def test_copyDefaultConfig() -> None:
"""Test copying of default config"""
from datapaths import path_config_copy
from resistics.config.defaults import copyDefaultConfig
from resistics.config.io import loadConfig
copyDefaultConfig(path_config_copy)
# load in this file
config = loadConfig(str(path_config_copy))
assert config["name"] == "global copy"
defaultConfig = loadConfig()
for key in config.keys():
if key == "name":
continue
assert config[key] == defaultConfig[key]
def __init__(
self, sampleFreq: float, winSamples: int, config: Union[Dict, None] = None
) -> None:
"""Initialise
Parameters
----------
sampleFreq : float
Sampling frequency of time data
winSamples : int
Number of samples in a window
"""
self.sampleFreq: float = sampleFreq
self.numSamples: int = winSamples
if config is None:
config = loadConfig()
self.detrend: bool = True
self.applywindow: bool = config["Spectra"]["applywindow"]
self.window: str = config["Spectra"]["windowfunc"]
self.windowFunc: np.ndarray = signal.get_window(
config["Spectra"]["windowfunc"], winSamples
)
# create an pyfftw plan
self.dataArray: np.ndarray = pyfftw.empty_aligned(
self.numSamples, dtype="float64"
)
self.fftObj: pyfftw.FFTW = pyfftw.builders.rfft(self.dataArray)
def __init__(self, refTime: datetime, timeData: TimeData, winSize: int,
winOlap: int) -> None:
"""Initialise the windower
Parameters
----------
refTime : datetime
The reference time
timeData : TimeData
The time series data to window
winSize : int
The window size in samples
winOlap : int
The overlap size between windows in samples
"""
self.timeData: TimeData = timeData
self.numSamples: int = timeData.numSamples
self.sampleFreq: float = timeData.sampleFreq
self.winSize: int = winSize
self.winDuration: float = (winSize - 1) / timeData.sampleFreq
self.winOlap: int = winOlap
self.chans: List[str] = timeData.chans
# refTime and dataTime are already datetime objects
self.refTime: datetime = refTime
self.dataTime: datetime = timeData.startTime
# min window warning setting
config = loadConfig()
self.minWindows: int = config["Window"]["minwindows"]
# initialise
self.initialiseWindows()
self.calcWindowTimes()
def getDefaultParameter(param: str) -> Any:
"""Get the default global configuration option
Parameters
----------
param : str
The config parameter
"""
from resistics.config.io import loadConfig
config = loadConfig()
return config[param]
def __init__(self, configFile: str = "") -> None:
"""Initialise with default configuration options
Parameters
----------
configFile : str
Path to the configuration file
"""
self.configFile: str = configFile
self.configParams = loadConfig(self.configFile)
# options dictionary
self.flags: Dict[str, bool] = {}
self.configure()
def __init__(self, decParams: DecimationParameters) -> None:
"""Initialise with decParams and default window parameters
Parameters
----------
decParams : int
Decimation level
"""
self.decParams = decParams
config = loadConfig()
self.minSize = config["Window"]["minwindowsize"]
self.minOlap = config["Window"]["minoverlapsize"]
self.windowFactor = config["Window"]["windowfactor"]
self.overlapFraction = config["Window"]["overlapfraction"]
self.calcParameters(self.windowFactor, self.overlapFraction)
def test_loadConfig() -> None:
"""Test loading config"""
from resistics.config.io import loadConfig
config = loadConfig()
assert config["name"] == "default"
assert config["ncores"] == -1
assert config["Calibration"]["extend"] == True
assert config["Calibration"]["usetheoretical"] == False
assert config["Decimation"]["numlevels"] == 7
assert config["Decimation"]["minsamples"] == 100
assert config["Frequencies"]["frequencies"] == []
assert config["Frequencies"]["perlevel"] == 7
assert config["Window"]["minwindows"] == 5
