{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "c06675f6",
   "metadata": {},
   "source": [
    "# The Reciprocal Lattice Units Axis\n",
    "\n",
    "The main object to plot data in reciprocal lattice units is the <code>RLUAxis</code> which takes care of conversion between the calculated ($Q_x$,$Q_y$) and the scattering plane in ($H$,$K$,$L$) units with the correct grid. This can at times prove difficult when dealing with non-orthogonal unit cells and/or if the scattering plane is non-trivial. For detailed technical information about the implementation see section below or the source code."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "e60caf9a",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-05-01T08:37:30.735847Z",
     "iopub.status.busy": "2023-05-01T08:37:30.735847Z",
     "iopub.status.idle": "2023-05-01T08:37:33.186908Z",
     "shell.execute_reply": "2023-05-01T08:37:33.186068Z"
    }
   },
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "from MJOLNIR.Data import DataSet\n",
    "from MJOLNIR import _tools # Usefull tools useful across MJOLNIR\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "\n",
    "plt.rcParams['figure.figsize'] = [14, 10]\n",
    "plt.rcParams['figure.dpi'] = 200\n",
    "\n",
    "numbers = '137' # String of data numbers\n",
    "fileList = _tools.fileListGenerator(numbers,folder=r'C:\\Users\\lass_j\\Documents\\CAMEA2018',year=2018) # Create file list from 2018 in specified folder\n",
    "\n",
    "ds = DataSet.DataSet(fileList)\n",
    "ds.convertDataFile(binning=8)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7c28613d",
   "metadata": {},
   "source": [
    "The RLU axis can be created directly from the <code>DataSet</code> object using the <code>Sample</code> as loaded from the data file and found in each <code>DataFile</code>. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "79b0e81f",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-05-01T08:37:33.189903Z",
     "iopub.status.busy": "2023-05-01T08:37:33.189903Z",
     "iopub.status.idle": "2023-05-01T08:37:33.409216Z",
     "shell.execute_reply": "2023-05-01T08:37:33.408505Z"
    }
   },
   "outputs": [],
   "source": [
    "# Create RLU axis\n",
    "ax = ds.createQAxis()\n",
    "# Get the figure corresponding to the returned axis\n",
    "fig = ax.get_figure();\n",
    "\n",
    "# The axis should contain v1 and v2\n",
    "v1 = [-1.5,-1.5,0]\n",
    "v2 = [1.5,1.5,0]\n",
    "\n",
    "ax.set_axis(v1,v2)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "afb2fd61",
   "metadata": {},
   "source": [
    "A couple of points are created to highlight the methods of the <code>RLUAxis</code> object. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "e47081d3",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-05-01T08:37:33.412215Z",
     "iopub.status.busy": "2023-05-01T08:37:33.412215Z",
     "iopub.status.idle": "2023-05-01T08:37:33.424584Z",
     "shell.execute_reply": "2023-05-01T08:37:33.424283Z"
    }
   },
   "outputs": [],
   "source": [
    "# Generate some points to plot\n",
    "points = np.array([[-1,-1],[-1,1],[1,1],[1,-1],[-1,-1]]).T\n",
    "\n",
    "# Use points as distance along projections\n",
    "projection = np.array(ax.sample.inv_tr(points[0],points[1]))\n",
    "# Convert into HKL (corresponds to the points above)\n",
    "HKL = np.array([points[0],points[1],np.zeros_like(points[0])])\n",
    "\n",
    "# Calculate actual position of HKL points\n",
    "P1P2 = np.array(ax.sample.calculateHKLtoProjection(HKL[0],HKL[1],HKL[2]))\n",
    "QxQy = np.array(ax.sample.inv_tr(P1P2[0],P1P2[1]))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c8ef85c2",
   "metadata": {},
   "source": [
    "The above points are converted in 3 different ways to specific locations within the plot:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "16644da2",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-05-01T08:37:33.427216Z",
     "iopub.status.busy": "2023-05-01T08:37:33.427216Z",
     "iopub.status.idle": "2023-05-01T08:37:33.819243Z",
     "shell.execute_reply": "2023-05-01T08:37:33.818444Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1400x800 with 1 Axes>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Plot all 3 lines\n",
    "ax.plot(points[0],points[1],label='QxQy')\n",
    "ax.plot(projection[0],projection[1],label='Projection')\n",
    "ax.plot(QxQy[0],QxQy[1],'g',label='HK',marker='o', linestyle='dashed')\n",
    "\n",
    "ax.legend()\n",
    "\n",
    "ax.grid(True)\n",
    "ax.get_figure()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "14815212",
   "metadata": {},
   "source": [
