Zero Fill¶
- class nmrPype.fn.ZF.ZeroFill(zf_count: int = -1, zf_pad: int = 0, zf_size: int = 0, zf_auto: bool = False, zf_inv: bool = False, mp_enable: bool = False, mp_proc: int = 0, mp_threads: int = 0)¶
Data Function object for performing a zero-fill on the data
- Parameters:
zf_count (int) – Number of times to double the data
zf_pad (int) – Number of zeros to pad the data by
zf_size (int) – Set data to new size while filling empty data with zeros
zf_auto (bool) – Automatically add zeros to pad data to the next power of two
zf_inv (bool) – Reverse a zero-fill operation based on header params
mp_enable (bool) – Enable multiprocessing
mp_proc (int) – Number of processors to utilize for multiprocessing
mp_threads (int) – Number of threads to utilize per process
- static clArgs(subparser, parent_parser)¶
Zero Fill command-line arguments
Adds Zero Fill parser to the subparser, with its corresponding default args Called by
nmrPype.parse.parser().- Parameters:
subparser (_SubParsersAction[ArgumentParser]) – Subparser object that will receive function and its arguments
- initialize(data: DataFrame)¶
- Initialization follows the following steps:
Handle function specific arguments
Update any header values before any calculations occur that are independent of the data, such as flags and parameter storage
- Parameters:
data (DataFrame) – target data to manipulate
- static nextPowerOf2(x: int)¶
Helper function to set input integer to the nearest power of two greater than input integer.
- parallelize(array: ndarray, verb: tuple[int, int, str] = (0, 16, 'H')) ndarray¶
Multiprocessing implementation for function to properly optimize for hardware
- Parameters:
array (ndarray) – Target data array to process with function
verb (tuple[int,int,str], optional)
print (Tuple containing elements for verbose) –
Verbosity level
Verbosity Increment
Direct Dimension Label
(0 (by default) –
Verbosity level
Verbosity Increment
Direct Dimension Label
16 –
Verbosity level
Verbosity Increment
Direct Dimension Label
'H') –
Verbosity level
Verbosity Increment
Direct Dimension Label
- Returns:
new_array – Updated array after function operation
- Return type:
ndarray
- process(array: ndarray, verb: tuple[int, int, str] = (0, 16, 'H')) ndarray¶
See
nmrPype.fn.function.DataFunction.process()for documentation
- processMP(array: ndarray, arg: tuple, operation, verb: tuple[int, int, str] = (0, 16, 'H')) ndarray¶
Process specifically for MP, changes how it performs operation
- Parameters:
array (ndarray) – array to process
args (tuple) – Arguments to implement for target operation
operation (function) – function to call in each thread
- Returns:
modified array post-process
- Return type:
ndarray
- run(data: DataFrame) int¶
See
nmrPype.fn.function.DataFunction.run()for documentation
- static truncate(array: array, size: int)¶