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ml-gsd

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ml-gsd - npm Package Compare versions

Comparing version 7.0.1 to 8.0.0

lib-esm/gsd.d.ts

lib-esm/gsd.d.ts.map

lib-esm/gsd.js

lib-esm/gsd.js.map

lib-esm/index.d.ts

lib-esm/index.d.ts.map

lib-esm/index.js

lib-esm/index.js.map

lib-esm/post/broadenPeaks.d.ts

lib-esm/post/broadenPeaks.d.ts.map

lib-esm/post/broadenPeaks.js

lib-esm/post/broadenPeaks.js.map

lib-esm/post/groupPeaks.d.ts

lib-esm/post/groupPeaks.d.ts.map

lib-esm/post/groupPeaks.js

lib-esm/post/groupPeaks.js.map

lib-esm/post/joinBroadPeaks.d.ts

lib-esm/post/joinBroadPeaks.d.ts.map

lib-esm/post/joinBroadPeaks.js

lib-esm/post/joinBroadPeaks.js.map

lib-esm/post/optimizePeaks.d.ts

lib-esm/post/optimizePeaks.d.ts.map

lib-esm/post/optimizePeaks.js

lib-esm/post/optimizePeaks.js.map

lib/gsd.d.ts

lib/gsd.d.ts.map

lib/gsd.js

lib/gsd.js.map

lib/index.d.ts

lib/index.d.ts.map

lib/index.js.map

lib/post/broadenPeaks.d.ts

lib/post/broadenPeaks.d.ts.map

lib/post/broadenPeaks.js

lib/post/broadenPeaks.js.map

lib/post/groupPeaks.d.ts

lib/post/groupPeaks.d.ts.map

lib/post/groupPeaks.js

lib/post/groupPeaks.js.map

lib/post/joinBroadPeaks.d.ts

lib/post/joinBroadPeaks.d.ts.map

lib/post/joinBroadPeaks.js

lib/post/joinBroadPeaks.js.map

lib/post/optimizePeaks.d.ts

lib/post/optimizePeaks.d.ts.map

lib/post/optimizePeaks.js

lib/post/optimizePeaks.js.map

src/__tests__/bigLowS2NSpectrum.test.ts

src/__tests__/broadNMR.test.ts

src/__tests__/ethylvinylether.test.ts

src/__tests__/general.test.ts

src/__tests__/infraRed.test.ts

src/__tests__/massPeakPicking.test.ts

src/__tests__/simple.test.ts

src/__tests__/simpleShifted.test.ts

src/__tests__/simulated.test.ts

src/__tests__/ubiquitin.test.ts

src/__tests__/zero.test.ts

src/gsd.ts

src/index.ts

src/post/__tests__/broadenPeaks.test.ts

src/post/__tests__/groupPeaks.test.ts

src/post/__tests__/optimizePeaks.test.ts

src/post/broadenPeaks.ts

src/post/groupPeaks.ts

src/post/joinBroadPeaks.ts

src/post/optimizePeaks.ts

141

CHANGELOG.md

		# Changelog

		## [8.0.0](https://www.github.com/mljs/global-spectral-deconvolution/compare/v7.0.1...v8.0.0) (2021-10-31)


		### ⚠ BREAKING CHANGES

		* setup typescript (#66)

		### Features

		* setup typescript ([#66](https://www.github.com/mljs/global-spectral-deconvolution/issues/66)) ([4e61017](https://www.github.com/mljs/global-spectral-deconvolution/commit/4e610172b9ebd36f232f2b99585e8c2481b78502))

		### [7.0.1](https://www.github.com/mljs/global-spectral-deconvolution/compare/v7.0.0...v7.0.1) (2021-10-11)


		### Bug Fixes

		* remove type definition file ([efea5e2](https://www.github.com/mljs/global-spectral-deconvolution/commit/efea5e2443a7fd1298a4d4ba6fa5e6ab70bbe53b))
		- remove type definition file ([efea5e2](https://www.github.com/mljs/global-spectral-deconvolution/commit/efea5e2443a7fd1298a4d4ba6fa5e6ab70bbe53b))

		## [7.0.0](https://www.github.com/mljs/global-spectral-deconvolution/compare/v6.9.2...v7.0.0) (2021-10-11)


		### ⚠ BREAKING CHANGES

		* homogenize and generalize output (#63)
		- homogenize and generalize output (#63)

		### Features

		* homogenize and generalize output ([#63](https://www.github.com/mljs/global-spectral-deconvolution/issues/63)) ([2b3a403](https://www.github.com/mljs/global-spectral-deconvolution/commit/2b3a403747a8d83effb5bef8053863382d608546))
		- homogenize and generalize output ([#63](https://www.github.com/mljs/global-spectral-deconvolution/issues/63)) ([2b3a403](https://www.github.com/mljs/global-spectral-deconvolution/commit/2b3a403747a8d83effb5bef8053863382d608546))

		### [6.9.2](https://www.github.com/mljs/global-spectral-deconvolution/compare/v6.9.1...v6.9.2) (2021-10-07)


		### Bug Fixes

		* GSDPeak index rather than ndex ([da4dfd3](https://www.github.com/mljs/global-spectral-deconvolution/commit/da4dfd32192d8aca72501a252d43ecbaf0a61f14))
		- GSDPeak index rather than ndex ([da4dfd3](https://www.github.com/mljs/global-spectral-deconvolution/commit/da4dfd32192d8aca72501a252d43ecbaf0a61f14))

		### [6.9.1](https://www.github.com/mljs/global-spectral-deconvolution/compare/v6.9.0...v6.9.1) (2021-10-07)


		### Bug Fixes

		* wrong search replace yield bad typescript definition ([fcfc3c6](https://www.github.com/mljs/global-spectral-deconvolution/commit/fcfc3c69b7f31058dae73005dca6ba6f672bdcff))
		- wrong search replace yield bad typescript definition ([fcfc3c6](https://www.github.com/mljs/global-spectral-deconvolution/commit/fcfc3c69b7f31058dae73005dca6ba6f672bdcff))

		## [6.9.0](https://www.github.com/mljs/global-spectral-deconvolution/compare/v6.8.2...v6.9.0) (2021-10-05)


		### Features

		* fix and improve type script definition ([e3148cd](https://www.github.com/mljs/global-spectral-deconvolution/commit/e3148cdc7989fcb17c11c0fceb6eda1710f2e497))
		* improve typescript definition ([3c772f7](https://www.github.com/mljs/global-spectral-deconvolution/commit/3c772f76dc3476e72f2f297a746fb314a0b5e609))
		- fix and improve type script definition ([e3148cd](https://www.github.com/mljs/global-spectral-deconvolution/commit/e3148cdc7989fcb17c11c0fceb6eda1710f2e497))
		- improve typescript definition ([3c772f7](https://www.github.com/mljs/global-spectral-deconvolution/commit/3c772f76dc3476e72f2f297a746fb314a0b5e609))


		### Bug Fixes

		* update dependencies and fix build ([48b4f41](https://www.github.com/mljs/global-spectral-deconvolution/commit/48b4f41e41db29fb21e54a86a1aeb02aa930aea0))
		- update dependencies and fix build ([48b4f41](https://www.github.com/mljs/global-spectral-deconvolution/commit/48b4f41e41db29fb21e54a86a1aeb02aa930aea0))

		### [6.8.2](https://www.github.com/mljs/global-spectral-deconvolution/compare/v6.8.1...v6.8.2) (2021-09-29)


		### Bug Fixes

		* make optional option for GSD ([d3657de](https://www.github.com/mljs/global-spectral-deconvolution/commit/d3657de8fb407043890e899494a221b862c30973))
		- make optional option for GSD ([d3657de](https://www.github.com/mljs/global-spectral-deconvolution/commit/d3657de8fb407043890e899494a221b862c30973))

		### [6.8.1](https://www.github.com/mljs/global-spectral-deconvolution/compare/v6.8.0...v6.8.1) (2021-09-29)


		### Bug Fixes

		* add types in files ([28f9dcb](https://www.github.com/mljs/global-spectral-deconvolution/commit/28f9dcb1425c8d7b9940c333c6cf123834a8ab7e))
		- add types in files ([28f9dcb](https://www.github.com/mljs/global-spectral-deconvolution/commit/28f9dcb1425c8d7b9940c333c6cf123834a8ab7e))

