def test_load(self):
t1 = KerrArray([1, 2, 3], metadata={'a': 5})
self.assertTrue(np.array_equal(t1, np.array([1, 2, 3])),
'Initialising from list failed')
self.assertTrue(t1.metadata['a'] == 5,
'Initialising metadata from data failed')
t1 = KerrArray([1, 2, 3])
self.assertTrue(np.array_equal(t1, np.array([1, 2, 3])))
def correct_drift(im, ref, threshold=0.005, upsample_factor=50):
"""Align images to correct for image drift.
Detects common features on the images and tracks them moving.
Adds 'drift_shift' to the metadata as the (x,y) vector that translated the
image back to it's origin.
Parameters
----------
ref: KerrArray or ndarray
reference image with zero drift
threshold: float
threshold for detecting imperfections in images
(see skimage.feature.corner_fast for details)
upsample_factor:
the resolution for the shift 1/upsample_factor pixels registered.
see skimage.feature.register_translation for more details
Returns
-------
shift: array
shift vector relative to ref (x drift, y drift)
transim: KerrArray
copy of im translated to account for drift"""
refed=KerrArray(ref,get_metadata=False)
refed=refed.filter_image(sigma=1)
refed=refed.corner_fast(threshold=threshold)
imed=im.clone
imed=imed.filter_image(sigma=1)
imed=imed.corner_fast(threshold=threshold)
shift,err,phase=feature.register_translation(refed,imed,upsample_factor=upsample_factor)
im=im.translate(translation=(-shift[1],-shift[0])) #x,y
im.metadata['correct_drift']=(-shift[1],-shift[0])
return im
# -*- coding: utf-8 -*-
"""
Created on Mon Jun 20 19:21:48 2016
@author: phyrct
"""
from kermit import KerrArray
import numpy as np
a=KerrArray('coretestdata/im2_noannotations.png')
a1=KerrArray('coretestdata/im1_annotated.png')
b=a.translate((2.5,3))
c=b.correct_drift(ref=a)
print a.metadata
print a1.metadata
print all([k in a.metadata.keys() for k in a1.metadata.keys()])
# -*- coding: utf-8 -*-
"""
Created on Mon Jun 20 19:21:48 2016
@author: phyrct
"""
from kermit import KerrArray
import numpy as np
a = KerrArray([[.1, .2, .3], [.2, .3, .4], [.3, .4, .5]], dtype=np.float64)
b = a.level_image()
c = a.level_image(poly_vert=0)
assert np.allclose(
b, np.array([[.3, .3, .3], [.3, .3, .3], [.3, .3, .3]], dtype=np.float64))
c = a.level_image(poly_vert=0)
assert np.allclose(
c, np.array([[.2, .2, .2], [.3, .3, .3], [.4, .4, .4]], dtype=np.float64))
d = b.level_image(poly=-np.array(b.metadata['poly_sub']))
assert np.allclose(d, a) #should get it back to original
def _load_KerrArray(f,img_num=0, **kwargs):
return KerrArray(f, **kwargs)
@author: phyrct
"""
from kermit import KerrArray,KerrList
import numpy as np
import matplotlib.pyplot as plt
a=KerrList('coretestdata/*.png')
#check loaded ok
print a[1].metadata
assert all([k in ['floatdata','filename'] for k in a[1].metadata.keys()])
#check set item
a[0]=KerrArray([1,2,3],dtype=np.float64,metadata={'abc':3})
assert 'abc' in a[0].metadata.keys()
print a[0].metadata
a.files
#check reload doesn't destroy setitems
a.reload()
print a[0].metadata
assert 'abc' in a[0].metadata.keys()
#check loading from arrays
print 'load array test'
b=KerrList([KerrArray('coretestdata\\im1_annotated.png'),
KerrArray('coretestdata\\im2_noannotations.png')])
print b[1].metadata
def setUp(self):
self.td1 = KerrArray(td1)
self.td2 = KerrArray(td2)
self.anim = KerrArray('coretestdata/im1_annotated.png')
self.unanim = KerrArray('coretestdata/im2_noannotations.png')
self.testdata = (self.td1, self.td2, self.anim, self.unanim)
Created on Wed Jun 29 11:45:26 2016
@author: phyrct
"""
import os
import numpy as np
from kermit import KerrArray, KerrList
from skimage.viewer import CollectionViewer, ImageViewer
import matplotlib.pyplot as plt
folder = r'..\tests\coretestdata\hysteresis_test'
editfolder = r'..\tests\coretestdata\hysteresis_test\edited_ims'
os.chdir(folder)
background = KerrArray('image0000_background.png')
background = background.convert_float()
print 'loading images...'
kl = KerrList('image000*unproccessed.png',
conserve_memory=False,
get_metadata=False)
list(kl) #make sure all images loaded
print 'images loaded'
#%%
print 'convert float'
kl.apply_all('convert_float') #convert pixels to decimal values
print 'correct_drift'
kl.apply_all('correct_drift', ref=background, upsample_factor=200)
print 'subtract'