def shift_report(inFID,
outFID,
inHdr,
outHdr,
ppmlim=(0.2, 4.2),
html=None,
function='shift'):
"""
Generate report
"""
import plotly.graph_objects as go
from plotly.subplots import make_subplots
from fsl_mrs.utils.preproc.reporting import plotStyles, plotAxesStyle
plotIn = MRS(FID=inFID, header=inHdr)
plotOut = MRS(FID=outFID, header=outHdr)
# Fetch line styles
lines, colors, _ = plotStyles()
# Make a new figure
fig = make_subplots(rows=1, cols=2, subplot_titles=['Spectra', 'FID'])
# Add lines to figure
trace1 = go.Scatter(x=plotIn.getAxes(ppmlim=ppmlim),
y=np.real(plotIn.getSpectrum(ppmlim=ppmlim)),
mode='lines',
name='Original',
line=lines['in'])
trace2 = go.Scatter(x=plotOut.getAxes(ppmlim=ppmlim),
y=np.real(plotOut.getSpectrum(ppmlim=ppmlim)),
mode='lines',
name='Shifted',
line=lines['out'])
fig.add_trace(trace1, row=1, col=1)
fig.add_trace(trace2, row=1, col=1)
# Add lines to figure
trace3 = go.Scatter(x=plotIn.getAxes(axis='time'),
y=np.real(plotIn.FID),
mode='lines',
name='Original',
line=lines['emph'])
trace4 = go.Scatter(x=plotOut.getAxes(axis='time'),
y=np.real(plotOut.FID),
mode='lines',
name='Shifted',
line=lines['diff'])
fig.add_trace(trace3, row=1, col=2)
fig.add_trace(trace4, row=1, col=2)
# Axes layout
plotAxesStyle(fig, ppmlim, title='Shift summary')
fig.layout.xaxis2.update(title_text='Time (s)')
fig.layout.yaxis2.update(zeroline=True,
zerolinewidth=1,
zerolinecolor='Gray',
showgrid=False,
showticklabels=False)
if html is not None:
from plotly.offline import plot
from fsl_mrs.utils.preproc.reporting import figgroup, singleReport
from datetime import datetime
import os.path as op
if op.isdir(html):
filename = 'report_' + datetime.now().strftime(
"%Y%m%d_%H%M%S%f")[:-3] + '.html'
htmlfile = op.join(html, filename)
elif op.isdir(op.dirname(html)) and op.splitext(html)[1] == '.html':
htmlfile = html
else:
raise ValueError('Report html path must be file or directory. ')
operation, function, description = reportStrings(function)
opName = operation
timestr = datetime.now().strftime("%H:%M:%S")
datestr = datetime.now().strftime("%d/%m/%Y")
headerinfo = f'Report for fsl_mrs.utils.preproc.shifting.{function}.\n'\
+ f'Generated at {timestr} on {datestr}.'
# Figures
div = plot(fig, output_type='div', include_plotlyjs='cdn')
figurelist = [
figgroup(fig=div, name='', foretext=f'{description}', afttext=f'')
]
singleReport(htmlfile, opName, headerinfo, figurelist)
return fig
else:
return fig
def combine_FIDs_report(inFIDs,
outFID,
hdr,
ncha=2,
ppmlim=(0.0, 6.0),
method='not specified',
html=None):
""" Take list of FIDs that are passed to combine and output
If uncombined data it will display ncha channels (default 2).
