def _rotdif(arr,
nvecs=1000,
rvecin=None,
rseed=80531,
order=2,
ncorr=-1,
tol=1E-6,
d0=0.03,
nmesh=2,
dt=0.002,
ti=0.0,
tf=-1,
itmax=-1.,
dtype='ndarray'):
'''
Parameters
----------
arr : array-like, shape (n_frames, 3, 3) or (n_frames, 9)
'''
_nvecs = 'nvecs ' + str(nvecs)
_rvecin = 'rvecin ' + rvecin if rvecin is not None else ''
_rseed = 'rseed ' + str(rseed)
_order = 'order ' + str(order)
_ncorr = 'ncorr ' + str(ncorr) if ncorr > 0 else ''
_tol = 'tol ' + str(tol)
_d0 = 'd0 ' + str(d0)
_nmesh = 'nmesh ' + str(nmesh)
_dt = 'dt ' + str(dt)
_ti = 'ti ' + str(ti)
_tf = 'tf ' + str(tf)
_itmax = 'itmax ' + str(itmax)
_rmatrix = 'rmatrix mymat'
act = CpptrajAnalyses.Analysis_Rotdif()
dslist = CpptrajDatasetList()
dslist.add_set('mat3x3', 'mymat')
arr = np.asarray(arr, dtype='f8')
msg = 'array must have shape=(n_frames, 9) or (n_frames, 3, 3)'
shape = arr.shape
if arr.ndim == 2:
assert shape[1] == 9, msg
elif arr.ndim == 3:
assert shape[1:3] == (3, 3), msg
# need to reshape to (n_frames, 9)
arr = arr.reshape(shape[0], shape[1] * shape[2])
else:
raise ValueError(msg)
def _rotdif(arr,
nvecs=1000,
rvecin=None,
rseed=80531,
order=2,
ncorr=-1,
tol=1E-6,
d0=0.03,
nmesh=2,
dt=0.002,
ti=0.0,
tf=-1,
itmax=-1.,
dtype='ndarray'):
'''
Parameters
----------
arr : array-like, shape (n_frames, 3, 3) or (n_frames, 9)
'''
_nvecs = 'nvecs ' + str(nvecs)
_rvecin = 'rvecin ' + rvecin if rvecin is not None else ''
_rseed = 'rseed ' + str(rseed)
_order = 'order ' + str(order)
_ncorr = 'ncorr ' + str(ncorr) if ncorr > 0 else ''
_tol = 'tol ' + str(tol)
_d0 = 'd0 ' + str(d0)
_nmesh = 'nmesh ' + str(nmesh)
_dt = 'dt ' + str(dt)
_ti = 'ti ' + str(ti)
_tf = 'tf ' + str(tf)
_itmax = 'itmax ' + str(itmax)
_rmatrix = 'rmatrix mymat'
act = CpptrajAnalyses.Analysis_Rotdif()
dslist = CpptrajDatasetList()
dslist.add_set('mat3x3', 'mymat')
arr = np.asarray(arr, dtype='f8')
msg = 'array must have shape=(n_frames, 9) or (n_frames, 3, 3)'
shape = arr.shape
if arr.ndim == 2:
assert shape[1] == 9, msg
elif arr.ndim == 3:
assert shape[1:3] == (3, 3), msg
# need to reshape to (n_frames, 9)
arr = arr.reshape(shape[0], shape[1] * shape[2])
else:
raise ValueError(msg)
def lifetime(data, cut=0.5, rawcurve=False, more_options='', dtype='ndarray'):
"""lifetime (adapted lightly from cpptraj doc)
Parameters
----------
data : 1D-array or 2D array-like
cut : cutoff to use when determining if data is 'present', default 0.5
more_options : str, more cpptraj's options. Check cpptraj's manual.
"""
data = np.asarray(data)
if data.ndim == 1:
data_ = [
data,
]
else:
data_ = data
_outname = 'name lifetime_'
_cut = 'cut ' + str(cut)
_rawcurve = 'rawcurve' if rawcurve else ''
# do not sorting dataset's names. We can accessing by indexing them.
_nosort = 'nosort'
namelist = []
cdslist = CpptrajDatasetList()
for idx, arr in enumerate(data_):
# create datasetname so we can reference them
name = 'data_' + str(idx)
if 'int' in arr.dtype.name:
cdslist.add_set("integer", name)
else:
cdslist.add_set("double", name)
cdslist[-1].data = np.asarray(arr)
namelist.append(name)
act = CpptrajAnalyses.Analysis_Lifetime()
_cm = ' '.join(namelist)
command = " ".join((_cm, _outname, _cut, _rawcurve, _nosort, more_options))
act(command, dslist=cdslist)
for name in namelist:
cdslist.remove_set(cdslist[name])
return get_data_from_dtype(cdslist, dtype=dtype)
def lifetime(data, cut=0.5, rawcurve=False, more_options='', dtype='ndarray'):
"""lifetime (adapted lightly from cpptraj doc)
Parameters
----------
data : 1D-array or 2D array-like
cut : cutoff to use when determining if data is 'present', default 0.5
more_options : str, more cpptraj's options. Check cpptraj's manual.
"""
data = np.asarray(data)
if data.ndim == 1:
data_ = [data, ]
else:
data_ = data
_outname = 'name lifetime_'
_cut = 'cut ' + str(cut)
_rawcurve = 'rawcurve' if rawcurve else ''
# do not sorting dataset's names. We can accessing by indexing them.
_nosort = 'nosort'
namelist = []
cdslist = CpptrajDatasetList()
for idx, arr in enumerate(data_):
# create datasetname so we can reference them
name = 'data_' + str(idx)
if 'int' in arr.dtype.name:
cdslist.add_set("integer", name)
else:
cdslist.add_set("double", name)
cdslist[-1].data = np.asarray(arr)
namelist.append(name)
act = CpptrajAnalyses.Analysis_Lifetime()
_cm = ' '.join(namelist)
command = " ".join((_cm, _outname, _cut, _rawcurve, _nosort, more_options))
act(command, dslist=cdslist)
for name in namelist:
cdslist.remove_set(cdslist[name])
return get_data_from_dtype(cdslist, dtype=dtype)
