def getStatisticDataForSampleFreq(
projData: ProjectData,
site: str,
sampleFreq: float,
stat: str,
declevel: int = 0,
**kwargs
) -> List[StatisticData]:
"""Get the statistic data (for a particular decimation level) for all measurements in a site with sampling frequency sampleFreq
Parameters
----------
projData : ProjectData
Project instance
site : str
The site for which to get the statistic data
sampleFreq : float
The sampling frequency
stat : str
The statistic for which to get the measurement
declevel : int, optional
The decimation level to read in. Default is 0.
specdir : str, optional
The spectra directory
Returns
-------
Dict[str, StatisticData]
A statistic data object
"""
from resistics.statistics.io import StatisticIO
options = {}
options["specdir"] = projData.config.configParams["Spectra"]["specdir"]
options = parseKeywords(options, kwargs)
siteData = projData.getSiteData(site)
if not siteData:
projectError("Unable to find site {} in project".format(site), quitrun=True)
# load the statistic data
statData: Dict[str, StatisticData] = {}
statIO = StatisticIO()
measurements = siteData.getMeasurements(sampleFreq)
for meas in measurements:
statIO.setDatapath(
os.path.join(siteData.getMeasurementStatPath(meas), options["specdir"])
)
# make sure some data was found
chk = statIO.read(stat, declevel)
if chk is not None:
statData[meas] = statIO.read(stat, declevel)
else:
projectWarning(
"No {} data found for site {} and measurement {}".format(
stat, site, meas
)
)
return statData
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 getSpecReader(projData: ProjectData, site: str, meas: str,
**kwargs) -> Union[SpectrumReader, None]:
"""Get the spectrum reader for a measurement
Parameters
----------
site : str
Site for which to get the spectra reader
meas : str
The measurement
options : Dict
Options in a dictionary
declevel : int, optional
Decimation level for which to get data
specdir : str, optional
String that specifies spectra directory for the measurement
Returns
-------
SpectrumReader
The SpectrumReader object or None if data does not exist
"""
options = {}
options["declevel"]: int = 0
options["specdir"]: str = projData.config.configParams["Spectra"][
"specdir"]
options = parseKeywords(options, kwargs)
siteData = projData.getSiteData(site)
measurements = siteData.getMeasurements()
if meas not in measurements:
projectError("Measurement directory {} not found".format(meas),
quitrun=True)
# create the spectrum reader
specReader = SpectrumReader(
os.path.join(siteData.getMeasurementSpecPath(meas),
options["specdir"]))
specReader.printInfo()
# open the spectra file for the current decimation level if it exists
check = specReader.openBinaryForReading("spectra", options["declevel"])
if not check:
projectWarning("Spectra file does not exist at level {}".format(
options["declevel"]))
return None
return specReader
def viewSpectraStack(projData: ProjectData, site: str, meas: str,
**kwargs) -> Union[Figure, None]:
"""View spectra stacks for a measurement
Parameters
----------
projData : projecData
The project data
site : str
The site to view
meas: str
The measurement of the site to view
chans : List[str], optional
Channels to plot
declevel : int, optional
Decimation level to plot
numstacks : int, optional
The number of windows to stack
coherences : List[List[str]], optional
A list of coherences to add, specified as [["Ex", "Hy"], ["Ey", "Hx"]]
specdir : str, optional
String that specifies spectra directory for the measurement
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, then None is returned.
"""
from resistics.common.plot import savePlot, plotOptionsSpec, colorbarMultiline
options = {}
options["chans"] = []
options["declevel"] = 0
options["numstacks"] = 10
options["coherences"] = []
options["specdir"] = projData.config.configParams["Spectra"]["specdir"]
options["show"] = True
options["save"] = False
options["plotoptions"] = plotOptionsSpec()
options = parseKeywords(options, kwargs)
projectText("Plotting spectra stack for measurement {} and site {}".format(
meas, site))
specReader = getSpecReader(projData, site, meas, **options)
if specReader is None:
return None
# channels
dataChans = specReader.getChannels()
if len(options["chans"]) > 0:
dataChans = options["chans"]
numChans = len(dataChans)
# get windows
numWindows = specReader.getNumWindows()
sampleFreqDec = specReader.getSampleFreq()
f = specReader.getFrequencyArray()
# calculate num of windows to stack in each set
stackSize = int(np.floor(1.0 * numWindows / options["numstacks"]))
if stackSize == 0:
projectWarning("Too few windows for number of stacks {}".format(
options["numstacks"]))
options["numstacks"] = numWindows
stackSize = 1
projectWarning("Number of stacks changed to {}".format(
options["numstacks"]))
# calculate number of rows - in case interested in coherences too
nrows = (2 if len(options["coherences"]) == 0 else 2 +
