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This module is intended to store generic, reusable, sub-classable plot classes to minimize formulaic copying and pasting.
Author: Nickolas Fotopoulos <nvf@gravity.phys.uwm.edu>
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BasicPlot A very default meta-class to almost any plot you might want to make. |
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SimplePlot Exactly what you get by calling pylab.plot(), but with the handy extras of the BasicPlot class. |
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BarPlot A simple vertical bar plot. |
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VerticalBarHistogram Histogram data sets with a common binning, then make a vertical bar plot. |
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NumberVsBinBarPlot Make a bar plot in which the width and placement of the bars are set by the given bins. |
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CumulativeHistogramPlot Cumulative histogram of foreground that also has a shaded region, determined by the mean and standard deviation of the background population coincidence statistics. |
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ImagePlot The equivalent of pylab.imshow(), but with the BasicPlot niceties and some defaults that are more in tune with what a scientist wants -- origin="lower", requiring x and y bins so that we can label axes correctly, and a colorbar. |
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FillPlot Given a list of vertices (passed by x-coords and y-coords), fill the regions (by default with successively darker gray shades). |
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SixStripSeriesPlot Given a time- or frequency-series, plot it across six horizontal axes, stacked on top of one another. |
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ROCPlot Plot the receiver operating characteristic (ROC) based on the foreground and background values from given techniques. |
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QQPlot Plot the global rank versus the self rank, like a Q-Q plot, i.e. |
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SimpleMapPlot Class to create a clickable map html page. |
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Plot3D Exactly what you get by calling pylab.plot(), but with the handy extras of the BasicPlot class. |
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ScatterPlot Exactly what you get from calling pylab.scatter(), but with the handy extras of the BasicPlot class. |
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ColorbarScatterPlot Exactly what you get from calling pylab.scatter() when you want a colorbar, but with the handy extras of the BasicPlot class. |
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PlotSegmentsPlot Horizontal bar segment plot. |
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DQScatterPlot A DQ-formatted scatter plot, with those triggers below some threshold on the colour axis get plotted tiny wee. |
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LineHistogram A simple line histogram plot. |
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SkyPositionsPlot A spherical projection plot. |
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TestSimpleMapPlot |
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_dq_params = {"text.usetex": True, "text.verticalalignment": "
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plot3D_head =
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plot3D_body =
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Convert a floating point number to a latex representation. In particular, scientific notation is handled gracefully: e -> 10^ |
Given a some nested sequences (e.g. list of lists), determine the largest and smallest values over the data sets and determine a common binning. |
Format the string columnName (e.g. xml table column) into latex format for an axis label. Formats known acronyms, greek letters, units, subscripts, and some miscellaneous entries. Examples: >>> display_name('snr') 'SNR' >>> display_name('bank_chisq_dof') 'Bank $\chi^2$ DOF' >>> display_name('hoft') '$h(t)$' Arguments: columnName : str string to format |
Adds a figure colorbar to the given Axes object ax, based on the values found in the mappable object. If visible=True, returns the Colorbar object, otherwise, no return. Arguments: ax : matplotlib.axes.AxesSubplot axes object beside which to draw colorbar Keyword arguments: mappable : [ matplotlib.image.Image | matplotlib.contour.ContourSet... ] image object from which to map colorbar values visible : [ True | False] add colorbar to figure, or simply resposition ax as if to draw one log : [ True | False ] use logarithmic scale for colorbar clim : tuple (vmin, vmax) pair for limits of colorbar label : str label string for colorbar All other keyword arguments will be passed to pylab.colorbar. Logarithmic colorbars can be created by plotting log10 of the data and setting log=True. |
Parser ConfigParser.ConfigParser section for plotting parameters. Returns a dict that can be passed to any plotutils.plot_xxx function in **kwargs form. Set ycolumn to 'hist' or 'rate' to generate those types of plots. Arguments: cp : ConfigParser.ConfigParser INI file object from which to read section : str section name to read for options Basic parseable options: xcolumn : str parameter to plot on x-axis ycolumn : str parameter to plot on y-axis zcolumn : str parameter to plot on z-axis rank-by : str parameter by which to rank elements xlim : list [xmin, xmax] pair for x-axis limits ylim : list [ymin, ymax] pair for y-axis limits zlim : list [zmin, zmax] pair for z-axis limits clim : list [cmin, cmax] pair for colorbar limits logx : [ True | False ] plot x-axis in log scale logy : [ True | False ] plot y-axis in log scale logz : [ True | False ] plot z-axis in log scale Trigger plot options: detchar-style : [ True | False ] use S6-style plotting: low snr triggers small with no edges detchar-style-theshold : float z-column threshold at below which to apply detchar-style Trigger rate plot options: bins : str semi-colon-separated list of comma-separated bins for rate plot Histogram options: cumulative : [ True | False ] plot cumulative counts in histogram rate : [ True | False ] plot histogram counts as rate num-bins : int number of bins for histogram fill : [ True | False ] plot solid colour underneath histogram curve color-bins : str semi-colon-separated list of comma-separated bins for colorbar histogram Data plot options: zero-indicator : [ True | False ] draw vertical dashed red line at t=0 Other options: greyscale : [ True | False ] save plot in black-and-white bbox-inches : 'tight' save figure with tight bounding box around Axes calendar-time : [ True | False ] plot time axis with date and time instead of time from zero. |
Work out renormalisation for the time axis, makes the label more appropriate. Returns unit (in seconds) and string descriptor. Example: >>> time_axis_unit(100) (1, 'seconds') >>> time_axis_unit(604800) (86400, 'days') Arguments: duration : float plot duration to normalise |
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_dq_params
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plot3D_head
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plot3D_body
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