def getFileNames(self, maskName: str,
sampleFreq: float) -> Tuple[str, str]:
"""Get the name of a mask file
This method is here to give consistent file names for mask files.
Parameters
----------
maskName : str
The name of the mask
sampleFreq : float
The sampling frequency of the data
Returns
-------
infoFile : str
The name of the mask infoFile
winFile : str
The name of the mask winFile
"""
checkAndMakeDir(self.datapath)
sampleFreqStr = fileFormatSampleFreq(sampleFreq)
name: str = maskName + "_{}".format(sampleFreqStr)
infoFile: str = os.path.join(self.datapath, name + ".info")
winFile: str = os.path.join(
self.datapath, name) # no need for extension here, numpy adds one
return infoFile, winFile
def writeResult(self, specdir: str, postpend: str, freq, data: np.ndarray,
variances: np.ndarray, **kwargs):
"""Write the transfer function file
Parameters
----------
specdir : str
The spectra data being used for the transfer function estimate
postpend : str
The optional postpend to the transfer function file
data : np.ndarray
The transfer function estimates
variances : np.ndarray
The transfer function variances
remotesite : str, optional
Optionally, if there is a remote site
remotechans : List[str], optional
Optionally add the remote channels if there is a remote site
"""
# path for writing out to
sampleFreqStr = fileFormatSampleFreq(self.decParams.sampleFreq)
if postpend == "":
filename = "{}_fs{:s}_{}".format(self.outSite, sampleFreqStr,
specdir)
else:
filename = "{}_fs{:s}_{}_{}".format(self.outSite, sampleFreqStr,
specdir, postpend)
datapath = os.path.join(self.outpath, sampleFreqStr)
checkAndMakeDir(datapath)
outfile = os.path.join(datapath, filename)
# now construct the transferFunctionData object
numFreq = len(freq)
dataDict = {}
varDict = {}
for i in range(0, self.outSize):
for j in range(0, self.inSize):
key = "{}{}".format(self.outChannels[i], self.inChannels[j])
dataArray = np.empty(shape=(numFreq), dtype="complex")
varArray = np.empty(shape=(len(freq)), dtype="float")
for ifreq in range(0, numFreq):
dataArray[ifreq] = data[ifreq][i, j]
varArray[ifreq] = variances[ifreq][i, j]
dataDict[key] = dataArray
varDict[key] = varArray
tfData = TransferFunctionData(freq, dataDict, varDict)
# now make the writer and write out
tfWriter = TransferFunctionWriter(outfile, tfData)
tfWriter.setHeaders(
sampleFreq=self.decParams.sampleFreq,
insite=self.inSite,
inchans=self.inChannels,
outsite=self.outSite,
outchans=self.outChannels,
)
if "remotesite" in kwargs:
tfWriter.addHeader("remotesite", kwargs["remotesite"])
if "remotechans" in kwargs:
tfWriter.addHeader("remotechans", kwargs["remotechans"])
tfWriter.write()
def getTransferFunctionData(projData: ProjectData, site: str,
sampleFreq: float,
**kwargs) -> TransferFunctionData:
"""Get transfer function data
Parameters
----------
projData : projecData
The project data
site : str
Site to get the transfer functiond data for
sampleFreq : int, float
The sampling frequency for which to get the transfer function data
specdir : str, optional
The spectra directories used
postpend : str, optional
The postpend on the transfer function files
"""
from resistics.transfunc.io import TransferFunctionReader
options: Dict = dict()
options["specdir"]: str = projData.config.configParams["Spectra"][
"specdir"]
options["postpend"]: str = ""
options = parseKeywords(options, kwargs)
# deal with the postpend
if options["postpend"] != "":
postpend = "_{}".format(options["postpend"])
else:
postpend = options["postpend"]
siteData = projData.getSiteData(site)
sampleFreqStr = fileFormatSampleFreq(sampleFreq)
path = os.path.join(
siteData.transFuncPath,
"{:s}".format(sampleFreqStr),
"{}_fs{:s}_{}{}".format(site, sampleFreqStr, options["specdir"],
postpend),
)
# check path
if not checkFilepath(path):
projectWarning("No transfer function file with name {}".format(path))
return False
projectText(
"Reading transfer function for site {}, sample frequency {}, file {}".
