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# Author: Julien Pilet <julien.pilet@attolight.com> | |
# Date: 05/09/2019 | |
# | |
# Attempt to use sympy to automatically generate a python function that computes | |
# analytical derivatives of a lmfit model. | |
# | |
# This code needs the following lmfit version: | |
# https://github.com/jpilet/lmfit-py/tree/jp-sympy-hack | |
import math |
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function A() { | |
this.a = "from A()"; | |
} | |
A.prototype.a = "from A.prototype"; | |
function B() { } | |
B.prototype = Object.create(A.prototype); | |
function C() { } |
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### Keybase proof | |
I hereby claim: | |
* I am jpilet on github. | |
* I am leto (https://keybase.io/leto) on keybase. | |
* I have a public key whose fingerprint is 151B 6FF4 5775 A9D7 69BE 85ED B588 D2E1 01B4 2416 | |
To claim this, I am signing this object: |