def check(tilt, img0, img180):
"""check tilt using a pair of images
"""
from imars3d import io
apply(tilt, img0, io.ImageFile("tilted-0.npy"))
apply(tilt, img180, io.ImageFile("tilted-180.npy"))
return
def getEdge(imgpath, edgepath, **kwds):
img = io.ImageFile(imgpath).data
edge = feature.canny(img, **kwds)
edge = np.array(edge, dtype="float32")
edgeimg = io.ImageFile(path=edgepath)
edgeimg.data = edge
edgeimg.save()
return edge
def _test_ext(ext):
data = np.arange(300 * 400, dtype="float32")
data.shape = 300, 400
imgfile = io.ImageFile("img1.%s" % ext)
imgfile.data = data
imgfile.save()
data2 = io.ImageFile("img1.%s" % ext).data
assert ((data == data2).all())
return
def main():
img0 = os.path.join(datadir, 'injectorG/normalized_000.000.tiff')
img180 = os.path.join(datadir, 'injectorG/normalized_180.000.tiff')
img0 = io.ImageFile(img0)
img180 = io.ImageFile(img180)
from imars3d.tilt.use_centers import computeTilt
computeTilt(img0,
img180,
workdir="_tmp.use_centers",
sigma=3,
maxshift=200)
return
def test():
from skimage import feature
from imars3d import io
dir = os.path.dirname(__file__)
datadir = os.path.join(dir, "..", "..", 'iMars3D_data_set')
imgpath = os.path.join(datadir, 'injectorG/normalized_000.000.tiff')
img = io.ImageFile(imgpath).data
edge = feature.canny(img, sigma=3)
edge = np.array(edge, dtype="float32")
edgeimg = io.ImageFile(path="edge_sigma3.tiff")
edgeimg.data = edge
edgeimg.save()
return
def test(interactive=False):
# test data
dir = os.path.dirname(__file__)
path = os.path.join(dir, "..", "..", "iMars3D_data_set",
"20120618_TURBINECT_0180_46_750_0055.fits")
img = io.ImageFile(path).getData()
assert img.dtype == np.dtype('uint16')
# force a pixel to be an outlier
img[0, 0] = (1 << 16) - 1
# filter
orig_max = np.max(img)
img = filters.gamma_filtering.filter_one(img)
new_max = np.max(img)
assert new_max < orig_max
if interactive:
# display
import pylab
pylab.imshow(img)
pylab.colorbar()
pylab.show()
def test_computeTilt():
img0 = io.ImageFile(os.path.join(datadir, "smoothed_000.000.tiff")).data
img180 = io.ImageFile(os.path.join(datadir, "smoothed_180.200.tiff")).data
t = direct.computeTilt(img0, img180)
assert t > -2 and t < -1
return
def test_shift():
img0 = io.ImageFile(os.path.join(datadir, "cropped_000.000.tiff")).data
img180 = io.ImageFile(os.path.join(datadir, "cropped_180.000.tiff")).data
flipped_180 = np.fliplr(img180)
assert np.isclose(direct.findShift(img0, flipped_180), -78)
return
def test_computeTilt():
img0 = io.ImageFile(os.path.join(datadir, "cropped_000.000.tiff")).data
img180 = io.ImageFile(os.path.join(datadir, "cropped_180.000.tiff")).data
assert np.isclose(direct.computeTilt(img0, img180), 0.4)
return
import os
import numpy as np
import matplotlib.pyplot as plt
from imars3d import config, io
from imars3d import detector_correction
file = './tests/iMars3D_data_set/Low_res_Gdmask_r0000.fits'
#print('Does file exist: %s' %os.path.isfile(file))
# retrieve image
image_data = io.ImageFile(file).getData()
#plt.figure(1)
#plt.title("Before")
#plt.imshow(image_data, cmap='gray')
#plt.colorbar()
#plt.show()
(detector_width, detector_height) = image_data.shape
chip_width = int(detector_width/2)
chip_height = int(detector_height/2)
# isolate chips data
chip1 = image_data[0:chip_height, 0:chip_width]
chip2 = image_data[0:chip_height, chip_width:detector_width]
chip3 = image_data[chip_height:detector_height, 0:chip_width]
chip4 = image_data[chip_height:detector_height, chip_width:detector_width]
# init final image
def test_filter_one():
newimg = io.ImageFile('ifced.tiff')
newimg.data = ifc.filter_one(img.data, sigma=3)
newimg.save()
return
#!/usr/bin/env python
import os, numpy as np
from imars3d.filters import ifc
from imars3d import io
dir = os.path.dirname(__file__)
datadir = os.path.join(dir, "..", "..", "..", 'iMars3D_data_set')
imgpath = os.path.join(datadir, 'injectorG/normalized_000.000.tiff')
img = io.ImageFile(imgpath)
def test_getBoundary():
ifc.getBoundary(img.data, sigma=3, debug=True)
return
def test_getBG():
print(ifc.getBG(img.data, sigma=3, debug=True))
return
def test_filter_one():
newimg = io.ImageFile('ifced.tiff')
newimg.data = ifc.filter_one(img.data, sigma=3)
newimg.save()
return
def main():
