{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "source": [
    "# Tutorial 04: Dzyaloshinskii-Moriya energy term\n",
    "\n",
    "Dzyaloshinskii-Moriya energy density, depending on the crystallographic class, is computed as\n",
    "\n",
    "$$\\mathbf{w_\\text{dmi}} = \\left\\{\n",
    "\\begin{array}{ll}\n",
    "D \\mathbf{m} \\cdot (\\nabla \\times \\mathbf{m}), & \\text{for}\\,\\,T(O) \\\\\n",
    "D ( \\mathbf{m} \\cdot \\nabla m_{z} - m_{z} \\nabla \\cdot \\mathbf{m}), & \\text{for}\\,\\,C_{nv} \\\\\n",
    "D\\mathbf{m} \\cdot \\left( \\frac{\\partial \\mathbf{m}}{\\partial x} \\times \\hat{x} - \\frac{\\partial \\mathbf{m}}{\\partial y} \\times \\hat{y} \\right), & \\text{for}\\,\\,D_{2d} \\\\\n",
    "\\end{array}\n",
    "\\right. $$\n",
    "\n",
    "where $\\mathbf{m}$ is the normalised ($|\\mathbf{m}|=1$) magnetisation, and $D$ is the DM energy constant. DMI energy term tends to align neighbouring magnetic moments perpendicular to each other.\n",
    "\n",
    "In `oommfc`, $\\mathbf{m}$ is a part of the magnetisation field `system.m`. Therefore, only DMI energy constant $D$ should be provided as an input parameter to uniquely define the Exchange energy term. $D$ can be constant in space or spatially varying.\n",
    "\n",
    "## Spatially constant $D$\n",
    "\n",
    "Let us start by assembling a simple simple simulation where $D$ does not vary in space. The sample is a \"one-dimensional\" chain of magnetic moments. We are going to choose $C_{nv}$ as the crystallographic class."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import discretisedfield as df\n",
    "import micromagneticmodel as mm\n",
    "\n",
    "import oommfc as oc\n",
    "\n",
    "p1 = (-10e-9, 0, 0)\n",
    "p2 = (10e-9, 1e-9, 1e-9)\n",
    "cell = (1e-9, 1e-9, 1e-9)\n",
    "region = df.Region(p1=p1, p2=p2)\n",
    "mesh = df.Mesh(region=region, cell=cell)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The mesh is"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": [
     "nbval-ignore-output"
    ]
   },
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "5036529c25f749fab4474120b48d5f8a",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "mesh.k3d()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The system has a Hamiltonian, which consists of only DMI energy term."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "D = 1e-3  # Dzyaloshinksii-Moriya energy constant (J/m**2)\n",
    "system = mm.System(name=\"dmi_constant_D\")\n",
    "system.energy = mm.DMI(D=D, crystalclass=\"Cnv_z\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We are going to minimise the system's energy using `oommfc.MinDriver` later. Therefore, we do not have to define the system's dynamics equation. Finally, we need to define the system's magnetisation (`system.m`). We are going to make it random with $M_\\text{s}=8\\times10^{5} \\,\\text{Am}^{-1}$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "import random\n",
    "\n",
    "import discretisedfield as df\n",
    "\n",
    "Ms = 8e5  # saturation magnetisation (A/m)\n",
    "\n",
    "\n",
    "def m_fun(pos):\n",
    "    \"\"\"Return random 3d vectors for initial random magnetisation\"\"\"\n",
    "    return [2 * random.random() - 1, 2 * random.random() - 1, 2 * random.random() - 1]\n",
    "\n",
    "\n",
    "system.m = df.Field(mesh, nvdim=3, value=m_fun, norm=Ms)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The magnetisation, we have set as initial values looks like:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": [
     "nbval-ignore-output"
    ]
   },
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "ebf3d7c340454292abea64d8762bd43a",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "system.m.k3d.vector(color_field=system.m.z)  # k3d plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 800x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "system.m.sel(\"y\").mpl()  # matplotlib plot"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now, we can minimise the system's energy by using `oommfc.MinDriver`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Running OOMMF (ExeOOMMFRunner)[2023/10/18 12:35]... (0.4 s)\n"
     ]
    }
   ],
   "source": [
    "md = oc.MinDriver()\n",
    "md.drive(system)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We expect that now all magnetic moments are aligned orthogonally to each other."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": [
     "nbval-ignore-output"
    ]
   },
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "6bd0fde890064699a5814efcc3e2ee03",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "system.m.k3d.vector(color_field=system.m.z)  # k3d plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 800x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "system.m.sel(\"y\").mpl()  # matplotlib plot"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Spatially varying $D$\n",
    "\n",
    "In the case of DMI, there is only one way how a parameter can be made spatially varying - using a dictionary.\n",
    "\n",
    "In order to define a parameter using a dictionary, regions must be defined in the mesh. Regions are defined as a dictionary, whose keys are the strings and values are `discretisedfield.Region` objects, which take two corner points of the region as input parameters. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "p1 = (-10e-9, 0, 0)\n",
    "p2 = (10e-9, 1e-9, 1e-9)\n",
    "cell = (1e-9, 1e-9, 1e-9)\n",
    "subregions = {\n",
    "    \"region1\": df.Region(p1=(-10e-9, 0, 0), p2=(0, 1e-9, 1e-9)),\n",
    "    \"region2\": df.Region(p1=(0, 0, 0), p2=(10e-9, 1e-9, 1e-9)),\n",
    "}\n",
    "region = df.Region(p1=p1, p2=p2)\n",
    "mesh = df.Mesh(region=region, cell=cell, subregions=subregions)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The regions we have defined are:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": [
     "nbval-ignore-output"
    ]
   },
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "d88e40c6de7b4548ab9f04cd01a01867",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "mesh.k3d.subregions()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let us say there is no DMI energy ($D=0$) in region 1, whereas in region 2 $D=10^{-3} \\,\\text{Jm}^{-2}$. Unlike Zeeman and anisotropy energy terms, the DMI energy constant is defined between cells. Therefore, it is necessary to also define the value of $D$ between the two regions. This is achieved by adding another item to the dictionary with key `'region1:region2'`. The object `D` is now defined as a dictionary:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "D = {\"region1\": 0, \"region2\": 1e-3, \"region1:region2\": 0.5e-3}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The system object is"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "system = mm.System(name=\"dmi_dict_D\")\n",
