Very useful, can I ask a question?
If you need to make your expression in a symbolic way using sympy which
includes log or exp. Which fitting library would you recommend to easily
pass your sympy expression and get your fitted parameters.
Zohreh Karimzadeh
*https://www.researchgate.net/profile/Zohreh-Karimzadeh*
<https://www.researchgate.net/profile/Zohreh-Karimzadeh>
Skype Name 49a52224a8b6b38b
Twitter Account @zohrehkarimzad1
z.karimza...@gmail.com
+989102116325
((((((((((((((((Value Water)))))))))))))))


On Thu, Aug 18, 2022 at 4:49 PM Peter Stahlecker <peter.stahlec...@gmail.com>
wrote:

> Most welcome! If I was of help, great! If not, I still enjoyed our
> conversation.
>
> On Thu 18. Aug 2022 at 19:08, Zohreh Karimzadeh <z.karimza...@gmail.com>
> wrote:
>
>> thank you very much.
>> Zohreh Karimzadeh
>> *https://www.researchgate.net/profile/Zohreh-Karimzadeh*
>> <https://www.researchgate.net/profile/Zohreh-Karimzadeh>
>> Skype Name 49a52224a8b6b38b
>> Twitter Account @zohrehkarimzad1
>> z.karimza...@gmail.com
>> +989102116325
>> ((((((((((((((((Value Water)))))))))))))))
>>
>>
>> On Thu, Aug 18, 2022 at 4:35 PM Peter Stahlecker <
>> peter.stahlec...@gmail.com> wrote:
>>
>>> Whatever they are, I believe your second return statement does not work,
>>> because you are adding ‚things‘ which cannot be added.
>>> I do not understand your program, but I do understand, that your second
>>> return statement cannot work.
>>>
>>> On Thu 18. Aug 2022 at 18:56 Zohreh Karimzadeh <z.karimza...@gmail.com>
>>> wrote:
>>>
>>>> L and K are independent variables that will be passed to minimize.
>>>> Zohreh Karimzadeh
>>>> *https://www.researchgate.net/profile/Zohreh-Karimzadeh*
>>>> <https://www.researchgate.net/profile/Zohreh-Karimzadeh>
>>>> Skype Name 49a52224a8b6b38b
>>>> Twitter Account @zohrehkarimzad1
>>>> z.karimza...@gmail.com
>>>> +989102116325
>>>> ((((((((((((((((Value Water)))))))))))))))
>>>>
>>>>
>>>> On Thu, Aug 18, 2022 at 4:08 PM Peter Stahlecker <
>>>> peter.stahlec...@gmail.com> wrote:
>>>>
>>>>> I just have no idea what
>>>>>
>>>>> np.sum((np.log(AV) + Vlam_est)**2)
>>>>>
>>>>> could possibly mean.  np.log(VA) is an array of floats, that is an
>>>>> array of *numbers*.
>>>>> Vlam_est is a *function*. How you can add numbers and a function I do
>>>>> not know..
>>>>> Vlam_est will become an array of numbers, once you give it the
>>>>> arguments.
>>>>>
>>>>> NB:
>>>>> it seems, that Vi_est uses the arguments alpha,.., eta, L, K
>>>>> When you lambdify it, you skipped the arguments L and K.
>>>>> Any reason for this?
>>>>>
>>>>> On Thu 18. Aug 2022 at 18:18 Zohreh Karimzadeh <z.karimza...@gmail.com>
>>>>> wrote:
>>>>>
>>>>>> It seems always an expression of parameters and independent variables
>>>>>> is needed to be passed to fit and find parameters.
>>>>>> Zohreh Karimzadeh
>>>>>> *https://www.researchgate.net/profile/Zohreh-Karimzadeh*
>>>>>> <https://www.researchgate.net/profile/Zohreh-Karimzadeh>
>>>>>> Skype Name 49a52224a8b6b38b
>>>>>> Twitter Account @zohrehkarimzad1
>>>>>> z.karimza...@gmail.com
>>>>>> +989102116325
>>>>>>
>>>>>> ((((((((((((((((Value Water)))))))))))))))
>>>>>>
>>>>>>
>>>>>> On Thu, Aug 18, 2022 at 3:28 PM Peter Stahlecker <
>>>>>> peter.stahlec...@gmail.com> wrote:
>>>>>>
>>>>>>> In your first return statement, where it works, you seem to return a
>>>>>>> number.
>>>>>>> In your second return, your a ‚mixture‘ of numbers and functions:
>>>>>>> Vlam_est is a *function*, which requires four arguments as per its
>>>>>>> definition. Would you not have to return Vlam_est(alpha, beta, gamma, 
>>>>>>> eta) ?
