def test_iden():
SEED = 314
random.seed(SEED)
X = range(10, 200, 20)
Y = range(10, 200, 20)
random.shuffle(X)
random.shuffle(Y)
img = tid.gen_fake_data(np.vstack([X, Y]), 5, 2.5, (210, 210))
bp_img = tid.band_pass(img, 2, 2.5)
res_lm = tid.find_local_max(bp_img, 3, .5)
locs, mass, r2 = tid.subpixel_centroid(bp_img, res_lm, 3)
assert np.all(np.abs(locs - res_lm) < .05)
def test_iden():
SEED = 314
random.seed(SEED)
X = range(10, 200, 20)
Y = range(10, 200, 20)
random.shuffle(X)
random.shuffle(Y)
img = tid.gen_fake_data(np.vstack([X, Y]), 5, 2.5, (210, 210))
bp_img = tid.band_pass(img, 2, 2.5)
res_lm = tid.find_local_max(bp_img, 3, .5)
locs, mass, r2 = tid.subpixel_centroid(bp_img, res_lm, 3)
assert np.all(np.abs(locs - res_lm) < .05)
from __future__ import division
import matplotlib
import trackpy.tracking as pt
import trackpy.identification as tid
import matplotlib.pyplot as plt
import random
import numpy as np
X = range(10, 200, 20)
Y = range(10, 200, 20)
random.shuffle(X)
random.shuffle(Y)
img = tid.gen_fake_data(np.vstack([X, Y]), 5, 2.5, (210, 210))
bp_img = tid.band_pass(img, 2, 2.5)
res_lm = tid.find_local_max(bp_img, 3, .5)
locs, mass, r2 = tid.subpixel_centroid(bp_img, res_lm, 3)
# make figure
fig = plt.figure()
ax = fig.gca()
# display image
ax.imshow(bp_img, cmap='gray', interpolation='nearest')
# add pixval like output
ax.format_coord = lambda x, y: 'r=%d,c=%d,v=%0.2f' % (
int(x + .5), int(y + .5), bp_img[int(x + .5), int(y + .5)]
from __future__ import division import matplotlib import trackpy.tracking as pt import trackpy.identification as tid import matplotlib.pyplot as plt import random import numpy as np X = range(10, 200, 20) Y = range(10, 200, 20) random.shuffle(X) random.shuffle(Y) img = tid.gen_fake_data(np.vstack([X, Y]), 5, 2.5, (210, 210)) bp_img = tid.band_pass(img, 2, 2.5) res_lm = tid.find_local_max(bp_img, 3, .5) locs, mass, r2 = tid.subpixel_centroid(bp_img, res_lm, 3) # make figure fig = plt.figure() ax = fig.gca() # display image ax.imshow(bp_img, cmap='gray', interpolation='nearest') # add pixval like output ax.format_coord = lambda x, y: 'r=%d,c=%d,v=%0.2f' % (int(x + .5),
