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# test find_subpixel_position
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from pylab import *
%matplotlib inline
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from openpiv.pyprocess import find_first_peak, find_second_peak, find_subpixel_peak_position
from openpiv.pyprocess import extended_search_area_piv, correlate_windows
from scipy.ndimage import shift
from scipy.ndimage.filters import gaussian_filter
/tmp/ipykernel_1212603/1798919731.py:4: DeprecationWarning: Please use `gaussian_filter` from the `scipy.ndimage` namespace, the `scipy.ndimage.filters` namespace is deprecated. from scipy.ndimage.filters import gaussian_filter
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from test_process import create_pair
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a = np.random.randn(32,32)
a = gaussian_filter(a,.5)
u0 = 2.8 # to the right
v0 = -5.3 # downwards
b = shift(a,(-v0, u0),mode='wrap')
plt.imshow(b)
Out[5]:
<matplotlib.image.AxesImage at 0x7ffb985d2a00>
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u,v = extended_search_area_piv(a,b,window_size=32)
--------------------------------------------------------------------------- ValueError Traceback (most recent call last) /home/user/Documents/repos/openpiv-python/openpiv/test/test_find_peaks.ipynb Cell 6 in <cell line: 1>() ----> <a href='vscode-notebook-cell:/home/user/Documents/repos/openpiv-python/openpiv/test/test_find_peaks.ipynb#W5sZmlsZQ%3D%3D?line=0'>1</a> u,v = extended_search_area_piv(a,b,window_size=32) ValueError: too many values to unpack (expected 2)
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print(u-u0,v-v0)
[[-0.00271353]] [[0.01545332]]
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corr = correlate_windows(a,b)# + correlate_windows(c,d)
from scipy.ndimage.filters import gaussian_filter
corr = gaussian_filter(corr,1.5)
x,y = np.meshgrid(np.arange(corr.shape[0]),np.arange(corr.shape[1]))
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x1, y1, p1 = find_first_peak(corr)
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x2, y2, p2 = find_second_peak(corr)
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(i,j) = find_subpixel_peak_position(corr)
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from mpl_toolkits.mplot3d import Axes3D
fig = plt.figure(figsize=(10,10))
ax = fig.add_subplot(111, projection='3d')
ax.plot_surface(x,y,corr);
ax.scatter(j,i,p1,'o',color='r')
Out[ ]:
<mpl_toolkits.mplot3d.art3d.Path3DCollection at 0x7f87925f5210>
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x1,y1,p1,x2,y2,p2,i,j
Out[ ]:
(26, 28, 60.07128420968547, 23, 28, 20.830743171795604, 25.74341384564399, 28.189462289160172)
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32-i
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6.256586154356011
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32-j
Out[ ]:
3.810537710839828
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