Package pipe_control :: Module align_tensor

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Module align_tensor

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Module containing functions for the handling of alignment tensors.

Functions

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bool

align_data_exists(tensor, pipe=None)
Function for determining if alignment data exists in the current data pipe.

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bool

all_tensors_fixed()
Determine if all alignment tensors are fixed.

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copy(tensor_from=None, pipe_from=None, tensor_to=None, pipe_to=None)
Function for copying alignment tensor data from one data pipe to another.

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data_names()
Function for returning a list of names of data structures associated with the sequence.

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float

default_value(param)
Return the default values for the alignment tensor parameters.

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delete(tensor=None)
Function for deleting alignment tensor data.

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display(tensor=None)
Function for displaying the alignment tensor.

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fix(id=None, fixed=True)
Fix the alignment tensor during optimisation.

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fold_angles(sim_index=None)
Wrap the Euler angles and remove the glide reflection and translational symmetries.

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float

gdo(A)
Calculate the generalized degree of order (GDO) for the given alignment tensor.

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list of str

get_align_ids()
Return the list of all alignment IDs.

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list of str

get_tensor_ids()
Return the list of all tensor IDs.

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int

get_tensor_index(tensor=None, align_id=None, pipe=None)
Function for returning the index corresponding to the 'tensor' argument.

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AlignTensorData instance

get_tensor_object(tensor, pipe=None)
Return the AlignTensorData instance corresponding to the tensor ID.

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AlignTensorData instance

get_tensor_object_from_align(align_id, pipe=None)
Return the unique AlignTensorData instance corresponding to the alignment ID.

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init(tensor=None, align_id=None, params=None, scale=1.0, angle_units='deg', param_types=0, domain=None, errors=False)
Function for initialising the alignment tensor. source code

map_bounds(param)
The function for creating bounds for the mapping function.

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map_labels(index, params, bounds, swap, inc)
Function for creating labels, tick locations, and tick values for an OpenDX map.

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matrix_angles(basis_set=0, tensors=None)
Function for calculating the 5D angles between the alignment tensors.

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int

num_tensors(skip_fixed=True)
Count the number of tensors.

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bool

opt_uses_align_data(align_id=None)
Determine if the PCS or RDC data for the given alignment ID is needed for optimisation.

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bool

opt_uses_tensor(tensor)
Determine if the given tensor is to be optimised.

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reduction(full_tensor=None, red_tensor=None)
Specify which tensor is a reduction of which other tensor.

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float

return_conversion_factor(param)
Function for returning the factor of conversion between different parameter units.

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str

return_data_name(name)
Return the parameter name.

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data.align_tensor.AlignTensorData instance

return_tensor(index, skip_fixed=True)
Return the tensor container for the given index, skipping fixed tensors if required.

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str

return_units(param)
Function for returning a string representing the parameters units.

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set(tensor=None, value=None, param=None, errors=False)
Set the tensor.

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set_align_id(tensor=None, align_id=None)
Set the align ID string for the given tensor.

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set_domain(tensor=None, domain=None)
Set the domain label for the given tensor.

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svd(basis_set=0, tensors=None)
Function for calculating the singular values of all the loaded tensors.

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Variables

[hide private]

__default_value_prompt_doc__ = '\n Alignment tensor paramet...

__return_data_name_prompt_doc__ = '\n Alignment tensor para...

__set_prompt_doc__ = '\n Alignment tensor set details\n ...

__package__ = 'pipe_control'

Imports: deepcopy, pi, sqrt, arccos, dot, float64, linalg, zeros, norm, search, sys, warn, AlignTensorList, calc_chi_tensor, kappa, RelaxError, RelaxNoTensorError, RelaxStrError, RelaxTensorError, RelaxUnknownParamCombError, RelaxUnknownParamError, write_data, RelaxWarning, pipe_control, pipes, wrap_angles

Function Details

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align_data_exists(tensor, pipe=None)

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Function for determining if alignment data exists in the current data pipe.