    "system.energy = mm.DMI(D=D, crystalclass=\"Cnv_z\")\n",
    "system.m = df.Field(mesh, nvdim=3, value=m_fun, norm=Ms)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Its initial (and random) magnetisation is"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": [
     "nbval-ignore-output"
    ]
   },
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "d820d73df8314a8c9e121c077244c8c1",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 800x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "system.m.k3d.vector(color_field=system.m.z)\n",
    "system.m.sel(\"y\").mpl()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "After we minimise the energy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Running OOMMF (ExeOOMMFRunner)[2023/10/18 12:35]... (0.2 s)\n"
     ]
    }
   ],
   "source": [
    "md.drive(system)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The magnetisation is as we expected. The magnetisation remains random in region 1, and it is orthogonally aligned in region 2."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": [
     "nbval-ignore-output"
    ]
   },
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "d7cc0c86c8704f3e992c1f5f46dc94d6",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 800x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "system.m.k3d.vector(color_field=system.m.z)\n",
    "system.m.sel(\"y\").mpl()"
   ]
  }
 ],
 "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": "3.10.12"
  },
  "widgets": {
   "application/vnd.jupyter.widget-state+json": {
    "state": {
     "0179446af3f34fc48b031d70b767f02a": {
      "model_module": "@jupyter-widgets/output",
      "model_module_version": "1.0.0",
      "model_name": "OutputModel",
      "state": {
       "layout": "IPY_MODEL_bfe3eb25bbb44630a1efd848d5214be5",
       "outputs": [
        {
         "data": {
          "application/vnd.jupyter.widget-view+json": {
           "model_id": "a2fe160c6bbc40838ff37c8fb6e12924",
           "version_major": 2,
           "version_minor": 0
          },
          "text/plain": "Plot(antialias=3, axes=['x', 'y', 'z'], axes_helper=1.0, background_color=16777215, camera_animation=[], camer…"
         },
         "metadata": {},
         "output_type": "display_data"
        }
       ]
      }
     },
     "0639b17ed43942d7b806d086e97d1c6f": {
      "model_module": "@jupyter-widgets/output",
      "model_module_version": "1.0.0",
      "model_name": "OutputModel",
      "state": {
       "layout": "IPY_MODEL_3356ecb317cf47b49a5c09cba8d69a6e",
       "outputs": [
        {
         "data": {
          "application/vnd.jupyter.widget-view+json": {
           "model_id": "20b8146d52c142c9be9f94a7f10b37b2",
           "version_major": 2,
           "version_minor": 0
          },
          "text/plain": "Plot(antialias=3, axes=['x', 'y', 'z'], axes_helper=1.0, background_color=16777215, camera_animation=[], camer…"
         },
         "metadata": {},
         "output_type": "display_data"
        }
       ]
      }
     },
     "0b673c1e7e0844a9a43fb2f47068015e": {
      "buffers": [
       {
        "data": "eISHAHiEhwB4hIcAeISHAHV0dAB1dHQAVczhAFXM4QB2lZwAdpWcAGxPRABsT0QANeX+ADXl/gBtQzEAbUMxAG1CLwBtQi8AeIuQAHiLkABkuswAZLrMAHRycgB0cnIAWMneAFjJ3gB3j5UAd4+VAE4iAABOIgAAStXtAErV7QB4iY4AeImOADjo/gA46P4Abj0mAG49JgBTzuQAU87kAA==",
        "encoding": "base64",
        "path": [
         "colors",
         "data"
        ]
       },
       {
        "data": "AACAPwAAAAAAAAAAAAAAAAAAAAAAAIA/AAAAAAAAAAAAAAAAAAAAAAAAgD8AAAAAAAAAAAAAAAAAAAAAAACAPw==",
        "encoding": "base64",
        "path": [
         "model_matrix",
         "data"
        ]
       },
       {
        "data": "EeIdwfi/dD9SmgA/AAAQwWQlTj9doQA/LfL7wDLkcT81qhM/2p/bwMbBIj7yiEQ+s2yowBThgz8umdg+O3aDwG4XWT8wB0M/nQp0wPZ8VD5I4809lm47wOsxiT5ZM1M/XQLRv358dz98AVQ/2+tfvzgRTz2wl/E+6LQOPjAXZT+ijYU+yEKEPxyJID6iQxY/DHIHQBbrLj4q31A+rs1CQCweXT81E+U+FyCGQDbHFD/2xX0/Dre7QFgRTT8Gcx8+FrDRQJCgij8pr/Q+h970QGh52j1cQ789XPkIQZ1udj8WrVo/RkoRQXdmQj9oHDw+",
        "encoding": "base64",
        "path": [
         "origins",
         "data"
        ]
       },
       {
        "data": "JkI8P/F/ab+EUZq7AACAP8hKHL/OXKG71iI/P2PIY7+qUR2+pv05Px2fLj+Hux0/lWnyvifCh79Gmx0+SZxIv9suMr9hDga/6lQgP4XBFT8uh0w/rnRbPyqc7T6yZia/6BKIPvv4br/5Aii/ttc/P9kdZj8FhWY9jKU4P2AuSr+85PQ+4PRuP3K7Lz8MHTK+oG9EP3WKKD9rkBc/kJJpP1k8Or9XZtc9jP4dP7A5Jr7ti3u/23A7v68iGr99RjA/6ArYvR9Blb9uDTU96NCbvqZhST8pL1A/mVv5vTrdbL8sWjW/NrdWP+7MBL/M8SE/",
        "encoding": "base64",
        "path": [
         "vectors",
         "data"
        ]
       }
      ],
      "model_module": "k3d",
      "model_module_version": "2.11.0",
      "model_name": "ObjectModel",
      "state": {
       "_view_count": null,
       "_view_module": null,
       "_view_module_version": "",
       "_view_name": null,
       "colorLegend": false,
       "colors": {
        "data": {},
        "dtype": "uint32",
        "shape": [
         20,
         2
        ]
       },
       "compression_level": 0,
       "head_color": 255,
       "head_size": 1,
       "id": 140597839836400,
       "label_size": 1,
       "labels": [],
       "line_width": 0.01,
       "model_matrix": {
        "data": {},
        "dtype": "float32",
        "shape": [
         4,
         4
        ]
       },
       "name": "Vectors #1",
       "origin_color": 255,
       "origins": {
        "data": {},
        "dtype": "float32",
        "shape": [
         20,
         3
        ]
       },
       "type": "Vectors",
       "use_head": true,
       "vectors": {
        "data": {},
        "dtype": "float32",
        "shape": [
         20,
         3
        ]
       },
       "visible": true
      }
     },
     "0e1f639a3136431a8194e12b23f7ed58": {
      "buffers": [
       {
        "data": "",
        "encoding": "base64",
        "path": [
         "attribute",
         "data"
        ]
       },
       {
        "data": "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",
        "encoding": "base64",
        "path": [
         "color_map",
         "data"
        ]
       },
       {
        "data": "",