"""
from fsl_mrs.core import MRS
import plotly.graph_objects as go
from fsl_mrs.utils.preproc.reporting import plotStyles, plotAxesStyle
from matplotlib.pyplot import cm
toMRSobj = lambda fid: MRS(FID=fid, header=hdr)
# Assemble data to plot
toPlotIn = []
colourVecIn = []
legendIn = []
if isinstance(inFIDs, list):
for idx, fid in enumerate(inFIDs):
if inFIDs[0].ndim > 1:
toPlotIn.extend([toMRSobj(f) for f in fid[:, :ncha].T])
colourVecIn.extend([idx / len(inFIDs)] * ncha)
legendIn.extend(
[f'FID #{idx}: CHA #{jdx}' for jdx in range(ncha)])
else:
toPlotIn.append(toMRSobj(fid))
colourVecIn.append(idx / len(inFIDs))
legendIn.append(f'FID #{idx}')
elif inFIDs.ndim > 1:
toPlotIn.extend([toMRSobj(f) for f in inFIDs[:, :ncha].T])
colourVecIn.extend([float(jdx) / ncha for jdx in range(ncha)])
legendIn.extend([f'FID #0: CHA #{jdx}' for jdx in range(ncha)])
toPlotOut = []
legendOut = []
if outFID.ndim > 1:
toPlotOut.extend([toMRSobj(f) for f in outFID[:, :ncha].T])
legendOut.extend([f'Combined: CHA #{jdx}' for jdx in range(ncha)])
else:
toPlotOut.append(toMRSobj(outFID))
legendOut.append('Combined')
def addline(fig, mrs, lim, name, linestyle):
trace = go.Scatter(x=mrs.getAxes(ppmlim=lim),
y=np.real(mrs.getSpectrum(ppmlim=lim)),
mode='lines',
name=name,
line=linestyle)
return fig.add_trace(trace)
lines, colors, _ = plotStyles()
colors = cm.Spectral(np.array(colourVecIn).ravel())
fig = go.Figure()
for idx, fid in enumerate(toPlotIn):
cval = np.round(255 * colors[idx, :])
linetmp = {'color': f'rgb({cval[0]},{cval[1]},{cval[2]})', 'width': 1}
fig = addline(fig, fid, ppmlim, legendIn[idx], linetmp)
for idx, fid in enumerate(toPlotOut):
fig = addline(fig, fid, ppmlim, legendOut[idx], lines['blk'])
plotAxesStyle(fig, ppmlim, 'Combined')
# Generate report
if html is not None:
from plotly.offline import plot
from fsl_mrs.utils.preproc.reporting import figgroup, singleReport
from datetime import datetime
import os.path as op
if op.isdir(html):
filename = 'report_' + datetime.now().strftime(
"%Y%m%d_%H%M%S%f")[:-3] + '.html'
htmlfile = op.join(html, filename)
elif op.isdir(op.dirname(html)) and op.splitext(html)[1] == '.html':
htmlfile = html
else:
raise ValueError('Report html path must be file or directory. ')
opName = 'Combination'
timestr = datetime.now().strftime("%H:%M:%S")
datestr = datetime.now().strftime("%d/%m/%Y")
headerinfo = 'Report for fsl_mrs.utils.preproc.combine.combine_FIDs.\n'\
+ f'Generated at {timestr} on {datestr}.'
# Figures
div = plot(fig, output_type='div', include_plotlyjs='cdn')
figurelist = [
figgroup(fig=div,
name='',
foretext=f'Combination of spectra. Method = {method}',
afttext=f'')
]
singleReport(htmlfile, opName, headerinfo, figurelist)
return fig
else:
return fig
def hlsvd_report(inFID,
outFID,
hdr,
limits,
limitUnits='ppm',
plotlim=(0.2, 6),
html=None):
"""
Generate hlsvd report
"""
# from matplotlib import pyplot as plt
from fsl_mrs.core import MRS
import plotly.graph_objects as go
from fsl_mrs.utils.preproc.reporting import plotStyles, plotAxesStyle
# Turn input FIDs into mrs objects
def toMRSobj(fid):
return MRS(FID=fid, header=hdr)
plotIn = toMRSobj(inFID)
plotOut = toMRSobj(outFID)
plotDiff = toMRSobj(outFID - inFID)
if limitUnits.lower() == 'ppm':
limits = np.array(limits) + H2O_PPM_TO_TMS
elif limitUnits.lower() == 'ppm+shift':
pass
elif limitUnits.lower() == 'hz':
limits = (np.array(limits)/(plotIn.centralFrequency/1E6)) + \
H2O_PPM_TO_TMS
else:
raise ValueError('limitUnits should be one of: ppm, ppm+shift or hz.')
