neurotools.obsolete.gpu.cu.sequence module

neurotools.obsolete.gpu.cu.sequence.GPUSequenceAutoDetect(distances, t, thresh)[source]
neurotools.obsolete.gpu.cu.sequence.GPUPointAutoDistance(t, k, n, data)[source]

limit to 5-13k timestep for 256x256 sim

Parameters:

  • t (int) – length of data in time

  • k (int) – number of time bins to use

  • n (int) – size of vector datapoints

  • data (int) – t*n data matrix, n is inner dimension

neurotools.obsolete.gpu.cu.sequence.GPUAutometric(t, n, data)[source]

limit to 5-13k timestep for 256x256 sim

Parameters:

  • t (int) – length of data in time

  • k (int) – number of time bins to use

  • n (int) – size of vector datapoints

  • data (int) – t*n data matrix, n is inner dimension

neurotools.obsolete.gpu.cu.sequence.GPUMagmetric(t, n, data)[source]

limit to 5-13k timestep for 256x256 sim

Parameters:

  • t (int) – length of data in time

  • k (int) – number of time bins to use

  • n (int) – size of vector datapoints

  • data (int) – t*n data matrix, n is inner dimension

neurotools.obsolete.gpu.cu.sequence.GPUDotmetric(t, n, data)[source]

limit to 5-13k timestep for 256x256 sim

Parameters:

  • t (int) – length of data in time

  • k (int) – number of time bins to use

  • n (int) – size of vector datapoints

  • data (int) – t*n data matrix, n is inner dimension

neurotools.obsolete.gpu.cu.sequence.deltamag(t, data)[source]
neurotools.obsolete.gpu.cu.sequence.summag(t, data)[source]
neurotools.obsolete.gpu.cu.sequence.gpuderivative(i)[source]
neurotools.obsolete.gpu.cu.sequence.gpusmooth(rad, data)[source]
neurotools.obsolete.gpu.cu.sequence.gputhing(rad, data)[source]
neurotools.obsolete.gpu.cu.sequence.mulmag(t, data)[source]
neurotools.obsolete.gpu.cu.sequence.FrameEater(filename, maxframes=None)[source]

TODO: document

file format : list of float images width height frames

first frame as tab delimited floats on one line

next frame

and so on

end file

neurotools.obsolete.gpu.cu.sequence.gpusubsetmean(p, d)[source]
neurotools.obsolete.gpu.cu.sequence.gpusubsetgfit(p, d)[source]
neurotools.obsolete.gpu.cu.sequence.gpunpdf(m, s, d)[source]
neurotools.obsolete.gpu.cu.sequence.gpulognpdf(m, s, d)[source]
neurotools.obsolete.gpu.cu.sequence.fitgaussbimodal(gpupoints, steps)[source]
neurotools.obsolete.gpu.cu.sequence.fitgausstrimodal(gpupoints, steps)[source]