{
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   "source": [
    ".. _plotting::\n",
    "\n",
    "|\n",
    "|\n",
    "\n",
    "Download This Notebook: :download:`Plotting.ipynb`\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Plotting  \n",
    "\n",
    "## Introduction\n",
    "\n",
    "This tutorial describes **skrf's** plotting features.  If you would like to use skrf's matplotlib interface with skrf styling, start with this"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from matplotlib import pyplot as plt  # for advanced smith chart only\n",
    "\n",
    "import skrf as rf"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Plotting Methods\n",
    "\n",
    "\n",
    "Plotting functions are implemented as methods of the `Network` class.\n",
    "\n",
    "* `Network.plot_s_re`\n",
    "* `Network.plot_s_im`\n",
    "* `Network.plot_s_mag`\n",
    "* `Network.plot_s_db`\n",
    "* ...\n",
    "    \n",
    "Similar methods exist for Impedance (`Network.z`) and Admittance Parameters (`Network.y`), \n",
    "\n",
    "\n",
    "* `Network.plot_z_re`\n",
    "* `Network.plot_z_im`\n",
    "* ...\n",
    "* `Network.plot_y_re`\n",
    "* `Network.plot_y_im`\n",
    "* ...\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "## Smith Chart \n",
    "\n",
    "\n",
    "As a first example, load a [Network](../api/network.rst) and plot all four  s-parameters on the Smith chart."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from skrf import Network\n",
    "\n",
    "ring_slot = Network('data/ring slot.s2p')\n",
    "ring_slot.plot_s_smith()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "scikit-rf includes a convenient command to make nicer figures quick:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "rf.stylely()  # nicer looking. Can be configured with different styles\n",
    "ring_slot.plot_s_smith()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "ring_slot.plot_s_smith(draw_labels=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Another common option is to draw admittance contours, instead of impedance. This is controlled through the  `chart_type` argument."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "ring_slot.plot_s_smith(chart_type='y')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Advanced Smith Chart with markers\n",
    "\n",
    "The Smith Chart is a convenient plot that shows complex numbers with real and imaginary parts from zero to infinity with a zoom on a real reference in the center region. It is, however, not straightforward to figure out what point is related to which frequency because there is no frequency axis. A common workaround is to provide some frequency markers related to a table."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# prepare markers\n",
    "lines = [\n",
    "    {'marker_idx': [30, 60, 90], 'color': 'g', 'm': 0, 'n': 0, 'ntw': ring_slot},\n",
    "    {'marker_idx': [15, 45, 75], 'color': 'r', 'm': 1, 'n': 0, 'ntw': ring_slot},\n",
    "]\n",
    "\n",
    "# prepare figure\n",
    "fig, ax = plt.subplots(1, 1, figsize=(7,8))\n",
    "\n",
    "# impedance smith chart\n",
    "rf.plotting.smith(ax = ax, draw_labels = True, ref_imm = 50.0, chart_type = 'z')\n",
    "\n",
    "# plot data\n",
    "col_labels = ['Frequency', 'Real Imag']\n",
    "row_labels = []\n",
    "row_colors = []\n",
    "cell_text = []\n",
    "for l in lines:\n",
    "    m = l['m']\n",
    "    n = l['n']\n",
    "    l['ntw'].plot_s_smith(m=m, n=n, ax = ax, color=l['color'])\n",
    "    #plot markers\n",
    "    for i, k in enumerate(l['marker_idx']):\n",
    "        x = l['ntw'].s.real[k, m, n]\n",
    "        y = l['ntw'].s.imag[k, m, n]\n",
    "        z = l['ntw'].z[k, m, n]\n",
    "        z = f'{z.real:.4f} + {z.imag:.4f}j ohm'\n",
    "        f = l['ntw'].frequency.f_scaled[k]\n",
    "        f_unit = l['ntw'].frequency.unit\n",
    "        row_labels.append(f'M{i + 1}')\n",
    "        row_colors.append(l['color'])\n",
    "        ax.scatter(x, y, marker = 'v', s=20, color=l['color'])\n",
    "        ax.annotate(row_labels[-1], (x, y), xytext=(-7, 7), textcoords='offset points', color=l['color'])\n",
    "        cell_text.append([f'{f:.3f} {f_unit}', z])\n",
    "leg1 = ax.legend(loc=\"upper right\", fontsize= 6)\n",
    "\n",
    "# plot the table\n",
    "the_table = ax.table(cellText=cell_text,\n",
    "                      colWidths=[0.4] * 2,\n",
    "                      rowLabels=row_labels,\n",
    "                      colLabels=col_labels,\n",
    "                      rowColours=row_colors,\n",
    "                      loc='bottom')\n",
    "the_table.auto_set_font_size(False)\n",
    "the_table.set_fontsize(6)\n",
    "#the_table.scale(1.5, 1.5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Advanced Smith Chart with background\n",
    "\n",
    "The Smith Chart can be drawn above a high-resolution Smith Chart background (or another image upon your fantasy)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# prepare figure\n",
    "fig, ax = plt.subplots(1, 1, figsize=(8,8))\n",
    "background = plt.imread('figures/smithchart.png')\n",
    "\n",
    "# tweak background position\n",
    "ax.imshow(background, extent=[-1.185, 1.14, -1.13, 1.155])\n",
    "rf.plotting.smith(ax = ax, draw_labels = True, ref_imm = 1.0, chart_type = 'z')\n",
    "\n",
    "ring_slot.plot_s_smith(ax = ax)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "    \n",
    "See `skrf.plotting.smith()` for more info on customizing the Smith Chart. \n",
    "\n",
    "## Complex Plane \n",
    "\n",
    "\n",