		## [6.8.0](https://www.github.com/mljs/global-spectral-deconvolution/compare/v6.7.0...v6.8.0) (2021-09-23)


		### Features

		* add types ([#55](https://www.github.com/mljs/global-spectral-deconvolution/issues/55)) ([d4f1564](https://www.github.com/mljs/global-spectral-deconvolution/commit/d4f15649572c0ec2f1142f4b3ed77655fca05a73))
		- add types ([#55](https://www.github.com/mljs/global-spectral-deconvolution/issues/55)) ([d4f1564](https://www.github.com/mljs/global-spectral-deconvolution/commit/d4f15649572c0ec2f1142f4b3ed77655fca05a73))

		## [6.7.0](https://www.github.com/mljs/global-spectral-deconvolution/compare/v6.6.3...v6.7.0) (2021-08-10)


		### Features

		* update ml-peak-shape-generator to 2.0.1 ([98128b8](https://www.github.com/mljs/global-spectral-deconvolution/commit/98128b85ea08bc1c9a3ebbecf4ddc2fca0b3e3b3))
		- update ml-peak-shape-generator to 2.0.1 ([98128b8](https://www.github.com/mljs/global-spectral-deconvolution/commit/98128b85ea08bc1c9a3ebbecf4ddc2fca0b3e3b3))

		### [6.6.3](https://www.github.com/mljs/global-spectral-deconvolution/compare/v6.6.2...v6.6.3) (2021-06-18)


		### Bug Fixes

		* maxCriteria=false gives more consistent results ([2652ec2](https://www.github.com/mljs/global-spectral-deconvolution/commit/2652ec265193207ff128348c8d0207d74e1b0c0c))
		- maxCriteria=false gives more consistent results ([2652ec2](https://www.github.com/mljs/global-spectral-deconvolution/commit/2652ec265193207ff128348c8d0207d74e1b0c0c))

		### [6.6.2](https://www.github.com/mljs/global-spectral-deconvolution/compare/v6.6.1...v6.6.2) (2021-05-11)


		### Bug Fixes

		* update dependencies ([4d9feac](https://www.github.com/mljs/global-spectral-deconvolution/commit/4d9feace7ffb106b68a7604df13e458f4474bc65))
		- update dependencies ([4d9feac](https://www.github.com/mljs/global-spectral-deconvolution/commit/4d9feace7ffb106b68a7604df13e458f4474bc65))

		### [6.6.1](https://www.github.com/mljs/global-spectral-deconvolution/compare/v6.6.0...v6.6.1) (2021-03-24)


		### Bug Fixes

		* update dependencies ([bf6ee4b](https://www.github.com/mljs/global-spectral-deconvolution/commit/bf6ee4b246e4d964945b034b6b430aa576caaded))
		- update dependencies ([bf6ee4b](https://www.github.com/mljs/global-spectral-deconvolution/commit/bf6ee4b246e4d964945b034b6b430aa576caaded))

		## [6.6.0](https://www.github.com/mljs/global-spectral-deconvolution/compare/v6.5.0...v6.6.0) (2021-01-21)


		### Features

		* update ml-spectra-fitting to 0.13.0 ([2b4f119](https://www.github.com/mljs/global-spectral-deconvolution/commit/2b4f119ce747208f1045b0a6ddc93b9b9bfbbe15))
		- update ml-spectra-fitting to 0.13.0 ([2b4f119](https://www.github.com/mljs/global-spectral-deconvolution/commit/2b4f119ce747208f1045b0a6ddc93b9b9bfbbe15))

		## [6.5.0](https://www.github.com/mljs/global-spectral-deconvolution/compare/v6.4.0...v6.5.0) (2021-01-13)


		### Features

		* update spectra-fitting ([03205a3](https://www.github.com/mljs/global-spectral-deconvolution/commit/03205a3d570d87f35d96dbe674ddb67b0f236564))
		- update spectra-fitting ([03205a3](https://www.github.com/mljs/global-spectral-deconvolution/commit/03205a3d570d87f35d96dbe674ddb67b0f236564))

		## [6.4.0](https://www.github.com/mljs/global-spectral-deconvolution/compare/v6.3.0...v6.4.0) (2020-12-21)


		### Features

		* added timeout option to avoid long executions. close [#37](https://www.github.com/mljs/global-spectral-deconvolution/issues/37) ([#47](https://www.github.com/mljs/global-spectral-deconvolution/issues/47)) ([b847438](https://www.github.com/mljs/global-spectral-deconvolution/commit/b8474381e9ccfef543251ffe2ea0d2afc1815eb7))
		- added timeout option to avoid long executions. close [#37](https://www.github.com/mljs/global-spectral-deconvolution/issues/37) ([#47](https://www.github.com/mljs/global-spectral-deconvolution/issues/47)) ([b847438](https://www.github.com/mljs/global-spectral-deconvolution/commit/b8474381e9ccfef543251ffe2ea0d2afc1815eb7))

		## [6.3.0](https://www.github.com/mljs/global-spectral-deconvolution/compare/v6.2.0...v6.3.0) (2020-12-13)


		### Features

		* update ml-peak-shape-generator ([9d446a9](https://www.github.com/mljs/global-spectral-deconvolution/commit/9d446a9993d360c2001cbb23e782b6b881b1f47e))
		* update ml-peak-shape-generator ([#44](https://www.github.com/mljs/global-spectral-deconvolution/issues/44)) ([70776d3](https://www.github.com/mljs/global-spectral-deconvolution/commit/70776d3a45b7e25296203ae5cfc8d89c3679d258))
		- update ml-peak-shape-generator ([9d446a9](https://www.github.com/mljs/global-spectral-deconvolution/commit/9d446a9993d360c2001cbb23e782b6b881b1f47e))
		- update ml-peak-shape-generator ([#44](https://www.github.com/mljs/global-spectral-deconvolution/issues/44)) ([70776d3](https://www.github.com/mljs/global-spectral-deconvolution/commit/70776d3a45b7e25296203ae5cfc8d89c3679d258))

		## [6.2.0](https://www.github.com/mljs/global-spectral-deconvolution/compare/v6.1.2...v6.2.0) (2020-12-05)


		### Features

		* add factorLimits parameter for optimizePeaks ([1af47e1](https://www.github.com/mljs/global-spectral-deconvolution/commit/1af47e1a32cfef957cc43078ae389ecc4f2d691b))
		* add failling test case ([a061013](https://www.github.com/mljs/global-spectral-deconvolution/commit/a06101315d97e70bc19119dad3692eff64848568))
		* improve groupPeaks ([6ef7024](https://www.github.com/mljs/global-spectral-deconvolution/commit/6ef7024a1e34ce63c71fa0679946df74271d3c88))
		* simplify optimizePeaks ([3abfe93](https://www.github.com/mljs/global-spectral-deconvolution/commit/3abfe93a4cc938d799acc495fea959d15db272a3))
		* update ml-spectra-fitting ([97899d5](https://www.github.com/mljs/global-spectral-deconvolution/commit/97899d5f3453d6f0b0a4afa0c8102b07c5d69a32))
		- add factorLimits parameter for optimizePeaks ([1af47e1](https://www.github.com/mljs/global-spectral-deconvolution/commit/1af47e1a32cfef957cc43078ae389ecc4f2d691b))
		- add failling test case ([a061013](https://www.github.com/mljs/global-spectral-deconvolution/commit/a06101315d97e70bc19119dad3692eff64848568))
		- improve groupPeaks ([6ef7024](https://www.github.com/mljs/global-spectral-deconvolution/commit/6ef7024a1e34ce63c71fa0679946df74271d3c88))
		- simplify optimizePeaks ([3abfe93](https://www.github.com/mljs/global-spectral-deconvolution/commit/3abfe93a4cc938d799acc495fea959d15db272a3))
		- update ml-spectra-fitting ([97899d5](https://www.github.com/mljs/global-spectral-deconvolution/commit/97899d5f3453d6f0b0a4afa0c8102b07c5d69a32))