format(site, sampleFreq, path))
tfReader = TransferFunctionReader(path)
tfReader.printInfo()
return tfReader.tfData
def test_fileFormatSampleFreq() -> None:
from resistics.common.io import fileFormatSampleFreq
assert fileFormatSampleFreq(128) == "128_000"
assert fileFormatSampleFreq(4096.1567) == "4096_157"
def viewStatisticDensityplot(
projData: ProjectData,
site: str,
sampleFreq: Union[int, float],
stat: str,
crossplots: List[List[str]],
**kwargs
) -> Union[Figure, None]:
"""View statistic data as a density plot for a single sampling frequency of a site
Parameters
----------
projData : ProjectData
A project instance
site : str
The site for which to plot statistics
stat : str
The statistic to plot
sampleFreq : float
The sampling frequency for which to plot statistics
crossplots : List[List[str]]
The statistic element pairs to crossplot
declevel : int
The decimation level to plot
eFreqI : int
The evaluation frequency index
specdir : str
The spectra directory
maskname : str
Mask name
xlim : List, optional
Limits for the x axis
ylim : List, optional
Limits for the y axis
maxcols : int
The maximum number of columns in the plots
show : bool, optional
Show the spectra plot
save : bool, optional
Save the plot to the images directory
plotoptions : Dict, optional
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. If no data was found, None.
"""
from resistics.common.plot import (
savePlot,
plotOptionsSpec,
getPlotRowsAndCols,
colorbar2dSpectra,
)
options = {}
options["declevel"] = 0
options["eFreqI"] = 0
options["specdir"] = projData.config.configParams["Spectra"]["specdir"]
options["maskname"] = ""
options["xlim"] = []
options["ylim"] = []
options["maxcols"] = 2
options["show"] = True
options["save"] = False
options["plotoptions"] = plotOptionsSpec()
options = parseKeywords(options, kwargs)
projectText(
"Plotting density plot for statistic {}, site {} and sampling frequency {}".format(
stat, site, sampleFreq
)
)
statData = getStatisticDataForSampleFreq(
projData,
site,
sampleFreq,
stat,
declevel=options["declevel"],
specdir=options["specdir"],
)
statMeas = list(statData.keys())
if len(statMeas) == 0:
projectWarning(
"No statistic files for site {}, sampling frequency {}, statistic {} and decimation level {}".format(
site, sampleFreq, stat, options["declevel"]
)
)
return None
# get the evaluation frequency
eFreq = statData[statMeas[0]].evalFreq[options["eFreqI"]]
# get the mask data
maskWindows = []
if options["maskname"] != "":
maskData = getMaskData(projData, site, options["maskname"], sampleFreq)
maskWindows = maskData.getMaskWindowsFreq(
options["declevel"], options["eFreqI"]
)
# plot information
nrows, ncols = getPlotRowsAndCols(options["maxcols"], len(crossplots))
plotfonts = options["plotoptions"]["plotfonts"]
fig = plt.figure(figsize=options["plotoptions"]["figsize"])
# suptitle
st = fig.suptitle(
"{} density plots for {}, sampling frequency {} Hz,\ndecimation level {} and evaluation frequency {} Hz".format(
stat, site, sampleFreq, options["declevel"], eFreq
),
fontsize=plotfonts["suptitle"],
)
st.set_y(0.98)
# now plot the data
for idx, cplot in enumerate(crossplots):
ax = plt.subplot(nrows, ncols, idx + 1)
plt.title("Crossplot {}".format(cplot), fontsize=plotfonts["title"])
plotAll1 = []
plotAll2 = []
for meas in statMeas:
stats = statData[meas].getStats(maskwindows=maskWindows)
plotI1 = statData[meas].winStats.index(cplot[0])
plotData1 = np.squeeze(stats[:, options["eFreqI"], plotI1])
plotI2 = statData[meas].winStats.index(cplot[1])
plotData2 = np.squeeze(stats[:, options["eFreqI"], plotI2])
# add to all data
if plotData1.size == 0:
continue
if plotData1.size == 1:
plotAll1 = plotAll1 + [float(plotData1)]
plotAll2 = plotAll2 + [float(plotData2)]
else:
plotAll1 = plotAll1 + plotData1.tolist()
plotAll2 = plotAll2 + plotData2.tolist()
plotAll1 = np.array(plotAll1)
plotAll2 = np.array(plotAll2)
nbins = 200
if len(options["xlim"]) > 0:
plt.xlim(options["xlim"])
rangex = options["xlim"]
else:
minx = np.percentile(plotAll1, 2)
maxx = np.percentile(plotAll1, 98)
ax.set_xlim(minx, maxx)
rangex = [minx, maxx]
if len(options["ylim"]) > 0:
plt.ylim(options["ylim"])
rangey = options["ylim"]
else:
miny = np.percentile(plotAll2, 2)
maxy = np.percentile(plotAll2, 98)
ax.set_ylim(miny, maxy)
rangey = [miny, maxy]
plt.hist2d(
plotAll1,
plotAll2,
