"powerSpectralDensity",
"polarisationDirection",
"partialCoherence",
"transferFunction",
"resPhase",
"""
# need the project path for loading
projectPath = os.path.join("exampleProject")
projData = loadProject(projectPath, configFile="ex1_04_config.ini")
projData.printInfo()
stats, remotestats = getStatNames()
# plot the examples we need
options = plotOptionsSpec()
options["figsize"] = (20, 7)
options["plotfonts"]["suptitle"] = 18
options["plotfonts"]["title"] = 16
# coherence
viewStatistic(
projData, "site1", 128, "coherence", save=True, show=False, plotoptions=options
)
viewStatisticHistogram(
projData, "site1", 128, "coherence", save=True, show=False, plotoptions=options
)
# polarisation directions
options["figsize"] = (17, 12)
viewStatistic(
def viewStatisticCrossplot(projData: ProjectData, site: str,
sampleFreq: Union[int, float], stat: str,
crossplots: List[List[str]],
**kwargs) -> Union[plt.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
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.
"""
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 crossplot 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())
# 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(
"{} crossplots 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, cplot in enumerate(crossplots):
ax = plt.subplot(nrows, ncols, idx + 1)
plt.title("Crossplot {}".format(cplot), fontsize=plotfonts["title"])
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])
scat = plt.scatter(plotData1,
plotData2,
edgecolors="none",
marker="o",
s=12,
label=meas)
# x axis options
if len(options["xlim"]) > 0:
plt.xlim(options["xlim"])
if len(options["ylim"]) > 0:
plt.ylim(options["ylim"])
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"])
plt.legend(loc=2, markerscale=4, fontsize=plotfonts["legend"])
# 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 = "statCrossplot_{: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
from resistics.project.projectIO import loadProject
projectPath = os.path.join("tutorialProject")
projData = loadProject(projectPath)
# calculate another set of spectra for the 128 Hz data with notching at 50Hz and 16.667Hz
from resistics.project.projectSpectra import calculateSpectra
calculateSpectra(projData, sampleFreqs=[128], notch=[50], specdir="notch")
projData.refresh()
# view the spectra
from resistics.utilities.utilsPlotter import plotOptionsSpec, getPaperFonts
from resistics.project.projectSpectra import viewSpectra, viewSpectraSection
plotOptions = plotOptionsSpec(plotfonts=getPaperFonts())
viewSpectra(
projData,
"site1",
"meas_2012-02-10_11-30-00",
specdir="notch",
plotoptions=plotOptions,
show=True,
save=True,
)
viewSpectraSection(
projData,
"site1",
"meas_2012-02-10_11-30-00",
specdir="notch",
def viewStatisticHistogram(projData: ProjectData, site: str, sampleFreq: float,
stat: str, **kwargs) -> Union[plt.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.
"""
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())
# 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[plt.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.
"""
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"],
)
# get the statistics
statMeas = list(statData.keys())
# 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
st = 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
def viewSpectraStack(
projData: ProjectData, site: str, meas: str, **kwargs
) -> Union[plt.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.
"""
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)
# 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"]))
# 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 viewSpectraSection(
projData: ProjectData, site: str, meas: str, **kwargs
) -> Union[plt.figure, None]:
"""View spectra section 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
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.
"""
options = {}
options["chans"] = []
options["declevel"] = 0
options["specdir"] = projData.config.configParams["Spectra"]["specdir"]
options["show"] = True
options["save"] = False
options["plotoptions"] = plotOptionsSpec()
options = parseKeywords(options, kwargs)
projectText(
"Plotting spectra section for measurement {} and site {}".format(meas, site)
)
specReader = getSpecReader(projData, site, meas, **options)
# channels
dataChans = specReader.getChannels()
if len(options["chans"]) > 0:
dataChans = options["chans"]
# get windows
numWindows = specReader.getNumWindows()
sampleFreqDec = specReader.getSampleFreq()
# freq array
f = specReader.getFrequencyArray()
# now if plotting a section, ignore plotwindow for now
if numWindows > 250:
windows = list(np.linspace(0, numWindows, 250, endpoint=False, dtype=np.int32))
else:
windows = np.arange(0, 250)
# create figure
plotfonts = options["plotoptions"]["plotfonts"]
fig = plt.figure(figsize=options["plotoptions"]["figsize"])
st = fig.suptitle(
"Spectra section, site = {}, meas = {}, fs = {:.2f} [Hz], decimation level = {:2d}, windows = {:d}, {} to {}".format(
site,
meas,
sampleFreqDec,
