{ "cells": [ { "cell_type": "code", "execution_count": 1, "metadata": { "scrolled": true }, "outputs": [], "source": [ "#Run the new window deformation" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "from openpiv import windef\n", "from openpiv import tools, process, scaling, validation, filters, preprocess\n", "import numpy as np\n", "import os\n", "from time import time\n", "import warnings\n", "\n", "\n", "import matplotlib.pyplot as plt\n", "%matplotlib inline " ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], "source": [ "settings = windef.Settings()\n", "\n", "\n", "'Data related settings'\n", "# Folder with the images to process\n", "settings.filepath_images = '../test1/'\n", "# Folder for the outputs\n", "settings.save_path = '../test1/'\n", "# Root name of the output Folder for Result Files\n", "settings.save_folder_suffix = 'Test_1'\n", "# Format and Image Sequence\n", "settings.frame_pattern_a = 'exp1_001_a.bmp'\n", "settings.frame_pattern_b = 'exp1_001_b.bmp'\n", "\n", "'Region of interest'\n", "# (50,300,50,300) #Region of interest: (xmin,xmax,ymin,ymax) or 'full' for full image\n", "settings.ROI = 'full'\n", "\n", "'Image preprocessing'\n", "# 'None' for no masking, 'edges' for edges masking, 'intensity' for intensity masking\n", "# WARNING: This part is under development so better not to use MASKS\n", "settings.dynamic_masking_method = 'None'\n", "settings.dynamic_masking_threshold = 0.005\n", "settings.dynamic_masking_filter_size = 7\n", "\n", "'Processing Parameters'\n", "settings.correlation_method='circular' # 'circular' or 'linear'\n", "settings.iterations = 2 # select the number of PIV passes\n", "# add the interroagtion window size for each pass. \n", "# For the moment, it should be a power of 2 \n", "settings.windowsizes = (64, 32, 16) # if longer than n iteration the rest is ignored\n", "# The overlap of the interroagtion window for each pass.\n", "settings.overlap = (32, 16, 8) # This is 50% overlap\n", "# Has to be a value with base two. In general window size/2 is a good choice.\n", "# methode used for subpixel interpolation: 'gaussian','centroid','parabolic'\n", "settings.subpixel_method = 'gaussian'\n", "# order of the image interpolation for the window deformation\n", "settings.interpolation_order = 3\n", "settings.scaling_factor = 1 # scaling factor pixel/meter\n", "settings.dt = 1 # time between to frames (in seconds)\n", "'Signal to noise ratio options (only for the last pass)'\n", "# It is possible to decide if the S/N should be computed (for the last pass) or not\n", "settings.extract_sig2noise = True # 'True' or 'False' (only for the last pass)\n", "# method used to calculate the signal to noise ratio 'peak2peak' or 'peak2mean'\n", "settings.sig2noise_method = 'peak2peak'\n", "# select the width of the masked to masked out pixels next to the main peak\n", "settings.sig2noise_mask = 2\n", "# If extract_sig2noise==False the values in the signal to noise ratio\n", "# output column are set to NaN\n", "'vector validation options'\n", "# choose if you want to do validation of the first pass: True or False\n", "settings.validation_first_pass = True\n", "# only effecting the first pass of the interrogation the following passes\n", "# in the multipass will be validated\n", "'Validation Parameters'\n", "# The validation is done at each iteration based on three filters.\n", "# The first filter is based on the min/max ranges. Observe that these values are defined in\n", "# terms of minimum and maximum displacement in pixel/frames.\n", "settings.MinMax_U_disp = (-30, 30)\n", "settings.MinMax_V_disp = (-30, 30)\n", "# The second filter is based on the global STD threshold\n", "settings.std_threshold = 7 # threshold of the std validation\n", "# The third filter is the median test (not normalized at the moment)\n", "settings.median_threshold = 3 # threshold of the median validation\n", "# On the last iteration, an additional validation can be done based on the S/N.\n", "settings.median_size=1 #defines the size of the local median\n", "'Validation based on the signal to noise ratio'\n", "# Note: only available when extract_sig2noise==True and only for the last\n", "# pass of the interrogation\n", "# Enable the signal to noise ratio validation. Options: True or False\n", "settings.do_sig2noise_validation = False # This is time consuming\n", "# minmum signal to noise ratio that is need for a valid vector\n", "settings.sig2noise_threshold = 1.2\n", "'Outlier replacement or Smoothing options'\n", "# Replacment options for vectors which are masked as invalid by the validation\n", "settings.replace_vectors = True # Enable the replacment. Chosse: True or False\n", "settings.smoothn=True #Enables smoothing of the displacemenet field\n", "settings.smoothn_p=0.5 # This is a smoothing parameter\n", "# select a