Source code for wfc3tools.pstack


    Plot the stack of MultiAccum sample values for a specified pixel in an
    IR multiaccum image.  Pixels from any of the SCI, ERR, DQ, or TIME image
    extensions can be plotted.  The total number of samples  is determined from
    the primary header keyword NSAMP and all samples (excluding the zeroth
    read) are plotted.  The SCI, ERR, DQ, values are plotted as a function of
    sample time, while TIME values are plotted as a  function  of  sample
    number.   The sample times  are read from the SAMPTIME keyword in the SCI
    header for each readout. If any of the ERR, DQ, SAMP, or TIME extensions
    have null data  arrays,  the value of the PIXVALUE extension header keyword
    is substituted for the pixel values.  The plotted data values can be saved
    to an output text table or printed to the terminal.

    The BUNIT keyword value is used to determine the starting units of the data,
    but you can plot either counts or rate using the optional keyword ``units``.


    >>> from wfc3tools import pstack
    >>> xdata, ydata = pstack('ibh719grq_ima.fits',
    >>> xdata
    array([ 100.651947,   93.470573,   86.2892  ,   79.107826,   71.926453,
             64.745079,   57.563702,   50.382328,   43.200954,   36.019581,
             28.838205,   21.65683 ,   14.475455,    7.29408 ,    0.112705,
              0.      ])
    >>> ydata
    array([ 136.75660802,  151.46077054,  133.8688648 ,  108.50410805,
            109.17918583,   81.5139582 ,   90.26712192,   61.68512157,
             59.11241987,   39.01870227,   32.63157047,   16.07532735,
             33.69198196,   16.90631634,   13.54113704,    0.        ])

.. Warning:

    Note that the arrays are structured in SCI order, so the final exposure is
    the first element in the array.


import os
from import fits
import numpy as np
from matplotlib import pyplot as plt


[docs] def pstack(filename, column=0, row=0, extname="sci", units="counts", title=None, xlabel=None, ylabel=None, plot=True): """ A function to plot the statistics of one pixels up the IR ramp image. Original implementation in the iraf nicmos package. Pixel values here are 0 based, not 1 based. Parameters ---------- filename : str Input MultiAccum image name. This should be either a _ima or _raw file, containing all the data from multiple readouts. You must specify just the file name, with no extension designation. column : int, default=0 The column index of the pixel to be plotted. row : int, default=0 The row index of the pixel to be plotted. extname : str, default="sci" Extension name (EXTNAME keyword value) of data to plot. Allowed values are "sci", "err", "dq", "samp", and "time". units : str, default="counts" Plot "sci" or "err" data in units of counts or countrate ("rate"). Input data can be in either unit; conversion will be performed automatically. Ignored when plotting "dq", "samp", or "time" data. Allowed values are "counts" and "rate". title : str, default=None Title for the plot. If left blank, the name of the input image, appended with the extname and column and row being plotted, is used. xlabel : str, default=None Label for the X-axis of the plot. If left blank, a suitable default is generated. ylabel : str, default=None Label for the Y-axis of the plot. If left blank, a suitable default based on the plot units and the extname of the data is generated. plot : bool, default=True If False, return data and do not plot. Returns ------- xaxis : numpy.ndarray Array of x-axis values that will be plotted. yaxis : numpy.ndarray Array of y-axis values that will be plotted as specified by 'units'. Examples -------- >>> from wfc3tools import pstack >>> inputFilename = 'ibh719grq_ima.fits' >>> x, y = 100, 25 >>> xdata, ydata = pstack(inputFilename, column=x, row=y, extname="sci", units="counts", title="", xlabel="", ylabel="") """ time = False valid_ext = ["sci", "err", "dq", "time"] if extname.lower() not in valid_ext: print("Invalid value given for extname") return 0, 0 with as myfile: nsamp = myfile[0].header["NSAMP"] bunit = myfile[1].header["BUNIT"] # must use data header for units yaxis = np.zeros(nsamp) # plots versus sample for TIME extension if "time" in extname.lower(): xaxis = np.arange(nsamp) + 1 time = True else: xaxis = np.zeros(nsamp) for i in range(1, nsamp, 1): if time: yaxis[i-1] = myfile["SCI", i].header['SAMPTIME'] else: # Numpy is row-major with array indices written row-first # (lexicographical access order) yaxis[i-1] = myfile[extname.upper(), i].data[row, column] xaxis[i-1] = myfile["SCI", i].header['SAMPTIME'] # convert to countrate if "rate" in units.lower() and "/" not in bunit.lower(): exptime = myfile["SCI", i].header['SAMPTIME'] yaxis[i-1] /= exptime # convert to counts if "counts" in units.lower() and "/" in bunit.lower(): exptime = myfile["SCI", i].header['SAMPTIME'] yaxis[i-1] *= exptime if not ylabel: if "rate" in units.lower(): if "/" in bunit.lower(): ylabel = bunit else: ylabel = bunit+" per second" else: if "/" in bunit: stop_index = bunit.find("/") ylabel = bunit[:stop_index] else: ylabel = bunit if plot: plt.clf() plt.ylabel(ylabel) if not xlabel and time: plt.xlabel("Sample Number") if not xlabel and not time: plt.xlabel("Sample time") if not title: title = "%s Pixel stack for col=%d, row=%d" % (filename, column, row) plt.title(title) if time: plt.xlim(np.max(xaxis), np.min(xaxis)) plt.ylabel("Seconds") plt.plot(xaxis, yaxis, "+") plt.draw() return xaxis, yaxis