def getSinTF(dname):
dp = getDataPairs(dname)
for exp in dp:
dpl = dp[exp]
print "Analyzing Sin Data for experiment %s" % exp
dpl = [p for p in dpl if p[0][10]=='S' and not p[0][11]=='T']
ds = assemble(dpl, dname)
dat = ds.getData()
dat[:,1] = cal._applyfilter(dat[:,1], MFF)
# dat[:,0] = smooth(dat[:,0]) #This now occurs in assemble BEFORE resampling
ds.datinit(dat, {"SampleType":"timeseries", "StartTime":0.0,
"Labels":["HairPosition","MicroFlownVelocity"], "SamplesPerSecond":SIGFS})
nfn = '%s_compositSinData.mdat' % exp
io.write(ds, nfn, newdoc=True)
tfds = ctf.tffmax(ds, False)
if not tfds:
continue
tfds.data[:,2]+=pi
tfds.data[:,2] = smoothphase(tfds.data[:,2])
io.write(tfds, "%s_SinTF_Function.mdat" % exp, newdoc=True)
tf = tfds.getData()
tf = row_stack( [array([[0,0,0]]), tf, array([[250,tf[-1,1],tf[-1,2]]])])
tf = ctf.uniformsample(tf, 1.0)
tfds = miendata.newData(tf, {'Name':exp+"SinTF", 'SampleType':'timeseries', 'SamplesPerSecond':1.0, "StartTime":0})
io.write(tfds, "%s_SinTF_ResampledTimeseries.mdat" % exp, newdoc=True)
def getWNTF(dname):
dp = getDataPairs(dname)
for exp in dp:
dpl = dp[exp]
print "Analyzing all data (using FT) for experiment %s" % exp
ds = assemble(dpl, dname)
dat = ds.getData()
dat[:,1] = cal._applyfilter(dat[:,1], MFF)
# dat[:,0] = smooth(dat[:,0]) #This now occurs in assemble BEFORE resampling
ds.datinit(dat, {"SampleType":"timeseries", "StartTime":0.0,
"Labels":["HairPosition","MicroFlownVelocity"], "SamplesPerSecond":SIGFS})
nfn = '%s_compositData.mdat' % exp
io.write(ds, nfn, newdoc=True)
tfds = ctf.tf1ft(ds)
if not tfds:
continue
tfds.data[:,1]+=pi
tfds.data[:,1] = smoothphase(tfds.data[:,1])
io.write(tfds, "%s_FTTF.mdat" % exp, newdoc=True)
def process(doc, filt):
ds = doc.getElements("Data", depth=1)[0]
dat = ds.getData()
dat[:,1] = cal._applyfilter(dat[:,1], filt)
dat[:,0] = smooth(dat[:,0])