method to replace the outliers: 'localmean', 'disk', 'distance'\n", "settings.filter_method = 'localmean'\n", "# maximum iterations performed to replace the outliers\n", "settings.max_filter_iteration = 4\n", "settings.filter_kernel_size = 2 # kernel size for the localmean method\n", "'Output options'\n", "# Select if you want to save the plotted vectorfield: True or False\n", "settings.save_plot = False\n", "# Choose wether you want to see the vectorfield or not :True or False\n", "settings.show_plot = True\n", "settings.scale_plot = 200 # select a value to scale the quiver plot of the vectorfield\n", "# run the script with the given settings" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "['RectBivariateSpline',\n", " 'Settings',\n", " '__builtins__',\n", " '__cached__',\n", " '__doc__',\n", " '__file__',\n", " '__loader__',\n", " '__name__',\n", " '__package__',\n", " '__spec__',\n", " 'correlation_func',\n", " 'display_vector_field',\n", " 'fftshift',\n", " 'filters',\n", " 'find_subpixel_peak_position',\n", " 'first_pass',\n", " 'frame_interpolation',\n", " 'get_coordinates',\n", " 'irfft2',\n", " 'multipass_img_deform',\n", " 'np',\n", " 'os',\n", " 'piv',\n", " 'plt',\n", " 'preprocess',\n", " 'process',\n", " 'pyprocess',\n", " 'rfft2',\n", " 'save',\n", " 'scaling',\n", " 'scn',\n", " 'sig2noise_ratio_function',\n", " 'smoothn',\n", " 'tools',\n", " 'validation']" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "dir(windef)" ] }, { "cell_type": "code", "execution_count": 5, "metadata": { "scrolled": false }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "C:\\Users\\Theo\\Anaconda3\\lib\\site-packages\\skimage\\util\\dtype.py:135: UserWarning: Possible precision loss when converting from float64 to uint8\n", " .format(dtypeobj_in, dtypeobj_out))\n" ] }, { "data": { "image/png": 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t3ZI2SPqgMeYBSd+W9B1r7TpJXZKeTMo/KanLWnuTpO8k5YKBMtWXljoc3tF9d2Ul36dS901DA88Gpu3s7WX7WSX7E4ThjY7y8i5nz4p1fkcHX9bR6lq0j8Qf0dmzbCVtLR+f587xMxPazspKJldQ4FCsjIYFr12L+35lVymSmz6d9yeVk3h/UjksnJPjqNQfUhr+5MQyHpKRn/xYSe+V9OPk99+X9NHkz48nf1fy7+8zJv00KNYGoFhzoViiKCpCxa2cEOBwdc0aB2NB4cLnSCfcAExQFN3d/iNGYjH/4zhIRGEApSHaGY8HGB49PemNDARAt2yMyTXGlEhqlbRL0kVJ3dba8ZOeeknjEcvLJV2WpOTfeyS9IajVGPOUMea4MeZ4G879/68YHg5EYONiVHy/hYWF/g3/woUO9RUYCgsDZJsvXOifyDdIkDpDCOrVjg7/cedOqSu0L10SuKDO4WH/JamDRPW0tgaIM/cLZPittXFr7QZJKyTdJ2n91cSS/16ty99gSa21z1hrN1lrNy2cYCxrkDj+dCcGFRXBUBkH5ObiQ9MQnC3FxexsN511+12YrahRqauTVq6ceJuuhrY2/+eBQYxfAKUhFtJBGLiCGCa/cNrkWGu7Je2V9ICkOcaY8VdlhaTxUJB6SSslKfn32ZKCFGBpbg6QuRsi68YFIVw9Dli9mnMcUKxaBUPhQrCPQThQxGKEGEoh6v8EIRwPYPgDpAYEoXNUWxtPMJqstXqMMQuNMXOSPxdLer+kc5L2SPpEUuwJSS8kf96c/F3Jv7+SPH32jiATa4jR5YLCQv8rfgfccIN/wx9Cp28EYArEcHk7XGrLpNXdMZVX/LEYC2ZIo3eBrPiXStpjjCmVdEzSLmvtVklfkfRlY0yVIh/+PyTl/0HS/OT3X5b0Vf/NjlBRwRbHg4MOrmO0NE2isZGVNxgdjbJ5CGIx7o+Px/nuAPJUTpvG+2pggEX25OcjEqzoRaBpsfE4K+8wOIj66Px55uI6f57nmG3Zwt7tEycYs5QUBYGQoK+REd6VTjY6xGwCDSBdk42MRMleBJWVrITz0JBDmWtadiTIdoOBRPWUWmvvsdbeZa29w1r7J8nvq62191lrb7LW/jdr7Ujy++Hk7zcl/+479uM/MWMGW6Xl5uIqBNHBDD3m7+lhUT35+TxMcWgIh16qvZ2Hg0GaxtFRzu+yfDnL9SouhkcMxnCWkR07mMG4eBEx8OTmMr6W5culRx8F7ZP0pS8xO7lwofT+9zOdy5Yx45eTwyNZjxyBQV99fTwl9vRpVml1YCBKMQY4epRlTRcU8MCDvDzmjmtrc4hi276dzRJ79vDZ2TcmEvzv+zPRBK6xMZ4/1d4O83j6+1ECk7U2ovWLx5HoYAdr6NCQtfEuRv04eLkd0cENDVkbb2DcfoODjDluaCjqz+Hh1LIDA0zODg3xrLCqKiQ2WN+BEqNiMZ43NzjIk62ozoEBpjMe5zopM2d5ucO9P7udCT77LKcwff55JFZebm1igL1HHR3s0qOjzIYkEg5MiTU1rEMvX+bj/U2gqUi9mJfHGQ1PnoQBI9OnS9u2MaXHj+MolC0vs3i5116TWofZGcPmg/NRKEpJiVQfY6fgmzezqJEzZyK/PdnwbNkC0x0OHeJ+T0ho/eJr89DOOzdX2rqVXZrS/0lc59atbHeQk8N17t/P5G67jb9HW2KgroUkfexj0a6MAJ5p3XabZLayhr78Mrt0fj67d2M4naNWr2YPacUKXq/CMzLa8LtgdDRAPaQAMeIzZvgPp1yxIuKG8Il16yJ/t1csWMCd3RBBEnTEqRd9B22EYJxLY47bpID3M9YQD94zpszjDlFvPYThnzmTV2ygWLLEP03inDkBQu7nz+cnyw79nq53MATJh0sUCjVoQc4YM4YqLAB6e3n40WQN57xeMJUNv0vRy2nT0FmoJH7rxsBABxfDD61aOvPxmpr855mECGFubQ1QJDJEinGAhzk2FsATECRG1C+mjOG3NsB2NkNcPS648caIEsAnli2DO46iogB1IBhC1MBpbmYlf10wpQ1/AH/twID/MhBOtF5Z6sUMRABf3vTpfMWdl+cQWwwRovhaJiRwDQx45wZXV5f/xChK5yrxoemSaIoRqqiQ5+JcATjhsyv+0Egk0kbRGiHAit+Fdnb+fF4ll8LF1VNYyNxSy5Zhbpe0gRp+mAcnKcrZI/l1ra38OdJnI/HFZDzO6xThBapLmi1VGoAj0mXFj5Fu3m6AjDb8/f08ZO2112CSSns7z2CqrJSqqpDotm2cNu7oUXb5vj7e1EOHmPt8ZETauZPpHB2NclBSoa8PRq0lEvziBw4gC1xWxgKFSkrY5DQwwHOYhoZYGOvgIC8XcewY2+VVV+OhqYsX2QTV3+9QRqqri7nthoelCxeYzrNncXnxbdtYP506xSLe+vpwBHF0PyTyobWVk1p4BpznJydmzZL+8A+Z7Gc/Cw/aFiyQfvEXmdKHH8Y8eL/xG2xzMG+e9JGPsMs/8ACvBPHLv8x23oWF0re+xXR+7GMsOXPOHOm3fxsozMmRfuVX2MV/5meQU/7OO5m7df16dvg/Z470ta+B9kn6vd9j50o33MDPAr7xDbboXbpUeve7mU5j2ARVW+uw46iqYiudwkLuvlm1Cp+Wf/3r7Hnefz9zx82YIW3ahC4d2RCy4i8q8k/YAJHRK36JH0Tm5PDs6IPxB5Bcad696h1hRCzUPVBWFnGlElRWMnre8vLo0JZMPAcORIYoFc6ciYwAqhT56qtaf7VC3q/HyZMR5zABtJQrVrC+X7OG13ehNq2oKOrPVDAmWskTnQsXMp0uHpEvf5npXL8+GkcIX/86WyIbwy3qTTfpQOdtSJSWu7rhBlZHyhjp40sOMqWf+xzbis+apQOrf5np9IyMN/zUd9zdDWvCO+js6