Result for 4664B3BB91CDE84FE1E749699AC102E4B775A96B

Query result

Key Value
FileName./usr/lib/python3/dist-packages/pyspectral/rayleigh.py
FileSize14615
MD566EF1AF1FBBB9B7C818AC41B4FCFC4B7
SHA-14664B3BB91CDE84FE1E749699AC102E4B775A96B
SHA-2561D059820698DEB9C4D1597434D4878C1123BAEDC1B5295536E34611A3F046936
SSDEEP384:OmKfL+TMGJ5PKjh6MOdhC/acM5MOITMBZMcMBM4c:OmKeajMDdc/acomE16Xc
TLSHT17E62B72E97116C23E2435DE748D76583677E4A530A4848A8BCBCC1642F1BE75C3E4BED
hashlookup:parent-total2
hashlookup:trust60

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Parents (Total: 2)

The searched file hash is included in 2 parent files which include package known and seen by metalookup. A sample is included below:

Key Value
FileSize172096
MD5638515C3A05034D18DD0E5D428B3E7CA
PackageDescriptionReading and manipulaing satellite sensor spectral responses Reading and manipulaing satellite sensor spectral responses and the solar spectrum, to perform various corrections to VIS and NIR band data. . Given a passive sensor on a meteorological satellite PySpectral provides the relative spectral response (rsr) function(s) and offer some basic operations like convolution with the solar spectrum to derive the in band solar flux, for instance. . The focus is on imaging sensors like AVHRR, VIIRS, MODIS, ABI, AHI, OLCI and SEVIRI. But more sensors are included and if others are needed they can be easily added. With PySpectral it is possible to derive the reflective and emissive parts of the signal observed in any NIR band around 3-4 microns where both passive terrestrial emission and solar backscatter mix the information received by the satellite. Furthermore PySpectral allows correcting true color imagery for the background (climatological) atmospheric signal due to Rayleigh scattering of molecules, absorption by atmospheric gases and aerosols, and Mie scattering of aerosols.
PackageMaintainerUbuntu Developers <ubuntu-devel-discuss@lists.ubuntu.com>
PackageNamepython3-pyspectral
PackageSectionpython
PackageVersion0.9.5+ds-1
SHA-1987C45577B9C254F644BB75981518844F9EE34B3
SHA-256AEA8177DBE8D3E880C1D06CFB50F4F27362C8EF7316E2EB41985F429DF5A773E
Key Value
FileSize185880
MD50916E097D0356A42C436CE0966AF9955
PackageDescriptionReading and manipulaing satellite sensor spectral responses Reading and manipulaing satellite sensor spectral responses and the solar spectrum, to perform various corrections to VIS and NIR band data. . Given a passive sensor on a meteorological satellite PySpectral provides the relative spectral response (rsr) function(s) and offer some basic operations like convolution with the solar spectrum to derive the in band solar flux, for instance. . The focus is on imaging sensors like AVHRR, VIIRS, MODIS, ABI, AHI, OLCI and SEVIRI. But more sensors are included and if others are needed they can be easily added. With PySpectral it is possible to derive the reflective and emissive parts of the signal observed in any NIR band around 3-4 microns where both passive terrestrial emission and solar backscatter mix the information received by the satellite. Furthermore PySpectral allows correcting true color imagery for the background (climatological) atmospheric signal due to Rayleigh scattering of molecules, absorption by atmospheric gases and aerosols, and Mie scattering of aerosols.
PackageMaintainerUbuntu Developers <ubuntu-devel-discuss@lists.ubuntu.com>
PackageNamepython3-pyspectral
PackageSectionpython
PackageVersion0.10.0+ds-1
SHA-16360BE7F1423D6E8D9DDCC4228F466C8D3B82019
SHA-256CDE1AD967F6C32FA2A11F150B174E8D812AE262A842DE45BB9B62624B1C31174