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Let's point out a mistake first: you only have one element in list1, which should be taken out with list1[0];
I have been looking for a solution to this problem, but I have come up with a way to increase the variables of the equation to solve it: add a variable - expression = 0, and combine this equation with the result you got before to form a ternary system of equations, and get the solution of the new variable.
z=symbol('z')
result1=solve([z-list1[0],x-result[x],y-result[y]],x,y,z])
result1[z] is the result you want, take it away without thanks
If the solution of the unary equation (x) brings back the expression, the idea is the same, but note that the solution of the unary equation is stored in a list (let's say result) instead of a dictionary, and the first element in the list is a real solution, so ** becomes:
y=symbol('y')
result1=solve([y-list1[0],x-result[0],[x,y])
result1[y] is.
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I don't know where the problem is, the format is probably right, you change the single quotation marks to double quotation marks when defining the variable.
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Numerical integration.
The integrate() function under sympy is an analytic integral, and the knot result cannot be obtained when the integrand does not exist in the original function. Therefore, it is recommended to use the quad() numerical integration of the scipy library.
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Theoretically, Sympy's modules are to be installed by themselves, it is not a standard Python library, and it will not be installed when Python is installed.
If you want to check if you have this module in the machine you are using, if you are a Linux user, please open the terminal and enter Python, if you are a Windows user, open the cmd command line, type Python, and enter the Python interactive mode
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Hello, currently python has a sympy package. He provides a function for the calculation of integrals:
integrate(function, (variable, lower bound, upper bound)) so your integral calculation above can be as follows:
from sympy import *
x = symbols('x')
print(integrate(abs(x-a), x, b1, b2)))
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Python is very good and can meet most of the needs, such as data preprocessing, format conversion, etc. For these places where the computing resource requirements are not very high, pure python can be used. If you encounter pure Python that is difficult to deal with, you can mix C to speed up the efficiency, and there are many C-based Python libraries.
As a scripting language, the advantages of Python for rapid development have been said in other answers. Another reason why Python is suitable for data mining is that the community is now more mature, and more and more Python programs are published on Mloss. The most famous is it, which covers almost all the algorithms commonly used in machine learning.
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Let's say that the contents of the file are only one letter x
def readit(fname) as f:
return
s = readit('')
from sympy import *
x = symbol(s)
If you want to create a variable name with the same letters as the letter in the file, you can use the following statement: globals()[s] = symbol(s).
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65 shifts one place to the right, which is equivalent to 65 2
The result was 32
Which version of python? If 3 comes with pip, it should be fine, pip install pillow if it is 2, you can install the **pillow library installation package online.
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