clip5imgs = ["/Users/phoetrymaster/Documents/School/Geography/Thesis/Data/MODIS_KANSAS_2007-2012/reprojected/clips/KansasNDVI_2012_clip5.tif", "/Users/phoetrymaster/Documents/School/Geography/Thesis/Data/MODIS_KANSAS_2007-2012/reprojected/clips/KansasEVI_2012_clip5.tif"] clip6imgs = ["/Users/phoetrymaster/Documents/School/Geography/Thesis/Data/MODIS_KANSAS_2007-2012/reprojected/clips/KansasNDVI_2012_clip6.tif", "/Users/phoetrymaster/Documents/School/Geography/Thesis/Data/MODIS_KANSAS_2007-2012/reprojected/clips/KansasEVI_2012_clip6.tif"] imagelist = [clip1imgs, clip2imgs, clip3imgs, clip4imgs, clip5imgs, clip6imgs] searchstrings = ["soy", "corn", "wwheat", "sorghum", "wwheatsoydbl"] fitmethods = ["SLSQP"]#, "TNC"] for method in fitmethods: for images in imagelist: for img in images: name = os.path.splitext(os.path.basename(img))[0] if "NDVI" in name: type = "NDVI" else: type = "EVI" for reffile, outfolder in zip(reffiles, outfolders): refs = {} for f in reffile: if type in f: for string in searchstrings: if string + "_" + type in f: error, refs[string] = read_reference_file(f) if not error: print refs phenological_classificaion(img, outfolder, name + "_" + method, refs, "ENVI", 17, 16, -500, 0, method, toprint=False) else: print "ERROR +++++++++++++++++++++++++++++++++++++++++++++++++++ ERROR"
imagelist = [] clip1imgs = ["/Users/phoetrymaster/Documents/School/Geography/Thesis/Data/MODIS_KANSAS_2007-2012/reprojected/clips/KansasNDVI_2012_clip1.tif"]#, "/Users/phoetrymaster/Documents/School/Geography/Thesis/Data/MODIS_KANSAS_2007-2012/reprojected/clips/KansasEVI_2012_clip1.tif"] imagelist.append(clip1imgs) searchstrings = ["soy", "corn", "wwheat", "sorghum", "wwheatsoydbl"] fitmethods = ["SLSQP"]#, "TNC"] fullpixels = get_px_coords_from_points(clip1imgs[0], "/Users/phoetrymaster/Documents/School/Geography/Thesis/Data/MODIS_KANSAS_2007-2012/reprojected/clips/clip1_fullcells_points.shp") for method in fitmethods: for images in imagelist: for img in images: name = os.path.splitext(os.path.basename(img))[0] if "NDVI" in name: type = "NDVI" else: type = "EVI" for reffile, outfolder in zip(reffiles, outfolders): refs = {} for f in reffile: if type in f: for string in searchstrings: if string + "_" + type in f: error, refs[string] = read_reference_file(f) if not error: print refs phenological_classificaion(img, outfolder, name + "_" + method, refs, "ENVI", 17, 16, 1000, 0, method, toprint=False, subset=fullpixels) else: print "ERROR +++++++++++++++++++++++++++++++++++++++++++++++++++ ERROR"