The Utilities Reference

Utility functions for time unit conversion and file I/O.

class neutronbraggedge.utilities.Utilities[source]

Utilities class

list_of_time_units: list[str] = ['s', 'ms', 'micros', 'ns']
static convert_time_units(data=None, from_units='micros', to_units='s')[source]

convert the time units

Parameters: * vdata: single data or array of value to convert * from_units: default ‘micros’. Must be either [‘s’,’micros’,’ns’] * to_units: default ‘s’. Must be either [‘s’, ‘micros’, ‘ns’]

Parameters:

  • data (ArrayLike | float | None)

  • from_units (Literal['s', 'ms', 'micros', 'ns'])

  • to_units (Literal['s', 'ms', 'micros', 'ns'])

Return type:

ndarray[tuple[Any, …], dtype[floating]] | float

static get_time_conversion_coeff(from_units='micros', to_units='s')[source]

return the coefficient to use to convert from first units to second units

Arguments: * from_units: default ‘micros’. Must be in the list of list_of_time_units * to_units: default ‘s’. Must be in the list of list_of_time_units

Returns: * coefficient to apply to data to convert from first units to second units provided

Raises: * ValueError: if any of the units is not supported

Parameters:

  • from_units (Literal['s', 'ms', 'micros', 'ns'])

  • to_units (Literal['s', 'ms', 'micros', 'ns'])

Return type:

float

static array_multiply_coeff(data=None, coeff=1)[source]

multiply each element of the array by the coeff

Parameters: * data: array to apply coefficient on * coeff: default value is 1. Coefficient to apply

Returns: * data * coefficient

Parameters:

  • data (ArrayLike | None)

  • coeff (float)

Return type:

ndarray[tuple[Any, …], dtype[floating]]

static array_add_coeff(data=None, coeff=1.0)[source]

Add coefficient to each element of the array

Parameters: * data: array to apply coefficient on * coeff: default value is 1. Coefficient to apply

Returns: * data + coefficient

Parameters:

  • data (ArrayLike | None)

  • coeff (float)

Return type:

ndarray[tuple[Any, …], dtype[floating]]

static array_divide_array(numerator=None, denominator=None)[source]

Divide two arrays of the same size

Parameters: * numerator: numpy array * denominator: numpy array

Returns: * numerator / denominator

Raises: * ValueError if array do not have the same size

Parameters:
Return type:

ndarray[tuple[Any, …], dtype[floating]]

static array_minus_array(array1=None, array2=None)[source]

Substract second array from first array provided

Parameters: * array1: left side of the ‘-’ operator * array2: right side of the ‘-’ operator

Returns: * Array1 - Array2

Raises: * ValueError if arrays do not have the same size

Parameters:
Return type:

ndarray[tuple[Any, …], dtype[floating]]

static load_csv(filename=None)[source]

Load a csv file and return its content

Parameters: * filename: name of the csv file to load

Returns: contents of the file as an array item for each line

Raise: ValueError if format is wrong

Parameters:

filename (str | None)

Return type:

list[float]

static load_ascii(filename=None, sep='')[source]

Load an ascii file using the separator provided to separete the value in the same row

Parameters: * filename: ascii full file name of file to load * sep: default ‘ ‘. Separator to use to separate values in the same row

Returns: Array of values

Raise: ValueError if file does not exist or format is wrong

Parameters:

  • filename (str | None)

  • sep (str)

Return type:

ndarray[tuple[Any, …], dtype[floating]]

static save_csv(filename=None, metadata=None, data=None)[source]

Create comma separated file (CSV)

Arguments: * filename: name of output file * metadata: metadata string array (will be placed at the top of the file with ‘#’ in front) * data: data float array

Parameters:
Return type:

None