{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Plotting routines in `touchsim`\n",
    "The `touchsim` package uses `holoviews` for plotting."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import touchsim as ts\n",
    "from touchsim.plotting import plot\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Hand model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "plot() # short for plot(ts.hand_surface)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Regions labels and the coordinate system can be overlaid on the plot."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "plot(tags=True,coord=10) # coord sets the lengths of the coordinate axes in mm"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Visualising `AfferentPopulation` objects"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "a = ts.affpop_hand(region='D2d')\n",
    "plot(a,size=10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Spatial plots can be overlaid on the hand outline or individual parts of it"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "_,(ax1,ax2,ax3) = plt.subplots(1,3)\n",
    "plt.sca(ax1)\n",
    "plot(region='D2d')\n",
    "plot(a['SA1'],size=10)\n",
    "\n",
    "plt.sca(ax2)\n",
    "plot(region='D2d')\n",
    "plot(a['RA'],size=10)\n",
    "\n",
    "plt.sca(ax3)\n",
    "plot(region='D2d')\n",
    "plot(a['PC'],size=10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Visualising `Stimulus` objects\n",
    "Plotting a `Stimulus` object shows the trace of all pins by default."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "s = ts.stim_ramp(len=0.25,amp=.1,ramp_len=0.05)\n",
    "plot(s)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "s += ts.stim_sine(freq=25.,len=.25,loc=[1.,1.])\n",
    "plot(s)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Pin positions can also be shown spatially."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "s = ts.stim_indent_shape(ts.shape_circle(hdiff=0.5,pins_per_mm=2,radius=3),ts.stim_ramp(len=0.1))\n",
    "plot(region='D2d')\n",
    "plot(s,spatial=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Visualising `Response` objects\n",
    "Plotting a `Response` object shows the spike trains of all included neurons"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "a = ts.affpop_hand(region='D2')\n",
    "s = ts.stim_sine(freq=50.,amp=0.1,len=0.5)\n",
    "r = a.response(s)\n",
    "plot(r)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Responses can be shown within a certain time window."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "plot(r,bin=[0,0.2])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Responses can also be plotted spatially, in which case the size of each dot scaled with the neuron's firing rate."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "plot(region='D2')\n",
    "plot(r,spatial=True,scaling_factor=.25)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Alternatively, firing rate can be indicated by color instead:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "_,(ax1,ax2) = plt.subplots(1,2)\n",
    "plt.sca(ax1)\n",
    "plot(region='D2')\n",
    "plot(r[r.aff['RA']],spatial=True,scale=False)\n",
    "\n",
    "plt.sca(ax2)\n",
    "plot(region='D2')\n",
    "plot(r[r.aff['PC']],spatial=True,scale=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Advanced example (might be slow to compute)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "contact_locs = np.zeros((2,2))\n",
    "contact_locs[0] = np.array([0.,0.])\n",
    "contact_locs[1] = np.array([150.,0])\n",
    "    \n",
    "a = ts.affpop_hand(noisy=False)\n",
    "s = ts.stim_indent_shape(contact_locs,ts.stim_ramp(amp=0.75,len=.2,ramp_len=0.05,ramp_type='lin',pin_radius=5.,pad_len=0.025))\n",
    "r = a.response(s)\n",
    "plot(r)"
   ]
  }
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