# Fetch line styles
lines, colors, _ = plotStyles()
# Make a new figure
fig = go.Figure()
# Add lines to figure
def addline(fig, mrs, lim, name, linestyle):
trace = go.Scatter(x=mrs.getAxes(ppmlim=lim),
y=np.real(mrs.getSpectrum(ppmlim=lim)),
mode='lines',
name=name,
line=linestyle)
return fig.add_trace(trace)
fig = addline(fig, plotIn, plotlim, 'Uncorrected', lines['in'])
fig = addline(fig, plotIn, limits, 'Limits', lines['emph'])
fig = addline(fig, plotOut, plotlim, 'Corrected', lines['out'])
fig = addline(fig, plotDiff, plotlim, 'Difference', lines['diff'])
# Axes layout
plotAxesStyle(fig, plotlim, title='HLSVD summary')
# Axes
if html is not None:
from plotly.offline import plot
from fsl_mrs.utils.preproc.reporting import figgroup, singleReport
from datetime import datetime
import os.path as op
if op.isdir(html):
filename = 'report_' + \
datetime.now().strftime("%Y%m%d_%H%M%S%f")[:-3]+'.html'
htmlfile = op.join(html, filename)
elif op.isdir(op.dirname(html)) and op.splitext(html)[1] == '.html':
htmlfile = html
else:
raise ValueError('Report html path must be file or directory. ')
opName = 'HLSVD'
timestr = datetime.now().strftime("%H:%M:%S")
datestr = datetime.now().strftime("%d/%m/%Y")
headerinfo = 'Report for fsl_mrs.utils.preproc.remove.HLSVD.\n' + \
f'Generated at {timestr} on {datestr}.'
# Figures
div = plot(fig, output_type='div', include_plotlyjs='cdn')
figurelist = [
figgroup(fig=div,
name='',
foretext='HLSVD removal of peaks in the range'
f' {limits[0]:0.1f} to'
f' {limits[1]:0.1f} ppm.',
afttext='')
]
singleReport(htmlfile, opName, headerinfo, figurelist)
return fig
else:
return fig
def apodize_report(inFID, outFID, hdr, plotlim=(0.2, 6), html=None):
"""
Generate report
"""
# from matplotlib import pyplot as plt
from fsl_mrs.core import MRS
import plotly.graph_objects as go
from fsl_mrs.utils.preproc.reporting import plotStyles, plotAxesStyle
# Turn input FIDs into mrs objects
toMRSobj = lambda fid: MRS(FID=fid, header=hdr)
plotIn = toMRSobj(inFID)
plotOut = toMRSobj(outFID)
# Fetch line styles
lines, colors, _ = plotStyles()
# Make a new figure
fig = go.Figure()
# Add lines to figure
def addline(fig, mrs, lim, name, linestyle):
trace = go.Scatter(x=mrs.getAxes(ppmlim=lim),
y=np.real(mrs.getSpectrum(ppmlim=lim)),
mode='lines',
name=name,
line=linestyle)
return fig.add_trace(trace)
fig = addline(fig, plotIn, plotlim, 'Uncorrected', lines['in'])
fig = addline(fig, plotOut, plotlim, 'Corrected', lines['out'])
# Axes layout
plotAxesStyle(fig, plotlim, title='Apodization summary')
# Generate report
if html is not None:
from plotly.offline import plot
from fsl_mrs.utils.preproc.reporting import figgroup, singleReport
from datetime import datetime
import os.path as op
if op.isdir(html):
filename = 'report_' + datetime.now().strftime(
"%Y%m%d_%H%M%S%f")[:-3] + '.html'
htmlfile = op.join(html, filename)
elif op.isdir(op.dirname(html)) and op.splitext(html)[1] == '.html':
htmlfile = html
else:
raise ValueError('Report html path must be file or directory. ')
opName = 'Apodization'
timestr = datetime.now().strftime("%H:%M:%S")
datestr = datetime.now().strftime("%d/%m/%Y")
headerinfo = 'Report for fsl_mrs.utils.preproc.filtering.apodize.\n'\
+ f'Generated at {timestr} on {datestr}.'
