PyWavelets

PyWavelets, wavelet transform module

Project description

PyWavelets is a Python wavelet transforms module that includes:

nD Forward and Inverse Discrete Wavelet Transform (DWT and IDWT)

1D and 2D Forward and Inverse Stationary Wavelet Transform (Undecimated Wavelet Transform)

1D and 2D Wavelet Packet decomposition and reconstruction

1D Continuous Wavelet Tranfsorm

Computing Approximations of wavelet and scaling functions

Over 100 built-in wavelet filters and support for custom wavelets

Single and double precision calculations

Real and complex calculations

Results compatible with Matlab Wavelet Toolbox (TM)

Project details

Release history Release notifications | RSS feed

This version

1.2.0

Nov 9, 2021

1.1.1

Oct 19, 2019

1.1.0

Oct 18, 2019

1.0.3

Apr 9, 2019

1.0.2

Feb 26, 2019

1.0.1

Sep 25, 2018

1.0.0

Aug 31, 2018

0.5.2

Mar 10, 2017

0.5.1

Nov 29, 2016

0.5.0

Nov 3, 2016

0.4.0

Dec 28, 2015

0.3.0

Jul 30, 2015

0.2.2

Aug 30, 2012

0.2.0

Mar 17, 2010

0.1.6

Dec 2, 2006

0.1.4

Jul 7, 2006

0.1.2

Mar 25, 2006

0.1.0

Mar 22, 2006

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Files for PyWavelets, version 1.2.0
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Hashes for PyWavelets-1.2.0-cp38-cp38-manylinux_2_5_x86_64.manylinux1_x86_64.whl

Hashes for PyWavelets-1.2.0-cp38-cp38-manylinux_2_5_x86_64.manylinux1_x86_64.whl
Algorithm	Hash digest
SHA256	`c8b388652b6afb4bf7be313be057240386de93817c6744c2aaf43a22890733c8`
MD5	`ef1fb42a4295d4eb15a5be81fc6497d5`
BLAKE2-256	`542ffb0bea7b5c19ce2b84fcf6e951bac3e31cb4d7b6e97d9d317ecc179a82aa`

Hashes for PyWavelets-1.2.0-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.whl

Hashes for PyWavelets-1.2.0-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.whl
Algorithm	Hash digest
SHA256	`44315d197bad9564210ef42f2d5a01c07ee6fd456c679d4a6d0f4e23ec9930cf`
MD5	`4193a6e61d40adf0d0316c99e034629c`
BLAKE2-256	`11380c3b5d8a6fe5dd2b4ad45444be2986da81238c0935f11a25dfe5dd5e2f0f`

Hashes for PyWavelets-1.2.0-cp38-cp38-macosx_11_0_arm64.whl

Hashes for PyWavelets-1.2.0-cp38-cp38-macosx_11_0_arm64.whl
Algorithm	Hash digest
SHA256	`333684cc0d0e89cf6cb3a8b3ea68528790e1a3edc565a100cda47e29860f892d`
MD5	`2972099f5f365c7a7388b5d1de540cee`
BLAKE2-256	`618213741d25c6568cdbbd8f038a9dc4cbd8ced28a54be2163ebdede454299a8`

Hashes for PyWavelets-1.2.0-cp38-cp38-macosx_10_13_x86_64.whl

Hashes for PyWavelets-1.2.0-cp38-cp38-macosx_10_13_x86_64.whl
Algorithm	Hash digest
SHA256	`7e4749ff324e8e01a2fdc859ac9714c4be1cbc6e8a34d5ddedb28fc9513b31a1`
MD5	`d54c1040362b9ad04ac0641226c16fe7`
BLAKE2-256	`f18c1d46b79b07a9877402b9323d9daaf4b59661d32b5c314c708167ffab33a3`

Hashes for PyWavelets-1.2.0-cp38-cp38-macosx_10_13_universal2.whl

Hashes for PyWavelets-1.2.0-cp38-cp38-macosx_10_13_universal2.whl
Algorithm	Hash digest
SHA256	`d9831b251f63460302811607f80a20285292ed0a0a046f95b4648edc0ed90f9c`
MD5	`7b3719fcdd11cbcfbb39592c6c8d6fea`
BLAKE2-256	`6de40911be1ebf5592f3cd4fdb38918b729978feb655f33662db2584651ef593`

