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def projFigure(vol, limits, plDims=[16,10,5], zscale=5, colors='gray',title=None):
        
    x,y,z = plDims
    grid = (y+z,x+z)
    zRat = zscale*(float(y)/z)
    plt.figure(figsize=grid[-1::-1])   
    
    # plot the x-y view (top-down)
    ax1 = plt.subplot2grid(grid,(0,0),rowspan=y,colspan=x)    
    plt.imshow(vol.max(0) + vol.min(0),clim=limits,cmap=colors,origin='leftcorner',interpolation='Nearest')

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from numpy import where,array,meshgrid, vstack
from matplotlib.path import Path

def getInteriorPoints(coords):
    """
    Given a list of pairs of points which define a polygon, return a list of pairs of points interior to the polygon
    """
    bounds = array(coords).astype('int')

    bMax = bounds.max(0)

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Done saving /tier2/ahrens/davis/data/spark/20150217/7dpf_gfap_gc6f_misha_omr_photo_20150217_202934/mat/mxProj_z_2-9
15/02/25 20:20:50 ERROR TaskSchedulerImpl: Lost executor 0 on h05u09.int.janelia.org: remote Akka client disassociated
15/02/25 20:20:50 ERROR SparkDeploySchedulerBackend: Asked to remove non-existent executor 0
15/02/25 20:20:50 ERROR SparkDeploySchedulerBackend: Asked to remove non-existent executor 0
15/02/25 20:21:36 ERROR TaskSchedulerImpl: Lost executor 1 on h07u27.int.janelia.org: remote Akka client disassociated
15/02/25 20:21:36 ERROR SparkDeploySchedulerBackend: Asked to remove non-existent executor 1
15/02/25 20:21:36 ERROR SparkDeploySchedulerBackend: Asked to remove non-existent executor 1
15/02/25 20:34:20 ERROR TaskSetManager: Task 10634 in stage 56.0 failed 4 times; aborting job
---------------------------------------------------------------------------
Py4JJavaError                             Traceback (most recent call last)

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def bz2compress(raw_fname, wipe=False, overwrite=False):
    """
    :param raw_fname: string, full path of file to be compressed
    :param wipe: bool, optional. If set to True, raw file will be deleted after compression. Defaults to False.
    :param overwrite: bool, optional. If set to True, overwrites file sharing name of output file. Defaults to False
    :return:
    """

    import bz2
    import os

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# test all matplotlib colormaps for a given image

# the image to plot
toPlot = vol[-1]
fName = '/Users/bennettd/Dropbox/media/imag/all_mpl_cmaps.png'

cmaps = 'Spectral, summer, coolwarm, Wistia_r, pink_r, Set1, Set2, Set3, brg_r, Dark2, prism, PuOr_r, afmhot_r, terrain_r, PuBuGn_r, RdPu, gist_ncar_r, gist_yarg_r, Dark2_r, YlGnBu, RdYlBu, hot_r, gist_rainbow_r, gist_stern, PuBu_r, cool_r, cool, gray, copper_r, Greens_r, GnBu, gist_ncar, spring_r, gist_rainbow, gist_heat_r, Wistia, OrRd_r, CMRmap, bone, gist_stern_r, RdYlGn, Pastel2_r, spring, terrain, YlOrRd_r, Set2_r, winter_r, PuBu, RdGy_r, spectral, rainbow, flag_r, jet_r, RdPu_r, gist_yarg, BuGn, Paired_r, hsv_r, bwr, cubehelix, Greens, PRGn, gist_heat, spectral_r, Paired, hsv, Oranges_r, prism_r, Pastel2, Pastel1_r, Pastel1, gray_r, jet, Spectral_r, gnuplot2_r, gist_earth, YlGnBu_r, copper, gist_earth_r, Set3_r, OrRd, gnuplot_r, ocean_r, brg, gnuplot2, PuRd_r, bone_r, BuPu, Oranges, RdYlGn_r, PiYG, CMRmap_r, YlGn, binary_r, gist_gray_r, Accent, BuPu_r, 

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# from thunder/rdds/timeseries.py
# found at https://github.com/thunder-project/thunder/blob/b15ba0a38642312d597a98643cf3514e2d46b69d/thunder/rdds/timeseries.py

def normalize(self, baseline='percentile', window=None, perc=20):
        """
        Normalize each time series by subtracting and dividing by a baseline.
        Baseline can be derived from a global mean or percentile,
        or a smoothed percentile estimated within a rolling window.
        Parameters
        ----------

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# from thunder/rdds/timeseries.py
# found at https://github.com/thunder-project/thunder/blob/b15ba0a38642312d597a98643cf3514e2d46b69d/thunder/rdds/timeseries.py

def normalize(self, baseline='percentile', window=None, perc=20):
        """
        Normalize each time series by subtracting and dividing by a baseline.
        Baseline can be derived from a global mean or percentile,
        or a smoothed percentile estimated within a rolling window.
        Parameters
        ----------

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# Convert a list of (k,v) pairs into an array
def kvp_to_array(dims, data, ind=0, baseline=0):
    vol = np.zeros(dims,dtype=data[0][1].dtype) + np.array(baseline).astype(data[0][1].dtype)
    
    for k,v in data:
        # check if data contains a single value or an iterable
        if hasattr(v,'__iter__'):
            vol[k] = v[ind]
        else:
            vol[k] = v

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import matplotlib.pyplot as plt
from ipywidgets import interact
%matplotlib inline

def browse_images(im):
    n = len(im)
    def view_image(i):
        plt.figure()
        plt.imshow(im[i])
        plt.show()

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%%html
<script>
    var code_show=true; //true -> hide code at first

    function code_toggle() {
        $('div.prompt').hide(); // always hide prompt

        if (code_show){
            $('div.input').hide();
        } else {