Dihedral

pytraj.analysis.dihedral_analysis.calc_phi(traj=None, resrange='', range360=False, top=None, dtype='dataset', frame_indices=None)
Parameters:

traj : Trajectory-like or anything that makes iterframe_master(traj) return Frame

resrange : string or iterable, cpptraj resrange, default “”

if resrange is a string, use index of 1-based if resrange is a python sequence (range, list, array, ...),

use index of 0-based

range360 : bool, default False

use -180/180 or 0/360

top : {str, Topology}, optional, default None

frame_indices : {None, 1D array-like}, default None

if not None, only compute for given indices

Examples

>>> import pytraj.dihedral_ as da
>>> da.calc_phi(traj)
>>> da.calc_psi(traj, resrange="3-10")
>>> da.calc_chip(traj, resrange="3-10")
>>> da.calc_chip(traj, resrange="3-10", range360=True)
>>> da.calc_chip(traj, resrange="3-10", dtype='dict')
>>> da.calc_multidihedral(traj, resrange="3-10")
>>> da.calc_multidihedral(traj, resrange=range(5, 10))
>>> # assert
>>> from pytraj import all_actions as pyca
>>> phi0 = pyca.calc_multidihedral(traj, "phi", dtype='dataset')
>>> phi1 = da.calc_phi(traj, dtype='dataset')
>>> from pytraj.testing import aa_eq
>>> for key in phi0.keys():
>>>     aa_eq(phi0[key], phi1[key])
pytraj.analysis.dihedral_analysis.calc_psi(traj=None, resrange='', range360=False, top=None, dtype='dataset', frame_indices=None)
Parameters:

traj : Trajectory-like or anything that makes iterframe_master(traj) return Frame

resrange : string or iterable, cpptraj resrange, default “”

if resrange is a string, use index of 1-based if resrange is a python sequence (range, list, array, ...),

use index of 0-based

range360 : bool, default False

use -180/180 or 0/360

top : {str, Topology}, optional, default None

frame_indices : {None, 1D array-like}, default None

if not None, only compute for given indices

Examples

>>> import pytraj.dihedral_ as da
>>> da.calc_phi(traj)
>>> da.calc_psi(traj, resrange="3-10")
>>> da.calc_chip(traj, resrange="3-10")
>>> da.calc_chip(traj, resrange="3-10", range360=True)
>>> da.calc_chip(traj, resrange="3-10", dtype='dict')
>>> da.calc_multidihedral(traj, resrange="3-10")
>>> da.calc_multidihedral(traj, resrange=range(5, 10))
>>> # assert
>>> from pytraj import all_actions as pyca
>>> phi0 = pyca.calc_multidihedral(traj, "phi", dtype='dataset')
>>> phi1 = da.calc_phi(traj, dtype='dataset')
>>> from pytraj.testing import aa_eq
>>> for key in phi0.keys():
>>>     aa_eq(phi0[key], phi1[key])
pytraj.analysis.dihedral_analysis.calc_chip(traj=None, resrange='', range360=False, top=None, dtype='dataset', frame_indices=None)
Parameters:

traj : Trajectory-like or anything that makes iterframe_master(traj) return Frame

resrange : string or iterable, cpptraj resrange, default “”

if resrange is a string, use index of 1-based if resrange is a python sequence (range, list, array, ...),

use index of 0-based

range360 : bool, default False

use -180/180 or 0/360

top : {str, Topology}, optional, default None

frame_indices : {None, 1D array-like}, default None

if not None, only compute for given indices

Examples

>>> import pytraj.dihedral_ as da
>>> da.calc_phi(traj)
>>> da.calc_psi(traj, resrange="3-10")
>>> da.calc_chip(traj, resrange="3-10")
>>> da.calc_chip(traj, resrange="3-10", range360=True)
>>> da.calc_chip(traj, resrange="3-10", dtype='dict')
>>> da.calc_multidihedral(traj, resrange="3-10")
>>> da.calc_multidihedral(traj, resrange=range(5, 10))
>>> # assert
>>> from pytraj import all_actions as pyca
>>> phi0 = pyca.calc_multidihedral(traj, "phi", dtype='dataset')
>>> phi1 = da.calc_phi(traj, dtype='dataset')
>>> from pytraj.testing import aa_eq
>>> for key in phi0.keys():
>>>     aa_eq(phi0[key], phi1[key])
pytraj.analysis.dihedral_analysis.calc_omega(traj=None, resrange='', range360=False, top=None, dtype='dataset', frame_indices=None)
Parameters:

traj : Trajectory-like or anything that makes iterframe_master(traj) return Frame

resrange : string or iterable, cpptraj resrange, default “”

if resrange is a string, use index of 1-based if resrange is a python sequence (range, list, array, ...),

