From d65d4ac438e45145d22b7026b8d3a7016d3c2615 Mon Sep 17 00:00:00 2001 From: Xaseiresh Date: Fri, 3 May 2024 15:17:58 +0200 Subject: [PATCH] feat: :art: add auto-figure-generating code --- Images/Datavis/.gitignore | 1 + Images/Datavis/DataPlot.ipynb | 142 ++++++++++++++++++++++++ Images/Datavis/generate_plot.py | 185 ++++++++++++++++++++++++++++++++ Images/Datavis/plots.yml | 102 ++++++++++++++++++ 4 files changed, 430 insertions(+) create mode 100644 Images/Datavis/.gitignore create mode 100644 Images/Datavis/DataPlot.ipynb create mode 100644 Images/Datavis/generate_plot.py create mode 100644 Images/Datavis/plots.yml diff --git a/Images/Datavis/.gitignore b/Images/Datavis/.gitignore new file mode 100644 index 0000000..aab52d9 --- /dev/null +++ b/Images/Datavis/.gitignore @@ -0,0 +1 @@ +*.png \ No newline at end of file diff --git a/Images/Datavis/DataPlot.ipynb b/Images/Datavis/DataPlot.ipynb new file mode 100644 index 0000000..f4868c3 --- /dev/null +++ b/Images/Datavis/DataPlot.ipynb @@ -0,0 +1,142 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 11, + "id": "3a714fd6-1ce2-49ec-8f34-5731788af32b", + "metadata": {}, + "outputs": [], + "source": [ + "import io\n", + "import re\n", + "\n", + "import numpy as np\n", + "import matplotlib.pyplot as plt\n", + "\n", + "class Re(object):\n", + " def __init__(self):\n", + " self.last_match = None\n", + " def match(self,pattern,text):\n", + " self.last_match = re.match(pattern,text)\n", + " return self.last_match\n", + " def search(self,pattern,text):\n", + " self.last_match = re.search(pattern,text)\n", + " return self.last_match" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "id": "a2e3aae8-3742-467d-8271-d2fe36afe84a", + "metadata": {}, + "outputs": [], + "source": [ + "INPUT_FILE = \"Parasitics/SingleStage_Cfp_Sweep.txt\"\n", + "\n", + "lines = [];\n", + "sweeps = dict();\n", + "current_step = None;\n", + "\n", + "def setup_sweep(key):\n", + " global sweeps;\n", + "\n", + " if(key in sweeps):\n", + " return;\n", + " \n", + " sweeps[key] = {\n", + " \"sweep\" : key\n", + " };\n", + "\n", + "\n", + "with io.open(INPUT_FILE, mode=\"r\", encoding=\"ISO8859\") as file:\n", + " header = file.readline();\n", + " lines = header.rstrip(\"\\n\").split(\"\\t\");\n", + " \n", + " for line in file:\n", + " line = line.rstrip(\"\\n\");\n", + " lre = Re();\n", + " \n", + " if lre.search(\"^Freq\", line):\n", + " next;\n", + " elif lre.search(\"^Step Information: (.*) \\(Step: .*\\)$\", line):\n", + " current_sweep = lre.last_match[1];\n", + " else:\n", + " setup_sweep(current_sweep);\n", + " sweep = sweeps[current_sweep];\n", + " \n", + " elements = line.split(\"\\t\");\n", + " for idx, element in enumerate(elements):\n", + " lname = lines[idx];\n", + " ere = Re();\n", + " if ere.search(\"^([\\d\\.e\\+-]+)$\", element):\n", + " if(not lname in sweep):\n", + " sweep[lname] = []\n", + " sweep[lname].append(float(ere.last_match[1]));\n", + " elif ere.search(\"^\\(([\\d\\.e\\+-]+)dB,([\\d\\.e\\+-]+)\", element):\n", + " if(not (lname+\" dB\") in sweep):\n", + " sweep[lname+\" dB\"] = []\n", + " sweep[lname+\" deg\"] = []\n", + " sweep[lname+\" dB\"].append(float(ere.last_match[1]));\n", + " sweep[lname+\" deg\"].append(float(ere.last_match[2]));\n", + " else:\n", + " raise RuntimeError(\"Unknown/Not configured parsing element!\");" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "id": "836be81c-901b-4d8f-87f5-e3f996fcf088", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "for sweep_key in sweeps.keys():\n", + " plt.semilogx(sweeps[sweep_key]['Freq.'], sweeps[sweep_key]['V(n002) dB']);\n", + "\n", + "plt.grid(True);\n", + "plt.xlabel(\"Frequency (in Hz)\");\n", + "plt.ylabel(\"Amplification (in dB)\");\n", + "plt.title(\"Frequency response of varied Rf values\");" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "f0b2b7e1-6163-4756-81fc-54120e5f68d1", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "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": "3.9.2" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/Images/Datavis/generate_plot.py