    "Network parameters can also be plotted in the complex plane without a Smith Chart through `Network.plot_s_complex`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from matplotlib import pyplot as plt\n",
    "\n",
    "ring_slot.plot_s_complex()\n",
    "\n",
    "plt.axis('equal') # otherwise circles won't be circles"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Log-Magnitude \n",
    "\n",
    "\n",
    "Scalar components of the complex network parameters can be plotted vs \n",
    "frequency as well. To plot the log-magnitude of the s-parameters vs. frequency,"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "ring_slot.plot_s_db()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "    \n",
    "When no arguments are passed to the plotting methods, all parameters are plotted. Single parameters can be plotted by passing indices `m` and `n` to the plotting commands (indexing start from 0). Comparing the simulated reflection coefficient off the ring slot to a measurement, "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from skrf.data import ring_slot_meas\n",
    "\n",
    "ring_slot.plot_s_db(m=0,n=0, label='Theory')\n",
    "ring_slot_meas.plot_s_db(m=0,n=0, label='Measurement')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Phase \n",
    "\n",
    "\n",
    "Plot phase, "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "ring_slot.plot_s_deg()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "    \n",
    "Or unwrapped phase, "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "ring_slot.plot_s_deg_unwrap()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Phase is radian (rad) is also available"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Group Delay "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "A Network has a `plot()` method which creates a rectangular plot of the argument vs frequency.  This can be used to make plots are aren't 'canned'. For example group delay"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "gd = abs(ring_slot.s21.group_delay) *1e9 # in ns\n",
    "\n",
    "ring_slot.plot(gd)\n",
    "plt.ylabel('Group Delay (ns)')\n",
    "plt.title('Group Delay of Ring Slot S21')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Impedance, Admittance \n",
    "\n",
    "\n",
    "The components the Impedance and Admittance parameters can be plotted \n",
    "similarly, "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "ring_slot.plot_z_im()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "ring_slot.plot_y_im()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Customizing Plots\n",
    "\n",
    "\n",
    "The legend entries are automatically filled in with the Network's `Network.name`. The entry can be overridden by passing the `label` argument to the plot method."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "ring_slot.plot_s_db(m=0,n=0, label = 'Simulation')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The frequency unit used on the x-axis is automatically filled in from \n",
    "the Networks `Network.frequency.unit` attribute. To change\n",
    "the label, change the frequency's `unit`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "ring_slot.frequency.unit = 'mhz'\n",
    "ring_slot.plot_s_db(0,0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Other key word arguments given to the plotting methods are passed through to the matplotlib `matplotlib.pyplot.plot` function. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "ring_slot.frequency.unit='ghz'\n",
    "ring_slot.plot_s_db(m=0,n=0, linewidth = 3, linestyle = '--', label = 'Simulation')\n",
    "ring_slot_meas.plot_s_db(m=0,n=0, marker = 'o', markevery = 10,label = 'Measured')\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "All components of the plots can be customized through  [matplotlib]( http://matplotlib.sourceforge.net) functions, and `styles` can be used with a context manager. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from matplotlib import pyplot as plt\n",
    "from matplotlib import style\n",
    "\n",
    "mpl_style = \"seaborn-ticks\"\n",
    "mpl_style = mpl_style if mpl_style in style.available else \"seaborn-v0_8-ticks\"\n",
    "\n",
    "with style.context(mpl_style):\n",
    "    ring_slot.plot_s_smith()\n",
    "    plt.xlabel('Real Part')\n",
    "    plt.ylabel('Imaginary Part')\n",
    "    plt.title('Smith Chart With Legend Room')\n",
    "    plt.axis([-1.1,2.1,-1.1,1.1])\n",
    "    plt.legend(loc=5)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Saving Plots\n",
    "\n",
    "Plots can be saved in various file formats using the GUI provided by the matplotlib. However, skrf provides a convenience function, called `skrf.plotting.save_all_figs`,  that allows all open figures to be saved to disk in multiple file formats, with filenames pulled from each figure's title,"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from skrf.plotting import save_all_figs\n",
    "\n",
    "save_all_figs('data/', format=['png','eps','pdf'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Adding Markers Post Plot\n",
    "\n",
    "\n",
    "A common need is to make a color plot, interpretable in greyscale print. \n",
    "The `skrf.plotting.add_markers_to_lines`  adds different markers each line in a plots *after* the plot has been made, which is usually when you remember to add them."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from skrf import plotting\n",
    "\n",
    "with plt.style.context('grayscale'):\n",
    "    ring_slot.plot_s_deg()\n",
    "    plotting.add_markers_to_lines()\n",
    "    plt.legend() # have to re-generate legend\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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