Skip to main content

CAS tools for danish high schools.

Project description

GYM CAS

PyPI - Version PyPI - Python Version Coverage

Hjælpepakke til at bruge Python som CAS (Computational Algebra System) i gymnasiet.

Installation

pip install gym-cas

eller

py -m pip install gym-cas

Cheatsheet

I nedenstående afsnit antages det at gym_cas først importeres således:

from gym_cas import *

B1. Tal- og bogstavregning

expand( udtryk )
factor( udtryk )

B2. Ligninger og uligheder

solve( udtryk )
solve( [udtryk1, udtryk2] )
nsolve( udtryk, start )

Bemærk at den nemmeste måde at bruge solve i SymPy er ved at omforme sin ligning så en af siderne er lig 0. Hvis man fx vil løse ligningen x/2 = 10 så kan det skrives solve(x/2-10).

B3. Geometri og trigonometri

Sin( vinkel )
Cos( vinkel )
Tan( vinkel )
aSin( forhold )
aCos( forhold )
aTan( forhold )

B4. Analytisk plangeometri

plot_list( X_list ,Y_list, is_point=True)
plot( funktion )
plot_implicit( udtryk ,xlim=( x_min, x_max),ylim=( y_min, y_max))
plot_geometry( Geometrisk objekt )

Flere grafer i en afbildning

p1 = plot( udtryk1 )
p2 = plot( udtryk2 )
p = p1 + p2
p.show()

B5. Vektorer

a = Matrix([x,y])
a.dot(b)
plot_vector( vektor )
plot_vector( start, vektor )
plot_vector( [vektor1, vektor2, ...])

B6. Deskriptiv Statistik

Ugrupperet

max( data )
min( data )
mean( data )
median( data )
var( data, ddof )
std( data, ddof ) 
kvartiler( data )
percentile( data , procenter )
frequency( data )
boxplot( data ) 
plot_sum( data )

Grupperet

group_mean( data, grupper )
group_percentile( data, grupper, procenter )
group_var( data, grupper, ddof )
group_std( data, grupper, ddof ) 
frequency( data, grupper )
boxplot( data, grupper ) 
plot_sum( data, grupper )
plot_hist( data, grupper )

B8. Funktioner

def f(x):
    return funktionsudtryk
f(3)

def f(x):
    return Piecewise(( funktion1, betingelse1), (funktion2, betingelse2))

plot( funktion , yscale="log")
plot( funktion , (variabel, start, stop), xscale="log", yscale="log")
regression_poly(X,Y, grad)
regression_power(X,Y)
regression_exp(X,Y)

B9. Differentialregning

limit( udtryk, variabel, grænse, retning )
diff( funktion )
def df(xi):
    return diff( funktion ).subs( variabel, xi )

B10. Integralregning

integrate( udtryk )
integrate( udtryk, ( variabel, start, slut ))

A1. Vektorer i rummet

a = Matrix([1,2,3])
a.cross(b)
plot3d_list( X, Y, is_point=True)
plot_vector( a )
plot3d_line( a + t * r )
plot3d_plane( a + s * r1 + t * r2 )
plot3d_implicit( ligning, backend=PB ) # Kræver Plotly eller K3D

A4. Differentialligninger

f = Function('f')
dsolve( ode )
plot_ode( ode, f, (x, start, stop), (f, start, stop))

A5. Diskret Matematik

X = [ udregning for x in range(start,slut)]
X = [ startbetingelse ]
for i in range(start, slut):
    X.append( rekursionsligning )

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

gym_cas-0.2.6.tar.gz (36.7 kB view details)

Uploaded Source

Built Distribution

gym_cas-0.2.6-py3-none-any.whl (16.1 kB view details)

Uploaded Python 3

File details

Details for the file gym_cas-0.2.6.tar.gz.

File metadata

  • Download URL: gym_cas-0.2.6.tar.gz
  • Upload date:
  • Size: 36.7 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: python-httpx/0.25.2

File hashes

Hashes for gym_cas-0.2.6.tar.gz
Algorithm Hash digest
SHA256 bde57915339bc6369b8bf91c63245509d8ed41547963c03b30e4644e0ce26751
MD5 aef95db41dd722b4aed681e833af06b1
BLAKE2b-256 bec8b8be3fe478fd006abfe7ba374c36ce3404833be3c32e9106a2e4f1f8d1df

See more details on using hashes here.

File details

Details for the file gym_cas-0.2.6-py3-none-any.whl.

File metadata

  • Download URL: gym_cas-0.2.6-py3-none-any.whl
  • Upload date:
  • Size: 16.1 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: python-httpx/0.25.2

File hashes

Hashes for gym_cas-0.2.6-py3-none-any.whl
Algorithm Hash digest
SHA256 6eb261ef0c4a9b2c6091b68d96f1f823a96172bd02ece159c29e12c7ffc13492
MD5 bad4dffa4cb16c5ea91281da7824c3a0
BLAKE2b-256 d5e2c0c26f91e6a0841a04ce45c64d53c7fe113e7964e8b213be81181f2852e5

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page