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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numpy rank-1 float array
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back_calc_r2eff(spins=None,
spin_ids=None,
cpmg_frqs=None,
spin_lock_offset=None,
spin_lock_nu1=None,
relax_times_new=None,
store_chi2=False)
Back-calculation of R2eff/R1rho values for the given spin. |
source code
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calculate_r2eff()
Calculate the R2eff values for fixed relaxation time period data. |
source code
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minimise_r2eff(spins=None,
spin_ids=None,
min_algor=None,
min_options=None,
func_tol=None,
grad_tol=None,
max_iterations=None,
constraints=False,
scaling_matrix=None,
verbosity=0,
sim_index=None,
lower=None,
upper=None,
inc=None)
Optimise the R2eff model by fitting the 2-parameter exponential
curves. |
source code
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__package__ = 'specific_analyses.relax_disp' |
Imports:
generic_minimise,
grid,
dot,
float64,
int32,
ones,
zeros,
inv,
mul,
match,
search,
sys,
warn,
C_module_exp_fn,
calc_two_point_r2eff,
calc_two_point_r2eff_err,
EXP_TYPE_LIST_CPMG,
MODEL_CR72,
MODEL_CR72_FULL,
MODEL_LM63,
MODEL_M61,
MODEL_MP05,
MODEL_TAP03,
MODEL_TP02,
RelaxError,
subsection,
RelaxWarning,
Memo,
Result_command,
Slave_command,
generate_spin_string,
spin_loop,
check_disp_points,
check_exp_type,
check_exp_type_fixed_time,
average_intensity,
count_spins,
find_intensity_keys,
has_exponential_exp_type,
has_proton_mmq_cpmg,
is_r1_optimised,
loop_exp,
loop_exp_frq_offset_point,
loop_exp_frq_offset_point_time,
loop_frq,
loop_offset,
loop_time,
pack_back_calc_r2eff,
return_cpmg_frqs,
return_offset_data,
return_param_key_from_data,
return_r1_data,
return_r2eff_arrays,
return_spin_lock_nu1,
assemble_param_vector,
disassemble_param_vector,
linear_constraints,
param_conversion,
param_num,
r1_setup,
Dispersion,
Relax_fit_opt
back_calc_peak_intensities(spin=None,
spin_id=None,
exp_type=None,
frq=None,
offset=None,
point=None)
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Back-calculation of peak intensity for the given relaxation time.
- Parameters:
spin (SpinContainer instance) - The specific spin data container.spin_id (str or None) - The optional spin ID string for use in warning messages.exp_type (str) - The experiment type.frq (float) - The spectrometer frequency.offset (None or float) - For R1rho-type data, the spin-lock offset value in ppm.point (float) - The dispersion point data (either the spin-lock field strength in
Hz or the nu_CPMG frequency in Hz). - Returns: numpy rank-1 float array
- The back-calculated peak intensities for the given exponential
curve.
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back_calc_r2eff(spins=None,
spin_ids=None,
cpmg_frqs=None,
spin_lock_offset=None,
spin_lock_nu1=None,
relax_times_new=None,
store_chi2=False)
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Back-calculation of R2eff/R1rho values for the given spin.
- Parameters:
spins (List of SpinContainer instances) - The list of specific spin data container for cluster.spin_ids (list of str) - The list of spin ID strings for the spin containers in cluster.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_offset (list of lists of numpy rank-1 float arrays) - The spin-lock offsets 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.relax_times_new (rank-4 list of floats) - The interpolated experiment specific fixed time period for
relaxation (in seconds). The dimensions are {Ei, Mi, Oi, Di,
Ti}.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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minimise_r2eff(spins=None,
spin_ids=None,
min_algor=None,
min_options=None,
func_tol=None,
grad_tol=None,
max_iterations=None,
constraints=False,
scaling_matrix=None,
verbosity=0,
sim_index=None,
lower=None,
upper=None,
inc=None)
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Optimise the R2eff model by fitting the 2-parameter exponential
curves.
This mimics the R1 and R2 relax_fit analysis.
- Parameters:
spins (list of SpinContainer instances) - The list of spins for the cluster.spin_ids (list of str) - The list of spin IDs for the cluster.min_algor (str) - The minimisation algorithm to use.min_options (array of str) - An array of options to be used by the minimisation algorithm.func_tol (None or float) - The function tolerance which, when reached, terminates
optimisation. Setting this to None turns of the check.grad_tol (None or float) - The gradient tolerance which, when reached, terminates
optimisation. Setting this to None turns of the check.max_iterations (int) - The maximum number of iterations for the algorithm.constraints (bool) - If True, constraints are used during optimisation.scaling_matrix (numpy rank-2, float64 array or None) - The diagonal and square scaling matrix.verbosity (int) - The amount of information to print. The higher the value, the
greater the verbosity.sim_index (None or int) - The index of the simulation to optimise. This should be None if
normal optimisation is desired.lower (list of numbers) - The model specific 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 (list of numbers) - The model specific 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 (list of int) - The model specific 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.
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