Spyrit

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spyrit.core
* General changes
* The input and output shapes have been standardized across operators. All still images (i.e. not videos) have shape `(*, h, w)`, where `*` is any batch dimension (e.g. batch size and number of channels), and `h` and `w` are the height and width of the image. All measurements have shape `(*, M)`, where `*` is the same batch dimension than the images they come from. Videos have shape `(*, t, c, h, w)` where `t` is the time dimension, representing the number of frames in the video, `c` is the number of channels. Dynamic measurements from videos will thus have shape `(*, c, M)`.
* The overall use of gpu has been improved. Every class of the `core` module now has a method `self.device` that allows to track the device on which its parameters are.
* spyrit.core.meas
* / The regularization value 'L1' has been changed to 'rcond'. The behavior is unchanged but the reconstruction did not correspond to L1 regularization.
* / Fixed .pinv() output shape (it was transposed with some regularisation methods)
* / Fixed some device errors when using cuda with .pinv()
* / The measurement matrix H is now stored with the data type it is given to the constructor (it was previously converted to torch.float32 for memory reasons)
* \+ added in the .pinv() method a diff parameter enabling differentiated reconstructions (subtracting negative patterns/measurements to the positive patterns/measurements), only available for dynamic operators.
* / For HadamSplit, the pinv has been overwritten to use a fast Walsh-Hadamard transform, zero-padding the measurements if necessary (in the case of subsampling). The inverse() method has been deprecated and will be removed in a future release.
* spyrit.core.recon
* \- The class core.recon.Denoise_layer is deprecated and will be removed in a future version
* / The class TikhonovMeasurementPriorDiag no longer uses Denoise_layer and uses instead an internal method to handle the denoising.
* spyrit.core.train
* / load_net() uses the weights_only=True parameter in the torch.load() function. Documentation updated.
* spyrit.core.warp
* / The warping operation (forward method) now has to be performed on (b,c,h,w) input tensors, and returns (b, time, c, h, w) output tensors.
* / The AffineDeformationField does not store anymore the field as an attribute, but is rather generated on the fly. This allows for more efficient memory management.
* / In AffineDeformationField the image size can be changed.
* \+ It is now possible to use biquintic (5th-order) warping. This uses scikit-image's (skimage) warp function, which relies on numpy arrays.

Tutorials
* Tutorial 2 integrated the change from 'L1' to 'rcond'
* All Tutorials have been updated to include the above mentioned changes.

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spyrit.core
* spyrit.core.meas
* / The regularization value 'L1' has been changed to 'rcond'. The behavior is unchanged but the reconstruction did not correspond to L1 regularization.
* spyrit.core.recon
* / The documentation for the class core.recon.Denoise_layer has been clarified.

Tutorials

* Tutorial 2 integrated the change from 'L1' to 'rcond'

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spyrit.core
* spyrit.core.meas
* / The method forward_H has been optimized for the HadamSplit class
* spyrit.core.torch
* \+ Added spyrit.core.torch.fwht that implements in Pytorch the fast Walsh-Hadamard tranform for natural and Walsh ordered tranforms.
* \+ Added spyrit.core.torch.fwht_2d that implements in Pytorch the fast Walsh-Hadamard tranform in 2 dimensions for natural and Walsh ordered tranforms.

spyrit.misc

* spyrit.misc.statistics
* / The function spyrit.misc.statistics.Cov2Var has been sped up and now supports an output shape for non-square images
* spyrit.misc.walsh_hadamard
* / The function spyrit.misc.walsh_hadamard.fwht has been significantly sped up, especially for sequency-ordered walsh-hadamard tranforms.
* \- fwht_torch is now deprecated. Use spyrit.core.torch.fwht instead.
* \- walsh_torch is now deprecated. Use spyrit.core.torch.fwht instead.
* \- walsh2_torch is now deprecated. Use spyrit.core.torch.fwht_2d instead.
* spyrit.misc.load_data
* \+ New function download_girder that downloads files identified by their hexadecimal ID from a url server

Tutorials

* Tutorials 3, 4, 6, 7, 8 now download data from our own servers instead of using google drive and the gdown library. Dependency on gdown library will be fully removed in a future version.

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spyrit.core

* spyrit.core.meas
* \+ For static classes, self.set_H_pinv has been renamed to self.build_H_pinv to match with the dynamic classes.
* \+ The dynamic classes now support bicubic dynamic reconstruction (spyrit.core.meas.DynamicLinear.build_h_dyn()). This uses cubic B-splines.
* spyrit.core.train
* load_net() must take the full path, **with** the extension name (xyz.pth).

Tutorials

* Tutorial 6 has been changed accordingly to the modification of spyrit.core.train.load_net().
* Tutorial 8 is now available.

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spyrit.core
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* / no longer supports numpy.array as input, must use torch.tensor
* spyrit.core.meas
* \- class LinearRowSplit (use LinearSplit instead)
* \+ 3 dynamic classes: DynamicLinear, DynamicLinearSplit, DynamicHadamSplit that allow measurements over time
* spyrit.core.meas.Linear
* \- self.get_H() deprecated (use self.H)
* \- self.H_adjoint (you might want to use self.H.T)
* / constructor argument 'reg' renamed to 'rtol'
* / self.H no longer refers to a torch.nn.Linear, but to a torch.tensor (not callable)
* / self.H_pinv no longer refers to a torch.nn.Linear, but to a torch.tensor (not callable)
* \+ self.__init__() has 'Ord' and 'meas_shape' optional arguments
* \+ self.pinv() now supports lstsq image reconstruction if self.H_pinv is not defined
* \+ self.set_H_pinv(), self.reindex() inherited from spyrit.misc.torch
* \+ self.meas_shape, self.indices, self.Ord, self.H_static
* spyrit.core.meas.LinearSplit
* / [includes changes from Linear]
* / self.P no longer refers to a torch.nn.Linear, but to a torch.tensor (not callable)
* spyrit.core.meas.HadamSplit
* / [includes changes from LinearSplit]
* \- self.__init__() does not need 'meas_shape' argument, it is taken as (h,h)
* \- self.Perm (use self.reindex() instead)
* spyrit.core.noise
* spyrit.core.noise.NoNoise
* \+ self.reindex() inherited from spyrit.core.meas.Linear.reindex()
* spyrit.core.prep
* \- class SplitRowPoisson (was used with LinearRowSplit)
* spyrit.core.recon
* spyrit.core.recon.PseudoInverse
* / self.forward() now has **kwargs that are passed to meas_op.pinv(), useful for lstsq image reconstruction
* \+ spyrit.core.torch
contains torch-specific functions that are commonly used in spyrit.core. Mirrors some spyrit.misc functions that are numpy-specific
* \+ spyrit.core.warp
* \+ class AffineDeformationField
warps an image using an affine transformation matrix
* \+ class DeformationField
warps an image using a deformation field
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spyrit.misc
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* spyrit.misc.matrix_tools
* \- Permutation_Matrix() is deprecated (already defined in spyrit.misc.sampling.Permutation_Matrix())
* spyrit.misc.sampling
* \- meas2img2() is deprecated (use meas2img() instead)
* / meas2img() can now handle batch of images
* \+ sort_by_significance() & reindex() to speed up permutation mattrix multiplication
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