The New Hotness

I’ll be giving an in-depth talk about my adventures restoring that old HP 7475A plotter for the Poughkeepsie ACM Chapter at Marist College this evening:

Superformula Plot - Composite D — Superformula Plot – Composite D

This being the Association for Computing Machinery, I will talk a bit about the Superformula that makes it all possible:

Gielis Superformula - parameters — Gielis Superformula – parameters

The presentation will look a lot like this: ACM – Plotting Like Its 1989. The PDF doesn’t include my patter, but perhaps the linky love on each screen can fill in the details.

If you’re following along, the Python source code running on the plotter as a GitHub Gist:

	from chiplotle import *
	from math import *
	from datetime import *
	from time import *
	from types import *
	import random


	def superformula_polar(a, b, m, n1, n2, n3, phi):
	''' Computes the position of the point on a
	superformula curve.
	Superformula has first been proposed by Johan Gielis
	and is a generalization of superellipse.
	see: http://en.wikipedia.org/wiki/Superformula
	Tweaked to return polar coordinates
	'''

	t1 = cos(m * phi / 4.0) / a
	t1 = abs(t1)
	t1 = pow(t1, n2)

	t2 = sin(m * phi / 4.0) / b
	t2 = abs(t2)
	t2 = pow(t2, n3)

	t3 = -1 / float(n1)
	r = pow(t1 + t2, t3)
	if abs(r) == 0:
	return (0, 0)
	else:
	# return (r * cos(phi), r * sin(phi))
	return (r, phi)


	def supershape(width, height, m, n1, n2, n3,
	point_count=10 * 1000, percentage=1.0, a=1.0, b=1.0, travel=None):
	'''Supershape, generated using the superformula first proposed
	by Johan Gielis.

	– `points_count` is the total number of points to compute.
	– `travel` is the length of the outline drawn in radians.
	3.1416 * 2 is a complete cycle.
	'''
	travel = travel or (10 * 2 * pi)

	# compute points…
	phis = [i * travel / point_count
	for i in range(1 + int(point_count * percentage))]
	points = [superformula_polar(a, b, m, n1, n2, n3, x) for x in phis]

	# scale and transpose…
	path = []
	for r, a in points:
	x = width * r * cos(a)
	y = height * r * sin(a)
	path.append(Coordinate(x, y))

	return Path(path)


	# RUN DEMO CODE

	if __name__ == '__main__':

	override = False

	plt = instantiate_plotters()[0]
	# plt.write('IN;')

	if plt.margins.soft.width < 11000: # A=10365 B=16640
	maxplotx = (plt.margins.soft.width / 2) – 100
	maxploty = (plt.margins.soft.height / 2) – 150
	legendx = maxplotx – 2900
	legendy = -(maxploty – 750)
	tscale = 0.45
	numpens = 4
	# prime/10 = number of spikes
	m_values = [n / 10.0 for n in [11, 13, 17, 19, 23]]
	# ring-ness 0.1 to 2.0, higher is larger
	n1_values = [
	n / 100.0 for n in range(55, 75, 2) + range(80, 120, 5) + range(120, 200, 10)]
	else:
	maxplotx = plt.margins.soft.width / 2
	maxploty = plt.margins.soft.height / 2
	legendx = maxplotx – 3000
	legendy = -(maxploty – 900)
	tscale = 0.45
	numpens = 6
	m_values = [n / 10.0 for n in [11, 13, 17, 19, 23, 29, 31,
	37, 41, 43, 47, 53, 59]] # prime/10 = number of spikes
	# ring-ness 0.1 to 2.0, higher is larger
	n1_values = [
	n / 100.0 for n in range(15, 75, 2) + range(80, 120, 5) + range(120, 200, 10)]

	print " Max: ({},{})".format(maxplotx, maxploty)

	# spiky-ness 0.1 to 2.0, higher is spiky-er (mostly)
	n2_values = [
	n / 100.0 for n in range(10, 60, 2) + range(65, 100, 5) + range(110, 200, 10)]

	plt.write(chr(27) + '.H200:') # set hardware handshake block size
	plt.set_origin_center()
	# scale based on B size characters
	plt.write(hpgl.SI(tscale * 0.285, tscale * 0.375))
	# slow speed for those abrupt spikes
	plt.write(hpgl.VS(10))

	while True:

	# standard loadout has pen 1 = fine black
	plt.write(hpgl.PA([(legendx, legendy)]))
	pen = 1
	plt.select_pen(pen)
	plt.write(hpgl.PA([(legendx, legendy)]))
	plt.write(hpgl.LB("Started " + str(datetime.today())))

	if override:
	m = 4.1
	n1_list = [1.15, 0.90, 0.25, 0.59, 0.51, 0.23]
	n2_list = [0.70, 0.58, 0.32, 0.28, 0.56, 0.26]
	else:
	m = random.choice(m_values)
	n1_list = random.sample(n1_values, numpens)
	n2_list = random.sample(n2_values, numpens)

	pen = 1
	for n1, n2 in zip(n1_list, n2_list):
	n3 = n2
	print "{0} – m: {1:.1f}, n1: {2:.2f}, n2=n3: {3:.2f}".format(pen, m, n1, n2)
	plt.select_pen(pen)
	plt.write(hpgl.PA([(legendx, legendy – 100 * pen)]))
	plt.write(
	hpgl.LB("Pen {0}: m={1:.1f} n1={2:.2f} n2=n3={3:.2f}".format(pen, m, n1, n2)))
	e = supershape(maxplotx, maxploty, m, n1, n2, n3)
	plt.write(e)
	pen = pen + 1 if (pen % numpens) else 1

	pen = 1
	plt.select_pen(pen)
	plt.write(hpgl.PA([(legendx, legendy – 100 * (numpens + 1))]))
	plt.write(hpgl.LB("Ended " + str(datetime.today())))
	plt.write(hpgl.PA([(legendx, legendy – 100 * (numpens + 2))]))
	plt.write(hpgl.LB("More at https://softsolder.com/?s=7475a"))
	plt.select_pen(0)
	plt.write(hpgl.PA([(-maxplotx,maxploty)]))

	print "Waiting for plotter… ignore timeout errors!"
	sleep(40)
	while NoneType is type(plt.status):
	sleep(5)

	print "Load more paper, then …"
	print " … Press ENTER on the plotter to continue"
	plt.clear_digitizer()
	plt.digitize_point()

	plotstatus = plt.status
	while (NoneType is type(plotstatus)) or (0 == int(plotstatus) & 0x04):
	plotstatus = plt.status

	print "Digitized: " + str(plt.digitized_point)

view raw PlotterShapes.py hosted with ❤ by GitHub

The New Hotness

Poughkeepsie ACM Chapter Presentation: Plotting Like It’s 1989!