integrate cos(x)*cos(2x)*...*cos(mx) via SAGE - python

I'm going to find $I_m=\int_0^{2\pi} \prod_{k=1}^m cos(kx){}dx$, where $m=1,2,3\ldots$
Simple SAGE code:
x=var('x')
f = lambda m,x : prod([cos(k*x) for k in range(1,m+1)])
for m in range(1,15+1):
print m, numerical_integral(f(m,x), 0, 2*pi)[0],integrate(f(m,x),x,0,2*pi).n()
Output:
1 -1.47676658757e-16 0.000000000000000
2 -5.27735962315e-16 0.000000000000000
3 1.57079632679 1.57079632679490
4 0.785398163397 0.785398163397448
5 -2.60536121164e-16 0.000000000000000
6 -1.81559273097e-16 0.000000000000000
7 0.392699081699 0.392699081698724
8 0.343611696486 0.147262155637022
9 -1.72448482421e-16 0.294524311274043
10 -1.8747663502e-16 0.196349540849362
11 0.214757310304 0.312932080728671
12 0.190213617698 0.177941771394734
13 -1.30355375996e-16 0.208621387152447
14 -1.25168280013e-16 0.0859029241215959
15 0.138441766107 0.134223318939994
As you can see numerical answer is right, but result of integrate(...) is right for $m=1,2,\ldots,7$ and then there is some bug.
We can print indefinite integral:
for m in range(7,11+1):
print 'm=',m
print 'Indef_I_m=',integrate(f(m,x),x)
And Output:
m = 7
Indef_I_m = 1/16*x + 1/16*sin(2*x) + 1/32*sin(4*x) + 7/384*sin(6*x) +
7/512*sin(8*x) + 3/320*sin(10*x) + 5/768*sin(12*x) + 5/896*sin(14*x) +
1/256*sin(16*x) + 1/384*sin(18*x) + 1/640*sin(20*x) + 1/704*sin(22*x) +
1/1536*sin(24*x) + 1/1664*sin(26*x) + 1/1792*sin(28*x)
m = 8
Indef_I_m = 3/128*x + 5/256*sin(2*x) + 1/32*sin(3*x) + 5/512*sin(4*x) +
5/768*sin(6*x) + 1/256*sin(8*x) + 1/256*sin(10*x) + 1/256*sin(12*x) +
1/256*sin(14*x) + 1/256*sin(16*x) + 7/2304*sin(18*x) + 3/1280*sin(20*x)
+ 5/2816*sin(22*x) + 1/768*sin(24*x) + 3/3328*sin(26*x) +
1/1792*sin(28*x) + 1/1920*sin(30*x) + 1/4096*sin(32*x) +
1/4352*sin(34*x) + 1/4608*sin(36*x) + 3/32*sin(x)
m = 9
Indef_I_m = 3/64*x + 3/128*sin(2*x) + 23/768*sin(3*x) + 3/256*sin(4*x) +
3/640*sin(5*x) + 1/128*sin(6*x) + 5/1792*sin(7*x) + 5/2304*sin(9*x) +
3/2816*sin(11*x) + 1/832*sin(13*x) + 1/1280*sin(15*x) + 3/4352*sin(17*x)
+ 5/4864*sin(19*x) + 1/1344*sin(21*x) + 3/2944*sin(23*x) +
7/6400*sin(25*x) + 1/1152*sin(27*x) + 3/3712*sin(29*x) +
5/7936*sin(31*x) + 1/2112*sin(33*x) + 3/8960*sin(35*x) +
1/4736*sin(37*x) + 1/4992*sin(39*x) + 1/10496*sin(41*x) +
1/11008*sin(43*x) + 1/11520*sin(45*x) + 23/256*sin(x)
m = 10
Indef_I_m = 1/32*x + 1/64*sin(2*x) + 17/512*sin(3*x) + 1/128*sin(4*x) +
7/2560*sin(5*x) + 1/192*sin(6*x) + 3/1792*sin(7*x) + 1/1152*sin(9*x) +
5/5632*sin(11*x) + 3/6656*sin(13*x) + 1/2560*sin(15*x) +
5/8704*sin(17*x) + 3/9728*sin(19*x) + 1/2688*sin(21*x) +
1/2944*sin(23*x) + 1/6400*sin(25*x) + 1/4608*sin(27*x) +
3/14848*sin(29*x) + 3/15872*sin(31*x) + 5/16896*sin(33*x) +
3/8960*sin(35*x) + 3/9472*sin(37*x) + 1/3328*sin(39*x) +
5/20992*sin(41*x) + 1/5504*sin(43*x) + 1/7680*sin(45*x) +
1/12032*sin(47*x) + 1/12544*sin(49*x) + 1/26112*sin(51*x) +
1/27136*sin(53*x) + 1/28160*sin(55*x) + 13/128*sin(x)
m = 11
Indef_I_m = 51/1024*x + 53/2048*sin(2*x) + 13/768*sin(3*x) + 53/4096*sin(4*x) +
13/1536*sin(6*x) + 1/2048*sin(8*x) + 1/2560*sin(10*x) + 1/3072*sin(12*x)
+ 5/14336*sin(14*x) + 1/4096*sin(16*x) + 5/18432*sin(18*x) +
1/4096*sin(20*x) + 1/5632*sin(22*x) + 5/24576*sin(24*x) +
5/26624*sin(26*x) + 5/28672*sin(28*x) + 1/5120*sin(30*x) +
3/16384*sin(32*x) + 5/34816*sin(34*x) + 1/9216*sin(36*x) +
5/38912*sin(38*x) + 1/10240*sin(40*x) + 1/10752*sin(42*x) +
3/22528*sin(44*x) + 3/23552*sin(46*x) + 1/8192*sin(48*x) +
3/25600*sin(50*x) + 5/53248*sin(52*x) + 1/13824*sin(54*x) +
3/57344*sin(56*x) + 1/29696*sin(58*x) + 1/30720*sin(60*x) +
1/63488*sin(62*x) + 1/65536*sin(64*x) + 1/67584*sin(66*x) +
13/256*sin(x)
so for $m=7$ answer is right compare with Indef_I_7 via WolframAlpha
and for $m=8$ answer is incorrect Indef_I_8 via WolframAlpha
There should be Indef_I_8=$\frac{7x}{128}+\ldots$ and no $\sin(x)$, $\sin(3x)$ in summation, only $\sin(2k)$ for $k=1,2,3,\ldots 18$
Sorry for volumetric calculations !
The question is - Am I right that it is the bug in the symbolic integration?

