############################################## data0 = loadtxt(file0) data1 = loadtxt(file1) data0 = data0 - data0.min() data1 = data1 - data1.min() print data0.shape print data1.shape #data0 = data0[:,100:320]; data0 = data0[:, 200:400] ############################################# ## process of the images ############################################# img0 = ImgArray() img0.set('img_array', data0) img1 = ImgArray() img1.set('img_array', data1) nslope = 2 img0.remove_spikes(nslope=nslope) img1.remove_spikes(nslope=nslope) new_mimg, paras = img0.find_match(img1, paras0=None) ############################################# ## plot the images ####################################### data0 = img0.get('img_array') data1 = img1.get('img_array')
############################################## data0 = loadtxt(file0); data1 = loadtxt(file1); data0 = data0-data0.min(); data1 = data1-data1.min(); print data0.shape print data1.shape #data0 = data0[:,100:320]; data0 = data0[:,200:400]; ############################################# ## process of the images ############################################# img0= ImgArray(); img0.set('img_array',data0); img1= ImgArray(); img1.set('img_array',data1); nslope = 2; img0.remove_spikes(nslope=nslope); img1.remove_spikes(nslope=nslope); new_mimg,paras = img0.find_match(img1,paras0=None); ############################################# ## plot the images ####################################### data0 = img0.get('img_array'); data1 = img1.get('img_array'); subplot(2,3,1);
from pylab import *; from pydao.io import Lox_Stack,ImgArray; from pydao.ohdf import OGroup; import os; dirname = r"D:\2014_12_CLSPEEM\141213"; filename = "141213016.tif"; tif_filename = os.path.join(dirname,filename); img = ImgArray(tif_filename); img.read(); #img.savebmp(); figure(); img_array = img.get('img_array'); imshow(img_array); colorbar(); show();
from pylab import *; from pydao.io import Lox_Stack,ImgArray; from pydao.ohdf import OGroup; import os; dirname = r"D:\2014_12_CLSPEEM\141212"; files = os.listdir(dirname); for file in files: if file.endswith('.tif'): tif_filename = os.path.join(dirname,file); img = ImgArray(tif_filename); img.read(dtype=0); img.savebmp(renormalize='minmax');
from pylab import *; from pydao.io import Lox_Stack,ImgArray; from pydao.ohdf import OGroup; import os; dirname = r"E:\2014_08_CLS\140801\140801020"; filename_pre = "140801020#1.tif"; filename = "140801020#107.tif"; tif_filename_pre = os.path.join(dirname,filename_pre); img_pre = ImgArray(tif_filename_pre); tif_filename = os.path.join(dirname,filename); img = ImgArray(tif_filename); img_array_pre = img_pre.get('img_array'); img_array = img.get('img_array'); subplot(2,2,1); imshow(img_array_pre); colorbar(); subplot(2,2,2); imshow(img_array); colorbar(); subplot(2,2,3); imshow(img_array/img_array_pre); colorbar(); show();
from pylab import * from pydao.io import Lox_Stack, ImgArray from pydao.ohdf import OGroup import os dirname = r"D:\2014_12_CLSPEEM\141213" filename = "141213016.tif" tif_filename = os.path.join(dirname, filename) img = ImgArray(tif_filename) img.read() #img.savebmp(); figure() img_array = img.get('img_array') imshow(img_array) colorbar() show()