        "encoding": "base64",
        "path": [
         "colors",
         "data"
        ]
       },
       {
        "data": "AACAPwAAAAAAAAAAAAAAAAAAAAAAAIA/AAAAAAAAAAAAAAAAAAAAAAAAgD8AAAAAAAAAAAAAAAAAAAAAAACAPw==",
        "encoding": "base64",
        "path": [
         "model_matrix",
         "data"
        ]
       },
       {
        "data": "",
        "encoding": "base64",
        "path": [
         "opacities",
         "data"
        ]
       },
       {
        "data": "",
        "encoding": "base64",
        "path": [
         "opacity_function",
         "data"
        ]
       },
       {
        "data": "",
        "encoding": "base64",
        "path": [
         "point_sizes",
         "data"
        ]
       },
       {
        "data": "AAAYwQAAAD8AAAA/AAAIwQAAAD8AAAA/AADwwAAAAD8AAAA/AADQwAAAAD8AAAA/AACwwAAAAD8AAAA/AACQwAAAAD8AAAA/AABgwAAAAD8AAAA/AAAgwAAAAD8AAAA/AADAvwAAAD8AAAA/AAAAvwAAAD8AAAA/AAAAPwAAAD8AAAA/AADAPwAAAD8AAAA/AAAgQAAAAD8AAAA/AABgQAAAAD8AAAA/AACQQAAAAD8AAAA/AACwQAAAAD8AAAA/AADQQAAAAD8AAAA/AADwQAAAAD8AAAA/AAAIQQAAAD8AAAA/AAAYQQAAAD8AAAA/",
        "encoding": "base64",
        "path": [
         "positions",
         "data"
        ]
       }
      ],
      "model_module": "k3d",
      "model_module_version": "2.11.0",
      "model_name": "ObjectModel",
      "state": {
       "_view_count": null,
       "_view_module": null,
       "_view_module_version": "",
       "_view_name": null,
       "attribute": {
        "data": {},
        "dtype": "float32",
        "shape": [
         0
        ]
       },
       "color": 5010096,
       "colorLegend": false,
       "color_map": {
        "data": {},
        "dtype": "float32",
        "shape": [
         1024
        ]
       },
       "color_range": [],
       "colors": {
        "data": {},
        "dtype": "uint32",
        "shape": [
         0
        ]
       },
       "compression_level": 0,
       "id": 140597839837168,
       "mesh_detail": 2,
       "model_matrix": {
        "data": {},
        "dtype": "float32",
        "shape": [
         4,
         4
        ]
       },
       "name": "Points #1",
       "opacities": {
        "data": {},
        "dtype": "float32",
        "shape": [
         0
        ]
       },
       "opacity": 1,
       "opacity_function": {
        "data": {},
        "dtype": "float32",
        "shape": [
         0
        ]
       },
       "point_size": 0.25,
       "point_sizes": {
        "data": {},
        "dtype": "float32",
        "shape": [
         0
        ]
       },
       "positions": {
        "data": {},
        "dtype": "float32",
        "shape": [
         20,
         3
        ]
       },
       "shader": "3dSpecular",
       "type": "Points",
       "visible": true
      }
     },
     "14177d1a0a794fb2ba3419d0d3544a8f": {
      "model_module": "@jupyter-widgets/output",
      "model_module_version": "1.0.0",
      "model_name": "OutputModel",
      "state": {
       "layout": "IPY_MODEL_6c347f36b6f64e12abfc79d2bef21431",
       "outputs": [
        {
         "data": {
          "application/vnd.jupyter.widget-view+json": {
           "model_id": "37fcb793244d486899933fc12a576e50",
           "version_major": 2,
           "version_minor": 0
          },
          "text/plain": "Plot(antialias=3, axes=['x', 'y', 'z'], axes_helper=1.0, background_color=16777215, camera_animation=[], camer…"
         },
         "metadata": {},
         "output_type": "display_data"
        }
       ]
      }
     },
     "1fc57b9c010644788bce107cee192e03": {
      "buffers": [
       {
        "data": "VCUAAFQlAABZyNwAWcjcAFTN4gBUzeIAV8rfAFfK3wBtXFUAbVxVAEjX7wBI1+8AeIqPAHiKjwBps8MAabPDAE4iAABOIgAAbEY2AGxGNgB0nKYAdJymAHExAABxMQAAbEw/AGxMPwBRJAAAUSQAAGO8zgBjvM4AdZigAHWYoABtXVcAbV1XAGxXTwBsV08AcDQMAHA0DAA46P4AOOj+AA==",
        "encoding": "base64",
        "path": [
         "colors",
         "data"
        ]
       },
       {
        "data": "AACAPwAAAAAAAAAAAAAAAAAAAAAAAIA/AAAAAAAAAAAAAAAAAAAAAAAAgD8AAAAAAAAAAAAAAAAAAAAAAACAPw==",
        "encoding": "base64",
        "path": [
         "model_matrix",
         "data"
        ]
       },
       {
        "data": "gegUwSYqrz5gInY/QrwMwZBDOz9SHQk+9dv6wCC8Gj/IEOk9QkvEwIZHAz80Wf49fa2lwB5rYT84jik/7qaUwF5jcz7geo49jg0/wG2W4T4hMNY++dkHwJUQiD4EEWI+TKXUv/vLJj9cw3k/IopUv1B/TD/1+UY/QnZUPyTwBT5WPqc+9gPXP+KkTj7dcmQ/eCYNQNpBFD465D8/2k1qQDzapT6Pm3c/eJSaQOpZeT7O/zs+DHShQLQ1Nz/u9bM+SBLRQAAAAAByvCc/4xz9QFqBRD+gXDA/wB0FQYZJUT+Rb2A/HCsVQWZs3z6AGCg8",
        "encoding": "base64",
        "path": [
         "origins",
         "data"
        ]
       },
       {
        "data": "ud/FvrOroT7BRGy/UIgXPz8O7b5XcTs/Tr8tP/zgVb7Ou0U/5ks7v2Hh0byzaUA/NSglvzzWQr/iOKa+vN2UPlFOBj9IYVw/ysmDv5ZM8z18Pyc+OzBBv9be7z5+9w4/YiqlPu0vm763hnO/RBQpP6D+GL/q8w2/hewov+4HPT9Tg7E+tB+4vo+tGD+65Ui/Q8wWPxPfNT/pkP++nd2kvolLtD4eN2+/gkcpvwtTAz8ZACI/SL9oP8/W3L4jFJg+PySJvQAAgD/K8Z6+Ns5Rv7UCCb+BcsG++o+4PguTIr8i30C/Ajm1PmZOAj48v3o/",
        "encoding": "base64",
        "path": [
         "vectors",
         "data"
        ]
       }
      ],
      "model_module": "k3d",
      "model_module_version": "2.11.0",
      "model_name": "ObjectModel",
      "state": {
       "_view_count": null,
       "_view_module": null,
       "_view_module_version": "",
       "_view_name": null,
       "colorLegend": false,
       "colors": {
        "data": {},
        "dtype": "uint32",
        "shape": [
         20,
         2
        ]
       },
       "compression_level": 0,
       "head_color": 255,
       "head_size": 1,
       "id": 140596210471984,
       "label_size": 1,
       "labels": [],
       "line_width": 0.01,
       "model_matrix": {
        "data": {},
        "dtype": "float32",
        "shape": [
         4,
         4
        ]
       },
       "name": "Vectors #1",
       "origin_color": 255,
       "origins": {
        "data": {},
        "dtype": "float32",
        "shape": [
         20,
         3
        ]
       },
       "type": "Vectors",
       "use_head": true,
       "vectors": {
        "data": {},
        "dtype": "float32",
        "shape": [
         20,
         3
        ]
       },
       "visible": true
      }
     },
     "20b8146d52c142c9be9f94a7f10b37b2": {
      "model_module": "k3d",
      "model_module_version": "2.11.0",
      "model_name": "PlotModel",
      "state": {
       "_backend_version": "2.11.0",
       "_dom_classes": [],
       "_view_count": null,
       "antialias": 3,
       "auto_rendering": true,