Parameters:

tensor (str) - The alignment tensor identification string.
pipe (str) - The data pipe to search for data in.

Returns: bool

The answer to the question.

all_tensors_fixed()

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Determine if all alignment tensors are fixed.

Returns: bool: True if all tensors are fixed, False otherwise.

copy(tensor_from=None, pipe_from=None, tensor_to=None, pipe_to=None)

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Function for copying alignment tensor data from one data pipe to another.

Parameters:

tensor_from (str) - The identification string of the alignment tensor to copy the data from.
pipe_from (str) - The data pipe to copy the alignment tensor data from. This defaults to the current data pipe.
tensor_to (str or None) - The identification string of the alignment tensor to copy the data to. If set to None, then the ID string will be set to the value of tensor_from.
pipe_to (str) - The data pipe to copy the alignment tensor data to. This defaults to the current data pipe.

default_value(param)

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Return the default values for the alignment tensor parameters.

Parameters:

param (str) - The name of the parameter.

Returns: float

The default value, which for all parameters is set to zero.

delete(tensor=None)

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Function for deleting alignment tensor data.

Parameters:

tensor (str or None) - The alignment tensor identification string.

display(tensor=None)

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Function for displaying the alignment tensor.

Parameters:

tensor (str or None) - The alignment tensor identification string.

fix(id=None, fixed=True)

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Fix the alignment tensor during optimisation.

Parameters:

id (str or None) - The alignment tensor ID string. If set to None, then all alignment tensors will be fixed.
fixed (bool) - If True, the alignment tensor will be fixed during optimisation. If False, the alignment tensors will be optimised.

fold_angles(sim_index=None)

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Wrap the Euler angles and remove the glide reflection and translational symmetries.

Wrap the angles such that:

   0 <= alpha <= 2pi,
   0 <= beta <= pi,
   0 <= gamma <= 2pi.

For the simulated values, the angles are wrapped as:

   alpha - pi <= alpha_sim <= alpha + pi
   beta - pi/2 <= beta_sim <= beta + pi/2
   gamma - pi <= gamma_sim <= gamma + pi

Parameters:

sim_index (int or None) - The simulation index. If set to None then the actual values will be folded rather than the simulation values.

gdo(A)

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Calculate the generalized degree of order (GDO) for the given alignment tensor.

Parameters:

A (rank-2, 3D numpy array) - The alignment tensor.

Returns: float

The GDO value.

get_align_ids()

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Return the list of all alignment IDs.

Returns: list of str: The list of all alignment IDs.

get_tensor_ids()

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Return the list of all tensor IDs.

Returns: list of str: The list of all tensor IDs.

get_tensor_index(tensor=None, align_id=None, pipe=None)

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Function for returning the index corresponding to the 'tensor' argument.

Parameters:

tensor (str or None) - The alignment tensor identification string.
align_id (str or None) - Alternative to the tensor argument, used to return the tensor index for the tensors corresponding to the alignment ID string. If more than one tensor exists, then this will fail.
pipe (str) - The data pipe to search for data in.

Returns: int

The index corresponding to the 'tensor' arg.

get_tensor_object(tensor, pipe=None)

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Return the AlignTensorData instance corresponding to the tensor ID.

Parameters:

tensor (str) - The alignment tensor identification string.
pipe (str) - The data pipe to search for data in.

Returns: AlignTensorData instance

The alignment tensor object corresponding to the 'tensor' arg.

get_tensor_object_from_align(align_id, pipe=None)

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Return the unique AlignTensorData instance corresponding to the alignment ID.

Parameters:

align_id (str) - The alignment ID for the unique tensor.

Returns: AlignTensorData instance

The alignment tensor object corresponding to the 'tensor' arg.

init(tensor=None, align_id=None, params=None, scale=1.0, angle_units=`'deg'`, param_types=0, domain=None, errors=False)

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Function for initialising the alignment tensor.

