I have a sympy expression I want to put numerical values in after differentiating it. The variables I want to replace are all the x[i], y[i] and R_abs[i] in the last expression and are numpy arrays a la
rx=np.array([-0.357, -0.742, -1.078, 0.206])
But trying subs or replace either doesn't do anything or raises the error that Symbols dont allow indexation for for example e1.subs(x[1],rx[0]). I pretty much went through every iteration I could think of to no avail.
import sympy as sp
r0,ge_x,ge_y,bx,by = sp.symbols('r0,ge_x,ge_y,bx,by', real=True) #Main symbols
i,x,y,R_abs = sp.symbols('i,x,y,R_abs', real=True) #Helper symbols
n=4
s2=sp.Sum((bx+r0*sp.Indexed('x',i)/sp.Indexed('R_abs',i)+ge_x*sp.Indexed('x',i)+ge_y*sp.Indexed('y',i)-sp.Indexed('x',i))**2+(by+r0*sp.Indexed('y',i)/sp.Indexed('R_abs',i)-ge_x*sp.Indexed('y',i)+ge_y*sp.Indexed('x',i)-sp.Indexed('y',i))**2,(i,1,n))
e1=sp.Eq(sp.diff(s2,bx).doit(),0)
With e1 then being
Eq(8*bx + 2*ge_x*x[1] + 2*ge_x*x[2] + 2*ge_x*x[3] + 2*ge_x*x[4] + 2*ge_y*y[1] + 2*ge_y*y[2] + 2*ge_y*y[3] + 2*ge_y*y[4] + 2*r0*x[4]/R_abs[4] + 2*r0*x[3]/R_abs[3] + 2*r0*x[2]/R_abs[2] + 2*r0*x[1]/R_abs[1] - 2*x[1] - 2*x[2] - 2*x[3] - 2*x[4], 0)
In here I would like to replace all the x, y, and R_abs with their numerical values.
I've always struggled with indexing in SymPy. Turns out, making Function instances are way easier than indexing instances of Symbol. It also makes notation simpler.
Also note that by using strings in your expression, I think SymPy makes its own symbols with those same string names but they can't be accessed with yours since your symbols are different. At least that's what happens sometimes to me.
Here is a working sample:
import sympy as sp
r0, ge_x, ge_y, bx, by = sp.symbols("r0 ge_x ge_y bx by", real=True) # main symbols
# define functions that will take the role of indexed symbols
x = sp.Function("x")
y = sp.Function("y")
R_abs = sp.Function("R_abs")
i = sp.Symbol("i", positive=True, integer=True)
n = 4
s2 = sp.Sum((bx + r0 * x(i) / R_abs(i) + ge_x * x(i) + ge_y * y(i) - x(i)) ** 2 +
(by + r0 * y(i) / R_abs(i) - ge_x * y(i) + ge_y * x(i) - y(i)) ** 2, (i, 1, n))
s2_prime = sp.diff(s2, bx).doit().simplify()
print(s2_prime)
# whatever lists you want. Can even be an instance of `np.ndarray`
# note that you summed from 1 to n so the 0th element will not be used
x_array = [0, 1, 2, 3, 4]
y_array = [4, 3, 2, 1, 0]
R_abs_array = [-10, 10, 5, 4, 3]
# define a function to access these array elements
x_function = lambda index: x_array[index]
y_function = lambda index: y_array[index]
R_abs_function = lambda index: R_abs_array[index]
# no idea why subs does not work and you MUST keep the same name for the variable.
# you can't have for example `evaluated_s2_prime = ...`.
# Probably something to do with forcing sp to remove references to `x`?
s2_prime = s2_prime.replace(x, x_function).replace(y, y_function).replace(R_abs, R_abs_function)
print(s2_prime)
Producing:
8*bx + 2*ge_x*x(1) + 2*ge_x*x(2) + 2*ge_x*x(3) + 2*ge_x*x(4) + 2*ge_y*y(1) + 2*ge_y*y(2) + 2*ge_y*y(3) + 2*ge_y*y(4) + 2*r0*x(4)/R_abs(4) + 2*r0*x(3)/R_abs(3) + 2*r0*x(2)/R_abs(2) + 2*r0*x(1)/R_abs(1) - 2*x(1) - 2*x(2) - 2*x(3) - 2*x(4)
8*bx + 20*ge_x + 12*ge_y + 31*r0/6 - 20
Related
Basically I have [5x5][5x1]=[0] and would like to have the symbolic expression of the solution.
