def temporalPlotSingleEmg(cls):
# ----DATA-----
DATA_PATH = pyCGM2.TEST_DATA_PATH + "EMG\\SampleNantes\\"
gaitTrial = "gait.c3d"
restTrial = "repos.c3d"
EMG_LABELS = ['EMG1']
acq = btkTools.smartReader(DATA_PATH + gaitTrial)
bf = emgFilters.BasicEmgProcessingFilter(acq, EMG_LABELS)
bf.setHighPassFrequencies(20.0, 200.0)
bf.run()
btkTools.smartWriter(acq, "testBasicPlot.c3d")
trial = trialTools.smartTrialReader(None, "testBasicPlot.c3d")
fig = plt.figure()
ax = plt.gca()
plot.temporalPlot(ax,
trial,
"EMG1_Rectify",
0,
color="blue",
title="test",
xlabel="frame",
ylabel="emg",
ylim=None,
legendLabel=None,
customLimits=None)
plot.addTemporalNormalActivationLayer(ax, trial, "RECFEM", "Left")
plt.show()
def test_temporalPlotSingleEmg(self):
# ----DATA-----
DATA_PATH = pyCGM2.TEST_DATA_PATH+"GaitData\\EMG\\Hånnibøl Lecter-nerve block\\"
gaitTrial = "PRE-gait trial 01.c3d"
restTrial = "PRE-repos.c3d"
DATA_PATH_OUT = pyCGM2.TEST_DATA_PATH_OUT+"GaitData\\EMG\\Hånnibøl Lecter-nerve block\\"
files.createDir(DATA_PATH_OUT)
EMG_LABELS=['EMG1']
acq = btkTools.smartReader(DATA_PATH +gaitTrial)
bf = emgFilters.BasicEmgProcessingFilter(acq,EMG_LABELS)
bf.setHighPassFrequencies(20.0,200.0)
bf.run()
btkTools.smartWriter(acq,DATA_PATH_OUT+"test_temporalPlotSingleEmg.c3d")
trial =trialTools.smartTrialReader(DATA_PATH_OUT,"test_temporalPlotSingleEmg.c3d")
fig = plt.figure()
ax = plt.gca()
plot.temporalPlot(ax,trial,"EMG1_Rectify",0,
color="blue",
title="test", xlabel="frame", ylabel="emg",ylim=None,legendLabel=None,
customLimits=None)
plot.addTemporalNormalActivationLayer(ax,trial,"RECFEM","Left")
def __setData(self):
#suffixPlus = "_" + self.m_pointLabelSuffix if self.m_pointLabelSuffix!="" else ""
for i in range(0, len(self.emgs)):
label = self.emgs[i]["Label"]+"_Rectify" if self.rectify else self.emgs[i]["Label"]+"_HPF"
context = self.emgs[i]["Context"]
colorContext = plotUtils.colorContext(context)
normalActivationLabel = self.m_normalActivEmgs[i]
plot.temporalPlot(self.fig.axes[i],self.m_trial,
label,0,
color=colorContext)
plot.addTemporalNormalActivationLayer(self.fig.axes[i],self.m_trial,self.m_normalActivEmgs[i],context)