Utils

Logger

class ipctk.LoggerLevel

Bases: pybind11_object

Members:

trace

debug

info

warn

error

critical

off

__annotations__ = {}
__eq__(self, other: object) bool
__getstate__(self) int
__hash__(self) int
__index__(self) int
__init__(self, value: int)
__int__(self) int
__members__ = {'critical': <LoggerLevel.critical: 5>, 'debug': <LoggerLevel.debug: 1>, 'error': <LoggerLevel.error: 4>, 'info': <LoggerLevel.info: 2>, 'off': <LoggerLevel.off: 6>, 'trace': <LoggerLevel.trace: 0>, 'warn': <LoggerLevel.warn: 3>}
__module__ = 'ipctk'
__ne__(self, other: object) bool
__repr__(self) str
__setstate__(self, state: int) None
__str__()

name(self: handle) -> str

critical = <LoggerLevel.critical: 5>
debug = <LoggerLevel.debug: 1>
error = <LoggerLevel.error: 4>
info = <LoggerLevel.info: 2>
property name : str
off = <LoggerLevel.off: 6>
trace = <LoggerLevel.trace: 0>
property value : int
warn = <LoggerLevel.warn: 3>
ipctk.set_logger_level(level: ipctk.LoggerLevel) None

Set log level

Multi-Threading

ipctk.get_num_threads() int

get maximum number of threads to use

ipctk.set_num_threads(nthreads: int) None

set maximum number of threads to use

Positive Semi-Definite Projection

ipctk.project_to_psd(A: numpy.ndarray[numpy.float64[m, n]], method: ipctk.PSDProjectionMethod) numpy.ndarray[numpy.float64[m, n]]

Matrix projection onto positive semi-definite cone

Parameters:
A: numpy.ndarray[numpy.float64[m, n]]

Symmetric matrix to project

method: ipctk.PSDProjectionMethod

PSD projection method

Returns:

Projected matrix

ipctk.project_to_pd(A: numpy.ndarray[numpy.float64[m, n]], eps: float = 1e-08) numpy.ndarray[numpy.float64[m, n]]

Matrix projection onto positive definite cone

Parameters:
A: numpy.ndarray[numpy.float64[m, n]]

Symmetric matrix to project

Returns:

Projected matrix


Last update: Jun 12, 2024