neuroprob/utils/stats.py
def cdf_count_deq(n, deq, count_prob, N_MAX=100):
    """
    Compute the dequantized cdf count.
    
    :param int n: integer spike count
    :param float deq: dequantization noise
    :param LambdaFunction count_prob: 
    """
    N = np.arange(n+1)
    C = count_prob(N)
    cdf = C[:n].sum() + deq*C[n]
    return cdf

    Compute the dequantized cdf count.
    
    :param int n: integer spike count
    :param float deq: dequantization noise
    :param LambdaFunction count_prob: 
    
Compute the dequantized cdf count.
Compute the dequantized cdf count .
def cdf_count_deq(n, deq, count_prob, N_MAX=100):
    N = np.arange(n+1)
    C = count_prob(N)
    cdf = C[:n].sum() + deq*C[n]
    return cdf
def cdf_count_deq ( n , deq , count_prob , N_MAX = 100 ) : N = np . arange ( n + 1 ) C = count_prob ( N ) cdf = C [ : n ] . sum ( ) + deq * C [ n ] return cdf
Compute the dequantized cdf count.
Compute the dequantized cdf count .
"""
    Compute the dequantized cdf count.
    
    :param int n: integer spike count
    :param float deq: dequantization noise
    :param LambdaFunction count_prob: 
    """
n
integer spike count
integer spike count
deq
None
count_prob
None
N_MAX