       "axes": [
        "x\\,\\text{ (nm)}",
        "y\\,\\text{ (nm)}",
        "z\\,\\text{ (nm)}"
       ],
       "axes_helper": 1,
       "background_color": 16777215,
       "camera": [
        16.25208379679217,
        -23.831855771739693,
        2.12212377877615,
        0.030846595764160156,
        0.5000000298023224,
        0.5000000586733222,
        0,
        0,
        1
       ],
       "camera_animation": [],
       "camera_auto_fit": true,
       "camera_damping_factor": 0,
       "camera_fov": 60,
       "camera_mode": "trackball",
       "camera_no_pan": false,
       "camera_no_rotate": false,
       "camera_no_zoom": false,
       "camera_pan_speed": 0.3,
       "camera_rotate_speed": 1,
       "camera_zoom_speed": 1.2,
       "clipping_planes": [],
       "colorbar_object_id": -1,
       "colorbar_scientific": false,
       "fps": 25,
       "fps_meter": false,
       "grid": [
        -1,
        -1,
        -1,
        1,
        1,
        1
       ],
       "grid_auto_fit": true,
       "grid_color": 15132390,
       "grid_visible": true,
       "height": 512,
       "label_color": 4473924,
       "layout": "IPY_MODEL_35f923428e994f5aadcacdf4873fe7f5",
       "lighting": 1.5,
       "manipulate_mode": "translate",
       "menu_visibility": true,
       "mode": "view",
       "name": null,
       "object_ids": [
        140597179609968,
        140597179610064
       ],
       "rendering_steps": 1,
       "screenshot": "",
       "screenshot_scale": 2,
       "snapshot": "",
       "snapshot_type": "full",
       "time": 0,
       "voxel_paint_color": 0
      }
     },
     "22709b8b6a4e4915a864c53d5e83d2b9": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "278745247e0c40e78e5086ba1bdb7a3f": {
      "model_module": "k3d",
      "model_module_version": "2.11.0",
      "model_name": "PlotModel",
      "state": {
       "_backend_version": "2.11.0",
       "_dom_classes": [],
       "_view_count": null,
       "antialias": 3,
       "auto_rendering": true,
       "axes": [
        "x\\,\\text{ (nm)}",
        "y\\,\\text{ (nm)}",
        "z\\,\\text{ (nm)}"
       ],
       "axes_helper": 1,
       "background_color": 16777215,
       "camera": [
        16.251555606228855,
        -24.09432410374693,
        2.139621607223303,
        -0.14466047286987305,
        0.5000000149011612,
        0.4999999993134032,
        0,
        0,
        1
       ],
       "camera_animation": [],
       "camera_auto_fit": true,
       "camera_damping_factor": 0,
       "camera_fov": 60,
       "camera_mode": "trackball",
       "camera_no_pan": false,
       "camera_no_rotate": false,
       "camera_no_zoom": false,
       "camera_pan_speed": 0.3,
       "camera_rotate_speed": 1,
       "camera_zoom_speed": 1.2,
       "clipping_planes": [],
       "colorbar_object_id": -1,
       "colorbar_scientific": false,
       "fps": 25,
       "fps_meter": false,
       "grid": [
        -1,
        -1,
        -1,
        1,
        1,
        1
       ],
       "grid_auto_fit": true,
       "grid_color": 15132390,
       "grid_visible": true,
       "height": 512,
       "label_color": 4473924,
       "layout": "IPY_MODEL_bc3d7637eb034fbb8b79f47c93348e83",
       "lighting": 1.5,
       "manipulate_mode": "translate",
       "menu_visibility": true,
       "mode": "view",
       "name": null,
       "object_ids": [
        140596209962528,
        140596210484464
       ],
       "rendering_steps": 1,
       "screenshot": "",
       "screenshot_scale": 2,
       "snapshot": "",
       "snapshot_type": "full",
       "time": 0,
       "voxel_paint_color": 0
      }
     },
     "3356ecb317cf47b49a5c09cba8d69a6e": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "35f923428e994f5aadcacdf4873fe7f5": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "37fcb793244d486899933fc12a576e50": {
      "model_module": "k3d",
      "model_module_version": "2.11.0",
      "model_name": "PlotModel",
      "state": {
       "_backend_version": "2.11.0",
       "_dom_classes": [],
       "_view_count": null,
       "antialias": 3,
       "auto_rendering": true,
       "axes": [
        "x\\,\\text{(nm)}",
        "y\\,\\text{(nm)}",
        "z\\,\\text{(nm)}"
       ],
       "axes_helper": 1,
       "background_color": 16777215,
       "camera": [
        16.707952970489703,
        -24.636929447073253,
        2.175795296471578,
        -0.04999999422580004,
        0.5,
        0.5,
        0,
        0,
        1
       ],
       "camera_animation": [],
       "camera_auto_fit": true,
       "camera_damping_factor": 0,
       "camera_fov": 60,
       "camera_mode": "trackball",
       "camera_no_pan": false,
       "camera_no_rotate": false,
       "camera_no_zoom": false,
       "camera_pan_speed": 0.3,
       "camera_rotate_speed": 1,
       "camera_zoom_speed": 1.2,
       "clipping_planes": [],
       "colorbar_object_id": -1,
       "colorbar_scientific": false,
       "fps": 25,
       "fps_meter": false,
       "grid": [
        -1,
        -1,
        -1,
        1,
        1,
        1
       ],
       "grid_auto_fit": true,
       "grid_color": 15132390,
       "grid_visible": true,
       "height": 512,
       "label_color": 4473924,
       "layout": "IPY_MODEL_c0c0e36472e34ce38a95ed5a219bcf54",
       "lighting": 1.5,
       "manipulate_mode": "translate",
       "menu_visibility": true,
       "mode": "view",
       "name": null,
       "object_ids": [
        140597180501392
       ],
       "rendering_steps": 1,
       "screenshot": "",
       "screenshot_scale": 2,
       "snapshot": "",
       "snapshot_type": "full",
       "time": 0,
       "voxel_paint_color": 0
      }
     },
     "3ad20828d625498285a40eee7a9dbde4": {
      "buffers": [
       {
        "data": "",
        "encoding": "base64",
        "path": [
         "attribute",
         "data"
        ]
       },
       {
        "data": "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",
        "encoding": "base64",
        "path": [
         "color_map",
         "data"
        ]
       },
       {
        "data": "",
        "encoding": "base64",
        "path": [
         "colors",
         "data"
        ]
       },
       {
        "data": "AACAPwAAAAAAAAAAAAAAAAAAAAAAAIA/AAAAAAAAAAAAAAAAAAAAAAAAgD8AAAAAAAAAAAAAAAAAAAAAAACAPw==",
        "encoding": "base64",
        "path": [
         "model_matrix",
         "data"
        ]
       },
       {
        "data": "",
        "encoding": "base64",