Well, apparently setting algorithm='mathematica_free' solved the issue; this is probably a bug in the default algorithm used bye SAGE ('maxima').

So the answer is - Yes. It is a bug in algorithm='maxima', so use algorithm='mathematica_free' (def new function to find definite integral) or simplify_full() for such product of cos(kx) and than integrate.
f(8,x).simplify_full().integral(x,0,2pi) == 7/64pi and
(7/64*pi).n() == 0.343611696486384 is correct

Related

What transformation does `simplify` apply when both `powsimp` and `collect` do nothing?

I have the following expression and want to group it by powers of the variable e:
from sympy import symbols
e = symbols('e')
expr = (
0.363635891123757*e
+ 1.27444227529689*(0.006290933064*e + 0.526290933064)*(0.12408152*e + 0.12408152)
+ 2.76494336639746*(0.0483917928*e + 1.0483917928)*(0.12408152*e + 0.12408152)
+ 1.27444227529689*(0.12408152*e + 0.12408152)*(
0.012581866128*e
+ 0.39*(0.006290933064*e + 0.526290933064)*(0.12408152*e + 0.12408152)
+ 0.922581866128
)
+ 2.76494336639746*(0.12408152*e + 0.12408152)*(
0.0967835856*e
+ 0.39*(0.0483917928*e + 1.0483917928)*(0.12408152*e + 0.12408152)
+ 1.0967835856
)
+ 1.63807816642065
)
From their descriptions both powsimp and collect should work, however they return the expression unmodified. When I apply simplify then the expression gets simplified as expected. So I'm wondering what other type of transformation gets applied during the call to simplify?
from sympy.simplify import simplify, powsimp, collect
print(f'{powsimp(expr) = }')
print(f'{collect(expr, e) = }')
print(f'{simplify(expr) = }')
This produces the following output:
powsimp(expr) = 0.363635891123757*e + (0.0080174310478246*e + 0.670727414202207)*(0.12408152*e + 0.12408152) + (0.12408152*e + 0.12408152)*(0.13380056649044*e + 2.8987439328879) + (0.158134734671097*e + 0.158134734671097)*(0.012581866128*e + (0.00245346389496*e + 0.20525346389496)*(0.12408152*e + 0.12408152) + 0.922581866128) + (0.343078375616514*e + 0.343078375616514)*(0.0967835856*e + (0.018872799192*e + 0.408872799192)*(0.12408152*e + 0.12408152) + 1.0967835856) + 1.63807816642065
collect(expr, e) = 0.363635891123757*e + (0.0080174310478246*e + 0.670727414202207)*(0.12408152*e + 0.12408152) + (0.12408152*e + 0.12408152)*(0.13380056649044*e + 2.8987439328879) + (0.158134734671097*e + 0.158134734671097)*(0.012581866128*e + (0.00245346389496*e + 0.20525346389496)*(0.12408152*e + 0.12408152) + 0.922581866128) + (0.343078375616514*e + 0.343078375616514)*(0.0967835856*e + (0.018872799192*e + 0.408872799192)*(0.12408152*e + 0.12408152) + 1.0967835856) + 1.63807816642065
simplify(expr) = 0.000851550024540092*e**3 + 0.0759270659579648*e**2 + 1.42522479477876*e + 2.62459155414223
P.S.: For my use case, this expression is part of a larger expression which I cannot transform via simplify because I get the error described here.
$ conda list | grep sympy
sympy 1.8 py39hf3d152e_0 conda-forge
In general you need to use expand before collect although in this case expand is enough:
In [7]: expr.expand()
Out[7]:
3 2
0.000851550024540092⋅e + 0.0759270659579648⋅e + 1.42522479477876⋅e + 2.62459155414223