assert config["Window"]["windowfactor"] == 2.0
assert config["Window"]["minwindowsize"] == 512
assert config["Window"]["minoverlapsize"] == 128
assert config["Window"]["overlapfraction"] == 0.25
assert config["Window"]["windowsizes"] == []
assert config["Window"]["overlapsizes"] == []
assert config["Spectra"]["ncores"] == -1
assert config["Spectra"]["specdir"] == "spectra"
assert config["Spectra"]["applywindow"] == True
assert config["Spectra"]["windowfunc"] == "hann"
assert config["Statistics"]["ncores"] == -1
assert config["Statistics"]["stats"] == ["coherence", "transferFunction"]
assert config["Statistics"]["remotestats"] == [
"RR_coherence", "RR_transferFunction"
]
assert config["Solver"]["ncores"] == -1
assert config["Solver"]["method"] == "cm"
assert config["Solver"]["intercept"] == False
assert config["Solver"]["smoothfunc"] == "hann"
assert config["Solver"]["smoothlen"] == 9
assert config["Solver"]["OLS"] == {}
assert config["Solver"]["MM"]["weightfnc1"] == "huber"
assert config["Solver"]["MM"]["weightfnc2"] == "bisquare"
assert config["Solver"]["CM"] == {}
def test_config_data() -> None:
"""Test ConfigData initialiser"""
from resistics.config.io import loadConfig
# load default config
config = ConfigData()
assert config.configFile == ""
configParams = config.configParams
flags = config.flags
defaultConfig = loadConfig()
for key in defaultConfig.keys():
assert configParams[key] == defaultConfig[key]
assert flags["customfrequencies"] is False
assert flags["customwindows"] is False
assert config.getSpectraCores() == 0
assert config.getStatisticCores() == 0
assert config.getSolverCores() == 0
assert config.getConfigComment() == "Using default configuration"
def __init__(self, calDirectory: str) -> None:
"""Set the calibration directory and initialise
Calibrator will automatically find calibration files in the provided directory
Parameters
----------
calDirectory : str
Path of directory containing calibration files
"""
self.calExt, self.calFormats = getKnownCalibrationFormats()
self.calFiles: List[str] = []
self.numCalFiles = 0
self.calDir: str = calDirectory
self.findCalFiles()
# set whether to use theoretical calibration functions
conf = loadConfig()
self.extend: bool = conf["Calibration"]["extend"]
self.useTheoretical: bool = conf["Calibration"]["usetheoretical"]
def __init__(self, timeData: TimeData, decParams: DecimationParameters) -> None:
"""Initialise with timeData and decimation parameters
Parameters
----------
timeData : TimeData
The time data to decimate
decParams : DecimationParams
Decimation parameters for performing the decimation
"""
self.timeData: TimeData = timeData
self.sampleFreq: float = timeData.sampleFreq * 1.0
self.chans: List = timeData.chans
self.numSamples: int = timeData.numSamples
self.decParams: DecimationParameters = decParams
config = loadConfig()
self.minSamples: int = config["Decimation"]["minsamples"]
self.level: int = -1
self.maxDownsampleFactor: int = 8
def __init__(self, sampleFreq: float):
"""Initialise decimation parameters with sampling frequency
Calculates decimation factors and evaluation frequencies based on defaults
Parameters
----------
sampleFreq : float
Sampling frequency
"""
self.sampleFreq = sampleFreq
config = loadConfig()
self.divFactor: int = 2
self.numLevels: int = config["Decimation"]["numlevels"]
self.freqPerLevel: int = config["Frequencies"]["perlevel"]
self.decFactors: Union[np.ndarray, None] = None
self.decFrequencies: Union[np.ndarray, None] = None
self.evalFreq: Union[np.ndarray, None] = None
self.evalFreqPerLevel: Union[np.ndarray, None] = None
# calculate some initial values decimation parameters based on defaults
self.calcFrequencyParams(self.numLevels, self.freqPerLevel)