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Poetry fix #126

Merged
merged 2 commits into from
May 13, 2024
Merged

Poetry fix #126

merged 2 commits into from
May 13, 2024

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EthanMarx
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@EthanMarx EthanMarx merged commit df1ebdc into ML4GW:dev May 13, 2024
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@EthanMarx EthanMarx deleted the poetry-fix branch May 13, 2024 19:41
EthanMarx added a commit that referenced this pull request May 13, 2024
* re-implement distributions using torch.distributions (#110)

* loosely re-implement distributions using torch.distributions

* further enhancement

* rename

* log_uniform as transformed dist

* delete uniform and log_normal since they are already implemented

* bring back LogNormal, change parameter sampler

* add delta function distribution, minor fixes to other distributions

* fix

* Initial commit of q-transform

* Added a MultiQTransform

* Reparameterized to number of t and f bins

* Re-factored SingleQTransform to allow for eventually using different q's for batch/channels

* Changed interpolation to better match gwpy and added option to specify frequency range in which to search for max energy tile

* Added QScan to __init__

* Changed from torch median to quantile to match numpy median

* Added documentation to qtransform

* Added gwpy to dev dependencies

* Added tests and corrected get_freqs bug

* Changed method of normalization and updated documentation

* Updated more documentation and changed interpolation method

* Changed how interpolation shape is parameterized

* Reverted documentation to state expectation of 3D input

* Fixed type hint for spectrogram_shape in qtransform

* Switched tuple to Tuple

* `InMemoryDataset` improvements (#119)

* in memory dataset inherits from torch iterable dataset

* pre-commit issues

* fix yielding logic

* fix in memory dataset tests

* handle deprecated transpose ops in phenomd (#120)

* Torch dependency fix into dev (#124)

* udpate poetry lock

* increment version once more

* re add gwpy dev dep

* update poetry lock

* fix poetry conflic

* fix poety conflict

* Poetry fix (#126)

* remove gwpy dep for now

* poetry lock file

---------

Co-authored-by: Deep Chatterjee <[email protected]>
Co-authored-by: wbenoit26 <[email protected]>
Co-authored-by: William Benoit <[email protected]>
Co-authored-by: William Benoit <[email protected]>
EthanMarx added a commit that referenced this pull request May 14, 2024
* Adding funding statement

* Add requirements to docs (#107)

* add requirements to docs

* remove myst_parser req

* Update requirements.txt

* Update conf.py

* Update docs.yaml (#108)

* Update docs.yaml

* Update docs.yaml (#109)

* simplify torch dependencies (#122)

* simplify torch dependency

* remove python constratints

* fix pre-commit

* Merge `dev` into `main` for 0.4.2 release (#123)

* re-implement distributions using torch.distributions (#110)

* loosely re-implement distributions using torch.distributions

* further enhancement

* rename

* log_uniform as transformed dist

* delete uniform and log_normal since they are already implemented

* bring back LogNormal, change parameter sampler

* add delta function distribution, minor fixes to other distributions

* fix

* Initial commit of q-transform

* Added a MultiQTransform

* Reparameterized to number of t and f bins

* Re-factored SingleQTransform to allow for eventually using different q's for batch/channels

* Changed interpolation to better match gwpy and added option to specify frequency range in which to search for max energy tile

* Added QScan to __init__

* Changed from torch median to quantile to match numpy median

* Added documentation to qtransform

* Added gwpy to dev dependencies

* Added tests and corrected get_freqs bug

* Changed method of normalization and updated documentation

* Updated more documentation and changed interpolation method

* Changed how interpolation shape is parameterized

* Reverted documentation to state expectation of 3D input

* Fixed type hint for spectrogram_shape in qtransform

* Switched tuple to Tuple

* `InMemoryDataset` improvements (#119)

* in memory dataset inherits from torch iterable dataset

* pre-commit issues

* fix yielding logic

* fix in memory dataset tests

* handle deprecated transpose ops in phenomd (#120)

* Torch dependency fix into dev (#124)

* udpate poetry lock

* increment version once more

* re add gwpy dev dep

* update poetry lock

* fix poetry conflic

* fix poety conflict

* Poetry fix (#126)

* remove gwpy dep for now

* poetry lock file

---------

Co-authored-by: Deep Chatterjee <[email protected]>
Co-authored-by: wbenoit26 <[email protected]>
Co-authored-by: William Benoit <[email protected]>
Co-authored-by: William Benoit <[email protected]>

* increment version (#127)

