())
if annotation.lower() != 'none':
final_notes = writeEpisodeNote(zData, viewRange[m][0], channels=channels, mode=annotation)
# Draw more annotations
textbox.append(TextArea(final_notes, minimumdescent=False, textprops=dict(color=colorfy[n%len(colorfy)])))
# Group all the episode annotation text
if annotation.lower() != 'none':
box = VPacker(children=textbox, align="left",pad=0, sep=2)
annotationbox = AnchoredOffsetbox(loc=3, child=box, frameon=False, bbox_to_anchor=[1, 1.1])
ax[-1].add_artist(annotationbox)
scalebar = [annotationbox]
else:
scalebar = []
# set axis
for c, vr in enumerate(viewRange_dict.items()):
l, r = vr
ind = np.ravel_multi_index(l, (nrows, ncols), order='C')
ax[ind].set_xlim(r[2])
ax[ind].set_ylim(r[3])
# Add scalebar
if scalebarAt.lower()=='all' or (scalebarAt.lower()=='first' and ind in first_last_mat[0]) or (scalebarAt.lower()=='last' and ind in first_last_mat[-1]):
scalebar.append(AddTraceScaleBar(xunit='ms', yunit='mV' if r[0]=='Voltage' else 'pA', ax=ax[ind]))
else: # including 'none'
TurnOffAxis(ax=ax[ind])
plt.subplots_adjust(hspace = .001)
# temp = 510 + c
temp = tic.MaxNLocator(3)
ax[ind].yaxis.set_major_locator(temp)
# Draw annotation artist for each export
DrawAnnotationArtists(artists, axs=[ax[ind]])
if (isinstance(setFont, str) and setFont.lower() in ['default', 'arial', 'helvetica']) or \
(isinstance(setFont, bool) and setFont):
SetFont(ax, fig, fontsize=fontSize, fontname=os.path.join(__location__,'../resources/Helvetica.ttf'))
else:
SetFont(ax, fig, fontsize=fontSize, fontname=setFont)
# save the figure
if adjustFigW:
fig_size = (fig_size[0]*ncols, fig_size[1])
if adjustFigH:
fig_size = (fig_size[0], fig_size[1]*nrows)
fig.set_size_inches(fig_size)
# plt.subplots_adjust(hspace=-0.8)
fig.savefig(saveDir, bbox_inches='tight', bbox_extra_artists=tuple(scalebar), dpi=dpi, transparent=True)
# Close the figure after save
plt.close(fig)
if '.svg' in saveDir:
svg2eps_ai(source_file=saveDir, target_file=saveDir.replace('.svg', '.eps'))
return(ax)
def PlotTracesConcatenated(df, index, viewRange, saveDir, colorfy=False, artists=None, dpi=300,
fig_size=None, nullRange=None, hSpaceType='Fixed', hFixedSpace=0.10,
adjustFigW=True, adjustFigH=True, trimH=(None,None),
annotation='Simple', setFont='default', fontSize=10,
linewidth=1.0, monoStim=False, stimReflectCurrent=True):
"""Export traces arranged horizontally.
Good for an experiments acquired over multiple episodes.
trimH: (t1, t2) trim off the beginning of first episode by t1 seconds, and the
the end of the last episode by t2 seconds
"""
nchannels = len(viewRange.keys())
if not colorfy:
colorfy=['k']
fig, _= plt.subplots(nrows=nchannels, ncols=1, sharex=True)
ax = fig.get_axes()
# text annotation area
textbox = []
nullBase = dict()
currentTime = 0
maxWindow = max(df['Duration'])
for n, i in enumerate(index): #iterate over episodes
zData = df['Data'][i]
ts = zData.Protocol.msPerPoint
channels = []
for c, m in enumerate(viewRange.keys()): # iterate over channels/streams
# Draw plots
X = zData.Time + currentTime
Y = getattr(zData, m[0])[m[1]]
# null the trace
if nullRange is not None:
if n == 0: # calculate nullBase
if isinstance(nullRange, list):
nullBase[(m[0],m[1])] = np.mean(spk_window(Y, ts, nullRange))
else:
nullBase[(m[0],m[1])] = Y[time2ind(nullRange, ts)]
Y = Y - nullBase[(m[0],m[1])]
if n == 0 and trimH[0] is not None:
X = spk_window(X, ts, (trimH[0], None))
Y = spk_window(X, ts, (trimH[0], None))
elif n + 1 == len(index) and trimH[1] is not None:
X = spk_window(X, ts, (None, trimH[1]))
