diff --git a/tutorials/2-examples/DTEx203_particle_sizing.ipynb b/tutorials/2-examples/DTEx203_particle_sizing.ipynb index 3af9842f..7900d774 100644 --- a/tutorials/2-examples/DTEx203_particle_sizing.ipynb +++ b/tutorials/2-examples/DTEx203_particle_sizing.ipynb @@ -1,1201 +1,938 @@ { - "cells": [ - { - "cell_type": "raw", - "metadata": { - "vscode": { - "languageId": "raw" - } - }, - "source": [ - "# TODO: Complete example" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "metadata": { - "execution": { - "iopub.execute_input": "2022-06-30T10:14:50.508741Z", - "iopub.status.busy": "2022-06-30T10:14:50.508741Z", - "iopub.status.idle": "2022-06-30T10:14:52.554954Z", - "shell.execute_reply": "2022-06-30T10:14:52.554954Z" - } - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Requirement already satisfied: deeptrack in c:\\users\\gu\\deeptrack\\deeptrack-2.0 (1.2.0)\n", - "Requirement already satisfied: tensorflow in c:\\users\\gu\\appdata\\local\\programs\\python\\python310\\lib\\site-packages (from deeptrack) (2.9.1)\n", - "Requirement already satisfied: tensorflow-probability in c:\\users\\gu\\appdata\\local\\programs\\python\\python310\\lib\\site-packages (from deeptrack) (0.17.0)\n", - "Requirement already satisfied: numpy in c:\\users\\gu\\appdata\\local\\programs\\python\\python310\\lib\\site-packages (from deeptrack) (1.23.0)\n", - "Requirement already satisfied: scipy in c:\\users\\gu\\appdata\\local\\programs\\python\\python310\\lib\\site-packages (from deeptrack) (1.8.1)\n", - "Requirement already satisfied: pint in c:\\users\\gu\\appdata\\local\\programs\\python\\python310\\lib\\site-packages (from deeptrack) (0.19.2)\n", - "Requirement already satisfied: scikit-image>=0.18.0 in c:\\users\\gu\\appdata\\local\\programs\\python\\python310\\lib\\site-packages (from deeptrack) (0.19.3)\n", - "Requirement already satisfied: pydeepimagej in c:\\users\\gu\\appdata\\local\\programs\\python\\python310\\lib\\site-packages (from deeptrack) (1.1.0)\n", - "Requirement already satisfied: more_itertools in c:\\users\\gu\\appdata\\local\\programs\\python\\python310\\lib\\site-packages (from deeptrack) (8.13.0)\n", - "Requirement already satisfied: tensorflow_addons in c:\\users\\gu\\appdata\\local\\programs\\python\\python310\\lib\\site-packages (from deeptrack) (0.17.1)\n", - "Requirement already satisfied: pillow!=7.1.0,!=7.1.1,!=8.3.0,>=6.1.0 in c:\\users\\gu\\appdata\\local\\programs\\python\\python310\\lib\\site-packages (from scikit-image>=0.18.0->deeptrack) (9.1.1)\n", - "Requirement already satisfied: packaging>=20.0 in c:\\users\\gu\\appdata\\local\\programs\\python\\python310\\lib\\site-packages (from scikit-image>=0.18.0->deeptrack) (21.3)\n", - "Requirement already satisfied: PyWavelets>=1.1.1 in c:\\users\\gu\\appdata\\local\\programs\\python\\python310\\lib\\site-packages (from scikit-image>=0.18.0->deeptrack) (1.3.0)\n", - "Requirement already satisfied: networkx>=2.2 in c:\\users\\gu\\appdata\\local\\programs\\python\\python310\\lib\\site-packages (from scikit-image>=0.18.0->deeptrack) (2.8.4)\n", - "Requirement already satisfied: imageio>=2.4.1 in c:\\users\\gu\\appdata\\local\\programs\\python\\python310\\lib\\site-packages (from scikit-image>=0.18.0->deeptrack) (2.19.3)\n", - "Requirement already satisfied: tifffile>=2019.7.26 in c:\\users\\gu\\appdata\\local\\programs\\python\\python310\\lib\\site-packages (from scikit-image>=0.18.0->deeptrack) (2022.5.4)\n", - "Requirement already satisfied: keras-preprocessing>=1.1.1 in c:\\users\\gu\\appdata\\local\\programs\\python\\python310\\lib\\site-packages (from tensorflow->deeptrack) (1.1.2)\n", - "Requirement already satisfied: keras<2.10.0,>=2.9.0rc0 in c:\\users\\gu\\appdata\\local\\programs\\python\\python310\\lib\\site-packages (from tensorflow->deeptrack) (2.9.0)\n", - "Requirement already satisfied: google-pasta>=0.1.1 in c:\\users\\gu\\appdata\\local\\programs\\python\\python310\\lib\\site-packages (from tensorflow->deeptrack) (0.2.0)\n", - "Requirement already satisfied: h5py>=2.9.0 in c:\\users\\gu\\appdata\\local\\programs\\python\\python310\\lib\\site-packages (from tensorflow->deeptrack) (3.7.0)\n", - "Requirement already satisfied: gast<=0.4.0,>=0.2.1 in c:\\users\\gu\\appdata\\local\\programs\\python\\python310\\lib\\site-packages (from tensorflow->deeptrack) (0.4.0)\n", - "Requirement already satisfied: tensorflow-io-gcs-filesystem>=0.23.1 in c:\\users\\gu\\appdata\\local\\programs\\python\\python310\\lib\\site-packages (from tensorflow->deeptrack) (0.26.0)\n", - "Requirement already satisfied: opt-einsum>=2.3.2 in c:\\users\\gu\\appdata\\local\\programs\\python\\python310\\lib\\site-packages (from tensorflow->deeptrack) (3.3.0)\n", - "Requirement already satisfied: tensorboard<2.10,>=2.9 in c:\\users\\gu\\appdata\\local\\programs\\python\\python310\\lib\\site-packages (from tensorflow->deeptrack) (2.9.1)\n", - "Requirement already satisfied: six>=1.12.0 in c:\\users\\gu\\appdata\\local\\programs\\python\\python310\\lib\\site-packages (from tensorflow->deeptrack) (1.16.0)\n", - "Requirement already satisfied: wrapt>=1.11.0 in c:\\users\\gu\\appdata\\local\\programs\\python\\python310\\lib\\site-packages (from tensorflow->deeptrack) (1.14.1)\n", - "Requirement already satisfied: termcolor>=1.1.0 in c:\\users\\gu\\appdata\\local\\programs\\python\\python310\\lib\\site-packages (from tensorflow->deeptrack) (1.1.0)\n", - "Requirement already satisfied: grpcio<2.0,>=1.24.3 in c:\\users\\gu\\appdata\\local\\programs\\python\\python310\\lib\\site-packages (from tensorflow->deeptrack) (1.47.0)\n", - "Requirement already satisfied: setuptools in c:\\users\\gu\\appdata\\local\\programs\\python\\python310\\lib\\site-packages (from tensorflow->deeptrack) (58.1.0)\n", - "Requirement already satisfied: libclang>=13.0.0 in c:\\users\\gu\\appdata\\local\\programs\\python\\python310\\lib\\site-packages (from tensorflow->deeptrack) (14.0.1)\n", - "Requirement already satisfied: absl-py>=1.0.0 in c:\\users\\gu\\appdata\\local\\programs\\python\\python310\\lib\\site-packages (from tensorflow->deeptrack) (1.1.0)\n", - "Requirement already satisfied: astunparse>=1.6.0 in c:\\users\\gu\\appdata\\local\\programs\\python\\python310\\lib\\site-packages (from tensorflow->deeptrack) (1.6.3)\n", - "Requirement already satisfied: typing-extensions>=3.6.6 in c:\\users\\gu\\appdata\\local\\programs\\python\\python310\\lib\\site-packages (from tensorflow->deeptrack) (4.2.0)\n", - "Requirement already satisfied: tensorflow-estimator<2.10.0,>=2.9.0rc0 in c:\\users\\gu\\appdata\\local\\programs\\python\\python310\\lib\\site-packages (from tensorflow->deeptrack) (2.9.0)\n", - "Requirement already satisfied: protobuf<3.20,>=3.9.2 in c:\\users\\gu\\appdata\\local\\programs\\python\\python310\\lib\\site-packages (from tensorflow->deeptrack) (3.19.4)\n", - "Requirement already satisfied: flatbuffers<2,>=1.12 in c:\\users\\gu\\appdata\\local\\programs\\python\\python310\\lib\\site-packages (from tensorflow->deeptrack) (1.12)\n", - "Requirement already satisfied: typeguard>=2.7 in c:\\users\\gu\\appdata\\local\\programs\\python\\python310\\lib\\site-packages (from tensorflow_addons->deeptrack) (2.13.3)\n", - "Requirement already satisfied: decorator in c:\\users\\gu\\appdata\\local\\programs\\python\\python310\\lib\\site-packages (from tensorflow-probability->deeptrack) (5.1.1)\n", - "Requirement already satisfied: dm-tree in c:\\users\\gu\\appdata\\local\\programs\\python\\python310\\lib\\site-packages (from tensorflow-probability->deeptrack) (0.1.7)\n", - "Requirement already satisfied: cloudpickle>=1.3 in c:\\users\\gu\\appdata\\local\\programs\\python\\python310\\lib\\site-packages (from tensorflow-probability->deeptrack) (2.1.0)\n", - "Requirement already satisfied: wheel<1.0,>=0.23.0 in c:\\users\\gu\\appdata\\local\\programs\\python\\python310\\lib\\site-packages (from astunparse>=1.6.0->tensorflow->deeptrack) (0.37.1)\n", - "Requirement already satisfied: pyparsing!=3.0.5,>=2.0.2 in c:\\users\\gu\\appdata\\local\\programs\\python\\python310\\lib\\site-packages (from packaging>=20.0->scikit-image>=0.18.0->deeptrack) (3.0.9)\n", - "Requirement already satisfied: tensorboard-data-server<0.7.0,>=0.6.0 in c:\\users\\gu\\appdata\\local\\programs\\python\\python310\\lib\\site-packages (from tensorboard<2.10,>=2.9->tensorflow->deeptrack) (0.6.1)\n", - "Requirement already satisfied: google-auth-oauthlib<0.5,>=0.4.1 in c:\\users\\gu\\appdata\\local\\programs\\python\\python310\\lib\\site-packages (from tensorboard<2.10,>=2.9->tensorflow->deeptrack) (0.4.6)\n", - "Requirement already satisfied: requests<3,>=2.21.0 in c:\\users\\gu\\appdata\\local\\programs\\python\\python310\\lib\\site-packages (from tensorboard<2.10,>=2.9->tensorflow->deeptrack) (2.28.0)\n", - "Requirement already satisfied: werkzeug>=1.0.1 in c:\\users\\gu\\appdata\\local\\programs\\python\\python310\\lib\\site-packages (from tensorboard<2.10,>=2.9->tensorflow->deeptrack) (2.1.2)\n", - "Requirement already satisfied: tensorboard-plugin-wit>=1.6.0 in c:\\users\\gu\\appdata\\local\\programs\\python\\python310\\lib\\site-packages (from tensorboard<2.10,>=2.9->tensorflow->deeptrack) (1.8.1)\n", - "Requirement already satisfied: markdown>=2.6.8 in c:\\users\\gu\\appdata\\local\\programs\\python\\python310\\lib\\site-packages (from tensorboard<2.10,>=2.9->tensorflow->deeptrack) (3.3.7)\n", - "Requirement already satisfied: google-auth<3,>=1.6.3 in c:\\users\\gu\\appdata\\local\\programs\\python\\python310\\lib\\site-packages (from tensorboard<2.10,>=2.9->tensorflow->deeptrack) (2.9.0)\n", - "Requirement already satisfied: rsa<5,>=3.1.4 in c:\\users\\gu\\appdata\\local\\programs\\python\\python310\\lib\\site-packages (from google-auth<3,>=1.6.3->tensorboard<2.10,>=2.9->tensorflow->deeptrack) (4.8)\n", - "Requirement already satisfied: pyasn1-modules>=0.2.1 in c:\\users\\gu\\appdata\\local\\programs\\python\\python310\\lib\\site-packages (from google-auth<3,>=1.6.3->tensorboard<2.10,>=2.9->tensorflow->deeptrack) (0.2.8)\n", - "Requirement already satisfied: cachetools<6.0,>=2.0.0 in c:\\users\\gu\\appdata\\local\\programs\\python\\python310\\lib\\site-packages (from google-auth<3,>=1.6.3->tensorboard<2.10,>=2.9->tensorflow->deeptrack) (5.2.0)\n", - "Requirement already satisfied: requests-oauthlib>=0.7.0 in c:\\users\\gu\\appdata\\local\\programs\\python\\python310\\lib\\site-packages (from google-auth-oauthlib<0.5,>=0.4.1->tensorboard<2.10,>=2.9->tensorflow->deeptrack) (1.3.1)\n", - "Requirement already satisfied: idna<4,>=2.5 in c:\\users\\gu\\appdata\\local\\programs\\python\\python310\\lib\\site-packages (from requests<3,>=2.21.0->tensorboard<2.10,>=2.9->tensorflow->deeptrack) (3.3)\n", - "Requirement already satisfied: urllib3<1.27,>=1.21.1 in c:\\users\\gu\\appdata\\local\\programs\\python\\python310\\lib\\site-packages (from requests<3,>=2.21.0->tensorboard<2.10,>=2.9->tensorflow->deeptrack) (1.26.9)\n", - "Requirement already satisfied: charset-normalizer~=2.0.0 in c:\\users\\gu\\appdata\\local\\programs\\python\\python310\\lib\\site-packages (from requests<3,>=2.21.0->tensorboard<2.10,>=2.9->tensorflow->deeptrack) (2.0.12)\n", - "Requirement already satisfied: certifi>=2017.4.17 in c:\\users\\gu\\appdata\\local\\programs\\python\\python310\\lib\\site-packages (from requests<3,>=2.21.0->tensorboard<2.10,>=2.9->tensorflow->deeptrack) (2022.6.15)\n", - "Requirement already satisfied: pyasn1<0.5.0,>=0.4.6 in c:\\users\\gu\\appdata\\local\\programs\\python\\python310\\lib\\site-packages (from pyasn1-modules>=0.2.1->google-auth<3,>=1.6.3->tensorboard<2.10,>=2.9->tensorflow->deeptrack) (0.4.8)\n", - "Requirement already satisfied: oauthlib>=3.0.0 in c:\\users\\gu\\appdata\\local\\programs\\python\\python310\\lib\\site-packages (from requests-oauthlib>=0.7.0->google-auth-oauthlib<0.5,>=0.4.1->tensorboard<2.10,>=2.9->tensorflow->deeptrack) (3.2.0)\n" - ] - } - ], - "source": [ - "%matplotlib inline\n", - "!pip install deeptrack" - ] - }, + "cells": [ + { + "cell_type": "markdown", + "id": "dtex203-00", + "metadata": {}, + "source": [ + "# DTEx203. Single particle sizing\n", + "\n", + "This notebook trains a neural network to estimate the radius and refractive index of single particles from simulated brightfield images." + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "id": "62ed9144", + "metadata": {}, + "outputs": [], + "source": [ + "\n", + "# !pip install deeplay deeptrack # Uncomment if running on Colab/Kaggle." + ] + }, + { + "cell_type": "markdown", + "id": "dtex203-01", + "metadata": {}, + "source": [ + "## 1. Setup\n", + "\n", + "The tutorial uses DeepTrack2 for simulation and deeplay for the regression model. Here we import the necessary libraries and set up the simulation the training parameters." + ] + }, + { + "cell_type": "code", + "execution_count": 30, + "id": "dtex203-02", + "metadata": {}, + "outputs": [ { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "\"Open" - ] - }, + "name": "stdout", + "output_type": "stream", + "text": [ + "Torch version: 2.12.1\n", + "Training samples: 512, validation samples: 128, epochs: 30\n" + ] + } + ], + "source": [ + "from pathlib import Path\n", + "\n", + "import matplotlib.pyplot as plt\n", + "import numpy as np\n", + "import torch\n", + "from lightning.pytorch.callbacks import EarlyStopping\n", + "from torch.utils.data import DataLoader, TensorDataset\n", + "\n", + "import deeptrack as dt\n", + "import deeptrack.deeplay as dl\n", + "\n", + "IMAGE_SIZE = 64\n", + "IMAGE_SCALE = 50\n", + "PRE_OPTICS_NOISE_MAX = 1.2\n", + "\n", + "TRAIN_DATASET_SIZE = 512\n", + "VALIDATION_SET_SIZE = 128\n", + "BATCH_SIZE = 32\n", + "EPOCHS = 30\n", + "EARLY_STOPPING_PATIENCE = 8\n", + "\n", + "rng_seed = 3\n", + "rng = np.random.default_rng(rng_seed)\n", + "torch.manual_seed(rng_seed)\n", + "\n", + "print(\"Torch version:\", torch.__version__)\n", + "print(\n", + " f\"Training samples: {TRAIN_DATASET_SIZE}, validation samples: {VALIDATION_SET_SIZE}, \"\n", + " f\"epochs: {EPOCHS}\"\n", + ")" + ] + }, + { + "cell_type": "markdown", + "id": "dtex203-03", + "metadata": {}, + "source": [ + "## 2. Defining the simulated dataset\n", + "\n", + "The training data consists of simulated 64 by 64 pixel images containing one Mie sphere. The radius and refractive index are sampled for each generated image, then encoded as a two-value regression target." + ] + }, + { + "cell_type": "code", + "execution_count": 31, + "id": "dtex203-04", + "metadata": {}, + "outputs": [], + "source": [ + "particle = dt.MieSphere(\n", + " position=lambda: (IMAGE_SIZE / 2, IMAGE_SIZE / 2) + rng.random(2) * 4 - 2,\n", + " z=lambda: rng.standard_normal() * 2,\n", + " # Deeptrack supports callable parameters, but Pylance might complain\n", + " radius=lambda: 1e-7 + 3e-7 * rng.random(), # type: ignore[arg-type]\n", + " refractive_index=lambda: rng.random() * 0.3 + 1.37, # type: ignore[arg-type]\n", + " L=8,\n", + " position_unit=\"pixel\",\n", + " input_polarization=0,\n", + " output_polarization=0,\n", + ")" + ] + }, + { + "cell_type": "markdown", + "id": "dtex203-05", + "metadata": {}, + "source": [ + "The brightfield optics return the complex field at the camera. The Mie scatterer infers the collection angle from the objective properties. The pupil is mildly aberrated and cropped at high frequencies." + ] + }, + { + "cell_type": "code", + "execution_count": 32, + "id": "dtex203-06", + "metadata": {}, + "outputs": [], + "source": [ + "HC = dt.HorizontalComa(\n", + " coefficient=lambda c1: c1,\n", + " c1=lambda: rng.standard_normal() * 0.25,\n", + ")\n", + "VC = dt.VerticalComa(\n", + " coefficient=lambda c2: c2,\n", + " c2=lambda: rng.standard_normal() * 0.25,\n", + ")\n", + "\n", + "\n", + "def crop(pupil_radius):\n", + " \"\"\"Crop the pupil to a circular aperture.\"\"\"\n", + " def inner(image):\n", + " image = np.array(image, copy=True)\n", + " x = np.arange(image.shape[0]) - image.shape[0] / 2\n", + " y = np.arange(image.shape[1]) - image.shape[1] / 2\n", + " X, Y = np.meshgrid(x, y)\n", + " image[pupil_radius ** 2 < X ** 2 + Y ** 2] = 0\n", + " return image\n", + "\n", + " return inner\n", + "\n", + "\n", + "CROP = dt.Lambda(crop, pupil_radius=23)\n", + "\n", + "optics = dt.Brightfield(\n", + " NA=1.3,\n", + " resolution=1.13e-6,\n", + " wavelength=635e-9,\n", + " magnification=10,\n", + " output_region=(0, 0, IMAGE_SIZE, IMAGE_SIZE),\n", + " padding=(64, 64, 64, 64),\n", + " return_field=True,\n", + " pupil=HC >> VC >> CROP,\n", + ")" + ] + }, + { + "cell_type": "markdown", + "id": "dtex203-07", + "metadata": {}, + "source": [ + "The real and imaginary parts of the complex field are represented in two complementary ways. The first two channels keep the fixed-scale field amplitude, which carries scattering-strength information. The last two channels are normalized per image, which emphasizes the spatial pattern. Noise is added before the optics to simulate realistic conditions." + ] + }, + { + "cell_type": "code", + "execution_count": 33, + "id": "dtex203-08", + "metadata": {}, + "outputs": [], + "source": [ + "real_noise = dt.Gaussian(\n", + " mu=0,\n", + " sigma=lambda: rng.random() * PRE_OPTICS_NOISE_MAX,\n", + ")\n", + "\n", + "noise = real_noise >> dt.Gaussian(\n", + " mu=0,\n", + " sigma=lambda real_sigma: real_sigma * 0.03j,\n", + " real_sigma=real_noise.sigma,\n", + ")\n", + "\n", + "\n", + "def make_model_channels(raw_field):\n", + " raw_field = np.asarray(raw_field, dtype=np.float32)\n", + " raw_scaled = raw_field * IMAGE_SCALE\n", + "\n", + " normalized = raw_scaled - raw_scaled.mean(axis=(0, 1), keepdims=True)\n", + " normalized /= raw_scaled.std(axis=(0, 1), keepdims=True) + 1e-6\n", + "\n", + " return np.concatenate([raw_scaled, normalized], axis=-1).astype(np.float32)\n", + "\n", + "\n", + "def complex_field_to_channels():\n", + " def inner(image):\n", + " field = image - 1\n", + " if field.ndim == 3 and field.shape[-1] == 1:\n", + " field = field[..., 0]\n", + "\n", + " raw = np.zeros((*field.shape[:2], 2), dtype=np.float32)\n", + " raw[..., 0] = np.real(field)\n", + " raw[..., 1] = np.imag(field)\n", + " return make_model_channels(raw)\n", + "\n", + " return inner\n", + "\n", + "\n", + "complex_to_float = dt.Lambda(complex_field_to_channels)\n", + "image_pipeline = optics(particle >> noise) >> complex_to_float" + ] + }, + { + "cell_type": "markdown", + "id": "dtex203-09", + "metadata": {}, + "source": [ + "Labels are read from the currently resolved particle properties, because the current pipeline resolves to plain NumPy arrays." + ] + }, + { + "cell_type": "code", + "execution_count": 34, + "id": "dtex203-10", + "metadata": {}, + "outputs": [], + "source": [ + "def encode_label(radius, refractive_index):\n", + " radius_scaled = radius / 1e-6 * 10\n", + " refractive_index_scaled = (refractive_index - 1.33) * 10\n", + " return np.array([radius_scaled, refractive_index_scaled], dtype=np.float32)\n", + "\n", + "\n", + "def decode_label(label):\n", + " label = np.asarray(label)\n", + " radius_nm = label[..., 0] * 100\n", + " refractive_index = label[..., 1] / 10 + 1.33\n", + " return radius_nm, refractive_index\n", + "\n", + "\n", + "def image_to_tensor(image):\n", + " image = np.asarray(image, dtype=np.float32)\n", + " return torch.from_numpy(np.moveaxis(image, -1, 0))\n", + "\n", + "\n", + "def label_from_current_particle():\n", + " def inner(_image):\n", + " radius = float(particle.radius.current_value())\n", + " refractive_index = float(particle.refractive_index.current_value())\n", + " return encode_label(radius, refractive_index)\n", + "\n", + " return inner\n", + "\n", + "\n", + "label_pipeline = image_pipeline >> dt.Lambda(label_from_current_particle)\n", + "particle_sizing_pipeline = image_pipeline & label_pipeline\n", + "\n", + "\n", + "def resolve_image_label_metadata():\n", + " particle_sizing_pipeline.update()\n", + " image, label = particle_sizing_pipeline.resolve()\n", + " metadata = {\n", + " \"radius\": float(particle.radius.current_value()),\n", + " \"refractive_index\": float(particle.refractive_index.current_value()),\n", + " \"pre_optics_noise_sigma\": float(real_noise.sigma.current_value()),\n", + " }\n", + " return np.asarray(image, dtype=np.float32), np.asarray(label, dtype=np.float32), metadata" + ] + }, + { + "cell_type": "markdown", + "id": "dtex203-11", + "metadata": {}, + "source": [ + "## 3. Inspecting the simulated input signal\n", + "\n", + "The model uses both fixed-scale and normalized channels. For visualization, the fixed-scale real and imaginary fields are the most useful because they preserve amplitude." + ] + }, + { + "cell_type": "code", + "execution_count": 35, + "id": "dtex203-12", + "metadata": {}, + "outputs": [ { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Example 3. Single particle sizing\n", - "\n" + "data": { + "image/png": "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", + "text/plain": [ + "
