xmipp3.protocols.protocol_movie_gain module

class xmipp3.protocols.protocol_movie_gain.XmippProtMovieGain(**args)[source]

Bases: pwem.protocols.protocol_movies.ProtProcessMovies

Estimate the gain image of a camera, directly analyzing one of its movies.

createOutputStep()[source]
doGainProcess(movieId)[source]
estimateOrientationStep(movieDict)[source]
getArgs(movieFn, movieId, extraArgs='')[source]
getBestGain()[source]
getCurrentGain(movieId)[source]
getFinalGain()[source]
getInputGain()[source]
match_orientation(exp_gain, est_gain)[source]

Calculates the correct orientation of the experimental gain image with respect to the estimated Input: 2 Xmipp Images

normalizeGainStep()[source]
xmipp3.protocols.protocol_movie_gain.applyTransform(imag_array, M, shape)[source]

Apply a transformation(M) to a np array(imag) and return it in a given shape

xmipp3.protocols.protocol_movie_gain.array_zeros_to_median(a, thres=0.01, depth=1)[source]

Return an array, replacing the zeros (values under a threshold) with the median of its surrounding values (with a depth)

xmipp3.protocols.protocol_movie_gain.arrays_correlation_FT(ar1, ar2_ft_conj, normalize=True)[source]

Return the correlation matrix of an array and the FT_conjugate of a second array using the fourier transform

xmipp3.protocols.protocol_movie_gain.invert_array(gain, thres=0.01, depth=1)[source]

Return the inverted array by first converting the values under the threshold to the median of the surrounding

xmipp3.protocols.protocol_movie_gain.rotation(imag, angle, shape, P)[source]

Rotate a np.array and return also the transformation matrix #imag: np.array #angle: angle in degrees #shape: output shape #P: transform matrix (further transformation in addition to the rotation)

xmipp3.protocols.protocol_movie_gain.translation_correction(Loc, shape)[source]

Return translation corrections given the max/min Location and the image shape