		### Bug Fixes

		* always ascending order in x dimension ([6ffc64f](https://www.github.com/mljs/global-spectral-deconvolution/commit/6ffc64f288220f4d004b7627c2fb44caa9b21bbf))
		* update dependencies ([5ea4c7f](https://www.github.com/mljs/global-spectral-deconvolution/commit/5ea4c7fbb042c2145e760b97aab6c92788eeb117))
		- always ascending order in x dimension ([6ffc64f](https://www.github.com/mljs/global-spectral-deconvolution/commit/6ffc64f288220f4d004b7627c2fb44caa9b21bbf))
		- update dependencies ([5ea4c7f](https://www.github.com/mljs/global-spectral-deconvolution/commit/5ea4c7fbb042c2145e760b97aab6c92788eeb117))

		### [6.1.2](https://www.github.com/mljs/global-spectral-deconvolution/compare/v6.1.1...v6.1.2) (2020-11-18)


		### Bug Fixes

		* method name in README ([cb0e563](https://www.github.com/mljs/global-spectral-deconvolution/commit/cb0e563b5eeaee233004fdcd87882b470654bd99))
		- method name in README ([cb0e563](https://www.github.com/mljs/global-spectral-deconvolution/commit/cb0e563b5eeaee233004fdcd87882b470654bd99))

		### [6.1.1](https://www.github.com/mljs/global-spectral-deconvolution/compare/v6.1.0...v6.1.1) (2020-11-14)


		### Bug Fixes

		* update spectra-fitting ([33d89df](https://www.github.com/mljs/global-spectral-deconvolution/commit/33d89dfba443e5b2080e51e9f265305301f8409a))
		- update spectra-fitting ([33d89df](https://www.github.com/mljs/global-spectral-deconvolution/commit/33d89dfba443e5b2080e51e9f265305301f8409a))

		## [6.1.0](https://www.github.com/mljs/global-spectral-deconvolution/compare/v6.0.0...v6.1.0) (2020-11-13)


		### Features

		* change factorWidth from 4 to 1 ([3de56ae](https://www.github.com/mljs/global-spectral-deconvolution/commit/3de56ae345322446b0bafa1d020bf6fdff0ff5ee))
		* update spectra-fitting package ([#33](https://www.github.com/mljs/global-spectral-deconvolution/issues/33)) ([e62e27b](https://www.github.com/mljs/global-spectral-deconvolution/commit/e62e27b0aeb527878af9240b367fee951ba7a889))
		- change factorWidth from 4 to 1 ([3de56ae](https://www.github.com/mljs/global-spectral-deconvolution/commit/3de56ae345322446b0bafa1d020bf6fdff0ff5ee))
		- update spectra-fitting package ([#33](https://www.github.com/mljs/global-spectral-deconvolution/issues/33)) ([e62e27b](https://www.github.com/mljs/global-spectral-deconvolution/commit/e62e27b0aeb527878af9240b367fee951ba7a889))


		### Bug Fixes

		* fix docs for optimize ([96ea711](https://www.github.com/mljs/global-spectral-deconvolution/commit/96ea71123f4989308bf060dc5108c24e55baaab5))
		* improve speed by not predefining arrays length ([e03737c](https://www.github.com/mljs/global-spectral-deconvolution/commit/e03737c42ae097d1c8ddec7303613ea87cec955c))
		- fix docs for optimize ([96ea711](https://www.github.com/mljs/global-spectral-deconvolution/commit/96ea71123f4989308bf060dc5108c24e55baaab5))
		- improve speed by not predefining arrays length ([e03737c](https://www.github.com/mljs/global-spectral-deconvolution/commit/e03737c42ae097d1c8ddec7303613ea87cec955c))

		## [6.0.0](https://www.github.com/mljs/global-spectral-deconvolution/compare/v5.0.2...v6.0.0) (2020-11-06)


		### ⚠ BREAKING CHANGES

		* Remove compatibility with node 8
		- Remove compatibility with node 8

		### Features

		* change parameters ([4653e16](https://www.github.com/mljs/global-spectral-deconvolution/commit/4653e164ab5181e5d65a443dec043934aae3d01e))
		- change parameters ([4653e16](https://www.github.com/mljs/global-spectral-deconvolution/commit/4653e164ab5181e5d65a443dec043934aae3d01e))


		### Miscellaneous Chores

		* update travis ([3120a4a](https://www.github.com/mljs/global-spectral-deconvolution/commit/3120a4a673d4d1826e92c3073a7803eef07b8d4b))
		- update travis ([3120a4a](https://www.github.com/mljs/global-spectral-deconvolution/commit/3120a4a673d4d1826e92c3073a7803eef07b8d4b))

		# [5.0.0](https://github.com/mljs/global-spectral-deconvolution/compare/v4.0.0...v5.0.0) (2020-05-19)



		# [4.0.0](https://github.com/mljs/global-spectral-deconvolution/compare/v3.0.1...v4.0.0) (2020-03-20)


		### Features

		* broadenPeaks takes into account the inflection points if available ([d9302c7](https://github.com/mljs/global-spectral-deconvolution/commit/d9302c74a937f1202dc0898b0ca86bf684edf2c2))
		- broadenPeaks takes into account the inflection points if available ([d9302c7](https://github.com/mljs/global-spectral-deconvolution/commit/d9302c74a937f1202dc0898b0ca86bf684edf2c2))



		## [3.0.1](https://github.com/mljs/global-spectral-deconvolution/compare/v3.0.0...v3.0.1) (2020-02-28)



		# [3.0.0](https://github.com/mljs/global-spectral-deconvolution/compare/v2.0.6...v3.0.0) (2020-02-27)



		## [2.0.5](https://github.com/mljs/global-spectral-deconvolution/compare/v2.0.4...v2.0.5) (2019-01-09)



		## [2.0.4](https://github.com/mljs/global-spectral-deconvolution/compare/v2.0.3...v2.0.4) (2019-01-09)

		<a name="2.0.3"></a>


		<a name="2.0.3"></a>
		## [2.0.3](https://github.com/mljs/global-spectral-deconvolution/compare/v2.0.2...v2.0.3) (2018-11-01)

		<a name="2.0.2"></a>


		<a name="2.0.2"></a>
		## [2.0.2](https://github.com/mljs/global-spectral-deconvolution/compare/v2.0.1...v2.0.2) (2018-08-03)

		<a name="2.0.0"></a>


		<a name="2.0.0"></a>
		# [2.0.0](https://github.com/mljs/global-spectral-deconvolution/compare/v1.1.6...v2.0.0) (2016-11-08)


		### Bug Fixes

		* gsd: more understandable variable names ([e8e9ccb](https://github.com/mljs/global-spectral-deconvolution/commit/e8e9ccb))
		- gsd: more understandable variable names ([e8e9ccb](https://github.com/mljs/global-spectral-deconvolution/commit/e8e9ccb))


		### Features

		* gsd: fix a threshold for first derivative ([4cd0fbb](https://github.com/mljs/global-spectral-deconvolution/commit/4cd0fbb))
		* gsd: returns as option the boundaries and real height of each peak ([cf7d895](https://github.com/mljs/global-spectral-deconvolution/commit/cf7d895))
		- gsd: fix a threshold for first derivative ([4cd0fbb](https://github.com/mljs/global-spectral-deconvolution/commit/4cd0fbb))
		- gsd: returns as option the boundaries and real height of each peak ([cf7d895](https://github.com/mljs/global-spectral-deconvolution/commit/cf7d895))


		### BREAKING CHANGES

		* gsd: rename i for index
		- gsd: rename i for index

593

lib/index.js

		@@ -1,578 +0,17 @@
		'use strict';

		Object.defineProperty(exports, '__esModule', { value: true });

		var mlPeakShapeGenerator = require('ml-peak-shape-generator');
		var SG = require('ml-savitzky-golay-generalized');
		var mlSpectraFitting = require('ml-spectra-fitting');
		var mlSpectraProcessing = require('ml-spectra-processing');

		function _interopDefaultLegacy (e) { return e && typeof e === 'object' && 'default' in e ? e : { 'default': e }; }

		var SG__default = /#__PURE__/_interopDefaultLegacy(SG);