" ] - }, + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "number_of_images = 4\n", + "samples = [resolve_image_label_metadata() for _ in range(number_of_images)]\n", + "\n", + "fig, axes = plt.subplots(2, number_of_images, figsize=(3.2 * number_of_images, 6))\n", + "axes = np.atleast_2d(axes)\n", + "\n", + "for col, (image, label, metadata) in enumerate(samples):\n", + " radius_nm, refractive_index = decode_label(label)\n", + " real_field = image[:, :, 0]\n", + " imaginary_field = image[:, :, 1]\n", + "\n", + " im_real = axes[0, col].imshow(real_field, cmap=\"gray\")\n", + " axes[0, col].set_title(\n", + " f\"Real\\nr={radius_nm:.0f} nm, n={refractive_index:.2f}\"\n", + " )\n", + " axes[0, col].axis(\"off\")\n", + " fig.colorbar(im_real, ax=axes[0, col], fraction=0.046, pad=0.04)\n", + "\n", + " im_imaginary = axes[1, col].imshow(imaginary_field, cmap=\"gray\")\n", + " axes[1, col].set_title(\n", + " f\"Imaginary\\nnoise={metadata['pre_optics_noise_sigma']:.3f}\"\n", + " )\n", + " axes[1, col].axis(\"off\")\n", + " fig.colorbar(im_imaginary, ax=axes[1, col], fraction=0.046, pad=0.04)\n", + "\n", + "plt.tight_layout()" + ] + }, + { + "cell_type": "markdown", + "id": "dtex203-13", + "metadata": {}, + "source": [ + "## 4. Defining the network\n", + "\n", + "The network combines deeplay convolutional and dense templates, then wraps the result in a deeplay `Regressor`.\n" + ] + }, + { + "cell_type": "code", + "execution_count": 36, + "id": "dtex203-14", + "metadata": {}, + "outputs": [ { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 1. Setup\n", - "\n", - "Imports the objects needed for this example." - ] - }, + "name": "stdout", + "output_type": "stream", + "text": [ + "Regressor(\n", + " (loss): L1Loss()\n", + " (optimizer): AdamW[AdamW](lr=0.001, weight_decay=0.0001)\n", + " (train_metrics): MetricCollection,\n", + " prefix=train\n", + " )\n", + " (val_metrics): MetricCollection,\n", + " prefix=val\n", + " )\n", + " (test_metrics): MetricCollection,\n", + " prefix=test\n", + " )\n", + " (model): Sequential(\n", + " (0): ConvolutionalEncoder2d(\n", + " (blocks): LayerList(\n", + " (0): Conv2dBlock(\n", + " (layer): Conv2d(4, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n", + " (activation): ReLU()\n", + " )\n", + " (1): Conv2dBlock(\n", + " (pool): MaxPool2d(kernel_size=2, stride=2, padding=0, dilation=1, ceil_mode=False)\n", + " (layer): Conv2d(32, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n", + " (activation): ReLU()\n", + " )\n", + " (2): Conv2dBlock(\n", + " (pool): MaxPool2d(kernel_size=2, stride=2, padding=0, dilation=1, ceil_mode=False)\n", + " (layer): Conv2d(64, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n", + " (activation): Identity()\n", + " )\n", + " )\n", + " (postprocess): Identity()\n", + " )\n", + " (1): AdaptiveAvgPool2d(output_size=1)\n", + " (2): Flatten(start_dim=1, end_dim=-1)\n", + " (3): MultiLayerPerceptron(\n", + " (blocks): LayerList(\n", + " (0): LinearBlock(\n", + " (layer): Linear(in_features=128, out_features=64, bias=True)\n", + " (activation): ReLU()\n", + " (dropout): Dropout(p=0.1, inplace=False)\n", + " )\n", + " (1): LinearBlock(\n", + " (layer): Linear(in_features=64, out_features=2, bias=True)\n", + " (activation): Identity()\n", + " )\n", + " )\n", + " )\n", + " )\n", + ")\n" + ] + } + ], + "source": [ + "encoder_template = dl.ConvolutionalEncoder2d(\n", + " in_channels=4,\n", + " hidden_channels=[32, 64],\n", + " out_channels=128,\n", + ")\n", + "encoder = encoder_template.create()\n", + "\n", + "mlp_template = dl.MultiLayerPerceptron(\n", + " in_features=128,\n", + " hidden_features=[64],\n", + " out_features=2,\n", + ")\n", + "for block in mlp_template.blocks[:-1]:\n", + " block.append(dl.Layer(torch.nn.Dropout, 0.1))\n", + "mlp = mlp_template.create()\n", + "\n", + "model = torch.nn.Sequential(\n", + " encoder,\n", + " torch.nn.AdaptiveAvgPool2d(1),\n", + " torch.nn.Flatten(),\n", + " mlp,\n", + ")\n", + "\n", + "regressor_template = dl.Regressor(\n", + " model=model,\n", + " optimizer=dl.AdamW(lr=0.001, weight_decay=1e-4),\n", + ")\n", + "regressor = regressor_template.create()\n", + "\n", + "print(regressor)" + ] + }, + { + "cell_type": "markdown", + "id": "dtex203-15", + "metadata": {}, + "source": [ + "## 5. Training the network\n", + "\n", + "Training data is generated on demand through `dt.pytorch.Dataset`. The validation set is generated once so that validation loss and diagnostic plots are comparable across epochs.\n" + ] + }, + { + "cell_type": "code", + "execution_count": 37, + "id": "dtex203-16", + "metadata": {}, + "outputs": [ { - "cell_type": "code", - "execution_count": 2, - "metadata": { - "execution": { - "iopub.execute_input": "2022-06-30T10:14:52.574985Z", - "iopub.status.busy": "2022-06-30T10:14:52.574482Z", - "iopub.status.idle": "2022-06-30T10:16:36.119547Z", - "shell.execute_reply": "2022-06-30T10:16:36.119547Z" - } - }, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "c:\\users\\gu\\deeptrack\\deeptrack-2.0\\deeptrack\\backend\\_config.py:11: UserWarning: cupy not installed. GPU-accelerated simulations will not be possible\n", - " warnings.warn(\n", - "c:\\users\\gu\\deeptrack\\deeptrack-2.0\\deeptrack\\backend\\_config.py:25: UserWarning: cupy not installed, CPU acceleration not enabled\n", - " warnings.warn(\"cupy not installed, CPU acceleration not enabled\")\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Downloading ParticleSizing...\n", - "Downloading file: 370.0\tMB\r\n", - "Download Complete!\n", - "Extracting ParticleSizing...\n" - ] - } + "data": { + "text/html": [ + "
┏━━━┳━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━┳━━━━━━━━┳━━━━━━━┳━━━━━━━┓\n",
+       "┃    Name           Type              Params  Mode   FLOPs ┃\n",
+       "┡━━━╇━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━╇━━━━━━━━╇━━━━━━━╇━━━━━━━┩\n",
+       "│ 0 │ loss          │ L1Loss           │      0 │ eval  │     0 │\n",
+       "│ 1 │ train_metrics │ MetricCollection │      0 │ train │     0 │\n",
+       "│ 2 │ val_metrics   │ MetricCollection │      0 │ train │     0 │\n",
+       "│ 3 │ test_metrics  │ MetricCollection │      0 │ train │     0 │\n",
+       "│ 4 │ model         │ Sequential       │  101 K │ train │     0 │\n",
+       "│ 5 │ optimizer     │ AdamW            │      0 │ train │     0 │\n",
+       "└───┴───────────────┴──────────────────┴────────┴───────┴───────┘\n",
+       "
\n" ], - "source": [ - "import numpy as np\n", - "import matplotlib.pyplot as plt\n", - "\n", - "import deeptrack as dt\n", - "\n", - "from deeptrack.extras import datasets\n", - "datasets.load('ParticleSizing')\n", - "experimental_data = np.load('datasets/ParticleSizing/sizing_150nm_227nm_PSL.npy', allow_pickle=True)\n", - "\n", - "import scipy.io as IO\n", - "\n", - "IMAGE_SIZE = 64" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 2. Defining the dataset\n", - "\n", - "### 2.1 Defining the training set\n", - "\n", - "The training set consists of simulated 64 by 64 pixel images, containing a single particle each. The particles are simulated as spheres with a radius between 100nm and 400nm, and a refractive index between 1.37 and 1.67. Its position in the camera plane is constrained to be within within two pixels of the image center, and is sampled with a normal distribution with standard deviation of 2 pixel units along the axis normal to the camera plane. " - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": { - "execution": { - "iopub.execute_input": "2022-06-30T10:16:36.123048Z", - "iopub.status.busy": "2022-06-30T10:16:36.122548Z", - "iopub.status.idle": "2022-06-30T10:16:36.126049Z", - "shell.execute_reply": "2022-06-30T10:16:36.126049Z" - } - }, - "outputs": [], - "source": [ - "particle = dt.MieSphere(\n", - " position=lambda: (IMAGE_SIZE / 2, IMAGE_SIZE / 2) + np.random.rand(2) * 4 - 2,\n", - " z=lambda: np.random.randn() * 2,\n", - " radius=lambda:1e-7 + 3e-7 * np.random.rand() ,\n", - " refractive_index=lambda: np.random.rand() * 0.3 + 1.37,\n", - " L=8,\n", - " position_unit=\"pixel\",\n", - ")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "We use a single wavelength brightifeld feature to calculate the field at the camera plane. We aberrate the image with a random coma, which was observed in the experimental data. Moreover, the pupil is cropped at high frequencies." + "text/plain": [ + "┏━━━┳━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━┳━━━━━━━━┳━━━━━━━┳━━━━━━━┓\n", + "┃\u001b[1;35m \u001b[0m\u001b[1;35m \u001b[0m\u001b[1;35m \u001b[0m┃\u001b[1;35m \u001b[0m\u001b[1;35mName \u001b[0m\u001b[1;35m \u001b[0m┃\u001b[1;35m \u001b[0m\u001b[1;35mType \u001b[0m\u001b[1;35m \u001b[0m┃\u001b[1;35m \u001b[0m\u001b[1;35mParams\u001b[0m\u001b[1;35m \u001b[0m┃\u001b[1;35m \u001b[0m\u001b[1;35mMode \u001b[0m\u001b[1;35m \u001b[0m┃\u001b[1;35m \u001b[0m\u001b[1;35mFLOPs\u001b[0m\u001b[1;35m \u001b[0m┃\n", + "┡━━━╇━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━╇━━━━━━━━╇━━━━━━━╇━━━━━━━┩\n", + "│\u001b[2m \u001b[0m\u001b[2m0\u001b[0m\u001b[2m \u001b[0m│ loss │ L1Loss │ 0 │ eval │ 0 │\n", + "│\u001b[2m \u001b[0m\u001b[2m1\u001b[0m\u001b[2m \u001b[0m│ train_metrics │ MetricCollection │ 0 │ train │ 0 │\n", + "│\u001b[2m \u001b[0m\u001b[2m2\u001b[0m\u001b[2m \u001b[0m│ val_metrics │ MetricCollection │ 0 │ train │ 0 │\n", + "│\u001b[2m \u001b[0m\u001b[2m3\u001b[0m\u001b[2m \u001b[0m│ test_metrics │ MetricCollection │ 0 │ train │ 0 │\n", + "│\u001b[2m \u001b[0m\u001b[2m4\u001b[0m\u001b[2m \u001b[0m│ model │ Sequential │ 101 K │ train │ 0 │\n", + "│\u001b[2m \u001b[0m\u001b[2m5\u001b[0m\u001b[2m \u001b[0m│ optimizer │ AdamW │ 0 │ train │ 0 │\n", + "└───┴───────────────┴──────────────────┴────────┴───────┴───────┘\n" ] + }, + "metadata": {}, + "output_type": "display_data" }, { - "cell_type": "code", - "execution_count": 4, - "metadata": { - "execution": { - "iopub.execute_input": "2022-06-30T10:16:36.128547Z", - "iopub.status.busy": "2022-06-30T10:16:36.128547Z", - "iopub.status.idle": "2022-06-30T10:16:36.135047Z", - "shell.execute_reply": "2022-06-30T10:16:36.134547Z" - } - }, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "c:\\users\\gu\\deeptrack\\deeptrack-2.0\\deeptrack\\optics.py:171: UserWarning: Likely bad optical parameters. NA / wavelength * resolution * magnification = 23.133858267716537 should be at most 0.5\n", - "To fix, set magnification to 47.0, and downsample the resulting image with dt.AveragePooling((47.0, 47.0, 1))\n", - "\n", - " warnings.warn(\n" - ] - } + "data": { + "text/html": [ + "
Trainable params: 101 K                                                                                            \n",
+       "Non-trainable params: 0                                                                                            \n",
+       "Total params: 101 K                                                                                                \n",
+       "Total estimated model params size (MB): 0.408                                                                      \n",
+       "Modules in train mode: 30                                                                                          \n",
+       "Modules in eval mode: 1                                                                                            \n",
+       "Total FLOPs: 0                                                                                                     \n",
+       "
\n" ], - "source": [ - "HC = dt.HorizontalComa(coefficient=lambda c1: c1, c1=0 + np.random.randn() * 0.5)\n", - "VC = dt.VerticalComa(coefficient=lambda c2:c2, c2=0 + np.random.randn() * 0.5)\n", - "\n", - "def crop(pupil_radius):\n", - " def inner(image):\n", - " x = np.arange(image.shape[0]) - image.shape[0] / 2\n", - " y = np.arange(image.shape[1]) - image.shape[1] / 2\n", - " X, Y = np.meshgrid(x, y)\n", - " image[X ** 2 + Y ** 2 > pupil_radius ** 2] = 0\n", - " return image\n", - " return inner\n", - "CROP = dt.Lambda(crop, pupil_radius=23)\n", - "\n", - "optics = dt.Brightfield(\n", - " NA=1.3,\n", - " resolution=1.13e-6,\n", - " wavelength=635e-9,\n", - " aperature_angle=53.7 * 2 * np.pi / 360,\n", - " polarization_angle=lambda: np.random.rand() * 2 * np.pi,\n", - " magnification=10,\n", - " output_region=(0, 0, IMAGE_SIZE, IMAGE_SIZE),\n", - " padding=(64,) * 4,\n", - " return_field=True,\n", - " pupil= HC >> VC >> CROP\n", - ")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "The noise is simulated as gaussian distributed noise, with independent real and imaginary parts. The amplitude of the noise is determined by the dummy property `level`, which is explicitly shared between the two features. Finally, the real and imaginary parts of the field are separated into two layers, and the plane wave is subtracted." + "text/plain": [ + "\u001b[1mTrainable params\u001b[0m: 101 K \n", + "\u001b[1mNon-trainable params\u001b[0m: 0 \n", + "\u001b[1mTotal params\u001b[0m: 101 K \n", + "\u001b[1mTotal estimated model params size (MB)\u001b[0m: 0.408 \n", + "\u001b[1mModules in train mode\u001b[0m: 30 \n", + "\u001b[1mModules in eval mode\u001b[0m: 1 \n", + "\u001b[1mTotal FLOPs\u001b[0m: 0 \n" ] + }, + "metadata": {}, + "output_type": "display_data" }, { - "cell_type": "code", - "execution_count": 5, - "metadata": { - "execution": { - "iopub.execute_input": "2022-06-30T10:16:36.137550Z", - "iopub.status.busy": "2022-06-30T10:16:36.137049Z", - "iopub.status.idle": "2022-06-30T10:16:36.141549Z", - "shell.execute_reply": "2022-06-30T10:16:36.141549Z" - } - }, - "outputs": [], - "source": [ - "real_noise = dt.Gaussian(\n", - " mu=0, \n", - " sigma=lambda: np.random.rand() * 0.02,\n", - ")\n", - "\n", - "noise = real_noise >> dt.Gaussian(\n", - " mu=0, \n", - " sigma=lambda real_sigma: real_sigma * 0.03j,\n", - " real_sigma=real_noise.sigma\n", - ")\n", - "\n", - "def func():\n", - " def inner(image):\n", - " image = image - 1\n", - " output = np.zeros((*image.shape[:2], 2))\n", - " output[..., 0:1] = np.real(image)\n", - " output[..., 1:2] = np.imag(image)\n", - " return output\n", - " return inner\n", - "\n", - "\n", - "complex_to_float = dt.Lambda(func)" - ] + "name": "stdout", + "output_type": "stream", + "text": [ + " " + ] }, { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "We now define how these objects combine. Note that the noise is added inside the optics. This means that it will have the same PSF as the sample, which is what is observed. " - ] + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/edu/DeepTrack2/.venv312/lib/python3.12/site-packages/lightning/pytorch/utilities/_pytree.py:21: `isinstance(treespec, LeafSpec)` is deprecated, use `isinstance(treespec, TreeSpec) and treespec.is_leaf()` instead.\n", + "/Users/edu/DeepTrack2/.venv312/lib/python3.12/site-packages/lightning/pytorch/trainer/connectors/data_connector.py:434: The 'val_dataloader' does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` to `num_workers=17` in the `DataLoader` to improve performance.\n", + "/Users/edu/DeepTrack2/.venv312/lib/python3.12/site-packages/lightning/pytorch/core/module.py:522: You called `self.log('val_loss', ..., logger=True)` but have no logger configured. You can enable one by doing `Trainer(logger=ALogger(...))`\n", + "/Users/edu/DeepTrack2/.venv312/lib/python3.12/site-packages/lightning/pytorch/trainer/connectors/data_connector.py:434: The 'train_dataloader' does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` to `num_workers=17` in the `DataLoader` to improve performance.\n", + "/Users/edu/DeepTrack2/.venv312/lib/python3.12/site-packages/lightning/pytorch/loops/fit_loop.py:538: Found 1 module(s) in eval mode at the start of training. This may lead to unexpected behavior during training. If this is intentional, you can ignore this warning.\n" + ] }, { - "cell_type": "code", - "execution_count": 6, - "metadata": { - "execution": { - "iopub.execute_input": "2022-06-30T10:16:36.144048Z", - "iopub.status.busy": "2022-06-30T10:16:36.144048Z", - "iopub.status.idle": "2022-06-30T10:16:36.146550Z", - "shell.execute_reply": "2022-06-30T10:16:36.146550Z" - } - }, - "outputs": [], - "source": [ - "dataset = optics(particle >> noise) >> complex_to_float" - ] + "name": "stdout", + "output_type": "stream", + "text": [ + "Epoch 0: 6%|▋ | 1/16 [00:00<00:04, 3.36it/s, train_loss_step=2.420]" + ] }, { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### 2.2 Defining the training label\n", - "\n", - "We extract the parameters we want the network to learn. We also rescale them such that they have a similar size." - ] + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/edu/DeepTrack2/.venv312/lib/python3.12/site-packages/lightning/pytorch/core/module.py:522: You called `self.log('train_loss', ..., logger=True)` but have no logger configured. You can enable one by doing `Trainer(logger=ALogger(...))`\n" + ] }, { - "cell_type": "code", - "execution_count": 7, - "metadata": { - "execution": { - "iopub.execute_input": "2022-06-30T10:16:36.149050Z", - "iopub.status.busy": "2022-06-30T10:16:36.149050Z", - "iopub.status.idle": "2022-06-30T10:16:36.152050Z", - "shell.execute_reply": "2022-06-30T10:16:36.152050Z" - } - }, - "outputs": [], - "source": [ - "def get_label(image):\n", - " px = np.array(image.get_property(\"position\")) - IMAGE_SIZE / 2\n", - " z = image.get_property(\"z\") * 0.1\n", - " r = image.get_property(\"radius\") / 1e-6\n", - " n = image.get_property(\"refractive_index\") - 1.33\n", - " return np.array([r * 10, n * 10])" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# 2.3 Visualizing the dataset\n", - "\n", - "We resolve and show 16 images" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": { - "execution": { - "iopub.execute_input": "2022-06-30T10:16:36.154548Z", - "iopub.status.busy": "2022-06-30T10:16:36.154548Z", - "iopub.status.idle": "2022-06-30T10:16:38.134548Z", - "shell.execute_reply": "2022-06-30T10:16:38.134548Z" - } - }, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "c:\\users\\gu\\deeptrack\\deeptrack-2.0\\deeptrack\\optics.py:272: RuntimeWarning: invalid value encountered in sqrt\n", - " * np.sqrt(1 - (NA / refractive_index_medium) ** 2 * RHO),\n" - ] - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - }, - { - "data": { - "image/png": "iVBORw0KGgoAAAANSUhEUgAAAl0AAAEiCAYAAADDHmeiAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjUuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8qNh9FAAAACXBIWXMAAAsTAAALEwEAmpwYAABUN0lEQVR4nO29e/BdV3Xn+V36yTaWZVmSjY0smbG6LSdlTANBZWCSSrkxGCVhEDXDQ5CklcS0K93QIU26gh1qcMbEU6YmzSMdhimVcWJoEuN2SFmTcXDk13SnJhjJwAC2QywMHkv4gR7Glp/IWvPHPfeyfttn7d8659x7f7979vdTpdI5555z9j6Pu3777u96iKqCEEIIIYRMlmWL3QFCCCGEkBLgoIsQQgghZApw0EUIIYQQMgU46CKEEEIImQIcdBFCCCGETIHli90BQkh3tmzZogcOHGh83N13332Lqm6ZQJcIISRMGxs2i/aLgy5CesCBAwewe/fuxsctW7bstAl0hxBCGtHGhs2i/aK8SAghhBAyBTjTRUhPYKJjQsgsU4IN46CLkJ5QgsEihPSXEmwYB12E9ABVLcJgEUL6SSk2jIMuQnpCCQaLENJfSrBhHHQR0hNKMFiEkP5Sgg3joIuQnlCCwSKE9JcSbBgHXYT0hBIMFiGkv5RgwzjoIqQHlOKESgjpJ6XYMA66COkJJRgsQkh/KcGGcdBFSE8owWARQvpLCTaMgy5CekIJBosQ0l9KsGEcdBHSE0owWISQ/lKCDeOgi5AeUIoTKiGkn5RiwzjoIqQnlGCwCCH9pQQbxkEXIT2hBINFCOkvJdgwDroI6QklGCxCSH8pwYYtW+wOEEIIIYSUAGe6COkBpTihEkL6SSk2jIMuQnpCCQaLENJfSrBhHHQR0hNKMFiEkP5Sgg3joIuQnlCCwSKE9JcSbBgHXYT0hBIMFiGkv5RgwzjoIqQHlOKESgjpJ6XYMA66COkJJRgsQkh/KcGGcdBFSE8owWARQvpLCTaMyVEJ6QnD6fkm/yKIyBYR+a6I7BWRy2o+P0FEvlR9fpeInF1tP1VE7hCRIyLyp8kxrxWRb1fH/ImIyDjuASFkdpmE/VpqcNBFSE+YxKBLROYAfAbALwE4D8B7ROS8ZLdLABxW1XMAfBLAx6vtzwL4nwH8h5pTfxbAvwawqfq3pcUlE0J6BAddhJCZoM2AK2i0LgCwV1UfUNXnAVwPYGuyz1YA11XLNwK4SEREVZ9S1b/HYPA1QkTWAVilql/VQSc+D+Dt7a+eEDLrTGqmfqlBny5CekJLI3SaiOwx6ztUdYdZXw/gIbO+D8DrknOM9lHVoyLyYwCnAjjgtLm+Oo895/oWfSeE9IhZHUg1gYMuQnpCS4N1QFU3j7svhBDSlBIGXZ3kxYUcbAkh02NC0/P7AZxl1jdU22r3EZHlAE4BcHCBc25Y4JxTgTaMkKVDCfJi60FX0MGWEDIlJjTo2g1gk4hsFJHjAWwDsDPZZyeA7dXyOwDcrpmTq+rDAJ4QkddXUYv/CsBNTa+3K7RhhCwtShh0dZEXRw62ACAiQwfbe93Gli/X4447DsD8acT05gWjqmqXo8d425ctW1a7nO7n9f/YsWO1yznm5uYWbN9rGwBeeOGF2ja9+5i7xkibXnu59r3n5bWXHu/d40gbuXa8NnLX6LVp27DPdPny5bXbc30+ePDgAVV9KYJMyghVPlofAHALgDkA16rqPSJyJYA9qroTwOcAfEFE9gI4hMHADAAgIj8AsArA8SLydgAXq+q9AP4tgD8HcCKAv63+TZtGNmzNmjW6fv10Xc+aZtKIvgNN35WuNrYrXd/tcfbL68tS6uNic8899zSyXwAz0keIONhCRC4FcCkAHHfccTjnnHMAAD/5yU9G+zz33HPzjrGf2Ydg/2BF/6glfandbzgQBICXvOQlo+UTTzxx3vF2P/uH+Nlnn61dfuaZZ0bL9o942ueVK1fWLq9YsWK0bP+g2/sDAE899dRo+ciRI6Pl559/vvZ4e40nn3zyvHPZa7b3yLZp23jiiSfmHf/000+Plo8ePTpattdr27fLdp/0eHst9n2x+9jna8+ba8e+X/bZ2Wu09zftiz2XfV5r166tXU7vt+2X7f/nP//5B7FEUNWbAdycbPuoWX4WwDudY892tu8BcP74etmKBW2YtV9nnnkmbrzxxuH2UANdBze5HyV1bXg/TtJ17wdh5AdF7jNrM7wfFF1/XOV+sDf9cZf2pcsPMmuL6vpWh/c3KXe/PSL3LtqXNu+3XX7FK16xZOzXUmPiKSNUdYeqblbVzbkBESGkGxOSF4vG2q81a9YsdncI6TUl2K8uM10RB9t5LFu2bDQbYGcr0lG1HZzZG2tH/3aGIZ0hsXi/7uyvFdteVB70Zsrsrx27TzrTZc9tZ07sbIv3CzI9l23TW/Z+9dnZuHQ/26Y9l531it4j73nZvqRfIu8eeTNdXnsp9nl5x3j3IW3f7mdnuo4//vja9tJ+5WTjpsyqEVpEGtuwpjR9vrnvwDhnujy8maroTFdkhiTXj6bvcK5fk5rp8vqY2onUTi9EpI3cMR5tpOFx2qUmlGDDugy6Rg62GBiqbQDeO5ZeEUIaU4LBGjO0YYQsIUqwYa3lRVU9CmDoYHsfgBtU9Z5xdYwQ0gzKi82gDSNkaTEJ+9W2dmz12eXV9u+KyFvGcY2dkqPWOdjmmJubw6pVqwDMl9FOOOGEeftZKcniRd3Z5XTq2kphnizmLedkT88/zbaRTn1b7NSzvV4rRaUO83V9zOHt5zmCA/P7bPti+5ubNvfuixfskLtHHk0jNNP27ftmZUB73px8bd9diycpWnL3rqkcYeEgqh1NbVgdOfmma6Sb59geOW/UTkTsak6Gayoppn3vco9y+3j3q83z8s6bk2C7nDe3f9P7FX12kej+3LPrGn05CRtm0sK8GYNAmd0islMHEdRDRrVjRWQbBrVj312lj9kG4BUAzgRwq4icq6rtDTVYe5GQ3sCZLkLILDMB+9W6dmy1/XpVfU5Vvw9gb3W+TrAMECE9gYMoQsgs08KGTbJ27HoAX02O7Zyoj4MuQnoCB12EkFmmhQ2budqxUx10zc3NjZJ/Wp+X1IfL873y/A3sg0oT1FkiPjM5v61ImgovHUGuL1YLt9du9/HSGQB+agm73Z7LSzqaHmPxfBdyqRksEZ+u1AclWimg7rxpv+y6fUbWD8trO9eOl3rEYu936g8WfXcjcNC1tGmTEsA73mNSflxdUytEr73pfcl9T+130/t7kbuupu23qWDikUsdEtluyVXBaJp8N2XcqSUmYMOa1I7dJ/Nrx04kpQx9ugjpAW38uThII4QsFSZkv7rUjt0JYFsV3bgRwCYAX+t6nZQXCekJHEQRQmaZcdsw7VA7ttrvBgxqsR4F8P6ukYvAlAddIuKG0ls8ySmSMTd9aJ70ZvGyMOfkRe86vHOleDW7Ihnx02lsT1bz5EWvH0AsBUPuGXrPLnpfLN40eJs0D5GacJ7skL4HXsUEu+zVD03lRdt/L0VIFA66Js/wHkfD6L3lNjKgxWs/moKla3h/pC6it0/02j1yVSw8PHeOcaZTyH3WNN1H7rq63j+PpvUdm3wWZRI2TLvVjr0KwFXj7A9nugjpCRx0EUJmmRJsGAddhPSEEgwWIaS/lGDDpjroUtWRhGIltVwBZw9Pxmoz9erJczlZKRL9Y8lFo3jX4r2AuejFaIZkD09W8yTFtA277j3HNpnXvb540kraL0/Gi8iDaYSnV1Tce6b2+PT99M7VFDrGT5eozDJOWS0ifXV9B9pEWHrXOCkZrE3B7FzEoiUS2dcmwtPbHrXxketq2kb0XNOyK6XYMM50EdITSjBYhJD+UoINY8oIQgghhJApMNWZrhdeeAFHjhwB4BeiHu43xJOPvEjEVLrypKxIUrgcXafUI1FJ48Q7by4S0sp4aVHyuv1TvMSfUcnFi1z12sxNqVuJLxLJad/JVPZrcy2RczE56tJneI/bRJdFJK6cXB9xF8i9j10kqibtdDmvxbveqI2NuGqk2L557gJRlwbvvG1oEz3p0SVRa/SdaksJNozyIiE9oQSDRQjpLyXYMA66COkJJRgsQkh/KcGGTV1efPzxxwHMl1Jy8qLFS36Zm9b1ppgjie/SqVSvLqK33ZKLOMzVVfT6YrFtRqTOXH1Jry6hXc5FSHrP1av9GI0qaioHp+/Uc889V9um1y8vKjHXr4gckkqItv02UZ1DSon8WSpEJa7IM8m9Q00jo6PvwKQiCy1RCbVpQtJcvVbPJcESjTz13BW8Nsb5/YvawjbPsUtEbS4RcNd3qhQbxpkuQnpCCQaLENJfSrBhHHQR0hNKMFiEkP5Sgg2b6qDr2LFjjaMX7TSrleGs3GUlsVQuazp1badI06SYFi8JaEQaTfvpJWf1Imlysqcn3Vm8ewrMv5fesiW9Xq/PEdkxJ61E5OScjGfbtFKjfcZeEtP0XfEiPO1ymyS540xsScaPqoYklMj3zpMNo/Yr0l7KNCTFSFR2V3kx55IQOSZ3v5rKm1F5cZzfza6R95bIOzGN92ZICTaMM12E9IQSDBYhpL+UYMM46CKkB5TihEoI6Sel2DAOugjpCSUYLEJIfynBhi1awWvrPxP16YpkAs75RET8bHKpAmw/IwW37T4veclL3DY9ny6vjdRfyfooeT5dnn9Uztcscr9yIdvespfiIsXzD/PIpSF55plnFly2x9j20nfKZuf3MuVHsuan+3X1z5iUwRKRLQA+DWAOwDWqenXy+QkAPg/gtQAOAni3qv6g+uxyAJcAeAHA76jqLdX2fw/gfQAUwLcB/KaqPjuRC5gwUR8hi2e/cqllom16RFINdK2UEfHPyvlhNS3kHc0C39Wnayl9N5v2q02ahzbVBCIVExaihEHXgndJRK4VkcdE5Dtm21oR2SUi91f/r5lsNwkhCzGcnm/ybyFEZA7AZwD8EoDzALxHRM5LdrsEwGFVPQfAJwF8vDr2PADbALwCwBYA/7uIzInIegC/A2Czqp6PwWBu21huQv010IYRMgOM234tRSJD0z/HwGBaLgNwm6puAnBbtU4IWUQmMegCcAGAvar6gKo+D+B6AFuTfbYCuK5avhHARTL4SbwVwPWq+pyqfh/A3up8wGCW/UQRWQ5gBYAfdrr4PH8O2jBCljwlDLoWlBdV9b+KyNnJ5q0ALqyWrwNwJ4APRxocTk/mptSbTlHnsjZH5Dr78KJpIiLLuTQH3vV7U+JeBnzAT1lhr9GTFFN5MZLywbaR3q9IJndvGjoaSm7xJMxcYWkvXYldzn2hI9flybTp/e6Shd7SwQidJiJ7zPoOVd1h1tcDeMis7wPwuuQco31U9aiI/BjAqdX2rybHrlfVfxCRPwbw/wF4BsDfqerftel8hHHZMBEZPcuoLG7xpOSoXORJZNHn7knhkWLK4yzY3CbNwzjaWWj/3DFtUlFEnlebZ9dFjs19Ns5+tWGWB1JNaOvTdYaqPlwtPwLgDG9HEbkUwKXAi//gEELGR0uDdUBVN4+7LzkqKW8rgI0AHgfwX0Tk11T1P0+xGyEbZu3XunXrptQ1QsqkhEFXZ883Hdwl906p6g5V3ayqmz3nYkJIdyYkL+4HcJZZ31Btq92nkgtPwcCh3jv2TQC+r6o/UtWfAPgygP++xSWPhZwNs/Zr7dq1U+4ZIWVBedHnURFZp6oPi8g6AI9FDhKRURRfTl70JBcvyi8nl9nM9RYrD3hRa6lE5UUm2kzkNrLN9sVuTz+z1+9Jd7YvqaTnZVL35K6ctOBl5PdkvDZ98Z7JJPHkaPscvOn1NBu/l4Xeq5iQ+7ExTsMxISO0G8AmEdmIwYBpG4D3JvvsBLAdwD8AeAeA21VVRWQngL8QkU8AOBPAJgBfA3AMwOtFZAUG8uJFAPZgurSyYXVEI7q8d7CrpOg992hkX1eJKNKXNtKVd3wbove+S3b8aPHt3DEets/2+K7SsNeX6P0eZ3b8Ju3OMm1nuoZGFtX/N42nO4SQpYSqHgXwAQC3ALgPwA2qeo+IXCkib6t2+xyAU0VkL4APoXJKV9V7ANwA4F4AXwHwflV9QVXvwsDh/usYpItYBsD6kU0D2jBCyNRZcKZLRP4SA4fT00RkH4ArAFwN4AYRuQTAgwDeNclOEkIWZlK/ElX1ZgA3J9s+apafBfBO59irAFxVs/0KDGzJxKENI2Q2KGGmKxK9+B7no4uaNrZs2TKsWLECQD4Jp5fg04u+yUWHeZGFVsbzIu5S6cyTy2y/InJTup839e5FLOaiFy0RSTF9yb0C0N79ykmwFiuvRhOCepGYkQjJVNLzCnbb/Wx79r7kkqN6y57k3SZCM8Is+zhMmnHasAiRyGaPNhFwHrlEq57cFu2XJ0V1jdjrWlw5co05ea6L7Jq7jxFJ0NsfiN2XqNQXua6m2xf6LEIpNozhhIT0hBIMFiGkv5RgwzjoIqQnlGCwCCH9pQQbNtVBl4iMZJ5opIT3WXR6PFJLMFrfzMpaOUmzro+5GofevfAiLG2txXS/yPS6J7MCfhJRL5IyxYvYtLUnvci+XK1Le81eVFBUZrb98iRM756m57bLnrRsl1OpMlKvMUoJBmuxqUvu7O2TLntEE2x626OReZF6j1FJMFJjtauNbyOhNpXxcm2OM8LTkzcj9TDTY7z9opJg5G9nm6TN47A/JdgwznQR0hNKMFiEkP5Sgg3joIuQHlCKEyohpJ+UYsMWbdCVi+rx5C8vss/bp259SER6a5O0sA12uthLjtpG3otcVzpVbdt55plnRstW3rPtpzKelRGHkarAfEnvxBNPrO1Xbkrbq4vo3fucvBiR8dpMr3tSYa5tK0l2TRpbgsFaKnSN4uoSlZhrLycdNa0f6Nml9DPPHnkyWBupsQ1e0uloe03rHUZlR09qtOQSrUa252xcpP9R2XPclGDDONNFSE8owWARQvpLCTaMgy5CekIJBosQ0l9KsGEcdBHSE0owWISQ/lKCDZv6oGuorXuh+um656/lhfSnvjxeuL7nZ5Pzv4lkbvaIhlx79yX3Mnq+W55/V87XwUvTYJej/k5eUXDru2T3SSsAeKHsuXen7rxpm17KCs/XLb3eSPseuTD+LikjSnFCXSq08elqWhg6RxdblOtLxC7VrdedyyPa94g/bvQzz4+qTXb8aGZ/b79Iyoa07UhaD2//aBUMry+5CiaWrvanFBvGmS5CekIJBosQ0l9KsGEcdBHSE0owWISQ/lKCDZvqoEtVR+HFXsqH4X51y3Y/L6Q1dy4PK+tY6SkNhfam1CNyQnqsJ2VFMiLn0iHY/nuSXi5lRCTsObdP06zXuWdn5UYre3oFt3OyhSe72nsUlRe9voxjen0xjycLU/fuR1MFtEkT0aU4cZsi1ZHs8jki0lUuQ3pXIvcrl93dc2eJ/B1K24uk7/FsVupqEJFzvT5Gs/a3SRkxbptTgg3jTBchPaEEg0UI6S8l2LBu3piEEEIIISTE1Ge6hlOVbabUvUizNnhFqr1CxcB8ic5OuUYKXkfxIv5spvdU9rT3xe7nFZnORazYaWkv07R9draPgH8vvEz79j6mhby96Enbr2jW63FmAPciDiNRnbkC412jY0v4lbjYNP1OTyPzfPS8nqwWKaacIyKdRSt9NKVrFGnO7cOzM1EZz2LtYtPowZSIBJqLOIzIi5ZpZacvxYZRXiSkJ5RgsAgh/aUEG8ZBFyE9oQSDRQjpLyXYsKkPuoZTmJ5smPvMPhAvGi0tGtw0OWpOXvSmlXPH1LWXthlJPpeTsbxovIi8mJMq7Xk9eTOXhNTy7LPPjpa94t2pvGiPsZ95UVW5QrJeO54k2GZK3XtXLel2r5B3G0owWItNnQTTRsqOJvXtUjw7WjS5TYJNTzr0bGybwtBdJVhPrvP+jqTrXj+jyZG9ouCRqM5cEuWmiXWj97Fr5Po47E8JNowzXYT0hBIMFiGkv5RgwzjoIqQHlOKESgjpJ6XYsKkPuurqy+VqzkUiKnK1F+25PUkvmoTUThd7+3nL6TV6Mp43VW9lw/TF9JK7nnDCCQu2kU6PWxnxxBNPHC1bSc5KYunxnrzhJTT1pMZ03Yu48e5x2i/bZ7sciSTKJaNtGrmaS8Zo+9WGEgzWYiIiIXnR+ywiU0cTh3qSYi5Zb0RG9Fw7cnVoxxmlOM5ISk9GbCOb2mOszcolmvb+XkRcGtrIi9H71bQ+ZrQ+5TiiUkuwYZzpIqQnlGCwCCH9pQQbtmBiEBE5S0TuEJF7ReQeEflgtX2tiOwSkfur/9dMvruEEI/h9HyTf32H9ouQ2WGa9itqA0Rke7XP/SKyvdq2QkT+LxH5x8quXB1tNzLTdRTA76nq10XkZAB3i8guAL8B4DZVvVpELgNwGYAPRxuOJpLzpri9qdjcNLjFi4DLPciIpOn1NycvtpE6vX5ZedEuRyIsgfnyxIoVK0bLdkrdSo12OzA/4tBbjkqV3j32pFJLei6vjqM31e9FbqbrkfvqyazpOuXFiTBW+zX8To5TUmwjyUUkxVzbETuTs1+RaMRIrcdcnyPXkpPhPBcO7+9Iuh6JLPTqsEb77xGtI+sxziSm0QSuMxi9eBkWsAEishbAFQA2A1AM7MdOAM8B+GNVvUNEjgdwm4j8kqr+7UKNLvj0VPVhVf16tfwkgPsArAewFcB11W7XAXh76DIJIWOnzSxXCYM02i9CZoNFsF8RG/AWALtU9ZCqHgawC8AWVX1aVe+o+v08gK8D2BBptFHdERE5G8BrANwF4AxVfbj66BEAZzjHXCoie0Rkj1dWhhDSnUkZLRHZIiLfFZG91S/C9PMTRORL1ed3VXZi+Nnl1fbvishbzPbVInJjNT1/n4i8YRz3YIHrOBsd7NehQ4cm3UVCiqaF/Tpt+P2s/l3aoLmIDVgP4CGzvq/aNkJEVgP4HwDcFmk07EgvIisB/BWA31XVJ5KEnioitRZcVXcA2AEAJ510Uv9/WhOySExi5kpE5gB8BsCbMTA4u0Vkp6rea3a7BMBhVT1HRLYB+DiAd4vIeQC2AXgFgDMB3Coi56rqCwA+DeArqvqOanp+BSbIOOzXK1/5StovQiZICxt2QFU3ex+KyK0AXlbz0UeSdl0bkENElgP4SwB/oqoPRI4JDbpE5DgMDNYXVfXL1eZHRWSdqj4sIusAPBY513C2y/rS5FJGeGkTon4Qnq5u2/eKPOd08a4h07Zf3n7RAqj2vng+RnafnK+GTTNh74v1D7Pnevrpp+cd7/lLeT5h9n7n/PG87Pr2Gu25rA9Z+pntc5oFv66NFM93K/cee8yAT9cFAPYODYqIXI/BtLwddG0F8IfV8o0A/lQGL/VWANer6nMAvi8iewFcICL3AvhFDPyqhtPz850Dx8g47deE+le7nMOzTVE/Lvvd8uyH53eaa9Ozsd4+6XrEvyuHZ4s9m2GvHYinjYng/S3x/EhzRPx+2/heecvRdzL6vkYZtw1T1Td5n4lIxAbsB3ChWd8A4E6zvgPA/ar6qWifItGLAuBzAO5T1U+Yj3YC2F4tbwdwU7RRQsh46eDTtdD0/ILT63YfVT0K4McATs0cuxHAjwD8mYh8Q0SuEZGTxnQr5kH7RchssAg+XREbcAuAi0VkTRXdeHG1DSLyRwBOAfC7TRqNTKX8PIBfB/BGEflm9e+XAVwN4M0icj+AN1XrhJBFoqXROqCqm82/HVPo6nIAPwfgs6r6GgBPYRA5NAlovwiZEaY86Kq1ASKyWUSuqfpzCMDHAOyu/l2pqodEZAMGEuV5AL5e2ZX3RRpdcM5UVf8egDeHeFGkkSHHjh0bSTt26jWX+d3iTZnaKc506tab1o1M/aYP1ZtKjUyxpv3yXpjI9Hpu6tj2JZJuI3eNXvh1LuQ6ci+8a0mn+k866aeTHytXrhwt20z5tr1cdnt7L62kaKVG795byTUlIi2PM3x7EdgP4CyzvqHaVrfPvsrH4RQABzPH7gOwT1XvqrbfiAkNusZpvxq0ueA+XdNE5OQ677zed82TFxO/t3nn8mypt5yTCiNyV2Q57bO9Xttfe73pvUttUB2e1Jj2JSKb5ioIWDypN5IyJ3fe3L2sI32ncu/IUkdVD6LGBqjqHgDvM+vXArg22WcffLuSpVH0IiFk6TKh6fndADaJyMbK4X0bBtPyFjtN/w4At+vg5DsBbKuiGzcC2ATga6r6CICHRORnqmMuwnwfMUJIgUx5pmtRYBkgQnrCJIyQqh4VkQ9g4McwB+BaVb1HRK4EsEdVd2LgM/WFylH+EAYDM1T73YDBgOoogPfrIHIRAP4dgC9WA7kHAPzm2DtPCJkpZnUg1YSpDrpeeOEFPPnkk6PlUSeS6Vovn5d9IN4UbyrjRaa+vSnWdOrWm+L1jo9GQnrTzVGZ1UbmeBFD3v3OZWT2JAwvu3u