from numpy import array, delete
# Function to create a smaller matrix by removing a specified row and column
def smaller_matrix(matrix, j):
new_matrix = matrix.copy()
new_matrix = delete(new_matrix, 0, 0)
new_matrix = delete(new_matrix, j, 1)
return new_matrix
# Function to calculate the determinant of a matrix using cofactor expansion
def determinant(matrix):
num_rows = len(matrix)
# Check if the matrix is square
for row in matrix:
if len(row) != num_rows:
print("\nNot a Square Matrix")
return None
# Base case: If the matrix is 1x1, return its only element
if num_rows == 1:
return matrix[0][0]
# Base case: If the matrix is 2x2, calculate the determinant using the formula
elif num_rows == 2:
base_determinant = matrix[0][0] * matrix[1][1] - matrix[1][0] * matrix[0][1]
return base_determinant
else:
# Recursive case: Use cofactor expansion for larger matrices
answer = 0
num_coloumns = num_rows
for j in range(num_coloumns):
cofactor = (-1) ** j * matrix[0][j] * determinant(smaller_matrix(matrix, j))
answer += cofactor
return answer
# Input equations manually
equation_1 = list(map(float, input("Enter coefficients of equation 1 separated by space: ").split()))
equation_2 = list(map(float, input("Enter coefficients of equation 2 separated by space: ").split()))
equation_3 = list(map(float, input("Enter coefficients of equation 3 separated by space: ").split()))
# Create coefficient matrix A and constant vector B
A = array([equation_1, equation_2, equation_3], float)
B = array(list(map(float, input("Enter constants on the right-hand side separated by space: ").split())), float)
# Number of equations
N = len(B)
# Calculate the determinant of the coefficient matrix
coeffMatrix = determinant(A)
# Check if the system has a unique solution
if abs(coeffMatrix) < 1e-12:
print("Two or More Equations are Coincident or Parallel")
raise SystemExit
# Initialize a list to store determinants for each variable
detMatrix = []
# Calculate determinants by replacing each column with the constant vector
for j in range(N):
C = A.copy()
C[:, j] = B
# Calculate determinant using the modified matrix
Dx = determinant(C)
detMatrix.append(Dx)
# Calculate the solution vector by dividing each determinant by the determinant of A
xMatrix = detMatrix / coeffMatrix
# Display the solution of the system
print("The Solution of the System:")
for i in range(N):
print(f'X[{i + 1}] = {round(xMatrix[i], 6)}')
Write, Run & Share Python code online using OneCompiler's Python online compiler for free. It's one of the robust, feature-rich online compilers for python language, supporting both the versions which are Python 3 and Python 2.7. Getting started with the OneCompiler's Python editor is easy and fast. The editor shows sample boilerplate code when you choose language as Python or Python2 and start coding.
OneCompiler's python online editor supports stdin and users can give inputs to programs using the STDIN textbox under the I/O tab. Following is a sample python program which takes name as input and print your name with hello.
import sys
name = sys.stdin.readline()
print("Hello "+ name)
Python is a very popular general-purpose programming language which was created by Guido van Rossum, and released in 1991. It is very popular for web development and you can build almost anything like mobile apps, web apps, tools, data analytics, machine learning etc. It is designed to be simple and easy like english language. It's is highly productive and efficient making it a very popular language.
When ever you want to perform a set of operations based on a condition IF-ELSE is used.
if conditional-expression
#code
elif conditional-expression
#code
else:
#code
Indentation is very important in Python, make sure the indentation is followed correctly
For loop is used to iterate over arrays(list, tuple, set, dictionary) or strings.
mylist=("Iphone","Pixel","Samsung")
for i in mylist:
print(i)
While is also used to iterate a set of statements based on a condition. Usually while is preferred when number of iterations are not known in advance.
while condition
#code
There are four types of collections in Python.
List is a collection which is ordered and can be changed. Lists are specified in square brackets.
mylist=["iPhone","Pixel","Samsung"]
print(mylist)
Tuple is a collection which is ordered and can not be changed. Tuples are specified in round brackets.
myTuple=("iPhone","Pixel","Samsung")
print(myTuple)
Below throws an error if you assign another value to tuple again.
myTuple=("iPhone","Pixel","Samsung")
print(myTuple)
myTuple[1]="onePlus"
print(myTuple)
Set is a collection which is unordered and unindexed. Sets are specified in curly brackets.
myset = {"iPhone","Pixel","Samsung"}
print(myset)
Dictionary is a collection of key value pairs which is unordered, can be changed, and indexed. They are written in curly brackets with key - value pairs.
mydict = {
"brand" :"iPhone",
"model": "iPhone 11"
}
print(mydict)
Following are the libraries supported by OneCompiler's Python compiler
| Name | Description |
|---|---|
| NumPy | NumPy python library helps users to work on arrays with ease |
| SciPy | SciPy is a scientific computation library which depends on NumPy for convenient and fast N-dimensional array manipulation |
| SKLearn/Scikit-learn | Scikit-learn or Scikit-learn is the most useful library for machine learning in Python |
| Pandas | Pandas is the most efficient Python library for data manipulation and analysis |
| DOcplex | DOcplex is IBM Decision Optimization CPLEX Modeling for Python, is a library composed of Mathematical Programming Modeling and Constraint Programming Modeling |