{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Make and visualise DNA Models\n",
    "*It is recommended that you run this example inside a Jupyter environment*\n",
    "*rather than a VSCode or similar environment*\n",
    "\n",
    "This requires the mayavi jupyter extension\n",
    "`jupyter nbextension install --py mayavi --user`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import sys\n",
    "from pathlib import Path\n",
    "\n",
    "try:\n",
    "    from fractaldna.dna_models import dnachain as dna\n",
    "except (ImportError, ModuleNotFoundError):\n",
    "    # Path modifications for when running out of git repo\n",
    "    sys.path.append(str(Path.cwd().parent.parent.parent))\n",
    "    from fractaldna.dna_models import dnachain as dna\n",
    "\n",
    "from mayavi import mlab\n",
    "\n",
    "# Disable this option for interactive rendering\n",
    "mlab.options.offscreen = True\n",
    "\n",
    "# Enable this option for an interactive notebook\n",
    "# mlab.init_notebook()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Making Multi-Strand DNA\n",
    "The module currently supports 2-, 4- and 8- strand multi-chains in different configurations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Make a 40 base pair long DNA Strand\n",
    "chain = dna.FourStrandDNAChain(\"GTAC\" * 50, 50)\n",
    "# Generate a simple Matplotlib visualisation\n",
    "# The basic plot shows each molecule as a point\n",
    "plot = chain.to_plot()\n",
    "plot.gca().set_title(\"Basic Plot\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Generating nicer plots with MayaVI"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# MayaVI can generate nicer plots, joining the strands together\n",
    "plot = chain.to_strand_plot()\n",
    "plot.scene.save_jpg(\"multi_strand_strand_plot.jpg\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![multi_strand_strand_plot](multi_strand_strand_plot.jpg)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Generating curved strands"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# These can also be curved\n",
    "chain = dna.FourStrandTurnedDNAChain(\"GTAC\" * 50, 50)\n",
    "plot = chain.to_strand_plot()\n",
    "plot.scene.save_jpg(\"multi_strand_turned_strand_plot.jpg\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![multi_strand_turned_strand_plot](multi_strand_turned_strand_plot.jpg)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Exporting to dataframe or text\n",
    "\n",
    "The export dataframe has the following columns\n",
    "\n",
    "- name: molecule name\n",
    "- shape: molecule shape (sphere or ellipse)\n",
    "- chain_idx: The index of the DNA chain of the molecule (chains are double helices)\n",
    "- strand_idx: An index to indicate which side of the double helix a molecule is on.\n",
    "- bp_idx: The index of the base pair\n",
    "- size_x: semi-major x axis in Angstom\n",
    "- size_y: semi-major y axis in Angstom\n",
    "- size_z: semi-major z axis in Angstom\n",
    "- pos_x: x-position in Angstrom\n",
    "- pos_y: y-position in Angstrom\n",
    "- pos_z: z-position in Angstrom\n",
    "- rot_x: Euler rotation of molecule about the x-axis (radians)\n",
    "- rot_y: Euler rotation of molecule about the y-axis (radians)\n",
    "- rot_z: Euler rotation of molecule about the z-axis (radians)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# And then loaded into a data frame\n",
    "chain.to_frame()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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