Infeasible solution by pulp [duplicate]

I'm trying to solve an assignment problem with pulp. The basic part of the code is as follows:
set_I = range(1, numberOfPoints)
set_J = range(1, numberOfCentroids)
tau = 0.15
Q = 15
# decision variable
x_vars = LpVariable.dicts(name="x_vars", indexs=(set_I, set_J), lowBound=0, upBound=1, cat=LpInteger)
# model name
prob = LpProblem("MIP_Model", LpMinimize)
# constraints
for i in set_I:
prob += lpSum(x_vars[i][j] for j in set_J) == 1, ""
for j in set_J:
prob += lpSum(x_vars[i][j] for i in set_I) >= 1, ""
for j in set_J:
prob += lpSum(x_vars[i][j] for i in set_I) <= Q*(1-tau), ""
for j in set_J:
prob += lpSum(x_vars[i][j] for i in set_I) >= Q*(1+tau), ""
# objective
prob += lpSum(d[i, j]*x_vars[i][j] for i in set_I for j in set_J)
prob.solve()
The result is like this:
Problem MODEL has 31 rows, 76 columns and 304 elements
Coin0008I MODEL read with 0 errors
Problem is infeasible - 0.01 seconds
Option for printingOptions changed from normal to all
However, the problem is not infeasible and results are obtained with other solvers.
I wonder if there is a syntax error and is the problem caused by this?
I have asked a similar question in the next link:
Infeasible solution by pulp
When I run the problem locally, with d a matrix of ones, 20 points, and 3 centroids. It also becomes infeasible for me. Look at the constraints:
_C22: x_vars_10_1 + x_vars_11_1 + x_vars_12_1 + x_vars_13_1 + x_vars_14_1
+ x_vars_15_1 + x_vars_16_1 + x_vars_17_1 + x_vars_18_1 + x_vars_19_1
+ x_vars_1_1 + x_vars_2_1 + x_vars_3_1 + x_vars_4_1 + x_vars_5_1 + x_vars_6_1
+ x_vars_7_1 + x_vars_8_1 + x_vars_9_1 <= 12.75
_C23: x_vars_10_2 + x_vars_11_2 + x_vars_12_2 + x_vars_13_2 + x_vars_14_2
+ x_vars_15_2 + x_vars_16_2 + x_vars_17_2 + x_vars_18_2 + x_vars_19_2
+ x_vars_1_2 + x_vars_2_2 + x_vars_3_2 + x_vars_4_2 + x_vars_5_2 + x_vars_6_2
+ x_vars_7_2 + x_vars_8_2 + x_vars_9_2 <= 12.75
_C24: x_vars_10_1 + x_vars_11_1 + x_vars_12_1 + x_vars_13_1 + x_vars_14_1
+ x_vars_15_1 + x_vars_16_1 + x_vars_17_1 + x_vars_18_1 + x_vars_19_1
+ x_vars_1_1 + x_vars_2_1 + x_vars_3_1 + x_vars_4_1 + x_vars_5_1 + x_vars_6_1
+ x_vars_7_1 + x_vars_8_1 + x_vars_9_1 >= 17.25
_C25: x_vars_10_2 + x_vars_11_2 + x_vars_12_2 + x_vars_13_2 + x_vars_14_2
+ x_vars_15_2 + x_vars_16_2 + x_vars_17_2 + x_vars_18_2 + x_vars_19_2
+ x_vars_1_2 + x_vars_2_2 + x_vars_3_2 + x_vars_4_2 + x_vars_5_2 + x_vars_6_2
+ x_vars_7_2 + x_vars_8_2 + x_vars_9_2 >= 17.25
You require
x_vars_10_2 + x_vars_11_2 + x_vars_12_2 + x_vars_13_2 + x_vars_14_2
+ x_vars_15_2 + x_vars_16_2 + x_vars_17_2 + x_vars_18_2 + x_vars_19_2
+ x_vars_1_2 + x_vars_2_2 + x_vars_3_2 + x_vars_4_2 + x_vars_5_2 + x_vars_6_2
+ x_vars_7_2 + x_vars_8_2 + x_vars_9_2
to be greater than 17.25 and smaller than 12.75 at the same time. That's not possible, of course.