>>>>>>>
>>>>>>> On Thu 18. Aug 2022 at 17:35 Zohreh Karimzadeh <
>>>>>>> z.karimza...@gmail.com> wrote:
>>>>>>>
>>>>>>>> the following code is ok when expression is passed as :
>>>>>>>>
>>>>>>>> import numpy as np
>>>>>>>> from scipy.optimize import minimize, curve_fit
>>>>>>>> from lmfit import Model, Parameters
>>>>>>>>
>>>>>>>> L = np.array([0.299, 0.295, 0.290, 0.284, 0.279, 0.273, 0.268, 0.262, 
>>>>>>>> 0.256, 0.250])
>>>>>>>> K = np.array([2.954, 3.056, 3.119, 3.163, 3.215, 3.274, 3.351, 3.410, 
>>>>>>>> 3.446, 3.416])
>>>>>>>> VA = np.array([0.919, 0.727, 0.928, 0.629, 0.656, 0.854, 0.955, 0.981, 
>>>>>>>> 0.908, 0.794])
>>>>>>>>
>>>>>>>>
>>>>>>>> def f(param):
>>>>>>>>     gamma = param[0]
>>>>>>>>     alpha = param[1]
>>>>>>>>     beta = param[2]
>>>>>>>>     eta = param[3]
>>>>>>>>     VA_est = gamma - (1 / eta) * np.log(alpha * L ** -eta + beta * K 
>>>>>>>> ** -eta)
>>>>>>>>
>>>>>>>>     return np.sum((np.log(VA) - VA_est) ** 2)
>>>>>>>>
>>>>>>>>
>>>>>>>> bnds = [(1, np.inf), (0, 1), (0, 1), (-1, np.inf)]
>>>>>>>> x0 = (1, 0.01, 0.98, 1)
>>>>>>>> result = minimize(f, x0, bounds=bnds)
>>>>>>>> print(result.message)
>>>>>>>> print(result.x[0], result.x[1], result.x[2], result.x[3])
>>>>>>>>
>>>>>>>> but when the expression is passed as the following way:
>>>>>>>>
>>>>>>>> import numpy as np
>>>>>>>> import sympy as sp
>>>>>>>> from scipy.optimize import minimize, curve_fit
>>>>>>>> from lmfit import Model, Parameters
>>>>>>>>
>>>>>>>> L = np.array([0.299, 0.295, 0.290, 0.284, 0.279, 0.273, 0.268, 0.262, 
>>>>>>>> 0.256, 0.250])
>>>>>>>> K = np.array([2.954, 3.056, 3.119, 3.163, 3.215, 3.274, 3.351, 3.410, 
>>>>>>>> 3.446, 3.416])
>>>>>>>> VA = np.array([0.919, 0.727, 0.928, 0.629, 0.656, 0.854, 0.955, 0.981, 
>>>>>>>> 0.908, 0.794])
>>>>>>>>
>>>>>>>>
>>>>>>>> def f(param):
>>>>>>>>     gamma, alpha, beta, eta = sp.symbols('gamma, alpha, beta, eta')
>>>>>>>>     gamma = param[0]
>>>>>>>>     alpha = param[1]
>>>>>>>>     beta = param[2]
>>>>>>>>     eta = param[3]
>>>>>>>>     Vi_est = gamma - (1 / eta) * sp.log(alpha * L ** -eta + beta * K 
>>>>>>>> ** -eta)
>>>>>>>>     Vlam_est = sp.lambdify((gamma, alpha, beta, eta), Vi_est)
>>>>>>>>
>>>>>>>>     return np.sum((np.log(VA) - Vlam_est) ** 2)
>>>>>>>>
>>>>>>>>
>>>>>>>> bnds = [(1, np.inf), (0, 1), (0, 1), (-1, np.inf)]
>>>>>>>> x0 = (1, 0.01, 0.98, 1)
>>>>>>>>
>>>>>>>> result = minimize(f, x0, bounds=bnds)
>>>>>>>>
>>>>>>>> print(result.message)
>>>>>>>> print(result.x[0], result.x[1], result.x[2], result.x[3])
>>>>>>>>
>>>>>>>>
>>>>>>>> I face difficulty:
>>>>>>>> *********************************************
>>>>>>>> Traceback (most recent call last):
>>>>>>>>   File
>>>>>>>> "C:\Users\Zohreh\AppData\Roaming\Python\Python310\site-packages\sympy\core\cache.py",
>>>>>>>> line 70, in wrapper
>>>>>>>>     retval = cfunc(*args, **kwargs)
>>>>>>>> TypeError: unhashable type: 'numpy.ndarray'
>>>>>>>>
>>>>>>>> During handling of the above exception, another exception occurred:
>>>>>>>>
>>>>>>>> Traceback (most recent call last):
>>>>>>>>   File
>>>>>>>> "C:\Users\Zohreh\AppData\Roaming\Python\Python310\site-packages\sympy\core\cache.py",
>>>>>>>> line 70, in wrapper
>>>>>>>>     retval = cfunc(*args, **kwargs)
>>>>>>>> TypeError: unhashable type: 'numpy.ndarray'
>>>>>>>>
>>>>>>>> During handling of the above exception, another exception occurred:
>>>>>>>>
>>>>>>>> Traceback (most recent call last):
>>>>>>>>   File
>>>>>>>> "F:\Zohreh\MainZohreh\postdoc-field\CSU\pythonProject\fit_test_2.py", 
>>>>>>>> line
>>>>>>>> 26, in <module>
>>>>>>>>     result = minimize(f, x0, bounds=bnds)
>>>>>>>>   File