Y = spk_window(X, ts, (None, trimH[1]))
# Stim channel reflects current channel
if stimReflectCurrent and m[0]=='Stimulus':
CurBase = spk_window(zData.Current[m[1]], ts, viewRange[m][0]) # use view range of stimulus on current
CurBase = np.mean(spk_window(CurBase, ts, [0,50]))
Y = Y + CurBase
# do the plot
if m[0] in ['Voltage', 'Current'] or not monoStim: # temporary workaround
ax[c].plot(X, Y, color=colorfy[n%len(colorfy)], lw=linewidth, solid_joinstyle='bevel', solid_capstyle='butt')
else:
ax[c].plot(X, Y, color='k', lw=linewidth, solid_joinstyle='bevel', solid_capstyle='butt')
# Draw the initial value, only for the first plot
if n == 0:
InitVal = "{0:0.0f}".format(Y[0])
if m[0] == 'Voltage':
InitVal += 'mV'
elif m[0] == 'Current':
InitVal += 'pA'
elif m[0] == 'Stimulus':
if stimReflectCurrent:
InitVal += 'pA'
else:
InitVal = ''
ax[c].text(X[0]-0.03*(viewRange[m][0][1]-viewRange[m][0][0]), Y[0]-1, InitVal, ha='right', va='center', color=colorfy[n%len(colorfy)])
if m[1] not in channels:
channels.append(m[1])
if annotation.lower() != 'none':
final_notes = writeEpisodeNote(zData, viewRange[m][0], channels=channels, mode=annotation)
# Draw some annotations
textbox.append(TextArea(final_notes, minimumdescent=False, textprops=dict(color=colorfy[n%len(colorfy)])))
# Set some spacing for the next episode
if n+1 < len(index):
if hSpaceType.lower() == 'fixed':
currentTime = currentTime + (len(Y)-1)*ts + maxWindow * hFixedSpace / 100.0
elif hSpaceType.lower() in ['real time', 'realtime', 'rt']:
currentTime = currentTime + (df['Data'][index[n+1]].Protocol.WCtime - zData.Protocol.WCtime)*1000
# Group all the episodes annotation text
if annotation.lower() != 'none':
box = VPacker(children=textbox, align="left",pad=0, sep=2)
annotationbox = AnchoredOffsetbox(loc=3, child=box, frameon=False, bbox_to_anchor=[1, 1.1])
ax[-1].add_artist(annotationbox)
scalebar = [annotationbox]
else:
scalebar = []
# set axis
for c, vr in enumerate(viewRange.items()):
ax[c].set_ylim(vr[1][1])
# Add scalebar
scalebar.append(AddTraceScaleBar(xunit='ms', yunit='mV' if vr[0][0]=='Voltage' else 'pA', ax=ax[c]))
plt.subplots_adjust(hspace = .001)
temp = tic.MaxNLocator(3)
ax[c].yaxis.set_major_locator(temp)
# Set font
if (isinstance(setFont, str) and setFont.lower() in ['default', 'arial', 'helvetica']) or \
(isinstance(setFont, bool) and setFont):
SetFont(ax, fig, fontsize=fontSize, fontname=os.path.join(__location__,'../resources/Helvetica.ttf'))
else:
SetFont(ax, fig, fontsize=fontSize, fontname=setFont)
# figure out and set the figure size
if adjustFigW:
fig_size = (np.ptp(ax[0].get_xlim()) / maxWindow * fig_size[0], fig_size[1])
if adjustFigH:
fig_size = (fig_size[0], fig_size[1]*nchannels)
fig.set_size_inches(fig_size)
fig.savefig(saveDir, bbox_inches='tight', bbox_extra_artists=tuple(scalebar), dpi=dpi)
# Close the figure after save
plt.close(fig)
# Convert svg file to eps
if '.svg' in saveDir:
svg2eps_ai(source_file=saveDir, target_file=saveDir.replace('.svg', '.eps'))
return(ax)
def PlotTraces(df, index, viewRange, saveDir, colorfy=False, artists=None, dpi=300, fig_size=None,
adjustFigH=True, adjustFigW=True, nullRange=None, annotation='Simple',
setFont='default', fontSize=10, linewidth=1.0, monoStim=False, stimReflectCurrent=True):
"""Export multiple traces overlapping each other"""
# np.savez('R:/tmp.npz', df=df, index=index, viewRange=[viewRange], saveDir=saveDir, colorfy=colorfy)
# return
# set_trace()
# Start the figure
# viewRange= {(channel, stream):[[xmin,xmax],[ymin),ymax]]}
nchannels = len(viewRange.keys())