---------

Co-authored-by: wbenoit26 <[email protected]>
Co-authored-by: Deep Chatterjee <[email protected]>
Co-authored-by: William Benoit <[email protected]>
Co-authored-by: William Benoit <[email protected]>
ravioli1369 pushed a commit to ravioli1369/ml4gw that referenced this pull request Jun 10, 2024
* re-implement distributions using torch.distributions (ML4GW#110)

* loosely re-implement distributions using torch.distributions

* further enhancement

* rename

* log_uniform as transformed dist

* delete uniform and log_normal since they are already implemented

* bring back LogNormal, change parameter sampler

* add delta function distribution, minor fixes to other distributions

* fix

* Initial commit of q-transform

* Added a MultiQTransform

* Reparameterized to number of t and f bins

* Re-factored SingleQTransform to allow for eventually using different q's for batch/channels

* Changed interpolation to better match gwpy and added option to specify frequency range in which to search for max energy tile

* Added QScan to __init__

* Changed from torch median to quantile to match numpy median

* Added documentation to qtransform

* Added gwpy to dev dependencies

* Added tests and corrected get_freqs bug

* Changed method of normalization and updated documentation

* Updated more documentation and changed interpolation method

* Changed how interpolation shape is parameterized

* Reverted documentation to state expectation of 3D input

* Fixed type hint for spectrogram_shape in qtransform

* Switched tuple to Tuple

* `InMemoryDataset` improvements (ML4GW#119)

* in memory dataset inherits from torch iterable dataset

* pre-commit issues

* fix yielding logic

* fix in memory dataset tests

* handle deprecated transpose ops in phenomd (ML4GW#120)

* Torch dependency fix into dev (ML4GW#124)

* udpate poetry lock

* increment version once more

* re add gwpy dev dep

* update poetry lock

* fix poetry conflic

* fix poety conflict

* Poetry fix (ML4GW#126)

* remove gwpy dep for now

* poetry lock file

---------

Co-authored-by: Deep Chatterjee <[email protected]>
Co-authored-by: wbenoit26 <[email protected]>
Co-authored-by: William Benoit <[email protected]>
Co-authored-by: William Benoit <[email protected]>
EthanMarx added a commit that referenced this pull request Jul 5, 2024
* Adding funding statement

* Add requirements to docs (#107)

* add requirements to docs

* remove myst_parser req

* Update requirements.txt

* Update conf.py

* Update docs.yaml (#108)

* Update docs.yaml

* Update docs.yaml (#109)

* simplify torch dependencies (#122)

* simplify torch dependency

* remove python constratints

* fix pre-commit

* Merge `dev` into `main` for 0.4.2 release (#123)

* re-implement distributions using torch.distributions (#110)

* loosely re-implement distributions using torch.distributions

* further enhancement

* rename

* log_uniform as transformed dist

* delete uniform and log_normal since they are already implemented

* bring back LogNormal, change parameter sampler

* add delta function distribution, minor fixes to other distributions

* fix

* Initial commit of q-transform

* Added a MultiQTransform

* Reparameterized to number of t and f bins

* Re-factored SingleQTransform to allow for eventually using different q's for batch/channels

* Changed interpolation to better match gwpy and added option to specify frequency range in which to search for max energy tile

* Added QScan to __init__

* Changed from torch median to quantile to match numpy median

* Added documentation to qtransform

* Added gwpy to dev dependencies

* Added tests and corrected get_freqs bug

* Changed method of normalization and updated documentation

* Updated more documentation and changed interpolation method

* Changed how interpolation shape is parameterized

* Reverted documentation to state expectation of 3D input

* Fixed type hint for spectrogram_shape in qtransform

* Switched tuple to Tuple

* `InMemoryDataset` improvements (#119)

* in memory dataset inherits from torch iterable dataset

* pre-commit issues

* fix yielding logic

* fix in memory dataset tests

* handle deprecated transpose ops in phenomd (#120)

* Torch dependency fix into dev (#124)

* udpate poetry lock

* increment version once more

* re add gwpy dev dep

* update poetry lock

* fix poetry conflic

* fix poety conflict

* Poetry fix (#126)

* remove gwpy dep for now

* poetry lock file

---------

Co-authored-by: Deep Chatterjee <[email protected]>
Co-authored-by: wbenoit26 <[email protected]>
Co-authored-by: William Benoit <[email protected]>
Co-authored-by: William Benoit <[email protected]>

* increment version (#127)