>>>>>>>> "C:\Users\Zohreh\AppData\Roaming\Python\Python310\site-packages\scipy\optimize\_minimize.py",
>>>>>>>> line 692, in minimize
>>>>>>>>     res = _minimize_lbfgsb(fun, x0, args, jac, bounds,
>>>>>>>>   File
>>>>>>>> "C:\Users\Zohreh\AppData\Roaming\Python\Python310\site-packages\scipy\optimize\_lbfgsb_py.py",
>>>>>>>> line 308, in _minimize_lbfgsb
>>>>>>>>     sf = _prepare_scalar_function(fun, x0, jac=jac, args=args,
>>>>>>>> epsilon=eps,
>>>>>>>>   File
>>>>>>>> "C:\Users\Zohreh\AppData\Roaming\Python\Python310\site-packages\scipy\optimize\_optimize.py",
>>>>>>>> line 263, in _prepare_scalar_function
>>>>>>>>     sf = ScalarFunction(fun, x0, args, grad, hess,
>>>>>>>>   File
>>>>>>>> "C:\Users\Zohreh\AppData\Roaming\Python\Python310\site-packages\scipy\optimize\_differentiable_functions.py",
>>>>>>>> line 158, in __init__
>>>>>>>>     self._update_fun()
>>>>>>>>   File
>>>>>>>> "C:\Users\Zohreh\AppData\Roaming\Python\Python310\site-packages\scipy\optimize\_differentiable_functions.py",
>>>>>>>> line 251, in _update_fun
>>>>>>>>     self._update_fun_impl()
>>>>>>>>   File
>>>>>>>> "C:\Users\Zohreh\AppData\Roaming\Python\Python310\site-packages\scipy\optimize\_differentiable_functions.py",
>>>>>>>> line 155, in update_fun
>>>>>>>>     self.f = fun_wrapped(self.x)
>>>>>>>>   File
>>>>>>>> "C:\Users\Zohreh\AppData\Roaming\Python\Python310\site-packages\scipy\optimize\_differentiable_functions.py",
>>>>>>>> line 137, in fun_wrapped
>>>>>>>>     fx = fun(np.copy(x), *args)
>>>>>>>>   File
>>>>>>>> "F:\Zohreh\MainZohreh\postdoc-field\CSU\pythonProject\fit_test_2.py", 
>>>>>>>> line
>>>>>>>> 17, in f
>>>>>>>>     Vi_est = gamma - (1 / eta) * sp.log(alpha * L ** -eta + beta *
>>>>>>>> K ** -eta)
>>>>>>>>   File
>>>>>>>> "C:\Users\Zohreh\AppData\Roaming\Python\Python310\site-packages\sympy\core\cache.py",
>>>>>>>> line 74, in wrapper
>>>>>>>>     retval = func(*args, **kwargs)
>>>>>>>>   File
>>>>>>>> "C:\Users\Zohreh\AppData\Roaming\Python\Python310\site-packages\sympy\core\function.py",
>>>>>>>> line 476, in __new__
>>>>>>>>     result = super().__new__(cls, *args, **options)
>>>>>>>>   File
>>>>>>>> "C:\Users\Zohreh\AppData\Roaming\Python\Python310\site-packages\sympy\core\cache.py",
>>>>>>>> line 74, in wrapper
>>>>>>>>     retval = func(*args, **kwargs)
>>>>>>>>   File
>>>>>>>> "C:\Users\Zohreh\AppData\Roaming\Python\Python310\site-packages\sympy\core\function.py",
>>>>>>>> line 288, in __new__
>>>>>>>>     evaluated = cls.eval(*args)
>>>>>>>>   File
>>>>>>>> "C:\Users\Zohreh\AppData\Roaming\Python\Python310\site-packages\sympy\functions\elementary\exponential.py",
>>>>>>>> line 718, in eval
>>>>>>>>     coeff = arg.as_coefficient(I)
>>>>>>>> AttributeError: 'ImmutableDenseNDimArray' object has no attribute
>>>>>>>> 'as_coefficient'
>>>>>>>>
>>>>>>>>
>>>>>>>>
>>>>>>>>
>>>>>>>>
>>>>>>>>
>>>>>>>>
>>>>>>>>
>>>>>>>> Zohreh Karimzadeh
>>>>>>>> https://www.researchgate.net/profile/Zohreh-Karimzadeh
>>>>>>>> Skype Name 49a52224a8b6b38b
>>>>>>>> Twitter Account @zohrehkarimzad1
>>>>>>>> z.karimza...@gmail.com
>>>>>>>> +989102116325
>>>>>>>>
>>>>>>>> ((((((((((((((((Value Water)))))))))))))))
>>>>>>>>
>>>>>>>> Zohreh Karimzadeh
>>>>>>>> *https://www.researchgate.net/profile/Zohreh-Karimzadeh*
>>>>>>>> <https://www.researchgate.net/profile/Zohreh-Karimzadeh>
>>>>>>>> Skype Name 49a52224a8b6b38b
>>>>>>>> Twitter Account @zohrehkarimzad1
>>>>>>>> z.karimza...@gmail.com
>>>>>>>> +989102116325
>>>>>>>>
>>>>>>>> ((((((((((((((((Value Water)))))))))))))))
>>>>>>>>
>>>>>>>>
>>>>>>>> On Thu, Aug 18, 2022 at 10:42 AM Peter Stahlecker <
>>>>>>>> peter.stahlec...@gmail.com> wrote:
>>>>>>>>
>>>>>>>>> I use lambdify quite a bit, on rather large expressions.
