158 lines
3.6 KiB
Python
158 lines
3.6 KiB
Python
import matplotlib.pyplot as plt
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import matplotlib.ticker as mpt
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import matplotlib.cm as cm
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import numpy as np
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import wafer
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import VisTools.plotting as vtp
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import VisTools.tex as vtt
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plt.style.use('bmh')
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plt.rcParams['axes.facecolor'] = 'white'
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plt.figure(figsize=(8, 4))
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def gen_reg_theory():
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xdata = np.linspace(0, 150, 1001)
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# consts
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rpar = 75000
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rser = 9400
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r0 = 1.0029e-3
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r1 = 15.966e-3
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iret = 9.1
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plt.clf()
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plt.figure(figsize=(8, 4))
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for n, voff in enumerate([1.75, 1.8, 1.85, 1.9]):
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ydata = iret * r1 + r0 * xdata + voff
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ydata = (.7*30100 / (ydata - .7)) - 6490 - rser
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ydata = rpar * ydata / (rpar + ydata) * 256 / 10000
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plt.plot(
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[x for x, y in zip(xdata, ydata) if y >= 0],
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[y for y in ydata if y >= 0],
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color=f"C{n}",
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label=f"V$_{{off}}$ = {voff}"
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)
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plt.plot(
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xdata,
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ydata,
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color=f"C{n}",
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linestyle='dotted'
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)
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plt.legend()
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plt.xlabel("current (analog / digital) I / A")
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plt.ylabel("P$_{val}$")
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plt.savefig('reg.pdf')
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def gen_reticle_empty():
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plt.clf()
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w = wafer.WaferRepr()
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_, ax = plt.subplots()
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w.placeim(ax, (0, 0))
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ax.axis('off')
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ax.set_aspect("equal")
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plt.savefig('wafer.pdf', transparent=True)
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def gen_reticle_patterns():
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plt.clf()
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f, sax = plt.subplots(2, 2, figsize=(8, 6))
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sax = np.resize(sax, 4)
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patterns = [
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[0, 2, 8, 10, 12, 14, 25, 27, 29, 31, 41, 43],
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[1, 9, 11, 13, 24, 26, 28, 30, 32, 40, 42, 44],
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[3, 5, 7, 15, 17, 19, 21, 23, 34, 36, 38, 46],
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[4, 6, 16, 18, 20, 22, 33, 35, 37, 39, 45, 47]
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]
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for ax, p in zip(sax, patterns):
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w = wafer.WaferRepr()
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for r in p:
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w.set(r, .2)
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w.placeim(ax, (0, 0), cmap=cm.tab20c, nonumber=True)
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ax.set_ylim([-.6, 7.6])
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ax.set_xlim([-.6, 8.6])
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ax.set_aspect('equal')
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ax.axis('off')
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ax.invert_yaxis()
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plt.tight_layout()
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plt.savefig('wpattern.pdf')
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def gen_48v_theory():
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xdata = np.linspace(43, 53, 100)
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ydata = xdata / 241 * 8 * 1.1
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plt.clf()
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plt.plot(ydata, xdata)
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plt.xlabel('V$_{pin}$ / V')
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plt.ylabel('V$_{48V in}$ / V')
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plt.savefig('v48.pdf')
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def gen_48i_theory():
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xdata = np.linspace(0, 2000/48, 100)
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ydata = xdata * 500e-6 * 8 * 1.1
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plt.clf()
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plt.plot(ydata, xdata)
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plt.xlabel('V$_{pin}$ / V')
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plt.ylabel('I$_{48V in}$ / A')
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plt.savefig('i48.pdf')
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def gen_1v8_theory():
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rpara = 75000
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rseri = 2*4700
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xdata = np.arange(0, 256, 4, dtype=int)
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ydata = (xdata / 256 * 10000)
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ydata = ydata * rpara / (ydata + rpara) + rseri
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ydata = 30100 / (ydata + 6490) * .7 + .7
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plt.clf()
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plt.plot(xdata, ydata, label="Equation after Datasheet")
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vps = vtp.fit(
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xdata,
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ydata,
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lambda x, m, p, a, c: a/(m*x-p)+c, [.1, -1, 1, 1.5]
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)
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# plt.plot(xdata, vps[2].n / (vps[0].n * xdata - vps[1].n) + vps[3].n)
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vtt.unc_tolatex(vps[0], None, 'theo.tex', name="m")
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vtt.unc_tolatex(vps[1], None, 'theo.tex', name="p")
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vtt.unc_tolatex(vps[2], None, 'theo.tex', name="a")
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vtt.unc_tolatex(vps[3], None, 'theo.tex', name="c")
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plt.gca().xaxis.set_major_formatter(mpt.FuncFormatter(
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lambda v, x: '0x{:02x}'.format(int(v))
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))
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plt.xlabel("Potentiometer Setting P$_{val}$")
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plt.ylabel("V$_{MONITOR\_1V8}$ / V")
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plt.savefig('v18.pdf', transparent=True)
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if __name__ == "__main__":
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gen_48v_theory()
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gen_48i_theory()
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gen_1v8_theory()
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gen_reticle_empty()
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gen_reg_theory()
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gen_reticle_patterns()
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