WE12lx0xuO8rhDVWVjIJ0iqMzeX7zaw0sFBtoWQcGJCUxM/hqHNbGzkOulO3kWnSzsJ8vJYd+bk8JJTmjWLN4DWppL/e3eRNU0OLwd88I2t6XG6ZLzhp8jLi0L2fCI/33/0YQj2wZUrHYw0hFM2MLVoAYhY0plEGSJEtL/ffxRKe7v/Gv9ORf4dHlC6eZIQQqWLe8Tkbh0AHQghDL9LFUAKlxwmihAl/mfNclj9UVxnhj9E5m5Li/+ksPr6aCL3CheWpIyw5g7o708fuQNExht+inQbfmp8XAi48vP9x/GHoF7ECES9mC7DH4ItK0Q2cH19VG6aANvoEA1VmNpHWCe9eQcyp3SNzYw3/LTjXAw/fb4hDK8LcEaseD9hmkQX0Ewzl3oV8CHR+w6x6AzhQmlp8Z9lG4RttL3de1ZYCA/KyAisHOuCdLP4AWS84adI94o/BJYv919184YbAhj+hQtZmEVOjncLTNWFqNlCk1cTCd7OdLL6OVVMCFAjJYSRHh520ElXEQ6GP11erow3/Hv3skzX7m62OraWG77BQR6BU13NvBjWRqF9BLm5PJmouppNEsPDUZ8SHD4M3ULWRqGa5OI0qsfFWgL09zOjNjzMbkWSDh5k811NTRTGS7B7N4skq6hgmyxreaZ4UxNjKftPxQSjo3hF1tTE8wiqqtjmsaEBjuF4nB9qdXUhHz9lDw2BjDf8H/gAW1jQlYox/HA1HufhnNOns2gMY6Sbb2Y658/nO8q77mKyixZJjzzCdD7yCKy8u2YNMwQ5ObxQEGQOOX2ahbKePcsmxqIinLOnJ59k6QY33ig99RTT+fTTzC3T2xvxgaSCMZyE5ZVX+HjX1q2cE/n4caRyaIiXlpg5k5fgQDkPOTk8dffkSbTKjMelXbuYSu+YCG2X789EqRet5fRybW3W9vUxWcjqZ9varO3qYrJ1dUyuvT1iICRobGR0km1tkPrQWtvEGBptaytifYxAG9rSEtFZEhw/jsQqD7bZRCw1PeboaETtR9DQwKkX6fhsauI6yTMaG4vaSVBTw9p56pS1ly4xnba0FI+lxjPtSC6RsLa6mumk71s8zu+p6Swcm/X1+N5PnmRybwaFol40xqw0xuwxxpwzxpQbY76Y/P6bxpgGY0xJ8vOhK/7P14wxVcaYSmPMBwLOW3r1VSZXVsZXK3RiP3eOJ4VBPmlVV/OEkldfZXHitbX8LIDWPjp71oEsiza0pIT7UeHO4ObWAzKJ1Km7+fnc3XLgAG8mHZ/793Od5Bnl5bFsXCnaGRCdGzZw16LuvBOPpVfPsphXY3gdK/q+5eTwe9p/BlbcXL4c37t3FjsI4uqJSfpda+16SQ9IetoYM543/R1r7YbkZ7skJf/2KUm3S/qgpP9rjPGcxuIOl6qXIUIvKRYtckpkRAhBvThnDnfHYxQX85mUIs0x4r4vH4ImMURSWE+P/8CWDGA0lOQWIjppwzmttU3W2pPJn/sknZP0VlG/j0v6d2vtiLW2RlKVJFiAJRxyc7nhpy9rCDu1aBE/MKZYuND/ZDJnDq99hFFczLdl9CEFKJ1NEcJQhShzHyKB6/LlKGPcJ/r6/Fd6HhnhzHz0WQYJEfUMp7WDMWa1pHskjW+OvmCMKTXGfM8YM74PWi7pygIB9brKRGGMecoYc9wYc7yNVlS6Bris+ClCGP7iYrddBD0z9b3ynDs3gOGfNs1/hzrAt5F2SeCk1w7BllVf799Ih5hMXIitKPr6/O9MMiCMnxt+Y8wMSc9K+h1rba+k70paK2mDpCZJ/2tc9Cr//Q1mx1r7jLV2k7V200LvhULeiJwcXiGToqgorXYKh8eHwIwZAUo2hHL1QKvqe3J0KVdDrx2CerGjwz9ToAvfOEXW8PsDMvzGmHxFRv9frLU/kSRrbYu1Nm6tTUj6e/3UnVMv6cr1wwpJaedfCrXi9+3jd8HKlf5997Suj9MuggpOm+YQLzj5EYKIycVIu4DMjbEYD6cMgRCG38VIu0x6k7xUD4rqMZL+QdI5a+3/vuL7KyOUPyZpPCZis6RPGWMKjTFrJK2TBM/i3RCPc8q6EIY/5IqfDDKXzF1r2Y5n/nwWVeSS+IOR5hU/VUczwE+fZu6woSHIUKYoAoUcql+65D9TvanJP3n84CDnDggxkYYw0iEmE98gK/6HJP2KpPe+LnTzL40xZ4wxpZIelvQlSbLWlkv6D0lnJe2Q9LS11rOTJdn4nCiskKC6OiIuIdi/nz2QlhZ+/ZoaRvggSZs3M7meHkZ9KEVhhcQ1093NModHRqSXX2bXVmkpYzlpamKdZC3nnGxqQsk0tbUsY9sYaft2duklS1iyV3Gx9Ku/ynT+3M+xw93GRn4IvHUrG+80PDSR4Nnfe/dyl+Hhw4x5MRbjz+jYMbbQGRri4/3kSRagMTIivfQS0+kdEwn+9/25lgQumkB18aK1ly8z2R/+kMmNjFi7bRuTPXeOJ2adP8/krOXJZvTex8ai5CyfOu2ZMyw7aWTE2ldeYTq/9z0m94MfWNvRkVKsr8/aF15gKuvrmRxNyAqB4eEoOYngxAkmt3kzf99+8hMmV1dnbXc3k6XJW9byZLxz51huobVRAhvB4cNRQqBPnW8GhUrgmuw4CNnQGhtheQFJ/23aNiRXcPKIHruf+ZpuvbgNUYseORJFzBBs2yatXct00uqLL70EK0ru368Vs2Elzdpa5m45eDAiQSWgAQELF6Ig9RkzpJ/PYc+9rIy5UYyJnhHBtm182090FhZKL77I9N17L9P54Q/z9+2jH2U6V67kO4k1a3h/Usa5W2+VduxgsjSx8oEHeCmGNHGtZ77hp0Wbenv5wZQZhErjcZlh6JOGDc3P52GS9N4LC3mWLSbTTiS4P54qHR3l5U7ptcfG8GEEfe4DA9xI01sfGGBzo7WcL4FeO5FgZ+rGcJ3xOA98cNHpe8i5yKZbp09kvOGncCopS1FY6L0ucwguknnz+CE4RoiTbReCA2p5A8TxGpO+QzmXEFGKEIQxIcJOQ/AbuNBj0meeCRnGU8rw0ww9jIIC75yGs2f7j4+fOzdQeQXfsawhmG1yc68rwx8isqax0aHcMkRDA2f1oghx7yHi+Pv7uVs5Xchow+9at8T7LBzA8M+a5X/FP3Mmn0ywQXMpVEQ7PpTh9xx3ms7VnAuVLUVjY2ZMJgnseIQAACAASURBVCHYHF1qCtHn3td3HcTxT2akfWYN4OoJoDKMoQoRc19Q4N/wu7h6HDoqXSt+ymjo0r4Q3OBjY6xejUs7QxhUlwzjKZXANZnR0+M/ocMJAVb8Erc/IcpQYLis+Okbk5/vf9ZLo6unt5cdqlsrHTrErl1aypilLl0Kk2Xrm8O4q4tHsblcnyKEDcmu+APj5Eleq6azE1YDSCR4ymNuLj+W7+5GsiMjLElFilZVJCktFuPJY42NkO98YIBzVF66xIxvLMb5Kakxz8lhzzMex2VRa2qkixdTy9EIHGOiWvcEt9zCXBMXLnAXxs6drDvPn+dBAq+9xpPC6CRRUsLa2drKK9yWlLB7isejfqI6STXcsTGegOkbGW34163jYd9NTQ6rBfqE6+ujN4w2AIzavDxu+JcsYd6WvDweDTE6CkvKFhVx3/nAAAudoMTIEg/oPn8+YsxJBQfax3vvZbSGs2dHVIkEn/0sk/vMZ9g4fugh6X3vYzo//3n2eBIJTju5fj1r5/TpfNJbvpy1MyeHr7jXrYuoL1MhN1f63OeYzjvvlO64I7Vcfr70+ONMp3dMJOvL9+daMncrKphcWRnPnLX79zO5mhrM21ZxgvE+XroUUSUSlJcz+sOaGmv7+5nO4dJKJnjxorW9vUy2pITJVVSgLFtrrbX79jG5I0c45yakczx/ntNO0vFZUcEzfc+d8ys3fv1UiMe5znic6UwkeB/FYvz6paVMzuX6VM5F1kXn1aCpmrl7+jSTq6hw8HnSJXdNDU6JPV3FTqFra/n55pkz7J6qq/k5bOG5EiZ4/jzfo9MiSVVVnMGC7uU7OvhWj/hvFD125A4TH5+nT/MErtJSv9dOJJhsTg6/dk4O02kMb2duLpelNbRcrk/v3UWWXts3Mtrwj41xYx6PBzjsClDy0yVYhtozWmrZCXl5/ss/hjitDnBgPHMmN/y+EaI0cUuL/zDJEAec8ThPtgoBlwikdEV9UWS04Q9B7+aEABEjIaIkQ3ADKzfXv+EPEHMfIkQ0nYa/tla64Qa/Omtqojo4PhEiN6C7m0cATfbM2XQjow1/iAHrhAwx/MFW/L5X5wH6M8SKf9asAOxjECEWOw0NYZKtqE66Og6x25mqyGjD397un3haUlrrwIQy/N5X/KFcPSFW/NeRq2dkRKjKa1cXr+mTSPh3obS1sUQzF7gYfvoKe+bpkRSZBJeKAunAJG9eaqR1S5chK/6iogzx8Yda8U9yV08iwSfm/n42N1ZUSDfffG3tej1cfdy+jV8I2skQxRuDFIT0jIw2/CUlbDAmEo6HLXQ2CeCTdjH8iQSzkwUFAahsQ/n4fRt+lxU/fO4DA6w2eyIhbdnCLksTeQ4fZs3cuZPNd9bytJWzZ3lX1tSwR9nRwcdmVxeiVpC1fK6vr+e1sY4cYfdfVcWDzk6d8l+lhCCjDf+SJewlcKI4q65241OEoYo7drBBU1cXTWgEL73EBk1trVReznTqhRfYLEn7ydqI24/g4sVoqZoK8bj0yitMZ309S+CSIm49kGqbl8cJ6f/gD1LLGSN9+9ugfZL+4i/YmH/ySbbiN4Ynj/X3M+IfKTLmxH1UX8+r5p48Gbl3U8EYTpNoLZtMpChZlKzkFyzgZ49r1gSoGgxg7CSIO9q0aZM9fvy48/8bX3CSMM2amijbMuVLE49HU/tDD6XUGb94STm5RmZ16jCLEyekjRtTtzMWi0Lkb7sttSyN8IjFohUIKpN7+rR0992p5errI8tGTvAOH5YefDB1O8srlbtwnsyi1GnGsee3Ku+jH0597bq6yFrce29q2VOnpHvuSX3tWDThEpLwWIyNz/G68MSou+ikIcxENhaLDCUxVENDkVwqnWNj0SRKii02NUUZ6OSeaFloa6O2knScsTFupKnsyAhPXbkajDEnrLWbXP9fRq/48/KkZ59lsiUlcEuVm4s51vbUrFb3bBZbB3ODtG8fJ7B47TUmt2uXQ83x8+eZ3OnTvLrV5ctI7MXqWzQ0g9WWeG4MGH0pyqRZv57JwnuntW0k6Sc/4XLUw0jHPJWzlsnm5fH7KS5mOvPzOTH60qX8+pQi0hi+IX3+eSYnSc89x+ReeIHr9ImMNvw9PTxJJBMOXKQgQSjh4Hm3mJMTIPElEFmOb84ECpdoHQqX0EuKgQHO85wpmATOEW9IafiNMSuNMXuMMeeMMeXGmC8mv59njNlljLmQ/Hdu8ntjjPlrY0yVMabUGAP22BPD6dO8wJMT4BN2GQh0NZcxhj8ADVWIaM4QHRqCLIfiwgX/0TpnzzLXogsuX/afaDY0xNxrWaQGWfHHJP2utXa9pAckPW2MuU3SVyXtttauk7Q7+bskPSZpXfLzlKTvem91Ei7ZgZmSyZc1/F5VBsleC0GPSVFbK61alVrOhfe1o8N/Pgxtpws6O91q92fx5khp+K21Tdbak8mf+ySdk7Rc0uOSvp8U+76kjyZ/flzSPyeLxx2RNMcY4zl5+6fwbtAdsy98Xz8QtwsHNeYBZlIXw4/nnAAzaQhXD+1OmmxVV8dKR7vApVZOd7d/ghNX0pYs3hxOPn5jzGpJ90h6TdJia22TFE0OkhYlxZZLuvI0rz753et1PWWMOW6MOd5G2VTeoIPJOS1MHdiXQ/j8XKgX076L8dwBxmSGqydE5q7vsVReHsZ9Q8tFGON/fLoY/rS/G5Mc2PAbY2ZIelbS71hr32qje7Uuf8OwttY+Y63dZK3dtJCyhFyB5maeP9Td7XAg1tvrEALjH1Pd1eN9Mg3g6qF5ZsPDLFCotZWlGgwN8WiVXbuY3OXLmH9G+/fzV6OqitNT0sfT0cENPx1HY2PcjnR1sQl/YIAxcI3rTIfbEBl+Y0y+IqP/L9ba8YCqlnEXTvLf8Vutl3TlumCFJBYf6YCSEmnRotRyUpQ8hd/90tLoaQDU10cfgpdfZqvZy5dZspW10X0RXLoUfVJieJgnr7W3M95La3H2WEsL68/RUU6ZoKEh/hZeuIBIcjs6pFdfTa2usJDV1Zk7V7rrrtRyxcXSo4+mlpOkxx5jsfFFRdIDDzCdsRjMBVH0jMiq++JFbniPHePPffNm9r51dvKa+F1dTGdeHjYh6u31nwCPkIqpRdEK/p8l/dXrvv+fkr6a/Pmrkv4y+fPPSXox+f8ekHQ01TUmwsDV18cZiy5csHZ4GCo+fBizam3ZYm1zM1O7YweT6+nBRFD2lVeY3MsvW9vVBQQTCWv/5m+Y0h/+MGLhIvjLv0Ri27ZFzyoVEglrv/IVdml7/Li1P/oRk/3Hf8TUWpQJanSUydGx7BuJBL82ZR2z1trBQSY3MmLtwACTravj1z9/nsvSd5iy2FnL78lF59WggAxcD0n6FUnvNcaUJD8fkvQXkh4xxlyQ9Ejyd0naLqlaUpWkv5f0W9c8O10FM2ZEKwqSxHTTTdGiE7lQ7r9fR1tYHNqqVTyPgG5R6+o4rylNNZ8/H4bBGcMyXKUo1xwu/1578HeQ3KJFzIdsjPTBDyKVkTAln731VpQWeuJENKYITp1icseOcfcETdwjcuO+eCKbl8evXVzMZAsKpLIypnPlSn59uuKWoggkAlz2RPyeXHT6BInqOWCtNdbau6y1G5Kf7dbaDmvt+6y165L/diblrbX2aWvtWmvtndZa91oMECMjUWo2wYULMIHLGOYWUWSkKajO5mZeqZHqpANbEvddNTVhS3WpgeW5t7Xx8w0cD9DaykNR4AMN8YwuXWKukaEh7u6gz72vj9XAkfj9jIzgBHjV1DA5l+uH0OnyHrk893QgozN3S0tZWZlQCJENHIKEyqXGCEYigcNeaYRFiErPIQ53gzCaQZw/zxO46A6ivFy6446Jt+lqqKmRbrzRr86BAb7LDYEplbk7mXHxov/BNV4siyAEj2+IysQONpojQMF1l0rPTnH8ng1/EEYziKoq7maiqKvzn2x18SKv5EkXBm1tUZE2nzqnKjLa8Ev+H3BnJ89iDLECcCH1SuvgDjCbhGBzDLXiT5fhj8XY7s2VtISMpdFRvnMcGGBRRS5wMfxZvDUy3vATuAzY9vb0Dq4Qrp4gE4RDTQA6QWaKq4dSWYbYadG+PHNGuvNOvzqrqqR16/zqdFk8tbZmDb8vZKzhb23lSVku/sb2dv9coS4I4eoJ5pv0PKOk3fDDjqIqh4dZHH9nJ1sdDwwgnhhJEWkJeT/a26MER4JDh1htrFgMpUNIit5jujPp7/e/iwgBa/k7l0gEyFYHyFjD/+yzfBBs28ZtVGkpNz5VVSzrLpGIuF0IWlpY+XqXiKZ4PD2Daxy072OxACTmroYfdFRXF4vGKClhgUL79zP6wcFBnovW28sCD9rbeUhySwubyHJzOa3Dvn2cevHVV3mY5vbtzPhevhy98wRlZVF0YCoMDvLM6XPnOFeHT2Ss4f/oR6V3vYvJ3ncf3/YWF/OdxOzZbPLJyWGZmVJ0vkCKWxUU8FXVoUOwqFh1tdtbAEastZzAoq2NT2aUIVK1tfyeXnwRzfoLFjDWpDvvlB55JLXcQw9Jjz+eWm7BAul//I/UcpL01a8yN9ONN0qf/CTT+aUvsfFujPQnf8J0vvvd0oc+xGR/67f47uDzn2cLjhUrpJ//eabzU59iB+vTp0t/+IdM5+c/z91nXjGRrC/fn4lk7o6jvZ3JdXWxzMOxMa6zrY1nM7a2MrmODp7tSTMZG852WxuLpRZMJKw9dIgpPXAA3/yRI0xlQwPPZKTNtA0N1p49i0TbSy4jOZdnRMdSezvPoHXRSZHVOfl1Xg0KmLk7qUFJlXftYiuAvDxp926mc98+JidxbvADB7ir6fBhJrfs3G62PDaGJ3C1tmL/EU18OXGCu4VoM3XyJGYE2V25Asnt2cMPbelY2r2b3zvVSd+NRCK9Oqmci2wInfQddtHp0k6fyGjD39PDqwXSOuYuB6Eh4vjpgaDk0FaXhrqUNfScFRag4GfURkS2zBHisJzqdBnzFA0NkctjsuscGro2YvIsfoqMNvxlZTzjkK6mQpE9uATAeA+/DBXW47mhmWT405VDUVMTlUnyiYoK6ZZb/OqsrPSvs6WFM+5l8dbIaMNfX+9/VVFXx8kmKDLE7rohwE0FqccfwPBLrO9d6A8pamv9c9l2dbGkRZcwxRB0jk1NWcPvCxlt+CX/LFwuLEMUIyP+3TchjIpiMf++KwcEWfEXFKTN8A8OStOm+b0udQUODnJictrnra3S4sVMlsKF6bS52f/1pyoy1vC7rD5cSJqHhvwXggpB6jU05N+oOOXZB9huuBh+PEHk53unNKPXTmfCUYiaPpWVvGQ4RUMDJ3cZG/NfFDHdSNeuPWMNf0NDFAVCsGsXX8jW1rKomv5+Tpl2+TJ/wGNjLHO3vz9ApcI0p0Zmio+foro6mqBT4fx5XkZ461bWR1u3Mn2trdJxWDh9yxa2Ou/s5HXzabSdFCVB0lIZx44xnY2NkQuJoKaGJdB1d3NWr7IyXr7aJzLW8C9ZIj35JJOdP1/atInJ9vay6J+REV4XHdMEioeMnToFB4y1jCdQiiwQTZ0tK0Nv4cAAfwkvXIgOGgn27oWTRHs7Sp91MRYVFSwzdWyM7TSXLJEefphd+4tfZIbykUek9etTy82fL3384+zav/ALzNUyd26UYEmwerW0YQOTfec7mZsrJ4cfLBcW8vo/S5aw5MrZs6V77mE63/nOSO/bjokE//v+XEsCF4ELrR2ljLM2okkk6O+3Nh5nspQGrq7O2sss38jaf/1XJrdvn7WlpUz2u9+FF49YGgnKyzll3bPPwouXlET3BfDMM0xlaSl7nqOj6aNUvB7h0pf0fbOWJ2G66Hy7nrumagIXqYlhjHTwYLT6TIXiYl5n4+RJ5j6ePp0napSXM8/EypVRnQ+ExYuZ/+qhh7SrmdW22HPT57EHhZbAaGvjXAjUI7Wv6y6NbHoIydKa9K2tbLeRn++WYEjdXHR8UjlJeuklv3IhdBrD74n2uxQl5BG4JFu5PPd0IOMNPy3a1NDAoxyozpYWfthEdba18bwozCva0cEOOXJzeTs7c/G5Ca3+2NnJ/b1UZ/+AUcyy2QTVM1LUnTQShfZnd7dbrgnVSRCL8fMqeu2+Pn60QnWOjnJPpAvnLpVNt06fyHjD7xIFQl7WEDH3IQ5ix8bSGnkpyX9EAs2udkEQchelLxojxPhsbOSRNRQhoopCtHOqIqUpNMZ8zxjTaowpu+K7bxpjGowxJcnPh67429eMMVXGmEpjzAdCNdwV9EXt6WEHOC46QyTdNDc7HApBa5HmMH6nmG6KIDX+A4AadJeSHhR1df7Hp0uGMX2PQuTYuOB6onMkr9k/SfrgVb7/jrV2Q/KzXZKMMbdJ+pSk25P/5/8aYzyv4f4rfD+MEEkitbX+OU2bmqRly/zq7O7m/vhQ8P08XXh8KdJpAFwWJhR0EeGy26Ax9y46W1r4u+nCAeG7jFUmIKXht9bul9QJ9T0u6d+ttSPW2hpJVZLuu4b2vSVGRvwndLS0+A+v6uvjCVx0wDY2+k9fd0l0yxSEWPG7GADfk0QIw08pIkOw07mUYQjhCgyxg8oEXMvG+gvGmNKkK2jcXCyXdCV/VH3yuzfAGPOUMea4MeZ4W1vbhBpw6hRLqLBWOnuW6WxtZYM7xMvvonN01H+lwlAF6tKJdLp6hoZYApcUJTyRdp49yxirenv5YfXICBt7FRXS2rWp5WIxPpbPnWM6Jd7OWIyf6wwNuZVTIdePx/n1u7r4GPGJiRr+70paK2mDpCZJ/yv5/dVM3FW7ylr7jLV2k7V208IJMiivWROxF6WCMTyi5+BBxmx16BA/kd+2jQ2YY8c4p2pzM4yaGBpi6Y5JnZSGr72d3VNXVyRLUF3NktISiYjWkCCRYGG8LtyndXVR9FUqdHYy6kVJuvtu5nIoKGB+7sFBbvhpSOHevSx8eXAwopMk2LOHM2PSEMmxMbdESMoXsXs3ez+bmjjp26VLaXIdkmB/SasllaX6m6SvSfraFX/bKenBVPpDJ3BZa+3ICJOrqWFydXURuRMBZYs6c8baykom+wd/AJNEWlut/aM/Qjr/7M+srapi1//t32ZynZ3W/p//w2T/4z/4c/rbv2VyP/6xtTt2pJYbGrL2ySeZzv/3/yJ5go4OJkcTfgiR2jh6e5lcUxOTa2zk16ay9B2ylrfTRW9/P2fHq67m16f3T5NA3wx6OxO4jDFXeuU+Jmk84mezpE8ZYwqNMWskrZN0dCLXoKiuZnIdHWyLvHo1q5uycmW0QiQroAcfZO28/fZo20m2/H/0R7C+y8KF0ic+gZR+/vM8qubXf521c+5cxjsrRdzI9PofgPFi69ezXWFRkfRrv8Z0vuc9/GyJxtJfusR2ULm5vK4P9aAuWcLG59Kl/H2jssuWcZ20nRLe5Gr6dJ4b4OKKpdenu2HfIOGc/ybpsKRbjDH1xpgnJf2lMeaMMaZU0sOSviRJ1tpySf8h6aykHZKettYGiKL+KWiBqdpa/iJQnUePckNFdBoT0SmSA6wZM3htGVVWooYuWMB1VlXxF+HMGS5HC2meOsXk6uq4C4cSvZ8+zX24dCydPs0TnqhOKifx5051Wstl6bVddLrcO5WlRSFddLq00ydSehWttb90la//4S3k/1TSn15Lo1xAjc/06czX66KTMhq61s4PwsDlOUA+RAJZTg430hTTpkU7PZ9lsUNUER0vIuo7BJLAOjCKhWCyozp7e/1HNE1VZHzmrsReBBfD7xvt7bwCIH0J0lxBWZL/CSqE4S8u9h81EdLwpwMuNAwULslWtC8bGvznrsRi/kNEMwEZb/gXLWIhnSEMPx2wLhSRVKdT5m6GpByGMvzkbMcF15vhd1md0/sOkWXrQtpC0d/PI9mmVALXZMeaNeywK92G3/eAdclipIjH07v6cTH8tO+nTcucFb9nojCMzk5p3jy/OgcHeX2qEO4jihA7Z5fSI1kGrglixgzG9jPu600HhodZHoFr+vqiRRNv09UwMBCA1csBmeLqoaTwiQSPGGlvZ/HkY2M8Pp8ihOGnGBhwoxD1nQzpsuKnGBnxn1zpGxlv+GfOZIPh8mV2Kt/czELG4vHohSHo7WVRIE1N/CUYHYUhhYkE9iE0NfEXpreXhazRbEcp0kcNJQ1/LCjwbyh7e1nynjGcgnDhQjbp5uRE5GcEO3eyR19SwhKTqqp4ZNyhQ+z5HDjAjfmhQ+w96ujgXBUVFbwk9alTbGFy4QJn3du+PT07vYw3/IWF0m/+Zmq5G26IYs9TYe5cVlAtJ4eXgThxgm39aDaqFGUmoixfY6QdO5DO5mZe3qCyksmNjUWDm6CjgxuW3l5mMJqaGJ2jtdLmzezaQ0Ns92iM9Gd/xnQ++KB0112p5XJzpW9+k+l86inG7bBiBauXY4x0xx3s2vfey55Pfj6nKbz/fuaKnDOHUy8WFfHztxUr2Hu8aJG0bh3T+Xu/lx4CeWMnwYnFpk2b7PEJBrS6hKJR0KJVtJol3Ur39ESuKzK4Xcre0kpYIyNRX5KB6FLJk5al7u2N7p/0/eAg3x21tjK3WFkZM2zpdon5Bn2Hxk0FlfUpF0rW5VzLRTaEXboajDEnrLWQUfynyPgV/49/zOROnOBZfz/5CZM7doy5EebNk370o9Rys2dLL77IfNJr1vB7f7l8KcogLSyUtmxhOk+eZDWNJJ6gc+QId/W8+CKT276dH95RovedO3kCF31GP/4xd4k9+6zfaxvDZI3h13bR6dJO8h5JvJ25ufz6zz/P5CRuQ+j9+EbGG356GLhsWRRd41Pn8DDfplGdg4O8WiDVmZfHQwWpQZs1i5cjoO0sLuaRV7SdhYX8cJe2MxbjURtUp0uSn4tOCt86Xc52XOSobIh7d2FyC/GMfCLjDf+CBSyOf/HiKBKGgL6A+IDVEb63iAUF/g+Q5s7lhp9ixgz/Ibeh4vgzITUinV7c7m7/uQFDQ24RQJmAbDjnBHHvvZHbIRVoCJ4LKDFEuo9RQhj+OXP8G/7p03lZaooQ4ZwumKoTBD1XcUGIsFPXcioU6X7nUyHjDf/cuf7D9Xw/NJdklhAIYfhnz/bf76FW/Ok0/OkENWhDQ5yvgiJTDH+IXUSoycQnMt7wpxN0gkg3l20Iwx+C2ep6W/GPjPDD6ra29JXodYlSogatrc0/TWNnpzR/vl+dIQx/KBewT1wXhr+yMopYTIX29vQYAReeVJeVAp148vL4fTc3s4SWsTH/fRmirEYIw9/WxpN+aEnq3Fx2YNzVJe3bx3ReuMAm0u5uFlAQj/MxNzjIxvLwMA88oAxxiQRflAwM8N1OIsFZ5+ih7YED6TngvS4M/4MPshm2vp755LduZQ/j7FmWwXnmDDMU1kbXJmhujsIfCWprpfJyJjs8zJJ+4nFeS7yigtVTamrihnLHDmbQa2tZ7X6XRLO+PmakCwulP/5jpvPXfo25MebOlZ5+mumcMYOt5MvLWeDD0BCnPzxyhGV2d3XxZMCyMh5CvHMnkysp4dSL27ezyJ7GRu4Gfec7vVdMZ5gIbZfvjw/qRUJd19fHdJ06xeS+/3123R07rG1uZjqPHmVy1lpbUcHkRketbWlhspRS0Fpr29qY3IEDURtSIR63du9epvP8eSYXj3PKvDNnmNzAAJNLN8bGmFx3N3/uly8zOTrerOXjyEUnpT7s6OAUlXV1TC4ej/qUgFJuvhn0dlIvTiaMR/Sk2lbW1XFSZ7qdvf9+5pp49FFGIi5FZwHUz03DFGtreW4ArXFy/jzXOW0a20VUVEgPPMB0UpdQeTkrwSFxl0NlJR8jlCns1Cmuk5b2oLun2bP5c6clNRYt4vdO82tcdNJaOfPmRTWICOhuIyeH02O6lGnxiYw3/OfPM7nCQl7c6sIFJtfVxQq1GcPb2d3N8hIk3s54nGct03aOjESTqU+d9HxB4vdO5Vxkz5/nZzEu7aQ6aX9SufHr+5Rzkc2UdqZbp09kvOGfPZvFky9axBO4KFyiUOhLPW8er/pJccMN3I9JsXJlVPHUJ2bM8B/V41Ibna64XTJsfYf1udSL8V3C2AWTgSEuizdHxhv+++6LSM9TIURcbYi487lz2YGxxO+pqIgdtEm8Jr5LHD9tZ4j+dLm+b4SIO083aQpFCKKgkZH0ZspP9qQsF6Q0/MaY7xljWo0xZVd8N88Ys8sYcyH579zk98YY89fGmCpjTKkx5t6QjZeiuF7qe6MIQeBOQXcwkttApIN7+fKI4s6XPsmtP32v+CloRVYXtLVxrmWK9nb/8fFdXf7zTJyoQSH6+vyTpkhhDPpknyTIUP8nSR983XdflbTbWrtO0u7k75L0mKR1yc9Tkr7rp5mTEyEMVW4uj+t1uT4diGvXShcvMlnfCLXiJwiRvdre7t/wh5hMXOrqULhk7tKx2dcXFQec7JjsRl8Cht9au1/S673Oj0v6fvLn70v66BXf/3My0uiIpDnGGEDxcG3IyWHxtUVFLPabukbSXQ5g6VKWuDYOMiAXLfLvu6fXTueKf2CA+aRjMe42O3iQ7d56enhS1qlTLDqNJhtJYVb8Y2MskssFvb1hVvwhzmHovbtUHPWJiW5uF1trmyQp+e/43L5c0pVmoz753RtgjHnKGHPcGHO8jcaIvQmmTWPsSbNnS3v2pJYrLo6o/VIhkeAhop2dLPxydDSimCPo6+MGgyaqDAzw67/0Erunnh6WQNbby6KPrI0yHgkqK5nr6vRpFgKYkyO9+iq79sMPMyao2bMZO5wUrfaJ79xazq1w4gQ7V6qt5bvBffvYoqiri9NTnjrFI95eeontnKuqeALZq6+yc60zZ3gU3ZYt10fm7tXmzqvOZ9baZ6y1m6y1mxZe4971/e9n299bb2WuBGuZ4e/u5nG4jY3Mh1xQIL3nPUznAw9ImyD3zuc+F0XipMKMGdI316rusAAAHCZJREFUvsF0fvGLrM7J7bczuenT2arbmOhQn+Cuu5ihXLuW6czJ4XSK99/Pzw0o/eCnPsXyJ3JzpT//c6bzjjukm25KLbdggbRxI9P5iU8w19mcOdJHP5paToraSfvpl3+Z9f3q1dL73sd0fvrTrPTKbbdJjz3GdP7pn/IoLZ9A1IvGmNWStlpr70j+XinpPdbapqQrZ6+19hZjzN8lf/6318u9lf5roV7s7WV+v6GhqGZNTk7qju7ujmRTGaHBwUh22bLU14fshxocjLaJZKtID7sGBiJjQQZYCJ3jW/RUW+r+/mjiI5Eb9LnTa0v83vv6orGRCTqpa4TK0n530