def processProject(projData: ProjectData, **kwargs) -> None:
"""Process a project
Parameters
----------
projData : ProjectData
The project data instance for the project
sites : List[str], optional
List of sites
sampleFreqs : List[float], optional
List of sample frequencies to process
specdir : str, optional
The spectra directories to use
inchans : List[str], optional
Channels to use as the input of the linear system
inputsite : str, optional
Site from which to take the input channels. The default is to use input and output channels from the same site
outchans : List[str], optional
Channels to use as the output of the linear system
remotesite : str, optional
The site to use as the remote site
remotechans : List[str], optional
Channels to use from the remote reference site
crosschannels : List[str], optional
List of channels to use for cross powers
masks : Dict, optional
Masks dictionary for passing mask data. The key should be a site name and the value should either be a string for a single mask or a list of multiple masks.
datetimes : List, optional
List of datetime constraints, each one as a dictionary. For example [{"type": "datetime", "start": 2018-08-08 00:00:00, "end": 2018-08-08 16:00:00, "levels": [0,1]}]. Note that levels is optional.
postpend : str, optional
String to postpend to the transfer function output
"""
options: Dict = dict()
options["sites"]: List[str] = projData.getSites()
options["sampleFreqs"]: List[float] = projData.getSampleFreqs()
options["specdir"]: str = projData.config.configParams["Spectra"][
"specdir"]
options["inchans"]: List[str] = ["Hx", "Hy"]
options["inputsite"]: str = ""
options["outchans"]: List[str] = ["Ex", "Ey"]
options["remotesite"]: str = ""
options["remotechans"]: List[str] = options["inchans"]
options["crosschannels"]: List[str] = []
options["masks"]: Dict = {}
options["datetimes"]: List = []
options["postpend"]: str = ""
options = parseKeywords(options, kwargs)
for site in options["sites"]:
siteData = projData.getSiteData(site)
siteFreqs = siteData.getSampleFreqs()
for sampleFreq in siteFreqs:
# check if not included
if sampleFreq not in options["sampleFreqs"]:
continue
processSite(projData, site, sampleFreq, **options)
def viewTipper(projData: ProjectData, **kwargs) -> None:
"""View transfer function data
Parameters
----------
projData : projecData
The project data
sites : List[str], optional
List of sites to plot transfer functions for
sampleFreqs : List[float], optional
List of samples frequencies for which to plot transfer functions
specdir : str, optional
The spectra directories used
postpend : str, optional
The postpend on the transfer function files
cols : bool, optional
Boolean flag, True to arrange tipper plot as 1 row with 3 columns
show : bool, optional
Show the spectra plot
save : bool, optional
Save the plot to the images directory
plotoptions : Dict
A dictionary of plot options. For example, set the resistivity y limits using res_ylim, set the phase y limits using phase_ylim and set the xlimits using xlim
"""
options = {}
options["sites"] = projData.getSites()
options["sampleFreqs"] = projData.getSampleFreqs()
options["specdir"] = projData.config.configParams["Spectra"]["specdir"]
options["postpend"] = ""
options["cols"] = True
options["save"] = False
options["show"] = True
options["plotoptions"] = plotOptionsTipper()
options = parseKeywords(options, kwargs)
# loop over sites
for site in options["sites"]:
siteData = projData.getSiteData(site)
sampleFreqs = set(siteData.getSampleFreqs())
# find the intersection with the options["freqs"]
sampleFreqs = sampleFreqs.intersection(options["sampleFreqs"])
sampleFreqs = sorted(list(sampleFreqs))
# if prepend is a string, then make it a list
if isinstance(options["postpend"], str):