    "The first example in the code above takes a data set measured on a crystal with unit cell \\[a = 6.11, b = 6.11, c = 11.35, $\\alpha$ = 90, $\\beta$ = 90, $\\gamma$ = 120\\], that is, the crystal is hexagonal and is placed in the ($H$,$K$,$0$) scattering plane. Behind the scene, data plotted in the axis is assumed to be in the ($Q_x$, $Q_y$) coordinate system rotated such that the first projection vector is along the x-axis (in this case ($H$,$0$,$0$). The data is then first converted into reciprocal space ($H$,$K$,$L$) and then into the projected in the scattering plane. This might seem like swatting flies with a sledge hammer, however, it allows for enough abstraction as to allow all cases to be plotted.\n",
    "\n",
    "As the axis object makes use of the non-standard <code>GridHelperCurveLinear</code> many features regarding the tick marks and setting limits are not working, but see section below for a dicussion of this. A custom function has been generated to set the limits of the shown graph called <code>set_limits</code>. It takes at least two vectors in either ($H$,$K$,$L$) or projection along principal directions and assures that these are visible. Multiple vectors can be provided and it is then assured that all vector positions are visible. An example is shown in where <code>v1</code> and <code>v2</code> are assured to both be visible. In this case, providing the vectors (-1,-1.5) and (2,1,0) is sufficient as the projections are simply (1,0,0) and (0,1,0).\n",
    "\n",
    "As to the data plotted in the axis; plotting directly into the axis corresponds to plotting the ($Q_x$, $Q_y$) system which in this case produces a square box around (0,0). However, wanting to plot things in terms of reciprocal lattice unites one has two options: Plot corresponding to projection or calculate ($Q_x$, $Q_y$) from HKL points. Both of these methods are shown in the first example resulting in the two parallellograms plotted on top of each other. Notice that the blue box does not have the same height as the two others due to the length of the ($H$,$0$,$0$) being 1.187 /AA and not unity."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "4cb7685c",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-05-01T08:37:33.822249Z",
     "iopub.status.busy": "2023-05-01T08:37:33.822249Z",
     "iopub.status.idle": "2023-05-01T08:37:34.356883Z",
     "shell.execute_reply": "2023-05-01T08:37:34.356431Z"
    }
   },
   "outputs": [],
   "source": [
    "numbers = '422' # String of data numbers\n",
    "fileList = _tools.fileListGenerator(numbers,folder=r'C:\\Users\\lass_j\\Documents\\CAMEA2018',year=2018) # Create file list from 2018 in specified folder\n",
    "\n",
    "ds = DataSet.DataSet(fileList)\n",
    "ds.convertDataFile(saveFile=False)\n",
    "\n",
    "ax = ds.createQAxis()\n",
    "fig = ax.get_figure()\n",
    "\n",
    "# The axis should contain v1 and v2\n",
    "\n",
    "v1 = [-2,1,1]\n",
    "v2 = [2,-1,-1]\n",
    "\n",
    "ax.set_axis(v1,v2)\n",
    "\n",
    "ax.grid(True)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "167d893b",
   "metadata": {},
   "source": [
    "The second example has a crystal with unit cell \\[a = 9.843, b = 9.843, c = 9.843, $\\alpha$ = 90, $\\beta$ = 90, $\\gamma$ = 90\\], i.e. simple cubic, but the scattering plane is ($H$,$K$,$K$). Setting the limits to include all points from -2 to 2 in $H$ and from -1 to 1 in $K$ is shown in the code by providing the position vectors. The same result is obtained by simply giving (-2,-1) and (2,1) to the method."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "aa4b4762",
   "metadata": {},
   "source": [
    "## Techical detials\n",
    "\n",
    "It was chosen to make use of the <code>GridHelperCurveLinear</code> despite the difficulties arising from it as this allows for plotting in RLU coordinates without having to skew data. That is, it is possible to keep data as measured by the instrument (sort of circular) while still providing all information about the reciprocal space to the user. As mentioned, some calculations happen behind the scenes when dealing with this object; most of the in the sample object itself. Mathematically what happens is as follows:\n",
    "\n",
    "The general relationship between measured points from the instrument, denoted ($Q_x$,$Q_y$,$Q_z$) for the two in-plane components along x and y, and the one out of plane, and the reciprocal lattice units ($H$,$K$,$L$) is given by the UB matrix\n",
    "\n",
    "$$ \\begin{pmatrix}Q_x\\\\Q_y\\\\Q_z\\end{pmatrix} = UB \\cdot \\begin{pmatrix}H\\\\K\\\\L\\end{pmatrix} $$\n",
    "\n",
    "From the geometrical constraints of the CAMEA backend, all scattering is performed in plane. Put in other words, $Q_z$ is always 0. Thus one can use a simple projection matrix from 2D to 3D:\n",
    "\n",
    "$$ \\begin{pmatrix}Q_x\\\\Q_y\\end{pmatrix} = \\underbrace{\\begin{pmatrix}1 & 0 & 0\\\\0 & 1 & 0\\end{pmatrix}}_{P_{23}} UB \\cdot \\begin{pmatrix}H\\\\K\\\\L\\end{pmatrix} $$\n",
    "\n",
