Module optimisation
source code
Module for the optimisation of the relaxation dispersion models.
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numpy rank-1 float array
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back_calc_r2eff(spin=None,
spin_id=None,
cpmg_frqs=None,
spin_lock_nu1=None,
store_chi2=False)
Back-calculation of R2eff/R1rho values for the given spin. |
source code
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(int, list of lists [int, float, float])
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grid_search_setup(spins=None,
spin_ids=None,
param_vector=None,
lower=None,
upper=None,
inc=None,
scaling_matrix=None)
The grid search setup function. |
source code
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__package__ = 'specific_analyses.relax_disp' |
Imports:
generic_minimise,
grid,
dot,
float64,
int32,
ones,
zeros,
inv,
search,
sys,
is_float,
RelaxError,
subsection,
Memo,
Result_command,
Slave_command,
count_spins,
has_disp_data,
has_proton_mmq_cpmg,
loop_exp,
loop_exp_frq,
loop_exp_frq_offset_point,
loop_frq,
loop_offset,
pack_back_calc_r2eff,
return_cpmg_frqs,
return_index_from_disp_point,
return_index_from_exp_type,
return_index_from_frq,
return_offset_data,
return_param_key_from_data,
return_r1_data,
return_r2eff_arrays,
return_spin_lock_nu1,
return_value_from_frq_index,
assemble_param_vector,
assemble_scaling_matrix,
disassemble_param_vector,
linear_constraints,
loop_parameters,
param_conversion,
param_num,
EXP_TYPE_CPMG_PROTON_MQ,
EXP_TYPE_CPMG_PROTON_SQ,
EXP_TYPE_LIST_CPMG,
MODEL_CR72,
MODEL_CR72_FULL,
MODEL_DPL94,
MODEL_LIST_MMQ,
MODEL_LM63,
MODEL_M61,
MODEL_M61B,
MODEL_MP05,
MODEL_NS_R1RHO_2SITE,
MODEL_TAP03,
MODEL_TP02,
Dispersion
back_calc_r2eff(spin=None,
spin_id=None,
cpmg_frqs=None,
spin_lock_nu1=None,
store_chi2=False)
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Back-calculation of R2eff/R1rho values for the given spin.
- Parameters:
spin (SpinContainer instance) - The specific spin data container.spin_id (str) - The spin ID string for the spin container.cpmg_frqs (list of lists of numpy rank-1 float arrays) - The CPMG frequencies to use instead of the user loaded values -
to enable interpolation.spin_lock_nu1 (list of lists of numpy rank-1 float arrays) - The spin-lock field strengths to use instead of the user loaded
values - to enable interpolation.store_chi2 (bool) - A flag which if True will cause the spin specific chi-squared
value to be stored in the spin container. - Returns: numpy rank-1 float array
- The back-calculated R2eff/R1rho value for the given spin.
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grid_search_setup(spins=None,
spin_ids=None,
param_vector=None,
lower=None,
upper=None,
inc=None,
scaling_matrix=None)
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The grid search setup function.
- Parameters:
spins (list of SpinContainer instances) - The list of spin data containers for the block.spin_ids (list of str) - The corresponding spin ID strings.param_vector (numpy array) - The parameter vector.lower (array of numbers) - The lower bounds of the grid search which must be equal to the
number of parameters in the model. This optional argument is
only used when doing a grid search.upper (array of numbers) - The upper bounds of the grid search which must be equal to the
number of parameters in the model. This optional argument is
only used when doing a grid search.inc (array of int) - The increments for each dimension of the space for the grid
search. The number of elements in the array must equal to the
number of parameters in the model. This argument is only used
when doing a grid search.scaling_matrix (numpy diagonal matrix) - The scaling matrix. - Returns: (int, list of lists [int, float, float])
- A tuple of the grid size and the minimisation options. For the
minimisation options, the first dimension corresponds to the
model parameter. The second dimension is a list of the number of
increments, the lower bound, and upper bound.
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