		/**
		* Global spectra deconvolution
		* @param {object} data - Object data with x and y arrays
		* @param {Array<number>} [data.x] - Independent variable
		* @param {Array<number>} [data.y] - Dependent variable
		* @param {object} [options={}] - Options object
		* @param {object} [options.shape={}] - Object that specified the kind of shape to calculate the FWHM instead of width between inflection points. see https://mljs.github.io/peak-shape-generator/#inflectionpointswidthtofwhm
		* @param {object} [options.shape.kind='gaussian']
		* @param {object} [options.sgOptions] - Options object for Savitzky-Golay filter. See https://github.com/mljs/savitzky-golay-generalized#options
		* @param {number} [options.sgOptions.windowSize = 9] - points to use in the approximations
		* @param {number} [options.sgOptions.polynomial = 3] - degree of the polynomial to use in the approximations
		* @param {number} [options.minMaxRatio = 0.00025] - Threshold to determine if a given peak should be considered as a noise
		* @param {number} [options.broadRatio = 0.00] - If `broadRatio` is higher than 0, then all the peaks which second derivative
		* smaller than `broadRatio * maxAbsSecondDerivative` will be marked with the soft mask equal to true.
		* @param {number} [options.noiseLevel = 0] - Noise threshold in spectrum units
		* @param {boolean} [options.maxCriteria = true] - Peaks are local maximum(true) or minimum(false)
		* @param {boolean} [options.smoothY = true] - Select the peak intensities from a smoothed version of the independent variables
		* @param {boolean} [options.realTopDetection = false] - Use a quadratic optimizations with the peak and its 3 closest neighbors
		* to determine the true x,y values of the peak?
		* @param {number} [options.heightFactor = 0] - Factor to multiply the calculated height (usually 2)
		* @param {number} [options.derivativeThreshold = -1] - Filters based on the amplitude of the first derivative
		* @return {Array<object>}
		*/
		function gsd(data, options = {}) {
		let {
		noiseLevel,
		sgOptions = {
		windowSize: 9,
		polynomial: 3,
		},
		shape = { kind: 'gaussian' },
		smoothY = true,
		heightFactor = 0,
		broadRatio = 0.0,
		maxCriteria = true,
		minMaxRatio = 0.00025,
		derivativeThreshold = -1,
		realTopDetection = false,
		} = options;

		let { y: yIn, x } = data;

		const y = yIn.slice();
		let equalSpaced = isEqualSpaced(x);

		if (maxCriteria === false) {
		for (let i = 0; i < y.length; i++) {
		y[i] *= -1;
		}
		}

		if (noiseLevel === undefined) {
		noiseLevel = equalSpaced ? getNoiseLevel(y) : 0;
		}
		for (let i = 0; i < y.length; i++) {
		y[i] -= noiseLevel;
		}
		for (let i = 0; i < y.length; i++) {
		if (y[i] < 0) {
		y[i] = 0;
		}
		}
		// If the max difference between delta x is less than 5%, then,
		// we can assume it to be equally spaced variable
		let yData = y;
		let dY, ddY;
		const { windowSize, polynomial } = sgOptions;

		if (equalSpaced) {
		if (smoothY) {
		yData = SG__default["default"](y, x[1] - x[0], {
		windowSize,
		polynomial,
		derivative: 0,
		});
		}
		dY = SG__default["default"](y, x[1] - x[0], {
		windowSize,
		polynomial,
		derivative: 1,
		});
		ddY = SG__default["default"](y, x[1] - x[0], {
		windowSize,
		polynomial,
		derivative: 2,
		});
		} else {
		if (smoothY) {
		yData = SG__default["default"](y, x, {
		windowSize,
		polynomial,
		derivative: 0,
		});
		}
		dY = SG__default["default"](y, x, {
		windowSize,
		polynomial,
		derivative: 1,
		});
		ddY = SG__default["default"](y, x, {
		windowSize,
		polynomial,
		derivative: 2,
		});
		}

		const xData = x;
		const dX = x[1] - x[0];
		let maxDdy = 0;
		let maxY = 0;
		for (let i = 0; i < yData.length; i++) {
		if (Math.abs(ddY[i]) > maxDdy) {
		maxDdy = Math.abs(ddY[i]);
		}
		if (Math.abs(yData[i]) > maxY) {
		maxY = Math.abs(yData[i]);
		}
		}

		let lastMax = null;
		let lastMin = null;
		let minddY = [];
		let intervalL = [];
		let intervalR = [];
		let broadMask = [];

		// By the intermediate value theorem We cannot find 2 consecutive maximum or minimum
		for (let i = 1; i < yData.length - 1; ++i) {
		// filter based on derivativeThreshold
		if (Math.abs(dY[i]) > derivativeThreshold) {
		// Minimum in first derivative
		if (
		(dY[i] < dY[i - 1] && dY[i] <= dY[i + 1]) \|\|
		(dY[i] <= dY[i - 1] && dY[i] < dY[i + 1])
		) {
		lastMin = {
		x: xData[i],
		index: i,
		};
		if (dX > 0 && lastMax !== null) {
		intervalL.push(lastMax);
		intervalR.push(lastMin);
		}
		}

		// Maximum in first derivative
		if (
		(dY[i] >= dY[i - 1] && dY[i] > dY[i + 1]) \|\|
		(dY[i] > dY[i - 1] && dY[i] >= dY[i + 1])
		) {
		lastMax = {
		x: xData[i],
		index: i,
		};
		if (dX < 0 && lastMin !== null) {
		intervalL.push(lastMax);
		intervalR.push(lastMin);
		}
		}
		}

		// Minimum in second derivative
		if (ddY[i] < ddY[i - 1] && ddY[i] < ddY[i + 1]) {
		minddY.push(i);
		broadMask.push(Math.abs(ddY[i]) <= broadRatio * maxDdy);
		}
		}

		let widthProcessor = mlPeakShapeGenerator.getShape1D(shape.kind, shape.options).widthToFWHM;

		let signals = [];
		let lastK = -1;
		let possible, frequency, distanceJ, minDistance, gettingCloser;
		for (let j = 0; j < minddY.length; ++j) {
		frequency = xData[minddY[j]];
		possible = -1;
		let k = lastK + 1;
		minDistance = Number.MAX_VALUE;
		distanceJ = 0;
		gettingCloser = true;
		while (possible === -1 && k < intervalL.length && gettingCloser) {
		distanceJ = Math.abs(frequency - (intervalL[k].x + intervalR[k].x) / 2);

		// Still getting closer?
		if (distanceJ < minDistance) {
		minDistance = distanceJ;
		} else {
		gettingCloser = false;
		}
		if (distanceJ < Math.abs(intervalL[k].x - intervalR[k].x) / 2) {
		possible = k;
		lastK = k;
		}
		++k;
		}

		if (possible !== -1) {
		if (Math.abs(yData[minddY[j]]) > minMaxRatio * maxY) {
		let width = Math.abs(intervalR[possible].x - intervalL[possible].x);
		signals.push({
		index: minddY[j],
		x: frequency,
		y: maxCriteria
		? yData[minddY[j]] + noiseLevel
		: -yData[minddY[j]] - noiseLevel,
		shape: {
		kind: shape.kind,
		width: widthProcessor(width),
		soft: broadMask[j],
		},
		});

		if (heightFactor) {
		let yLeft = yData[intervalL[possible].index];
		let yRight = yData[intervalR[possible].index];
		signals[signals.length - 1].shape.height =
		heightFactor *
		(signals[signals.length - 1].y - (yLeft + yRight) / 2);
		}
		}
		}
		}

		if (realTopDetection) {
		determineRealTop(signals, xData, yData);
		}

		// Correct the values to fit the original spectra data
		for (let j = 0; j < signals.length; j++) {
		signals[j].shape.noiseLevel = noiseLevel;
		}

		signals.sort((a, b) => {
		return a.x - b.x;
		});