options["postpend"] = [options["postpend"]]
plotfonts = options["plotoptions"]["plotfonts"]
# now loop over the postpend options
for pp in options["postpend"]:
# add an underscore if not empty
postpend = "_{}".format(pp) if pp != "" else pp
fig = plt.figure(figsize=options["plotoptions"]["figsize"])
mks = ["o", "*", "d", "^", "h"]
lstyles = ["solid", "dashed", "dashdot", "dotted"]
# loop over sampling frequencies
includedFreqs = []
for idx, sampleFreq in enumerate(sampleFreqs):
tfData = getTransferFunctionData(projData,
site,
sampleFreq,
specdir=options["specdir"],
postpend=pp)
if not tfData:
continue
includedFreqs.append(sampleFreq)
projectText(
"Plotting tipper for site {}, sample frequency {}".format(
site, sampleFreq))
mk = mks[idx % len(mks)]
ls = lstyles[idx % len(lstyles)]
tfData.viewTipper(
fig=fig,
rows=options["cols"],
mk=mk,
ls=ls,
label="{}".format(sampleFreq),
xlim=options["plotoptions"]["xlim"],
length_ylim=options["plotoptions"]["length_ylim"],
angle_ylim=options["plotoptions"]["angle_ylim"],
plotfonts=options["plotoptions"]["plotfonts"],
)
# check if any files found
if len(includedFreqs) == 0:
continue
# sup title
sub = "Site {} tipper: {}".format(site,
options["specdir"] + postpend)
sub = "{}\nfs = {}".format(
sub, arrayToString(includedFreqs, decimals=3))
st = fig.suptitle(sub, fontsize=plotfonts["suptitle"])
st.set_y(0.99)
fig.tight_layout()
fig.subplots_adjust(top=0.85)
if options["save"]:
impath = projData.imagePath
filename = "tipper_{}_{}{}".format(site, options["specdir"],
postpend)
savename = savePlot(impath, filename, fig)
projectText("Image saved to file {}".format(savename))
if not options["show"]:
plt.close("all")
else:
plt.show(block=options["plotoptions"]["block"])
def calculateRemoteStatistics(projData: ProjectData, remoteSite: str,
**kwargs):
"""Calculate statistics involving a remote reference site
Parameters
----------
projData : ProjectData
A project data instance
remoteSite : str
The name of the site to use as the remote site
sites : List[str], optional
A list of sites to calculate statistics for
sampleFreqs : List[float], optional
List of sampling frequencies for which to calculate statistics
chans : List[str], optional
List of data channels to use
specdir : str, optional
The spectra directory for which to calculate statistics
remotestats : List[str], optional
The statistics to calculate out. Acceptable statistics are: "RR_coherence", "RR_coherenceEqn", "RR_absvalEqn", "RR_transferFunction", "RR_resPhase". Configuration file values are used by default.
"""
options = {}
options["sites"] = projData.getSites()
options["sampleFreqs"] = projData.getSampleFreqs()
options["chans"] = []
options["specdir"] = projData.config.configParams["Spectra"]["specdir"]
options["remotestats"] = projData.config.configParams["Statistics"][
"remotestats"]
options = parseKeywords(options, kwargs)
projectText(
"Calculating stats: {} for sites: {} with remote site {}".format(
listToString(options["remotestats"]),
listToString(options["sites"]),
remoteSite,
))
# create the statistic calculator and IO object
statCalculator = StatisticCalculator()
statIO = StatisticIO()
# loop over sites
for site in options["sites"]:
siteData = projData.getSiteData(site)
measurements = siteData.getMeasurements()
for meas in measurements:
sampleFreq = siteData.getMeasurementSampleFreq(meas)
if sampleFreq not in options["sampleFreqs"]:
# don't need to calculate statistics for this sampling frequency
continue
projectText(
"Calculating stats for site {}, measurement {} with reference {}"
.format(site, meas, remoteSite))
# decimation and window parameters
decParams = getDecimationParameters(sampleFreq, projData.config)
decParams.printInfo()
numLevels = decParams.numLevels