Hashes for PyWavelets-1.2.0-cp37-cp37m-win_amd64.whl

Hashes for PyWavelets-1.2.0-cp37-cp37m-win_amd64.whl
Algorithm	Hash digest
SHA256	`7a725030682bf891ced9819b4b21d6ef356fa11b70399d2d3adb319aead1efb0`
MD5	`32324f8751586ae89e4aeab935af680d`
BLAKE2-256	`27e68f491c344f2811cee518121ff6030c813a8f6f1f6109a18173f802ffa3b6`

Hashes for PyWavelets-1.2.0-cp37-cp37m-win32.whl

Hashes for PyWavelets-1.2.0-cp37-cp37m-win32.whl
Algorithm	Hash digest
SHA256	`537b5a8a8a3e9e5b931d34b517aa2312a3d8385937f98c4f8ffa668483329cfb`
MD5	`887d6b05aa56c0df270b2f52678b53cb`
BLAKE2-256	`c5233d05af79bef7dc741c1b65fa525030d7f15d81149efe48688dcb627f8811`

Hashes for PyWavelets-1.2.0-cp37-cp37m-musllinux_1_1_x86_64.whl

Hashes for PyWavelets-1.2.0-cp37-cp37m-musllinux_1_1_x86_64.whl
Algorithm	Hash digest
SHA256	`9b05d2f21da666f918692f0313484002307794b5380f7291a395b9271abdda5c`
MD5	`f2e7dc6c824e6084f831cdb114255ccf`
BLAKE2-256	`f404394c98316402f8625d1510f15b51d597c6916edf05a80e50811ebbd2129c`

Hashes for PyWavelets-1.2.0-cp37-cp37m-musllinux_1_1_i686.whl

Hashes for PyWavelets-1.2.0-cp37-cp37m-musllinux_1_1_i686.whl
Algorithm	Hash digest
SHA256	`abedc0b49273a734d4592e325a5fb32f0741e115d6722e0c59964ecf21344640`
MD5	`e9623be8c9a4dfbccf0a5d9a52ed50f1`
BLAKE2-256	`7122bfda80c4d28a36c32580620f03002f9ce3a91605b33af31604df68056f06`

Hashes for PyWavelets-1.2.0-cp37-cp37m-manylinux_2_5_x86_64.manylinux1_x86_64.whl

Hashes for PyWavelets-1.2.0-cp37-cp37m-manylinux_2_5_x86_64.manylinux1_x86_64.whl
Algorithm	Hash digest
SHA256	`616fd2967dd153c3f539b1e0979168969f3702125caae4caa769efc5621cc2b7`
MD5	`b466b3e095174b20913b8b53f314b969`
BLAKE2-256	`a19c564511b6e1c4e1d835ed2d146670436036960d09339a8fa2921fe42dad08`

Hashes for PyWavelets-1.2.0-cp37-cp37m-manylinux_2_5_i686.manylinux1_i686.whl

Hashes for PyWavelets-1.2.0-cp37-cp37m-manylinux_2_5_i686.manylinux1_i686.whl
Algorithm	Hash digest
SHA256	`151a7f3d3db36baffe640d691403b7cd3938a1886c8a387b719e7e8b580dd4b1`
MD5	`54d08cc173e293858c026875026a5cc3`
BLAKE2-256	`b5c4154cca45673362acbabe9b6b6c9546181543bd184408a676e9b783184885`

Hashes for PyWavelets-1.2.0-cp37-cp37m-macosx_10_13_x86_64.whl

Hashes for PyWavelets-1.2.0-cp37-cp37m-macosx_10_13_x86_64.whl
Algorithm	Hash digest
SHA256	`ec670e78be2c3193e26c4bfa31dff1edd89ee8d7e2f4219782f3ef3f6daf37f0`
MD5	`e0879c3135421950c8798fc3df79d54c`
BLAKE2-256	`93ce4ce66274d1e882805d11cd7231be8bbcd75c07c26a95b923d3c65fb935ef`