Here is my code.
from sympy import symbols, solve
gm1, gm2, gm4 = symbols(['gm1', 'gm2', 'gm4'])
gds1, gds2, gds3, gds4, gds5 = symbols(['gds1', 'gds2', 'gds3', 'gds4', 'gds5'])
s = symbols(['s'])
Cd, CF , Cin, Ct = symbols(['Cd', 'CF', 'Cin', 'Ct'])
K = symbols(['K'])
vb, vc, ve, vout, iin = symbols(['vb', 'vc', 've', 'vout', 'iin'])
sol = solve([-(gds1+gds3+(s*Cd))*vb + (gm1+gds1)*ve + -gm1*vout, \
-gm4*vb + (gds4-gds2-(s*Cin)-(s*CF))*vc + (gds2+gm2)*ve + s*CF*vout + iin, \
gds1*vb + gds2*vc + (-(s*Ct)-gds5-gds1-gm1-gm2-gds2)*ve + gm1*vout, \
K*vc + vout], [vout])
print(sol)
but, I got this error
TypeError: can't multiply sequence by non-int of type 'Symbol'
From here, symbolic multiplication seems working just fine.
I am not sure whether I describe my problem in a way that does not comply with Sympy or something else.
What did I miss here?
The problem is in the assignment of the single symbols s and K. If instead you do:
s, K = symbols(['s', 'K'])
Or:
s = symbols('s')
K = symbols('K')
Whether you get the right answer or not is another matter :)
When you pass a list to symbols you get a list back. You can unpack that like [s] = symbols(['s']) or you can just pass a string of space or comma separated strings like x, y = symbols('x y') or x, y = symbols(','.join(['x', 'y']).
If you select manual=True you will get a solution vout=K*vc which sets the 4th equation to 0. But that was almost obvious, right? And you didn't need the other 3 equations to tell you that. So go ahead and pick up to 3 other variables for which you want to solve. There are lots of possibilities:
>>> from sympy.functions.combinatorial.numbers import nC
>>> allsym = Tuple(*eqs).free_symbols
>>> nfree = len(allsym) - 1 # always take vout
>>> print(nC(nfree, 3)) # want 3 others
816
For example, selecting (vout, gds4, gm1, gds5) gives a solution of
[{gds4: (CF*K*s*vc + CF*s*vc + Cin*s*vc + gds2*vc -
gds2*ve - gm2*ve + gm4*vb - iin)/vc,
gm1: (Cd*s*vb + gds1*vb - gds1*ve + gds3*vb)/(K*vc + ve),
gds5: -(Cd*s*vb + Ct*s*ve - gds2*vc + gds2*ve + gds3*vb + gm2*ve)/ve,
vout: -K*vc}]
I have an array of values x and y and have a function f(x,y). I want to get the value of f(x1,y1) corresponding to (x1,y1). How can we get it?
khmax = np.arange(0,0.5,0.001)
Ncmax = np.arange(0,0.5,0.001)
[X, Y] = np.meshgrid(Ncmax,khmax)
sum_real = 0
sum_imag = 0
for l in range (0,N): # C_jl * P_lj
sum_imag = sum_imag + (matrix_C[j_node-1][l])*(np.sin(Y*(x_j(l+1)-x_j(j_node)) / hmax))
sum_real = sum_real + (matrix_C[j_node-1][l])*(np.cos(Y*(x_j(l+1)-x_j(j_node)) / hmax))
Aj_real = (X * sum_real)
Aj_imag = (X * sum_imag)
G_imag = -Aj_imag + (2 * (Aj_real) * (Aj_imag)) / 2 - ((3 * ((Aj_real)**2) * (Aj_imag)) -((Aj_imag)**3)) + ((4*(Aj_real)*(Aj_imag))*((Aj_real)**2 - (Aj_imag)**2))/24
G_real = 1 - (Aj_real) + (((Aj_real)**2 - (Aj_imag)**2)/2) - ((((Aj_real)**3 - 3*(Aj_real)*((Aj_imag)**2)))/6) + ((((((Aj_real)**2 - (Aj_imag)**2 )**2- 4*((Aj_real)**2)*((Aj_imag)**2))))/ 24)
mod_G = (((G_real)**2) + ((G_imag)**2))**(0.5)
In this code mod_G is a function of (khmax, Ncmax). I want to get the value of mod_G corresponding to (khmax,Ncmax) suppose(0.1,0.1). I don't want to put the value of (khmax, Ncmax) into the function directly(i.e not replacing khmax with 0.1 and Ncmax with 0.1). How can I get mod_G without doing this?