winParams = getWindowParameters(decParams, projData.config)
# create the window selector and find the shared windows
winSelector = getWindowSelector(projData, decParams, winParams)
winSelector.setSites([site, remoteSite])
# calc shared windows between site and remote
winSelector.calcSharedWindows()
# create the spectrum reader
specReader = SpectrumReader(
os.path.join(siteData.getMeasurementSpecPath(meas),
options["specdir"]))
# loop through decimation levels
for iDec in range(0, numLevels):
# open the spectra file for the current decimation level
check = specReader.openBinaryForReading("spectra", iDec)
if not check:
# probably because this decimation level not calculated
continue
specReader.printInfo()
# get a set of the shared windows at this decimation level
# these are the global indices
sharedWindows = winSelector.getSharedWindowsLevel(iDec)
# get other information regarding only this spectra file
refTime = specReader.getReferenceTime()
winSize = specReader.getWindowSize()
winOlap = specReader.getWindowOverlap()
numWindows = specReader.getNumWindows()
evalFreq = decParams.getEvalFrequenciesForLevel(iDec)
sampleFreqDec = specReader.getSampleFreq()
globalOffset = specReader.getGlobalOffset()
fArray = specReader.getFrequencyArray()
# now want to find the size of the intersection between the windows in this file and the shared windows
sharedWindowsMeas = sharedWindows.intersection(
set(np.arange(globalOffset, globalOffset + numWindows)))
sharedWindowsMeas = sorted(list(sharedWindowsMeas))
numSharedWindows = len(sharedWindowsMeas)
statHandlers = {}
# create the statistic handlers
for stat in options["remotestats"]:
statElements = getStatElements(stat)
statHandlers[stat] = StatisticData(stat, refTime,
sampleFreqDec, winSize,
winOlap)
# remember, this is with the remote reference, so the number of windows is number of shared windows
statHandlers[stat].setStatParams(numSharedWindows,
statElements, evalFreq)
statHandlers[stat].comments = specReader.getComments()
statHandlers[stat].addComment(
projData.config.getConfigComment())
statHandlers[stat].addComment(
"Calculating remote statistic: {}".format(stat))
statHandlers[stat].addComment(
"Statistic components: {}".format(
listToString(statElements)))
# loop over the shared windows between the remote station and local station
for iW, globalWindow in enumerate(sharedWindowsMeas):
# get data and set in the statCalculator
winData = specReader.readBinaryWindowGlobal(globalWindow)
statCalculator.setSpectra(fArray, winData, evalFreq)
# for the remote site, use the reader in win selector
remoteSF, remoteReader = winSelector.getSpecReaderForWindow(
remoteSite, iDec, globalWindow)
winDataRR = remoteReader.readBinaryWindowGlobal(
globalWindow)
statCalculator.addRemoteSpec(winDataRR)
for sH in statHandlers:
data = statCalculator.getDataForStatName(sH)
statHandlers[sH].addStat(iW, globalWindow, data)
# save statistic
for sH in statHandlers:
statIO.setDatapath(
os.path.join(siteData.getMeasurementStatPath(meas),
options["specdir"]))
statIO.write(statHandlers[sH], iDec)
def calculateStatistics(projData: ProjectData, **kwargs):
"""Calculate statistics for sites
Parameters
----------
projData : ProjectData
A project data instance
sites : List[str], optional
A list of sites to calculate statistics for
sampleFreqs : List[float], optional
List of sampling frequencies for which to calculate statistics
chans : List[str], optional
List of data channels to use
specdir : str, optional
The spectra directory for which to calculate statistics
stats : List[str], optional
The statistics to calculate out. Acceptable values are: "absvalEqn" "coherence", "psd", "poldir", "transFunc", "resPhase", "partialcoh". Configuration file values are used by default.