        "path": [
         "opacities",
         "data"
        ]
       },
       {
        "data": "",
        "encoding": "base64",
        "path": [
         "opacity_function",
         "data"
        ]
       },
       {
        "data": "",
        "encoding": "base64",
        "path": [
         "point_sizes",
         "data"
        ]
       },
       {
        "data": "AAAYwQAAAD8AAAA/AAAIwQAAAD8AAAA/AADwwAAAAD8AAAA/AADQwAAAAD8AAAA/AACwwAAAAD8AAAA/AACQwAAAAD8AAAA/AABgwAAAAD8AAAA/AAAgwAAAAD8AAAA/AADAvwAAAD8AAAA/AAAAvwAAAD8AAAA/AAAAPwAAAD8AAAA/AADAPwAAAD8AAAA/AAAgQAAAAD8AAAA/AABgQAAAAD8AAAA/AACQQAAAAD8AAAA/AACwQAAAAD8AAAA/AADQQAAAAD8AAAA/AADwQAAAAD8AAAA/AAAIQQAAAD8AAAA/AAAYQQAAAD8AAAA/",
        "encoding": "base64",
        "path": [
         "positions",
         "data"
        ]
       }
      ],
      "model_module": "k3d",
      "model_module_version": "2.11.0",
      "model_name": "ObjectModel",
      "state": {
       "_view_count": null,
       "_view_module": null,
       "_view_module_version": "",
       "_view_name": null,
       "attribute": {
        "data": {},
        "dtype": "float32",
        "shape": [
         0
        ]
       },
       "color": 5010096,
       "colorLegend": false,
       "color_map": {
        "data": {},
        "dtype": "float32",
        "shape": [
         1024
        ]
       },
       "color_range": [],
       "colors": {
        "data": {},
        "dtype": "uint32",
        "shape": [
         0
        ]
       },
       "compression_level": 0,
       "id": 140597179610064,
       "mesh_detail": 2,
       "model_matrix": {
        "data": {},
        "dtype": "float32",
        "shape": [
         4,
         4
        ]
       },
       "name": "Points #1",
       "opacities": {
        "data": {},
        "dtype": "float32",
        "shape": [
         0
        ]
       },
       "opacity": 1,
       "opacity_function": {
        "data": {},
        "dtype": "float32",
        "shape": [
         0
        ]
       },
       "point_size": 0.25,
       "point_sizes": {
        "data": {},
        "dtype": "float32",
        "shape": [
         0
        ]
       },
       "positions": {
        "data": {},
        "dtype": "float32",
        "shape": [
         20,
         3
        ]
       },
       "shader": "3dSpecular",
       "type": "Points",
       "visible": true
      }
     },
     "3b2652cce1ae4b5f8c5d079acb44f0b7": {
      "buffers": [
       {
        "data": "VCUAAFQlAABTzuQAU87kAEzT6gBM0+oAUNHnAFDR5wBtXVcAbV1XADzf+AA83/gAeI6TAHiOkwBluckAZbnJAE4iAABOIgAAVCUAAFQlAABps8IAabPCADjo/gA46P4AbExAAGxMQABUJQAAVCUAAGmzwgBps8IAOOj+ADjo/gBsTEAAbExAAFQlAABUJQAAabPCAGmzwgA46P4AOOj+AA==",
        "encoding": "base64",
        "path": [
         "colors",
         "data"
        ]
       },
       {
        "data": "AACAPwAAAAAAAAAAAAAAAAAAAAAAAIA/AAAAAAAAAAAAAAAAAAAAAAAAgD8AAAAAAAAAAAAAAAAAAAAAAACAPw==",
        "encoding": "base64",
        "path": [
         "model_matrix",
         "data"
        ]
       },
       {
        "data": "zaUUwSJaqD6OC4A/bSINwS1CQD9kCtM9Psb7wO38HD9saKY9s07DwEaOAz8IfL09yc6kwOqgaT/IDi0/TAuVwBTAXD5QYAg9uUY8wEgG3z4KqtI++NAFwPrpez4G+Ek+umLWvwURKj8yA4I/zEZqvgEAAD8AAIA/AACAPwAAAD/IRmo+2UidPwAAAD8AAAAAAAAAQAAAAD9PbkU/lFtxQAAAAD///38/AACgQAAAAD+8Rmo+NlKnQAAAAD8AAAA0AADAQAAAAD9TbkU/yq34QAAAAD/9/38/AAAQQQAAAD+uRmo+G6kTQQAAAD8AAGA0",
        "encoding": "base64",
        "path": [
         "origins",
         "data"
        ]
       },
       {
        "data": "1ozWvrxLrz4dF4C/nU0kP1qEAL9nPUs/5GM8P2fnZ77lZVY/zxRLv4mR47z+oFA/dhMzv9NBU78eO7S+gmmhPvafET/2824/HOWOv+DmAz7ZVzU+QXhRvwMLAj/9Axs/0RWzPhREqL5jBoS/mtwKv5dymLMBAIC/AACAv5AG3DKc3Ao/ndwKP2tImDAAAIA///9/P/HDuC6e3Aq/oNwKvwXYyaz+/3+//f9/vxdLFa6i3Ao/pNwKP2JjTi78/38/+/9/P/+NFa+m3Aq/qNwKvx6xvC/6/3+/+f9/v6OHNjCp3Ao/qdwKP57zKzH5/38/",
        "encoding": "base64",
        "path": [
         "vectors",
         "data"
        ]
       }
      ],
      "model_module": "k3d",
      "model_module_version": "2.11.0",
      "model_name": "ObjectModel",
      "state": {
       "_view_count": null,
       "_view_module": null,
       "_view_module_version": "",
       "_view_name": null,
       "colorLegend": false,
       "colors": {
        "data": {},
        "dtype": "uint32",
        "shape": [
         20,
         2
        ]
       },
       "compression_level": 0,
       "head_color": 255,
       "head_size": 1,
       "id": 140597179609968,
       "label_size": 1,
       "labels": [],
       "line_width": 0.01,
       "model_matrix": {
        "data": {},
        "dtype": "float32",
        "shape": [
         4,
         4
        ]
       },
       "name": "Vectors #1",
       "origin_color": 255,
       "origins": {
        "data": {},
        "dtype": "float32",
        "shape": [
         20,
         3
        ]
       },
       "type": "Vectors",
       "use_head": true,
       "vectors": {
        "data": {},
        "dtype": "float32",
        "shape": [
         20,
         3
        ]
       },
       "visible": true
      }
     },
     "5ed019bc33e24f2a8b2a1567b7f35809": {
      "model_module": "k3d",
      "model_module_version": "2.11.0",
      "model_name": "PlotModel",
      "state": {
       "_backend_version": "2.11.0",
       "_dom_classes": [],
       "_view_count": null,
       "antialias": 3,
       "auto_rendering": true,
       "axes": [
        "x\\,\\text{ (nm)}",
        "y\\,\\text{ (nm)}",
        "z\\,\\text{ (nm)}"
       ],
       "axes_helper": 1,
       "background_color": 16777215,
       "camera": [
        16.12608488315921,
        -23.70132315031559,
        2.1134215433543995,
        -0.008130550384521484,
        0.5,
        0.5,
        0,
        0,
        1
       ],
       "camera_animation": [],
       "camera_auto_fit": true,
       "camera_damping_factor": 0,
       "camera_fov": 60,
       "camera_mode": "trackball",
       "camera_no_pan": false,
       "camera_no_rotate": false,
       "camera_no_zoom": false,
       "camera_pan_speed": 0.3,
       "camera_rotate_speed": 1,
       "camera_zoom_speed": 1.2,
       "clipping_planes": [],
       "colorbar_object_id": -1,
       "colorbar_scientific": false,
       "fps": 25,
       "fps_meter": false,
       "grid": [
        -1,
        -1,
        -1,
        1,
        1,
        1
       ],
       "grid_auto_fit": true,
       "grid_color": 15132390,
       "grid_visible": true,
       "height": 512,
       "label_color": 4473924,
