Result for 4A66745E62E55A17E9570D15EF1F048E08C30909

Query result

Key Value
FileName./usr/lib/python3/dist-packages/pyspectral/atm_correction_ir.py
FileSize5188
MD5F57036077776B966C6D9E363E28D7FD7
SHA-14A66745E62E55A17E9570D15EF1F048E08C30909
SHA-2563DE7089BE7E77675CE22146A89F82879447B17FB2754491CAC2EB0EAE331AEA3
SSDEEP96:VWzmLiMsV9YFM/dfgMdDZnlMBEqr9j3LMqcHRfMdjxmsUMk2MX2UxMV/iH6WJO:Cm2MsVCM1fgMdZnlMB79jb0MHm7Mk2MM
TLSHT1E7B1D81BF7044234B1126DB7A58BA382E72DBD27160856283C6CD2065F278B6C3B73D9
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