    "As the measured space from the instrument side is 2D the points in terms of RLU are also to lay in a plane. One can make use of this by finding the two most simple projection vectors spanning this plane. Assuming they are found the projection along these are denoted $P_1$ and $P_2$. One can then project the ($H$,$K$,$L$) points long these vectors as:\n",
    "\n",
    "$$\\begin{pmatrix}H\\\\K\\\\L\\end{pmatrix} = P_M \\cdot \\begin{pmatrix}P_0\\\\P_1\\end{pmatrix} $$\n",
    "\n",
    "Now remains finding the projection matrix $P_M$, which is given as the 3x2 column matrix of them divided by the square of their lengths. Putting it all together results in:\n",
    "\n",
    "$$ \\begin{pmatrix}Q_x\\\\Q_y\\end{pmatrix} = \\underbrace{\\begin{pmatrix}1 & 0 & 0\\\\0 & 1 & 0\\end{pmatrix}}_{P_{23}} UB \\cdot P_M \\cdot \\begin{pmatrix}P_0\\\\P_1\\end{pmatrix} $$\n",
    "\n",
    "One further detail is that due to the way that the instrument positions, ($Q_x$,$Q_y$) are calculated, one needs to rotate this system with an angle corresponding to the “mis-alignment” of the orientation of the crystal. In reality this angle corresponds to the difference between the $A_3$ zero offset and the one for which the first projection vector is along the x-axis."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "212a9869",
   "metadata": {},
   "source": [
    "## Examples\n",
    "\n",
    "### Example 1\n",
    "Using the crystal of example 1 above, the unit cell parameters are $a = b = 6.11$, $c = 11.35$, $\\alpha = \\beta = 90^\\circ$ and $\\gamma = 120^\\circ$, resulting in the reciprocal lattice vector matrix:\n",
    "$$ \\mathrm{RLUmatrix} = \\begin{pmatrix}1.187 & 0.594 & 0.0\\\\ 0.0 & -1.028 & 0.0 \\\\ 0.0 & 0.0 & -0.554\\end{pmatrix}$$\n",
    "\n",
    "For this specific experiment, the scattering plane was ($H$,$K$,$0$) and there is a rotational offset in the sample rotation $A_3$, the resulting $UB$ matrix becomes\n",
    "\n",
    "$$UB = \\begin{pmatrix}1.097 & 0.155 & 0.0 \\\\ -0.454 & -1.177 & 0.0\\\\ 0.0 & 0.0 & -0.554 \\end{pmatrix}$$\n",
    "\n",
    "The two projection vectors being (1,0,0) and (0,1,0) the convertion matrix taking the projection along the two vectors to ($Q_x$, $Q_y$) is\n",
    "$$convert = \\begin{pmatrix}1.187 & 0.594 \\\\ 0.0 & -1.028\\end{pmatrix}$$.\n",
    "\n",
    "As seen, the transformation is non-orthogonal and thus results in the axis shown above. For the “mis-alignment” the rotation angle to correct is found to be -22.5$^\\circ$. That is, all of the data is rotated by -22.5$^\\circ$ before being plotted in the RLU axis.\n",
    "\n",
    "### Example 2\n",
    "For the second example shown above, with the cartesian unit cell but the non-trivial scattering plane, the matrices are:\n",
    "$$UB = \\begin{pmatrix}-0.418 &  0.341 & 0.341 \\\\ 0.482 & 0.296 & 0.296\\\\ 0.0 & 0.451 & -0.451\\end{pmatrix}$$\n",
    "$$RLUmatrix = \\begin{pmatrix}0.638 &  0.0 & 0.0 \\\\ 0.0 & 0.638 & 0.0\\\\ 0.0 & 0.0 & 0.638\\end{pmatrix}$$\n",
    "$$convert = \\begin{pmatrix} 0.638 &  0.0 \\\\ 0.0 & 0.638 \\end{pmatrix}$$"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "29f7d0ca",
   "metadata": {},
   "source": [
    "## Tick Marks\n",
    "\n",
    "The discussion of the location of the tick marks is quite long and deserves a section of it’s own. It all revolves about the usage of the curve linear axis, which is provided as an experimental/development feature in the matplotlib package. \n",
    "\n",
    "Codewise, what is done is to create two subclasses of the <code>mticker.MultipleLocator</code> and the <code>mticker.MaxLocator</code> classes designed to calculate the positions of tick marks using two different methods. The <code>MaxLocator</code> expects a integer input signifying the maximal number of ticks along the given axis, which are chosen at ‘suitable’ positions and will update with zooming and panning.\n",
    "\n",
    "The <code>MultipleLocator</code> is designed to place tick marks at multiples of a given value. That is, if the base is 0.1, tick marks are located at all integer multiples of 0.1 inside of the viewable area. For static or panning, this solution is suitable and sufficient, but allowing the user to zoom requires the class to be more complex. In order to find a suitable base value, the class finds the window limits and given a wanted number of tick marks it finds the average wanted distance between the marks. As to be scale invariant this number is mapped to a value between 0.1 and 1, where it is compared to a predefined list of allowed fractions (1/1,1/2,1/3,1/4,1/5) where the closest is used.\n",
    "\n",
    "With the new tick marks found, a hook is created to overview the panning and zooming of the axis and force an update of the drawing of tick marks."
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "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": "3.9.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}