The hippoplotter.py module

Here is a summary of the classes and functions available in this module.

• newNTuple(arrays, labels, name="", register=1)
  Define and register a new hippo n-tuple. arrays is a tuple or list of numeric sequences (all the same length), and labels is a tuple or list of the labels to be applied to each sequence.

• addNTuple(nt, key="")
  Add an existing hippo n-tuple to hippoplotter's internal list.

• getDisplay()
  Returns the handle to the selected display.

• getDisplays()
  Returns a tuple of handles to all of the displays on the canvas.

Each of the plotting functions can use either the hippo n-tuple or be passed sequences as arguments. The former type of functions has capitalization appropriate for proper names. For example,

• Histogram(nt, xname, xlog=0, ylog=0, xrange=(), yrange=(), title="", pointRep="Column", oplot=0, color=None)
  Create a histogram of the values in the xname column of the n-tuple nt.

• histogram(x, xname='x', xlog=0, ylog=0, xrange=(), yrange=(), title="", pointRep="Column", oplot=0, color=None)
  Create a histogram of the values in x, which can be any kind of sequence (e.g., tuple, list, or flat numarray) of floats or integers.

Hereafter, we give only the signature and descriptions, when necessary, of the n-tuple versions of these plotting functions:

• YPlot(nt, yname, xlog=0, ylog=0, xrange=(), yrange=(), title="", pointRep="Symbol", oplot=0, color=None)

• Scatter(nt, xname, yname, xlog=0, ylog=0, xrange=(), yrange=(), title="", pointRep="Symbol", oplot=0, color=None)

• XYPlot(nt, xname, yname, xerr=None, yerr=None, xlog=0, ylog=0, xrange=(), yrange=(), title="", pointRep="Symbol", oplot=0, color=None)

• StripChart(nt, xname, yname, xlog=0, ylog=0, xrange=(), yrange=(), title="", pointRep="Line", oplot=0, color=None)

• Profile(nt, xname, yname, xlog=0, ylog=0, xrange=(), yrange=(), pointRep="Symbol", title="", oplot=0, color=None)

• XYHist(nt, xname, yname, xbinsize=0, ybinsize=0, xrange=(), yrange=(), xlog=0, ylog=0, Aitoff=0, title="", pointRep="ColorBox", oplot=0)
  HippoDraw's Color Plot.

• Contour(nt, xname, yname, xbinsize=0, ybinsize=0, xrange=(), yrange=(), xlog=0, ylog=0, Aitoff=0, title="", pointRep="Contour", oplot=0)

• Image(nt, zlog=0, aspect=0, transform=None, title="")
  HippoDraw's Z Plot, assuming nt has only one column.

• fitsImage(fits_image, zlog=0, aspect=0, transform=None, title="")
  Create an image display using Image, reading the data from the FITS file fits_image. fits_image can also be a FitsImage object.

• class FitsImage(file)
file is the filename of a FITS image file. This is a thin wrapper to a pyfits object, providing a single column hippo n-tuple of the image data and a method, getKeyVal, to access the primary image keyword values.

• FitsNTuple(fitsFiles, extension=1, name="")
  This wraps the FitsNTuple.FitsNTuple class, which reads in FITS files and creates a hippo n-tuple of the FITS columns and a FitsNTuple object that has numarrays of each FITS column as attributes. fitsFiles can either be the filename of a single FITS file or a tuple or list of FITS files, all having the same format.

• class StaticHist(xrange=(-1, 1), xBinWidth = 0.1, title="", xlabel="", color=None)
  This class wraps HippoDraw's Static Histogram display and delegates directly to the filling methods of the Static Histogram objects.

• class Static2DHist(xrange=(-1, 1), yrange=(-1, 1), xBinWidth=0.1, yBinWidth=0.1, title="", xlabel="", ylabel="")
  This class wraps HippoDraw's Static 2D Histogram class.

• setCut()
  This function allows the user to set the cut boundaries by right clicking at the end points of the range on a Cut display. To exit the setCut mode, the user must click on an empty part of the canvas.

• dragCut()
  This allows the user to set the center of an existing cut by right clicking on a Cut display.

• resize(restore=None)
  This function allows the user to set the plot limits by right clicking on opposite corners of the rectangular region defining the new plot limits. If a non-None restore argument is provided, then right clicking a display will restore its plot limits to the values it had when the display was created.

• fitData(display, funcName)
  This will apply and fit a hippo function, e.g., "PowerLaw", to the dataRep in the specified display. It returns a tuple of dictionaries of parameter values and error estimates and the handle to the function itself:

    >>> (params, errors, func) = fitData(display, "PowerLaw")
    >>> print "%.2e +/- %.2e" % (params["Index"], errors["Index"])
    -1.78e+00 +/- 5.93e-03
    

• slopes()
  This allows the user to estimate slopes, exponential scales, or power-law indices of displayed data without having to go through the fitter. Right clicking at two points on a display will cause a straight line to be drawn connecting the points; the slope, scale factor, or power-law index appropriate for that line will be printed, depending on whether the axes are both linear, log-linear, or log-log, respectively. This mode is exited by clicking on an empty part of the canvas.

• hline(y=None)
  This will draw a horizontal line on the selected display at y, if it is given. If y is not given, then the line will be drawn at the location given by a right-click on any display.

• vline(x=None)
  See hline.

• pickData()
  This allows the user to pick data values from a display by right clicking. The locations are printed, and a hippo n-tuple containing the pick data is returned. Once a display is selected by the initial right-click, only pick data from that display is extracted. Clicking on an empty portion of the canvas exits from the pickData mode.

• clear()
  This clears all displays from the canvas.

• prompt(prompt=None)
  Useful for writing interactive scripts, this prompts the user for input.

• setParam(target, value, func)
  This wraps the setParameters method of hippo function objects and allows a single parameter to be set:

    >>> setParam("Index", -2.1, pl)
    

• setFixed(targets, func)
  This wraps the setFixedFlags method of hippo function objects, allowing the user to pass a tuple of parameter names that he/she wishes to fix:

    >>> setFixed(("Prefactor", "Index"), pl)
    

---