#!/usr/bin/env python # coding: utf-8 # # OpenPIV on the bridgepile_wake # # See the post on LinkedIn by Stefano Brizzolara # https://www.linkedin.com/posts/stefano-brizzolara-6a8501198_rheinfall-flowvisualization-ugcPost-6672832128742408192-lRub # In[1]: from openpiv import tools, pyprocess, validation, filters, scaling import numpy as np import matplotlib.pyplot as plt get_ipython().run_line_magic('matplotlib', 'inline') import imageio # In[2]: frame_a = tools.imread('../test8/frame0001.tif') frame_b = tools.imread('../test8/frame0002.tif') # In[3]: fig,ax = plt.subplots(1,2,figsize=(12,10)) ax[0].imshow(frame_a,cmap=plt.cm.gray) ax[1].imshow(frame_b,cmap=plt.cm.gray) # In[4]: winsize = 12 # pixels searchsize = 32 # pixels, search in image B overlap = 6 # pixels dt = 1./30 # sec, assume 30 fps frame_a[:600,:] = 0 # basically masking out the non-illuminated region frame_b[:600,:] = 0 u0, v0, sig2noise = pyprocess.extended_search_area_piv(frame_a.astype(np.int32), frame_b.astype(np.int32), window_size=winsize, overlap=overlap, dt=dt, search_area_size=searchsize, sig2noise_method='peak2peak' ) # In[5]: x, y = pyprocess.get_coordinates(frame_a.shape,searchsize, overlap) # In[6]: u1, v1, mask = validation.sig2noise_val( u0, v0, sig2noise, threshold = 1.15) # In[7]: u2, v2 = filters.replace_outliers( u1, v1, method='localmean', max_iter=10, kernel_size=2) # In[8]: x, y, u3, v3 = scaling.uniform(x, y, u2, v2, scaling_factor = 1. ) # In[9]: tools.save(x, y, u3, v3, sig2noise, mask, 'exp1_001.txt' ) # In[10]: # tools.display_vector_field('exp1_001.txt', scaling_factor=100., width=0.0025) # In[11]: # If you need a larger view: fig, ax = plt.subplots(figsize=(12,12)) tools.display_vector_field('exp1_001.txt', ax=ax, scaling_factor=1.0, scale=1000, width=0.0045, on_img=True, image_name='~/Downloads/bridgepile_wake/frame0001.tif'); # In[ ]: # In[ ]: