gemmi.Mtz class

Classes

class Batch
class Column
class Dataset

Static methods

def data_fits_into(…)
def get_f_phi_on_grid(…)
def get_size_for_hkl(…)
def get_value_on_grid(…)
def row_as_dict(…)
def transform_f_phi_to_map(…)

Methods

def add_column(self, label: str, type: str, dataset_id: int = -1, pos: int = -1, expand_data: bool = True) -> Column
def add_dataset(self, name: str) -> Dataset
def column_labels(self, /) -> typing.List[str]
def column_with_label(self, label: str, dataset: Dataset = None) -> Column
def columns_with_type(self, type: str) -> typing.List[Column]
def copy_column(self, dest_idx: int, src_col: Column, trailing_cols: typing.List[str] = []) -> Column
def count(self, label: str) -> int
def dataset(self, id: int) -> Dataset
def ensure_asu(self, tnt_asu: bool = False) -> None
def expand_to_p1(self, /) -> None
def get_cell(self, dataset: int = -1) -> UnitCell
def get_f_phi(self, f: str, phi: str, as_is: bool = False) -> ComplexAsuData
def get_float(self, col: str, as_is: bool = False) -> FloatAsuData
def get_int(self, col: str, as_is: bool = False) -> IntAsuData
def get_value_sigma(self, f: str, sigma: str, as_is: bool = False) -> ValueSigmaAsuData
def make_1_d2_array(self, dataset: int = -1) -> numpy.ndarray[numpy.float32]
def make_d_array(self, dataset: int = -1) -> numpy.ndarray[numpy.float32]
def make_miller_array(self, /) -> numpy.ndarray[numpy.int32]
def reindex(self, op: Op) -> str
def remove_column(self, index: int) -> None
def replace_column(self, dest_idx: int, src_col: Column, trailing_cols: typing.List[str] = []) -> Column
def resolution_high(self, /) -> float
def resolution_low(self, /) -> float
def rfree_column(self, /) -> Column
def set_cell_for_all(self, arg0: UnitCell, /) -> None
def set_data(self, asu_data: ComplexAsuData) -> None
def set_data(self, asu_data: FloatAsuData) -> None
def set_data(self, array: numpy.ndarray[numpy.float32]) -> None
def sort(self, use_first: int = 3) -> bool
def switch_to_asu_hkl(self, /) -> bool
def switch_to_original_hkl(self, /) -> bool
def update_reso(self, /) -> None
def write_to_file(self, path: str) -> None

Special methods

def __init__(self, with_base: bool = False) -> None
def __repr__(self, /) -> str

Properties

appended_text: str get set
array: numpy.ndarray[numpy.float32] get
batches: MtzBatches get set
cell: UnitCell get set
columns: MtzColumns get set
datasets: MtzDatasets get set
history: typing.List[str] get set
max_1_d2: float get set
min_1_d2: float get set
nreflections: int get set
nsymop: int get
sort_order get set
spacegroup: SpaceGroup get set
spacegroup_name: str get
spacegroup_number: int get
title: str get set
valm: float get set