Difference: Photometry2016_Simulation (6 vs. 7)

Revision 719 Oct 2016 - AaronAndrews

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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
  • PoissonSimTest2.png
  • Larger pixel value range results in less obvious variations - almost indistinguishable from earlier gaussian simulation.

Part Three


  • 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)):
 \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}
  • (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)
  • SkewTest2.png
  • (Note - image is rotated 90 degrees clockwise)
  • Also - found a way to save images as FITS files, similar to images gained from observations.
 -- AaronAndrews - 09 Oct 2016

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META FILEATTACHMENT 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"
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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"
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