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%matplotlib
import numpy as np
import dmdd


    

    




Using matplotlib backend: MacOSX

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dmdd.Nexpected?


    

In [146]:

    

def plotfunction(element, Qmin, Qmax, binsize, exposure): #efficiency= fsdfsdfsdfsd binsize is number you want to count by
    #auto pass efficiency function
    binnumber = (Qmax - Qmin)/binsize
    binlist = np.arange(Qmin, Qmax+binsize, binsize) #includes the last point
    print binlist 
    print binnumber
    
    for 
    
    """# example data
    mu = 100 # mean of distribution
    sigma = 15 # standard deviation of distribution
    x = mu + sigma * np.random.randn(10000)
    num_bins = binnumber
    # the histogram of the data
    n, bins, patches = plt.hist(x, num_bins, normed=1, facecolor='green', alpha=0.5)
    # add a 'best fit' line
    y = mlab.normpdf(bins, mu, sigma)
    plt.plot(bins, y, 'r--')
    plt.xlabel('Energy of Events')
    plt.ylabel('Number of Expected Events')
    plt.title(r'Histogram of Dark Matter Energies')
    # Tweak spacing to prevent clipping of ylabel
    plt.subplots_adjust(left=0.15)
    plt.show()"""


    
    #dmdd.Nexpected(element, Qmin, Qmax, exposure,) #efficiency


    

In [148]:

    

plotfunction(1, 5, 50, 5, 1)
plt.show()


    

    




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