processing_library/arrays/cleaners.py
def update_moment_model(m_model, scalestack, lhs, rhs, gain, mscale, mval):
    """Update model with an appropriately scaled and centered blob for each moment

    """
    # Lines 28 - 33 of Algorithm 1
    nmoment, _, _ = m_model.shape
    for t in range(nmoment):
        # Line 29 of Algorithm 1. Note that the convolution is implemented here as an
        # appropriate shift.
        m_model[t, lhs[0]:lhs[1], lhs[2]:lhs[3]] += \
            scalestack[mscale, rhs[0]:rhs[1], rhs[2]:rhs[3]] * gain * mval[t]

    return m_model
Update model with an appropriately scaled and centered blob for each moment

    
Update model with an appropriately scaled and centered blob for each moment
Update model with an appropriately scaled and centered blob for each moment
def update_moment_model(m_model, scalestack, lhs, rhs, gain, mscale, mval):
    nmoment, _, _ = m_model.shape
    for t in range(nmoment):
        m_model[t, lhs[0]:lhs[1], lhs[2]:lhs[3]] += \
            scalestack[mscale, rhs[0]:rhs[1], rhs[2]:rhs[3]] * gain * mval[t]
    return m_model
def update_moment_model ( m_model , scalestack , lhs , rhs , gain , mscale , mval ) : nmoment , _ , _ = m_model . shape for t in range ( nmoment ) : m_model [ t , lhs [ 0 ] : lhs [ 1 ] , lhs [ 2 ] : lhs [ 3 ] ] += scalestack [ mscale , rhs [ 0 ] : rhs [ 1 ] , rhs [ 2 ] : rhs [ 3 ] ] * gain * mval [ t ] return m_model
Update model with an appropriately scaled and centered blob for each moment
Update model with an appropriately scaled and centered blob for each moment
"""Update model with an appropriately scaled and centered blob for each moment

    """ # Lines 28 - 33 of Algorithm 1 # Line 29 of Algorithm 1. Note that the convolution is implemented here as an # appropriate shift.
m_model
scalestack
lhs
rhs
gain
mscale
mval