"""
options = {}
options["sites"] = projData.getSites()
options["sampleFreqs"] = projData.getSampleFreqs()
options["chans"] = []
options["specdir"] = projData.config.configParams["Spectra"]["specdir"]
options["stats"] = projData.config.configParams["Statistics"]["stats"]
options = parseKeywords(options, kwargs)
projectText("Calculating stats: {} for sites: {}".format(
listToString(options["stats"]), listToString(options["sites"])))
# create the statistic calculator and IO object
statCalculator = StatisticCalculator()
statIO = StatisticIO()
# loop through sites and calculate statistics
for site in options["sites"]:
siteData = projData.getSiteData(site)
measurements = siteData.getMeasurements()
for meas in measurements:
sampleFreq = siteData.getMeasurementSampleFreq(meas)
if sampleFreq not in options["sampleFreqs"]:
# don't need to calculate statistics for this sampling frequency
continue
projectText("Calculating stats for site {}, measurement {}".format(
site, meas))
# decimation parameters
decParams = getDecimationParameters(sampleFreq, projData.config)
decParams.printInfo()
numLevels = decParams.numLevels
# create the spectrum reader
specReader = SpectrumReader(
os.path.join(siteData.getMeasurementSpecPath(meas),
options["specdir"]))
# loop through decimation levels
for iDec in range(0, numLevels):
# open the spectra file for the current decimation level
check = specReader.openBinaryForReading("spectra", iDec)
if not check:
# probably because this decimation level not calculated
continue
specReader.printInfo()
# get windows
refTime = specReader.getReferenceTime()
winSize = specReader.getWindowSize()
winOlap = specReader.getWindowOverlap()
numWindows = specReader.getNumWindows()
evalFreq = decParams.getEvalFrequenciesForLevel(iDec)
sampleFreqDec = specReader.getSampleFreq()
globalOffset = specReader.getGlobalOffset()
fArray = specReader.getFrequencyArray()
statHandlers = {}
# create the statistic handlers
for stat in options["stats"]:
statElements = getStatElements(stat)
statHandlers[stat] = StatisticData(stat, refTime,
sampleFreqDec, winSize,
winOlap)
statHandlers[stat].setStatParams(numWindows, statElements,
evalFreq)
statHandlers[stat].comments = specReader.getComments()
statHandlers[stat].addComment(
projData.config.getConfigComment())
statHandlers[stat].addComment(
"Calculating statistic: {}".format(stat))
statHandlers[stat].addComment(
"Statistic components: {}".format(
listToString(statElements)))
# loop over windows and calculate the relevant statistics
for iW in range(0, numWindows):
# get data
winData = specReader.readBinaryWindowLocal(iW)
globalIndex = iW + globalOffset
# give the statistic calculator the spectra
statCalculator.setSpectra(fArray, winData, evalFreq)
# get the desired statistics
for sH in statHandlers:
data = statCalculator.getDataForStatName(sH)
statHandlers[sH].addStat(iW, globalIndex, data)
# save statistic
for sH in statHandlers:
statIO.setDatapath(
os.path.join(siteData.getMeasurementStatPath(meas),
options["specdir"]))
statIO.write(statHandlers[sH], iDec)
def preProcess(projData: ProjectData, **kwargs) -> None:
"""Pre-process project time data
Preprocess the time data using filters, notch filters, resampling or interpolation. A new measurement folder is created under the site. The name of the new measurement folder is:
prepend_[name of input measurement]_postpend. By default, prepend is "proc" and postpend is empty.
Processed time series data can be saved in a new site by using the outputsite option.
Parameters
----------
projData : ProjectData
A project data object
sites : str, List[str], optional
Either a single site or a list of sites
sampleFreqs : int, float, List[float], optional
The frequencies to preprocess
start : str, optional
Start date of data to preprocess in format "%Y-%m-%d %H:%M:%S"
stop : str, optional
Stop date of data to process in format "%Y-%m-%d %H:%M:%S"
outputsite : str, optional
A site to output the preprocessed time data to. If this site does not exist, it will be created
polreverse : Dict[str, bool]
Keys are channels and values are boolean flags for reversing
scale : Dict[str, float]
Keys are channels and values are floats to multiply the channel data by
calibrate : bool, optional
Boolean flag for calibrating the data. Default is false and setting to True will calibrate where files can be found.
normalise : bool, optional
Boolean flag for normalising the data. Default is False and setting to True will normalise each channel independently.