---------

Co-authored-by: wbenoit26 <[email protected]>
Co-authored-by: Deep Chatterjee <[email protected]>
Co-authored-by: William Benoit <[email protected]>
Co-authored-by: William Benoit <[email protected]>
EthanMarx added a commit that referenced this pull request Jul 15, 2024
* re-implement distributions using torch.distributions (#110)

* loosely re-implement distributions using torch.distributions

* further enhancement

* rename

* log_uniform as transformed dist

* delete uniform and log_normal since they are already implemented

* bring back LogNormal, change parameter sampler

* add delta function distribution, minor fixes to other distributions

* fix

* Initial commit of q-transform

* Added a MultiQTransform

* Reparameterized to number of t and f bins

* Re-factored SingleQTransform to allow for eventually using different q's for batch/channels

* Changed interpolation to better match gwpy and added option to specify frequency range in which to search for max energy tile

* Added QScan to __init__

* Changed from torch median to quantile to match numpy median

* Added documentation to qtransform

* Added gwpy to dev dependencies

* Added tests and corrected get_freqs bug

* Changed method of normalization and updated documentation

* Updated more documentation and changed interpolation method

* Changed how interpolation shape is parameterized

* Reverted documentation to state expectation of 3D input

* Fixed type hint for spectrogram_shape in qtransform

* Switched tuple to Tuple

* `InMemoryDataset` improvements (#119)

* in memory dataset inherits from torch iterable dataset

* pre-commit issues

* fix yielding logic

* fix in memory dataset tests

* handle deprecated transpose ops in phenomd (#120)

* Torch dependency fix into dev (#124)

* udpate poetry lock

* increment version once more

* re add gwpy dev dep

* update poetry lock

* fix poetry conflic

* fix poety conflict

* Poetry fix (#126)

* remove gwpy dep for now

* poetry lock file

* Merge `main` into `dev` (#128)

* Adding funding statement

* Add requirements to docs (#107)

* add requirements to docs

* remove myst_parser req

* Update requirements.txt

* Update conf.py

* Update docs.yaml (#108)

* Update docs.yaml

* Update docs.yaml (#109)

* simplify torch dependencies (#122)

* simplify torch dependency

* remove python constratints

* fix pre-commit

* Merge `dev` into `main` for 0.4.2 release (#123)

* re-implement distributions using torch.distributions (#110)

* loosely re-implement distributions using torch.distributions

* further enhancement

* rename

* log_uniform as transformed dist

* delete uniform and log_normal since they are already implemented

* bring back LogNormal, change parameter sampler

* add delta function distribution, minor fixes to other distributions

* fix

* Initial commit of q-transform

* Added a MultiQTransform

* Reparameterized to number of t and f bins

* Re-factored SingleQTransform to allow for eventually using different q's for batch/channels

* Changed interpolation to better match gwpy and added option to specify frequency range in which to search for max energy tile

* Added QScan to __init__

* Changed from torch median to quantile to match numpy median

* Added documentation to qtransform

* Added gwpy to dev dependencies

* Added tests and corrected get_freqs bug

* Changed method of normalization and updated documentation

* Updated more documentation and changed interpolation method

* Changed how interpolation shape is parameterized

* Reverted documentation to state expectation of 3D input

* Fixed type hint for spectrogram_shape in qtransform

* Switched tuple to Tuple

* `InMemoryDataset` improvements (#119)

* in memory dataset inherits from torch iterable dataset

* pre-commit issues

* fix yielding logic

* fix in memory dataset tests

* handle deprecated transpose ops in phenomd (#120)

* Torch dependency fix into dev (#124)

* udpate poetry lock

* increment version once more

* re add gwpy dev dep

* update poetry lock

* fix poetry conflic

* fix poety conflict

* Poetry fix (#126)

* remove gwpy dep for now

* poetry lock file

---------

Co-authored-by: Deep Chatterjee <[email protected]>
Co-authored-by: wbenoit26 <[email protected]>
Co-authored-by: William Benoit <[email protected]>
Co-authored-by: William Benoit <[email protected]>

* increment version (#127)

---------

Co-authored-by: wbenoit26 <[email protected]>
Co-authored-by: Deep Chatterjee <[email protected]>
Co-authored-by: William Benoit <[email protected]>
Co-authored-by: William Benoit <[email protected]>

* Fix Distributions module typehints (#129)

