ectoolkits.analysis.uncertainty module#

ectoolkits.analysis.uncertainty.get_f_coarse_grained_data(data_list: Union[_SupportsArray[dtype], _NestedSequence[_SupportsArray[dtype]], bool, int, float, complex, str, bytes, _NestedSequence[Union[bool, int, float, complex, str, bytes]]], tau: int) → Union[_SupportsArray[dtype], _NestedSequence[_SupportsArray[dtype]], bool, int, float, complex, str, bytes, _NestedSequence[Union[bool, int, float, complex, str, bytes]]][source]#

coarse grain array data in forward direction with block length tau.

data_list (ArrayLike):

Time Serials Data, shape(1,N), like energies.

tau (int):

block length

ArrayLike:

Coarse-grained Time Serials Data, shape(1, int(N/tau)).

>>> get_f_coarse_grained_data(energies_list, 50)
ectoolkits.analysis.uncertainty.get_uncertainty(data_list: Union[_SupportsArray[dtype], _NestedSequence[_SupportsArray[dtype]], bool, int, float, complex, str, bytes, _NestedSequence[Union[bool, int, float, complex, str, bytes]]], tau_range: Tuple[int, int, int] = (1, 50, 1)) → Tuple[Union[_SupportsArray[dtype], _NestedSequence[_SupportsArray[dtype]], bool, int, float, complex, str, bytes, _NestedSequence[Union[bool, int, float, complex, str, bytes]]], Union[_SupportsArray[dtype], _NestedSequence[_SupportsArray[dtype]], bool, int, float, complex, str, bytes, _NestedSequence[Union[bool, int, float, complex, str, bytes]]]][source]#

calculate uncertainty for a time serial data, like energies.

data_list (ArrayLike):

Time Serials Data, shape(1,N), like energies.

tau_range (Tuple[int, int, int], optional):

A list of tau values. Defaults to (1, 50, 1).

Tuple[ArrayLike, ArrayLike]:

  1. a list of mean values corresponding to tau

  2. a list of uncertainties corresponding to tau

>>>  vgap
array([17.21097182, 17.21777723, 17.22483708, ..., 17.72987759,
   17.76217987, 17.80458071])
>>>  vgap.shape
(13401,)
>>> get_uncertainty(vgap, tau_range=(1, 50, 1))
(array([17.72412774, 17.72412174, 17.72412774, 17.72412174, 17.72412174,
    17.72411847, 17.72411847, 17.72412174, 17.72412774, 17.72412174,
    17.72411847, 17.72411469, 17.72409511, 17.72411847, 17.72412228,
    17.72411469, 17.72412114, 17.72411469, 17.72412228, 17.72412174,
    17.72411847, 17.72411847, 17.72401629, 17.72411469, 17.72412174,
    17.72409511, 17.72411469, 17.72395954, 17.72411847, 17.72383193,
    17.72411469, 17.72373849, 17.72411847, 17.72412114, 17.72374005,
    17.72411469, 17.72412206, 17.72373849, 17.72375512, 17.72412174,
    17.72376983, 17.72411847, 17.72372078, 17.72373849, 17.72377165,
    17.72401629, 17.72412228, 17.72411469, 17.72375512]),
array([0.00521475, 0.00736884, 0.00901134, 0.01038585, 0.01158367,
    0.01265499, 0.01362589, 0.014516  , 0.01533808, 0.01611023,
    0.01683463, 0.01752622, 0.01819687, 0.01873488, 0.01935648,
    0.01993202, 0.02041762, 0.02085271, 0.0213809 , 0.02189274,
    0.02239711, 0.02284273, 0.02327067, 0.02372226, 0.02401315,
    0.0244621 , 0.02488177, 0.02532788, 0.02569048, 0.02586628,
    0.0262883 , 0.02674231, 0.02682957, 0.02712625, 0.02778647,
    0.02759716, 0.02792354, 0.02817088, 0.02851189, 0.02871313,
    0.02902685, 0.0294121 , 0.02958297, 0.02987098, 0.0297415 ,
    0.02995385, 0.03045183, 0.03049436, 0.03114382]))