>>>>>>>>> Basically, it always works like this for me:
>>>>>>>>>
>>>>>>>>> import sympy as sm
>>>>>>>>> x1, x2, …, xn = sm.symbols(‚x1, x2, ….., xn‘)
>>>>>>>>> ….
>>>>>>>>> …
>>>>>>>>> expr = some expression of generally with me: sm.sin, sm.cos,
>>>>>>>>> sm.exp, sm.sqrt,
>>>>>>>>>             sm.Heaviside, etc..
>>>>>>>>> This expression may have 50,000 terms, may be an (axb) matrix,
>>>>>>>>> whatever.
>>>>>>>>>
>>>>>>>>> expr_lam = sm.lambdify([x1, x2, …,xn], expr)
>>>>>>>>>
>>>>>>>>> Now I can evaluate expr_lam(…) like I would evaluate any numpy
>>>>>>>>> function.
>>>>>>>>>
>>>>>>>>> I have no idea, what expr_lam looks like, I would not know how to
>>>>>>>>> look at it.
>>>>>>>>> I assume, it converts sm.sin(..) to np.sin(…), etc
>>>>>>>>>
>>>>>>>>> This is how it works for me.
>>>>>>>>> As I do not really understand your points, like ‚dynamically
>>>>>>>>> created‘, ‚parse and subs‘, this may be of not help at all for you.
>>>>>>>>>
>>>>>>>>> Peter
>>>>>>>>>
>>>>>>>>>
>>>>>>>>> On Thu 18. Aug 2022 at 09:21 Zohreh Karimzadeh <
>>>>>>>>> z.karimza...@gmail.com> wrote:
>>>>>>>>>
>>>>>>>>>> Before run I import sp.sqrt or sp.exp but after run they get
>>>>>>>>>> disappeared.  My expression is big and dynamically created  and not
>>>>>>>>>> possible to parse and subs np.exp or sp.exp.
>>>>>>>>>>
>>>>>>>>>> Zohreh Karimzadeh
>>>>>>>>>>
>>>>>>>>>> Contact me on
>>>>>>>>>>            +989102116325
>>>>>>>>>>                      and at
>>>>>>>>>>      z.karimza...@gmail.com
>>>>>>>>>>                                  🌧️🌍🌱
>>>>>>>>>>
>>>>>>>>>>
>>>>>>>>>> On Thu, 18 Aug 2022, 01:17 Aaron Meurer, <asmeu...@gmail.com>
>>>>>>>>>> wrote:
>>>>>>>>>>
>>>>>>>>>>> Your expression uses "sqrt" but you haven't imported it from
>>>>>>>>>>> anywhere, since you only did "import sympy as sp". You need to use 
>>>>>>>>>>> sp.sqrt.
>>>>>>>>>>>
>>>>>>>>>>> Aaron Meurer
>>>>>>>>>>>
>>>>>>>>>>> On Wed, Aug 17, 2022 at 11:02 AM Zohreh Karimzadeh <
>>>>>>>>>>> z.karimza...@gmail.com> wrote:
>>>>>>>>>>>
>>>>>>>>>>>> Here is my code:
>>>>>>>>>>>>
>>>>>>>>>>>> import matplotlib.pyplot as plt
>>>>>>>>>>>> import numpy as np
>>>>>>>>>>>> import sympy as sp
>>>>>>>>>>>> import pandas as pd
>>>>>>>>>>>> #exp_NaCl path: 
>>>>>>>>>>>> F:\Zohreh\MainZohreh\postdoc-field\CSU\Duplicat_Pure
>>>>>>>>>>>> df = 
>>>>>>>>>>>> pd.read_excel(r'F:\Zohreh\MainZohreh\postdoc-field\CSU\Duplicat_Pure\data.xlsx',
>>>>>>>>>>>>  sheet_name='NaCl_exp')
>>>>>>>>>>>> XNa = df['XNa']
>>>>>>>>>>>> XCl = df['XCl']
>>>>>>>>>>>> Xwater = df['Xwater']
>>>>>>>>>>>> Y = df['gama_x']
>>>>>>>>>>>> L=['WwaterNaCl', 'UwaterNaCl', 'VwaterNaCl', 'XCl', 'XNa', 
>>>>>>>>>>>> 'Xwater', 'BNaCl']
>>>>>>>>>>>> for j in range(len(L)):
>>>>>>>>>>>>     locals()[L[j]] = sp.symbols(L[j])
>>>>>>>>>>>> expr = 
>>>>>>>>>>>> -0.0118343195266272*BNaCl*XCl*XNa*(-2*(9.19238815542512*sqrt(XNa) 
>>>>>>>>>>>> + 9.19238815542512*sqrt(XCl + XNa) + 
>>>>>>>>>>>> 1)*exp(-9.19238815542512*sqrt(XNa) - 9.19238815542512*sqrt(XCl + 
>>>>>>>>>>>> XNa)) + 2)/((XCl + XNa)*(sqrt(XNa) + sqrt(XCl + XNa))**2) + 
>>>>>>>>>>>> 0.00591715976331361*BNaCl*XCl*(-2*(9.19238815542512*sqrt(XNa) + 
