alphabase.constants.aa

Data:

AA_ASCII_MASS

AA mass array with ASCII code, mass of 'A' is AA_ASCII_MASS[ord('A')]

Functions:

calc_AA_masses(sequence)
calc_AA_masses_for_same_len_seqs(sequence_array)	Calculate AA masses for the array of same-len AA sequences.
calc_AA_masses_for_var_len_seqs(sequence_array)	We recommend to use calc_AA_masses_for_same_len_seqs as it is much faster.
calc_sequence_masses_for_same_len_seqs(...)	Calculate sequence masses for the array of same-len AA sequences.
replace_atoms(atom_replace_dict)
reset_AA_Composition()
reset_AA_atoms([atom_replace_dict])
reset_AA_df()
reset_AA_mass()	AA mass in np.array with shape (128,)
update_an_AA(aa, formula[, smiles])

alphabase.constants.aa.AA_ASCII_MASS: ndarray = array([1.00000000e+08, 1.00000000e+08, 1.00000000e+08, 1.00000000e+08,        1.00000000e+08, 1.00000000e+08, 1.00000000e+08, 1.00000000e+08,        1.00000000e+08, 1.00000000e+08, 1.00000000e+08, 1.00000000e+08,        1.00000000e+08, 1.00000000e+08, 1.00000000e+08, 1.00000000e+08,        1.00000000e+08, 1.00000000e+08, 1.00000000e+08, 1.00000000e+08,        1.00000000e+08, 1.00000000e+08, 1.00000000e+08, 1.00000000e+08,        1.00000000e+08, 1.00000000e+08, 1.00000000e+08, 1.00000000e+08,        1.00000000e+08, 1.00000000e+08, 1.00000000e+08, 1.00000000e+08,        1.00000000e+08, 1.00000000e+08, 1.00000000e+08, 1.00000000e+08,        1.00000000e+08, 1.00000000e+08, 1.00000000e+08, 1.00000000e+08,        1.00000000e+08, 1.00000000e+08, 1.00000000e+08, 1.00000000e+08,        1.00000000e+08, 1.00000000e+08, 1.00000000e+08, 1.00000000e+08,        1.00000000e+08, 1.00000000e+08, 1.00000000e+08, 1.00000000e+08,        1.00000000e+08, 1.00000000e+08, 1.00000000e+08, 1.00000000e+08,        1.00000000e+08, 1.00000000e+08, 1.00000000e+08, 1.00000000e+08,        1.00000000e+08, 1.00000000e+08, 1.00000000e+08, 1.00000000e+08,        1.00000000e+08, 7.10371138e+01, 1.20000000e+07, 1.03009185e+02,        1.15026943e+02, 1.29042593e+02, 1.47068414e+02, 5.70214637e+01,        1.37058912e+02, 1.13084064e+02, 1.13084064e+02, 1.28094963e+02,        1.13084064e+02, 1.31040485e+02, 1.14042927e+02, 2.37147727e+02,        9.70527638e+01, 1.28058578e+02, 1.56101111e+02, 8.70320284e+01,        1.01047678e+02, 1.50953636e+02, 9.90684139e+01, 1.86079313e+02,        1.20000000e+07, 1.63063329e+02, 1.20000000e+07, 1.00000000e+08,        1.00000000e+08, 1.00000000e+08, 1.00000000e+08, 1.00000000e+08,        1.00000000e+08, 1.00000000e+08, 1.00000000e+08, 1.00000000e+08,        1.00000000e+08, 1.00000000e+08, 1.00000000e+08, 1.00000000e+08,        1.00000000e+08, 1.00000000e+08, 1.00000000e+08, 1.00000000e+08,        1.00000000e+08, 1.00000000e+08, 1.00000000e+08, 1.00000000e+08,        1.00000000e+08, 1.00000000e+08, 1.00000000e+08, 8.70320284e+01,        1.81014009e+02, 1.00000000e+08, 1.00000000e+08, 1.00000000e+08,        1.00000000e+08, 1.63063329e+02, 1.00000000e+08, 1.00000000e+08,        1.00000000e+08, 1.00000000e+08, 1.00000000e+08, 1.00000000e+08])

AA mass array with ASCII code, mass of ‘A’ is AA_ASCII_MASS[ord(‘A’)]

alphabase.constants.aa.AA_DF: DataFrame = aa formula smiles         mass 0                    100000000.0 1   
                 100000000.0 2                     100000000.0 3                     100000000.0 4                     100000000.0 ..  ..     ...    ...          ... 123  {                 100000000.0 124  |                 100000000.0 125  }                 100000000.0 126  ~                 100000000.0 127                   100000000.0  [128 rows x 4 columns]

128-len AA dataframe

alphabase.constants.aa.calc_AA_masses(sequence: str) → ndarray

Parameters:

sequence (str) – Unmodified peptide sequence

Returns:

Masses of each amino acid.

Return type:

np.ndarray

alphabase.constants.aa.calc_AA_masses_for_same_len_seqs(sequence_array: ndarray) → ndarray

Calculate AA masses for the array of same-len AA sequences.

Parameters:

sequence_array (np.ndarray or list) – unmodified sequences with the same length.

Returns:

2-D (array_size, sequence_len) array of masses.

Return type:

np.ndarray

Raises:

ValueError – If sequences are not with the same length.

alphabase.constants.aa.calc_AA_masses_for_var_len_seqs(sequence_array: ndarray) → ndarray

We recommend to use calc_AA_masses_for_same_len_seqs as it is much faster. # TODO it’s the same

Parameters:

sequence_array (np.ndarray) – Sequences with variable lengths.

Returns:

1D array of masses, values of 1e8 are used to fill the max length. # TODO change this to 0

Return type:

np.ndarray

alphabase.constants.aa.calc_sequence_masses_for_same_len_seqs(sequence_array: ndarray) → ndarray

Calculate sequence masses for the array of same-len AA sequences.

Parameters:

sequence_array (np.ndarray or list) – unmodified sequences with the same length.

Returns:

1-D (array_size, sequence_len) array of masses.

Return type:

np.ndarray

Raises:

ValueError – If sequences are not with the same length.

alphabase.constants.aa.replace_atoms(atom_replace_dict: Dict)

alphabase.constants.aa.reset_AA_Composition()

alphabase.constants.aa.reset_AA_atoms(atom_replace_dict: Dict = {})

alphabase.constants.aa.reset_AA_df()

alphabase.constants.aa.reset_AA_mass() → ndarray

AA mass in np.array with shape (128,)

alphabase.constants.aa.update_an_AA(aa: str, formula: str, smiles: str = '')