       "layout": "IPY_MODEL_22709b8b6a4e4915a864c53d5e83d2b9",
       "lighting": 1.5,
       "manipulate_mode": "translate",
       "menu_visibility": true,
       "mode": "view",
       "name": null,
       "object_ids": [
        140596210471984,
        140596210353488
       ],
       "rendering_steps": 1,
       "screenshot": "",
       "screenshot_scale": 2,
       "snapshot": "",
       "snapshot_type": "full",
       "time": 0,
       "voxel_paint_color": 0
      }
     },
     "641ef33648a641e8ab71f8fcb96f79f2": {
      "buffers": [
       {
        "data": "",
        "encoding": "base64",
        "path": [
         "attribute",
         "data"
        ]
       },
       {
        "data": "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",
        "encoding": "base64",
        "path": [
         "color_map",
         "data"
        ]
       },
       {
        "data": "",
        "encoding": "base64",
        "path": [
         "colors",
         "data"
        ]
       },
       {
        "data": "AACAPwAAAAAAAAAAAAAAAAAAAAAAAIA/AAAAAAAAAAAAAAAAAAAAAAAAgD8AAAAAAAAAAAAAAAAAAAAAAACAPw==",
        "encoding": "base64",
        "path": [
         "model_matrix",
         "data"
        ]
       },
       {
        "data": "",
        "encoding": "base64",
        "path": [
         "opacities",
         "data"
        ]
       },
       {
        "data": "",
        "encoding": "base64",
        "path": [
         "opacity_function",
         "data"
        ]
       },
       {
        "data": "",
        "encoding": "base64",
        "path": [
         "point_sizes",
         "data"
        ]
       },
       {
        "data": "AAAYwQAAAD8AAAA/AAAIwQAAAD8AAAA/AADwwAAAAD8AAAA/AADQwAAAAD8AAAA/AACwwAAAAD8AAAA/AACQwAAAAD8AAAA/AABgwAAAAD8AAAA/AAAgwAAAAD8AAAA/AADAvwAAAD8AAAA/AAAAvwAAAD8AAAA/AAAAPwAAAD8AAAA/AADAPwAAAD8AAAA/AAAgQAAAAD8AAAA/AABgQAAAAD8AAAA/AACQQAAAAD8AAAA/AACwQAAAAD8AAAA/AADQQAAAAD8AAAA/AADwQAAAAD8AAAA/AAAIQQAAAD8AAAA/AAAYQQAAAD8AAAA/",
        "encoding": "base64",
        "path": [
         "positions",
         "data"
        ]
       }
      ],
      "model_module": "k3d",
      "model_module_version": "2.11.0",
      "model_name": "ObjectModel",
      "state": {
       "_view_count": null,
       "_view_module": null,
       "_view_module_version": "",
       "_view_name": null,
       "attribute": {
        "data": {},
        "dtype": "float32",
        "shape": [
         0
        ]
       },
       "color": 5010096,
       "colorLegend": false,
       "color_map": {
        "data": {},
        "dtype": "float32",
        "shape": [
         1024
        ]
       },
       "color_range": [],
       "colors": {
        "data": {},
        "dtype": "uint32",
        "shape": [
         0
        ]
       },
       "compression_level": 0,
       "id": 140596210353488,
       "mesh_detail": 2,
       "model_matrix": {
        "data": {},
        "dtype": "float32",
        "shape": [
         4,
         4
        ]
       },
       "name": "Points #1",
       "opacities": {
        "data": {},
        "dtype": "float32",
        "shape": [
         0
        ]
       },
       "opacity": 1,
       "opacity_function": {
        "data": {},
        "dtype": "float32",
        "shape": [
         0
        ]
       },
       "point_size": 0.25,
       "point_sizes": {
        "data": {},
        "dtype": "float32",
        "shape": [
         0
        ]
       },
       "positions": {
        "data": {},
        "dtype": "float32",
        "shape": [
         20,
         3
        ]
       },
       "shader": "3dSpecular",
       "type": "Points",
       "visible": true
      }
     },
     "6c347f36b6f64e12abfc79d2bef21431": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "6d0e4d60b3e24a17ab75029571d433d3": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "8820c0f270864ed7842973c43a29da20": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "8f7ab83509e44d72a8ae2dca046a9ab8": {
      "buffers": [
       {
        "data": "sHJMAFKE3QA=",
        "encoding": "base64",
        "path": [
         "color_map",
         "data"
        ]
       },
       {
        "data": "AACgQQAAAAAAAAAAAAAAAAAAAAAAAIA/AAAAAAAAAD8AAAAAAAAAAAAAgD8AAAA/AAAAAAAAAAAAAAAAAACAPw==",
        "encoding": "base64",
        "path": [
         "model_matrix",
         "data"
        ]
       },
       {
        "data": "AQEBAQEBAQEBAQEBAQEBAQEBAQI=",
        "encoding": "base64",
        "path": [
         "voxels",
         "data"
        ]
       }
      ],
      "model_module": "k3d",
      "model_module_version": "2.11.0",
      "model_name": "ObjectModel",
      "state": {
       "_view_count": null,
       "_view_module": null,
       "_view_module_version": "",
       "_view_name": null,
       "colorLegend": false,
       "color_map": {
        "data": {},
        "dtype": "uint32",
        "shape": [
         2
        ]
       },
       "compression_level": 0,
       "id": 140596245188128,
       "model_matrix": {
        "data": {},
        "dtype": "float32",
        "shape": [
         4,
         4
        ]
       },
       "name": "Voxels #1",
       "opacity": 1,
       "outlines": false,
       "outlines_color": 0,
       "type": "Voxels",
       "visible": true,
       "voxels": {
        "data": {},
        "dtype": "uint8",
        "shape": [
         1,
         1,
         20
        ]
       },
       "wireframe": false
      }
     },
     "93f69cff4494445ba3acb33940592716": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "a2fe160c6bbc40838ff37c8fb6e12924": {
      "model_module": "k3d",
      "model_module_version": "2.11.0",
      "model_name": "PlotModel",
      "state": {
       "_backend_version": "2.11.0",
       "_dom_classes": [],
       "_view_count": null,
       "antialias": 3,
       "auto_rendering": true,
       "axes": [
        "x\\,\\text{ (nm)}",
        "y\\,\\text{ (nm)}",
        "z\\,\\text{ (nm)}"
       ],
       "axes_helper": 1,
       "background_color": 16777215,
       "camera": [
        16.513133545467245,
        -24.230944841726103,
        2.1487296298207603,
        0.025836944580078125,
        0.5000000596046448,
        0.4999999697320163,
        0,
        0,
        1
       ],
       "camera_animation": [],
       "camera_auto_fit": true,
       "camera_damping_factor": 0,
       "camera_fov": 60,
       "camera_mode": "trackball",
       "camera_no_pan": false,
       "camera_no_rotate": false,
       "camera_no_zoom": false,
