g-equations 1.1.1

A little package for working with equations

g_equations

g_equations is my Python module for working with equations (some things are powered by NumPy)

Special thanks to Nastya for her helpful support ^^

Using Library

The library is in development so this section is updated together with library itself

Library connection

import g_equations
import g_equations.np_handler

Package Requirements: Some functions from g_equations.np_handler module require NumPy

Linear equation to dictionary

g_equations module has equ_to_dict(equation) function that gets an str object with human-like written liner equation and returnes a dictionary with variablies' coefficients

equ_dict = g_equations.equ_to_dict("x + 72.3y - 3z = 8.0")
print(equ_dict) # {'res': 8.0, 'x': 1.0, 'y': 72.3, 'z': -3.0}
equ_dict = g_equations.equ_to_dict("x + 72.3y - 3z - 6 = 8.0 - x")
print(equ_dict) # {'res': 14.0, 'x': 2.0, 'y': 72.3, 'z': -3.0}

String should have two parts with = between them. All variables are moved to the left side and free terms are moved to the right one
Returned dictionary will have right side value by "res" key and variablies' coefficients by their names

[!WARNING] The function works only with variables whose names consist of a single Latin alphabet character

Linear equation to matrixs

g_equations.np_handler has matrixs_from_dicts(dictionaries) function that gets a list of dictionaties (like in 'the section upper') with variablies' coefficients from a system of equations and returnes tuple with three entries: matrix of variablies' coefficients, matrix with right side values and tuple with order of variablies' names

[!NOTE] Matrix (not a numpy.matrix) is a list of lists with a rectangular shape
Like this: [ [a11,a12,a13], [a21,a22,a23], [a31,a32,a33] ]

Let's take a look at this system of equations:
$3x - y + 2z = -4;$
$x + 4y - z = 10;$
$2x + 3y + z = 8;$

Matrix can be got via matrixs_from_dicts(dictionaries) like this:

equ1 = {'res': -4.0, 'x': 3.0, 'y': -1.0, 'z': 2.0}
equ2 = {'res': 10.0, 'x': 1.0, 'y':  4.0, 'z': -1.0}
equ3 = {'res':  8.0, 'x': 2.0, 'y':  3.0, 'z': 1.0}
matrix_pair = g_equations.np_handler.matrixs_from_dicts([equ1,equ2,equ3])

There is also matrixs_from_equs(equations) function that gets a list of str objects with 'human-like written liner equations' and do the same things as matrixs_from_dicts(dictionaries)

matrix_pair = g_equations.np_handler.matrixs_from_equs([
    "3x - y + 2z = -4",
    "x + 4y - z = 10",
    "2x + 3y + z = 8"
])

Both matrix_pair look like:

matrix_pair[0]: [ [3.0,-1.0, 2.0],        matrix_pair[1]: [ [-4.0],        matrix_pair[2]: ('x','y','z')
                  [1.0, 4.0,-1.0],                          [10.0], 
                  [2.0, 3.0, 1.0] ]                         [ 8.0] ]      

Both functions have optional key-word argument add_values: bool (standart value is False). When it is True, function will place 0.0 value if dictionary/equality does not have coefficients for some variables to avoid 'Equations must have the same variables' exception

Solve system of linear equations

g_equations.np_handler has numpy_from_dicts(dictionaries) function that gets a list of dictionaties (like in 'the section upper') with variablies' coefficients from a system of equations and returnes dictionary with system's roots: roots' coefficients by names of their variables

Let's take a look at this system of equations:
$3x - y + 2z = -4;$
$x + 4y - z = 10;$
$2x + 3y + z = 8;$

Roots can be got via numpy_from_dicts(dictionaries) like this:

equ1 = {'res': -4.0, 'x': 3.0, 'y': -1.0, 'z': 2.0}
equ2 = {'res': 10.0, 'x': 1.0, 'y':  4.0, 'z': -1.0}
equ3 = {'res':  8.0, 'x': 2.0, 'y':  3.0, 'z': 1.0}
system_roots = g_equations.np_handler.numpy_from_dicts([equ1,equ2,equ3])

There is also numpy_from_equs(equations) function that gets a list of str objects with 'human-like written liner equations' and do the same things as numpy_from_dicts(dictionaries)

system_roots = g_equations.np_handler.numpy_from_equs([
    "3x - y + 2z = -4",
    "x + 4y - z = 10",
    "2x + 3y + z = 8"
])

Both system_roots look like:

{'x': 0.16666666666666607, 'y': 2.166666666666668, 'z': -1.166666666666666}

Both functions have optional key-word argument add_values: bool (standart value is False). It is used for internal 'matrixs_from_dicts' calling to avoid its 'Equations must have the same variables' exception

[!NOTE] There are shorter names for these two functions. roots_of_dicts for numpy_from_dicts and solve_equs for numpy_from_equs