data:image/png;base64,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tekent een figuur op basis van een lijst punten waarbij de punten eventueel benadrukt worden

1zal het aantal punten van de schets aanpassen tot het gewenste aantal en die punten netjes verdelen over de volledige lengte

64laatstelast1past de schets aan zodat middelpunt op (0,0) ligt

geeft gemiddelde van lijst getallen, maar kan ook gebruikt voor gemiddelde van een puntenlijst!

Bepaalt de breedte van de schets door verschil te bepalen van maximale en minimale x-waarde. En past vervolgens de schets aan door alle punten te vermenigvuldigen met wensbreedte / breedte

200bepaalt de lengte van een schets door de lengtes van alle segmenten bij elkaar op te tellen

afstand tussen punten berekend met stelling van Pythagoras

de schets wordt geresampled, gecentereerd en naar de gewsnte breedte geschaald

64200

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