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