		return signals;
		}

		const isEqualSpaced = (x) => {
		let tmp;
		let maxDx = 0;
		let minDx = Number.MAX_SAFE_INTEGER;
		for (let i = 0; i < x.length - 1; ++i) {
		tmp = Math.abs(x[i + 1] - x[i]);
		if (tmp < minDx) {
		minDx = tmp;
		}
		if (tmp > maxDx) {
		maxDx = tmp;
		}
		}
		return (maxDx - minDx) / maxDx < 0.05;
		"use strict";
		var __createBinding = (this && this.__createBinding) \|\| (Object.create ? (function(o, m, k, k2) {
		if (k2 === undefined) k2 = k;
		Object.defineProperty(o, k2, { enumerable: true, get: function() { return m[k]; } });
		}) : (function(o, m, k, k2) {
		if (k2 === undefined) k2 = k;
		o[k2] = m[k];
		}));
		var __exportStar = (this && this.__exportStar) \|\| function(m, exports) {
		for (var p in m) if (p !== "default" && !Object.prototype.hasOwnProperty.call(exports, p)) __createBinding(exports, m, p);
		};

		const getNoiseLevel = (y) => {
		let mean = 0;

		let stddev = 0;
		let length = y.length;
		for (let i = 0; i < length; ++i) {
		mean += y[i];
		}
		mean /= length;
		let averageDeviations = new Array(length);
		for (let i = 0; i < length; ++i) {
		averageDeviations[i] = Math.abs(y[i] - mean);
		}
		averageDeviations.sort((a, b) => a - b);
		if (length % 2 === 1) {
		stddev = averageDeviations[(length - 1) / 2] / 0.6745;
		} else {
		stddev =
		(0.5 *
		(averageDeviations[length / 2] + averageDeviations[length / 2 - 1])) /
		0.6745;
		}

		return stddev;
		};

		const determineRealTop = (peakList, x, y) => {
		let alpha, beta, gamma, p, currentPoint;
		for (let j = 0; j < peakList.length; j++) {
		currentPoint = peakList[j].index; // peakList[j][2];
		// The detected peak could be moved 1 or 2 units to left or right.
		if (
		y[currentPoint - 1] >= y[currentPoint - 2] &&
		y[currentPoint - 1] >= y[currentPoint]
		) {
		currentPoint--;
		} else {
		if (
		y[currentPoint + 1] >= y[currentPoint] &&
		y[currentPoint + 1] >= y[currentPoint + 2]
		) {
		currentPoint++;
		} else {
		if (
		y[currentPoint - 2] >= y[currentPoint - 3] &&
		y[currentPoint - 2] >= y[currentPoint - 1]
		) {
		currentPoint -= 2;
		} else {
		if (
		y[currentPoint + 2] >= y[currentPoint + 1] &&
		y[currentPoint + 2] >= y[currentPoint + 3]
		) {
		currentPoint += 2;
		}
		}
		}
		}
		// interpolation to a sin() function
		if (
		y[currentPoint - 1] > 0 &&
		y[currentPoint + 1] > 0 &&
		y[currentPoint] >= y[currentPoint - 1] &&
		y[currentPoint] >= y[currentPoint + 1] &&
		(y[currentPoint] !== y[currentPoint - 1] \|\|
		y[currentPoint] !== y[currentPoint + 1])
		) {
		alpha = 20 * Math.log10(y[currentPoint - 1]);
		beta = 20 * Math.log10(y[currentPoint]);
		gamma = 20 * Math.log10(y[currentPoint + 1]);
		p = (0.5 * (alpha - gamma)) / (alpha - 2 * beta + gamma);
		// console.log(alpha, beta, gamma, `p: ${p}`);
		// console.log(x[currentPoint]+" "+tmp+" "+currentPoint);
		peakList[j].x =
		x[currentPoint] + (x[currentPoint] - x[currentPoint - 1]) * p;
		peakList[j].y =
		y[currentPoint] -
		0.25 * (y[currentPoint - 1] - y[currentPoint + 1]) * p;
		}
		}
		};

		/**
		* Group peaks based on factor and add group property in peaks
		* @param {array} peakList
		* @param {number} factor
		*/

		function groupPeaks(peakList, factor = 1) {
		if (peakList.length === 0) return [];

		let peaks = JSON.parse(JSON.stringify(peakList));
		peaks.sort((a, b) => a.x - b.x);

		let previousPeak = { x: Number.NEGATIVE_INFINITY, shape: { width: 1 } };
		let currentGroup = [previousPeak];
		let groups = [];
		for (let peak of peaks) {
		if (
		(peak.x - previousPeak.x) /
		(peak.shape.width + previousPeak.shape.width) <=
		factor / 2
		) {
		currentGroup.push(peak);
		} else {
		currentGroup = [peak];
		groups.push(currentGroup);
		}
		previousPeak = peak;
		}

		return groups;
		}

		/**
		* Optimize the position (x), max intensity (y), full width at half maximum (width)
		* and the ratio of gaussian contribution (mu) if it's required. It supports three kind of shapes: gaussian, lorentzian and pseudovoigt
		* @param {object} data - An object containing the x and y data to be fitted.
		* @param {Array} peakList - A list of initial parameters to be optimized. e.g. coming from a peak picking [{x, y, width}].
		* @param {object} [options = {}] -
		* @param {number} [options.factorWidth = 1] - times of width to group peaks.
		* @param {number} [options.factorLimits = 2] - times of width to use to optimize peaks
		* @param {object} [options.shape={}] - it's specify the kind of shape used to fitting.
		* @param {string} [options.shape.kind='gaussian'] - kind of shape; lorentzian, gaussian and pseudovoigt are supported.
		* @param {string} [options.shape.options={}] - options depending the kind of shape
		* @param {object} [options.optimization={}] - it's specify the kind and options of the algorithm use to optimize parameters.
		* @param {string} [options.optimization.kind='lm'] - kind of algorithm. By default it's levenberg-marquardt.
		* @param {object} [options.optimization.options={}] - options for the specific kind of algorithm.
		* @param {number} [options.optimization.options.timeout=10] - maximum time running before break in seconds.
		*/

		function optimizePeaks(data, peakList, options = {}) {
		const {
		factorWidth = 1,
		factorLimits = 2,
		shape = {
		kind: 'gaussian',
		},
		optimization = {
		kind: 'lm',
		options: {
		timeout: 10,
		},
		},
		} = options;

		if (data.x[0] > data.x[1]) {
		data.x.reverse();
		data.y.reverse();
		}

		let groups = groupPeaks(peakList, factorWidth);

		let results = [];
		for (const peaks of groups) {
		const firstPeak = peaks[0];
		const lastPeak = peaks[peaks.length - 1];

		const from = firstPeak.x - firstPeak.shape.width * factorLimits;
		const to = lastPeak.x + lastPeak.shape.width * factorLimits;
		const { fromIndex, toIndex } = mlSpectraProcessing.xGetFromToIndex(data.x, { from, to });
		// Multiple peaks
		const currentRange = {
		x: data.x.slice(fromIndex, toIndex),
		y: data.y.slice(fromIndex, toIndex),
		};
		if (currentRange.x.length > 5) {
		let { peaks: optimizedPeaks } = mlSpectraFitting.optimize(currentRange, peaks, {
		shape,
		optimization,
		});
		results = results.concat(optimizedPeaks);
		} else {
		results = results.concat(peaks);
		}
		}
		return results;
		}

