{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Data plotting guide"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import qcodes as qc"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Plotting data in QCoDeS can be done using either MatPlot or QTPlot, with matplotlib and pyqtgraph as backends, respectively. \n",
    "MatPlot and QTPlot tailor these plotting backends to QCoDeS, providing many features.\n",
    "For example, when plotting a DataArray in a DataSet, the corresponding ticks, labels, etc. are automatically added to the plot.\n",
    "Both MatPlot and QTPlot support live plotting while a measurement is running\n",
    "\n",
    "One of the main differences between the two backends is that matplotlib is more strongly integrated with Jupyter Notebook, while pyqtgraph uses the PyQT GUI.\n",
    "For matplotlib, this has the advantage that plots can be displayed within a notebook (though it also has a gui).\n",
    "The advantage of pyqtgraph is that it can be easily embedded in PyQT GUI's.\n",
    "\n",
    "This guide aims to provide a detailed guide on how to use each of the two plotting tools."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## MatPlot"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The QCoDeS MatPlot relies on the matplotlib package, which is quite similar to Matlab's plotting tools.\n",
    "It integrates nicely with Jupyter notebook, and as a result, interactive plots can be displayed within a notebook using the following command:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "%matplotlib notebook"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Simple 1D sweep"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As a first example, we perform a simple 1D sweep.\n",
    "We create two trivial parameters, one for measuring a value, and the other for sweeping the value of the measured parameter."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "p_measure = qc.ManualParameter(name='measured_val')\n",
    "p_sweep = qc.StandardParameter(name='sweep_val', set_cmd=p_measure.set)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Next we perform a measurement, and attach the `update` method of the `plot` object to the loop, resulting in live plotting.\n",
    "Note that the resulting plot automatically has the correct x values and labels."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
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\" width=\"600\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Started at 2017-09-28 11:01:41\n",
      "DataSet:\n",
      "   location = 'test_plotting_1D'\n",
      "   <Type>   | <array_id>    | <array.name> | <array.shape>\n",
      "   Setpoint | sweep_val_set | sweep_val    | (21,)\n",
      "   Measured | measured_val  | measured_val | (21,)\n",
      "Finished at 2017-09-28 11:01:53\n"
     ]
    }
   ],
   "source": [
    "loop = qc.Loop(\n",
    "    p_sweep.sweep(0, 20, step=1), delay=0.5).each(\n",
    "        p_measure)\n",
    "data = loop.get_data_set('test_plotting_1D')\n",
    "\n",
    "# Create plot for measured data\n",
    "plot = qc.MatPlot(data.measured_val)\n",
    "# Attach updating of plot to loop\n",
    "loop.with_bg_task(plot.update)\n",
    "\n",
    "loop.run();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Subplots"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In a measurement, there is often more than a single parameter that is measured.\n",
    "MatPlot supports multiple subplots, and upon initialization it will create a subplot for each of the arguments it receives.\n",
    "\n",
    "Let us create a second parameter that, when measured, always returns the value 10."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "p_measure2 = qc.ManualParameter(name='measured_val_2', initial_value=10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In the example below, three arguments are provided, resulting in three subplots.\n",
    "By default, subplots will be placed as columns on a single row, up to three columns.\n",
    "After this, a new row will be created (can be overridden in `MatPlot.max_subplot_columns`).\n",
    "\n",
    "Multiple DataArrays can also be plotted in a single subplot by passing them as a list in a single arg.\n",
    "As an example, notice how the first subplot shows multiple values."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<img 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\" width=\"1200\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Started at 2017-09-28 11:01:54\n",
      "DataSet:\n",
      "   location = 'test_plotting_1D_2'\n",
      "   <Type>   | <array_id>     | <array.name>   | <array.shape>\n",
      "   Setpoint | sweep_val_set  | sweep_val      | (21,)\n",
      "   Measured | measured_val   | measured_val   | (21,)\n",
      "   Measured | measured_val_2 | measured_val_2 | (21,)\n",
      "Finished at 2017-09-28 11:02:07\n"
     ]
    }
   ],
   "source": [
    "loop = qc.Loop(\n",
    "    p_sweep.sweep(0, 20, step=1), delay=0.5).each(\n",
    "        p_measure,\n",
    "        p_measure2)\n",
    "data = loop.get_data_set('test_plotting_1D_2')\n",