bins=(nbins, nbins),
range=[rangex, rangey],
cmap=plt.cm.inferno,
)
# axis format
plt.xlabel(cplot[0], fontsize=plotfonts["axisLabel"])
plt.ylabel(cplot[1], fontsize=plotfonts["axisLabel"])
plt.grid(True)
# set tick sizes
for label in ax.get_xticklabels() + ax.get_yticklabels():
label.set_fontsize(plotfonts["axisTicks"])
# plot format, show and save
# fig.tight_layout(rect=[0.02, 0.02, 0.98, 0.92])
if options["save"]:
impath = projData.imagePath
sampleFreqStr = fileFormatSampleFreq(sampleFreq)
filename = "statDensityplot_{:s}_{:s}_{:s}_dec{:d}_efreq{:d}_{:s}".format(
stat,
site,
sampleFreqStr,
options["declevel"],
options["eFreqI"],
options["specdir"],
)
if options["maskname"] != "":
filename = "{}_{}".format(filename, options["maskname"])
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 viewStatisticHistogram(
projData: ProjectData, site: str, sampleFreq: float, stat: str, **kwargs
) -> Union[Figure, None]:
"""View statistic histograms for a single sampling frequency of a site
Parameters
----------
projData : ProjectData
A project instance
site : str
The site for which to plot statistics
stat : str
The statistic to plot
sampleFreq : float
The sampling frequency for which to plot statistics
declevel : int
The decimation level to plot
eFreqI : int
The evaluation frequency index
specdir : str
The spectra directory
maskname : str
Mask name
numbins : int
The number of bins for the histogram data binning
xlim : List, optional
Limits for the x axis
maxcols : int
The maximum number of columns in the plots
show : bool, optional
Show the spectra plot
save : bool, optional
Save the plot to the images directory
plotoptions : Dict, optional
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. If no data was found, None.
"""
from resistics.common.plot import savePlot, plotOptionsSpec, getPlotRowsAndCols
options = {}
options["declevel"] = 0
options["eFreqI"] = 0
options["specdir"] = projData.config.configParams["Spectra"]["specdir"]
options["maskname"] = ""
options["numbins"] = 40
options["xlim"] = []
options["maxcols"] = 4
options["show"] = True
options["save"] = False
options["plotoptions"] = plotOptionsSpec()
options = parseKeywords(options, kwargs)
projectText(
"Plotting histogram for statistic {}, site {} and sampling frequency {}".format(
stat, site, sampleFreq
)
)
statData = getStatisticDataForSampleFreq(
projData,
site,
sampleFreq,
stat,
declevel=options["declevel"],
specdir=options["specdir"],
)
statMeas = list(statData.keys())
if len(statMeas) == 0:
projectWarning(
"No statistic files for site {}, sampling frequency {}, statistic {} and decimation level {}".format(
site, sampleFreq, stat, options["declevel"]
)
)
return None
# get the statistic components
statComponents = statData[statMeas[0]].winStats
# get the evaluation frequency
eFreq = statData[statMeas[0]].evalFreq[options["eFreqI"]]
# get the mask data
maskWindows = []
if options["maskname"] != "":
maskData = getMaskData(projData, site, options["maskname"], sampleFreq)
maskWindows = maskData.getMaskWindowsFreq(
options["declevel"], options["eFreqI"]
)
# plot information
nrows, ncols = getPlotRowsAndCols(options["maxcols"], len(statComponents))
numbins = options["numbins"]
plotfonts = options["plotoptions"]["plotfonts"]
fig = plt.figure(figsize=options["plotoptions"]["figsize"])
# suptitle
st = fig.suptitle(
"{} histogram for {}, sampling frequency {} Hz, decimation level {} and evaluation frequency {} Hz".format(
stat, site, sampleFreq, options["declevel"], eFreq
),
fontsize=plotfonts["suptitle"],
)
st.set_y(0.98)
# now plot the data
for idx, val in enumerate(statComponents):
ax = plt.subplot(nrows, ncols, idx + 1)
plt.title("Histogram {}".format(val), fontsize=plotfonts["title"])
plotData = np.empty(shape=(0))
for meas in statMeas:
stats = statData[meas].getStats(maskwindows=maskWindows)
plotData = np.concatenate(
(plotData, np.squeeze(stats[:, options["eFreqI"], idx]))
)
# remove infinities and nans
plotData = plotData[np.isfinite(plotData)]
# x axis options
xlim = (
options["xlim"]
if len(options["xlim"]) > 0
else [np.min(plotData), np.max(plotData)]
)
plt.xlim(xlim)
plt.xlabel("Value", fontsize=plotfonts["axisLabel"])
# now plot with xlim in mind
plt.hist(plotData, numbins, range=xlim, facecolor="red", alpha=0.75)
plt.grid()
# y axis options
plt.ylabel("Count", fontsize=plotfonts["axisLabel"])
