Standard pyCIF control vector#
The control vector plugin includes sub-routines to compute operation related to uncertainty matrices, and stores the control vector meta-data and data themselves. Only a standard control vector including most commonly used control vector shapes is implemented yet.
Configuration#
The control vector is defined with the following parameters:
components:the different types of components in the control vector; accepts:
fluxes,prescrconcs,prodloss3dandinicondfluxes: fluxes to be optimizedspecies: each species is defined through a paragraph with the following parameters:hresol: the horizontal resolution; should be one of:hpixels: for individual pixelsbands: for zonal and meridional bandsregions: for pre-defined regionstype: (optional) the type of increments to deal with; should be one of:scalar: (default) increments are applied to the scaling factor of the priorphysical: valid only withcomponent`=`fluxesandhresol`=`hpixels
errtype: (optional) the type of error; if not specified, a scalar is applied to the prior value; ifmaxis given, computes the max of the neighboring cells (spatially and temporally)err: error as a proportion of prior fluxesdir: directory where data files are storedfile: file format of the datahcorrelations: (optional) information on horizontalcorrelations if any
filelsm: path to the land-sea mask filedump_hcorr: (optional) dump correlation matrix if True;default is True
dircorrel: directory where to save the correlation matrixsigma_land: correlation distance over land in kmsigma_sea: correlation distance over sea in kmtcorrelations(optional) information on temporalcorrelations if any
sigma_t: correlation period in hoursdump_tcorr: (optional) dump correlation matrix if True;default is True
dircorrel: directory where to save the correlation matrix