filter : Dict, optional
Filtering options in a dictionary
notch : List[float], optional
List of frequencies to notch in spectra given as a list of floats
resamp : Dict, optional
Resampling parameters in a dictionary with entries in the format: {sampleRateFrom: sampleRateTo}. All measurement directories of sampleRateFrom will be resampled to sampleRateTo
interp : bool, optional
Boolean flag for interpolating the data on to the second, so that sampling is coincident with seconds. This is not always the case. For example, SPAM data is not necessarily sampled on the second, whereas ATS data is. This function is useful when combining data of multiple formats. Interpolation does not change the sampling rate. Default is False.
prepend : str, optional
String to prepend to the output folder. Default is "proc".
postpend : str, optional
String to postpend to the output folder. Default is empty.
"""
options: Dict = {}
options["sites"]: List = projData.getSites()
options["sampleFreqs"]: List[float] = projData.getSampleFreqs()
options["start"]: Union[bool, str] = False
options["stop"]: Union[bool, str] = False
options["outputsite"]: str = ""
options["polreverse"]: Union[bool, Dict[str, bool]] = False
options["scale"]: Union[bool, Dict[str, float]] = False
options["calibrate"]: bool = False
options["normalise"]: bool = False
options["filter"]: Dict = {}
options["notch"]: List[float] = []
options["resamp"]: Dict = {}
options["interp"]: bool = False
options["prepend"]: str = "proc"
options["postpend"]: str = ""
options = parseKeywords(options, kwargs)
# print info
text: List = ["Processing with options"]
for op, val in options.items():
text.append("\t{} = {}".format(op, val))
projectBlock(text)
if isinstance(options["sites"], str):
options["sites"] = [options["sites"]]
# outputting to another site
if options["outputsite"] != "":
projectText(
"Preprocessed data will be saved to output site {}".format(
options["outputsite"]
)
)
# create the site
projData.createSite(options["outputsite"])
projData.refresh()
outputSitePath = projData.getSiteData(options["outputsite"]).timePath
# output naming
outPre = options["prepend"] + "_" if options["prepend"] != "" else ""
outPost = "_" + options["postpend"] if options["postpend"] != "" else ""
if outPre == "" and outPost == "" and options["outputsite"] == "":
outPre = "proc_"
# create a data calibrator writer instance
cal = Calibrator(projData.calPath)
if options["calibrate"]:
cal.printInfo()
writer = DataWriterInternal()
# format dates
if options["start"]:
options["start"] = datetime.strptime(options["start"], "%Y-%m-%d %H:%M:%S")
if options["stop"]:
options["stop"] = datetime.strptime(options["stop"], "%Y-%m-%d %H:%M:%S")
for site in options["sites"]:
siteData = projData.getSiteData(site)
siteData.printInfo()
# loop over frequencies
for sampleFreq in options["sampleFreqs"]:
measurements = siteData.getMeasurements(sampleFreq)
if len(measurements) == 0:
# no data files at this sample rate
continue
# otherwise, process
for meas in measurements:
# get the reader
projectText("Processing site {}, measurement {}".format(site, meas))
reader = siteData.getMeasurement(meas)
startTime = reader.getStartDatetime()
stopTime = reader.getStopDatetime()
if (options["start"] or options["stop"]) and not checkDateOptions(
options, startTime, stopTime
):
continue
# if the data contributes, copy in the data if relevant
if options["start"]:
startTime = options["start"]
if options["stop"]:
stopTime = options["stop"]