How to convert symbolic expressions to float in Python?

Now i m trying to solve 6th order of nonlinear equations.
For solving this problem, 'fsolve' is the best module for my situation.
But i have a problem for using this 'fsolve'.
My Equations below : eq1, eq2, eq3, eq4, eq5, eq6
U = (E*h/32)*(pi**4*K3+8*pi**2*K4+16*J2-pi**4/b*K1**2-8*pi**2/b*K1*J1)+pi**2/2*D*((K1*K2)**0.5+(1-v)*K5-v*K6)+F/(4*b)*pi**2*K1
eq1 = diff(U,b_1)
eq2 = diff(U,b_2)
eq3 = diff(U,b_3)
eq4 = diff(U,b_4)
eq5 = diff(U,b_5)
eq6 = diff(U,b_6)
Now i m gonna try to define functions:
def functions(v):
b_1 = v[0]
b_2 = v[1]
b_3 = v[2]
b_4 = v[3]
b_5 = v[4]
b_6 = v[5]
return eq1,eq2,eq3,eq4,eq5,eq6
Until now, all of code is perfectly completed.
But next, I got a error code for 'fsolve'
x0 = [0.1,0.1,0.1,0.1,0.1,0.1]
solutions = fsolve(functions,x0)
Traceback (most recent call last):
File "C:\Users\user\AppData\Roaming\Python\Python37\site-packages\sympy\core\expr.py", line 327, in __float__
raise TypeError("can't convert expression to float")
TypeError: can't convert expression to float
Traceback (most recent call last):
File "C:\Users\user\Desktop\-----\trial.py", line 97, in <module>
solutions = fsolve(functions,x0)
File "C:\Users\user\anaconda3\lib\site-packages\scipy\optimize\minpack.py", line 147, in fsolve
res = _root_hybr(func, x0, args, jac=fprime, **options)
File "C:\Users\user\anaconda3\lib\site-packages\scipy\optimize\minpack.py", line 225, in _root_hybr
ml, mu, epsfcn, factor, diag)
error: Result from function call is not a proper array of floats.
Actually i don't know exactly meaning about 'array of floats'.
The eq1~eq6 is really complicated expressions. For example (eq1):
519749583.393768*b_1**3 + 519749583.393768*b_1**2*b_2 + 311849750.036261*b_1**2*b_3 + 222749821.454472*b_1**2*b_4 + 173249861.131256*b_1**2*b_5 + 141749886.380119*b_1**2*b_6 + 589049527.846271*b_1*b_2**2 + 920699262.011818*b_1*b_2*b_3 + 742499404.84824*b_1*b_2*b_4 + 619499503.439037*b_1*b_2*b_5 + 530653420.807624*b_1*b_2*b_6 + 395009683.379264*b_1*b_3**2 + 672299461.117134*b_1*b_3*b_4 + 581053380.409443*b_1*b_3*b_5 + 510299590.968427*b_1*b_3*b_6 + 296183828.527375*b_1*b_4**2 + 524699579.42609*b_1*b_4*b_5 + 469323153.224931*b_1*b_4*b_6 + 236661575.009363*b_1*b_5**2 + 429394392.660243*b_1*b_5*b_6 + 196977114.839905*b_1*b_6**2 + 39642.9110110422*b_1 + 193049845.260542*b_2**3 + 482129613.548124*b_2**2*b_3 + 406949673.808743*b_2**2*b_4 + 350618949.729969*b_2**2*b_5 + 307488215.070719*b_2**2*b_6 + 420149663.228267*b_2*b_3**2 + 732095017.5835*b_2*b_3*b_4 + 645437944.186494*b_2*b_3*b_5 + 575987321.121736*b_2*b_3*b_6 + 326318969.207663*b_2*b_4**2 + 585464236.60242*b_2*b_4*b_5 + 529609601.687166*b_2*b_4*b_6 + 266189415.118358*b_2*b_5**2 + 486862510.0121*b_2*b_5*b_6 + 224616040.694387*b_2*b_6**2 - 29192.3833775011*b_2 + 125272976.510293*b_3**3 + 334349732.001359*b_3**2*b_4 + 299655189.675087*b_3**2*b_5 + 270932940.727941*b_3**2*b_6 + 302393649.018531*b_3*b_4**2 + 549176644.826696*b_3*b_4*b_5 + 501838635.183477*b_3*b_4*b_6 + 252001834.206563*b_3*b_5**2 + 464613445.578031*b_3*b_5*b_6 + 215729827.081362*b_3*b_6**2 - 28558.195613361*b_3 + 92286363.2746599*b_4**3 + 253972873.350655*b_4**2*b_5 + 234063996.922265*b_4**2*b_6 + 234970783.525745*b_4*b_5**2 + 436229928.976872*b_4*b_5*b_6 + 203716223.26551*b_4*b_6**2 - 24903.5955817128*b_4 + 72968765.0411644*b_5**3 + 204424758.743579*b_5**2*b_6 + 191897759.069662*b_5*b_6**2 - 21706.6337724143*b_5 + 60314467.7838601*b_6**3 - 19178.52782655*b_6 + 52.9828871992195*((35.720610813872*b_2**2 + 142.882443255488*b_2*b_3 + 214.323664883232*b_2*b_4 + 285.764886510976*b_2*b_5 + 357.20610813872*b_2*b_6 + 257.188397859878*b_3**2 + 918.529992356708*b_3*b_4 + 1333.56947038455*b_3*b_5 + 1753.55725813553*b_3*b_6 + 893.0152703468*b_4**2 + 2727.7557348775*b_4*b_5 + 3709.44804605594*b_4*b_6 + 2154.22760600582*b_5**2 + 6001.0626167305*b_5*b_6 + 4254.9551116524*b_6**2)*(0.482*b_1**2 + 0.321333333333333*b_1*b_2 + 0.1928*b_1*b_3 + 0.137714285714286*b_1*b_4 + 0.107111111111111*b_1*b_5 + 0.0876363636363637*b_1*b_6 + 0.0964*b_2**2 + 0.137714285714286*b_2*b_3 + 0.107111111111111*b_2*b_4 + 0.0876363636363637*b_2*b_5 + 0.0741538461538462*b_2*b_6 + 0.0535555555555556*b_3**2 + 0.0876363636363637*b_3*b_4 + 0.0741538461538462*b_3*b_5 + 0.0642666666666667*b_3*b_6 + 0.0370769230769231*b_4**2 + 0.0642666666666667*b_4*b_5 + 0.0567058823529412*b_4*b_6 + 0.0283529411764706*b_5**2 + 0.0507368421052632*b_5*b_6 + 0.022952380952381*b_6**2))**0.5*(0.964*b_1 + 0.321333333333333*b_2 + 0.1928*b_3 + 0.137714285714286*b_4 + 0.107111111111111*b_5 + 0.0876363636363637*b_6)/(0.482*b_1**2 + 0.321333333333333*b_1*b_2 + 0.1928*b_1*b_3 + 0.137714285714286*b_1*b_4 + 0.107111111111111*b_1*b_5 + 0.0876363636363637*b_1*b_6 + 0.0964*b_2**2 + 0.137714285714286*b_2*b_3 + 0.107111111111111*b_2*b_4 + 0.0876363636363637*b_2*b_5 + 0.0741538461538462*b_2*b_6 + 0.0535555555555556*b_3**2 + 0.0876363636363637*b_3*b_4 + 0.0741538461538462*b_3*b_5 + 0.0642666666666667*b_3*b_6 + 0.0370769230769231*b_4**2 + 0.0642666666666667*b_4*b_5 + 0.0567058823529412*b_4*b_6 + 0.0283529411764706*b_5**2 + 0.0507368421052632*b_5*b_6 + 0.022952380952381*b_6**2) + (-1.28102213260338e-7*b_2 - 3.20255533150846e-8*b_3 - 3.20255533150846e-8*b_4 - 1.60127766575423e-8*b_6)*(0.482*b_1**2 + 0.321333333333333*b_1*b_2 + 0.1928*b_1*b_3 + 0.137714285714286*b_1*b_4 + 0.107111111111111*b_1*b_5 + 0.0876363636363637*b_1*b_6 + 0.0964*b_2**2 + 0.137714285714286*b_2*b_3 + 0.107111111111111*b_2*b_4 + 0.0876363636363637*b_2*b_5 + 0.0741538461538462*b_2*b_6 + 0.0535555555555556*b_3**2 + 0.0876363636363637*b_3*b_4 + 0.0741538461538462*b_3*b_5 + 0.0642666666666667*b_3*b_6 + 0.0370769230769231*b_4**2 + 0.0642666666666667*b_4*b_5 + 0.0567058823529412*b_4*b_6 + 0.0283529411764706*b_5**2 + 0.0507368421052632*b_5*b_6 + 0.022952380952381*b_6**2) + (1.18477228028269e-9*b_1 + 6.14508444130024e-10*b_2 + 4.60881333097518e-10*b_3 + 1.53627111032506e-10*b_4 + 1.53627111032506e-10*b_5)*(78.9568352087149*b_1**2 + 52.6378901391433*b_1*b_2 + 31.582734083486*b_1*b_3 + 22.5590957739185*b_1*b_4 + 17.5459633797144*b_1*b_5 + 14.3557882197663*b_1*b_6 + 15.791367041743*b_2**2 + 22.5590957739185*b_2*b_3 + 17.5459633797144*b_2*b_4 + 14.3557882197663*b_2*b_5 + 12.1472054167254*b_2*b_6 + 8.77298168985721*b_3**2 + 14.3557882197663*b_3*b_4 + 12.1472054167254*b_3*b_5 + 10.5275780278287*b_3*b_6 + 6.07360270836269*b_4**2 + 10.5275780278287*b_4*b_5 + 9.2890394363194*b_4*b_6 + 4.6445197181597*b_5**2 + 8.31124581144368*b_5*b_6 + 3.75984929565309*b_6**2) + (0.964*b_1 + 0.321333333333333*b_2 + 0.1928*b_3 + 0.137714285714286*b_4 + 0.107111111111111*b_5 + 0.0876363636363637*b_6)*(-1.28102213260338e-7*b_1*b_2 - 3.20255533150846e-8*b_1*b_3 - 3.20255533150846e-8*b_1*b_4 - 1.60127766575423e-8*b_1*b_6 - 1.60127766575423e-8*b_2**2 - 3.20255533150846e-8*b_2*b_3 - 1.60127766575423e-8*b_2*b_5 - 8.00638832877115e-9*b_3**2 + 1.60127766575423e-8*b_3*b_4 - 8.00638832877115e-9*b_3*b_6 - 8.00638832877115e-9*b_4*b_5 + 8.00638832877115e-9*b_4*b_6 + 4.00319416438558e-9*b_5**2 - 8.00638832877115e-9*b_5*b_6 + 4.00319416438558e-9*b_6**2 + 41123.3516712057) - 129937395.848442*(4*b_1 + 1.33333333333333*b_2 + 0.8*b_3 + 0.571428571428572*b_4 + 0.444444444444445*b_5 + 0.363636363636364*b_6)*(b_1**2 + 0.666666666666667*b_1*b_2 + 0.4*b_1*b_3 + 0.285714285714286*b_1*b_4 + 0.222222222222222*b_1*b_5 + 0.181818181818182*b_1*b_6 + 0.2*b_2**2 + 0.285714285714286*b_2*b_3 + 0.222222222222222*b_2*b_4 + 0.181818181818182*b_2*b_5 + 0.153846153846154*b_2*b_6 + 0.111111111111111*b_3**2 + 0.181818181818182*b_3*b_4 + 0.153846153846154*b_3*b_5 + 0.133333333333333*b_3*b_6 + 0.076923076923077*b_4**2 + 0.133333333333333*b_4*b_5 + 0.117647058823529*b_4*b_6 + 0.0588235294117647*b_5**2 + 0.105263157894737*b_5*b_6 + 0.0476190476190477*b_6**2) + (157.91367041743*b_1 + 52.6378901391433*b_2 + 31.582734083486*b_3 + 22.5590957739185*b_4 + 17.5459633797144*b_5 + 14.3557882197663*b_6)*(5.92386140141343e-10*b_1**2 + 6.14508444130024e-10*b_1*b_2 + 4.60881333097518e-10*b_1*b_3 + 1.53627111032506e-10*b_1*b_4 + 1.53627111032506e-10*b_1*b_5 + 2.30440666548759e-10*b_2**2 + 1.53627111032506e-10*b_2*b_3 + 1.53627111032506e-10*b_2*b_4 + 1.53627111032506e-10*b_2*b_6 + 7.6813555516253e-11*b_3**2 - 7.6813555516253e-11*b_3*b_4 + 7.6813555516253e-11*b_3*b_6 + 7.6813555516253e-11*b_4*b_5 + 7.6813555516253e-11*b_4*b_6 + 3.84067777581265e-11*b_5**2 - 251.041666666667)
I must solve such theses 6 equations.
But " Result from function call is not a proper array of floats. " error message comes out.
Is there anyone who help my code?
I'm Python beginning, so Plz understane me