       "camera_pan_speed": 0.3,
       "camera_rotate_speed": 1,
       "camera_zoom_speed": 1.2,
       "clipping_planes": [],
       "colorbar_object_id": -1,
       "colorbar_scientific": false,
       "fps": 25,
       "fps_meter": false,
       "grid": [
        -1,
        -1,
        -1,
        1,
        1,
        1
       ],
       "grid_auto_fit": true,
       "grid_color": 15132390,
       "grid_visible": true,
       "height": 512,
       "label_color": 4473924,
       "layout": "IPY_MODEL_d0cdfc2163a94de1b5cc9ad91eb6e69e",
       "lighting": 1.5,
       "manipulate_mode": "translate",
       "menu_visibility": true,
       "mode": "view",
       "name": null,
       "object_ids": [
        140597839836400,
        140597839837168
       ],
       "rendering_steps": 1,
       "screenshot": "",
       "screenshot_scale": 2,
       "snapshot": "",
       "snapshot_type": "full",
       "time": 0,
       "voxel_paint_color": 0
      }
     },
     "b1509915ea67473e893945e521e33efd": {
      "model_module": "k3d",
      "model_module_version": "2.11.0",
      "model_name": "PlotModel",
      "state": {
       "_backend_version": "2.11.0",
       "_dom_classes": [],
       "_view_count": null,
       "antialias": 3,
       "auto_rendering": true,
       "axes": [
        "x\\,\\text{(nm)}",
        "y\\,\\text{(nm)}",
        "z\\,\\text{(nm)}"
       ],
       "axes_helper": 1,
       "background_color": 16777215,
       "camera": [
        16.707952970489703,
        -24.636929447073253,
        2.175795296471578,
        -0.04999999422580004,
        0.5,
        0.5,
        0,
        0,
        1
       ],
       "camera_animation": [],
       "camera_auto_fit": true,
       "camera_damping_factor": 0,
       "camera_fov": 60,
       "camera_mode": "trackball",
       "camera_no_pan": false,
       "camera_no_rotate": false,
       "camera_no_zoom": false,
       "camera_pan_speed": 0.3,
       "camera_rotate_speed": 1,
       "camera_zoom_speed": 1.2,
       "clipping_planes": [],
       "colorbar_object_id": -1,
       "colorbar_scientific": false,
       "fps": 25,
       "fps_meter": false,
       "grid": [
        -1,
        -1,
        -1,
        1,
        1,
        1
       ],
       "grid_auto_fit": true,
       "grid_color": 15132390,
       "grid_visible": true,
       "height": 512,
       "label_color": 4473924,
       "layout": "IPY_MODEL_8820c0f270864ed7842973c43a29da20",
       "lighting": 1.5,
       "manipulate_mode": "translate",
       "menu_visibility": true,
       "mode": "view",
       "name": null,
       "object_ids": [
        140596245188128
       ],
       "rendering_steps": 1,
       "screenshot": "",
       "screenshot_scale": 2,
       "snapshot": "",
       "snapshot_type": "full",
       "time": 0,
       "voxel_paint_color": 0
      }
     },
     "bc3d7637eb034fbb8b79f47c93348e83": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "bfe3eb25bbb44630a1efd848d5214be5": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "c0c0e36472e34ce38a95ed5a219bcf54": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "c1c14d4771a445d1ac153218775dafdf": {
      "buffers": [
       {
        "data": "caWwAHGlsAA46P4AOOj+AGxVTQBsVU0ATiIAAE4iAABxpbAAcaWwADjo/gA46P4AbFVNAGxVTQBOIgAATiIAAHGlsABxpbAAOOj+ADjo/gBsVU0AbFVNAE4iAABOIgAAcaWwAHGlsAA46P4AOOj+AGxVTQBsVU0ATiIAAE4iAABxpbAAcaWwADjo/gA46P4AbFVNAGxVTQBOIgAATiIAAA==",
        "encoding": "base64",
        "path": [
         "colors",
         "data"
        ]
       },
       {
        "data": "AACAPwAAAAAAAAAAAAAAAAAAAAAAAIA/AAAAAAAAAAAAAAAAAAAAAAAAgD8AAAAAAAAAAAAAAAAAAAAAAACAPw==",
        "encoding": "base64",
        "path": [
         "model_matrix",
         "data"
        ]
       },
       {
        "data": "AQAQwQAAAD+uIZQ+814LwQAAAD8AABg1////wAAAAD8o7zU/G0LJwAAAAD/3/38/AQCgwAAAAD+yIZQ+5b2WwAAAAD8AAAg1/v9/wAAAAD8l7zU/N4QSwAAAAD/4/38/AwCAvwAAAD+8IZQ+IO81vwAAAD8AAMA0AACgNAAAAD8e7zU/jvfaPwAAAD/8/38///8/QAAAAD/KIZQ+OoRSQAAAAD8AAEA0AACAQAAAAD8X7zU/4722QAAAAD/+/38/AADgQAAAAD/YIZQ+HkLpQAAAAD8AAAAzAAAAQQAAAD8S7zU/8V4bQQAAAD8AAIA/",
        "encoding": "base64",
        "path": [
         "origins",
         "data"
        ]
       },
       {
        "data": "7f9/v31Gba+kvNc+pLzXPgA9Tibt/38/7f9/P2lTDiqivNe+oLzXvgxgBKnu/3+/7v9/vy3WmKGcvNc+mLzXPtlQJKXv/38/8P9/PwTCyCSTvNe+j7zXvsxj1iTx/3+/8/9/v4tJUKaIvNc+grzXPk6BkSb0/38/9v9/P7gQE6V6vNe+crzXvh5xQ7H3/3+/+f9/v+4+nbBrvNc+ZLzXPj/Y+aT6/38//P9/P9Up1qNbvNe+VrzXvgBRlKX9/3+//v9/v4uwfqZRvNc+TbzXPt5LEyj//38/AACAP0wZsKlJvNe+R7zXvtL0BrEAAIC/",
        "encoding": "base64",
        "path": [
         "vectors",
         "data"
        ]
       }
      ],
      "model_module": "k3d",
      "model_module_version": "2.11.0",
      "model_name": "ObjectModel",
      "state": {
       "_view_count": null,
       "_view_module": null,
       "_view_module_version": "",
       "_view_name": null,
       "colorLegend": false,
       "colors": {
        "data": {},
        "dtype": "uint32",
        "shape": [
         20,
         2
        ]
       },
       "compression_level": 0,
       "head_color": 255,
       "head_size": 1,
       "id": 140596209962528,
       "label_size": 1,
       "labels": [],
       "line_width": 0.01,
       "model_matrix": {
        "data": {},
        "dtype": "float32",
        "shape": [
         4,
         4
        ]
       },
       "name": "Vectors #1",
       "origin_color": 255,
       "origins": {
        "data": {},
        "dtype": "float32",
        "shape": [
         20,
         3
        ]
       },
       "type": "Vectors",
       "use_head": true,
       "vectors": {
        "data": {},
        "dtype": "float32",
        "shape": [
         20,
         3
        ]
       },
       "visible": true
      }
     },
     "c93d64e5736e4ef1ae830be153ded9e9": {
      "model_module": "@jupyter-widgets/output",
      "model_module_version": "1.0.0",
      "model_name": "OutputModel",
      "state": {
       "layout": "IPY_MODEL_93f69cff4494445ba3acb33940592716",
       "outputs": [
        {
         "data": {
          "application/vnd.jupyter.widget-view+json": {
           "model_id": "5ed019bc33e24f2a8b2a1567b7f35809",
           "version_major": 2,
           "version_minor": 0
          },
          "text/plain": "Plot(antialias=3, axes=['x', 'y', 'z'], axes_helper=1.0, background_color=16777215, camera_animation=[], camer…"
         },
         "metadata": {},
         "output_type": "display_data"
        }
       ]
      }
     },