use index of 0-based

range360 : bool, default False

use -180/180 or 0/360

top : {str, Topology}, optional, default None

frame_indices : {None, 1D array-like}, default None

if not None, only compute for given indices

Examples

>>> import pytraj.dihedral_ as da
>>> da.calc_phi(traj)
>>> da.calc_psi(traj, resrange="3-10")
>>> da.calc_chip(traj, resrange="3-10")
>>> da.calc_chip(traj, resrange="3-10", range360=True)
>>> da.calc_chip(traj, resrange="3-10", dtype='dict')
>>> da.calc_multidihedral(traj, resrange="3-10")
>>> da.calc_multidihedral(traj, resrange=range(5, 10))
>>> # assert
>>> from pytraj import all_actions as pyca
>>> phi0 = pyca.calc_multidihedral(traj, "phi", dtype='dataset')
>>> phi1 = da.calc_phi(traj, dtype='dataset')
>>> from pytraj.testing import aa_eq
>>> for key in phi0.keys():
>>>     aa_eq(phi0[key], phi1[key])
pytraj.analysis.dihedral_analysis.calc_alpha(traj=None, resrange='', range360=False, top=None, dtype='dataset', frame_indices=None)
Parameters:

traj : Trajectory-like or anything that makes iterframe_master(traj) return Frame

resrange : string or iterable, cpptraj resrange, default “”

if resrange is a string, use index of 1-based if resrange is a python sequence (range, list, array, ...),

use index of 0-based

range360 : bool, default False

use -180/180 or 0/360

top : {str, Topology}, optional, default None

frame_indices : {None, 1D array-like}, default None

if not None, only compute for given indices

Examples

>>> import pytraj.dihedral_ as da
>>> da.calc_phi(traj)
>>> da.calc_psi(traj, resrange="3-10")
>>> da.calc_chip(traj, resrange="3-10")
>>> da.calc_chip(traj, resrange="3-10", range360=True)
>>> da.calc_chip(traj, resrange="3-10", dtype='dict')
>>> da.calc_multidihedral(traj, resrange="3-10")
>>> da.calc_multidihedral(traj, resrange=range(5, 10))
>>> # assert
>>> from pytraj import all_actions as pyca
>>> phi0 = pyca.calc_multidihedral(traj, "phi", dtype='dataset')
>>> phi1 = da.calc_phi(traj, dtype='dataset')
>>> from pytraj.testing import aa_eq
>>> for key in phi0.keys():
>>>     aa_eq(phi0[key], phi1[key])
pytraj.analysis.dihedral_analysis.calc_beta(traj=None, resrange='', range360=False, top=None, dtype='dataset', frame_indices=None)
Parameters:

traj : Trajectory-like or anything that makes iterframe_master(traj) return Frame

resrange : string or iterable, cpptraj resrange, default “”

if resrange is a string, use index of 1-based if resrange is a python sequence (range, list, array, ...),

use index of 0-based

range360 : bool, default False

use -180/180 or 0/360

top : {str, Topology}, optional, default None

frame_indices : {None, 1D array-like}, default None

if not None, only compute for given indices

Examples

>>> import pytraj.dihedral_ as da
>>> da.calc_phi(traj)
>>> da.calc_psi(traj, resrange="3-10")
>>> da.calc_chip(traj, resrange="3-10")
>>> da.calc_chip(traj, resrange="3-10", range360=True)
>>> da.calc_chip(traj, resrange="3-10", dtype='dict')
>>> da.calc_multidihedral(traj, resrange="3-10")
>>> da.calc_multidihedral(traj, resrange=range(5, 10))
>>> # assert
>>> from pytraj import all_actions as pyca
>>> phi0 = pyca.calc_multidihedral(traj, "phi", dtype='dataset')
>>> phi1 = da.calc_phi(traj, dtype='dataset')
>>> from pytraj.testing import aa_eq
>>> for key in phi0.keys():
>>>     aa_eq(phi0[key], phi1[key])
pytraj.analysis.dihedral_analysis.calc_gamma(traj=None, resrange='', range360=False, top=None, dtype='dataset', frame_indices=None)
Parameters:

traj : Trajectory-like or anything that makes iterframe_master(traj) return Frame

resrange : string or iterable, cpptraj resrange, default “”

if resrange is a string, use index of 1-based if resrange is a python sequence (range, list, array, ...),

