Commit 63ab88fe authored by Bilheux, Jean-Christophe's avatar Bilheux, Jean-Christophe
Browse files

added histogram tutorial in gamma_filtering

parent be81c282
......@@ -10,16 +10,16 @@
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"title": "Gamma Filtering Tool",
"tags": [],
"description": "",
"content": " Notebook name: gamma_filtering_tool.ipynb\nDescription This notebook will allow you to compare data loaded without any correction against data loaded with gamma filtering on. You will be able to change the gamma filtering coefficient to optimize the cleaning of the gammas without dammaging the images.\nStart the notebook If you need help accessing this notebook, check the How To \u0026gt; Start the python notebooks tutorial.\nHow to Use It? Select your IPTS Check the full tutorial here\nSelect Images Simply select all the images you want to work on.\nCheck the file selection tool tutorial to learn how to use the file selector tool. Display Images Mouse Infos / Zoom and Pan Moving the mouse over the raw or filtered image will give you its value in the status bar (bottom left) of the UI. Also any zoom or pan transformation in one of the image will be reproduced in the other image.\nChanging the filtering coefficient After changing the gamma filtering coefficient and hitting ENTER, the entire stack of data will be reloaded using the new filter coefficient. The table will show you the new percentage and number of pixels cleaned. The gamma filtered plot will be refreshed to display the new cleaned selected image.\nGamma Filtering Algorithm If you wonder how the gamma filtering algorithm works and what is the meaning behind this magic gamma filtering coefficient\nHere is the workflow:\n user determine the gamma filtering coefficient (coefficient). Value between 0 and 1. Image per image, the program calculate the average counts (image_average_counts). if the coefficient * pixel_value \u0026gt; image_average_counts then this pixel is considered to be a gamma and is replaced by the average value of its 8 neighbor pixels. Feel free to move the plot around and resize them! "
"content": " Notebook name: gamma_filtering_tool.ipynb\nDescription This notebook will allow you to compare data loaded without any correction against data loaded with gamma filtering on. You will be able to change the gamma filtering coefficient to optimize the cleaning of the gammas without dammaging the images.\nStart the notebook If you need help accessing this notebook, check the How To \u0026gt; Start the python notebooks tutorial.\nHow to Use It? Select your IPTS Check the full tutorial here\nSelect Images Simply select all the images you want to work on.\nCheck the file selection tool tutorial to learn how to use the file selector tool. Display Images click the Auto scale to initialize the image just after launching the UI. Mouse Infos / Zoom and Pan Moving the mouse over the raw or filtered image will give you its value in the status bar (bottom left) of the UI. Also any zoom or pan transformation in one of the image will be reproduced in the other image.\nChanging the filtering coefficient After changing the gamma filtering coefficient and hitting ENTER, the entire stack of data will be reloaded using the new filter coefficient. The table will show you the new percentage and number of pixels cleaned. The gamma filtered plot will be refreshed to display the new cleaned selected image.\nGamma Filtering Algorithm If you wonder how the gamma filtering algorithm works and what is the meaning behind this magic gamma filtering coefficient\nHere is the workflow:\n user determine the gamma filtering coefficient (coefficient). Value between 0 and 1. Image per image, the program calculate the average counts (image_average_counts). if the coefficient * pixel_value \u0026gt; image_average_counts then this pixel is considered to be a gamma and is replaced by the average value of its 8 neighbor pixels. Feel free to move the plot around and resize them! Histogram of Raw and Filtered Data Sets A newer version of the UI offers the histogram of the images before and after filtering. This helps figuring out where the gamma are located.\n"
},
{
"uri": "/en/github/",
......@@ -326,7 +326,7 @@
"title": "Radial Profile",
"tags": [],
"description": "",
