Collection of tools for programmation and modeling X
Project description
PMXUtils
Tools for ProgModX
Note that the package is in development and may undergo frequent updates
Install with python -m pip install pmxutils
for windows and python3 -m pip install pmxutils
for unix/linux
Table of content
Mathtools (pmxutils.mathtools
)
-
construct(expression, var=x)
Returns a function computing the given expression
expression
- The mathematical expression to compute, type = stringvar
- The variable used in the mathematical expression, defaults tp 'x', type = string
-
`advConstruct(expression, *args, constants = {})
Returns a function computing the given expression
expression
- The mathematical expression to compute, type = stringargs
- Any number of individual arguments naming the variables used in the expresion, type = stringconstants
- A dictionary with any numerical constants in the expression, type = dict
-
computeLists(function, low, high, step=1)
Returns a touple of two lists containing x values inbetween low and high, and the computed results for y. In the format of (x_list, y_list)
low
- The lower end of the function limit, type = numberhigh
- The upper end of the function limit, type = numberfunction
- The mathematical expression to use for y value computation, type = string or function from constructstep
- The step size in the x value list, defaults to '1', type = number
-
newton(function, derivative, low, high, tolerance=1e-8, rounding = 3, iterations = 1000)
Uses Newtons way of finding the root of a function, using the function and its derivative, within the given limits.Returns None if it can't find a solution that satisfies the tolerance after the defined number of terations
function
- The target mathematical expression, type = string or function from constructderivative
- The derivative of the target mathematical expression, type = string or function from constructlow
- The lower end of the are which should be checked for roots, type = numberhigh
- The upper end of the are which should be checked for roots, type = numbertolerance
- The tolerance for error to speed up computation, defaults to '1e-8', type = numberrounding
- Rounds the x value for the root to the specified amount of decimals, defaults to '3', type = numberiterations
- The number of tries, after which the function will end early
-
isInbetween(number, low, high)
Returns True if number is inbetween limOne and limTwo, returns False otherwise
number
- The number to be checked, type = numberlow
- The lower limit for which the number is checked, type = numberhigh
- The upper limit for which the number is checked, type = number
-
rectangleIntegral(function, low, high, n)
Returns the numerically calculated integral of the function f inbetween a and b using n rectangles
function
- The function to integrate, type = string or function from constructlow
- The low end of the area to be computed, type = numberhigh
- The high end of the area to be computed, type = numbern
- The number of rectangles to use, type = int
-
trapezoidIntegral(function, low, high, n)
Returns the numerically calculated integral of the function f inbetween a and b using n trapezoids
function
- The function to integrate, type = string or function from constructlow
- The low end of the area to be computed, type = numberhigh
- The high end of the area to be computed, type = numbern
- The number of trapezoids to use, type = int
-
simpsonIntegral(function, low, high, n)
Returns the numerically calculated integral of the function inbetween low and high using n quadratic splines
function
- The function to integrate, type = string or function from constructlow
- The low end of the area to be computed, type = numberhigh
- The high end of the area to be computed, type = numbern
- The number of quadratic splines to use, type = int
-
euler(functionDerivative, low, high, y0, n)
Returns a numpy array x, containing the x values of the function, and an array F, containing the computed values for the antiderivative function of the given function functionDerivative inbetween low and high with N steps
Only supports functions with one variable
functionDerivative
- The derivative of the goal function, type = string or function from constructlow
- The low end of the function to be computed, type = numberhigh
- The high end of the area to be computed, type = numbery0
- The initial value of the goal functionn
- The number of computations to perform
-
lemma(a, b)
Returns the greatest common denominator of a and b using the lemma algorithm
a
- The first numberb
- The second number
Other (pmxutils.other
)
-
profile(function)
Time profiler. Prints out the elapsed time during function execution
function
- The function to profile, type = function
loading()
Loading class
-
start(flavor="loading")
Starts a loading sequence
flavor
- The message to be displayed during loading, defaults to 'loading', type = string
-
stop()
Stops the loading sequence
-
animate()
DO NOT USE, internal function
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