>>>>>>>>>>>> 9.19238815542512*sqrt(XCl + XNa) + 
>>>>>>>>>>>> 1)*exp(-9.19238815542512*sqrt(XNa) - 9.19238815542512*sqrt(XCl + 
>>>>>>>>>>>> XNa)) + 2)/(sqrt(XNa) + sqrt(XCl + XNa))**2 + 
>>>>>>>>>>>> 0.00591715976331361*BNaCl*XNa*(-2*(9.19238815542512*sqrt(XNa) + 
>>>>>>>>>>>> 9.19238815542512*sqrt(XCl + XNa) + 
>>>>>>>>>>>> 1)*exp(-9.19238815542512*sqrt(XNa) - 9.19238815542512*sqrt(XCl + 
>>>>>>>>>>>> XNa)) + 2)/(sqrt(XNa) + sqrt(XCl + XNa))**2 - 
>>>>>>>>>>>> 1.0*Cl*WwaterNaCl*Xwater*(0.5*XCl + 0.5*XNa + 0.5)/XCl - 
>>>>>>>>>>>> 0.5*Cl*WwaterNaCl/XCl - 4.0*UwaterNaCl*XCl*XNa*Xwater + 
>>>>>>>>>>>> 2.0*UwaterNaCl*XCl*Xwater + 2.0*UwaterNaCl*XNa*Xwater - 
>>>>>>>>>>>> 4.0*UwaterNaCl*XNa - 6.0*VwaterNaCl*XCl*XNa*Xwater**2 - 
>>>>>>>>>>>> 4.0*VwaterNaCl*XCl*Xwater**2 + 2.0*VwaterNaCl*XNa*Xwater**2 - 
>>>>>>>>>>>> 1.0*WwaterNaCl*Xwater*(0.5*XCl + 0.5*XNa + 0.5) + 
>>>>>>>>>>>> 2.0*WwaterNaCl*Xwater - 0.5*WwaterNaCl - 
>>>>>>>>>>>> 1.45739430799067*(0.707106781186548*sqrt(XNa) + 
>>>>>>>>>>>> 0.707106781186548*sqrt(XCl + XNa))*(-XCl - XNa + 
>>>>>>>>>>>> 1)/(9.19238815542512*sqrt(XNa) + 9.19238815542512*sqrt(XCl + XNa) 
>>>>>>>>>>>> + 1) - 1.45739430799067*(0.707106781186548*sqrt(XNa) + 
>>>>>>>>>>>> 0.707106781186548*sqrt(XCl + XNa))*(-1.4142135623731*sqrt(XNa) - 
>>>>>>>>>>>> 1.4142135623731*sqrt(XCl + XNa) + 1)/(9.19238815542512*sqrt(XNa) + 
>>>>>>>>>>>> 9.19238815542512*sqrt(XCl + XNa) + 1) - 
>>>>>>>>>>>> 0.448429017843282*log(9.19238815542512*sqrt(XNa) + 
>>>>>>>>>>>> 9.19238815542512*sqrt(XCl + XNa) + 1)
>>>>>>>>>>>> model_func = sp.lambdify(L, expr )
>>>>>>>>>>>>
>>>>>>>>>>>> def f(param):
>>>>>>>>>>>>     BNaCl = param[0]
>>>>>>>>>>>>     UwaterNaCl = param[1]
>>>>>>>>>>>>     VwaterNaCl = param[2]
>>>>>>>>>>>>     WwaterNaCl = param[3]
>>>>>>>>>>>>     Y_est = model_func
>>>>>>>>>>>>     return np.sum((np.log(Y) - Y_est)**2)
>>>>>>>>>>>>
>>>>>>>>>>>>
>>>>>>>>>>>> bnds = [(1, np.inf), (0, 1), (0, 1), (-1, np.inf)]
>>>>>>>>>>>> x0 = (1, 0.01, 0.98, 1)
>>>>>>>>>>>> con = {"type": "eq", "fun": c}
>>>>>>>>>>>>
>>>>>>>>>>>> result = minimize(f, x0, bounds=bnds)
>>>>>>>>>>>>
>>>>>>>>>>>> print(result.fun)
>>>>>>>>>>>> print(result.message)
>>>>>>>>>>>> print(result.x[0], result.x[1], result.x[2], result.x[3])
>>>>>>>>>>>>
>>>>>>>>>>>> while I got :
>>>>>>>>>>>> NameError: name 'sqrt' is not defined
>>>>>>>>>>>>
>>>>>>>>>>>> Zohreh Karimzadeh
>>>>>>>>>>>> *https://www.researchgate.net/profile/Zohreh-Karimzadeh*
>>>>>>>>>>>> <https://www.researchgate.net/profile/Zohreh-Karimzadeh>
>>>>>>>>>>>> Skype Name 49a52224a8b6b38b
>>>>>>>>>>>> Twitter Account @zohrehkarimzad1
>>>>>>>>>>>> z.karimza...@gmail.com
>>>>>>>>>>>> +989102116325
>>>>>>>>>>>>
>>>>>>>>>>>> ((((((((((((((((Value Water)))))))))))))))
>>>>>>>>>>>>
>>>>>>>>>>>>
>>>>>>>>>>>> On Wed, Aug 17, 2022 at 7:46 PM Peter Stahlecker <
>>>>>>>>>>>> peter.stahlec...@gmail.com> wrote:
>>>>>>>>>>>>
>>>>>>>>>>>>> I use lambdify(....) a lot, but always like this:
>>>>>>>>>>>>>
>>>>>>>>>>>>> x = sympy.symbols('x')
>>>>>>>>>>>>> expr = symy.S(10.) * sympy.sqrt(x)
>>>>>>>>>>>>> expr_lam = sympy.lambdify([x], expr)
>>>>>>>>>>>>>
>>>>>>>>>>>>> a = expr_lam(10.)