Parameters:

tensor (str) - The alignment tensor identification string.
align_id (str or None) - The alignment ID string that the tensor corresponds to.
params (float) - The alignment tensor parameters.
scale (float) - The alignment tensor eigenvalue scaling value.
angle_units (str) - The units for the angle parameters (either 'deg' or 'rad').
param_types (int) - The type of parameters supplied. The flag values correspond to, 0: {Axx, Ayy, Axy, Axz, Ayz}, and 1: {Azz, Axx-yy, Axy, Axz, Ayz}.
domain (str or None) - The domain label.
errors (bool) - A flag which determines if the alignment tensor data or its errors are being input.

map_labels(index, params, bounds, swap, inc)

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Function for creating labels, tick locations, and tick values for an OpenDX map.

Parameters:

index (int) - The index (which isn't used here?!?).
params (list of str) - The list of parameter names.
bounds (list of lists (of a float and bin)) - The bounds of the map.
swap (list of int) - An array for switching axes around.
inc (list of int) - The number of increments of one dimension in the map.

matrix_angles(basis_set=0, tensors=None)

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Function for calculating the 5D angles between the alignment tensors.

The basis set used for the 5D vector construction changes the angles calculated.

Parameters:

basis_set (int) - The basis set to use for constructing the 5D vectors. If set to 0, the basis set is {Sxx, Syy, Sxy, Sxz, Syz}. If 1, then the basis set is {Szz, Sxxyy, Sxy, Sxz, Syz}.
tensors (None or array of str) - An array of tensors to apply SVD to. If None, all tensors will be used.

num_tensors(skip_fixed=True)

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Count the number of tensors.

Parameters:

skip_fixed (bool) - If set to True, then only the tensors without the fixed flag will be counted. If set to False, then all tensors will be counted.

Returns: int

The number of tensors (excluding fixed tensors by default).

opt_uses_align_data(align_id=None)

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Determine if the PCS or RDC data for the given alignment ID is needed for optimisation.

Parameters:

align_id (str) - The optional alignment ID string.

Returns: bool

True if alignment data is to be used for optimisation, False otherwise.

opt_uses_tensor(tensor)

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Determine if the given tensor is to be optimised.

Parameters:

tensor (AlignmentTensor object.) - The alignment tensor to check.

Returns: bool

True if the tensor is to be optimised, False otherwise.

reduction(full_tensor=None, red_tensor=None)

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Specify which tensor is a reduction of which other tensor.

Parameters:

full_tensor (str) - The full alignment tensor.
red_tensor (str) - The reduced alignment tensor.

return_conversion_factor(param)

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Function for returning the factor of conversion between different parameter units.

Parameters:

param (str) - The parameter name.

Returns: float

The conversion factor.

return_data_name(name)

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Return the parameter name.

Parameters:

name (str) - The name of the parameter to return the name of.

Returns: str

The parameter name.

return_tensor(index, skip_fixed=True)

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Return the tensor container for the given index, skipping fixed tensors if required.

Parameters:

index (int) - The index of the tensor (if skip_fixed is True, then fixed tensors are not included in the index count).
skip_fixed (bool) - A flag which if True will exclude fixed tensors from the indexation.

Returns: data.align_tensor.AlignTensorData instance

The tensor corresponding to the index.

return_units(param)

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Function for returning a string representing the parameters units.

Parameters:

param (str) - The parameter name.

Returns: str

The string representation of the units.

set(tensor=None, value=None, param=None, errors=False)

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Set the tensor.

Parameters:

tensor (AlignTensorData instance) - The alignment tensor object.
value (list of float) - The list of values to set the parameters to.
param (list of str) - The list of parameter names.
errors (bool) - A flag which determines if the alignment tensor data or its errors are being input.

set_align_id(tensor=None, align_id=None)

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Set the align ID string for the given tensor.

Parameters:

tensor (str) - The alignment tensor label.
align_id (str) - The alignment ID string.

set_domain(tensor=None, domain=None)

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Set the domain label for the given tensor.

