def assemble(filepairs, dname):
dat_all = []
for fp in filepairs:
bfn = os.path.join(dname, fp[0])
afn = os.path.join(dname, fp[1])
dbin = io.read(bfn).getElements("Data")[0]
daos = io.read(afn).getElements("Data")[0]
trig= dbin.getData()[:,TRIGCHAN]
ind = argmax(trig[1:] - trig[:-1])+1
mfd = dbin.getData()[ind:,MFCHAN]
dbin.datinit(mfd, {"SampleType":"timeseries", "StartTime":0.0,
"Labels":["MicroFlownVoltage"], "SamplesPerSecond":dbin.fs()})
tsd = smooth(daos.getData(),daos.attrib("SamplesPerSecond")) #remove clicks BEFORE resampling
daos.datinit(tsd, {"SampleType":"timeseries", "StartTime":0.0,
"Labels":["HairPosition"], "SamplesPerSecond":daos.fs()})
resample(dbin, SIGFS)
resample(daos, SIGFS)
dat2 = dbin.getData()
dat1 = daos.getData()
if dat1.shape[0] < dat2.shape[0]:
dat2 = dat2[:dat1.shape[0]]
elif dat1.shape[0] > dat2.shape[0]:
dat1 = dat1[:dat2.shape[0]]
dat1 -= dat1.mean()
dat2 -= dat2.mean()
dd = column_stack([dat1, dat2])
dat_all.append(dd)
dat = row_stack(dat_all)
ds = miendata.newData(dat, {'SampleType':'timeseries', 'SamplesPerSecond':SIGFS,
'StartTime':0.0, "Labels":['HairPosition', 'MicroFlownVoltage']})
return ds
def knit(dname):
if os.path.isfile(os.path.join(dname, 'concat_ex.mdat')):
os.unlink(os.path.join(dname, 'concat_ex.mdat'))
if os.path.isfile(os.path.join(dname, 'concat.mdat')):
os.unlink(os.path.join(dname, 'concat.mdat'))
print("=== processing directory %s ===" % dname)
dat_all = []
dat_ex = []
mf_allch = []
mdat = [f for f in os.listdir(dname) if f.endswith("_ts.mdat")]
date = mdat[0][:10]
if all([f[:10] == date for f in mdat]):
if os.path.isfile(os.path.join(dname, date+'concat_ex.mdat')):
os.unlink(os.path.join(dname, date+'concat_ex.mdat'))
if os.path.isfile(os.path.join(dname, date+'concat.mdat')):
os.unlink(os.path.join(dname, date+'concat.mdat'))
else:
print "Multiple experiments present -- aborting. Put separate experiments in different folders."
return None
bin = [f for f in os.listdir(dname) if f.endswith(".bin")]
for f in mdat:
ff1=os.path.join(dname, f)
f2 = getMatch(f[:-8], bin)
if not f2:
print("can't match %s" % (f,))
continue
ff2 = os.path.join(dname, f2)
print("adding file pair %s, %s" % (f, f2))
dat1 = io.read(ff1).getElements("Data")[0]
dat2 = io.read(ff2).getElements("Data")[0]
dat2 = cropMicroflown(dat2)
# crpd = dat2.getData()
# ds = miendata.newData(crpd, {'SampleType':'timeseries', 'SamplesPerSecond':10000})
# doc = nmpml.blankDocument()
# doc.newElement(ds)
# io.write(doc, os.path.join(dname, 'crpd.mdat'))
resample(dat1, 1000)
resample(dat2, 1000)
dat1 = dat1.getData()
dat2 = dat2.getData()[:,2]
if dat1.shape[0] < dat2.shape[0]:
dat2 = dat2[:dat1.shape[0]]
elif dat1.shape[0] > dat2.shape[0]:
dat1 = dat1[:dat2.shape[0]]
dat1 -= dat1.mean()
dat2 -= dat2.mean()
dd = column_stack([dat1, dat2])
dat_all.append(dd)
if not any([q in f.lower() for q in EXCLUDE]):
dat_ex.append(dd)
dat = row_stack(dat_all)
ds = miendata.newData(dat, {'SampleType':'timeseries', 'SamplesPerSecond':1000})
doc = nmpml.blankDocument()
doc.newElement(ds)
io.write(doc, os.path.join(dname, date+'concat.mdat'))
if len(dat_ex) < len(dat_all):
dat = row_stack(dat_ex)
ds.datinit(dat)
io.write(doc, os.path.join(dname, date+'concat_ex.mdat'))