use index of 0-based

range360 : bool, default False

use -180/180 or 0/360

top : {str, Topology}, optional, default None

frame_indices : {None, 1D array-like}, default None

if not None, only compute for given indices

Examples

>>> import pytraj.dihedral_ as da
>>> da.calc_phi(traj)
>>> da.calc_psi(traj, resrange="3-10")
>>> da.calc_chip(traj, resrange="3-10")
>>> da.calc_chip(traj, resrange="3-10", range360=True)
>>> da.calc_chip(traj, resrange="3-10", dtype='dict')
>>> da.calc_multidihedral(traj, resrange="3-10")
>>> da.calc_multidihedral(traj, resrange=range(5, 10))
>>> # assert
>>> from pytraj import all_actions as pyca
>>> phi0 = pyca.calc_multidihedral(traj, "phi", dtype='dataset')
>>> phi1 = da.calc_phi(traj, dtype='dataset')
>>> from pytraj.testing import aa_eq
>>> for key in phi0.keys():
>>>     aa_eq(phi0[key], phi1[key])
pytraj.analysis.dihedral_analysis.calc_delta(traj=None, resrange='', range360=False, top=None, dtype='dataset', frame_indices=None)
Parameters:

traj : Trajectory-like or anything that makes iterframe_master(traj) return Frame

resrange : string or iterable, cpptraj resrange, default “”

if resrange is a string, use index of 1-based if resrange is a python sequence (range, list, array, ...),

use index of 0-based

range360 : bool, default False

use -180/180 or 0/360

top : {str, Topology}, optional, default None

frame_indices : {None, 1D array-like}, default None

if not None, only compute for given indices

Examples

>>> import pytraj.dihedral_ as da
>>> da.calc_phi(traj)
>>> da.calc_psi(traj, resrange="3-10")
>>> da.calc_chip(traj, resrange="3-10")
>>> da.calc_chip(traj, resrange="3-10", range360=True)
>>> da.calc_chip(traj, resrange="3-10", dtype='dict')
>>> da.calc_multidihedral(traj, resrange="3-10")
>>> da.calc_multidihedral(traj, resrange=range(5, 10))
>>> # assert
>>> from pytraj import all_actions as pyca
>>> phi0 = pyca.calc_multidihedral(traj, "phi", dtype='dataset')
>>> phi1 = da.calc_phi(traj, dtype='dataset')
>>> from pytraj.testing import aa_eq
>>> for key in phi0.keys():
>>>     aa_eq(phi0[key], phi1[key])
pytraj.analysis.dihedral_analysis.calc_epsilon(traj=None, resrange='', range360=False, top=None, dtype='dataset', frame_indices=None)
Parameters:

traj : Trajectory-like or anything that makes iterframe_master(traj) return Frame

resrange : string or iterable, cpptraj resrange, default “”

if resrange is a string, use index of 1-based if resrange is a python sequence (range, list, array, ...),

use index of 0-based

range360 : bool, default False

use -180/180 or 0/360

top : {str, Topology}, optional, default None

frame_indices : {None, 1D array-like}, default None

if not None, only compute for given indices

Examples

>>> import pytraj.dihedral_ as da
>>> da.calc_phi(traj)
>>> da.calc_psi(traj, resrange="3-10")
>>> da.calc_chip(traj, resrange="3-10")
>>> da.calc_chip(traj, resrange="3-10", range360=True)
>>> da.calc_chip(traj, resrange="3-10", dtype='dict')
>>> da.calc_multidihedral(traj, resrange="3-10")
>>> da.calc_multidihedral(traj, resrange=range(5, 10))
>>> # assert
>>> from pytraj import all_actions as pyca
>>> phi0 = pyca.calc_multidihedral(traj, "phi", dtype='dataset')
>>> phi1 = da.calc_phi(traj, dtype='dataset')
>>> from pytraj.testing import aa_eq
>>> for key in phi0.keys():
>>>     aa_eq(phi0[key], phi1[key])
pytraj.analysis.dihedral_analysis.calc_zeta(traj=None, resrange='', range360=False, top=None, dtype='dataset', frame_indices=None)
Parameters:

traj : Trajectory-like or anything that makes iterframe_master(traj) return Frame

resrange : string or iterable, cpptraj resrange, default “”

if resrange is a string, use index of 1-based if resrange is a python sequence (range, list, array, ...),

use index of 0-based

range360 : bool, default False

use -180/180 or 0/360

top : {str, Topology}, optional, default None

frame_indices : {None, 1D array-like}, default None

if not None, only compute for given indices

Examples

>>> import pytraj.dihedral_ as da
>>> da.calc_phi(traj)
>>> da.calc_psi(traj, resrange="3-10")
>>> da.calc_chip(traj, resrange="3-10")
>>> da.calc_chip(traj, resrange="3-10", range360=True)
>>> da.calc_chip(traj, resrange="3-10", dtype='dict')
>>> da.calc_multidihedral(traj, resrange="3-10")
>>> da.calc_multidihedral(traj, resrange=range(5, 10))
>>> # assert
>>> from pytraj import all_actions as pyca
>>> phi0 = pyca.calc_multidihedral(traj, "phi", dtype='dataset')
>>> phi1 = da.calc_phi(traj, dtype='dataset')
>>> from pytraj.testing import aa_eq
>>> for key in phi0.keys():
>>>     aa_eq(phi0[key], phi1[key])
pytraj.analysis.dihedral_analysis.calc_nu1(traj=None, resrange='', range360=False, top=None, dtype='dataset', frame_indices=None)
Parameters:

