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| META TOPICPARENT |
name="StewartBoogertPhotometry2016" |
Part One |
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- Test 2: 100x100 pixels, A=65535 (pixel value range for camera), 10 stars
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- Larger pixel value range results in less obvious variations - almost indistinguishable from earlier gaussian simulation.
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Part Three
Aims:
- Implement correlated 2d gaussian function
- Implement way to save simulated star fields as FITS files
Corelated gaussian (18/10/16): Simulation_test5.py.txt
- Implemented a true 2D Gaussian with correlation between x and y (with correlation coefficient P (rho)):
- (Note: normalisation factor is ignored so far for programming purposes; maximum pixel value is being used in its place)
- Integration of 2D Gaussian in this form is done numerically.
- Tested for P =0, P =0.5, P =0.999 (sigma_x=sigma_y=3 in each case)
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- (Note - image is rotated 90 degrees clockwise)
- Also - found a way to save images as FITS files, similar to images gained from observations.
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| | -- AaronAndrews - 09 Oct 2016
| META FILEATTACHMENT |
attachment="PositionSimTest2.png" attr="" comment="random position test (100x100, 50 stars)" date="1476004481" name="PositionSimTest2.png" path="PositionSimTest2.png" size="19417" user="zyva010" version="1" |
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attachment="PoissonExample1.png" attr="" comment="Example of poisson distributed pixel values on a 16x1 pixel grid" date="1476354830" name="PoissonExample1.png" path="PoissonExample1.png" size="51505" user="zyva010" version="1" |
| META FILEATTACHMENT |
attachment="PoissonSimTest1.png" attr="" comment="Poisson simulation test 1: 100x100 pixels, A=100, 10 stars" date="1476446063" name="PoissonSimTest1.png" path="Y:\PH4100\Images_s\PoissonSimTest1.png" size="40318" user="zyva010" version="1" |
| META FILEATTACHMENT |
attachment="PoissonSimTest2.png" attr="" comment="Poisson simulation test 2: 100x100 pixels, A=65535, 10 stars" date="1476446081" name="PoissonSimTest2.png" path="Y:\PH4100\Images_s\PoissonSimTest2.png" size="30068" user="zyva010" version="1" |
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| META FILEATTACHMENT |
attachment="Simulation_test5.py.txt" attr="" comment="simulation test 5" date="1476906045" name="Simulation_test5.py.txt" path="Simulation_test5.py" size="7782" user="zyva010" version="1" |
| META FILEATTACHMENT |
attachment="SkewTest2.png" attr="" comment="Testing x and y correlation (P) for P=0, P=0.5, P=0.999" date="1476906074" name="SkewTest2.png" path="SkewTest2.png" size="19013" user="zyva010" version="1" |
| META FILEATTACHMENT |
attachment="latex5f9f5400b35695f2f95ae5e6adc621f5.png" attr="h" comment="" date="1476906342" name="latex5f9f5400b35695f2f95ae5e6adc621f5.png" user="zyva010" version="1" |
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![\begin{equation} f\left ( x,y\right )= \frac{1}{\pi \sigma _{x} \sigma _{y} \sqrt{1-\rho ^{2}}} \exp {\left [ - \frac{1}{2\left ( 1-\rho ^{2} \right )}\left ( \left (\frac{ x-x_0 }{2{\sigma _{x}}^{2}} \right )^2 + \left (\frac{ y-y_0 }{2{\sigma _{y}}^{2}}\right )^2 -2\rho \left (\frac{ x-x_0 }{2{\sigma _{x}}^{2}} \right )\left (\frac{ y-y_0 }{2{\sigma _{y}}^{2}}\right ) \right )\right ]} \end{equation}](/twiki/pub/Public/Photometry2016_Simulation/latex5f9f5400b35695f2f95ae5e6adc621f5.png)
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