{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Linking to parent datasets\n", "\n", "When performing a measurement in QCoDeS, it is possible to annotate the outcome (the dataset) of that measurement as having one or more parent datasets. This is done by adding a link to each parent dataset. This notebook covers the mechanisms to do that by going through a few practical examples." ] }, { "cell_type": "code", "execution_count": 17, "metadata": {}, "outputs": [], "source": [ "import datetime\n", "import os\n", "\n", "import matplotlib.pyplot as plt\n", "import numpy as np\n", "import scipy.optimize as opt\n", "\n", "from qcodes.dataset import (\n", " Measurement,\n", " initialise_or_create_database_at,\n", " load_by_run_spec,\n", " load_or_create_experiment,\n", " plot_dataset,\n", ")" ] }, { "cell_type": "code", "execution_count": 18, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "tutorial 2019-11-07 09:45:31.867247#no sample#2@C:\\Users\\a-halakh\\Documents\\Microsoft\\QcodesHarshit\\docs\\examples\\DataSet\\linking_datasets_tutorial.db\n", "------------------------------------------------------------------------------------------------------------------------------------------------------" ] }, "execution_count": 18, "metadata": {}, "output_type": "execute_result" } ], "source": [ "now = str(datetime.datetime.now())\n", "tutorial_db_path = os.path.join(os.getcwd(), 'linking_datasets_tutorial.db')\n", "initialise_or_create_database_at(tutorial_db_path)\n", "load_or_create_experiment('tutorial ' + now, 'no sample')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Example 1: Measuring and then fitting\n", "\n", "Say we measure some raw data and subsequently do a curve fit to those data. We'd like to save the fit as a separate dataset that has a link to the dataset of the original data. This is achieved in two steps." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Step 1: measure raw data" ] }, { "cell_type": "code", "execution_count": 19, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Starting experimental run with id: 4\n" ] } ], "source": [ "meas = Measurement()\n", "meas.register_custom_parameter(name='time',\n", " label='Time', unit='s',\n", " paramtype='array')\n", "meas.register_custom_parameter(name='signal',\n", " label='Signal', unit='V',\n", " paramtype='array',\n", " setpoints=['time'])\n", "\n", "N = 500\n", "\n", "with meas.run() as datasaver:\n", " time_data = np.linspace(0, 1, N)\n", " signal_data = np.sin(2*np.pi*time_data) + 0.25*np.random.randn(N)\n", "\n", " datasaver.add_result(('time', time_data), ('signal', signal_data))\n", "dataset = datasaver.dataset" ] }, { "cell_type": "code", "execution_count": 20, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "cbs, axs = plot_dataset(dataset)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Step 2: Set up a fit \"measurement\"\n", "\n", "We now load the raw data dataset, set up a new measurement for the fit, register the raw data as a parent and save a fit." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "As the very first step, we supply a model to fit to." ] }, { "cell_type": "code", "execution_count": 21, "metadata": {}, "outputs": [], "source": [ "def fit_func(x, a, b):\n", " return a*np.sin(2*np.pi*x)+b" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Next, we set up the fitting measurement." ] }, { "cell_type": "code", "execution_count": 22, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 22, "metadata": {}, "output_type": "execute_result" } ], "source": [ "raw_data = load_by_run_spec(captured_run_id=dataset.captured_run_id)\n", "\n", "meas = Measurement()\n", "meas.register_custom_parameter('fit_axis',\n", " label='Fit axis', unit='t',\n", " paramtype='array')\n", "meas.register_custom_parameter('fit_curve',\n", " label='Fitted curve', unit='V',\n", " paramtype='array',\n", " setpoints=['fit_axis'])\n", "meas.register_custom_parameter('fit_param_a',\n", " label='Fitted parameter amplitude',\n", " unit='V')\n", "meas.register_custom_parameter('fit_param_b',\n", " label='Fitted parameter offset',\n", " unit='V')\n", "meas.register_parent(parent=raw_data, link_type=\"curve fit\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "As we now run the measurement, the parent datasets become available via the datasaver. The datasets appear in the order they were registered." ] }, { "cell_type": "code", "execution_count": 32, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Starting experimental run with id: 8\n" ] } ], "source": [ "with meas.run() as datasaver:\n", " raw = datasaver.parent_datasets[0]\n", " xdata = np.ravel(raw.get_parameter_data()['signal']['time'])\n", " ydata = np.ravel(raw.get_parameter_data()['signal']['signal'])\n", "\n", " popt, pcov = opt.curve_fit(fit_func, xdata, ydata, p0=[1, 1])\n", "\n", " fit_axis = xdata\n", " fit_curve = fit_func(fit_axis, *popt)\n", "\n", " datasaver.add_result(('fit_axis', fit_axis),\n", " ('fit_curve', fit_curve),\n", " ('fit_param_a', popt[0]),\n", " ('fit_param_b', popt[1]))\n", "\n", "fit_data = datasaver.dataset" ] }, { "cell_type": "code", "execution_count": 33, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "cbs, axs = plot_dataset(fit_data)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "And just for completeness, let us plot both datasets on top of each other." ] }, { "cell_type": "code", "execution_count": 31, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 31, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "fig, ax = plt.subplots(1)\n", "cbs, axs = plot_dataset(raw_data, axes=ax, label='data')\n", "cbs, axs = plot_dataset(fit_data, axes=ax, label='fit', linewidth=4)\n", "ax.set_xlabel('Time (s)')\n", "ax.set_ylabel('Signal (V)')\n", "plt.legend()" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] } ], "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": "3.7.4" } }, "nbformat": 4, "nbformat_minor": 4 }