{ "cells": [ { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "import schemdraw\n", "from schemdraw import elements as elm" ] }, { "cell_type": "code", "execution_count": 123, "metadata": {}, "outputs": [ { "data": { "image/png": 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**kwargs)\n", "\n", " box = kwargs.get('box', True)\n", " boxfill = kwargs.get('boxfill', False)\n", " bpad = kwargs.get('boxpad', .2)\n", " label1, label2 = kwargs.get('label1'), kwargs.get('label2')\n", " rev1, rev2 = kwargs.get('reverse1', False), kwargs.get('reverse2', False)\n", "\n", " D1 = self.add(elm.Diode(d='down', reverse=rev1))\n", " D2 = self.add(elm.Diode(d='down', reverse=rev2, at=[2, 0]))\n", " if label1:\n", " self.segments.append(schemdraw.segments.SegmentText(D1.start + (0, 0.5), label1))\n", " if label2:\n", " self.segments.append(schemdraw.segments.SegmentText(D2.start + (0, 0.5), label2))\n", " \n", " self.add(elm.Arrow('r', at=[.6, -unit/2 + .2], l=.4, headwidth=.15, headlength=.4))\n", " self.add(elm.Arrow('r', at=[.6, -unit/2 - .2], l=.4, headwidth=.15, headlength=.4))\n", "\n", " bbox = self.get_bbox()\n", " if box:\n", " self.add(elm.Rect(\n", " 'r', at=[0, 0],\n", " corner1=[bbox.xmin-bpad, bbox.ymin-bpad],\n", " corner2=[bbox.xmax+bpad, bbox.ymax+bpad],\n", " fill=boxfill, zorder=0))\n", "\n", " A = self.add(elm.Line('r', at=D2.start, l=bpad*2))\n", " B = self.add(elm.Line('r', at=D2.end, l=bpad*2))\n", " C = self.add(elm.Line('l', at=D1.start, tox=bbox.xmin-bpad))\n", " D = self.add(elm.Line('l', at=D1.end, tox=bbox.xmin-bpad))\n", " self.anchors['anode1'] = C.end\n", " self.anchors['cathode1'] = D.end\n", " self.anchors['anode2'] = B.end\n", " self.anchors['cathode2'] = A.end\n", "DiodeOptocoupler(box=False, reverse2=True, label2='D2')" ] }, { "cell_type": "code", "execution_count": 177, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n" ], "text/plain": [ "" ] }, "execution_count": 177, "metadata": {}, "output_type": "execute_result" } ], "source": [ "d = schemdraw.Drawing()\n", "V1 = d.add(elm.SourceV(label='5V'))\n", "d.add(elm.Line(d='right', l=d.unit*2))\n", "d.add(elm.Resistor(d='down', label='R1'))\n", "coupler = d.add(DiodeOptocoupler(d='right', box=False, label1='D1', label2='D2', anchor='anode1', reverse2=True))\n", "d.here = coupler.cathode1\n", "Q1 = d.add(elm.BjtNpn(d='right', anchor='collector', label='Q1'))\n", "d.add(elm.Line(xy=Q1.emitter, d='down', l=d.unit*0.25))\n", "d.add(elm.Line(d='left', tox=V1.start))\n", "d.add(elm.Line(d='up', toy=V1.start))\n", "d.add(elm.Resistor(xy=Q1.base, d='left', label='R2'))\n", "d.add(elm.Dot(open=True, lftlabel='TX in'))\n", "\n", "d.add(elm.Line(xy=coupler.cathode2, d='up', toy=V1.end + d.unit*0.5))\n", "vbus = d.add(elm.Line(d='right', l=d.unit*5))\n", "\n", "d.add(elm.Line(xy=coupler.anode2, d='right', l=d.unit*0.5))\n", "j1 = d.add(elm.Dot())\n", "d.add(elm.Line(l=d.unit*0.5))\n", "amp1 = d.add(elm.Opamp(d='right', anchor='in1'))\n", "\n", "d.add(elm.Line(xy=j1.xy, d='up', l=d.unit))\n", "j2 = d.add(elm.Dot())\n", "\n", "d.add(elm.Resistor(label='R3', d='right'))\n", "d.add(elm.Line(l=d.unit*0.5))\n", "j3 = d.add(elm.Dot())\n", "d.add(elm.Line(d='down', toy=amp1.out))\n", "j4 = d.add(elm.Dot())\n", "d.add(elm.Line('left', tox=amp1.out))\n", "\n", "d.add(elm.Line('up', xy=j2.xy, l=d.unit*0.5))\n", "d.add(elm.Capacitor(label='C1', d='right'))\n", "d.add(elm.Line(tox=j3.xy))\n", "d.add(elm.Line(d='down', toy=j3.xy))\n", "\n", "d.add(elm.Line(d='left', xy=amp1.in2, l=d.unit*0.2))\n", "d.add(elm.Line(d='down', l=d.unit*0.5))\n", "vgnd_bus = d.add(elm.Line(d='right', l=d.unit*5))\n", "\n", "d.draw()" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.8.6" } }, "nbformat": 4, "nbformat_minor": 4 }