Import equation from text file in Python

I have a complex equation which is generated into a .txt file. I would like to import this equation (which is all the text in the .txt file) and make a function from it, which can be subsequently fit.
Does anybody know how I might go about this? The equation to be fitted is at the the very bottom. My feeble attempt to import is below...
myfile1= open("dummyfile.txt", 'r')
def fcn(J1,J2,T,k,g):
return myfile1.read()
"dummyfile.txt" contents:
B**2*N*(12.0*g**2*sp.exp(2.0*J2/(T*k)) + 60.0*g**2*sp.exp(6.0*J2/(T*k)) + 168.0*g**2*sp.exp(12.0*J2/(T*k)) + 360.0*g**2*sp.exp(20.0*J2/(T*k)) + 30.0*g**2*sp.exp((2.0*J1 + 4.0*J2)/(T*k)) + 168.0*g**2*sp.exp((4.0*J1 + 8.0*J2)/(T*k)) + 360.0*g**2*sp.exp((6.0*J1 + 14.0*J2)/(T*k)) + 180.0*g**2*sp.exp((8.0*J1 + 12.0*J2)/(T*k)) + 660.0*g**2*sp.exp((8.0*J1 + 22.0*J2)/(T*k)) + 660.0*g**2*sp.exp((12.0*J1 + 18.0*J2)/(T*k)) + 1092.0*g**2*sp.exp((16.0*J1 + 26.0*J2)/(T*k)) + 546.0*g**2*sp.exp((18.0*J1 + 24.0*J2)/(T*k)) + 1680.0*g**2*sp.exp((24.0*J1 + 32.0*J2)/(T*k)) + 1224.0*g**2*sp.exp((32.0*J1 + 40.0*J2)/(T*k)))/(3*T*k*(6*sp.exp(2.0*J2/(T*k)) + 10*sp.exp(6.0*J2/(T*k)) + 14*sp.exp(12.0*J2/(T*k)) + 18*sp.exp(20.0*J2/(T*k)) + 5*sp.exp((2.0*J1 + 4.0*J2)/(T*k)) + 14*sp.exp((4.0*J1 + 8.0*J2)/(T*k)) + 18*sp.exp((6.0*J1 + 14.0*J2)/(T*k)) + 9*sp.exp((8.0*J1 + 12.0*J2)/(T*k)) + 22*sp.exp((8.0*J1 + 22.0*J2)/(T*k)) + 22*sp.exp((12.0*J1 + 18.0*J2)/(T*k)) + 26*sp.exp((16.0*J1 + 26.0*J2)/(T*k)) + 13*sp.exp((18.0*J1 + 24.0*J2)/(T*k)) + 30*sp.exp((24.0*J1 + 32.0*J2)/(T*k)) + 17*sp.exp((32.0*J1 + 40.0*J2)/(T*k)) + 1))
You can do that with exec().
Code:
def build_function(filename):
with open(filename, 'rU') as f:
eqn = f.read().strip()
exec("def fcn(J1, J2, T, k, g):\n return ({})".format(eqn))
return locals()['fcn']
Test Code:
fcn = build_function('file1')
print(fcn(1, 2, 3, 4, 5))
File1:
J2 + T*k
Results:
14

How to retrieve only those elements of list which matches user input? [closed]