Rmindejzqvh7aZe3CzpieTPT0h64YrvP5uM7nlAUk8qo3+t2LaNyTU0SKWlzFDt3MlWnufOcR///v1M7sIFvk2ktWUqK7lOSmlYUsLPF158kRm0fft49izkj8c1WyTen9u3c78w7U/aR646Kei90353uX6IdrropLLpvnefIOGc/ybpsKRbjDH1xpgnJf2FpEeMMRckPZL8XZK2S6qWVCXp7yX9VpBWX4H8fFZy+MYb/UerLFvGSzHQl/qmm3gKOcVNN/EMQXrQ5HKwTO89RKlnl+v7Rjzu/9qxmH/XQIhEs9FR/4e7WfhDXioBa+0vvcmf3uAZSxYNgrUD/WDjxqheT6oaLyEYuBYt4gehFK65AdamfmlnzeJ14SmWLuUlMChcDL/vpBsXQ0WvHSKcs7XVf2JUV5f/pLAQCVwhIoWmKjI+c3f1anYQ6wJKTp6bywmYacipC+bP91/egZZNKC7mYY0ULqTwvifxECQf9FzHBY2N7EzJBSHYskLcuwuvRbqRZeAKDNcMUmIwli/nLhyKZcu4a4QatRBuoRtv5OcBvpGfH8bVQ9DREcbw+85ebWz0b1BDJFs1N/tvZ29v5hj+yZ7ElfGGX+L1ZZYtY7Haq1bxypMUIXSuXOlf5+rVvKSsb4Ty8ROEMPw9PSwCJhbjhmJ4mGcYU50haBKHh3nZbtrOUCt+36vzyW70pevE8N96a5SEkgp33hlF9qTCkiW8njfF4sXcJdXZyVbdo6M8kamujtVcHx2V9u5lOg8eZIO8pYUlvgwPs0Si7m7OT1tdzdpYUcEMwKVLbklM5L4vXuSliV9+mbniLl/mu8GGBpaI2N7OM6urq5nO7m6+E66q4q7AU6fYYrCmhiX4SdKxY+z8raqKcwwcPsx5NXziujD8M2eysChrWYZvfz/PiN2zhx2c9vZGA4fgrruYzuJi6ZFHmM7HHmNp+bNn8+STd7yD86rSvARacI+Sx1Pu19FRtkJdsIAnj/3+77M+X7dO+vznmc4vfYmFGs+fL90LSyT29bHciaYmXsUzkWA68/L4intkhOcQLF/OErjmzo2S9wje8Q52/4sXR4tMgocf9k/2ToASuELjWhK4xkG36pWVLI3+yBHGBnXyJH/BXCIdXOqupwskokji2/7xFWJhYWpZWlSNyo2MsOtK/L7TDdpO2kexWDQuST+59CeVHR3lZZljsWhSIaD95PLcQ+i8Gt7uBK5Jg/HaO6mM/sWLkbuDGP29e5nRP3eOR1js2cOM/tmz0QRBjD51yZSU8FLPVOfx43zbT0nhXegHCQeDFLWTRFMVFvJ737ePt5Pq3LvXv066ay0uZjrz8iLXBIFLf1KdBQVcJ3WBSryfaBKmi04q5xsZb/hbWtgLs2zZT/l5iU6CWbO4H5UWl5o3jxeNojolfk9UZyzGCWOozu5u7sKhOpubeb0cqrO1la/SXPqd6qTtdGGc8z0+rHXrT4oQ957Odrro9ImMN/y3384SiULEnbuWRSZYvJgfLNMV4sKFnCSbYs4cvouguN4yd0NcO0QSUwgughChl2Njk9/9mSnIeMN/xx3+M0hp3X4aRirxWvMhjNSCBTwKhiKTDH+64BLSSBGCgSsEuUuIzN3ubs4b4NsXPy57vSDjDb+roSQP78Yb/ceyr1vnP9mK1ikqLOQuFNqf15vhdyFlp3AxVBQhjHRra2YY/q4u/0xh6S4D4bJ49Hrdt/+S/kENxqpVLL7WpaAbNZRr1vjPiHXJBvYNFwJ3CpfMXd+rr4EB/4TjLpSG9H5Crfh9l2wIMZm4GH7an4OD/t1cLnAp++IT14Xh37gxit5IhbvvZsQp06fzpAo6wAoKePLJ6Cg7OJ02jR1Yx+P8wHhoiGUDDwzws4iuLn7vxMU2MsKLzg0Ps2v39zPDn0jwe7l0ifmkx8b4DvP8eaZzaIiXDO/p8U9pSMMpXVwt1PBbyxclzc38edbUsD7t6eFJYb29bgfRvnBdGP7Fi6Uf/CC1XF6e9MorqeXicR4u2NTEMmLjcU6FV1DAdC5YwNwtubl8OztnDkuiys/nrp6zZ5kRoNmm1kaZtgSvvcZWVCdPMq5hYyJaP4KmJuY+cilO19/PDP/wMC/FffAge+bl5TzDeNculuVaX88TG197jRlJY3jYZ2cnd7VYy85siovddqTUDesV1tq0fzZu3GivFTt3Mrl//3cm973vMblTp6ytrmayZWVMLhaztr+fyQ4PM7mRESY3NhZ9CAYGmFxXF5Pr6+P3TXW2tTG59nZrOzuZbFMTk+vrY3LWWjs0xOQGB7lOej81NUxudNTaqiomW1HB5BIJay9cYLK0ndZa29LC5EZH+TtE5azl75vL87waJB23E7C5Gb/iH1+lPfroW8t1dkYrkF/8RabziSdSy7W3Rwlhq1cznbffnlqurS1a/RG3Q309y3hsaeHb6eZmtjpvbuZZlDTRq6+PZ3tSnaOjbMU/fz7nQYjH2Spxxgxes6W9na0Si4u5Tno/q1cznfn5/PnccgvTaQyPfKLtlPgqOj+fhzq7hETT+HxaosQ3Mt7wHzzI5GKxKIOUGMCDB9kWvasrcmNQnQTt7W5bdIKyssiXSECzKEtLufGlZDUuOmk7T55kxcIk3s4jR/hWnuo8fJhPzvTe6fhwkXUhHqKyLjpDtJPqpP3uInvkSHoi2TLe8C9ZwiJbFi3yn8S0Zo3/sM8Q0T8hInAKCrhBpXBJsqOGNz+f+88p0h3P7fv6LnVtKIaG/OcwhKpflc4Ev3nzeAa8T2S84X/wQf/0h9RQ5uXxUKwZM1gkSlERN6h0wBYWcp3UqLjkBlDQxDkX0FwHV6SrhvvICHexuVBE+g4RDcHAFSKO3wUuEy6VnT8/Pe6ejDf8rgaIPJCbb+buForbbmOROpL/FV1hof8Vv8tkQlFcHMbw0xV/JmRwhjB+6aZepP0ZgiwnBHm9C0LQpxJkvOGXoheWHLZR18zatf6zbENwA9MXxmUXQRHC8IdySYVw9aTLPZAphj9E5q4LLzJ9PiHqFLkgI1f8xphLxpgzxpgSY8zx5HfzjDG7jDEXkv8G35zdcw9LzNqwgcmF2EXk5IRZKRKdIVb8eXl8dd7fz9pZVMQT52IxNtlniquHIoThD6EzFuO5I7QvQ6z4XQw/5ex2QYhdLoGPFf/D1toN9qdkAF+VtNtau07S7uTvQXHzzYx6saCAUeFJ0eqCPOSCAl7umVIVNjZGyTKp0NbGMpZraxnlpCS98AIzqHV1rI1SdAZDXu66Ot7OnTuZzosXpTNnUsuNjf2U2yEVqqpYSY+2NjYupeh+yM7kyBEWKtjRwc++jh9n70VNDc8yPXuWTbgNDbzsSGkpOyeLxViiphQtBClv9YkTLMlPkp5/nr3rnZ1u0VfeMJHg//GPpEuSFrzuu0pJS5M/L5VUmUrPtSZwxePWfu5zqeUSCWufeILp/M3fZHLl5dZu3cpkf/ADrvPSpdRy586xBKXBwUgnAU28GR21trWVyVK5WMza+nom29jI5Do7eRLXjh1Mbs8elqCTSESyBIcPM7kzZ6J+Ijh+nMlt387kqqut3bWLyX7nO0yuudnaH/2Iyf7rv/LkwhdfZHLt7dY2NDBZmqhprbWVlVz26FEu+3pogglc10S9aIypkdQlyUr6O2vtM8aYbmvtnCtkuqy1b9hIGmOekvSUJK1atWpjbW3thNshRTPnvHmp5Wh1Q5ftL63wl07fcBZZXCvGXR0kx8UlRJSGaWbfnzciXdSLD1lr75X0mKSnjTE/S/+jtfYZa+0ma+2mhddQxu+556J/Uxr9igrp3Dlk9F94gRn9kpLowJYY/RdeYIPWZTv5wgtMjhLCS4yMXpJefplnhlKde/bwRDOqc/dunhRG+/PFF/m5AdW5eTP3H1OdVI7KGsPrTeXl8etv28bkjEnfvUt8zLnIbt6cgWWZrbWNyX9bJT0n6T5JLcaYpZKU/DcouRhNydfatZHjEYBGqyxfzpOt6OHq0qU8+oe2Mxbj2YEuOmkOA733ggJu+KnOwkI+6bnkOlDDT3WOjPDVLNXpkgzn0k6CRMJ/H7nIplsn7fvp0zMsnNMYM90YM3P8Z0mPSiqTtFnSeKWbJyQ5zL3uuPtueCDoUOydrrwWLHDLBiZ6lyzh5Y4pQtT8DkEgMWsWN9IUM2fyyYSioCBNFRUVhjCmp8c/TSJ1vUr8fUt36GWIqLwQ7zvBtQyhxZIOGGNOSzoqaZu1doekv5D0iDHmgqRHkr8Hwy238BK9FDTL1hi+Slu8mEVEhAj7DGGkQ+icOdO/4Z81K4zhT1cZiJ6eqRvH39HBJ5NMQboM/4QrdFhrqyXdfZXvOyS971oa5QLnwx5wQnTjjZEL5+433N3EccstERnKkiWpZakRoPeeSSt+mjhH+2jWLO6Oo/2ZzhV/Z6d/w9/SEnlCCWi/Nzfz94f2u8sugiLEDsoFc+dmmKtnMiEnBxq2lSvRyalL8TX6IoSY2em1Qxl+3zpDrPivN1dPCOMXgsfXZXVOx3GIex8Z8V9MzgWhEjtTXvftv6R/bNgA/fx33YUEi4rcDqZo1IiLe4CspkdH2SFSby9LCx8bk06fTi0nRRMjYWOyNkpmIWho4GxM58+z67e28ns6dIi9hG1tbBcRi3E35Pnz7FmWlbFDxq4uXru+rY1N4rEYN1KJhP+VNN3tuNBjNjfzg9i2Nn6m19DAbEg87n+xQ3BdGP5ly6R/+RcgmJcXccKlQCzGQ8x6enj45c6dTO7MGbbjqKlhWZyxGEsLz8+P+pJg40Zp/frUcsZI3/oW03nDDdKnP81kP/IRRoCzbJn0rncxnRs2MLfD4sXsMDQvjx9GFhUxkpPCQuaPLyzkK9naWnbfpaVRVjnBSy+xMXfhAg62w1nLxvB3rafHrcS3S3kJEuadk8MXOz5xTQlcvrBp0yZ7nNQeeAs895z0sY8BwRdekB5/PKVYWZl0xx2p1fX3Ry8ZeciNjcyw1tVJK1akXjHRcrrDw1H7SJJMqJrnmQC6SnVJZBodZWWUaRKgy/OhOvv6GNn6OMk9GXOVldG5VirEYtFu57bbUstWVEi33ppaTuLVQROJ6L7IBD0ywhnIBgeladOY7LXUIEpXAlfaUVYW/ZvK6F++nKxHAox+eTkz+uPx9uTlKi9nRv/SpciPSYwKrZtSX8/j+F1cE9QdRmv6XLjAY6WpTpd20rLZLlFktLz3+fNs5Zmby++9spLJzZz50/forVBYyM+pbrmFtTMvj6+4b72V3zs9MM3J4Yf/LhV76Rlhebn/wnMEGW/46UCIx/mLTXV2dHDjS3X29fGiUeRllaKtPM2ypdvuixe5b5Tee1MTf2GpztbWaGfkU+fZs9xYUZ3l5dyN4KKTIp066Zhz0UnfDRedIdpZUZGlXpwQcnNZx8GAHifMmeOfNm3ZMu5HpQgRhRIiUmjOHF49lWLBAm74MwEu9WqoXAj3nsvhbghvc6bU9Jk923/UGUHGG/7x+PhUyM31H3c+dy43/HRwz5vHV73pjDsPZfi7u/3qDGH403ksFiLLNkQ9/t5e/+10oZ3MFMye7X/ME2S84V+/3n/mLsXs2XyFmpvLQsxcViou0Qi+DX9env8taoiXwGVydkG6VpQh+HFD6AwRc08PoV0QgkfXBSF2uQQZb/hdDJBvo+qy6l22LD2p2ZJbiYF0JoW5JFvRBLIQO710IgQLVSjDH2IXMWuWX5008ikUQuxyCTLe8IfA9OmcApBixQqeUEORTldPfz/nCt2zh7MR0QP4nBx2gDY2xtvZ0sLaOTTEYtQpVZ8LpZ+L4U8npaHLip+202XFT/tzeDi9mbsuXgOfuC4Mv7UsaqWoiBmB3l7ptddSyw0NRYkqBImEdOAAk62uZmGNly+zA+u6OhaRkEjweutjY3xyfOwx9nLPm8div6UoRpucheTm8pDKmhrWzuZmlkh09iy/Ns1uPnCAZY+2t0uHDzOdx46xvmxt5RNzWRmbHEdGeBRbTQ3f3Z88yYz/+fM8Mu/UKdZP1kp79zKdHR1uEUi+MOEibZMJo6PS0aPSww+/tVwiEfFbfuQjby334IPMqBUXS1/5Cmvj8uUs01SKBg45xFq7lq2A7rqL8Zrm5Ehf/3pqOUl65BG+Rf75n2dyOTnSJz/JZB94gLmvcnKkb3yD6fzmN5nck0+y1ez69dHuMRWMkf7kT9i1n3giqiWVCvPnS5/5DNP57nezZKd586Q772Q658yJPqlQUMBLnvT18aSoVavYJL5okbRuHdP54IPMfWWM9OijTOeiRTwpzScyPnN3PCu1t/etH8q4q6OvL/W2lm7/RkejMwYStjY8HCXApBqM48QyJJOQZgeOjER9RNtJ7n08woK8XFmdTI6MD1ed1I1BZWlN/Hg8mpiJThpVNJ43QnQODLBJV+L35MIHQGVdnvvVMGUzdzdvjrbzqQZOeXmUFUt8mZQ27cgRXrRp82b2cI8f5+GHW7cyuQMH+AESdfW88gpfqdH+3L+ft5PqPHiQ+/ipThdaP6pzyxb+8rvQ+lH4ph/MzeWyoHyWpMjgU5201pbExzx931x0UrvgGxlv+CluuCHKYPWJadP8HwIvWsT8xxI/wCou5u2kOvPy/JORzJrl/6ArFNFFpiQIpRO+E82y8IeMN/zUAIWI5542jZdCoHAx/BTFxeygzQUOTJYYIdiy0sVwJIWJEQ+RxBSihPIk8CBnDLL1+CeAtWtZ8aQQq4oQK36XWHZ6Ty4rfqozxIo/RPp6uhiOpDAcsSFCL/v7I7pRAjo+XO6dGr5YzH9piXQzcIVIhCTIeMN/882MkCMEXAx/iG0vfWGmTeMrfpds4BArfhdXD2mrMelbfXZ3hyEx9234Q5SBCJFlOzjID2wphoZ4pFAIZA3/BFFczKtE+oaL4S8o4O30vTsJ4eqhK35refLY9OmcjcilplG60NPDQhpdEIJwPERGrIvhp+PdJVKH6nSpm+8Cev38fP87Z4Jght8Y80FjTKUxpsoY89VQ13EBXfn19LDzgOZmnnwxa9ZP6/f7BLmn/Hy+kq6sZDpra1kyjzE8ya2xUTpxgsn290v79qWWs1Z6+WWmc+dOVgbi8GHWn2fOMNfVwIBbuWGyQhwb41Vem5tZiGQ8zlenoVb81EjTdz2ETpdM7Nzc9Cxcgxh+Y0yupP9P0mOSbpP0S8YYwLEzMZw5w0IL6+ujOvIE5MVetUq6+26mb2yME2O88AIbOJcvR9mEqdDczAvZ5eSw1cqmTYysRpK+/W0mt3y59MUvMtn3vpexNhkjffzjTOev/irzIT/+OHONzJvHkoOmTYvKhhMUFrJdRF4eDxK4cIG9Py6T+NGjEe9sKljLQx9PneJlTzZvZjWaTp7k0X7PP88XReS9HJel2dA+ESSByxjzoKRvWms/kPz9a5Jkrf3zq8lfK/XiP/5jlNGY6pDm1VejF3HJkreWGxiIXkafLpdEIloFEYNBaR8vX474X0mUR2sr42p1oZfL4q3hUjufRtbEYpFRJ6CukfGCaqStlNLw0qVoIifZ3ceOSe94R2q56upo0iOurvJy6fbbU8u1tkbjnbyX1dXSjTemlpOi+yeZ+m1t0bUnGqk10QSuUIb/E5I+aK399eTvvyLpfmvtF66QeUrSU5K0atWqjbXXEGTvwpUaXXvCl8oiiyyymDSYqOEPVavnaqb1v8ww1tpnJD0jScaYNmPM6y3/AknXEXfShJHth2wfjCPbD9k+GMd4P9wwkf8cyvDXS7rSa7lC0pseNVlrF77+O2PM8YnMZNcbsv2Q7YNxZPsh2wfjuNZ+CBXVc0zSOmPMGmNMgaRPSXKoHJJFFllkkUUoBFnxW2tjxpgvSNopKVfS96y1MGAtiyyyyCKLkAhWj99au13S9mtQ8YyvtmQ4sv2Q7YNxZPsh2wfjuKZ+mBT1+LPIIosssnj7kPElG7LIIosssnBD1vBnkUUWWUwxTDrDPxlr/ISCMeZ7xphWY0zZFd/NM8bsMsZcSP47N/m9Mcb8dbJfSo0x96av5f5gjFlpjNljjDlnjCk3xnwx+f1U64ciY8xRY8zpZD98K/n9GmPMa8l++GEySk7GmMLk71XJv69OZ/t9whiTa4w5ZYzZmvx9KvbBJWPMGWNMiTHmePI7b+/EpDL8b3eNn0mAf5L0wdd991VJu6216yTtTv4uRX2yLvl5StJ336Y2hkZM0u9aa9dLekDS08lnPtX6YUTSe621d0vaIOmDxpgHJH1b0neS/dAl6cmk/JOSuqy1N0n6TlLuesEXJV1ZwWYq9oEkPWyt3XBFvL6/d8JaO2k+kh6UtPOK378m6Wvpblfge14tqeyK3yslLU3+vFRSZfLnv5P0S1eTu54+kl6Q9MhU7gdJ0ySdlHS/ouzMvOT3//l+KAqVfjD5c15SzqS77R7ufUXSqL1X0lZFVQCmVB8k7+eSpAWv+87bOzGpVvySlku6fMXv9cnvphIWW2ubJCn573hpteu+b5Jb9XskvaYp2A9JF0eJpFZJuyRdlNRtrR0vhnzlvf5nPyT/3iPJM0VLWvBXkv5A0nhtzfmaen0gRSVuXjLGnEjWNZM8vhPB4vgniJQ1fqYwruu+McbMkPSspN+x1vaaN6+kd932g7U2LmmDMWaOpOckrb+aWPLf664fjDEfltRqrT1hjHnP+NdXEb1u++AKPGStbTTGLJK0yxjzVoXVnfthsq34nWr8XKdoMcYslaTkv+NV1a/bvjHG5Csy+v9irf1J8usp1w/jsNZ2S9qr6MxjjjFmfIF25b3+Zz8k/z5b0iTnJEuJhyR9xBhzSdK/K3L3/JWmVh9Ikqy1jcl/WxUtAu6Tx3dishn+bI2f6H6fSP78hCKf9/j3n02e4D8gqWd825fJMNHS/h8knbPW/u8r/jTV+mFhcqUvY0yxpPcrOuDcI+kTSbHX98N4/3xC0is26eDNVFhrv2atXWGtXa3o3X/FWvsZTaE+kCRjzHRjzMzxnyU9KqlMPt+JdB9iXOVQ40OSzivyb/5hutsT+F7/TVKTpDFFs/aTinyUuyVdSP47LylrFEU8XZR0RtKmdLffUx+8S9G2tFRSSfLzoSnYD3dJOpXshzJJf5z8/kZJRyVVSfqRpMLk90XJ36uSf78x3ffguT/eI2nrVOyD5P2eTn7Kx+2gz3ciW7IhiyyyyGKKYbK5erLIIosssgiMrOHPIosssphiyBr+LLLIIosphqzhzyKLLLKYYsga/iyyyCKLKYas4c8iiyyymGLIGv4sssgiiymG/x+qG41AYkZsNQAAAABJRU5ErkJggg==\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "Image Pair 1\n" ] } ], "source": [ "windef.piv(settings)" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [], "source": [ "#Run the extended search area PIV" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "\n", "\n", "# we can run it from any folder\n", "path = settings.filepath_images\n", "\n", "\n", "frame_a = tools.imread( os.path.join(path,settings.frame_pattern_a))\n", "frame_b = tools.imread( os.path.join(path,settings.frame_pattern_b))\n", "\n", "frame_a = (frame_a).astype(np.int32)\n", "frame_b = (frame_b).astype(np.int32)\n", "\n", "u, v, sig2noise = process.extended_search_area_piv( frame_a, frame_b, \\\n", " window_size=32, overlap=16, dt=1, search_area_size=64, sig2noise_method='peak2peak' )\n", "x, y = process.get_coordinates( image_size=frame_a.shape, window_size=32, overlap=16 )\n", "u, v, mask = validation.sig2noise_val( u, v, sig2noise, threshold = 1.3 )\n", "u, v, mask = validation.global_val( u, v, (-1000, 2000), (-1000, 1000) )\n", "u, v = filters.replace_outliers( u, v, method='localmean', max_iter=10, kernel_size=2)\n", "x, y, u, v = scaling.uniform(x, y, u, v, scaling_factor = 1)\n", "tools.save(x, y, u, v, mask, 'test1.vec' )\n", "tools.display_vector_field('test1.vec', scale=75, width=0.0035)" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [], "source": [ "#Run the widim" ] }, { "cell_type": "code", "execution_count": 9, "metadata": { "scrolled": true }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "----------------------------------------------------------\n", "|-----> || The Open Source P article |\n", "| Open || I mage |\n", "| PIV || V elocimetry Toolbox |\n", "| <-----|| www.openpiv.net version 1.0 |\n", "----------------------------------------------------------\n", " \n", "('Algorithm : ', 'WiDIM')\n", " \n", "Parameters \n", "-----------------------------------\n", "(' ', 'Size of image', ' | ', [369, 511])\n", "(' ', 'total number of iterations', ' | ', 3)\n", "(' ', 'overlap ratio', ' | ', 0.0)\n", "(' ', 'coarse factor', ' | ', 2)\n", "(' ', 'time step', ' | ', 1.0)\n", "(' ', 'validation method', ' | ', 'mean_velocity')\n", "(' ', 'number of validation iterations', ' | ', 1)\n", "(' ', 'subpixel_method', ' | ', 'gaussian')\n", "(' ', 'Nrow', ' | ', array([ 5, 11, 23]))\n", "(' ', 'Ncol', ' | ', array([ 7, 15, 31]))\n", "(' ', 'Window sizes', ' | ', array([64, 32, 16]))\n", "-----------------------------------\n", "| STARTING |\n", "-----------------------------------\n", "('ITERATION # ', 0)\n", "..[DONE]\n", "(' --residual : ', 1.0000000344701572)\n", "no validation : trusting 1st iteration\n", "going to next iteration.. \n", "performing interpolation of the displacement field\n", " \n", "('..[DONE] -----> going to iteration ', 1)\n", " \n", "('ITERATION # ', 1)\n", "..[DONE]\n", "(' --residual : ', 0.08178167496214502)\n", "Starting validation..\n", "('Validation, iteration number ', 0)\n", " \n", "..[DONE]\n", " \n", "going to next iteration.. \n", "performing interpolation of the displacement field\n", " \n", "('..[DONE] -----> going to iteration ', 2)\n", " \n", "('ITERATION # ', 2)\n", "..[DONE]\n", "(' --residual : ', 0.12538231899438257)\n", "Starting validation..\n", "('Validation, iteration number ', 0)\n", " \n", "..[DONE]\n", " \n", "//////////////////////////////////////////////////////////////////\n", "end of iterative process.. Re-arranging vector fields..\n", "...[DONE]\n", "-------------------------------------------------------------\n", "('[DONE] ..after ', -20.805788278579712, 'seconds ')\n", "-------------------------------------------------------------\n" ] }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "\n", "\n", "scaling_factor = 1\n", "\n", "# we can run it from any folder\n", "path = settings.filepath_images\n", "\n", "\n", "frame_a = tools.imread( os.path.join(path,settings.frame_pattern_a))\n", "frame_b = tools.imread( os.path.join(path,settings.frame_pattern_b))\n", "\n", "#no background removal will be performed so 'mark' is initialized to 1 everywhere\n", "mark = np.zeros(frame_a.shape, dtype=np.int32)\n", "for I in range(mark.shape[0]):\n", " for J in range(mark.shape[1]):\n", " mark[I,J]=1\n", "\n", "#main algorithm\n", "with warnings.catch_warnings():\n", " warnings.simplefilter(\"ignore\")\n", " x,y,u,v, mask=process.WiDIM( frame_a.astype(np.int32), frame_b.astype(np.int32), mark, min_window_size=16, overlap_ratio=0.0, coarse_factor=2, dt=1, validation_method='mean_velocity', trust_1st_iter=1, validation_iter=1, tolerance=0.7, nb_iter_max=3, sig2noise_method='peak2peak')\n", "\n", "#display results\n", "x, y, u, v = scaling.uniform(x, y, u, v, scaling_factor = scaling_factor )\n", "\n", "tools.save(x, y, u, v, mask, '2image_00.txt' )\n", "\n", "tools.display_vector_field('2image_00.txt',on_img=False, image_name=os.path.join(path,'../test2/2image_00.tif'), window_size=16, scaling_factor=scaling_factor, scale=200, width=0.001)\n", "\n", "#further validation can be performed to eliminate the few remaining wrong vectors\n" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.7.3" } }, "nbformat": 4, "nbformat_minor": 2 }