* fix type hints in dists

* fix type hints in dists

* Added ringdown waveform function

* fix prefactor four thirds

* Ringdown Waveform updated

* Updated Ringdown with added precision and equation changes

* Added KAGRA geometry

* Add test for K1 geometry

* Fix pre-commit issue

* Restrict numpy

* Unrestrict numpy

* Update tox settings

* Added GroupNorm1D dimension check

* fix thinko in variable names (#135)

* Refactor TaylorF2 and IMRPhenomD (#137)

* refactor taylorf2 and phenom_d into a torch module

* subtract 3PN terms from phasing and Dphasing

* update tolerance for phenomd tests

* Added ringdown

* fixed negative time issues

* Add IMRPhenomPv2 waveform (#138)

* add IMRPhenomPv2 torch implementation

* perform phase correction term by taking finite difference derivative

* add tests for phenomPv2

* added constants

* use dtype of parameters for sg waveform

* Fixed constants import

* Allow arbitrary window in `SpectralDensity` (#140)

* allow arbitrary window function

* allow arbitrary window function

* update error message

* revert spectral transform filename

* delete test_spectral

* constrain numpy version to <2.0.0 (#145)

* Use .mT instead of .T (#147)

* update to use .mT instead of .T

* update taylorf2 to use .mT

* Docstring for phenom_d, phenom_p, tf2 (#148)

* docstring for phenom_d, phenom_p, tf2

* update docs for consistency

* add units to some params

* forward/__call__ and cross/plus refactor (#149)

* remove .forward and call directly

* update sine gaussian to use forward instead of __call__

* update ringdown to use forward instead of __call__

* swap cross and plus polarisations in return. now returns (cross, plus)

* Resolve main conflicts (#151)

* Adding funding statement

* Add requirements to docs (#107)

* add requirements to docs

* remove myst_parser req

* Update requirements.txt

* Update conf.py

* Update docs.yaml (#108)

* Update docs.yaml

* Update docs.yaml (#109)

* simplify torch dependencies (#122)

* simplify torch dependency

* remove python constratints

* fix pre-commit

* Merge `dev` into `main` for 0.4.2 release (#123)

* re-implement distributions using torch.distributions (#110)

* loosely re-implement distributions using torch.distributions

* further enhancement

* rename

* log_uniform as transformed dist

* delete uniform and log_normal since they are already implemented

* bring back LogNormal, change parameter sampler

* add delta function distribution, minor fixes to other distributions

* fix

* Initial commit of q-transform

* Added a MultiQTransform

* Reparameterized to number of t and f bins

* Re-factored SingleQTransform to allow for eventually using different q's for batch/channels

* Changed interpolation to better match gwpy and added option to specify frequency range in which to search for max energy tile

* Added QScan to __init__

* Changed from torch median to quantile to match numpy median

* Added documentation to qtransform

* Added gwpy to dev dependencies

* Added tests and corrected get_freqs bug

* Changed method of normalization and updated documentation

* Updated more documentation and changed interpolation method

* Changed how interpolation shape is parameterized

* Reverted documentation to state expectation of 3D input

* Fixed type hint for spectrogram_shape in qtransform

* Switched tuple to Tuple

* `InMemoryDataset` improvements (#119)

* in memory dataset inherits from torch iterable dataset

* pre-commit issues

* fix yielding logic

* fix in memory dataset tests

* handle deprecated transpose ops in phenomd (#120)

* Torch dependency fix into dev (#124)

* udpate poetry lock

* increment version once more

* re add gwpy dev dep

* update poetry lock

* fix poetry conflic

* fix poety conflict

* Poetry fix (#126)

* remove gwpy dep for now

* poetry lock file

---------

Co-authored-by: Deep Chatterjee <[email protected]>
Co-authored-by: wbenoit26 <[email protected]>
Co-authored-by: William Benoit <[email protected]>
Co-authored-by: William Benoit <[email protected]>

* increment version (#127)

---------

Co-authored-by: wbenoit26 <[email protected]>
Co-authored-by: Deep Chatterjee <[email protected]>
Co-authored-by: William Benoit <[email protected]>
Co-authored-by: William Benoit <[email protected]>

* resolve merge conflicts

* resolve merge conflicts

---------

Co-authored-by: Deep Chatterjee <[email protected]>
Co-authored-by: wbenoit26 <[email protected]>
Co-authored-by: William Benoit <[email protected]>
Co-authored-by: William Benoit <[email protected]>
Co-authored-by: Trevor William Blodgett <[email protected]>
Co-authored-by: Ravi Kumar <[email protected]>
Co-authored-by: Trevor William Blodgett <[email protected]>
Co-authored-by: Ravi Kumar <[email protected]>
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