# set tick sizes
for label in ax.get_xticklabels() + ax.get_yticklabels():
label.set_fontsize(plotfonts["axisTicks"])
# plot format, show and save
fig.tight_layout(rect=[0.02, 0.02, 0.98, 0.92])
if options["save"]:
impath = projData.imagePath
sampleFreqStr = fileFormatSampleFreq(sampleFreq)
filename = "statHist_{:s}_{:s}_{:s}_dec{:d}_efreq{:d}_{:s}".format(
stat,
site,
sampleFreqStr,
options["declevel"],
options["eFreqI"],
options["specdir"],
)
if options["maskname"] != "":
filename = "{}_{}".format(filename, options["maskname"])
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 viewStatistic(
projData: ProjectData, site: str, sampleFreq: Union[int, float], stat: str, **kwargs
) -> Union[Figure, None]:
"""View statistic data for a single sampling frequency of a site
Parameters
----------
projData : ProjectData
A project instance
site : str
The site for which to plot statistics
stat : str
The statistic to plot
sampleFreq : float
The sampling frequency for which to plot statistics
declevel : int
The decimation level to plot
eFreqI : int
The evaluation frequency index
specdir : str
The spectra directory
maskname : str
Mask name
clim : List, optional
Limits for colourbar axis
xlim : List, optional
Limits for the x axis
ylim : List, optional
Limits for the y axis
colortitle : str, optional
Title for the colourbar
show : bool, optional
Show the spectra plot
save : bool, optional
Save the plot to the images directory
plotoptions : Dict, optional
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. If no data was found, None.
"""
from resistics.common.plot import savePlot, plotOptionsSpec, getPlotRowsAndCols
options = {}
options["declevel"] = 0
options["eFreqI"] = 0
options["specdir"] = projData.config.configParams["Spectra"]["specdir"]
options["maskname"] = ""
options["clim"] = []
options["xlim"] = []
options["ylim"] = []
options["colortitle"] = ""
options["show"] = True
options["save"] = False
options["plotoptions"] = plotOptionsSpec()
options = parseKeywords(options, kwargs)
projectText(
"Plotting statistic {} for site {} and sampling frequency {}".format(
stat, site, sampleFreq
)
)
statData = getStatisticDataForSampleFreq(
projData,
site,
sampleFreq,
stat,
declevel=options["declevel"],
specdir=options["specdir"],
)
statMeas = list(statData.keys())
if len(statMeas) == 0:
projectWarning(
"No statistic files for site {}, sampling frequency {}, statistic {} and decimation level {}".format(
site, sampleFreq, stat, options["declevel"]
)
)
return None
# get the evaluation frequency
eFreq = statData[statMeas[0]].evalFreq[options["eFreqI"]]
# get the mask data
maskWindows = []
if options["maskname"] != "":
maskData = getMaskData(projData, site, options["maskname"], sampleFreq)
maskWindows = maskData.getMaskWindowsFreq(
options["declevel"], options["eFreqI"]
)
# setup the figure
plotfonts = options["plotoptions"]["plotfonts"]
fig = plt.figure(figsize=options["plotoptions"]["figsize"])
# get the date limits
siteData = projData.getSiteData(site)
if len(options["xlim"]) == 0:
start = siteData.getMeasurementStart(statMeas[0])
end = siteData.getMeasurementEnd(statMeas[0])
for meas in statMeas:
start = min(start, siteData.getMeasurementStart(meas))
end = max(end, siteData.getMeasurementEnd(meas))
options["xlim"] = [start, end]
# do the plots
for meas in statMeas:
statData[meas].view(
options["eFreqI"],
fig=fig,
xlim=options["xlim"],
ylim=options["ylim"],
clim=options["clim"],
label=meas,
plotfonts=options["plotoptions"]["plotfonts"],
maskwindows=maskWindows,
)
# add a legened
plt.legend(markerscale=4, fontsize=plotfonts["legend"])
# do the title after all the plots
fig.suptitle(
"{} values for {}, sampling frequency = {:.2f} Hz, decimation level = {} and evaluation frequency {} Hz".format(
stat, site, sampleFreq, options["declevel"], eFreq
),
fontsize=plotfonts["suptitle"],
)
# plot format, show and save
fig.tight_layout(rect=[0.02, 0.02, 0.98, 0.92])
if options["save"]:
impath = projData.imagePath
sampleFreqStr = fileFormatSampleFreq(sampleFreq)
filename = "stat_{:s}_{:s}_{:s}_dec{:d}_efreq{:d}_{:s}".format(
stat,
site,
sampleFreqStr,
options["declevel"],
options["eFreqI"],
options["specdir"],
)
if options["maskname"] != "":
filename = "{}_{}".format(filename, options["maskname"])
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