Could you try defining it as an actual python function, i.e. using the def keyword and then calling it with the two parameters? This way you could just easily call it as mod_G(0.1,0.1) without changing anything else.
Using sympy, I need to replace all occurrence of exp(C+anything) with C*exp(anything). Because exp(C) is constant, I just write at as C.
I can do this for one occurrence of exp in the expression. But do not how to do it if there are than one instance.
For example, for one instance, as in x+exp(C_0+3*x)+3*y, I need to change it to x+C_0*exp(3*x)+3*y
For one instance, this seems to work after some trial and error
from sympy import *
x,y,C_0 = symbols('x y C_0')
expr=x+exp(C_0+3*x)+3*y
#first check if exp is in the expression
if any([isinstance(a, exp) for a in preorder_traversal(expr)]):
p_1=Wild('p1');p_2=Wild('p_2');p_3=Wild('p_3')
r=(p_1+exp(C_0+p_2)+p_3).matches(expr)
expr.subs(exp(C_0+r[p_2]),C_0*exp(r[p_2]))
Which gives
C_0*exp(3*x) + x + 3*y
But what about something like x+exp(C_0+3*x)+3*y+exp(C_0+30*x+y) which I need to change to x+C_0*exp(3*x)+3*y+C_0*exp(30*x+y) I can't make special pattern match for each possible case. I need a way to change all occurrences
In Mathematica, I do the above as follows
expr = x + Exp[c + 3*x]*3*y + 3*y + Exp[c + 30*x + y]
expr /. Exp[c + any_] :> (c Exp[any])
Which gives
I actually prefer to tell Python just to change exp(C+anything) to C*exp(anything) without having to give pattern for the overall expression, since that can change in many way.
I am sure the above is also possible in python/sympy. Any hints how to do it?
I would look for function exp inside of the expression, check whether its argument is Add, and then whether C_0 is among the arguments of Add. Then build a thing to replace exp with. Consider the following:
from sympy import *
x, y, C_0 = symbols('x y C_0')
expr = x + exp(C_0+3*x) + 3*y + exp(y+C_0+30*x) - exp(x+y-C_0) + exp(x*y)
exp_sum = [(a, a.args[0].args) for a in preorder_traversal(expr) if a.func == exp and a.args[0].func == Add]
exp_sum = [p for p in exp_sum if C_0 in p[1]]
new_exp = [C_0*exp(Add(*[x for x in p[1] if x != C_0])) for p in exp_sum]
for (old, new) in zip(exp_sum, new_exp):
expr = expr.subs(old[0], new)
Initially, exp_sum contains all parts of the form exp(Add(...)). After that it's filtered down to sums containing C_0. New exponentials are formed by taking all summands that are not C_0, adding them, applying exp and multiplying by C_0. Then substitution happens.
To clarify the process, here is what exp_sum is in the above example: a list of tuples (exponential and the summands inside):
[(exp(C_0 + 3*x), (C_0, 3*x)), (exp(C_0 + 30*x + y), (C_0, y, 30*x))]
And this is new_exp
[C_0*exp(3*x), C_0*exp(30*x + y)]
Finally, expr at the end:
C_0*exp(3*x) + C_0*exp(30*x + y) + x + 3*y + exp(x*y) - exp(-C_0 + x + y)
Notice that exp(-C_0...) is not affected by the change; it's not a part of the pattern.
When the following code is run Derivative(Ksi(uix, uiy), uix)) and Derivative(Ksi(uix, uiy), uiy)) terms appear:
In [4]: dgN
Out[4]:
Matrix([
[-(x1x - x2x)*(-x1y + x2y)*((x1x - x2x)**2 + (-x1y + x2y)**2)**(-0.5)*Derivative(Ksi(uix, uiy), uix) + (-x1y + x2y)*(-(-x1x + x2x)*Derivative(Ksi(uix, uiy), uix) + 1)*((x1x - x2x)**2 + (-x1y + x2y)**2)**(-0.5)],
[-(-x1x + x2x)*(-x1y + x2y)*((x1x - x2x)**2 + (-x1y + x2y)**2)**(-0.5)*Derivative(Ksi(uix, uiy), uiy) + (x1x - x2x)*(-(-x1y + x2y)*Derivative(Ksi(uix, uiy), uiy) + 1)*((x1x - x2x)**2 + (-x1y + x2y)**2)**(-0.5)]])
I would like to replace this Derivative terms by, let's say, the symbolic expression of the derivative of a function that I know for example, I would like to set Derivative(Ksi(uix,uiy), uix) = 2 * uix.
