Well, it’s actually not “sensing”, but the demo code now sizes the graph to the paper size reported by the plotter, so you can plot on cheap and readily available A-size paper. The Vulcan Nerve Pinch that switches paper size on the fly is `Enter+Size`

; I leave the DIP switches set for B-size sheets, because they’re more impressive and take longer to plot.

A collection of A-size plots:

The perspective foreshortening makes the sheets look square and the plots seem circular; they’re not.

The plots lie in rough time sequence from lower left to upper right, showing that I tweaked the `n1`

parameter to avoid the sort of tiny middle that gnawed a hole right through the center-bottom sheet. I also removed higher `m`

parameter values, because more than 50-ish points doesn’t work well on smaller sheets.

I figured out how to use the Python ternary “operator” and tweaked the print formatting, but basically it’s a hack job through & through.

The Python source code, including the hacked Chiplotle routines that produce the SuperFormula:

from chiplotle import * from math import * from datetime 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__': 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 - 2600 legendy = -(maxploty - 650) tscale = 0.45 numpens = 4 m_list = [n/10.0 for n in [11, 13, 17, 19, 23]]; # prime/10 = number of spikes n1_list = [n/100.0 for n in range(55,75,1) + range(80,120,5) + range(120,200,10)] # ring-ness 0.1 to 2.0, higher is larger else: maxplotx = plt.margins.soft.width / 2 maxploty = plt.margins.soft.height / 2 legendx = maxplotx - 3000 legendy = -(maxploty - 700) tscale = 0.45 numpens = 6 m_list = [n/10.0 for n in [11, 13, 17, 19, 23, 29, 31, 37, 41, 43, 47, 53, 59]]; # prime/10 = number of spikes n1_list = [n/100.0 for n in range(15,75,1) + range(80,120,5) + range(120,200,10)] # ring-ness 0.1 to 2.0, higher is larger print "Max: ({},{})".format(maxplotx,maxploty) n2_list = [n/100.0 for n in range(10,50,1) + range(55,100,5) + range(110,200,10)] # spike-ness 0.1 to 2.0, lower is spiky plt.write(chr(27) + '.H200:') # set hardware handshake block size plt.set_origin_center() plt.write(hpgl.SI(tscale*0.285,tscale*0.375)) # scale based on B size characters plt.write(hpgl.VS(10)) # slow speed for those abrupt spikes plt.select_pen(1) # standard loadout has pen 1 = black plt.write(hpgl.PA([(legendx,legendy)])) plt.write(hpgl.LB("Started " + str(datetime.today()))) m = random.choice(m_list) pen = 1 for n1, n2 in zip(random.sample(n1_list,numpens),random.sample(n2_list,numpens)): 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 plt.select_pen(1) plt.write(hpgl.PA([(legendx, legendy - 100*(numpens + 1))])) plt.write(hpgl.LB("Ended " + str(datetime.today()))) plt.select_pen(0)

I absolutely love it