toolpath1 = [
"M3, 0, 0, 0",
`M3, ${thrishasValue}, 0, 0`,
`M3, 0, ${toolpathWidth}, 0`,
"M3, 0, 10, 0",
"M3, 0, 0, 0"
]
toolpath3 = [
`M3, 0, 0, ${depth}`,
`M3, ${thrishasValue}, 0, ${depth}`,
`M3, 0, ${toolpathWidth}, ${depth}`,
`M3, 0, 10, ${depth}`,
`M3, 0, 0, ${depth}`
]
xyVals = [
[0, 0],
[6, 0],
[0, 4],
[0, 10],
[0, 0]
]
depth = [0, 0.25, 0.5, 1.5]
thrishaArray = depth
.map((d, index) => {
return xyVals.map((xyPair) => {
return [xyPair[0], xyPair[1], d];
});
})
.flat()
hello = thrishaArray.map(
(triple) => `M3,${triple[0]}, ${triple[1]}, ${triple[2]}`
)
thrishasValue.value
instructionsToSend = hello
testInstructions = ["M3,5,0,,"]
Inputs.button("Dispatch SBP code", {
reduce: (_) => {
sendSbpCodesToMachine(testInstructions);
}
})
shelfThickness = 0.5
shopbotBedDims = ({
width: workPieceDim,
height: workPieceDim
})
import { VisualizationSpace, populateVizSpace } from "@machine-agency/minishelf"
import { sendSbpCodesToMachine } from "@machine-agency/quickdraw-sketch-based-milling"
VisualizationSpace
Review notebook how dispatching works- naviagate to machineAgency: collection -> imprimer -> connection
continue improve this notebook to cut a more interesting object,
Purpose-built for displays of data
Observable is your go-to platform for exploring data and creating expressive data visualizations. Use reactive JavaScript notebooks for prototyping and a collaborative canvas for visual data exploration and dashboard creation.