b/Images/Datavis/generate_plot.py new file mode 100644 index 0000000..8bbb4a4 --- /dev/null +++ b/Images/Datavis/generate_plot.py @@ -0,0 +1,185 @@ + +import sys +import io +import re + +import yaml + +import numpy as np +import matplotlib +import matplotlib.pyplot as plt +from matplotlib.ticker import EngFormatter + +import colorsys + +import os +SCRIPT_DIR = os.path.dirname(os.path.realpath(__file__)) + +class Re(object): + def __init__(self): + self.last_match = None + def match(self,pattern,text): + self.last_match = re.match(pattern,text) + return self.last_match + def search(self,pattern,text): + self.last_match = re.search(pattern,text) + return self.last_match + + +def setup_step(plot_data, key): + if(key == None): + key = "default"; + + if(key in plot_data): + return; + + next_step = { + "step" : key + }; + + plot_data[key] = next_step; + plot_data['steps'].append(next_step); + +def read_ltspice_file(filename): + print(f"Reading LTSpice .txt file {filename}..."); + + series = []; + plot_data = { + 'steps': [] + }; + current_step = None; + + with io.open(filename, mode="r", encoding="ISO8859") as file: + header = file.readline(); + lines = header.rstrip("\n").split("\t"); + + for line in file: + line = line.rstrip("\n"); + lre = Re(); + + if lre.search("^Step Information: (.*) \(Step: .*\)$", line): + current_step = lre.last_match[1]; + else: + setup_step(plot_data, current_step); + step = plot_data[current_step]; + + elements = line.split("\t"); + for idx, element in enumerate(elements): + lname = lines[idx]; + ere = Re(); + if ere.search("^([\d\.e\+-]+)$", element): + if(not lname in step): + step[lname] = [] + step[lname].append(float(ere.last_match[1])); + elif ere.search("^\(([\d\.e\+-]+)dB,([\d\.e\+-]+)", element): + if(not (lname+" dB") in step): + step[lname+" dB"] = [] + step[lname+" deg"] = [] + step[lname+" dB"].append(float(ere.last_match[1])); + step[lname+" deg"].append(float(ere.last_match[2])); + else: + raise RuntimeError("Unknown/Not configured parsing element!"); + + return plot_data; + +def decorate_ax(ax, plot_config): + ax.set_title(plot_config['title']); + + ax.set_xlabel(plot_config['xlabel']); + ax.set_ylabel(plot_config['ylabel']); + + if('yscale' in plot_config): + ax.set_yscale(plot_config['yscale']); + if('xscale' in plot_config): + ax.set_xscale(plot_config['xscale']); + + if('xformatter' in plot_config): + if('engineering' == plot_config['xformatter']): + formatter = EngFormatter(places=plot_config.get('xplaces', 0), sep="\N{THIN SPACE}") + ax.xaxis.set_major_formatter(formatter) + + if('yformatter' in plot_config): + if('engineering' == plot_config['yformatter']): + formatter = EngFormatter(places=plot_config.get('yplaces', 0)) + ax.yaxis.set_major_formatter(formatter) + + ax.grid(True); + +def plot_lt_sweep(fig, plot_config, plot_data): + step_keys = plot_data.keys(); + + ax = fig.add_subplot(); + ax.set_xscale('log'); + + x_key = "Freq."; + if("x_key" in plot_config): + x_key = plot_config['x_key']; + + y_key = None; + if('y_key' in plot_config): + y_key = plot_config['y_key']; + + if(y_key == None): + raise RuntimeError("No Y-Data Key (`y_key`) specified for plot!"); + + num_steps = len(plot_data['steps']); + cmap = plt.cm.coolwarm; + + custom_lines = [matplotlib.lines.Line2D([0], [0], color=cmap(0.), lw=4), + matplotlib.lines.Line2D([0], [0], color=cmap(.5), lw=4), + matplotlib.lines.Line2D([0], [0], color=cmap(1.), lw=4)]; + + for idx, step in enumerate(plot_data['steps']): + ax.plot(step[x_key], step[y_key], color=cmap(idx/(num_steps-1))); + + if(not 'xformatter' in plot_config): + plot_config['xformatter'] = 'engineering'; + + legend_data = []; + for x in [0, int(num_steps/2), num_steps-1]: + step_name = plot_data['steps'][x]['step']; + for orig, replacement in