    "\n",
    "# Create plot for measured data\n",
    "plot = qc.MatPlot([data.measured_val, data.measured_val_2], data.measured_val, data.measured_val_2)\n",
    "# Attach updating of plot to loop\n",
    "loop.with_bg_task(plot.update)\n",
    "\n",
    "loop.run();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The data arrays don't all have to be passed along during initialization of the MatPlot instance.\n",
    "We can access the subplots of the plot object as if the plot was a list (e.g. `plot[0]` would give you the first subplot).\n",
    "To illustrate this, the example below results in the same plot as above."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<img 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\" width=\"1200\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Started at 2017-09-28 11:02:07\n",
      "DataSet:\n",
      "   location = 'test_plotting_1D_3'\n",
      "   <Type>   | <array_id>     | <array.name>   | <array.shape>\n",
      "   Setpoint | sweep_val_set  | sweep_val      | (21,)\n",
      "   Measured | measured_val   | measured_val   | (21,)\n",
      "   Measured | measured_val_2 | measured_val_2 | (21,)\n",
      "Finished at 2017-09-28 11:02:20\n"
     ]
    }
   ],
   "source": [
    "loop = qc.Loop(\n",
    "    p_sweep.sweep(0, 20, step=1), delay=0.5).each(\n",
    "        p_measure,\n",
    "        p_measure2)\n",
    "data = loop.get_data_set('test_plotting_1D_3')\n",
    "\n",
    "# Create plot for measured data\n",
    "plot = qc.MatPlot(subplots=3)\n",
    "plot[0].add(data.measured_val)\n",
    "plot[0].add(data.measured_val_2)\n",
    "plot[1].add(data.measured_val)\n",
    "plot[2].add(data.measured_val_2)\n",
    "\n",
    "# Attach updating of plot to loop\n",
    "loop.with_bg_task(plot.update)\n",
    "\n",
    "loop.run();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Note that we passed the kwarg `subplots=3` to specify that we need 3 subplots.\n",
    "the `subplots` kwarg can be either an int or a tuple.\n",
    "If it is an int, it will segment the value such that there are at most three columns.\n",
    "If a tuple is provided, its first element indicates the number of rows, and the second the number of columns.\n",
    "\n",
    "Furthermore, the size of the figure is automatically computed based on the number of subplots.\n",
    "This can be overridden by passing the kwarg `figsize=(x_length, y_length)` upon initialization.\n",
    "Additionally, `MatPlot.default_figsize` can be overridden to change the default computed figsize for a given subplot dimensionality."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2D Plots"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As illustrated below, MatPlot can also plot two-dimensional data arrays.\n",
    "MatPlot automatically handles setting the appropriate x- and y-axes, and also adds a colorbar by default.\n",
    "Note that we can also plot the individual traces of a 2D array, as shown in the first subplot below.\n",
    "This is done by passing all the elements (=rows) of the 2D array as a single argument using the splat (*) operator."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "p_sweep2 = qc.StandardParameter(name='sweep_val_2', set_cmd=p_measure2.set)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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\" width=\"900\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Started at 2017-09-28 11:02:21\n",
      "DataSet:\n",
      "   location = 'test_plotting_2D'\n",
      "   <Type>   | <array_id>      | <array.name> | <array.shape>\n",
      "   Setpoint | sweep_val_set   | sweep_val    | (21,)\n",
      "   Setpoint | sweep_val_2_set | sweep_val_2  | (21, 11)\n",
      "   Measured | measured_val    | measured_val | (21, 11)\n",
      "Finished at 2017-09-28 11:02:56\n"
     ]
    }
   ],
   "source": [
    "loop = qc.Loop(\n",
    "    p_sweep.sweep(0, 20, step=1), delay=0.5).loop(\n",
    "        p_sweep2.sweep(0, 10, step=1), delay=0.1).each(\n",
    "            p_measure)\n",
    "data = loop.get_data_set('test_plotting_2D')\n",
    "\n",
    "# Create plot for measured data\n",
    "plot = qc.MatPlot([*data.measured_val], data.measured_val)\n",
    "# Attach updating of plot to loop\n",
    "loop.with_bg_task(plot.update)\n",
    "\n",
    "loop.run();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In the example above, the colorbar can be accessed via `plot[1].qcodes_colorbar`.\n",
    "This can be useful when you want to modify the colorbar (e.g. change the color limits `clim`).\n",
    "\n",
    "Note that the above plot was updated every time an inner loop was completed. \n",
    "This is because the update method was attached to the outer loop.\n",
    "If you instead want it to update within an outer loop, you have to attach it to an inner loop: `loop[0].with_bg_task(plot.update)` (`loop[0]` is the first action of the outer loop, which is the inner loop)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Interfacing with Matplotlib\n",