if not fig_size: # if not specified size, set to (4, 4*nchannels)
fig_size = (4, 4*nchannels)
if not colorfy:
colorfy=['k']
fig, _ = plt.subplots(nrows=nchannels, ncols=1, sharex=True)
ax = fig.get_axes()
# text annotation area
textbox = []
for n, i in enumerate(index):
zData = df['Data'][i]
ts = zData.Protocol.msPerPoint
channels = []
for c, m in enumerate(viewRange.keys()):
# Draw plots
X = zData.Time
Y = getattr(zData, m[0])[m[1]]
# null the trace, but ignore arithmetic data since their data were already nulled
if nullRange is not None and zData.Protocol.acquireComment != 'PySynapse Arithmetic Data':
if isinstance(nullRange, list):
Y = Y - np.mean(spk_window(Y, ts, nullRange))
else: # a single number
Y = Y - Y[time2ind(nullRange, ts)]
# window the plot
X = spk_window(X, ts, viewRange[m][0])
Y = spk_window(Y, ts, viewRange[m][0])
# Stim channel reflects current channel
if stimReflectCurrent and m[0]=='Stimulus':
CurBase = spk_window(zData.Current[m[1]], ts, viewRange[m][0]) # use view range of stimulus on current
CurBase = np.mean(spk_window(CurBase, ts, [0,50]))
Y = Y + CurBase
# do the plot
if m[0] in ['Voltage', 'Current'] or not monoStim:
ax[c].plot(X, Y, color=colorfy[n%len(colorfy)], lw=linewidth, solid_joinstyle='bevel', solid_capstyle='butt')
else:
ax[c].plot(X, Y, color='k', lw=linewidth, solid_joinstyle='bevel', solid_capstyle='butt')
# Draw initial value
InitVal = "{0:0.0f}".format(Y[0])
if m[0] == 'Voltage':
InitVal += 'mV'
elif m[0] == 'Current':
InitVal += 'pA'
elif m[0] == 'Stimulus':
if stimReflectCurrent:
InitVal += 'pA'
else:
InitVal = ''
if m[1] not in channels:
channels.append(m[1])
#kkks = viewRange[m][0][1]-viewRange[m][0][0]
#set_trace()
ax[c].text(X[0]-0.03*(viewRange[m][0][1]-viewRange[m][0][0]), Y[0]-1, InitVal, ha='right', va='center', color=colorfy[n%len(colorfy)])
if annotation.lower() != 'none':
final_notes = writeEpisodeNote(zData, viewRange[m][0], channels=channels, mode=annotation)
# Draw more annotations
textbox.append(TextArea(final_notes, minimumdescent=False, textprops=dict(color=colorfy[n%len(colorfy)])))
# Group all the episode annotation text
if annotation.lower() != 'none':
box = VPacker(children=textbox, align="left", pad=0, sep=2)
annotationbox = AnchoredOffsetbox(loc=3, child=box, frameon=False, bbox_to_anchor=[1, 1.1])
ax[-1].add_artist(annotationbox)
scalebar = [annotationbox]
else:
scalebar = []
# Draw annotation artists
DrawAnnotationArtists(artists, axs=ax)
# set axis
for c, vr in enumerate(viewRange.items()):
l, r = vr
ax[c].set_xlim(r[0])
ax[c].set_ylim(r[1])
# Add scalebar
scalebar.append(AddTraceScaleBar(xunit='ms', yunit='mV' if l[0]=='Voltage' else 'pA', ax=ax[c]))
plt.subplots_adjust(hspace=.001)
# temp = 510 + c
temp = tic.MaxNLocator(3)
ax[c].yaxis.set_major_locator(temp)
if (isinstance(setFont, str) and setFont.lower() in ['default', 'arial', 'helvetica']) or \
(isinstance(setFont, bool) and setFont):
SetFont(ax, fig, fontsize=fontSize, fontname=os.path.join(__location__,'../resources/Helvetica.ttf'))
else:
SetFont(ax, fig, fontsize=fontSize, fontname=setFont)
# save the figure
if adjustFigH:
fig_size = (fig_size[0], fig_size[1]*nchannels)
fig.set_size_inches(fig_size)
# plt.subplots_adjust(hspace=-0.8)
fig.savefig(saveDir, bbox_inches='tight', bbox_extra_artists=tuple(scalebar), dpi=dpi, transparent=True)
# Close the figure after save
plt.close(fig)
# Convert from svg to eps
if '.svg' in saveDir:
svg2eps_ai(source_file=saveDir, target_file=saveDir.replace('.svg', '.eps'))
return(ax)