# Figures
div = plot(fig, output_type='div', include_plotlyjs='cdn')
figurelist = [
figgroup(fig=div,
name='',
foretext=f'Apodization of spectra.',
afttext=f'')
]
singleReport(htmlfile, opName, headerinfo, figurelist)
return fig
else:
return fig
def phase_freq_align_diff_report(inFIDs0,
inFIDs1,
outFIDs0,
outFIDs1,
hdr,
eps,
phi,
ppmlim=None,
diffType='add',
shift=True,
html=None):
from fsl_mrs.utils.preproc.combine import combine_FIDs
import plotly.graph_objects as go
from fsl_mrs.utils.preproc.reporting import plotStyles, plotAxesStyle
from plotly.subplots import make_subplots
# Fetch line styles
lines, _, _ = plotStyles()
# Make a new figure
fig = make_subplots(rows=1, cols=2, subplot_titles=['Phase', 'Shift'])
trace1 = go.Scatter(x=np.arange(1,
len(phi) + 1),
y=np.array(phi) * (180.0 / np.pi),
mode='lines',
name='Phase',
line=lines['out'])
fig.add_trace(trace1, row=1, col=1)
fig.layout.xaxis.update(title_text='Transient #')
fig.layout.yaxis.update(title_text=r'$\phi$ (degrees)')
trace2 = go.Scatter(x=np.arange(1,
len(eps) + 1),
y=eps,
mode='lines',
name='Shift',
line=lines['diff'])
fig.add_trace(trace2, row=1, col=2)
fig.layout.yaxis2.update(title_text='Shift (Hz)')
fig.layout.xaxis2.update(title_text='Transient #')
diffFIDListIn = []
diffFIDListOut = []
for fid0i, fid1i, fid0o, fid1o in zip(inFIDs0, inFIDs1, outFIDs0,
outFIDs1):
if diffType.lower() == 'add':
diffFIDListIn.append(add(fid1i, fid0i))
diffFIDListOut.append(add(fid1o, fid0o))
elif diffType.lower() == 'sub':
diffFIDListIn.append(subtract(fid1i, fid0i))
diffFIDListOut.append(subtract(fid1o, fid0o))
else:
raise ValueError('diffType must be add or sub.')
meanIn = combine_FIDs(diffFIDListIn, 'mean')
meanOut = combine_FIDs(diffFIDListOut, 'mean')
toMRSobj = lambda fid: MRS(FID=fid, header=hdr)
meanIn = toMRSobj(meanIn)
meanOut = toMRSobj(meanOut)
if shift:
axis = 'ppmshift'
else:
axis = 'ppm'
toPlotIn, toPlotOut = [], []
for fid in diffFIDListIn:
toPlotIn.append(toMRSobj(fid))
for fid in diffFIDListOut:
toPlotOut.append(toMRSobj(fid))
def addline(fig, mrs, lim, name, linestyle):
trace = go.Scatter(x=mrs.getAxes(ppmlim=lim, axis=axis),
y=np.real(mrs.getSpectrum(ppmlim=lim, shift=shift)),
mode='lines',
name=name,
line=linestyle)
return fig.add_trace(trace)
fig2 = go.Figure()
for idx, fid in enumerate(toPlotIn):
cval = np.round(255 * idx / len(toPlotIn))
linetmp = {'color': f'rgb(0,{cval},{cval})', 'width': 1}
fig2 = addline(fig2, fid, ppmlim, f'#{idx}', linetmp)
fig2 = addline(fig2, meanIn, ppmlim, f'Mean - Unligned', lines['blk'])
plotAxesStyle(fig2, ppmlim, 'Unaligned')
fig3 = go.Figure()
for idx, fid in enumerate(toPlotOut):
cval = np.round(255 * idx / len(toPlotIn))
linetmp = {'color': f'rgb(0,{cval},{cval})', 'width': 1}
fig3 = addline(fig3, fid, ppmlim, f'#{idx}', linetmp)
fig3 = addline(fig3, meanIn, ppmlim, f'Mean - Unligned', lines['out'])
fig3 = addline(fig3, meanOut, ppmlim, f'Mean - Aligned', lines['blk'])
plotAxesStyle(fig3, ppmlim, 'Aligned')
if html is not None:
from plotly.offline import plot
from fsl_mrs.utils.preproc.reporting import figgroup, singleReport
from datetime import datetime
import os.path as op
if op.isdir(html):
filename = 'report_' + datetime.now().strftime(
"%Y%m%d_%H%M%S%f")[:-3] + '.html'
htmlfile = op.join(html, filename)
elif op.isdir(op.dirname(html)) and op.splitext(html)[1] == '.html':
htmlfile = html
else:
raise ValueError('Report html path must be file or directory. ')
opName = 'AlignDiff'
timestr = datetime.now().strftime("%H:%M:%S")
datestr = datetime.now().strftime("%d/%m/%Y")
headerinfo = 'Report for fsl_mrs.utils.align.phase_freq_align_diff.\n'\
+ f'Generated at {timestr} on {datestr}.'