     "d0cdfc2163a94de1b5cc9ad91eb6e69e": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "d5a67821f40846e38523709c574f35d8": {
      "model_module": "@jupyter-widgets/output",
      "model_module_version": "1.0.0",
      "model_name": "OutputModel",
      "state": {
       "layout": "IPY_MODEL_6d0e4d60b3e24a17ab75029571d433d3",
       "outputs": [
        {
         "data": {
          "application/vnd.jupyter.widget-view+json": {
           "model_id": "b1509915ea67473e893945e521e33efd",
           "version_major": 2,
           "version_minor": 0
          },
          "text/plain": "Plot(antialias=3, axes=['x', 'y', 'z'], axes_helper=1.0, background_color=16777215, camera_animation=[], camer…"
         },
         "metadata": {},
         "output_type": "display_data"
        }
       ]
      }
     },
     "d9454cb4359e490e822954545cca0b0a": {
      "model_module": "@jupyter-widgets/output",
      "model_module_version": "1.0.0",
      "model_name": "OutputModel",
      "state": {
       "layout": "IPY_MODEL_de500e9a47f340ec9f0e9dd30fb4d9f5",
       "outputs": [
        {
         "data": {
          "application/vnd.jupyter.widget-view+json": {
           "model_id": "278745247e0c40e78e5086ba1bdb7a3f",
           "version_major": 2,
           "version_minor": 0
          },
          "text/plain": "Plot(antialias=3, axes=['x', 'y', 'z'], axes_helper=1.0, background_color=16777215, camera_animation=[], camer…"
         },
         "metadata": {},
         "output_type": "display_data"
        }
       ]
      }
     },
     "db5366622f6e4539bc6bc0aa5fceeba4": {
      "buffers": [
       {
        "data": "",
        "encoding": "base64",
        "path": [
         "attribute",
         "data"
        ]
       },
       {
        "data": "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",
        "encoding": "base64",
        "path": [
         "color_map",
         "data"
        ]
       },
       {
        "data": "",
        "encoding": "base64",
        "path": [
         "colors",
         "data"
        ]
       },
       {
        "data": "AACAPwAAAAAAAAAAAAAAAAAAAAAAAIA/AAAAAAAAAAAAAAAAAAAAAAAAgD8AAAAAAAAAAAAAAAAAAAAAAACAPw==",
        "encoding": "base64",
        "path": [
         "model_matrix",
         "data"
        ]
       },
       {
        "data": "",
        "encoding": "base64",
        "path": [
         "opacities",
         "data"
        ]
       },
       {
        "data": "",
        "encoding": "base64",
        "path": [
         "opacity_function",
         "data"
        ]
       },
       {
        "data": "",
        "encoding": "base64",
        "path": [
         "point_sizes",
         "data"
        ]
       },
       {
        "data": "AAAYwQAAAD8AAAA/AAAIwQAAAD8AAAA/AADwwAAAAD8AAAA/AADQwAAAAD8AAAA/AACwwAAAAD8AAAA/AACQwAAAAD8AAAA/AABgwAAAAD8AAAA/AAAgwAAAAD8AAAA/AADAvwAAAD8AAAA/AAAAvwAAAD8AAAA/AAAAPwAAAD8AAAA/AADAPwAAAD8AAAA/AAAgQAAAAD8AAAA/AABgQAAAAD8AAAA/AACQQAAAAD8AAAA/AACwQAAAAD8AAAA/AADQQAAAAD8AAAA/AADwQAAAAD8AAAA/AAAIQQAAAD8AAAA/AAAYQQAAAD8AAAA/",
        "encoding": "base64",
        "path": [
         "positions",
         "data"
        ]
       }
      ],
      "model_module": "k3d",
      "model_module_version": "2.11.0",
      "model_name": "ObjectModel",
      "state": {
       "_view_count": null,
       "_view_module": null,
       "_view_module_version": "",
       "_view_name": null,
       "attribute": {
        "data": {},
        "dtype": "float32",
        "shape": [
         0
        ]
       },
       "color": 5010096,
       "colorLegend": false,
       "color_map": {
        "data": {},
        "dtype": "float32",
        "shape": [
         1024
        ]
       },
       "color_range": [],
       "colors": {
        "data": {},
        "dtype": "uint32",
        "shape": [
         0
        ]
       },
       "compression_level": 0,
       "id": 140596210484464,
       "mesh_detail": 2,
       "model_matrix": {
        "data": {},
        "dtype": "float32",
        "shape": [
         4,
         4
        ]
       },
       "name": "Points #1",
       "opacities": {
        "data": {},
        "dtype": "float32",
        "shape": [
         0
        ]
       },
       "opacity": 1,
       "opacity_function": {
        "data": {},
        "dtype": "float32",
        "shape": [
         0
        ]
       },
       "point_size": 0.25,
       "point_sizes": {
        "data": {},
        "dtype": "float32",
        "shape": [
         0
        ]
       },
       "positions": {
        "data": {},
        "dtype": "float32",
        "shape": [
         20,
         3
        ]
       },
       "shader": "3dSpecular",
       "type": "Points",
       "visible": true
      }
     },
     "de500e9a47f340ec9f0e9dd30fb4d9f5": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "f4ee8587bc804deb849e2f2d0bee20bc": {
      "buffers": [
       {
        "data": "sHJMAFKE3QBoqFUAUk7EALNygQBgeJMAw4vaAIyMjAB0ucwAzbVkAA==",
        "encoding": "base64",
        "path": [
         "color_map",
         "data"
        ]
       },
       {
        "data": "AACgQQAAAAAAAAAAAAAAAAAAAAAAAIA/AAAAAAAAAD8AAAAAAAAAAAAAgD8AAAA/AAAAAAAAAAAAAAAAAACAPw==",
        "encoding": "base64",
        "path": [
         "model_matrix",
         "data"
        ]
       },
       {
        "data": "AQEBAQEBAQEBAQICAgICAgICAgI=",
        "encoding": "base64",
        "path": [
         "voxels",
         "data"
        ]
       }
      ],
      "model_module": "k3d",
      "model_module_version": "2.11.0",
      "model_name": "ObjectModel",
      "state": {
       "_view_count": null,
       "_view_module": null,
       "_view_module_version": "",
       "_view_name": null,
       "colorLegend": false,
       "color_map": {
        "data": {},
        "dtype": "uint32",
        "shape": [
         10
        ]
       },
       "compression_level": 0,
       "id": 140597180501392,
       "model_matrix": {
        "data": {},
        "dtype": "float32",
        "shape": [
         4,
         4
        ]
       },
       "name": "Voxels #1",
       "opacity": 1,
       "outlines": false,
       "outlines_color": 0,
       "type": "Voxels",
       "visible": true,
       "voxels": {
        "data": {},
        "dtype": "uint8",
        "shape": [
         1,
         1,
         20
        ]
       },
       "wireframe": false
      }
     }
    },
    "version_major": 2,
    "version_minor": 0
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}