##### https://github.com/maartenpaul/DBD_tracking

Tip revision:

**36f032f51402940b51db3b5835153ca6552ce15b**authored by**Maarten Paul**on**07 March 2022, 11:26:44 UTC****Update README.md** Tip revision:

**36f032f** make_table.py

```
x0, y0, x1, y1, x2, y2, trnums0, trnums1, trnums2 = getTrackPiecesForInfo(x, y, allStates)
numPmsd = 4
numPmss = 4
minLen = 10
p = np.linspace(0.5, 6, 12)
info = []
i = 0
for xx, yy, tn in zip(x0 + x1 + x2, y0 + y1 + y2, trnums0 + trnums1 + trnums2):
lx = len(xx)
st = 0 + (i >= len(x0)) * 1 + (i >= len(x0 + x1)) * 1
closest = min(indices, key = lambda x:abs(x-int(np.floor(tn))))
cn = ((closest - int(np.floor(tn))) < 0) * indices.index(closest) + \
((closest - int(np.floor(tn))) > 0) * (indices.index(closest) - 1)
if len(xx) > max(numPmsd, numPmss, minLen):
dif, _, smss, _ = getMSDandMSS([xx], [yy], numPmsd, numPmss, p)
else:
dif = 'NA'
smss = 'NA'
info.append([st, cn, tn, lx, dif, smss])
i = i +1
colSt = [i[0] for i in info]
colCn = [i[1] for i in info]
colTn = [i[2] for i in info]
colLx = [i[3] for i in info]
colDi = [i[4] for i in info]
colSm = [i[5] for i in info]
df = pd.DataFrame({'State' : colSt, \
'Cell number' : colCn, \
'Track number': colTn, \
'Tracklet length': colLx, \
'Diffusion constant': colDi, \
'Smss': colSm})
dfSorted = df.sort_values(by=['Track number'])
dfSorted.columns.names = ['Tracklet number']
```