plot_config.get('legend_replace', dict()).items(): + step_name = step_name.replace(orig, replacement); + + legend_data.append(step_name); + + ax.legend(custom_lines, legend_data); + + decorate_ax(ax, plot_config); + +def generate_plot(plot_config): + global YAML_DIR; + + plot_data = None; + if("load" in plot_config): + if(not "loadtype" in plot_config): + raise RuntimeError("Missing load type (`loadtype`) for plot config"); + + if(plot_config['loadtype'] == 'ltspice'): + plot_data = read_ltspice_file(os.path.join(YAML_DIR, plot_config['load'])); + + fig = plt.figure(); + + if(plot_config['type'] == 'lt_sweep'): + plot_lt_sweep(fig, plot_config, plot_data); + + fig.subplots_adjust(0.15, 0.12, 0.96, 0.9) + + fig.savefig(os.path.join(YAML_DIR, plot_config['ofile']), dpi=plot_config.get('dpi', 300)); + + + +INPUT_YAML_FILE = SCRIPT_DIR + "/plots.yml" if (len(sys.argv) <= 1) else sys.argv[1]; +YAML_DIR = os.path.dirname(INPUT_YAML_FILE); +PLOT_CONFIG = None; + +print(f"Reading YAML config {INPUT_YAML_FILE}"); + +with open(INPUT_YAML_FILE, "r") as file: + PLOT_CONFIG = yaml.load(file, yaml.Loader); + + +for plot in PLOT_CONFIG['plots']: + plot = {**PLOT_CONFIG['defaults'], **plot}; + + generate_plot(plot); \ No newline at end of file diff --git a/Images/Datavis/plots.yml b/Images/Datavis/plots.yml new file mode 100644 index 0000000..0a5ccf1 --- /dev/null +++ b/Images/Datavis/plots.yml @@ -0,0 +1,102 @@ +defaults: + xlabel: Frequenz (Hz) + legend_replace: + Rf: $R_f$ + Cfp: $C_{fp}$ + Gbwp: GBWP + Cin: $C_{in}$ + +plots: + - load: Parasitics/SingleStage_Cfp_Sweep.txt + loadtype: ltspice + + ofile: Parasitics/SingleStage_Cfp_Sweep.png + + type: lt_sweep + y_key: V(n002) dB + + title: Verstärkung bei konstantem $R_f = 1G\Omega$ und varriertem $C_{f}$ + ylabel: Gain (dB) + - load: Parasitics/SingleStage_Rf_Sweep.txt + loadtype: ltspice + + ofile: Parasitics/SingleStage_Rf_Sweep.png + + type: lt_sweep + y_key: V(n002) dB + + title: Verstärkung bei konstantem $C_{f} = 100fF$ und varriertem $R_{f}$ + ylabel: Gain (dB) + - load: Parasitics/SingleStage_Rf_Sweep_Noise.txt + loadtype: ltspice + + ofile: Parasitics/SingleStage_Rf_Sweep_Noise.png + + type: lt_sweep + y_key: V(onoise)/{Rf} + x_key: frequency + + title: Eingangsbezogener Noise-Level bei varriertem $R_{f}$ (idealer OpAmp) + ylabel: Noise $\left(A/\sqrt{Hz}\right)$ + yformatter: engineering + yplaces: 0 + - load: Parasitics/SingleStage_LTC6268-10_Rf_Sweep_Noise.txt + loadtype: ltspice + + ofile: Parasitics/SingleStage_LTC_Rf_Sweep_Noise.png + + type: lt_sweep + y_key: V(onoise)/{Rf} + x_key: frequency + + title: Eingangsbezogener Noise-Level bei varriertem $R_{f}$ (LTC6268-10) + ylabel: Noise $\left(A/\sqrt{Hz}\right)$ + yformatter: engineering + yplaces: 0 + - load: Parasitics/SingleStage_LTC6268-10_Cin_Sweep_Noise.txt + loadtype: ltspice + + ofile: Parasitics/SingleStage_LTC_Cin_Sweep_Noise.png + + type: lt_sweep + y_key: V(onoise)/1G + x_key: frequency + + title: Eingangsbezogener Noise-Level bei varriertem $C_{in}$ (LTC6268-10) + ylabel: Noise $\left(A/\sqrt{Hz}\right)$ + yformatter: engineering + yplaces: 0 + - load: Parasitics/SingleStage_LTC6268-10_Cin_Sweep_Noise.txt + loadtype: ltspice + + ofile: Parasitics/SingleStage_LTC_Cin_Sweep_Noise_log.png + + type: lt_sweep + y_key: V(onoise)/1G + x_key: frequency + + title: Eingangsbezogener Noise-Level bei varriertem $C_{in}$ (LTC6268-10) + ylabel: Noise $\left(A/\sqrt{Hz}\right)$ + yformatter: engineering + yscale: log + yplaces: 0 + - load: Parasitics/SingleStage_GBWP_Sweep.txt + loadtype: ltspice + + ofile: Parasitics/SingleStage_GBWP_Sweep.png + + type: lt_sweep + y_key: V(n002) dB + + title: Verstärkung bei variiertem GBWP + ylabel: Gain (dB) + - load: Parasitics/SingleStage_Cin_Sweep.txt + loadtype: ltspice + + ofile: Parasitics/SingleStage_Cin_Sweep.png + + type: lt_sweep + y_key: V(vout) dB + + title: Verstärkung bei variierter Eingangskapazität + ylabel: Gain (dB) \ No newline at end of file