Outputs an index I of isolated points from their integer coordinates, XYZ (3, n), and under k-connectivity, k = 6, 18 or 26.
Wrapper for random threshold functions (without connexity constraints)
Parameters : | Y: array of shape (n,) Observations : K: int, :
p: float, lp norm : stop <bool> Stop when minimum is attained (save computation time) : verbose <bool> ‘Chatty’ mode : varwind <bool> Varying window variant (vs. fixed window, with width K) : knownull <bool> :
Returns : ——- : A dictionary D containing the following fields: : “C” (n-K) :
“thresh” <float> Detection threshold : “detect” (k,) Index of detected activations : “v” <float> Estimated null variance (if knownull is False) : |
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Notes
Random thresholding is performed only if null hypothesis of no activations is rejected at level 5%
Wrapper for random threshold functions under connexity constraints
Parameters : | Y (n,) Observations : K <int> :
XYZ (3,n) voxel coordinates : p <float> lp norm : stop <bool> Stop when minimum is attained (save computation time) : verbose <bool> ‘Chatty’ mode : varwind <bool> Varying window variant (vs. fixed window, with width K) : knownull <bool> :
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Returns : | A dictionary D containing the following fields: : “C” (n-K) :
“thresh” <float> Detection threshold : “detect” (ncoeffs,) Index of detected voxels : |
Notes
Random thresholding is performed only if null hypothesis of no activations is rejected at level 5%
Random threshold with fixed window and null gaussian distribution
Parameters : | Y array of shape (n,) :
K, int, Some positive integer :
p, float, lp norm : stop: bool, :
one_sided: bool, :
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Returns : | C array of shape (n-K) :
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Random threshold with fixed-window and gaussian null distribution, using connexity constraint on non-null set.
Parameters : | X (n,): Observations (assumed Gaussian under H0) : XYZ (3,n): voxel coordinates : K <int>: :
p <float>: Lp norm : stop <bool>: Stop when minimum is attained (save computation time) : |
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Returns : | C (n-K): :
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Random threshold with fixed-window and known null distribution
Parameters : | X (n,): Observations (must be Exp(1) under H0) : K <int>: :
p <float>: Lp norm : stop <bool>: Stop when minimum is attained (save computation time) : |
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Returns : | C (n-K): :
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Random threshold with fixed-window and known null distribution, using connexity constraint on non-null set.
Parameters : | X (n,): Observations (must be Exp(1) under H0) : XYZ (3,n): voxel coordinates : K <int>: :
p <float>: Lp norm : stop <bool>: Stop when minimum is attained (save computation time) : |
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Returns : | C (n-K): :
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Wrapper for random threshold functions
Parameters : | Y: array of shape (n,),Observations : K: int, Some positive integer :
XYZ: array of shape (3, n) voxel coordinates. :
p: float, optional, lp norm : varwind: bool, :
knownull: bool, optional, :
stop: bool, optional :
verbose: bool, ‘Chatty’ mode : |
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Returns : | D : dict
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Notes
Random thresholding is performed only if null hypothesis of no activations is rejected at level 5%
Random threshold with fixed window and gaussian null distribution
Parameters : | Y (n,) Observations (assumed Gaussian under H0, with unknown variance) : K <int> :
p <float> lp norm : stop <bool> Stop when minimum is attained (save computation time) : one_sided <bool> :
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Returns : | C (n-K) :
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Random threshold with fixed-window and gaussian null distribution, using connexity constraint on non-null set.
Parameters : | X (n,): Observations (assumed Gaussian under H0) : XYZ (3,n): voxel coordinates : K <int>: :
p <float>: Lp norm : stop <bool>: Stop when minimum is attained (save computation time) : |
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Returns : | C (n-K): :
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Random threshold with varying window and known null distribution
Parameters : | X (n,): Observations (Exp(1) under H0) : K <int>: :
p <float>: lp norm : stop <bool>: Stop when minimum is attained (save computation time) : |
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Returns : | C (n-K) :
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Random threshold with varying window and known null distribution
Parameters : | X (n,): Observations (Exp(1) under H0) : K <int>: :
XYZ (3,n): voxel coordinates : p <float>: lp norm : stop <bool>: Stop when minimum is attained (save computation time) : |
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Returns : | C (n-K) :
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Test statistic of global null hypothesis that all observations have zero-mean
Parameters : | X (n,) : X[j] = -log(1-F(|Y[j]|))
p : Lp norm (<= inf) to use for computing test statistic |
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Returns : | D <float> : test statistic |