options["declevel"],
len(windows),
windows[0],
windows[-1],
),
fontsize=plotfonts["suptitle"],
)
st.set_y(0.98)
# collect the data
specData = np.empty(
shape=(len(windows), len(dataChans), specReader.getDataSize()), dtype="complex"
)
dates = []
for idx, iW in enumerate(windows):
winData = specReader.readBinaryWindowLocal(iW)
for cIdx, chan in enumerate(dataChans):
specData[idx, cIdx, :] = winData.data[chan]
dates.append(winData.startTime)
ampLim = options["plotoptions"]["amplim"]
for idx, chan in enumerate(dataChans):
ax = plt.subplot(1, len(dataChans), idx + 1)
plotData = np.transpose(np.absolute(np.squeeze(specData[:, idx, :])))
if len(ampLim) == 2:
plt.pcolor(
dates,
f,
plotData,
norm=LogNorm(vmin=ampLim[0], vmax=ampLim[1]),
cmap=colorbar2dSpectra(),
)
else:
plt.pcolor(
dates,
f,
plotData,
norm=LogNorm(vmin=plotData.min(), vmax=plotData.max()),
cmap=colorbar2dSpectra(),
)
cb = plt.colorbar()
cb.ax.tick_params(labelsize=plotfonts["axisTicks"])
# set axis limits
ax.set_ylim(0, specReader.getSampleFreq() / 2.0)
ax.set_xlim([dates[0], dates[-1]])
if isMagnetic(chan):
plt.title("Amplitude {} [nT]".format(chan), fontsize=plotfonts["title"])
else:
plt.title("Amplitude {} [mV/km]".format(chan), fontsize=plotfonts["title"])
ax.set_ylabel("Frequency [Hz]", fontsize=plotfonts["axisLabel"])
ax.set_xlabel("Time", fontsize=plotfonts["axisLabel"])
# set tick sizes
for label in ax.get_xticklabels() + ax.get_yticklabels():
label.set_fontsize(plotfonts["axisTicks"])
plt.grid(True)
# plot format
fig.autofmt_xdate(rotation=90, ha="center")
fig.tight_layout(rect=[0.02, 0.02, 0.96, 0.92])
# plot show and save
if options["save"]:
impath = projData.imagePath
filename = "spectraSection_{}_{}_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 viewSpectra(
projData: ProjectData, site: str, meas: str, **kwargs
) -> Union[plt.figure, None]:
"""View spectra 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
plotwindow : int, str, Dict, optional
Windows to plot (local). If int, the window with local index plotwindow will be plotted. If string and "all", all the windows will be plotted if there are less than 20 windows, otherwise 20 windows throughout the whole spectra dataset will be plotted. If a dictionary, needs to have start and stop to define a range.
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.
"""
options = {}
options["chans"]: List[str] = []
options["declevel"]: int = 0
options["plotwindow"]: Union[int, Dict, str] = [0]
options["specdir"]: str = projData.config.configParams["Spectra"]["specdir"]
options["show"]: bool = True
options["save"]: bool = False
options["plotoptions"]: Dict = plotOptionsSpec()
options = parseKeywords(options, kwargs)
projectText("Plotting spectra for measurement {} and site {}".format(meas, site))
specReader = getSpecReader(projData, site, meas, **options)
# channels
dataChans = specReader.getChannels()
if len(options["chans"]) > 0:
dataChans = options["chans"]
numChans = len(dataChans)
# get windows
numWindows = specReader.getNumWindows()
sampleFreqDec = specReader.getSampleFreq()
# get the window data
windows = options["plotwindow"]
if isinstance(windows, str) and windows == "all":
if numWindows > 20:
windows = list(
np.linspace(0, numWindows, 20, endpoint=False, dtype=np.int32)
)
else:
windows = list(np.arange(0, numWindows))
elif isinstance(windows, int):
windows = [windows] # if an integer, make it into a list
elif isinstance(windows, dict):
windows = list(np.arange(windows["start"], windows["stop"] + 1))
# create a figure
plotfonts = options["plotoptions"]["plotfonts"]
cmap = colorbarMultiline()
fig = plt.figure(figsize=options["plotoptions"]["figsize"])
for iW in windows:
if iW >= numWindows:
break
color = cmap(iW/numWindows)
winData = specReader.readBinaryWindowLocal(iW)
winData.view(
fig=fig,
chans=dataChans,
label="{} to {}".format(
winData.startTime.strftime("%m-%d %H:%M:%S"),
winData.stopTime.strftime("%m-%d %H:%M:%S"),
),
plotfonts=plotfonts,
color=color,
)
st = fig.suptitle(
"Spectra plot, site = {}, meas = {}, fs = {:.2f} [Hz], decimation level = {:2d}".format(
site, meas, sampleFreqDec, options["declevel"]
),
fontsize=plotfonts["suptitle"],
)
st.set_y(0.98)
# put on axis labels etc
for idx, chan in enumerate(dataChans):
ax = plt.subplot(numChans, 1, idx + 1)
plt.title("Amplitude {}".format(chan), fontsize=plotfonts["title"])
if len(options["plotoptions"]["amplim"]) == 2:
ax.set_ylim(options["plotoptions"]["amplim"])
ax.set_xlim(0, specReader.getSampleFreq() / 2.0)
plt.grid(True)
# fig legend and formatting
ax = plt.gca()
h, l = ax.get_legend_handles_labels()
fig.tight_layout(rect=[0.02, 0.02, 0.77, 0.92])
# legend axis
legax = plt.axes(position=[0.77, 0.02, 0.23, 0.88], in_layout=False)
plt.tick_params(left=False, labelleft=False, bottom=False, labelbottom="False")
plt.box(False)
legax.legend(h, l, loc="upper left", fontsize=plotfonts["legend"])
# plot show and save
if options["save"]:
impath = projData.imagePath
filename = "spectraData_{}_{}_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