Functions¶
Commonly used functions
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sls_detector_tools.function.double_gaus_edge_new(x, p0, A, mu, sigma1, sigma2)[source]¶ Variant of the double gaussian.
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sls_detector_tools.function.gaus(x, A, mu, sigma)[source]¶ Gaussian function
\[f(x) = A e^{-0.5*(x-\mu) / {\sigma^2}}\]Parameters: - x – x values to evaluate the function at
- A (double) – scaling
- mu (double) – center
- sigma (double) – width
Returns: y – evaluated vales at each x
Return type: value or array
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sls_detector_tools.function.ideal_dqe(omega)[source]¶ Expression for the ideal DQE given an ideal MTF
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sls_detector_tools.function.paralyzable(x, tau)[source]¶ Paralyzable detector model, used for rate measurements
\[f(x) = xe^{- \tau x}\]
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sls_detector_tools.function.pol1(x, p0, p1)[source]¶ Linear function. Parameters in the same order as in ROOT
\[f(x) = p_0 + p_1x\]
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sls_detector_tools.function.pol2(x, p0, p1, p2)[source]¶ Second degree polynomial
\[f(x) = p_0 + p_1x + p_2x^2\]
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class
sls_detector_tools.function.root[source]¶ Bases:
objectStrings to build ROOT functions from
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double_gaus_edge= '[0]+[1]/4 * ((1-TMath::Erf( (x-[2])/(sqrt(2)*[3])))+ (1-TMath::Erf( (x-[2])/(sqrt(2)*[4]) ) ) ) '¶
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scurve= ' ([0]+[1]*x) + 0.5 * (1+TMath::Erf( (x-[2])/(sqrt(2)*[3]) ) )* ( [4] + [5]*(x-[2])) '¶
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scurve2= ' ([0]+[1]*x) + 0.5 * (1-TMath::Erf( (x-[2])/(sqrt(2)*[3]) ) )* ( [4] + [5]*(x-[2])) '¶
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scurve4= ' ([0]+[1]*x) + 0.5 * (1-TMath::Erf( (x-[2])/(sqrt(2)*[3]) ) )* ( [4] + [4]/[5]*(x-[2])) '¶
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sls_detector_tools.function.scurve(x, p0, p1, mu, sigma, A, C)[source]¶ scruve function used for energy calibration scurve(x, p0,p1, mu, sigma, A, C)
[0] - p0 [1] - p1 [2] - mu [3] - sigma [4] - A [5] - C