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"
