FAµST python toolbox

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FAµST logo pipeline status coverage python3

The FAµST toolbox provides algorithms and data structures to decompose a given dense matrix into a product of sparse matrices in order to reduce its computational complexity (both for storage and manipulation).

FaµST can be used to:

  • speed up / reduce the memory footprint of iterative algorithms commonly used for solving high dimensional linear inverse problems,
  • learn dictionaries with an intrinsically efficient implementation,
  • compute (approximate) fast Fourier transforms on graphs.

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This version

3.42.2

3.42.2a0 pre-release

3.42.1

3.42.1a3 pre-release

3.42.0

3.42.0a2 pre-release

3.41.0

3.41.0a2 pre-release

3.40.3a2 pre-release

3.40.2

3.40.1

3.40.0

3.40.0a0 pre-release

3.39.25

3.39.25a0 pre-release

3.39.24

3.39.24a0 pre-release

3.39.23

3.39.23a0 pre-release

3.39.22

3.39.22a0 pre-release

3.39.21

3.39.21a0 pre-release

3.39.20

3.39.20a0 pre-release

3.39.19

3.39.19a1 pre-release

3.39.19a0 pre-release

3.39.18

3.39.17

3.39.16

3.39.15

3.39.14

3.39.13

3.39.12

3.39.11

3.39.10

3.39.9

3.39.8

3.39.7

3.39.6

3.39.5

3.39.4

3.39.3

3.39.2

3.39.1

3.39.0

3.38.23

3.38.22

3.38.21

3.38.20

3.38.19

3.38.18

3.38.17

3.38.16

3.38.15

3.38.14

3.38.13

3.38.12

3.38.11

3.38.10

3.38.9

3.38.8

3.38.7

3.38.6

3.38.4

3.38.3

3.38.2

3.38.1

3.38.0

3.37.13

3.37.12

3.37.11

3.37.10

3.37.9

3.37.8

3.37.7

3.37.6

3.37.5

3.37.4

3.37.3

3.37.2

3.37.1

3.37.0

3.36.0

3.35.18

3.35.17

3.35.16

3.35.15

3.35.14

3.35.13

3.35.11

3.35.10

3.35.9

3.35.8

3.35.7

3.35.6

3.35.5

3.35.4

3.35.3

3.35.0

3.33.5

3.33.4

3.33.3

3.33.2

3.33.1

3.33.0

3.32.5

3.32.4

3.32.3

3.32.2

3.32.1

3.32.0

3.31.6

3.31.5

3.31.4

3.31.3

3.31.2

3.31.1

3.31.0

3.30.0

3.29.1

3.29.0

3.28.12

3.28.10

3.28.9

3.28.8

3.28.7

3.28.6

3.28.5

3.28.4

3.28.3

3.28.2

3.28.1

3.28.0

3.27.2

3.27.1

3.27.0

3.26.7

3.26.6

3.26.5

3.26.4

3.26.3

3.26.2

3.26.1

3.26.0

3.25.10

3.25.9

3.25.8

3.25.7

3.25.6

3.25.5

3.25.4

3.25.3

3.25.2

3.25.1

3.25.0

3.24.2

3.24.1

3.24.0

3.23.2

3.23.1

3.22.0

3.21.0

3.20.0

3.19.0

3.18.1

3.18.0

3.17.0

3.16.0

3.15.0

3.14.1

3.13.0

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