    "As Matplot is built directly on top of Matplotlib, you can use standard Matplotlib functions which are readily available online in Matplotlib documentation as well as StackOverflow and similar sites. Here, we first perform the same measurement and obtain the corresponding figure:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<img 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\" width=\"900\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Started at 2017-09-28 11:02:56\n",
      "DataSet:\n",
      "   location = 'test_plotting_2D_2'\n",
      "   <Type>   | <array_id>      | <array.name> | <array.shape>\n",
      "   Setpoint | sweep_val_set   | sweep_val    | (21,)\n",
      "   Setpoint | sweep_val_2_set | sweep_val_2  | (21, 11)\n",
      "   Measured | measured_val    | measured_val | (21, 11)\n",
      "Finished at 2017-09-28 11:03:31\n"
     ]
    }
   ],
   "source": [
    "loop = qc.Loop(\n",
    "    p_sweep.sweep(0, 20, step=1), delay=0.5).loop(\n",
    "        p_sweep2.sweep(0, 10, step=1), delay=0.1).each(\n",
    "            p_measure)\n",
    "data = loop.get_data_set('test_plotting_2D_2')\n",
    "\n",
    "# Create plot for measured data\n",
    "plot = qc.MatPlot([*data.measured_val], data.measured_val)\n",
    "# Attach updating of plot to loop\n",
    "loop.with_bg_task(plot.update)\n",
    "\n",
    "loop.run();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To use the matplotlib api, we need access to the matplotlib Figure and Axis objects. \n",
    "Each subplot has its correspond Axis object, which are grouped together into a single Figure object.\n",
    "A subplot Axis can be accessed via its index. As an example, we will modify the title of the first axis:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "ax = plot[0] # shorthand for plot.subplots[0]\n",
    "ax.set_title(\"My left subplot title\");"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Note that this returns the actual matplotlib Axis object.\n",
    "It does have the additional QCoDeS method `Axis.add()`, which allows easily adding of a QCoDeS DataArray. See http://matplotlib.org/api/axes_api.html for documentation of the Matplotlib Axes class.\n",
    "\n",
    "The Matplotlib Figure object can be accessed via the fig attribute on the QCoDeS Matplot object:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "fig = plot.fig\n",
    "fig.tight_layout();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "See http://matplotlib.org/api/figure_api.html for documentation of the Matplotlib Figure class.\n",
    "\n",
    "Matplotlib also offers a second way to modify plots, namely pyplot.\n",
    "This can be imported via:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from matplotlib import pyplot as plt"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In pyplot, there is always an active axis and figure, similar to Matlab plotting.\n",
    "Every time a new plot is created, it will update the active axis and figure.\n",
    "The active Figure and Axis can be changed via `plt.scf(fig)` and `plt.sca(ax)`, respectively.\n",
    "\n",
    "As an example, the following code will change the title of the last-created plot (the right subplot of the previous figure)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "plt.title('My right subplot title');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "See https://matplotlib.org/users/pyplot_tutorial.html for documentation on Pyplot"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Event handling"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Since matplotlib is an interactive plotting tool, one can program actions that are dependent on events.\n",
    "There are many events, such as clicking on a plot, pressing a key, etc.\n",
    "\n",
    "As an example, we can attach a trivial function to occur when the plot object is closed. You can replace this with other functionality, such as stopping the loop."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
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\" width=\"600\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def handle_close(event):\n",
    "    print('Plot closed')\n",
    "    \n",
    "plot = qc.MatPlot()\n",
    "plot.fig.canvas.mpl_connect('close_event', handle_close);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "On a related note, matplotlib also has widgets that can be added to plots, allowing additional interactivity with the dataset.\n",
    "An example would be adding a slider to show 2D plots of a 3D dataset (e.g. https://matplotlib.org/examples/widgets/slider_demo.html)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## QTPlot"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "QTPlot is a second package that allows plotting of data.  \n",
    "For a guide on using QTPlot, please go to the QCoDeS homepage"
   ]
  }
 ],
 "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": "3.6.3"
  },
  "toc": {
   "hide_others": true,
   "nav_menu": {},
   "number_sections": true,
   "sideBar": true,
   "skip_h1_title": false,
   "toc_position": {},
   "toc_section_display": "block",
   "toc_window_display": false
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}