List of Routines By Functionality | MISR Toolkit: Main Page
-Abstract
MTK_REGRESSION_COEFF_CALC Calculate linear regression coefficients for translating values in data buffer 1 to corresponding values in data buffer 2.
-Copyright
Copyright (2013), California Institute of Technology.
U.S. Government sponsorship acknowledged.
-I/O
Given:
data1 Data Buffer 1
valid_mask1 Valid Mask for Buffer 1
data2 Data Buffer 2
data2_sigma Uncertainty
valid_mask2 Valid Mask for Buffer 2
map_info Map info for input data
size_factor Number of pixel to aggregate
the call:
status = MTK_REGRESSION_COEFF_CALC( data1, valid_mask1, data2, data2_sigma, valid_mask2, mapinfo, size_factor, regression_coeff, regression_coeff_map_info )
returns:
status 0 on success; otherwise failure
regression_coeff Structure with 4 data buffers contain regression coefficient information (valid_mask, slope, intercept, correlation)
regression_coeff_map_info Map info for regression coefficients
-Examples
;;
;; Set up input parameters
;;
data1 = RANDOMU(seed, 512, 704)
valid_mask1 = byte(replicate(1,512,704))
data2 = RANDOMU(seed, 512, 704)
data2_sigma = RANDOMU(seed, 512, 704)
valid_mask2 = byte(replicate(1,512,704))
path = 37
resolution = 275
lat = 66.0
lon = -89.0
lat_extent = 1.5
lon_extent = 1.0
status = MTK_SETREGION_BY_LATLON_EXTENT( lat, lon, lat_extent, lon_extent, "degrees", region )
status = MTK_SNAP_TO_GRID( path, resolution, region, mapinfo )
size_factor = 2
;;
;; The call
;;
status = MTK_REGRESSION_COEFF_CALC( data1, valid_mask1, data2, data2_sigma, valid_mask2, mapinfo, size_factor, regression_coeff, regression_coeff_map_info )
;;
;; Output...
;;
print, '================================================='
help, regression_coeff
print, regression_coeff_map_info.nsample, regression_coeff_map_info.nline
IDL outputs:
=================================================
** Structure regression_coeff, 4 tags, length=2523136, data length=2523136:
VALID_MASK LONG Array[256, 352]
SLOPE FLOAT Array[256, 352]
INTERCEPT FLOAT Array[256, 352]
CORRELATION FLOAT Array[256, 352]
256 352
-Particulars
None.
-Required Reading
For important details concerning this module's function, please refer to
the MTK routine MtkRegressionCoeffCalc.c.
-Version
-IDL-MTK Version 1.2.4