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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def get_histogram( xall, yall, nbins=100, weights=None, avoid_zero_count=False):
 """Compute a two-dimensional histogram. Parameters xall : ndarray(T) Sample x-coordinates. yall : ndarray(T) Sample y-coordinates. nbins : int, optional, default=100 Number of histogram bins used in each dimension. weights : ndarray(T), optional, default=None Sample weights; by default all samples have the same weight. avoid_zero_count : bool, optional, default=True Avoid zero counts by lifting all histogram elements to the minimum value before computing the free energy. If False, zero histogram counts would yield infinity in the free energy. Returns ------- x : ndarray(nbins, nbins) The bins' x-coordinates in meshgrid format. y : ndarray(nbins, nbins) The bins' y-coordinates in meshgrid format. z : ndarray(nbins, nbins) Histogram counts in meshgrid format. """

    z, xedge, yedge = _np.histogram2d(
        xall, yall, bins=nbins, weights=weights)
    x = 0.5 * (xedge[:-1] + xedge[1:])
    y = 0.5 * (yedge[:-1] + yedge[1:])
    if avoid_zero_count:
        z = _np.maximum(z, _np.min(z[z.nonzero()]))
    return x, y, z.T