>>>>>>>>>>>>>
>>>>>>>>>>>>> This seems to work for me.
>>>>>>>>>>>>>
>>>>>>>>>>>>> On Wed 17. Aug 2022 at 20:38, Zohreh Karimzadeh <
>>>>>>>>>>>>> z.karimza...@gmail.com> wrote:
>>>>>>>>>>>>>
>>>>>>>>>>>>>> Dear sympy group
>>>>>>>>>>>>>> Thanks for your sympy.
>>>>>>>>>>>>>>
>>>>>>>>>>>>>> I am working on a code, after creating my big expression
>>>>>>>>>>>>>> using sympy it includes sqrt.
>>>>>>>>>>>>>>
>>>>>>>>>>>>>> I need to lambdify my expression to make it consistent with
>>>>>>>>>>>>>> numpy and other suffs.
>>>>>>>>>>>>>>
>>>>>>>>>>>>>> expr =10 * sp.sqrt(sp.symbols('x'))
>>>>>>>>>>>>>>
>>>>>>>>>>>>>> model_func = sp.lambdify('x', expr)
>>>>>>>>>>>>>>
>>>>>>>>>>>>>> But I found my expression after lambdifying becomes
>>>>>>>>>>>>>> somethings like this:
>>>>>>>>>>>>>>
>>>>>>>>>>>>>> 10*sqrt(x)
>>>>>>>>>>>>>>
>>>>>>>>>>>>>> while I need :
>>>>>>>>>>>>>>
>>>>>>>>>>>>>> 10*numpy.sqrt(x)
>>>>>>>>>>>>>>
>>>>>>>>>>>>>> Could possibly let me know how get sqrt to work with numpy?
>>>>>>>>>>>>>>
>>>>>>>>>>>>>> Regards,
>>>>>>>>>>>>>>
>>>>>>>>>>>>>> Zohreh
>>>>>>>>>>>>>>
>>>>>>>>>>>>>>
>>>>>>>>>>>>>>
>>>>>>>>>>>>>>
>>>>>>>>>>>>>>
>>>>>>>>>>>>>> --
>>>>>>>>>>>>>> You received this message because you are subscribed to the
>>>>>>>>>>>>>> Google Groups "sympy" group.
>>>>>>>>>>>>>> To unsubscribe from this group and stop receiving emails from
>>>>>>>>>>>>>> it, send an email to sympy+unsubscr...@googlegroups.com.
>>>>>>>>>>>>>> To view this discussion on the web visit
>>>>>>>>>>>>>> https://groups.google.com/d/msgid/sympy/1f0b313f-31c5-402e-991e-142a556016f4n%40googlegroups.com
>>>>>>>>>>>>>> <https://groups.google.com/d/msgid/sympy/1f0b313f-31c5-402e-991e-142a556016f4n%40googlegroups.com?utm_medium=email&utm_source=footer>
>>>>>>>>>>>>>> .
>>>>>>>>>>>>>>
>>>>>>>>>>>>> --
>>>>>>>>>>>>> Best regards,
>>>>>>>>>>>>>
>>>>>>>>>>>>> Peter Stahlecker
>>>>>>>>>>>>>
>>>>>>>>>>>>> --
>>>>>>>>>>>>> You received this message because you are subscribed to the
>>>>>>>>>>>>> Google Groups "sympy" group.
>>>>>>>>>>>>> To unsubscribe from this group and stop receiving emails from
>>>>>>>>>>>>> it, send an email to sympy+unsubscr...@googlegroups.com.
>>>>>>>>>>>>> To view this discussion on the web visit
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>>>>>>>>>>>>> <https://groups.google.com/d/msgid/sympy/CABKqA0ZoGwsadsk4SWCbJVMbCDwXcO_gNGumJH00GAeEFod7Cw%40mail.gmail.com?utm_medium=email&utm_source=footer>
>>>>>>>>>>>>> .
>>>>>>>>>>>>>
>>>>>>>>>>>> --
>>>>>>>>>>>> You received this message because you are subscribed to the
>>>>>>>>>>>> Google Groups "sympy" group.
>>>>>>>>>>>> To unsubscribe from this group and stop receiving emails from
>>>>>>>>>>>> it, send an email to sympy+unsubscr...@googlegroups.com.
>>>>>>>>>>>> To view this discussion on the web visit
>>>>>>>>>>>> https://groups.google.com/d/msgid/sympy/CA%2B1XYLPRvXZ6jiJbUS_xpWNKqMuUH7Kt5evue%2BwKEwDMvGekBQ%40mail.gmail.com
>>>>>>>>>>>> <https://groups.google.com/d/msgid/sympy/CA%2B1XYLPRvXZ6jiJbUS_xpWNKqMuUH7Kt5evue%2BwKEwDMvGekBQ%40mail.gmail.com?utm_medium=email&utm_source=footer>
>>>>>>>>>>>> .
>>>>>>>>>>>
>>>>>>>>>>>
>>>>>>>>>>>> --
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>>>>>>>>>>> To unsubscribe from this group and stop receiving emails from
>>>>>>>>>>> it, send an email to sympy+unsubscr...@googlegroups.com.
>>>>>>>>>>> To view this discussion on the web visit
>>>>>>>>>>> https://groups.google.com/d/msgid/sympy/CAKgW%3D6JfUmU7Uu%2BSrcA1STxVvWWm7bGWE%3Dit8CTchksTC0Qk7g%40mail.gmail.com
>>>>>>>>>>> <https://groups.google.com/d/msgid/sympy/CAKgW%3D6JfUmU7Uu%2BSrcA1STxVvWWm7bGWE%3Dit8CTchksTC0Qk7g%40mail.gmail.com?utm_medium=email&utm_source=footer>
>>>>>>>>>>> .
>>>>>>>>>>>
>>>>>>>>>> --
>>>>>>>>>> You received this message because you are subscribed to the
>>>>>>>>>> Google Groups "sympy" group.
>>>>>>>>>> To unsubscribe from this group and stop receiving emails from it,
>>>>>>>>>> send an email to sympy+unsubscr...@googlegroups.com.
>>>>>>>>>> To view this discussion on the web visit
>>>>>>>>>> https://groups.google.com/d/msgid/sympy/CA%2B1XYLPiCR%3DS2Fac3FZtjMpspqB7BRKtYEi45BVWPjkizVbNvw%40mail.gmail.com
>>>>>>>>>> <https://groups.google.com/d/msgid/sympy/CA%2B1XYLPiCR%3DS2Fac3FZtjMpspqB7BRKtYEi45BVWPjkizVbNvw%40mail.gmail.com?utm_medium=email&utm_source=footer>
>>>>>>>>>> .
>>>>>>>>>>
>>>>>>>>> --
>>>>>>>>> Best regards,
>>>>>>>>>
>>>>>>>>> Peter Stahlecker
>>>>>>>>>
>>>>>>>>> --
>>>>>>>>> You received this message because you are subscribed to the Google
>>>>>>>>> Groups "sympy" group.
>>>>>>>>> To unsubscribe from this group and stop receiving emails from it,
>>>>>>>>> send an email to sympy+unsubscr...@googlegroups.com.
>>>>>>>>>
>>>>>>>> To view this discussion on the web visit
>>>>>>>>> https://groups.google.com/d/msgid/sympy/CABKqA0b%3DF0akMH4oyg5%2By9dGvgrf_vvVJTnVhVduMP1f%2Bp1pFw%40mail.gmail.com
>>>>>>>>> <https://groups.google.com/d/msgid/sympy/CABKqA0b%3DF0akMH4oyg5%2By9dGvgrf_vvVJTnVhVduMP1f%2Bp1pFw%40mail.gmail.com?utm_medium=email&utm_source=footer>
>>>>>>>>> .
>>>>>>>>>
>>>>>>>> --
>>>>>>>> You received this message because you are subscribed to the Google
>>>>>>>> Groups "sympy" group.
>>>>>>>> To unsubscribe from this group and stop receiving emails from it,
>>>>>>>> send an email to sympy+unsubscr...@googlegroups.com.
>>>>>>>> To view this discussion on the web visit
>>>>>>>> https://groups.google.com/d/msgid/sympy/CA%2B1XYLMK-fgpxc71GYzue5gJvd%3Dfj2sV6Dvhj8zrmVpPhiVk%2Bw%40mail.gmail.com
>>>>>>>> <https://groups.google.com/d/msgid/sympy/CA%2B1XYLMK-fgpxc71GYzue5gJvd%3Dfj2sV6Dvhj8zrmVpPhiVk%2Bw%40mail.gmail.com?utm_medium=email&utm_source=footer>
>>>>>>>> .
>>>>>>>>
>>>>>>> --
>>>>>>> Best regards,
>>>>>>>
>>>>>>> Peter Stahlecker
>>>>>>>
>>>>>>> --
>>>>>>> You received this message because you are subscribed to the Google
>>>>>>> Groups "sympy" group.
>>>>>>> To unsubscribe from this group and stop receiving emails from it,
>>>>>>> send an email to sympy+unsubscr...@googlegroups.com.
>>>>>>>
>>>>>> To view this discussion on the web visit
>>>>>>> https://groups.google.com/d/msgid/sympy/CABKqA0aBsD2WhpTuQqzZGUK1pfkUyH4q3Om9DdBQOpoaaO4rqQ%40mail.gmail.com
>>>>>>> <https://groups.google.com/d/msgid/sympy/CABKqA0aBsD2WhpTuQqzZGUK1pfkUyH4q3Om9DdBQOpoaaO4rqQ%40mail.gmail.com?utm_medium=email&utm_source=footer>
>>>>>>> .