# calculate the samples
sampleStart, sampleEnd = reader.time2sample(startTime, stopTime)
# now get the data
timeData = reader.getPhysicalSamples(
startSample=sampleStart, endSample=sampleEnd
)
timeData.printInfo()
headers = reader.getHeaders()
chanHeaders, chanMap = reader.getChanHeaders()
# apply options
applyPolarisationReversalOptions(options, timeData)
applyScaleOptions(options, timeData)
applyCalibrationOptions(options, cal, timeData, reader)
applyFilterOptions(options, timeData)
applyNotchOptions(options, timeData)
applyInterpolationOptions(options, timeData)
applyResampleOptions(options, timeData)
applyNormaliseOptions(options, timeData)
# output dataset path
if options["outputsite"] != "":
timePath = outputSitePath
else:
timePath = siteData.timePath
outPath = os.path.join(timePath, "{}{}{}".format(outPre, meas, outPost))
# write time data - need to manually change some headers (hence the keywords)
writer = DataWriterInternal()
writer.setOutPath(outPath)
writer.writeData(
headers,
chanHeaders,
timeData,
start_time=timeData.startTime.strftime("%H:%M:%S.%f"),
start_date=timeData.startTime.strftime("%Y-%m-%d"),
stop_time=timeData.stopTime.strftime("%H:%M:%S.%f"),
stop_date=timeData.stopTime.strftime("%Y-%m-%d"),
numSamples=timeData.numSamples,
sample_freq=timeData.sampleFreq,
physical=True,
)
writer.printInfo()
def viewTime(
projData: ProjectData, startDate: str, endDate: str, **kwargs
) -> Union[plt.figure, None]:
"""View timeseries in the project
Parameters
----------
startDate : str
The start of the data range to plot
endDate : str
The end of the date range to plot
sites : List[str], optional
List of sites
sampleFreqs : List[float], optional
List of sample frequencies to plot
chans : List[str], optional
List of channels to plot
polreverse : Dict[str, bool]
Keys are channels and values are boolean flags for reversing
calibrate : bool, optional
Boolean flag to calibrate data
normalise : bool, optional
Boolean flag to normalise the data. Default is False and setting to True will normalise each channel independently.
notch : List[float], optional
List of frequencies to notch out
filter : Dict, optional
Filter parameters
show : bool, optional
Boolean flag to show the plot
save : bool, optional
Boolean flag to save the plot to images folder
plotoptions : Dict
Dictionary of plot options
Returns
-------
matplotlib.pyplot.figure or None
A matplotlib figure unless the plot is not shown and is saved, in which case None and the figure is closed.
"""
# default options
options = {}
options["sites"]: List[str] = projData.sites
options["sampleFreqs"]: Union[List[float], List[str]] = projData.getSampleFreqs()
options["chans"]: List[str] = ["Ex", "Ey", "Hx", "Hy", "Hz"]
options["polreverse"]: Union[bool, Dict[str, bool]] = False
options["calibrate"]: bool = False
options["normalise"]: bool = False
options["filter"]: Dict = {}
options["notch"]: List[float] = []
options["show"]: bool = True
options["save"]: bool = False
options["plotoptions"]: Dict = plotOptionsTime()
options = parseKeywords(options, kwargs)
# prepare calibrator
cal = getCalibrator(projData.calPath, projData.config)
if options["calibrate"]:
cal.printInfo()
# format startDate and endDate
start = datetime.strptime("{}.000".format(startDate), "%Y-%m-%d %H:%M:%S.%f")
stop = datetime.strptime("{}.000".format(endDate), "%Y-%m-%d %H:%M:%S.%f")
# collect relevant data - dictionary to store timeData
timeDataAll = {}
for site in options["sites"]:
siteData = projData.getSiteData(site)
siteData.printInfo()
measurements = siteData.getMeasurements()
