3.7.8.4.8. Database Coefficient Histogram Plots¶
The "SweepCoeffHist"
class of subfigure is used to plot histograms or range
histograms of any database coefficient. Users can create a histogram of the
raw data or a histogram of the deltas to another database. A “range” histogram
is only defined when there is a Target database, and it plots a histogram of
the absolute values of the deltas.
- S:
dict
Dictionary of settings for SweepCoeffHist subfigure
- Type: {
"SweepCoeffHist"
} |str
Subfigure type
- Header: {
""
} |str
Heading placed above subfigure (bold, italic)
- Position:
"t"
|"c"
| {"b"
}Vertical alignment of subfigure
- Alignment:
"left"
| {"center"
}Horizontal alignment
- Width: {
0.5
} |float
Width of subfigure as a fraction of page text width
- FigWidth: {
6.0
} |float
Width of figure internally to Python; affects aspect ratio of figure and font size when integrated into report; decrease this parameter to make text appear larger in report
- FigHeight: {
4.5
} |float
Similar to FigWidth and primarily used to set aspect ratio
- Component: {
"entire"
} |str
|list
Component or list of components to plot, must be name(s) of components defined in
Config.xml
- Coefficient:
"CA"
|"CY"
| {"CN"
} |str
Name of coefficient to plot, any database value
- Target: {
None
} |str
Name of target database to which to compare each point
- TargetLabel:
str
Name of the target to use in legend
- Format: {
"pdf"
} |"svg"
|"png"
|str
Format of graphic file to save
- DPI: {
150
} |int
Resolution (dots per inch) if saved as a raster format
- StandardDeviation: {
3.0
} |float
If nonzero, plot the value StandardDeviation above and below the mean value on the histogram
- OutlierSigma: {
4.0
} |float
Multiple of standard deviation to use as filter for outlier data
- Range: {
4.0
} |None
|float
Multiple of standard deviation; manually-specified plot range
- Delta: {
0.0
} |float
Fixed value to plot for scale reference between histograms
- PlotMean: {
True
} |False
Whether or not to plot vertical line
- PlotGaussian:
True
| {False
}Whether or not to plot curve representing idealized normal distribution
- HistOptions: {
{"facecolor": "c", "bins": 20}
} |dict
Options passed to
pyplot.hist()
- MeanOptions: {
{"color": "k", "lw": 2}
} |dict
Plot options for the vertical line of the mean value
- DeltaOptions: {
{"color": "r", "ls": "--"}
} |dict
Plot options for vertical fixed-range lines
- GaussianOptions: {
{"color":"navy", "lw": 1.5}
} |dict
Options for plot of ideal normal distribution
- StDevOptions: {
{"color":"b"}
} |dict
Plot options for vertical line showing multiple of standard deviation
- ShowMu: {
True
} |False
Prints value of mean value in upper right corner of plot
- ShowSigma:
True
| {False
}Prints value of standard deviation in upper left corner
- ShowDelta:
True
| {False
}Prints value of fixed width in upper right corner
- MuFormat: {
"%.4f"
} |str
Format flag for value of mean printed via ShowMu
- SigmaFormat: {
"%.4f"
} |str
Format flag for value of mean printed via ShowSigma
- DeltaFormat: {
"%.4f"
} |str
Format flag for value of mean printed via ShowDelta
- SigmaLabel:
str
Label for standard deviation printed using ShowSigma