>>>>>>>
>>>>>> --
>>>>>> You received this message because you are subscribed to the Google
>>>>>> Groups "sympy" group.
>>>>>> To unsubscribe from this group and stop receiving emails from it,
>>>>>> send an email to sympy+unsubscr...@googlegroups.com.
>>>>>> To view this discussion on the web visit
>>>>>> https://groups.google.com/d/msgid/sympy/CA%2B1XYLNiQNVa_hg25e-_f8xs%2B2w88p7JC4ntneBrqO4YFajTgA%40mail.gmail.com
>>>>>> <https://groups.google.com/d/msgid/sympy/CA%2B1XYLNiQNVa_hg25e-_f8xs%2B2w88p7JC4ntneBrqO4YFajTgA%40mail.gmail.com?utm_medium=email&utm_source=footer>
>>>>>> .
>>>>>>
>>>>> --
>>>>> Best regards,
>>>>>
>>>>> Peter Stahlecker
>>>>>
>>>>> --
>>>>> You received this message because you are subscribed to the Google
>>>>> Groups "sympy" group.
>>>>> To unsubscribe from this group and stop receiving emails from it, send
>>>>> an email to sympy+unsubscr...@googlegroups.com.
>>>>>
>>>> To view this discussion on the web visit
>>>>> https://groups.google.com/d/msgid/sympy/CABKqA0YedBPPLH73J6ScxkgNWN9_NCR-YvOcd7vpGX4SsGZj0g%40mail.gmail.com
>>>>> <https://groups.google.com/d/msgid/sympy/CABKqA0YedBPPLH73J6ScxkgNWN9_NCR-YvOcd7vpGX4SsGZj0g%40mail.gmail.com?utm_medium=email&utm_source=footer>
>>>>> .
>>>>>
>>>> --
>>>> You received this message because you are subscribed to the Google
>>>> Groups "sympy" group.
>>>> To unsubscribe from this group and stop receiving emails from it, send
>>>> an email to sympy+unsubscr...@googlegroups.com.
>>>> To view this discussion on the web visit
>>>> https://groups.google.com/d/msgid/sympy/CA%2B1XYLOkAu3fHK8Fm1eRoO8CQxkN70mnO%3DM7iNqeRg3bt44yZQ%40mail.gmail.com
>>>> <https://groups.google.com/d/msgid/sympy/CA%2B1XYLOkAu3fHK8Fm1eRoO8CQxkN70mnO%3DM7iNqeRg3bt44yZQ%40mail.gmail.com?utm_medium=email&utm_source=footer>
>>>> .
>>>>
>>> --
>>> Best regards,
>>>
>>> Peter Stahlecker
>>>
>>> --
>>> You received this message because you are subscribed to the Google
>>> Groups "sympy" group.
>>> To unsubscribe from this group and stop receiving emails from it, send
>>> an email to sympy+unsubscr...@googlegroups.com.
>>>
>> To view this discussion on the web visit
>>> https://groups.google.com/d/msgid/sympy/CABKqA0aeQ%3D47NmCUei%3DvtXwFyjs4dw%3DfZ%3DjQGqpJvsk68BRYHA%40mail.gmail.com
>>> <https://groups.google.com/d/msgid/sympy/CABKqA0aeQ%3D47NmCUei%3DvtXwFyjs4dw%3DfZ%3DjQGqpJvsk68BRYHA%40mail.gmail.com?utm_medium=email&utm_source=footer>
>>> .
>>>
>> --
>> You received this message because you are subscribed to the Google Groups
>> "sympy" group.
>> To unsubscribe from this group and stop receiving emails from it, send an
>> email to sympy+unsubscr...@googlegroups.com.
>> To view this discussion on the web visit
>> https://groups.google.com/d/msgid/sympy/CA%2B1XYLMg7bq4X3iedc0u_9nwiKHXrFd8GV1%3DdUt9n255dcwJxw%40mail.gmail.com
>> <https://groups.google.com/d/msgid/sympy/CA%2B1XYLMg7bq4X3iedc0u_9nwiKHXrFd8GV1%3DdUt9n255dcwJxw%40mail.gmail.com?utm_medium=email&utm_source=footer>
>> .
>>
> --
> Best regards,
>
> Peter Stahlecker
>
> --
> You received this message because you are subscribed to the Google Groups
> "sympy" group.
> To unsubscribe from this group and stop receiving emails from it, send an
> email to sympy+unsubscr...@googlegroups.com.
> To view this discussion on the web visit
> https://groups.google.com/d/msgid/sympy/CABKqA0a6gewUiwcUHfk%3DR2fQVkwGgkefwYN0ziJoAesjKaabRg%40mail.gmail.com
> <https://groups.google.com/d/msgid/sympy/CABKqA0a6gewUiwcUHfk%3DR2fQVkwGgkefwYN0ziJoAesjKaabRg%40mail.gmail.com?utm_medium=email&utm_source=footer>
> .
>

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