neurotools.obsolete.gpu.cu.statistics module
Contains statistical routines. All routines assume float32 arrays as the underlying datatype.
- neurotools.obsolete.gpu.cu.statistics.gpusdv(a, b)
Computes elementwise squared deviation from a constant value. For example, gpusdev(data,c) will return the squared distance of all elements in data from c. This is a slightly better way of writing (data-c)**2 as it avoids an intermediate array creation and copy
- neurotools.obsolete.gpu.cu.statistics.gpumean(v)
Computes the population mean of a float vector on the GPU
- neurotools.obsolete.gpu.cu.statistics.gpucenter(v)
Mean-centers a vector on the GPU
- neurotools.obsolete.gpu.cu.statistics.gpusqmag(v)
Computes the squared magnitude of a vector
- neurotools.obsolete.gpu.cu.statistics.gpumag(x)
Computes the magnitude of a vector
- neurotools.obsolete.gpu.cu.statistics.gpusqdev(v)
Computes the sum of squared deviation from mean for a vector
- neurotools.obsolete.gpu.cu.statistics.gpuvar(v)
Computes the population variance of a vector
- neurotools.obsolete.gpu.cu.statistics.gpusvar(v)
Computes the sample variance of a vector
- neurotools.obsolete.gpu.cu.statistics.gpustd(x)
Computes the population standard deviation of a vector
- neurotools.obsolete.gpu.cu.statistics.gpusstd(x)
Computes the sample standard deviation of a vector
- neurotools.obsolete.gpu.cu.statistics.gpucov(a, b)
Computes the covariance of two vectors.
- neurotools.obsolete.gpu.cu.statistics.gpucorr(a, b)
Computes the correlation coefficient between two vectors
- neurotools.obsolete.gpu.cu.statistics.gpuscov(a, b)
Computes the sample covariance of two vectors
- neurotools.obsolete.gpu.cu.statistics.gpuscorr(a, b)
Computes the sample correlation of two vectors
- neurotools.obsolete.gpu.cu.statistics.gpusem(v)
Computes the standard error of mean for a vector
- neurotools.obsolete.gpu.cu.statistics.gpuzscore(v)
Computes the z-scores for a vector using sample statistics
- neurotools.obsolete.gpu.cu.statistics.gpubarlinedata(xdata, ydata, bins, minval=None, maxval=None)[source]
- neurotools.obsolete.gpu.cu.statistics.sebarline(datasets, bins, min=None, max=None, lx='', ly='', title='')[source]
- neurotools.obsolete.gpu.cu.statistics.gpuhistogram(xdata, ydata, bins, minval=None, maxval=None)[source]
- neurotools.obsolete.gpu.cu.statistics.sdgpubarlinedata(xdata, ydata, bins, minval=None, maxval=None)[source]
- neurotools.obsolete.gpu.cu.statistics.sdbarline(datasets, bins, min=None, max=None, lx='', ly='', title='')[source]
- neurotools.obsolete.gpu.cu.statistics.gpubin(size)