Parameters:

tensor (str) - The alignment tensor label.
domain (str) - The domain label.

svd(basis_set=0, tensors=None)

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Function for calculating the singular values of all the loaded tensors.

The matrix on which SVD will be performed is:

   | Sxx1 Syy1 Sxy1 Sxz1 Syz1 |
   | Sxx2 Syy2 Sxy2 Sxz2 Syz2 |
   | Sxx3 Syy3 Sxy3 Sxz3 Syz3 |
   |  .    .    .    .    .   |
   |  .    .    .    .    .   |
   |  .    .    .    .    .   |
   | SxxN SyyN SxyN SxzN SyzN |

This is the default unitary basis set (selected when basis_set is 0). Alternatively a geometric basis set consisting of the stretching and skewing parameters Szz and Sxx-yy respectively replacing Sxx and Syy can be chosen by setting basis_set to 1. The matrix in this case is:

   | Szz1 Sxxyy1 Sxy1 Sxz1 Syz1 |
   | Szz2 Sxxyy2 Sxy2 Sxz2 Syz2 |
   | Szz3 Sxxyy3 Sxy3 Sxz3 Syz3 |
   |  .     .     .    .    .   |
   |  .     .     .    .    .   |
   |  .     .     .    .    .   |
   | SzzN SxxyyN SxyN SxzN SyzN |

The relationships between the geometric and unitary basis sets are:

   Szz = - Sxx - Syy,
   Sxxyy = Sxx - Syy,

The SVD values and condition number are dependendent upon the basis set chosen.

Parameters:

basis_set (int) - The basis set to create the 5 by n matrix on which to perform SVD.
tensors (None or array of str) - An array of tensors to apply SVD to. If None, all tensors will be used.

Variables Details

[hide private]

__default_value_prompt_doc__

Value:

'''
    Alignment tensor parameter default values
    ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

    __________________________________________________________________
______
    |                        |                    |                   
     |
...

__return_data_name_prompt_doc__

Value:

'''
    Alignment tensor parameter string matching patterns
    ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

    __________________________________________________________________
__________________________
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      |                  |
...

__set_prompt_doc__

Value:

'''
    Alignment tensor set details
    ~~~~~~~~~~~~~~~~~~~~~~~~~~~~

    If the alignment tensor has not been setup, use the more powerful 
function
    \'alignment_tensor.init\' to initialise the tensor parameters.

...

Module align_tensor

align_data_exists(tensor, pipe=None)

all_tensors_fixed()

copy(tensor_from=None, pipe_from=None, tensor_to=None, pipe_to=None)

default_value(param)

delete(tensor=None)

display(tensor=None)

fix(id=None, fixed=True)

fold_angles(sim_index=None)

gdo(A)

get_align_ids()

get_tensor_ids()

get_tensor_index(tensor=None, align_id=None, pipe=None)

get_tensor_object(tensor, pipe=None)

get_tensor_object_from_align(align_id, pipe=None)

init(tensor=None, align_id=None, params=None, scale=1.0, angle_units='deg', param_types=0, domain=None, errors=False)

map_labels(index, params, bounds, swap, inc)

matrix_angles(basis_set=0, tensors=None)

num_tensors(skip_fixed=True)

opt_uses_align_data(align_id=None)

opt_uses_tensor(tensor)

reduction(full_tensor=None, red_tensor=None)

return_conversion_factor(param)

return_data_name(name)

return_tensor(index, skip_fixed=True)

return_units(param)

set(tensor=None, value=None, param=None, errors=False)

set_align_id(tensor=None, align_id=None)

set_domain(tensor=None, domain=None)

svd(basis_set=0, tensors=None)

__default_value_prompt_doc__

__return_data_name_prompt_doc__

__set_prompt_doc__

init(tensor=None, align_id=None, params=None, scale=1.0, angle_units=`'deg'`, param_types=0, domain=None, errors=False)