Is there a neat way to do this substitution and to get a symbolic expression for dgN with Derivative(Ksi(uix,uiy), uix) set to 2 * uix? Here is my code:
import sympy as sp
sp.var("kPenN, Xix, Xiy, uix, uiy, Alpha, x1x, x1y, x2x, x2y, x3x, x3y ", real = True)
Ksi = sp.Function('Ksi')(uix,uiy)
Xi = sp.Matrix([Xix, Xiy])
ui = sp.Matrix([uix, uiy])
xix = Xix + uix
xiy = Xiy + uiy
xi = sp.Matrix([xix, xiy])
x1 = sp.Matrix([x1x, x1y])
x2 = sp.Matrix([x2x, x2y])
N = sp.Matrix([x2 - x1, sp.zeros(1)]).cross(sp.Matrix([sp.zeros(2,1) , sp.ones(1)]))
N = sp.Matrix(2,1, sp.flatten(N[0:2]))
N = N / (N.dot(N))**(0.5)
xp = x1 + (x2 - x1)*Ksi
# make it scalar (in agreement with 9.231)
gN = (xi - xp).dot(N)
dgN = sp.Matrix([gN.diff(uix), gN.diff(uiy)])
The substitution you want can be achieved with
dgN_subbed = dgN.subs(sp.Derivative(Ksi, uix), 2*uix)
Here Ksi is without arguments (uix,uiy) since those were already declared when Ksi was created.
The syntax would be a little more intuitive if you defined Ksi as Ksi = sp.Function('Ksi'), leaving the arguments -- whatever they may be -- to be supplied later. Then sp.Derivative(Ksi(uix, uiy), uix) would be the way to reference the derivative.
In order to calculate derivatives and other expressions I used the sympy package and said that T = sy.Symbol('T') now that I have calculated the right expression:
E= -T**2*F_deriv_T(T,rho)
where
def F_deriv_rho(T,rho):
ret = 0
for n in range(5):
for m in range(4):
inner= c[n,m]*g_rho_deriv_rho_np*g_T_np
ret += inner
return ret
that looks like this:
F_deriv_rho: [0.0 7.76971e-5*T 0.0001553942*T**2*rho
T*(-5.14488e-5*log(rho) - 5.14488e-5)*log(T) + T*(1.22574e-5*log(rho)+1.22574e-5)*log(T) + T*(1.89488e-5*log(rho) + 1.89488e-5)*log(T) + T(2.29441e-5*log(rho) + 2.29441e-5)*log(T) + T*(7.49956e-5*log(rho) + 7.49956e-5)*log(T)
T**2*(-0.0001028976*rho*log(rho) - 5.14488e-5*rho)*log(T) + T**2*(2.45148e-5*rho*log(rho) + 1.22574e-5*rho)*log(T) + T**2*(3.78976e-5*rho*log(rho) + 1.89488e-5*rho)*log(T) + T**2*(4.58882e-5*rho*log(rho) + 2.29441e-5*rho)*log(T) + T**2*(0.0001499912*rho*log(rho) + 7.49956e 5*rho)*log(T)]
with python I would like to change T (and rho) as a symbol to a value. How could I do that?
So, I would like to create 10 numbers like T_def = np.arange(2000, 10000, 800)and exchange all my sy.symbol(T) by iterating through the 10 values I created in the array.
Thanks for your help
I have found the solution according to this post:
How to substitute multiple symbols in an expression in sympy?
by usings "subs":
>>> from sympy import Symbol
>>> x, y = Symbol('x y')
>>> f = x + y
>>> f.subs({x:10, y: 20})
>>> f
30
There's more for this kinda thing here: http://docs.sympy.org/latest/tutorial/basic_operations.html
EDIT: A faster way would be by using "lamdify" as suggested by #Bjoern Dahlgren