f_r mishap
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@@ -845,7 +845,7 @@ def delayed_raman_w(t, dt, raman_type="stolen"):
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return fft(delayed_raman_t(t, raman_type)) * dt
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def create_non_linear_op(behaviors, w_c, w0, gamma, raman_type="stolen", f_r=None, hr_w=None):
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def create_non_linear_op(behaviors, w_c, w0, gamma, raman_type="stolen", f_r=0, hr_w=None):
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"""
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Creates a non-linear operator with the desired features
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@@ -861,10 +861,10 @@ def create_non_linear_op(behaviors, w_c, w0, gamma, raman_type="stolen", f_r=Non
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nonlinear parameter
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raman_type : str, optional
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name of the raman response function model. default : "stolen"
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f_r : float, optional
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fractional contribution of the delayed raman effect. default : 0
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hr_w : 1d array, optional unless "raman" in behaviors
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pre-calculated frequency-dependent delayed raman response function
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f_r : float, optional
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overwrite fractional contribution of the delayed raman effect. default : None
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returns
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-------
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@@ -874,11 +874,11 @@ def create_non_linear_op(behaviors, w_c, w0, gamma, raman_type="stolen", f_r=Non
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"""
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# Compute raman response function if necessary
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f_r = 0.18
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if "raman" in behaviors:
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if hr_w is None:
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raise ValueError("freq-dependent Raman response must be give")
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if f_r is None:
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if f_r == 0:
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f_r = 0.18
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if raman_type == "agrawal":
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f_r = 0.245
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