		/**
		* This function try to join the peaks that seems to belong to a broad signal in a single broad peak.
		* @param {Array} peaks - A list of initial parameters to be optimized. e.g. coming from a peak picking [{x, y, width}].
		* @param {object} [options = {}] - options
		* @param {number} [options.width=0.25] - width limit to join peaks.
		* @param {object} [options.shape={}] - it's specify the kind of shape used to fitting.
		* @param {string} [options.shape.kind = 'gaussian'] - kind of shape; lorentzian, gaussian and pseudovoigt are supported.
		* @param {object} [options.optimization = {}] - it's specify the kind and options of the algorithm use to optimize parameters.
		* @param {string} [options.optimization.kind = 'lm'] - kind of algorithm. By default it's levenberg-marquardt.
		* @param {number} [options.optimization.options.timeout = 10] - maximum time running before break in seconds.
		* @param {object} [options.optimization.options = {}] - options for the specific kind of algorithm.
		*/
		function joinBroadPeaks(peakList, options = {}) {
		let {
		width = 0.25,
		shape = { kind: 'gaussian' },
		optimization = { kind: 'lm', timeout: 10 },
		} = options;
		let broadLines = [];
		// Optimize the possible broad lines
		let max = 0;
		let maxI = 0;
		let count = 1;

		const peaks = JSON.parse(JSON.stringify(peakList));
		for (let i = peaks.length - 1; i >= 0; i--) {
		if (peaks[i].shape.soft) {
		broadLines.push(peaks.splice(i, 1)[0]);
		}
		}
		// Push a feke peak
		broadLines.push({ x: Number.MAX_VALUE });

		let candidates = { x: [broadLines[0].x], y: [broadLines[0].y] };
		let indexes = [0];
		for (let i = 1; i < broadLines.length; i++) {
		if (Math.abs(broadLines[i - 1].x - broadLines[i].x) < width) {
		candidates.x.push(broadLines[i].x);
		candidates.y.push(broadLines[i].y);
		if (broadLines[i].y > max) {
		max = broadLines[i].y;
		maxI = i;
		}
		indexes.push(i);
		count++;
		} else {
		if (count > 2) {
		let fitted = mlSpectraFitting.optimize(
		candidates,
		[
		{
		x: broadLines[maxI].x,
		y: max,
		shape: {
		width: Math.abs(
		candidates.x[0] - candidates.x[candidates.x.length - 1],
		),
		},
		},
		],
		{ shape, optimization },
		);
		let { peaks: peak } = fitted;
		peak[0].index = Math.floor(
		indexes.reduce((a, b) => a + b, 0) / indexes.length,
		);
		peak[0].shape.soft = false;
		peaks.push(peak[0]);
		} else {
		// Put back the candidates to the signals list
		indexes.forEach((index) => {
		peaks.push(broadLines[index]);
		});
		}
		candidates = { x: [broadLines[i].x], y: [broadLines[i].y] };
		indexes = [i];
		max = broadLines[i].y;
		maxI = i;
		count = 1;
		}
		}
		peaks.sort((a, b) => {
		return a.x - b.x;
		});

		return peaks;
		}

		/**
		* This method will allow to enlarge peaks and prevent overlap between peaks
		* Because peaks may not be symmetric after we add 2 properties, from and to.
		* @param {Array} peakList
		* @param {object} [options={}]
		* @param {number} [options.factor=2]
		* @param {boolean} [options.overlap=false] by default we don't allow overlap
		* @return {Array} peakList
		*/
		function broadenPeaks(peakList, options = {}) {
		const { factor = 2, overlap = false } = options;

		const peaks = JSON.parse(JSON.stringify(peakList));

		for (let peak of peaks) {
		peak.from = peak.x - (peak.shape.width / 2) * factor;
		peak.to = peak.x + (peak.shape.width / 2) * factor;
		}

		if (!overlap) {
		for (let i = 0; i < peaks.length - 1; i++) {
		let peak = peaks[i];
		let nextPeak = peaks[i + 1];
		if (peak.to > nextPeak.from) {
		peak.to = nextPeak.from = (peak.to + nextPeak.from) / 2;
		}
		}
		}

		for (let peak of peaks) {
		peak.shape.width = peak.to - peak.from;
		}

		return peaks.map((peak) => {
		const { x, y, shape } = peak;
		return { x, y, shape };
		});
		}

		exports.broadenPeaks = broadenPeaks;
		exports.gsd = gsd;
		exports.joinBroadPeaks = joinBroadPeaks;
		exports.optimizePeaks = optimizePeaks;
		Object.defineProperty(exports, "__esModule", { value: true });
		__exportStar(require("./gsd"), exports);
		__exportStar(require("./post/optimizePeaks"), exports);
		__exportStar(require("./post/joinBroadPeaks"), exports);
		__exportStar(require("./post/broadenPeaks"), exports);
		//# sourceMappingURL=index.js.map

package.json

		{
		"name": "ml-gsd",
		"version": "7.0.1",
		"version": "8.0.0",
		"description": "Global Spectra Deconvolution",
		"main": "lib/index.js",
		"module": "src/index.js",
		"main": "./lib/index.js",
		"module": "./lib-esm/index.js",
		"types": "./lib/index.d.ts",
		"files": [
		"lib",
		"src"
		"src",
		"lib-esm"
		],
		@@ -15,13 +17,16 @@ "env": {
		"scripts": {
		"build": "rollup -c && cheminfo-build --entry src/index.js --root GSD",
		"build": "npm run tsc-esm && cheminfo-build --entry lib-esm/index.js --root GSD",
		"check-types": "tsc --noEmit",
		"clean": "rimraf lib lib-esm",
		"example": "nodemon -w src -w examples/example.js -r esm examples/example.js",
		"eslint": "eslint src --cache",
		"eslint-fix": "npm run eslint -- --fix",
		"compile": "rollup -c",
		"prepack": "npm run compile",
		"prepack": "npm run tsc",
		"prettier": "prettier --check src",
		"prettier-write": "prettier --write src",
		"test": "npm run test-coverage && npm run eslint",
		"test-only": "jest",
		"test-coverage": "jest --coverage"
		"test": "npm run test-only && npm run eslint && npm run check-types",
		"test-only": "jest --coverage",
		"tsc": "npm run clean && npm run tsc-cjs && npm run tsc-esm",
		"tsc-cjs": "tsc --project tsconfig.cjs.json",
		"tsc-esm": "tsc --project tsconfig.esm.json"
		},
		@@ -49,5 +54,2 @@ "repository": {
		"homepage": "https://github.com/mljs/global-spectral-deconvolution",
		"jest": {
		"testEnvironment": "node"
		},
		"prettier": {
		@@ -61,21 +63,24 @@ "arrowParens": "always",
		"devDependencies": {
		"@babel/plugin-transform-modules-commonjs": "^7.15.4",
		"@types/jest": "^27.0.2",
		"chemcalc": "^3.4.1",
		"cheminfo-build": "^1.1.11",
		"eslint": "^7.32.0",
		"eslint-config-cheminfo": "^5.5.0",
		"eslint": "^8.1.0",
		"eslint-config-cheminfo-typescript": "^10.1.1",
		"eslint-plugin-import": "^2.25.2",
		"eslint-plugin-jest": "^25.2.2",
		"esm": "^3.2.25",
		"jest": "^27.2.4",
		"jest-matcher-deep-close-to": "^3.0.0",
		"mf-global": "^1.4.6",
		"jest": "^27.3.1",
		"jest-matcher-deep-close-to": "^3.0.2",
		"mf-global": "^1.4.7",
		"ml-stat": "^1.3.3",
		"nodemon": "^2.0.13",
		"nodemon": "^2.0.14",
		"prettier": "^2.4.1",
		"rollup": "^2.58.0",
		"spectrum-generator": "^5.4.0",
		"rimraf": "^3.0.2",
		"spectrum-generator": "^5.4.1",
		"ts-jest": "^27.0.7",
		"typescript": "^4.4.4",
		"xy-parser": "^3.2.0"
		},
		"dependencies": {
		"cheminfo-types": "^0.5.0",
		"cheminfo-types": "^0.6.0",
		"ml-peak-shape-generator": "^2.0.2",
		@@ -82,0 +87,0 @@ "ml-savitzky-golay-generalized": "2.0.3",