timeDataAll[site] = {}
# loop over measurements and save data for each one
for meas in measurements:
sampleFreq = siteData.getMeasurementSampleFreq(meas)
if sampleFreq not in options["sampleFreqs"]:
continue
# check if data contributes to user defined time period
siteStart = siteData.getMeasurementStart(meas)
siteStop = siteData.getMeasurementEnd(meas)
if siteStop < start or siteStart > stop:
continue
reader = siteData.getMeasurement(meas)
# get the samples of the datetimes
sampleStart, sampleStop = reader.time2sample(start, stop)
# as the samples returned from time2sample are rounded use sample2time to get the appropriate start and end times for those samples
readStart, readStop = reader.sample2time(sampleStart, sampleStop)
# get the data for any available channels meaning even those sites with missing channels can be plotted
timeData = reader.getPhysicalData(readStart, readStop)
projectText(
"Plotting measurement {} of site {} between {} and {}".format(
meas, site, readStart, readStop
)
)
# apply various options
applyPolarisationReversalOptions(options, timeData)
applyCalibrationOptions(options, cal, timeData, reader)
applyFilterOptions(options, timeData)
applyNotchOptions(options, timeData)
applyNormaliseOptions(options, timeData)
timeDataAll[site][meas] = timeData
# plot all the data
plotfonts = options["plotoptions"]["plotfonts"]
fig = plt.figure(figsize=options["plotoptions"]["figsize"])
for site in timeDataAll:
for meas in timeDataAll[site]:
timeData = timeDataAll[site][meas]
timeData.view(
sampleStop=timeDataAll[site][meas].numSamples - 1,
fig=fig,
chans=options["chans"],
label="{} - {}".format(site, meas),
xlim=[start, stop],
plotfonts=plotfonts,
)
# add the suptitle
st = fig.suptitle(
"Time data from {} to {}".format(
start.strftime("%Y-%m-%d %H-%M-%S"), stop.strftime("%Y-%m-%d %H-%M-%S")
),
fontsize=plotfonts["suptitle"],
)
st.set_y(0.98)
# do the axis labels
numChans = len(options["chans"])
for idx, chan in enumerate(options["chans"]):
plt.subplot(numChans, 1, idx + 1)
# do the yaxis
if isElectric(chan):
plt.ylabel("mV/km", fontsize=plotfonts["axisLabel"])
if len(options["plotoptions"]["Eylim"]) > 0:
plt.ylim(options["plotoptions"]["Eylim"])
else:
if options["calibrate"]:
plt.ylabel("nT", fontsize=plotfonts["axisLabel"])
else:
plt.ylabel("mV", fontsize=plotfonts["axisLabel"])
if len(options["plotoptions"]["Hylim"]) > 0:
plt.ylim(options["plotoptions"]["Hylim"])
plt.legend(loc=1, fontsize=plotfonts["legend"])
# plot format
fig.tight_layout(rect=[0, 0.02, 1, 0.96])
fig.subplots_adjust(top=0.92)
# plot show and save
if options["save"]:
impath = projData.imagePath
filename = "timeData_{}_{}".format(
start.strftime("%Y-%m-%d_%H-%M-%S_"), stop.strftime("%Y-%m-%d_%H-%M-%S")
)
savename = savePlot(impath, filename, fig)
projectText("Image saved to file {}".format(savename))
if options["show"]:
plt.show(block=options["plotoptions"]["block"])
if not options["show"] and options["save"]:
plt.close(fig)
return None
return fig
def calculateSpectra(projData: ProjectData, **kwargs) -> None:
"""Calculate spectra for the project time data
The philosophy is that spectra are calculated out for all data and later limited using statistics and time constraints
Parameters
----------
projData : ProjectData
A project data object
sites : str, List[str], optional
Either a single site or a list of sites
sampleFreqs : int, float, List[float], optional
The frequencies in Hz for which to calculate the spectra. Either a single frequency or a list of them.
