def logicle(fcm,
channels,
T,
m,
r=None,
scale_max=1e5,
scale_min=0,
w=0.5,
a=0,
rquant=None):
"""return logicle transformed points in fcm data for channels listed"""
npnts = fcm.view().copy()
for i in channels:
if rquant:
w = None
tmp = npnts[:, i]
r = quantile(tmp[tmp < 0], 0.05)
if r is None and w is None:
w = 0.5
tmp = scale_max * _logicle(npnts[:, i].T, T, m, r, w, a)
#tmp[tmp<scale_min] = scale_min
npnts.T[i] = tmp
node = TransformNode('', fcm.get_cur_node(), npnts)
fcm.add_view(node)
return fcm
def log_transform(fcm, channels):
npnts = fcm.view().copy()
for i in channels:
#npnts[:,i] = where(npnts[:,i] <= 1, 0, log10(npnts[:,i]))
npnts[:, i] = _log_transform(npnts[:, i])
node = TransformNode('', fcm.get_cur_node(), npnts)
fcm.add_view(node)
return fcm
def hyperlog(fcm, channels, b, d, r, order=2, intervals=1000.0):
npnts = fcm.view().copy()
for i in channels:
npnts.T[i] = _hyperlog(npnts[:, i].T,
b,
d,
r,
order=2,
intervals=1000.0)
node = TransformNode('', fcm.get_cur_node(), npnts)
fcm.add_view(node)
return fcm