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i need to take input from user and only that group of words should return to me where the input string occurs. For example if i search for people then only those group of words where people appears should be retrieved as output.
here is my sample output:
[(0, '0.897*"allah" + 0.120*"indeed" + 0.117*"lord" + 0.110*"said" + 0.101*"people" + 0.093*"upon" + 0.083*"shall" + 0.082*"unto" + 0.072*"believe" + 0.070*"earth"'), (1, '0.495*"lord" + 0.398*"said" + -0.377*"allah" + 0.252*"shall" + 0.241*"people" + 0.236*"unto" + 0.195*"indeed" + 0.131*"upon" + 0.117*"come" + 0.109*"thou"'), (2, '-0.682*"lord" + 0.497*"shall" + 0.350*"unto" + 0.125*"thee" + 0.125*"thou" + -0.098*"indeed" + -0.092*"said" + 0.092*"come" + 0.091*"people" + 0.080*"truth"'), (3, '-0.615*"shall" + 0.520*"people" + -0.395*"lord" + 0.259*"said" + 0.227*"indeed" + 0.103*"would" + 0.081*"sent" + 0.078*"among" + -0.059*"deeds" + -0.053*"good"'), (4, '0.675*"unto" + -0.425*"shall" + -0.335*"indeed" + 0.214*"thou" + 0.180*"thee" + 0.161*"lord" + -0.105*"said" + 0.099*"hath" + -0.075*"upon"'), (5, '-0.760*"said" + 0.356*"indeed" + 0.261*"upon" + 0.157*"would" + -0.130*"shall" + 0.109*"earth" + -0.108*"allah" + 0.105*"lord" + 0.100*"truth" + 0.096*"good"')
Here is my expected output:
[(0, '0.897*"allah" + 0.120*"indeed" + 0.117*"lord" + 0.110*"said" + 0.101*"people" + 0.093*"upon" + 0.083*"shall" + 0.082*"unto" + 0.072*"believe" + 0.070*"earth"'), (1, '0.495*"lord" + 0.398*"said" + -0.377*"allah" + 0.252*"shall" + 0.241*"people" + 0.236*"unto" + 0.195*"indeed" + 0.131*"upon" + 0.117*"come" + 0.109*"thou"'), (2, '-0.682*"lord" + 0.497*"shall" + 0.350*"unto" + 0.125*"thee" + 0.125*"thou" + -0.098*"indeed" + -0.092*"said" + 0.092*"come" + 0.091*"people" + 0.080*"truth"'), (3, '-0.615*"shall" + 0.520*"people" + -0.395*"lord" + 0.259*"said" + 0.227*"indeed" + 0.103*"would" + 0.081*"sent" + 0.078*"among" + -0.059*"deeds" + -0.053*"good"')]
Use a function with two parameter , one is your desired string and
second is your list :
Data is :
data=[(0,
'0.897*"allah" + 0.120*"indeed" + 0.117*"lord" + 0.110*"said" + 0.101*"people" + 0.093*"upon" + 0.083*"shall" + 0.082*"unto" + 0.072*"believe" + 0.070*"earth"'),
(1,
'0.495*"lord" + 0.398*"said" + -0.377*"allah" + 0.252*"shall" + 0.241*"people" + 0.236*"unto" + 0.195*"indeed" + 0.131*"upon" + 0.117*"come" + 0.109*"thou"'),
(2,
'-0.682*"lord" + 0.497*"shall" + 0.350*"unto" + 0.125*"thee" + 0.125*"thou" + -0.098*"indeed" + -0.092*"said" + 0.092*"come" + 0.091*"people" + 0.080*"truth"'),
(3,
'-0.615*"shall" + 0.520*"people" + -0.395*"lord" + 0.259*"said" + 0.227*"indeed" + 0.103*"would" + 0.081*"sent" + 0.078*"among" + -0.059*"deeds" + -0.053*"good"'),
(4,
'0.675*"unto" + -0.425*"shall" + -0.335*"indeed" + 0.214*"thou" + 0.180*"thee" + 0.161*"lord" + -0.105*"said" + 0.099*"hath" + -0.075*"upon"'),
(5,
'-0.760*"said" + 0.356*"indeed" + 0.261*"upon" + 0.157*"would" + -0.130*"shall" + 0.109*"earth" + -0.108*"allah" + 0.105*"lord" + 0.100*"truth" + 0.096*"good"')]
Detailed solution :
def search_strin(stri,list_1):
final_list=[]
for tup in list_1:
for item in tup:
if isinstance(item,str):
if stri in item:
final_list.append(tup)
return final_list
print(search_strin('people',data))
output:
Its returning only those group which have 'people' in string.
[(0, '0.897*"allah" + 0.120*"indeed" + 0.117*"lord" + 0.110*"said" + 0.101*"people" + 0.093*"upon" + 0.083*"shall" + 0.082*"unto" + 0.072*"believe" + 0.070*"earth"'), (1, '0.495*"lord" + 0.398*"said" + -0.377*"allah" + 0.252*"shall" + 0.241*"people" + 0.236*"unto" + 0.195*"indeed" + 0.131*"upon" + 0.117*"come" + 0.109*"thou"'), (2, '-0.682*"lord" + 0.497*"shall" + 0.350*"unto" + 0.125*"thee" + 0.125*"thou" + -0.098*"indeed" + -0.092*"said" + 0.092*"come" + 0.091*"people" + 0.080*"truth"'), (3, '-0.615*"shall" + 0.520*"people" + -0.395*"lord" + 0.259*"said" + 0.227*"indeed" + 0.103*"would" + 0.081*"sent" + 0.078*"among" + -0.059*"deeds" + -0.053*"good"')]
Just for fun one line solution if you want to try:
search='people'
print([tup for tup in data for item in tup if isinstance(item,str) if search in item])
As you commented you are getting empty list , You should check that you are passing correct list. You can check here live running code :

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