traj : Trajectory-like or anything that makes iterframe_master(traj) return Frame

resrange : string or iterable, cpptraj resrange, default “”

if resrange is a string, use index of 1-based if resrange is a python sequence (range, list, array, ...),

use index of 0-based

range360 : bool, default False

use -180/180 or 0/360

top : {str, Topology}, optional, default None

frame_indices : {None, 1D array-like}, default None

if not None, only compute for given indices

Examples

>>> import pytraj.dihedral_ as da
>>> da.calc_phi(traj)
>>> da.calc_psi(traj, resrange="3-10")
>>> da.calc_chip(traj, resrange="3-10")
>>> da.calc_chip(traj, resrange="3-10", range360=True)
>>> da.calc_chip(traj, resrange="3-10", dtype='dict')
>>> da.calc_multidihedral(traj, resrange="3-10")
>>> da.calc_multidihedral(traj, resrange=range(5, 10))
>>> # assert
>>> from pytraj import all_actions as pyca
>>> phi0 = pyca.calc_multidihedral(traj, "phi", dtype='dataset')
>>> phi1 = da.calc_phi(traj, dtype='dataset')
>>> from pytraj.testing import aa_eq
>>> for key in phi0.keys():
>>>     aa_eq(phi0[key], phi1[key])
pytraj.analysis.dihedral_analysis.calc_nu2(traj=None, resrange='', range360=False, top=None, dtype='dataset', frame_indices=None)
Parameters:

traj : Trajectory-like or anything that makes iterframe_master(traj) return Frame

resrange : string or iterable, cpptraj resrange, default “”

if resrange is a string, use index of 1-based if resrange is a python sequence (range, list, array, ...),

use index of 0-based

range360 : bool, default False

use -180/180 or 0/360

top : {str, Topology}, optional, default None

frame_indices : {None, 1D array-like}, default None

if not None, only compute for given indices

Examples

>>> import pytraj.dihedral_ as da
>>> da.calc_phi(traj)
>>> da.calc_psi(traj, resrange="3-10")
>>> da.calc_chip(traj, resrange="3-10")
>>> da.calc_chip(traj, resrange="3-10", range360=True)
>>> da.calc_chip(traj, resrange="3-10", dtype='dict')
>>> da.calc_multidihedral(traj, resrange="3-10")
>>> da.calc_multidihedral(traj, resrange=range(5, 10))
>>> # assert
>>> from pytraj import all_actions as pyca
>>> phi0 = pyca.calc_multidihedral(traj, "phi", dtype='dataset')
>>> phi1 = da.calc_phi(traj, dtype='dataset')
>>> from pytraj.testing import aa_eq
>>> for key in phi0.keys():
>>>     aa_eq(phi0[key], phi1[key])
pytraj.analysis.dihedral_analysis.calc_chin(traj=None, resrange='', range360=False, top=None, dtype='dataset', frame_indices=None)
Parameters:

traj : Trajectory-like or anything that makes iterframe_master(traj) return Frame

resrange : string or iterable, cpptraj resrange, default “”

if resrange is a string, use index of 1-based if resrange is a python sequence (range, list, array, ...),

use index of 0-based

range360 : bool, default False

use -180/180 or 0/360

top : {str, Topology}, optional, default None

frame_indices : {None, 1D array-like}, default None

if not None, only compute for given indices

Examples

>>> import pytraj.dihedral_ as da
>>> da.calc_phi(traj)
>>> da.calc_psi(traj, resrange="3-10")
>>> da.calc_chip(traj, resrange="3-10")
>>> da.calc_chip(traj, resrange="3-10", range360=True)
>>> da.calc_chip(traj, resrange="3-10", dtype='dict')
>>> da.calc_multidihedral(traj, resrange="3-10")
>>> da.calc_multidihedral(traj, resrange=range(5, 10))
>>> # assert
>>> from pytraj import all_actions as pyca
>>> phi0 = pyca.calc_multidihedral(traj, "phi", dtype='dataset')
>>> phi1 = da.calc_phi(traj, dtype='dataset')
>>> from pytraj.testing import aa_eq
>>> for key in phi0.keys():
>>>     aa_eq(phi0[key], phi1[key])