# Figures
div = plot(fig, output_type='div', include_plotlyjs='cdn')
figurelist = [
figgroup(fig=div,
name='',
foretext=f'Alignment parameters.',
afttext=f'')
]
div2 = plot(fig2, output_type='div', include_plotlyjs='cdn')
figurelist.append(
figgroup(fig=div2,
name='',
foretext=f'Transients before alignment.',
afttext=f''))
div3 = plot(fig3, output_type='div', include_plotlyjs='cdn')
figurelist.append(
figgroup(fig=div3,
name='',
foretext=f'Transients after alignment.',
afttext=f''))
singleReport(htmlfile, opName, headerinfo, figurelist)
return fig, fig2, fig3
else:
return fig, fig2, fig3
def identifyUnlikeFIDs_report(goodFIDs,badFIDs,hdr,keepIndicies,rmIndicies,metric,ppmlim=(0.2,4.2),sdlimit = 1.96,html=None):
from fsl_mrs.utils.preproc.combine import combine_FIDs
import plotly.graph_objects as go
from fsl_mrs.utils.preproc.reporting import plotStyles,plotAxesStyle
metricGd = np.array(metric)[keepIndicies]
metricBd = np.array(metric)[rmIndicies]
metric_avg = np.mean(metric)
metric_std = np.std(metric)
metricGd_SD = np.abs(metricGd-metric_avg)/metric_std
metricBd_SD = np.abs(metricBd-metric_avg)/metric_std
gdIndex = np.argsort(metricGd_SD)
bdIndex = np.argsort(metricBd_SD)
plotGood,plotBad = [],[]
gdLegend,bdLegend = [],[]
toMRSobj = lambda fid : MRS(FID=fid,header=hdr)
for idx in gdIndex:
fid = goodFIDs[idx]
plotGood.append(toMRSobj(fid))
gdLegend.append(f'Kept (SD={metricGd_SD[idx]:0.2f})')
for idx in bdIndex:
fid = badFIDs[idx]
plotBad.append(toMRSobj(fid))
bdLegend.append(f'Removed (SD={metricBd_SD[idx]:0.2f})')
target = get_target_FID(goodFIDs,target='median')
tgtmrs = toMRSobj(target)
# Fetch line styles
lines,colors,_ = plotStyles()
# Make a new figure
fig = go.Figure()
# Add lines to figure
def addline(fig,mrs,lim,name,linestyle):
trace = go.Scatter(x=mrs.getAxes(ppmlim=lim),
y=np.real(mrs.getSpectrum(ppmlim=lim)),
mode='lines',
name=name,
line=linestyle)
return fig.add_trace(trace)
for fid,leg in zip(plotGood,gdLegend):
fig = addline(fig,fid,ppmlim,leg,lines['out'])
for fid,leg in zip(plotBad,bdLegend):
fig = addline(fig,fid,ppmlim,leg,lines['emph'])
fig = addline(fig,tgtmrs,ppmlim,'Target',lines['blk'])
plotAxesStyle(fig,ppmlim,title = 'Bad average removal summary')
# Generate report
if html is not None:
from plotly.offline import plot
from fsl_mrs.utils.preproc.reporting import figgroup, singleReport
from datetime import datetime
import os.path as op
if op.isdir(html):
filename = 'report_' + datetime.now().strftime("%Y%m%d_%H%M%S%f")[:-3]+'.html'
htmlfile=op.join(html,filename)
elif op.isdir(op.dirname(html)) and op.splitext(html)[1]=='.html':
htmlfile = html
else:
raise ValueError('Report html path must be file or directory. ')
opName = 'BadAverageRemoval'
timestr = datetime.now().strftime("%H:%M:%S")
datestr = datetime.now().strftime("%d/%m/%Y")
headerinfo = 'Report for fsl_mrs.utils.preproc.unlike.identifyUnlikeFIDs.\n'\
+ f'Generated at {timestr} on {datestr}.'