377

src/__tests__/data/C2.json

		@@ -1,1 +0,376 @@
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		24.528, 24.529, 24.53, 24.531, 24.532, 24.533, 24.534, 24.535, 24.536,
		24.537, 24.538, 24.539, 24.54, 24.541, 24.542, 24.543, 24.544, 24.545,
		24.546, 24.547, 24.548, 24.549, 24.55, 24.551, 24.552, 24.553, 24.554,
		24.555, 24.556, 24.557, 24.558, 24.559, 24.56, 24.561, 24.562, 24.563,
		24.564, 24.565, 24.566, 24.567, 24.568, 24.569, 24.57, 24.571, 24.572,
		24.573, 24.574, 24.575, 24.576, 24.577, 24.578, 24.579, 24.58, 24.581,
		24.582, 24.583, 24.584, 24.585, 24.586, 24.587, 24.588, 24.589, 24.59,
		24.591, 24.592, 24.593, 24.594, 24.595, 24.596, 24.597, 24.598, 24.599,
		24.6, 24.601, 24.602, 24.603, 24.604, 24.605, 24.606, 24.607, 24.608,
		24.609, 24.61, 24.611, 24.612, 24.613, 24.614, 24.615, 24.616, 24.617,
		24.618, 24.619, 24.62, 24.621, 24.622, 24.623, 24.624, 24.625, 24.626,
		24.627, 24.628, 24.629, 24.63, 24.631, 24.632, 24.633, 24.634, 24.635,
		24.636, 24.637, 24.638, 24.639, 24.64, 24.641, 24.642, 24.643, 24.644,
		24.645, 24.646, 24.647, 24.648, 24.649, 24.65, 24.651, 24.652, 24.653,
		24.654, 24.655, 24.656, 24.657, 24.658, 24.659, 24.66, 24.661, 24.662,
		24.663, 24.664, 24.665, 24.666, 24.667, 24.668, 24.669, 24.67, 24.671,
		24.672, 24.673, 24.674, 24.675, 24.676, 24.677, 24.678, 24.679, 24.68,
		24.681, 24.682, 24.683, 24.684, 24.685, 24.686, 24.687, 24.688, 24.689,
		24.69, 24.691, 24.692, 24.693, 24.694, 24.695, 24.696, 24.697, 24.698,
		24.699, 24.7, 24.701, 24.702, 24.703, 24.704, 24.705, 24.706, 24.707,
		24.708, 24.709, 24.71, 24.711, 24.712, 24.713, 24.714, 24.715, 24.716,
		24.717, 24.718, 24.719, 24.72, 24.721, 24.722, 24.723, 24.724, 24.725,
		24.726, 24.727, 24.728, 24.729, 24.73, 24.731, 24.732, 24.733, 24.734,
		24.735, 24.736, 24.737, 24.738, 24.739, 24.74, 24.741, 24.742, 24.743,
		24.744, 24.745, 24.746, 24.747, 24.748, 24.749, 24.75, 24.751, 24.752,
		24.753, 24.754, 24.755, 24.756, 24.757, 24.758, 24.759, 24.76, 24.761,
		24.762, 24.763, 24.764, 24.765, 24.766, 24.767, 24.768, 24.769, 24.77,
		24.771, 24.772, 24.773, 24.774, 24.775, 24.776, 24.777, 24.778, 24.779,
		24.78, 24.781, 24.782, 24.783, 24.784, 24.785, 24.786, 24.787, 24.788,
		24.789, 24.79, 24.791, 24.792, 24.793, 24.794, 24.795, 24.796, 24.797,
		24.798000000000002, 24.799, 24.8, 24.801, 24.802, 24.803, 24.804, 24.805,
		24.806, 24.807, 24.808, 24.809, 24.81, 24.811, 24.812, 24.813, 24.814,
		24.815, 24.816, 24.817, 24.818, 24.819, 24.82, 24.821, 24.822, 24.823,
		24.824, 24.825, 24.826, 24.827, 24.828, 24.829, 24.83, 24.831, 24.832,
		24.833, 24.834, 24.835, 24.836, 24.837, 24.838, 24.839, 24.84, 24.841,
		24.842, 24.843, 24.844, 24.845, 24.846, 24.847, 24.848, 24.849, 24.85,
		24.851, 24.852, 24.853, 24.854, 24.855, 24.856, 24.857, 24.858, 24.859,
		24.86, 24.861, 24.862000000000002, 24.863, 24.864, 24.865, 24.866, 24.867,
		24.868, 24.869, 24.87, 24.871, 24.872, 24.873, 24.874, 24.875, 24.876,
		24.877, 24.878, 24.879, 24.88, 24.881, 24.882, 24.883, 24.884, 24.885,
		24.886, 24.887, 24.888, 24.889, 24.89, 24.891, 24.892, 24.893, 24.894,
		24.895, 24.896, 24.897, 24.898, 24.899, 24.9, 24.901, 24.902, 24.903,
		24.904, 24.905, 24.906, 24.907, 24.908, 24.909, 24.91, 24.911, 24.912,
		24.913, 24.914, 24.915, 24.916, 24.917, 24.918, 24.919, 24.92, 24.921,
		24.922, 24.923000000000002, 24.924, 24.925, 24.926, 24.927, 24.928, 24.929,
		24.93, 24.931, 24.932, 24.933, 24.934, 24.935, 24.936, 24.937, 24.938,
		24.939, 24.94, 24.941, 24.942, 24.943, 24.944, 24.945, 24.946, 24.947,
		24.948, 24.949, 24.95, 24.951, 24.952, 24.953, 24.954, 24.955, 24.956,
		24.957, 24.958, 24.959, 24.96, 24.961, 24.962, 24.963, 24.964, 24.965,
		24.966, 24.967, 24.968, 24.969, 24.97, 24.971, 24.972, 24.973, 24.974,
		24.975, 24.976, 24.977, 24.978, 24.979, 24.98, 24.981, 24.982, 24.983,
		24.984, 24.985, 24.986, 24.987000000000002, 24.988, 24.989, 24.99, 24.991,
		24.992, 24.993, 24.994, 24.995, 24.996, 24.997, 24.998, 24.999, 25, 25.001,
		25.002, 25.003, 25.004, 25.005, 25.006, 25.007, 25.008, 25.009, 25.01,
		25.011, 25.012, 25.012999999999998, 25.014, 25.015, 25.016, 25.017, 25.018,
		25.019, 25.02, 25.021, 25.022, 25.023, 25.024, 25.025, 25.026, 25.027,
		25.028, 25.029, 25.03, 25.031, 25.032, 25.033, 25.034, 25.035, 25.036,
		25.037, 25.038, 25.039, 25.04, 25.041, 25.042, 25.043, 25.044, 25.045,
		25.046, 25.047, 25.048000000000002, 25.049, 25.05, 25.051, 25.052, 25.053,
		25.054, 25.055, 25.056, 25.057, 25.058, 25.059, 25.06, 25.061, 25.062,
		25.063, 25.064, 25.065, 25.066, 25.067, 25.068, 25.069, 25.07, 25.071,
		25.072, 25.073, 25.074, 25.075, 25.076, 25.076999999999998, 25.078, 25.079,
		25.08, 25.081, 25.082, 25.083, 25.084, 25.085, 25.086, 25.087, 25.088,
		25.089, 25.09, 25.091, 25.092, 25.093, 25.094, 25.095, 25.096, 25.097,
		25.098, 25.099, 25.1, 25.101, 25.102, 25.103, 25.104, 25.105, 25.106,
		25.107, 25.108, 25.109, 25.11, 25.111, 25.112000000000002, 25.113, 25.114,
		25.115, 25.116, 25.117, 25.118, 25.119, 25.12, 25.121, 25.122, 25.123,
		25.124, 25.125, 25.126, 25.127, 25.128, 25.129, 25.13, 25.131, 25.132,
		25.133, 25.134, 25.135, 25.136, 25.137, 25.137999999999998, 25.139, 25.14,
		25.141, 25.142, 25.143, 25.144, 25.145, 25.146, 25.147, 25.148, 25.149,
		25.15, 25.151, 25.152, 25.153, 25.154, 25.155, 25.156, 25.157, 25.158,
		25.159, 25.16, 25.161, 25.162, 25.163, 25.164, 25.165, 25.166, 25.167,
		25.168, 25.169, 25.17, 25.171, 25.172, 25.173000000000002, 25.174, 25.175,
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		25.185, 25.186, 25.187, 25.188, 25.189, 25.19, 25.191, 25.192, 25.193,
		25.194, 25.195, 25.196, 25.197, 25.198, 25.199, 25.2, 25.201,
		25.201999999999998, 25.203, 25.204, 25.205, 25.206, 25.207, 25.208, 25.209,
		25.21, 25.211, 25.212, 25.213, 25.214, 25.215, 25.216, 25.217, 25.218,
		25.219, 25.22, 25.221, 25.222, 25.223, 25.224, 25.225, 25.226, 25.227,
		25.228, 25.229, 25.23, 25.231, 25.232, 25.233, 25.234, 25.235, 25.236,
		25.237000000000002, 25.238, 25.239, 25.24, 25.241, 25.242, 25.243, 25.244,
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		25.281, 25.282, 25.283, 25.284, 25.285, 25.286, 25.287, 25.288, 25.289,
		25.29, 25.291, 25.292, 25.293, 25.294, 25.295, 25.296, 25.297,
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		25.306, 25.307, 25.308, 25.309, 25.31, 25.311, 25.312, 25.313, 25.314,
		25.315, 25.316, 25.317, 25.318, 25.319, 25.32, 25.321, 25.322, 25.323,
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		25.341, 25.342, 25.343, 25.344, 25.345, 25.346, 25.347, 25.348, 25.349,
		25.35, 25.351, 25.352, 25.353, 25.354, 25.355, 25.356, 25.357, 25.358,
		25.359, 25.36, 25.361, 25.362, 25.363, 25.364, 25.365, 25.366, 25.367,
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		25.377, 25.378, 25.379, 25.38, 25.381, 25.382, 25.383, 25.384, 25.385,
		25.386, 25.387, 25.388, 25.389, 25.39, 25.391, 25.392, 25.393, 25.394,
		25.395, 25.396, 25.397, 25.398, 25.399, 25.4, 25.401, 25.402, 25.403,
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		25.413, 25.414, 25.415, 25.416, 25.417, 25.418, 25.419, 25.42, 25.421,
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		25.448, 25.449, 25.45, 25.451, 25.451999999999998, 25.453, 25.454, 25.455,
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		25.474, 25.475, 25.476, 25.477, 25.478, 25.479, 25.48, 25.481, 25.482,
		25.483, 25.484, 25.485, 25.486, 25.487, 25.488, 25.489, 25.49, 25.491,
		25.492, 25.493, 25.494, 25.495, 25.496, 25.497, 25.498, 25.499, 25.5,
		25.501, 25.502, 25.503, 25.504, 25.505, 25.506, 25.507, 25.508, 25.509,
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		25.546, 25.547, 25.548000000000002, 25.549, 25.55, 25.551, 25.552, 25.553,
		25.554, 25.555, 25.556, 25.557, 25.558, 25.559, 25.56, 25.561, 25.562,
		25.563, 25.564, 25.565, 25.566, 25.567, 25.568, 25.569, 25.57, 25.571,
		25.572, 25.573, 25.574, 25.575, 25.576, 25.576999999999998, 25.578, 25.579,
		25.58, 25.581, 25.582, 25.583, 25.584, 25.585, 25.586, 25.587, 25.588,
		25.589, 25.59, 25.591, 25.592, 25.593, 25.594, 25.595, 25.596, 25.597,
		25.598, 25.599, 25.6, 25.601, 25.602, 25.603, 25.604, 25.605, 25.606,
		25.607, 25.608, 25.609, 25.61, 25.611, 25.612, 25.613, 25.614, 25.615,
		25.616, 25.617, 25.618, 25.619, 25.62, 25.621, 25.622, 25.623, 25.624,
		25.625, 25.626, 25.627, 25.628, 25.629, 25.63, 25.631, 25.632, 25.633,
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		25.652, 25.653, 25.654, 25.655, 25.656, 25.657, 25.658, 25.659, 25.66,
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		25.882, 25.883, 25.884, 25.885, 25.886, 25.887, 25.888, 25.889, 25.89,
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559

