def test2(self):
sol = [[(2, 3), (1.6, 2.7)], [(4, 5, 6), (0.1, 0.2, 0.1)]]
test = [([2, 3], [1.6, 2.7]), ([4, 5, 5, 6], [.1, .1, .1, .1])]
res = ctmc.datacorrection(test)
npt.assert_allclose(flatten(res), flatten(sol))
def test6(self):
sol = [[(4, 6), (0.1, 0.1)]]
test = [([4, 5, 6], [.1, .0, .1]), ([7, 8, 9], [.1, .0, .0])]
res = ctmc.datacorrection(test)
npt.assert_allclose(flatten(res), flatten(sol))
def test1(self):
sol = [[(2, 3), (1.6, 2.7)]]
test = [([1], [0.5]), ([2, 3], [1.6, 2.7])]
res = ctmc.datacorrection(test)
# npt.assert_allclose(res, sol)
npt.assert_allclose(flatten(res), flatten(sol))
def panelctmc(
paneldata: np.ndarray,
mapping: list,
lastdate: datetime = None,
transintv: float = 1.0,
toltime: float = 1e-8,
debug: bool = True
) -> (np.ndarray, np.ndarray, np.ndarray, np.ndarray, list):
# check if numpy array
if not isinstance(paneldata, np.ndarray):
raise Exception("'paneldata' is not a numpy array")
# force dtype=object
paneldata = paneldata.astype(dtype=object)
# convert str to datetime objects
if isinstance(paneldata[:, 1][0], str):
paneldata[:, 1] = [
datetime.strptime(p, "%Y-%m-%d") for p in paneldata[:, 1]
]
# encode state labels
paneldata[:, 2] = grouplabelencode(paneldata[:, 2], mapping, nastate=True)
# convert panel data to ctmc-datalist object
datalist = panel_to_datalist(paneldata, lastdate=lastdate)
# auto correct datalist
datalist = datacorrection(datalist)
# Compute transitition matrix
transmat, genmat, transcount, statetime = ctmc(datalist,
len(mapping) + 1,
transintv=transintv,
toltime=toltime,
debug=debug)
# done
return transmat, genmat, transcount, statetime, datalist