# Figures
div = plot(fig, output_type='div',include_plotlyjs='cdn')
figurelist = [figgroup(fig = div,
name= '',
foretext= f'Identification of FIDs unlike others. SD limit = {sdlimit:0.2f}',
afttext= f'')]
singleReport(htmlfile,opName,headerinfo,figurelist)
return fig
else:
return fig
def phaseCorrect_report(inFID,
outFID,
hdr,
position,
ppmlim=(2.8, 3.2),
html=None):
"""
Generate report for phaseCorrect
"""
# from matplotlib import pyplot as plt
from fsl_mrs.core import MRS
import plotly.graph_objects as go
from fsl_mrs.utils.preproc.reporting import plotStyles, plotAxesStyle
# Turn input FIDs into mrs objects
toMRSobj = lambda fid: MRS(FID=fid, header=hdr)
plotIn = toMRSobj(inFID)
plotOut = toMRSobj(outFID)
widelimit = (0, 6)
# Fetch line styles
lines, colors, _ = plotStyles()
# Make a new figure
fig = go.Figure()
# Add lines to figure
def addline(fig, mrs, lim, name, linestyle):
trace = go.Scatter(x=mrs.getAxes(ppmlim=lim),
y=np.real(mrs.getSpectrum(ppmlim=lim)),
mode='lines',
name=name,
line=linestyle)
return fig.add_trace(trace)
fig = addline(fig, plotIn, widelimit, 'Unphased', lines['in'])
fig = addline(fig, plotIn, ppmlim, 'Search region', lines['emph'])
if position is None:
# re-estimate here.
position = np.argmax(np.abs(plotIn.getSpectrum(ppmlim=ppmlim)))
axis = [plotIn.getAxes(ppmlim=ppmlim)[position]]
y_data = [np.real(plotIn.getSpectrum(ppmlim=ppmlim))[position]]
trace = go.Scatter(x=axis,
y=y_data,
mode='markers',
name='max point',
marker=dict(color=colors['emph'], symbol='x', size=8))
fig.add_trace(trace)
fig = addline(fig, plotOut, widelimit, 'Phased', lines['out'])
# Axes layout
plotAxesStyle(fig, widelimit, title='Phase correction summary')
# Axes
if html is not None:
from plotly.offline import plot
from fsl_mrs.utils.preproc.reporting import figgroup, singleReport
from datetime import datetime
import os.path as op
if op.isdir(html):
filename = 'report_' + datetime.now().strftime(
"%Y%m%d_%H%M%S%f")[:-3] + '.html'
htmlfile = op.join(html, filename)
elif op.isdir(op.dirname(html)) and op.splitext(html)[1] == '.html':
htmlfile = html
else:
raise ValueError('Report html path must be file or directory. ')
opName = 'Phase correction'
timestr = datetime.now().strftime("%H:%M:%S")
datestr = datetime.now().strftime("%d/%m/%Y")
headerinfo = 'Report for fsl_mrs.utils.preproc.phasing.phaseCorrect.\n'\
+ f'Generated at {timestr} on {datestr}.'
# Figures
div = plot(fig, output_type='div', include_plotlyjs='cdn')
figurelist = [
figgroup(
fig=div,
name='',
foretext=
f'Phase correction of spectra based on maximum in the range {ppmlim[0]} to {ppmlim[1]} ppm.',
afttext=f'')
]
singleReport(htmlfile, opName, headerinfo, figurelist)
return fig
else:
return fig
