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#assert fit.bounds is not None, f"For {algorithm}, there is no default fit boundary"
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#assert fit.initial_guess is not None, f"For {algorithm}, there is no default fit initial guess"
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iffit.boundsisnotNone:
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assert0<=fit.bounds[0][0] <=0.003, f"For {algorithm}, the default lower bound of D {fit.bounds[0][0]} is unrealistic"
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assert0<=fit.bounds[1][0] <=0.01, f"For {algorithm}, the default upper bound of D {fit.bounds[1][0]} is unrealistic"
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assert0<=fit.bounds[0][1] <=1, f"For {algorithm}, the default lower bound of f {fit.bounds[0][1]} is unrealistic"
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assert0<=fit.bounds[1][1] <=1, f"For {algorithm}, the default upper bound of f {fit.bounds[1][1]} is unrealistic"
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assert0.003<=fit.bounds[0][2] <=0.05, f"For {algorithm}, the default lower bound of Ds {fit.bounds[0][2]} is unrealistic"
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assert0.003<=fit.bounds[1][2] <=0.5, f"For {algorithm}, the default upper bound of Ds {fit.bounds[1][2]} is unrealistic"
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assert0<=fit.bounds[0][3] <=1, f"For {algorithm}, the default lower bound of S {fit.bounds[0][3]} is unrealistic; note data is normaized"
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assert1<=fit.bounds[1][3] <=1000, f"For {algorithm}, the default upper bound of S {fit.bounds[1][3]} is unrealistic; note data is normaized"
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assertfit.bounds[1][0] <=fit.bounds[0][2], f"For {algorithm}, the default upper bound of D {fit.bounds[1][0]} is higher than lower bound of D* {fit.bounds[0][2]}"
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iffit.initial_guessisnotNone:
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assert0.0008<=fit.initial_guess[0] <=0.002, f"For {algorithm}, the default initial guess for D {fit.initial_guess[0]} is unrealistic"
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assert0<=fit.initial_guess[1] <=0.5, f"For {algorithm}, the default initial guess for f {fit.initial_guess[1]} is unrealistic"
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assert0.003<=fit.initial_guess[2] <=0.1, f"For {algorithm}, the default initial guess for Ds {fit.initial_guess[2]} is unrealistic"
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assert0.9<=fit.initial_guess[3] <=1.1, f"For {algorithm}, the default initial guess for S {fit.initial_guess[3]} is unrealistic; note signal is normalized"
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