chans : List[str], optional
The channels for which to calculate out the spectra
polreverse : Dict[str, bool]
Keys are channels and values are boolean flags for reversing
scale : Dict[str, float]
Keys are channels and values are floats to multiply the channel data by
calibrate : bool, optional
Flag whether to calibrate the data or not
notch : List[float], optional
List of frequencies to notch
filter : Dict, optional
Filter parameters
specdir : str, optional
The spectra directory to save the spectra data in
"""
# default options
options = {}
options["sites"] = projData.getSites()
options["sampleFreqs"]: List[float] = projData.getSampleFreqs()
options["chans"]: List[str] = []
options["polreverse"]: Union[bool, Dict[str, bool]] = False
options["scale"]: Union[bool, Dict[str, float]] = False
options["calibrate"]: bool = True
options["notch"]: List[float] = []
options["filter"]: Dict = {}
options["specdir"]: str = projData.config.configParams["Spectra"]["specdir"]
options = parseKeywords(options, kwargs)
# prepare calibrator
cal = getCalibrator(projData.calPath, projData.config)
if options["calibrate"]:
cal.printInfo()
datetimeRef = projData.refTime
for site in options["sites"]:
siteData = projData.getSiteData(site)
siteData.printInfo()
# calculate spectra for each frequency
for sampleFreq in options["sampleFreqs"]:
measurements = siteData.getMeasurements(sampleFreq)
projectText(
"Site {} has {:d} measurement(s) at sampling frequency {:.2f}".format(
site, len(measurements), sampleFreq
)
)
if len(measurements) == 0:
continue # no data files at this sample rate
for meas in measurements:
projectText(
"Calculating spectra for site {} and measurement {}".format(
site, meas
)
)
# get measurement start and end times - this is the time of the first and last sample
reader = siteData.getMeasurement(meas)
startTime = siteData.getMeasurementStart(meas)
stopTime = siteData.getMeasurementEnd(meas)
dataChans = (
options["chans"]
if len(options["chans"]) > 0
else reader.getChannels()
)
timeData = reader.getPhysicalData(startTime, stopTime, chans=dataChans)
timeData.addComment(breakComment())
timeData.addComment("Calculating project spectra")
timeData.addComment(projData.config.getConfigComment())
# apply various options
applyPolarisationReversalOptions(options, timeData)
applyScaleOptions(options, timeData)
applyCalibrationOptions(options, cal, timeData, reader)
applyFilterOptions(options, timeData)
applyNotchOptions(options, timeData)
# define decimation and window parameters
decParams = getDecimationParameters(sampleFreq, projData.config)
decParams.printInfo()
numLevels = decParams.numLevels
winParams = getWindowParameters(decParams, projData.config)
dec = Decimator(timeData, decParams)
timeData.addComment(
"Decimating with {} levels and {} frequencies per level".format(
numLevels, decParams.freqPerLevel
)
)
# loop through decimation levels
for iDec in range(0, numLevels):
# get the data for the current level
check = dec.incrementLevel()
if not check:
break # not enough data
timeData = dec.timeData
# create the windower and give it window parameters for current level
sampleFreqDec = dec.sampleFreq
win = Windower(
datetimeRef,
timeData,
winParams.getWindowSize(iDec),
winParams.getOverlap(iDec),
)
if win.numWindows < 2:
break # do no more decimation
# add some comments
timeData.addComment(
"Evaluation frequencies for this level {}".format(
listToString(decParams.getEvalFrequenciesForLevel(iDec))
)
)
timeData.addComment(
"Windowing with window size {} samples and overlap {} samples".format(
winParams.getWindowSize(iDec), winParams.getOverlap(iDec)
)
)
# create the spectrum calculator and statistics calculators
specCalc = SpectrumCalculator(
sampleFreqDec, winParams.getWindowSize(iDec)
)
# get ready a file to save the spectra
specPath = os.path.join(
siteData.getMeasurementSpecPath(meas), options["specdir"]
)
specWrite = SpectrumWriter(specPath, datetimeRef)
specWrite.openBinaryForWriting(
"spectra",
iDec,
sampleFreqDec,
winParams.getWindowSize(iDec),
winParams.getOverlap(iDec),
win.winOffset,
win.numWindows,
dataChans,
)
# loop though windows, calculate spectra and save
for iW in range(0, win.numWindows):
# get the window data
winData = win.getData(iW)
# calculate spectra
specData = specCalc.calcFourierCoeff(winData)
# write out spectra
specWrite.writeBinary(specData)
# close spectra file
specWrite.writeCommentsFile(timeData.getComments())
specWrite.closeFile()