src/__tests__/data/infraRed.json

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		}

src/__tests__/data/test.json

		@@ -1,1 +0,36 @@
		[[7,9,9.1,9.2,9.3,9.4,9.5,9.6,9.7,9.8,9.9,10,10.1,10.2,10.3,10.4,10.5,10.6,10.7,10.8,10.9,11,11.1,11.2,11.3,11.4,11.5,11.6,11.7,11.8,11.9,12,12.1,12.2,12.3,12.4,12.5,12.6,12.7,12.8,12.9,13,13.1,13.2,13.3,13.4,13.5,13.6,13.7,13.8,13.9,14,14.1,14.2,14.3,14.4,14.5,14.6,14.7,14.8,14.9,15,15.1,15.2,15.3,15.4,15.5,15.6,15.7,15.8,15.9,16,18],[0,1.3670611642005019e-12,7.018086806749659e-12,3.408530039598323e-11,1.566149139777829e-10,6.807955480447043e-10,2.799741264282628e-9,1.0892728768715286e-8,4.0093417978312345e-8,1.3961339042194703e-7,4.5993733696714487e-7,0.0000014334675420984624,0.000004226634174912734,0.000011790142647798723,0.00003111437370683429,0.00007768204955055934,0.00018348387377726662,0.0004100083945771263,0.0008667727242782787,0.001733546091298024,0.0032800711886719187,0.005871498495868112,0.009943347114095245,0.01593068598959557,0.0241465479122752,0.03462542672692695,0.046973848446379925,0.06028934116907687,0.07320700001112898,0.0841007412472281,0.09141030799602905,0.09400723223468063,0.09148237573734981,0.08425429229202339,0.0734587840992098,0.06065939675121234,0.04747989885270652,0.0352766117093386,0.024937897013924,0.016839966447159693,0.010931586752334044,0.0068875528273207405,0.004268351566479456,0.0026429525578170743,0.001658457916881255,0.001062033447037501,0.0006915187612199856,0.00045217216244198535,0.00029227323368097015,0.00018409073424885283,0.00011177068037381833,0.00006493783224280769,0.00003593624229100207,0.00001888916056485795,0.000009414867005196313,0.000004445430848023085,0.0000019873111386235026,8.408686570700081e-7,3.366812086048201e-7,1.2755306072424386e-7,4.5721144094463724e-8,1.5505362353033094e-8,4.974557268319468e-9,1.5100204968309241e-9,4.3363951518037203e-10,1.1781279472885229e-10,3.028124080443153e-11,7.363299670553255e-12,1.6939043561733317e-12,3.6865734785911304e-13,7.590572003661311e-14,1.4785762111538834e-14,0]]
		[
		[
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		10.4, 10.5, 10.6, 10.7, 10.8, 10.9, 11, 11.1, 11.2, 11.3, 11.4, 11.5, 11.6,
		11.7, 11.8, 11.9, 12, 12.1, 12.2, 12.3, 12.4, 12.5, 12.6, 12.7, 12.8, 12.9,
		13, 13.1, 13.2, 13.3, 13.4, 13.5, 13.6, 13.7, 13.8, 13.9, 14, 14.1, 14.2,
		14.3, 14.4, 14.5, 14.6, 14.7, 14.8, 14.9, 15, 15.1, 15.2, 15.3, 15.4, 15.5,
		15.6, 15.7, 15.8, 15.9, 16, 18
		],
		[
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		0.000004445430848023085, 0.0000019873111386235026, 8.408686570700081e-7,
		3.366812086048201e-7, 1.2755306072424386e-7, 4.5721144094463724e-8,
		1.5505362353033094e-8, 4.974557268319468e-9, 1.5100204968309241e-9,
		4.3363951518037203e-10, 1.1781279472885229e-10, 3.028124080443153e-11,
		7.363299670553255e-12, 1.6939043561733317e-12, 3.6865734785911304e-13,
		7.590572003661311e-14, 1.4785762111538834e-14, 0
		]
		]

src/__tests__/bigLowS2NSpectrum.test.js

src/__tests__/broadNMR.test.js

src/__tests__/ethylvinylether.test.js

src/__tests__/general.test.js

src/__tests__/infraRed.test.js

src/__tests__/massPeakPicking.test.js

src/__tests__/simple.test.js

src/__tests__/simpleShifted.test.js

src/__tests__/simulated.test.js

src/__tests__/ubiquitin.test.js

src/__tests__/zero.test.js

src/gsd.js

src/index.js

src/post/__tests__/broadenPeaks.test.js

src/post/__tests__/groupPeaks.test.js

src/post/__tests__/optimizePeaks.test.js

src/post/broadenPeaks.js

src/post/groupPeaks.js

src/post/joinBroadPeaks.js

src/post/optimizePeaks.js

src/__tests__/data/bigLowS2NSpectrum.json

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src/__tests__/data/broadNMR.json

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src/__tests__/data/ethylvinylether.json

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