"content": " Notebook name: radial_profile.ipynb\nDescription This notebook allows you to display and export the radial profile of a set of images. Radial profile means that, after defining the center of your profile region, the closest pixel to the center will produces the first data point. Then the next ones will produces the second data point (average counts over the set of each pixels).\nConfusing!\nWell the following drawings should help you understand how that works.\nFull circle Step1: User defined the center of the profile (Red pixel in this example) Step2: User defined the sector to use (in this case, we used the entire sector 0 -\u0026gt; 360degrees) Program then calculate the position of each pixel relative to the new center defined Program order the pixels by their distance relative to the center. All the pixels at the same distance from the center will have their counts averaged. Profile of Counts vs pixel index position is then calculated. Sector Step1: User defined the center of the profile (Red pixel in this example) Step2: User defined the sector to use Program keeps only the pixel that are within the sector defined Program then calculate the position of each pixel relative to the new center defined Program order the pixels by their distance relative to the center. All the pixels at the same distance from the center will have their counts averaged. Profile of Counts vs pixel index position is then calculated. Start the notebook If you need help accessing this notebook, check the How To \u0026gt; Start the python notebooks tutorial.\nSelect your IPTS Need help using the IPTS selector?\n Select Images to Process Select the images you want to process using the File Selector. Once you click the Select button, the time stamp and the images will be automatically loaded. Wait for the progress bar to be done.\nNeed help using the File Selector?\n Profile UI Presentation Comig Soon\n"
"content": " Notebook name: radial_profile.ipynb\nDescription This notebook allows you to display and export the radial profile of a set of images. Radial profile means that, after defining the center of your profile region, the closest pixel to the center will produces the first data point. Then the next ones will produces the second data point (average counts over the set of each pixels).\nConfusing!\nWell the following drawings should help you understand how that works.\nFull circle Step1: User defined the center of the profile (Red pixel in this example) Step2: User defined the sector to use (in this case, we used the entire sector 0 -\u0026gt; 360degrees) Program then calculate the position of each pixel relative to the new center defined Program order the pixels by their distance relative to the center. All the pixels at the same distance from the center will have their counts averaged. Profile of Counts vs pixel index position is then calculated. Sector Step1: User defined the center of the profile (Red pixel in this example) Step2: User defined the sector to use Program keeps only the pixel that are within the sector defined Program then calculate the position of each pixel relative to the new center defined Program order the pixels by their distance relative to the center. All the pixels at the same distance from the center will have their counts averaged. Profile of Counts vs pixel index position is then calculated. Start the notebook If you need help accessing this notebook, check the How To \u0026gt; Start the python notebooks tutorial.\nSelect your IPTS Need help using the IPTS selector?\n Select Images to Process Select the images you want to process using the File Selector. Once you click the Select button, the time stamp and the images will be automatically loaded. Wait for the progress bar to be done.\nNeed help using the File Selector?\n Profile UI Presentation After running the lauch User Interface cell, the following GUI pops up.\nSelection of Sector Center Using the mouse, click the vertical and then horizontal lines on the image window to define the center of the sector.\nSelection of Sector Range Grid Settings It\u0026rsquo;s possible to change the settings of the grid (usefull when color of image and grid are too close).\nCalculate Radial Profiles Jump to the Profile tab and click the Calculate Profiles to calculate the radial profile of each image loaded. All those profiles will be displayed in the same plot below.\nExport Profiles Once the calculation of all profiles has been performed, the Export Profiles button becomes available. Click the Export Profiles \u0026hellip; and select where you want to create the ascii files.\nFile Name Convention The ASCII files creates will have the names bases such as\n\u0026lt;name_of_image\u0026gt;_profile_c_x\u0026lt;x_center\u0026gt;_y\u0026lt;y_center\u0026gt;angle\u0026lt;from_angle_in_deg\u0026gt;to\u0026lt;to_angle_in_deg\u0026gt;.txt\nwhere:\n name_of_image: is the name of the source image without the extension (20170811_Nautical_compass_0030_356_250_1875) x_center: the x axis position of the center (1024.0) y_center: the y axis position of the center (1024.0) from_angle_in_deg: starting sector angle in degrees (24.0) to_angle_in_deg: ending sector angle in degrees (137.0) giving a name of\n20170811_Nautical_compass_0030_356_250_1875_profile_c_x1024.0_y1024.0_angle_24.0_to_137.0.txt\nFile Format Each ASCII file produced start with the following metadata\n# source image: /Volumes/my_book_thunderbolt_duo/IPTS/IPTS-19621-CLOCK/CT/20170811_Nautical_compass_0030_356_250_1875.tiff # center [x0, y0]: [1024.0,1024.0] # angular range from 24.0degrees to 137.0degrees #pixel_from_center, Average_counts "
},
{
"uri": "/en/tutorial/notebooks/bin_images/",
......
......@@ -13,19 +13,19 @@
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