np.ceil(1.0 * len(options["coherences"]) / numChans))
# setup the figure
plotfonts = options["plotoptions"]["plotfonts"]
cmap = colorbarMultiline()
fig = plt.figure(figsize=options["plotoptions"]["figsize"])
st = fig.suptitle(
"Spectra stack, fs = {:.6f} [Hz], decimation level = {:2d}, windows in each set = {:d}"
.format(sampleFreqDec, options["declevel"], stackSize),
fontsize=plotfonts["suptitle"],
)
st.set_y(0.98)
# do the stacking
for iP in range(0, options["numstacks"]):
stackStart = iP * stackSize
stackStop = min(stackStart + stackSize, numWindows)
color = cmap(iP / options["numstacks"])
# dictionaries to hold data for this section
stackedData = {}
ampData = {}
phaseData = {}
powerData = {}
# assign initial zeros
for c in dataChans:
stackedData[c] = np.zeros(shape=(specReader.getDataSize()),
dtype="complex")
ampData[c] = np.zeros(shape=(specReader.getDataSize()),
dtype="complex")
phaseData[c] = np.zeros(shape=(specReader.getDataSize()),
dtype="complex")
for c2 in dataChans:
powerData[c + c2] = np.zeros(shape=(specReader.getDataSize()),
dtype="complex")
# now stack the data and create nice plots
for iW in range(stackStart, stackStop):
winData = specReader.readBinaryWindowLocal(iW)
for c in dataChans:
stackedData[c] += winData.data[c]
ampData[c] += np.absolute(winData.data[c])
phaseData[c] += np.angle(winData.data[c]) * (180.0 / np.pi)
# get coherency data
for c2 in dataChans:
powerData[c + c2] += winData.data[c] * np.conjugate(
winData.data[c2])
if iW == stackStart:
startTime = winData.startTime
if iW == stackStop - 1:
stopTime = winData.stopTime
# scale powers and stacks
ampLim = options["plotoptions"]["amplim"]
for idx, c in enumerate(dataChans):
stackedData[c] = stackedData[c] / (stackStop - stackStart)
ampData[c] = ampData[c] / (stackStop - stackStart)
phaseData[c] = phaseData[c] / (stackStop - stackStart)
for c2 in dataChans:
# normalisation
powerData[c + c2] = 2 * powerData[c + c2] / (stackStop -
stackStart)
# normalisation
powerData[c + c2][[0, -1]] = powerData[c + c2][[0, -1]] / 2
# plot
ax1 = plt.subplot(nrows, numChans, idx + 1)
plt.title("Amplitude {}".format(c), fontsize=plotfonts["title"])
h = ax1.semilogy(
f,
ampData[c],
color=color,
label="{} to {}".format(
startTime.strftime("%m-%d %H:%M:%S"),
stopTime.strftime("%m-%d %H:%M:%S"),
),
)
if len(ampLim) == 2:
ax1.set_ylim(ampLim)
else:
ax1.set_ylim(0.01, 1000)
ax1.set_xlim(0, sampleFreqDec / 2.0)
if isMagnetic(c):
ax1.set_ylabel("Amplitude [nT]",
fontsize=plotfonts["axisLabel"])
else:
ax1.set_ylabel("Amplitude [mV/km]",
fontsize=plotfonts["axisLabel"])
ax1.set_xlabel("Frequency [Hz]", fontsize=plotfonts["axisLabel"])
plt.grid(True)
# set tick sizes
for label in ax1.get_xticklabels() + ax1.get_yticklabels():
label.set_fontsize(plotfonts["axisTicks"])
# plot phase
ax2 = plt.subplot(nrows, numChans, numChans + idx + 1)
plt.title("Phase {}".format(c), fontsize=plotfonts["title"])
ax2.plot(
f,
phaseData[c],
color=color,
label="{} to {}".format(
startTime.strftime("%m-%d %H:%M:%S"),
stopTime.strftime("%m-%d %H:%M:%S"),
),
)
ax2.set_ylim(-180, 180)
ax2.set_xlim(0, sampleFreqDec / 2.0)
ax2.set_ylabel("Phase [degrees]", fontsize=plotfonts["axisLabel"])
ax2.set_xlabel("Frequency [Hz]", fontsize=plotfonts["axisLabel"])
plt.grid(True)
# set tick sizes
for label in ax2.get_xticklabels() + ax2.get_yticklabels():
label.set_fontsize(plotfonts["axisTicks"])
# plot coherences
for idx, coh in enumerate(options["coherences"]):
c = coh[0]
c2 = coh[1]
cohNom = np.power(np.absolute(powerData[c + c2]), 2)
cohDenom = powerData[c + c] * powerData[c2 + c2]
coherence = cohNom / cohDenom
ax = plt.subplot(nrows, numChans, 2 * numChans + idx + 1)
plt.title("Coherence {} - {}".format(c, c2),
fontsize=plotfonts["title"])
ax.plot(
f,
coherence,
color=color,
label="{} to {}".format(
startTime.strftime("%m-%d %H:%M:%S"),
stopTime.strftime("%m-%d %H:%M:%S"),
),
)
ax.set_ylim(0, 1.1)
ax.set_xlim(0, sampleFreqDec / 2)
ax.set_ylabel("Coherence", fontsize=plotfonts["axisLabel"])
ax.set_xlabel("Frequency [Hz]", fontsize=plotfonts["axisLabel"])
plt.grid(True)
# set tick sizes
for label in ax.get_xticklabels() + ax.get_yticklabels():
label.set_fontsize(plotfonts["axisTicks"])
# fig legend and layout
ax = plt.gca()
h, l = ax.get_legend_handles_labels()
fig.tight_layout(rect=[0.01, 0.01, 0.98, 0.81])
# legend
legax = plt.axes(position=[0.01, 0.82, 0.98, 0.12], in_layout=False)
plt.tick_params(left=False,
labelleft=False,
bottom=False,
labelbottom=False)
plt.box(False)
legax.legend(h,
l,
ncol=4,
loc="upper center",
fontsize=plotfonts["legend"])
# plot show and save
if options["save"]:
impath = projData.imagePath
filename = "spectraStack_{}_{}_dec{}_{}".format(
site, meas, options["declevel"], options["specdir"])
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 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