0z14UqpUNgfmS4qpVq0bLaYb4IVYqfOqpp+Z95sl93rsWjVz1sl5bcpG69piuBmdSBktVbwZwc7Lto2b5WQDvdI69CsBVNdu/iUGW55mkqSwDxDKcp/JNxN3Aaz/9bnuSol32pM70+2C/N140shell5OoPLksKq1G7K8XuZ6uexGP0QjHiATsXVfary4Ri7l75BWs9t6pcUcrpnDQRQiZCWZ5up0QQkqxYRx0EdITSjBYhJD+UoINWxLyYhox4k3Feok07YNKp2W9gqSRiLJ0uthON3tRghFpNO2n7WOugGqkX1aiszKg3SeaxDMy9Z0r4OwlJ/SipVJ58eSTTx4t20hGG03oSYXpPfKSPnqygdff6LXYfnlyZHpMmwSMlhIM1mLT9B63kRS99iIRaTm5KVIA2pL7nns2y4v+zsnw3nfAuy9R++PZ+1zBe889w5MavehlwI/y9mRHz2YAzeW+rhGx0USr46YEG8aZLkJ6QgkGixDSX0qwYRx0EdITSjBYhJD+UoINm+qgS1VHkS45ec/KYp6M6EVa5KbBvYhFe65oNJkXteJFyaXXa/tl6wR6kUCWdHreRvN50+he0r/0Gr0p+WgkpTfdvmLFitrttl9pVKI9xkqKueSuQ9J7lGtniH12NnLSLgPzZVDbL9umlSly8qJ3fFNKcUJdirS57568GD1XRG5K37VcUuMhnlxvbXK67kmKXo3D9PtnvwNejVivj2n0tO2XZ1dz8mKkjqTtvxeJDfjuBpHI0+h7EJEX033a1H4cEq3p2IZSbBhnugjpCSUYLEJIfynBhnHQRUhPKMFgEUL6Swk2bKqDLhEZTRnnksp5SUi9aVE7DZ5ON+emkod4kSV1/a9r05MB7XXkoirt1Lc3DW6xkTRpO3Z63ZPhbF9S2cBOydvPvEikVCqw0psnw3mRQKkE6km9XuSnF32TtmkjIb3oQy8xa3q8vS5PJopGL3qyZ5QSDNZSYZySYrSdprXxcklILRFJMbVFEdcH+z5bW2DdBgBfXvQiP3PuJLbPNlnyM888U7vd2jsgX3u3rl/Rv2OeLYtED6ZE3qOu0YuWiDvHuCjBhnGmi5CeUILBIoT0lxJsGAddhPSAUpxQCSH9pBQbxkEXIT2hBINFCOkvJdiwqQ66li1bNtLzrd6d+ih5Pj+WSGHVKJ7GnstW7Pl0eSkucqkV7DVa3wkvPDdXyNb6R3j+RjmfLuvvYJe9CgKpH4D37Dz/rlwIsue75W33fNDSftlM916BW+t3Yn24gPnX4vlqeD4v0fegDSUYrFmjaRb69Bl6tslLeeO1nRIpZp/z6fJSQ1g/Lvu9sd+n1Hcxl3ZhiHfvctUivMoRXlofYL6PV+Q7nMvsb9dt+95z9NrL0SZlhCXiM5jzNWvjp5ijBBs2vfz+hBBCCCEFQ3mRkJ5Qwq9EQkh/KcGGTXXQNTc3h9WrVw8aNtOyVm4C/OlmL5w5Gl4bCQe25IpUe/KindLOpQqISIdeZv50et7KZXbZS0FgZcN0et2GVnuyg92ePjsvtYQ37W/Jpa+IZJTOTZV77XtShZfiAvAzZXdNI9C1sGwJBmup0DSVQ1tyKWyGRN8hz3XCs6te1vm0Hfu9iaSMSfsYKZ5tse2l300v8713X3IuJBF7n/ub4rUZkRrT5x6R7roWVPck61wh7nFIil5/+gpnugjpAaVE/hBC+kkpNoyDLkJ6QgkGixDSX0qwYVOXF0855RQAfpQd4EeEecVMLbnIPi9iJ7Kc9iVScDYnodr97DS4N71uJa00mm54TwGM5FvgxZmfhxw5cmS0nE7Pe8VkvQiWXDSLl7nZ7uMV/gaAJ554YrRsZU9PWs5lt7frXlHdaCShJ3t4BXJz702ueG9TSjBYS5GcBOhJ0YuBZ9u8COBcNJ1n26wt89wIrHsDADz55JOjZe87b7GypbV36bpXOSL3nbPrnqQY+Z4Dvm2yeFVLon97PEmwa1ShZ+9zNobRizEWdCIRkZeIyNdE5P8VkXtE5H+ptm8UkbtEZK+IfElE6r9hhJCpMJyeb/Kv79B+ETI7lGC/Ip67zwF4o6q+CsCrAWwRkdcD+DiAT6rqOQAOA7hkYr0khCwIB1210H4RMiOUYL8WlBd1cGVDPeq46p8CeCOA91bbrwPwhwA+mzuXiIymn+0UcRplZ6dcvcgJb0o/ncb1ptS9pHQ2Si6dXm86xetF0qSfeVErdrvd38qJAHDqqafWLttIRnvv7HS+LewM+NPgXgLXNpF9nqT41FNPzTvG9tNKova52H5ZOTUnL3rRi947kb5rkShDLwoqPZf3vJsyy0ZokozTftl73DVStasU0zVSLRKZZ9/NXKH2SBJS+z0/ePDgvHPt379/tPzwww+Plh9//PHavtsC9OvXr593rpe//OWj5Ze97GWjZWvnrC1OXTC8iGnvexr9/kZcLXJ47bR5D237njzaJnlv13e6FBsWilEXkTkR+SaAxwDsAvA9AI+r6vAbug/AeudwQsgU4ExXPbRfhMwGJdivkCO9qr4A4NUishrAXwP42WgDInIpgEuBFzuTE0LGx6waoUkzLvt15plnTqR/hJABJdiwRtGLqvq4iNwB4A0AVovI8urX4gYA+51jdgDYAQArV64c3dGu9aDsdLed6o4mmPTkLnveNJrOTr17U/peBFwqw0US99m+WDl27dq18/Y744wzRst2Sn3NmjWjZTvtb2U7O1Wf9tnri5X6ctGL9h6niU+H2Htsz5uuewldvQSw6XV4EYteJFNOZvawbbaRDdrUXrOUYLC60NV+nX/++Tq8x9GotabPJH1vrG3wpBzP/qTn8mQxT/7OSUdeXUG73b7PNirRyokAcN99942W9+7dO1p+9NFHa/tlXSjOPfdceFjb4EVVpvbDrlubY21DxM2kbn1ImxqclojUGI0w95YXy5aUYMMi0YsvrX4hQkROBPBmAPcBuAPAO6rdtgO4aUJ9JIQEoLz4Ymi/CJkdSrBfkZmudQCuE5E5DAZpN6jq34jIvQCuF5E/AvANAJ+bYD8JIRlm2QhNGNovQmaAUmxYJHrxWwBeU7P9AQAXNGlMVUdykp3KTGUVL2Gcl6wzGmXjyXie9BWpe5ae11tO5S67bpe9aXsbiZjKi1ZStNE8Vna0/nQ2SjCN3rH326t32ObZebUb7RR+Kufaddt+5B7narLZ/nsJd+09SvtlDYOXkNXeb3tP0ql+L4qsDZMyWCKyBcCnAcwBuEZVr04+PwHA5wG8FsBBAO9W1R9Un12OQTqGFwD8jqreYo6bA7AHwH5Vfesk+j5O+wXU24SukYzR/bxjvPcr2kak/6nt9JIKW+x368c//vFo2UYoAsD3vve90fK3vvWt0fJDDz00Wrb33dq7tO82Oerpp58+WrY209qGnBuC97cjEsmY28/iHZ9Ljmqfq/cc2siLHlEJlclRY7AMECE9YRIGqxoYfQYDWW4fgN0islNV7zW7XQLgsKqeIyLbMMiB9W4ROQ/ANgCvAHAmgFtF5NzKsR0APoiB1DffsZAQUiQlDLpiXueEkCXPhHy6LgCwV1UfUNXnAVwPYGuyz1YMcl0BwI0ALpLBz96tAK5X1edU9fsA9lbng4hsAPArAK7pfOGEkF5Qgk8XB12ElM1pIrLH/Ls0+Xw9gIfMel1Oq9E+VTTgjwGcusCxnwLw+wBiGj4hhPSAqcqLx44dG/nKWP+V1A/LC131fKxyRWW9Qsee/uxlEk+x/Yqkqchp4ZG0GNYPIfXDsv5eNpz6pS99ae0x1o8qvUbre3Ho0KHRss0ObQvRplnkvVQcdnvEbyw9xise64V/p6Hgdj/P18L2xd6jtECvPd5r3/OviKY0aUPLX34HVHXzuPuSQ0TeCuAxVb1bRC6cZttdUNXRuzuuSgJA3P/GEnm/cj42Eb+e3D5eO14KFvsdOnz48Lxz2dQQNp3Egw8+OFr2fHut3xYw32ZZ2+QVk0+/j00zx0fseG6/Nj5duf3qaJMyIkr0+tucr6/Qp4uQHjDB6fb9AM4y63U5rYb77BOR5QBOwcCh3jv2bQDeJiK/DOAlAFaJyH9W1V+bxAUQQpY+sywZNoHyIiE9YUI+XbsBbBKRjSJyPAaO8TuTfXZikOsKGOS+ul0HJ98JYJuInCAiGwFsAvA1Vb1cVTeo6tnV+W7ngIsQUoJP19TlxWEYsZeCAIhNWdqpXyvrpOfyZAB7vJfdPi2a7MmNXsoH216aDsCGU3sZob30Cyle2gRPhrNt2Ez3wPxUB3bZyzqd0jTFh70v6TV6xcNtv+yzzxVRt9fvvXu2X/b5pNJEpNh6LmO5R1fpcRJGSFWPisgHANyCQcqIa1X1HhG5EsAeVd2JQY6rL4jIXgCHMBhIodrvBgD3AjgK4P0mcnGmydmoNnKdtz0iHUZS1gDz39umElPURkdksPR7HikOH1mO9muckmAbeS2SUT4nG3Zt33t3vDbHmXpkGudY6lBeJKQnTMpgqerNAG5Otn3ULD8L4J3OsVcBuCpz7jsB3DmOfhJCZhsOugghM0MJBosQ0l9KsGGLNujKyUqRoqtWbsplfveiJL1oOks6Pe8Vg/YKHdvrsJFxaZte/20frXRmowfTdRuxk0bdDfEyr6efeZGFdjmVTb0vjTd1brfnqglYvIhBTw5Nz2XvvZfR2ZOMU5pGO+UKB+faWYhZ9nGYJYb3eBbudS7i0HvvI5nX0/WIC4f9zq5cuXLeuWy2eFtFw3PBWLdu3WjZRmsDwKpVP82za21D1PZ7f5faRKtGpL9pvEfR6EWvuHr0XF0pxYZxpouQnlCCwSKE9JcSbBgHXYT0hBIMFiGkv5Rgw6Y66Fq2bNlomtkrgAw0n5b1ouHSdtK+1J3Lm1IG/MKyngyWi2Dz+uVFLNo20un5gwcPjpZPOumk2jat9GblyLT47A9/+MPR8o9+9KPRsk2aamXL9DoiUVGeDJfeR0+C9QrW5uQ9rx27nEuuarHvhdevXJFrSy7arCklGKylgpfAOf1snPKLJWIj27x3nl1M2/AiDu1+ns2yEiIAbNy4cbRs7beVDu13ziZ9Pvfcc+edy0qPVmq07gZeAldgvj2zfRlnEtLI8W0S247zXYsm3B33+12CDeNMFyE9oQSDRQjpLyXYMA66COkBpTihEkL6SSk2bOry4nCa2UbJ2WXAjzSJSEQpdoo4lR6b4kWaeZFAuWlsL8GfPd6LsovWFbQ1zuzxVh60dc8A4KGHflqfeN++faNlKzU++eSTtX0E/FqXEWk2GiHlSTu5upleZKBt30aI2nfF3t+0L965PNkzR5foRaCMX4mLzfDda1MvsQ2RhJlRSdCTjOy76klqOXnRO8ae10p9Z5555rxz2XPbOrK23qvdZ/Xq1aPlDRs2zDvXWWedVbuf/W7Z/qZR5V7Etmeju7oHRGpr5j6LvGtdkzPnrpHyYnM400VITyjBYBFC+ksJNoy1FwnpCU3rlpVg4Aghs8M07ZeIrBWRXSJyf/X/Gme/7dU+94vI9prPd4rId6LtctBFSE/goIsQMstM2X5dBuA2Vd0E4LZqfR4ishbAFQBeB+ACAFfYwZmI/I8AjjRpdOo+XcOUBl6RaWC+5u75dKXn9fB8ujzfh1x2e09L9/rlFX9O1+1+9lze9lwh2yNHfvr8re+X3cdmoT9w4MC8cz322GOjZevH9cQTT4yWbVh1eo+8TO6ej1MuC7JXKcC7r9YfI+fnZ4lkzY4WvLZ471fOb60LHERNHhFp7LfT1OelzTP0/EOjPl2ef2ou5Y3n02W/K9ZHcsWKFaPl008/fd65bDqb0047bbTsVdSw51qzZv7khM1ub+2f7b+1E2kb1r/Y+3sRyexft96EqJ+gt72rzYkUVE/362p/FsGGbQVwYbV8HQY1YD+c7PMWALtU9RAAiMguAFsA/KWIrATwIQCXArgh2ih9ugghhBAyi5wmInvM+g5V3RE89gxVHSaqfATAGTX7rAfwkFnfV20DgI8B+I8A6n8dOHDQRUhP4EwXIWSWaWHDDqjqZu9DEbkVwMtqPvpI0q6KSLhxEXk1gH+uqv9eRM6OHgdMedAlIiMJx97cNFQ+It9YcmkhrBTmFW32+pKmZohIVl52/FSislPcdj87XeuluEhfTHsumybCnsveBytB2kzz6brdzx6fm1L3JEWvQLklvb+5wtp1/bLSQNqGlynbEsl6n57Lk3Y8+cWTTNPztoGDrskzfL+7yirjfNbeO5jaUc89wvvO5lKweOlw7PfcHmO/TzYtBDBfhrTyoPedt21YaTJtx16XtRNWUrTVOdL9PPcOz4UiKr1FCoTn3g8v/Y4nKabvQaR4d18y0qvqm7zPRORREVmnqg+LyDoAj9Xsth8/lSABYAMGMuQbAGwWkR9gMI46XUTuVNULsQBh0VlE5kTkGyLyN9X6RhG5S0T2isiXROT4hc5BCJkcdKT3of0iZOkzZfu1E8AwGnE7gJtq9rkFwMUisqZyoL8YwC2q+llVPVNVzwbwCwD+KTLgAppFL34QwH1m/eMAPqmq5wA4DOCSBucihIwZDrqy0H4RssSZsv26GsCbReR+AG+q1iEim0Xkmqo/hzDw3dpd/bty6FTflpC8KCIbAPwKgKsAfEgGc4pvBPDeapfrAPwhgM8udK7h1GYuSjAXqVeHnRLOPQhP7vOOyZ3Li+jwpvfTqXKvL950sZXO0n7Zzzx50u5jp9RtJGO6nz3ee17ps/My0tv9vGtMJVjv2UeiF9Npb09ejLxfbQrZTltyKnAQFWZc9ktEauXFVL7p8hzayDURqTHdz4vA8+TFFM+2eZHNtr1UEvSKznclYvNSedGTND1XiZwt8Z6LJ9vm3GqaRina5Zw07GXajxbVHnf1hWnaMFU9COCimu17ALzPrF8L4NrMeX4A4Pxou1Gfrk8B+H0AQzH+VACPq+rwDbUe/fMQkUsxCKkc6xeKEDIfDrpcPoUx2K+0fA0hZLyUYMMW/JkvIm8F8Jiq3t2mAVXdoaqbVXWz/YVACBkvlBdfzDjtl3XyJoSMnxLsV2Sm6+cBvE1EfhnASwCsAvBpAKtFZHn1a3EDBl7+WY4dO/ai4tbAi6coI9Eh3tRtbrrTm36NJA1M+9VUXkyneCPTyrZfqfRmsVP6XiSnve9eUde0L/b6bVSQl/QQmC8deJKiJSole4XAvSjBtJCtxetXNPlu5Bhv/1xR665GZFaN0IQZm/0C6t/R6H2P2J9ce953wGK356LCvfPa70Ykyi3dz9qiaHJQ+2M8UvQ957bhuRtYGdHaQttfYP512n5Z+xdxmwBidiqXgNbDe1+iUaxNswNE2gbGY39KsGELfitU9XJV3VB56W8DcLuq/iqAOwC8o9rN8/wnhEwJznS9GNovQmaHEuxXl9qLH8bAKXUvBj4SnxtPlwghTWkz4JpVozUmaL8IWUKUYr8aJUdV1TsxSAwGVX0AgwKQYY4dOzaKHMlFL3pT720kKi8yx4vksc7+qeO/XU8jcIZEE5p6L4xXBy1aozA39T4kF33oPRc7pZ67R3a/SALJaDJHT6qIJAcE/FqXuWO8tr13ypNGPMkmXe9Sqw0oY2q+C13tF/DT9y1nl7znEJEXc9FhnhtD5LuVrnvvnX2H7Xc592550pmV8XJ2yUto6kWIRpNhe8teTUXAt3m2j3bZeya5PntJn3OSc9Moac/9JndMl/ai512IEmwYywAR0hNKMFiEkP5Sgg3joIuQnlCCwSKE9JcSbNhUB13Hjh0b1b3y6twN9xsSiSjzpEIgVv/PS86XRubZqD1PMvIkvZxE5dX18ur/5eQMO9UfkatSedGL0vGkzlw0iyeBeP3NfeG8a4lIkGlfIlFFOdnP3jMrM0fuXSpBjtPIlGCwlgo5WbrLc0i/TxE7533PUlnJsw2evJlzAfHajHyfcpKg9x2OyosRNwJLLrlzJGLR62PaF6+mo/e3LvceeERcJVKaRmLn3vUuUZHe+ftINycSQsiSYJKO9CKyRUS+W9UpvKzm8xOq+oV7q3qGZ5vPLq+2f1dE3lJtO0tE7hCRe0XkHhH54LjuAyFkNqEjPSFkppiEERKROQCfAfBmDDK37xaRnap6r9ntEgCHVfUcEdmGQV3Dd4vIeRikaXgFgDMB3Coi5wI4CuD3VPXrInIygLtFZFdyTkJIYczqQKoJnOkihOS4AMBeVX1AVZ8HcD2Arck+WzGoXwgANwK4qKpvuBXA9ar6nKp+H8BeABeo6sOq+nUAUNUnMShEXVuGhxBC+sRUZ7pUdaRtR0NtPaxvTG507PnfWKxeH8227mWL98KvU1+e1I+tbns083HEp8srOJv2w7tGi+erkH5ml5v6d6XHeL4m3v2OZk72ivV6vnmA/+y8Z9Tm2bVhQr8S1wN4yKzvA/A6bx9VPSoiP8Yg99V6AF9Njp03uKqkyNcAuGusvZ4Qw3cy6tPlVXiI+vJE3nvPXuZ8urzvh/cdyvk1RnzKchU4ct+1uuO95bpzD7H99/y20nUvlYXXr5yvmpeF3pKzX019r3J4zzXSRvqu51L+tKGEmS7Ki4T0hJYG6zQR2WPWd6jqjjF1KYuIrATwVwB+V1WfmEabhJClCwddhJCZoaXBOqCqmzOf7wdwllmvq1M43GefiCwHcAqAg7ljReQ4DAZcX1TVL7fpOCGkX3DQNQGGU5CRgs+AP6XuSTy5kHxvWtWey6aMSNuIZLT3+mKntNN1L0O8lfpycqondUQKVtvlun4OscVjh1UFgLy8aD+LFs+1NJXbcqkschn9h3hT5en+Xii896556TaAvFTShAlG8+wGsElENmIwYNoG4L3JPjsxqF/4DxjUM7xdVVVEdgL4CxH5BAaO9JsAfK3y9/ocgPtU9ROT6PSkGD7v3Pvh2TNP3stJlU2rcETtqkfErqXtR4pU595Nr5+eVBlNLRORFHPyYiR9RU5e9L7bkWoEbeTFyN+63Lki7hmTlBdnOSKxCZzpIqQnTMJgVT5aHwBwC4A5ANeq6j0iciWAPaq6E4MB1BeqOoaHMBiYodrvBgD3YhCx+H5VfUFEfgHArwP4toh8s2rqD1T15rFfACFkZuCgixAyM0zKYFWDoZuTbR81y88CeKdz7FUArkq2/T2Abt7AhJDewUHXBBhOW3oSTYqXFdnbnk6LegWJvann3BRrJAuz1/d0Gttr38qb3nXlopI8edFKlTl50bZpz2tlQ9uG3Q7MlxStJBnJhh2durbLXhRVGqnqTaN7FQC8fuT6H5UKLOPM6FyCwVpMVHX0HrfJ/m2JVN3IfRZ516KypyUqL1oi0r3XBpDv85CovNj0e566U3j235Ntc9nxI5KiF+GeSrYRmxl5V3LnijzvXPHsrtHX6fn6Cme6COkJJRgsQkh/KcGGcdBFSA8oxQmVENJPSrFhUx90DW9qtNCxJ3d55KIXvSLG3hRpKp1Z7Lm8IquWXGFpKyl6UY22vTRi0Ium8ZKA2v560YrpMVYqfPbZZ0fLzzzzzLxj7H65+1dHLkrQS7TqSbi5AuOeTO3Jzzl50TuXJSdFeclZ21CCwVps6iS6NrJwV3kx8qxziXg9m+fJi1GJPBLV2DUyr030ovf9z0VeetGHnr1vE4UflRcjCVGj7g1NE6Lm/u6O2+aUYMM400VITyjBYBFC+ksJNoyDLkJ6QgkGixDSX0qwYVOvvTicmvUSZw73G2Llr0jNqlTiaZoI08o96bm86WOvdliuX/a6crXA6tpIZTsr99nP7HSxd7/Tvtupd/vZkSNHapdt23V9G+JJcpZc9I8nW3oyYE7O9ZLGes8kVxsuIi/mEqDa59JFXizFH2IxUdVaG5CL+opIjzlXi6Y193KyeCQhazTZZSTSLRol50lvTZOApkRqDEaj8bwoxdyz89qMuDpMqr5irp3cfRmSS8zdlVJsGGe6COkJJRgsQkh/KcGGcdBFSE8owWARQvpLCTZsqoOuY8eOjWQiK0vlptQjEYteNEjueG+6OBclE5EKvGi6XJSgxZvqt9JTGjGYk/vq2rdSXZpE1O5n27fnffrpp0fLuQhFey+8pK8Wr+9pX7w27bPPRRx6cq6X9DVtz4s886bnvShSoFu0Z0oJBmupEJWCvJqpni2JRkJ6UXdtIg6jUpLFs6tem9E6jm0SDEeI1nH0XAE8STEXhRqJUow+L6/PkTqOKZ702NV+RJPp5ijBhnW/S4QQQgghZEFCM10i8gMATwJ4AcBRVd0sImsBfAnA2QB+AOBdqnp4Mt0khCxECb8S20D7RchsUIINazLT9S9V9dWqurlavwzAbaq6CcBt1TohZBEYRv40/VcQtF+ELGFKsV9dfLq2AriwWr4OwJ0APpw7QFVHfjvWlyVXpNrzN4hm8rV4Wc09/53UbyGin3shwOl1eFnkvf5aP6qnnnpq3n7Wp8v6e3kpFKzv1IoVK+ady7v3ER84wPfjssvWjyznw2L92Gyfm2ZnTvtl3xHP1y7Xhud7FcnynR7r+Yq0YVaN0CLR2H6JyOg9alooGIj5TkWLOdt3xSvSnOuXl3k+UmQ+189I8eocbTLiR84VTYvh+XR5x+fud1M/rpyfXSSVRxsfOO8Zefcu5389DkqwYdGZLgXwdyJyt4hcWm07Q1UfrpYfAXBG3YEicqmI7BGRPSXcUEIWi1J+KbZgLPbr0KFD0+grIcVSgv2KznT9gqruF5HTAewSkX+0H6qqikjtHVDVHQB2AMDc3Nxs3iVCZoBZNUJTYCz26/zzz+cNJmSClGDDQoMuVd1f/f+YiPw1gAsAPCoi61T1YRFZB+CxwHlGcopXtDglEnZrJbFckVeLV8DUSlq5TORehnVvijg9VyT7uN3Hyot2GZgvKVoZLpeh3SMij+aenVfI28qYXpqGlEgxaHu8J2ECfrZ5+x558l7ax4hs4ckGaRu58PWmlGCw2jAu+wX89LnmpBzv2Xvh+bl3ICLjecvpdzOS4d2+n11TGHh9z0lnkWzpXaXGnFTnfea5luTSFTVNDZFzOcllvq9rL/ccukqKHuOQGkuwYQvKiyJykoicPFwGcDGA7wDYCWB7tdt2ADdNqpOEkDx0pK+H9ouQ2aAU+xWZ/jgDwF9Xo9jlAP5CVb8iIrsB3CAilwB4EMC7JtdNQshCzKoRmjC0X4TMCCXYsAUHXar6AIBX1Ww/COCiJo2JyEi+sjc3nZb1Mrlb6SsSGQLEIoY8GTAXqREppporIOpFSXpRlVZCTKU2b+p5nBmdPQk4lS09Gc9bzuFNcafSYd1506hMKz3aa/GilXKFqL0oWC+KzJIzKl0zOpdgsJoyTvsF1MuLkf1TPOk+mkk8sk+u0LHFsxm5fkWqeESk94U+W2h7VEK15KIEI3KuV6A7Wlja4smZUTcE73nlMs03/ZuYsyvj/BuzUFt9gbUXCekJJRgsQkh/KcGGcdBFSE8owWARQvpLCTZsqoOuZcuW4aSTTgIwf3o6lRe9pJqRCLSUyLSuF2GUTsNaKc0uW7nLi6RMz+UVd/aSkOZkT3v99n7Z9u39sv21Um7afw9vejvtSwS7f9oXT3YYvkO5c9n7UHfuIVYqtAl7vYjQtF+eZONJjbmkrV2m52fZsXQWyUV3RWRi+6xzEbQRWS0a5ed9FnFJyJ0rkui5TYSmR046a+r2kXtWkcTcUXnNe1+8otq5qEpLxI1hVuTFUmwYZ7oI6QklGCxCSH8pwYZx0EVITyjBYBFC+ksJNmyqg665uTmsWbMGQD4Jn5W4TjzxxNGylYgikThAvrZfHV7S07R9K9FFkm2myVHteiSSMRfh40XmeXKoFx1ad+6F+pK7314kZkTaAOZfl5dQNRJVlOuLlRFtTUsrKab1Er1am560nJOPcnJ2U0owWItN5Bl57goeOYm5aXLU3LGR9yMiz6XrXgRvNCq8S4LgnHtDRF7Mtdf0fuWeXSSqMycJNo3qzF1jpF9eH9tEizahBBvGmS5CekIJBosQ0l9KsGHdEgMRQgghhJAQU53pWr58ea28mE7ZexKZF7WSO5eVhnLRIXVtpNKbF1VppUY73Zqr4+hFzXn1Hj15MF23y570lUsma/GkQtvHVC6zz8Vel5eENCd1epGNkSSkab9sn610aCXFI0eOjJZztTG9hL3ec7B9zL0HXeTFSUb+iMgWAJ8GMAfgGlW9Ovn8BACfB/BaAAcBvFtVf1B9djmASwC8AOB3VPWWyDmXIqo6ekbRiC5ve9e6gl3rD+Zk/QiedOdJq7lIbi+5cySqMlfvMGrnLG2kP297l6Sxuf56zysaOe61v9juDYxeJITMFJMwWCIyB+AzAN4MYB+A3SKyU1XvNbtdAuCwqp4jItsAfBzAu0XkPADbALwCwJkAbhWRc6tjFjonIaQwShh0UV4kpCdMqGDsBQD2quoDqvo8gOsBbE322Qrgumr5RgAXyeDn+FYA16vqc6r6fQB7q/NFzkkIKYwJ2C8XEVkrIrtE5P7q/zXOfturfe4Xke1m+/EiskNE/klE/lFE/qdIuxx0EdITWg66ThORPebfpclp1wN4yKzvq7bV7qOqRwH8GMCpmWMj5ySEFMY0B10ALgNwm6puAnBbtT4PEVkL4AoAr8Pgx+IVZnD2EQCPqeq5AM4D8H9HGp16RvqVK1cC8LOtA/M1fqtT25vs+WflfLq81Aye70CaMsL6btmCyl46g1zouFdc2bt2e3zq0+X5mnkpDHI0DZNO8e6r97xz/nhpVvm69r2UC2maB+vH9fTTT4+WrR+X3ceeK1fU274HNlO+3cfzc0v76fnzRWlphA6o6uZODRdExKfLK6geyWTeteC1pU3KiGjbkf5H0l2k6xG/Int/cz5duRQyXh8jfliR/aP7RQufe/5x3nVFU0ZEstOPOy1EjinLi1sBXFgtXwfgTgAfTvZ5C4BdqnoIAERkF4AtAP4SwG8B+FkAUNVjAA5EGqVPFyE9YIJOqPsBnGXWN1Tb6vbZJyLLAZyCgUN97tiFzkkIKYiWNuw0Edlj1neo6o7gsWeo6sPV8iMAzqjZp3ZWXkRWV+sfE5ELAXwPwAdU9dGFGuWgi5CeMKFB124Am0RkIwYDo20A3pvssxPAdgD/AOAdAG5XVRWRnQD+QkQ+gYEj/SYAXwMggXMSQgqjhQ3LztSLyK0AXlbz0UeSdlVEmjS+HIMfi/+Pqn5IRD4E4I8B/HrkwKkynKqMFgf1JEG7nMvq7cmLnjzppVYA5ktGXqoD23crG6b98uQ2L/tvTvb0+hIpSpv2q+nUcw6v+G30+EhYut3uZZoH5suIXuZ5+xzsPU5lzlWrVo2WTznllNGylRft8bnUId770oZJDLpU9aiIfADALRikd7hWVe8RkSsB7FHVnQA+B+ALIrIXwCEMBlGo9rsBwL0AjgJ4v6q+AAB15xx75xcJ7/2MSlGWpukkuspdkX7k+hVJl9EmHUL0XE37FZVgvfvVJs2C169oBYCuMnOEaUqKlnHbMFV9k/eZiDwqIutU9WERWQfgsZrd9uOnEiQwGGjdicFM/tMAvlxt/y8YRHEvCGe6COkJk/KHUNWbAdycbPuoWX4WwDudY68CcFXknISQspmyT9dwhv7q6v+bava5BcD/apznLwZweTUz9n9iMCC7HcBFGPy4XBAOugjpCVM2WIQQMlambMOuBnCDiFwC4EEA7wIAEdkM4LdV9X2qekhEPoaBmwUAXDl0qsfA6f4LIvIpAD8C8JuRRqc66FLVkZzjyX5ATPrzMtWneJFyXpSdJTd17UXQeJJaSiRKxsu8nIvYsdi+2Kg5T7LNte/d7/QeeX3xsjvnIg49edR73laeS+VFG7EYiVK0kqKVEwGMqioAwOrVq0fLNpIx0jbgR7E2ZYKO9MQQcY8Yp/zT9Fy5/SMZ1rtKUdPIrh+NzLPLnl1O5UEvEj5y76LvRJvKBF2k5dy5cq45dftMUnactg1T1YMYzFCl2/cAeJ9ZvxbAtTX7PQjgF5u2y5kuQnoCB12EkFmmBBvGQRchPaEEg0UI6S8l2LCpDrqOHj2Kxx9/fLRst1u8G2/lH6/ocC4JaSRZX06qjCTYi0xPt+mLJ62m2HaspGjlNitx5SQ9e4+9At+pnGj75hXJjkQIpX3zpr49eS5NQuoV3/YKVtuoxLVr1847l123+9n74r3fUSm8DSUYrMVm+P3oGoHn2Yz0vF7CzDYyTyRxadcoPU+K6tp3S0468yTFaBSpd81tvltN70Wbe9RVDo5Ih+N8dgtRgg0LlQESkdUicmNVX+g+EXmDBOsWEUKmw9Anosm/EqD9ImQ2KMF+RWsvfhrAV1T1ZwG8CsB9CNQtIoRMhzYDrlk1Wi2g/SJkiVOK/VpQXhSRUzDw0P8NAFDV5wE8LyKRukXzOHbsGJ588kkAfiRhild7MSoJWnIJRuvO5UXipX2x/Y/UGAR82cC26SU9Tfvl1XrzovlsNF0qL3r32/bFkyBzx3sRqTn515Mnve12OY0EtOe2z95KgsO6oMD8qEQrIQLAySefPFo+8cQTa89riSYCbpNo0TsXGTBO+yUio/c9J7lEIgOjUXZdZKk2EZYRCTL3mSfpWXJ2NUL0PY8mRLU0rf0YTdQakRpzNJWD20TEdpURx2F/SrBhkdHKRgxyUPyZiHxDRK4RkZMQq1tECCGLCe0XIWTJEBl0LQfwcwA+q6qvAfAUkql4HQxPa4eoInKpiOwRkT3RHFaEkOaUMj3fkLHZr8OHD0+8s4SUTAn2KxK9uA/APlW9q1q/EQOjFalbBB1U/N4BAMcdd5wOZa7cDcsl32yKJyl606e52osWLxrPS/oalVDtspXucvKil0TUk9tsJF8aMedFiHoRVqmklsqNdfvZe5G7R00lRXt87h5ZSdHKg1Y2tFKj3afu3HV9sfc7+h50fddn1QhNmLHZr1e+8pU6fPbRZ+VFMHuyelRitu+gJ2NF6xJ63+3o+xTZz7aXfgciNVaj96Xrd8D7uxCRFNNjm0qKOXkwKh02ZanZnBJs2IJ3XFUfAfCQiPxMtWlYY2hYtwjw6xYRQqYEZ7peDO0XIbNDCfYrmqfr3wH4oogcD+ABDGoMLUNN3SJCyPSZZSM0BWi/CFnilGLDQoMuVf0mgM01H72obhEhZHEowWC1gfaLkNmgBBs29TJAdRpyrmiyXY4UvM75MURSTuSy23vn8vy4PJ+kunMP8dJERH3NIhnxo5nyveVopuaIv0DOVyEStuylr0jvkf3M+mjZItV2u30Oab9sRv9Iyopcig7bf9tmG0owWIvN8J2O+sJ4Nsfzccr58kTOm6tWEfFLivp3dcnWHvU1ixD1fYqkScj1M+LHlbuuSB/H6dOVu6fTuN9tKcGGsfYiIT2hBINFCOkvJdgwDroI6QklGCxCSH8pwYZNddA1Nzc3CsXPSYJeOHQkTDqHNw3vyYs5Gc/LQm9lJbucC3n27oXXfm6qP5LF3ZKbXvZC3K1Elsv8Hul/NHNyJCzeyzQPzC/Y7cmItr/22q08mH7mVVaIpOtI6SIvluKEutgM73FOuorIWk3by53Xfgfse9dGamyT3T5if+13q40MZ4nme2xzLZG/MdPIKJ9z+4gwzsLUk0pXUddOCTaMM12E9IQSDBYhpL+UYMM46CKkJ5RgsAgh/aUEGzbVQddzzz13YO/evU8BODDNdpcYp6Hc6y/52oFm1//fNT15CQZrMfnOd75z4JxzznkQZb/HJV87UPb1T9R+AWXYsKkOulT1pSKyR1XrcuYUQcnXX/K1A5O//hIM1mKiqi8Fyn6PS752oOzrn8a1l2DDKC8S0gNKcUIlhPSTUmwYB12E9IQSDBYhpL+UYMMWY9C1YxHaXEqUfP0lXzsw4esvwWAtEUp+j0u+dqDs65/4tZdgw6SEiySk7xx//PF6+umnNz5u//79d5fqo0IIWTq0sWGzaL8oLxLSE/gDihAyy5Rgw2Kp3AkhS56hI2qTf10QkbUisktE7q/+X+Pst73a534R2W62v1ZEvi0ie0XkT6RKoy0i/5uI/KOIfEtE/lpEVnfqKCFkJpim/VospjroEpEtIvLdysheNs22p42InCUid4jIvSJyj4h8sNoe+kPVB0RkTkS+ISJ/U61vFJG7quf/JRFpX/dmiSMiq0XkxmrwcJ+IvGGSz77NgGsMRusyALep6iYAt1Xr8xCRtQCuAPA6ABcAuMJc92cB/GsAm6p/W6rtuwCcr6r/AsA/Abi8a0fHQUn2C6ANA8q1YdO2X8D0fzQuFlMbdInIHIDPAPglAOcBeI+InDet9heBowB+T1XPA/B6AO+vrnfBP1Q94oMA7jPrHwfwSVU9B8BhAJcsSq+mw6cBfEVVfxbAqzC4DxN99otgtLYCuK5avg7A22v2eQuAXap6SFUPYzCg2iIi6wCsUtWv6qAjnx8er6p/p6rDIoJfBbCha0e7UqD9AmjDgHJt2NTtF8CZrnFzAYC9qvqAqj4P4HoMjHYvUdWHVfXr1fKTGLy06xH7QzXziMgGAL8C4JpqXQC8EcCN1S59vvZTAPwigM8BgKo+r6qPY8LPvuWg6zQR2WP+XdqgyTNU9eFq+REAZ9Tssx7AQ2Z9X7VtfbWcbk/5LQB/26BPk6Io+wXQhpVqwxbLflVt9X7QNU1H+jrj+7optr9oiMjZAF4D4C7E/lD1gU8B+H0AJ1frpwJ43MxgeH9k+8BGAD8C8Gci8ioAd2Pwi3miz76lETqgmegfEbkVwMtqPvpI0raKyFitoIh8BIPZli+O87wtKdZ+AbRh1XopNmxR7BdAR3oyBkRkJYC/AvC7qvqE/aySVXr3lonIWwE8pqp3L3ZfFonlAH4OwGdV9TUAnkIyFT+JZz8JeVFV36Sq59f8uwnAo5VMiOr/x2pOsR/AWWZ9Q7VtP+bLhsPtqM73GwDeCuBXtQRLvIShDSuORbFf1Xl7P9M1zUGXZ3x7i4gch4Gx+qKqfrnaHPlDNev8PIC3icgPMJBh3oiBj8BqERnOrvb5+e8DsE9V76rWb8TAiE3s2bcZcI3BaO0EMIxG3A7gppp9bgFwsYisqRxvLwZwS/WL+QkReX0l2/yr4fEisgWDGYa3qerTXTs5JoqzXwBtWKE2bOr2C6Aj/STYDWBTFf1xPIBtGBjtXlL9IfkcgPtU9RPmo8gfqplGVS9X1Q2qejYGz/l2Vf1VAHcAeEe1Wy+vHQBU9READ4nIz1SbLgJwLyb87BfBaF0N4M0icj+AN1XrEJHNInJN1adDAD6Gwfd/N4Arq20A8G8x8JfZC+B7+Knv1p9iIOnsEpFvisj/0bWjY6Ao+wXQhpVqwxbLflVt937QNdWM9CLyyxjo5HMArlXVq6bW+JQRkV8A8N8AfBvAsWrzH2DgE3EDgJcDeBDAu8wfod4hIhcC+A+q+lYR+WcY/GpcC+AbAH5NVZ9bxO5NDBF5NQYDiuMBPADgNzH4kTORZ798+XJdtWpV4+MOHz48cxmdF4uS7BdAGzakRBs2bfsFtLNhs2i/WAaIkB6wfPlyPfnkkxfeMeHxxx+fOaNFCOkfbWzYLNovlgEipCfwBxQhZJYpwYZx0EVID5hlHwdCCCnFhnHQRUhPKMFgEUL6Swk2jIMuQnpCCQaLENJfSrBhHHQR0hNKMFiEkP5Sgg1jRnpCCCGEkCnAmS5CekIJvxIJIf2lBBvGQRchPaCUyB9CSD8pxYZx0EVITyjBYBFC+ksJNoyDLkJ6QgkGixDSX0qwYRx0EdITSjBYhJD+UoIN46CLkJ5QgsEihPSXEmwYB12E9IBSnFAJIf2kFBvGPF2E9ISh0WryjxBClgrTtF8islZEdonI/dX/a5z9tlf73C8i283294jIt0XkWyLyFRE5LdIuB12E9AQOugghs8yU7ddlAG5T1U0AbqvW5yEiawFcAeB1AC4AcIWIrBGR5QA+DeBfquq/APAtAB+INMpBFyE9gYMuQsgsM2X7tRXAddXydQDeXrPPWwDsUtVDqnoYwC4AWwBI9e8kEREAqwD8MNIofboI6QkcRBFCZpkWNuw0Edlj1neo6o7gsWeo6sPV8iMAzqjZZz2Ah8z6PgDrVfUnIvJvAHwbwFMA7gfw/kijHHQR0g9uARDyKUg4MO6OEEJIC9rYsAOqusX7UERuBfCymo8+YldUVUUkPOITkeMA/BsArwHwAID/BOByAH+00LEcdBHSA3KGhxBCljqTsGGq+ibvMxF5VETWqerDIrIOwGM1u+0HcKFZ3wDgTgCvrs7/vepcN6DGJ6wO+nQRQgghpDR2AhhGI24HcFPNPrcAuLhynl8D4OJq234A54nIS6v93gzgvkijQj8QQgghhJSEiJwK4AYALwfwIIB3qeohEdkM4LdV9X3Vfr8F4A+qw65S1T+rtv82gA8C+El1/G+o6sEF2+WgixBCCCFk8lBeJIQQQgiZAhx0EUIIIYRMAQ66CCGEEEKmAAddhBBCCCFTgIMuQgghhJApwEEXIYQQQsgU4KCLEEIIIWQK/P9JLgLnS5dJugAAAABJRU5ErkJggg==", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "## NUMBER_OF_IMAGES = 16\n", - "\n", - "for i in range(8):\n", - " dataset.update()\n", - " image_of_particle = dataset.resolve()\n", - "\n", - " plt.figure(figsize=(10,5))\n", - " plt.subplot(1,2,1)\n", - " plt.imshow(image_of_particle[:, :, 0], cmap=\"gray\")\n", - " plt.colorbar()\n", - " \n", - " plt.subplot(1,2,2)\n", - " plt.imshow(image_of_particle[:, :, 1], cmap=\"gray\")\n", - " plt.colorbar()\n", - " plt.show()\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 3. Defining the network\n", - "\n", - "The network used is a Convolutional network, with a the pixel error as loss." - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": { - "execution": { - "iopub.execute_input": "2022-06-30T10:16:38.137547Z", - "iopub.status.busy": "2022-06-30T10:16:38.137547Z", - "iopub.status.idle": "2022-06-30T10:16:38.592050Z", - "shell.execute_reply": "2022-06-30T10:16:38.591549Z" - } - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Model: \"model\"\n", - "_________________________________________________________________\n", - " Layer (type) Output Shape Param # \n", - "=================================================================\n", - " input_1 (InputLayer) [(None, 64, 64, 2)] 0 \n", - " \n", - " conv2d (Conv2D) (None, 64, 64, 32) 608 \n", - " \n", - " activation (Activation) (None, 64, 64, 32) 0 \n", - " \n", - " conv2d_1 (Conv2D) (None, 64, 64, 32) 9248 \n", - " \n", - " activation_1 (Activation) (None, 64, 64, 32) 0 \n", - " \n", - " spatial_dropout2d (SpatialD (None, 64, 64, 32) 0 \n", - " ropout2D) \n", - " \n", - " max_pooling2d (MaxPooling2D (None, 32, 32, 32) 0 \n", - " ) \n", - " \n", - " conv2d_2 (Conv2D) (None, 32, 32, 64) 18496 \n", - " \n", - " activation_2 (Activation) (None, 32, 32, 64) 0 \n", - " \n", - " conv2d_3 (Conv2D) (None, 32, 32, 64) 36928 \n", - " \n", - " activation_3 (Activation) (None, 32, 32, 64) 0 \n", - " \n", - " spatial_dropout2d_1 (Spatia (None, 32, 32, 64) 0 \n", - " lDropout2D) \n", - " \n", - " max_pooling2d_1 (MaxPooling (None, 16, 16, 64) 0 \n", - " 2D) \n", - " \n", - " conv2d_4 (Conv2D) (None, 16, 16, 128) 73856 \n", - " \n", - " activation_4 (Activation) (None, 16, 16, 128) 0 \n", - " \n", - " conv2d_5 (Conv2D) (None, 16, 16, 128) 147584 \n", - " \n", - " activation_5 (Activation) (None, 16, 16, 128) 0 \n", - " \n", - " max_pooling2d_2 (MaxPooling (None, 8, 8, 128) 0 \n", - " 2D) \n", - " \n", - " flatten (Flatten) (None, 8192) 0 \n", - " \n", - " dense (Dense) (None, 64) 524352 \n", - " \n", - " activation_6 (Activation) (None, 64) 0 \n", - " \n", - " dense_1 (Dense) (None, 64) 4160 \n", - " \n", - " activation_7 (Activation) (None, 64) 0 \n", - " \n", - " dense_2 (Dense) (None, 2) 130 \n", - " \n", - "=================================================================\n", - "Total params: 815,362\n", - "Trainable params: 815,362\n", - "Non-trainable params: 0\n", - "_________________________________________________________________\n" - ] - } - ], - "source": [ - "import tensorflow.keras.backend as K\n", - "import tensorflow.keras.optimizers as optimizers\n", - "\n", - "model = dt.models.Convolutional(\n", - " input_shape=(IMAGE_SIZE, IMAGE_SIZE, 2),\n", - " conv_layers_dimensions=(32, 64, 128),\n", - " dense_layers_dimensions=(64, 64),\n", - " steps_per_pooling=2,\n", - " number_of_outputs=2,\n", - " dropout=(.2, .2),\n", - " loss=\"mae\",\n", - " optimizer=\"adam\",\n", - " dense_block=dt.layers.DenseBlock(activation=\"relu\")\n", - ")\n", - "\n", - "model.summary()" - ] - }, + "name": "stdout", + "output_type": "stream", + "text": [ + "Epoch 29: 100%|██████████| 16/16 [00:04<00:00, 3.41it/s, train_loss_step=0.225, val_loss_step=0.238, val_loss_epoch=0.225, train_loss_epoch=0.267]\n" + ] + } + ], + "source": [ + "train_dataset = dt.pytorch.Dataset(\n", + " particle_sizing_pipeline,\n", + " length=TRAIN_DATASET_SIZE,\n", + " replace=True,\n", + ")\n", + "\n", + "validation_records = [\n", + " resolve_image_label_metadata() for _ in range(VALIDATION_SET_SIZE)\n", + "]\n", + "validation_images = torch.stack(\n", + " [image_to_tensor(image) for image, _label, _metadata in validation_records]\n", + ")\n", + "validation_labels = torch.stack(\n", + " [torch.from_numpy(label) for _image, label, _metadata in validation_records]\n", + ")\n", + "validation_metadata = [metadata for _image, _label, metadata in validation_records]\n", + "validation_dataset = TensorDataset(validation_images, validation_labels)\n", + "\n", + "train_dataloader = DataLoader(\n", + " train_dataset,\n", + " batch_size=BATCH_SIZE,\n", + " shuffle=True,\n", + ")\n", + "\n", + "validation_dataloader = DataLoader(\n", + " validation_dataset,\n", + " batch_size=BATCH_SIZE,\n", + " shuffle=False,\n", + ")\n", + "\n", + "early_stopping = EarlyStopping(\n", + " monitor=\"val_loss\",\n", + " mode=\"min\",\n", + " patience=EARLY_STOPPING_PATIENCE,\n", + " min_delta=1e-4,\n", + ")\n", + "\n", + "trainer = dl.Trainer(\n", + " max_epochs=EPOCHS,\n", + " accelerator=\"auto\",\n", + " logger=False,\n", + " callbacks=[early_stopping],\n", + " enable_checkpointing=False,\n", + " enable_progress_bar=True,\n", + ")\n", + "\n", + "trainer.fit(\n", + " regressor,\n", + " train_dataloader,\n", + " validation_dataloader,\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 38, + "id": "dtex203-17", + "metadata": {}, + "outputs": [ { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 4. Training the network" + "data": { + "image/png": "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", + "text/plain": [ + "
" ] - }, + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig, axes = trainer.history.plot()" + ] + }, + { + "cell_type": "markdown", + "id": "dtex203-17a", + "metadata": {}, + "source": [ + "The training dataset regenerates samples because the goal is to learn from a distribution of particle positions, optical aberrations, and pre-optics noise, not to memorize a finite rendered set. This is useful for synthetic training data. For a fully deterministic comparison, set `replace=False` or pre-generate a fixed training set. Validation remains fixed within a run, so its curve is less noisy. Validation loss can also be lower because dropout is disabled during validation.\n" + ] + }, + { + "cell_type": "markdown", + "id": "dtex203-18", + "metadata": {}, + "source": [ + "## 6. Evaluating the network\n", + "\n", + "The validation set is simulated independently from the training batches. We first report direct errors in physical units, then compare true and predicted values with parity plots and residual histograms." + ] + }, + { + "cell_type": "code", + "execution_count": 39, + "id": "dtex203-19", + "metadata": {}, + "outputs": [ { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "We use the `ContinuousGenerator` to generate the images. It creates a new thread and generates images while the model is training. \n", - "\n", - "Set TRAIN_MODEL to True to train the model, otherwise a pretrained model is downloaded." - ] - }, + "name": "stdout", + "output_type": "stream", + "text": [ + "Radius MAE: 15.4 nm\n", + "Refractive-index MAE: 0.030\n", + "Radius correlation: 0.987\n", + "Refractive-index correlation: 0.919\n" + ] + } + ], + "source": [ + "regressor.eval()\n", + "with torch.no_grad():\n", + " validation_prediction_array = (\n", + " regressor(validation_images.to(regressor.device)).cpu().numpy()\n", + " )\n", + "\n", + "validation_label_array = validation_labels.numpy()\n", + "validation_errors = validation_prediction_array - validation_label_array\n", + "predicted_radius_nm, predicted_refractive_index = decode_label(validation_prediction_array)\n", + "true_radius_nm, true_refractive_index = decode_label(validation_label_array)\n", + "\n", + "radius_error_nm = predicted_radius_nm - true_radius_nm\n", + "ri_error = predicted_refractive_index - true_refractive_index\n", + "\n", + "radius_mae_nm = np.mean(np.abs(radius_error_nm))\n", + "ri_mae = np.mean(np.abs(ri_error))\n", + "radius_corr = np.corrcoef(predicted_radius_nm, true_radius_nm)[0, 1]\n", + "ri_corr = np.corrcoef(predicted_refractive_index, true_refractive_index)[0, 1]\n", + "\n", + "print(f\"Radius MAE: {radius_mae_nm:.1f} nm\")\n", + "print(f\"Refractive-index MAE: {ri_mae:.3f}\")\n", + "print(f\"Radius correlation: {radius_corr:.3f}\")\n", + "print(f\"Refractive-index correlation: {ri_corr:.3f}\")" + ] + }, + { + "cell_type": "code", + "execution_count": 40, + "id": "dtex203-20", + "metadata": {}, + "outputs": [ { - "cell_type": "code", - "execution_count": 10, - "metadata": { - "execution": { - "iopub.execute_input": "2022-06-30T10:16:38.605548Z", - "iopub.status.busy": "2022-06-30T10:16:38.605047Z", - "iopub.status.idle": "2022-06-30T10:20:40.661050Z", - "shell.execute_reply": "2022-06-30T10:20:40.660553Z" - }, - "scrolled": false - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Generating 2009 / 2000 samples before starting training\n", - "Epoch 1/100\n", - "31/31 [==============================] - 4s 18ms/step - loss: 0.8815 - val_loss: 0.5950\n", - "Epoch 2/100\n", - "31/31 [==============================] - 0s 11ms/step - loss: 0.5773 - val_loss: 0.5481\n", - "Epoch 3/100\n", - "31/31 [==============================] - 0s 11ms/step - loss: 0.5761 - val_loss: 0.5358\n", - "Epoch 4/100\n", - "31/31 [==============================] - 0s 11ms/step - loss: 0.5635 - val_loss: 0.5392\n", - "Epoch 5/100\n", - "31/31 [==============================] - 0s 11ms/step - loss: 0.5547 - val_loss: 0.5305\n", - "Epoch 6/100\n", - "31/31 [==============================] - 0s 11ms/step - loss: 0.5409 - val_loss: 0.5485\n", - "Epoch 7/100\n", - "31/31 [==============================] - 0s 11ms/step - loss: 0.5339 - val_loss: 0.4989\n", - "Epoch 8/100\n", - "31/31 [==============================] - 0s 11ms/step - loss: 0.5282 - val_loss: 0.4923\n", - "Epoch 9/100\n", - "31/31 [==============================] - 0s 11ms/step - loss: 0.5099 - val_loss: 0.5271\n", - "Epoch 10/100\n", - "31/31 [==============================] - 0s 11ms/step - loss: 0.5131 - val_loss: 0.5194\n", - "Epoch 11/100\n", - "31/31 [==============================] - 0s 11ms/step - loss: 0.5215 - val_loss: 0.5228\n", - "Epoch 12/100\n", - "31/31 [==============================] - 0s 11ms/step - loss: 0.5130 - val_loss: 0.4946\n", - "Epoch 13/100\n", - "31/31 [==============================] - 0s 11ms/step - loss: 0.5097 - val_loss: 0.5089\n", - "Epoch 14/100\n", - "31/31 [==============================] - 0s 11ms/step - loss: 0.5029 - val_loss: 0.5175\n", - "Epoch 15/100\n", - "31/31 [==============================] - 0s 11ms/step - loss: 0.4996 - val_loss: 0.5064\n", - "Epoch 16/100\n", - "31/31 [==============================] - 0s 11ms/step - loss: 0.5138 - val_loss: 0.4990\n", - "Epoch 17/100\n", - "31/31 [==============================] - 0s 11ms/step - loss: 0.4995 - val_loss: 0.4963\n", - "Epoch 18/100\n", - "31/31 [==============================] - 0s 11ms/step - loss: 0.4959 - val_loss: 0.4907\n", - "Epoch 19/100\n", - "31/31 [==============================] - 0s 11ms/step - loss: 0.4915 - val_loss: 0.4914\n", - "Epoch 20/100\n", - "31/31 [==============================] - 0s 11ms/step - loss: 0.4739 - val_loss: 0.4631\n", - "Epoch 21/100\n", - "31/31 [==============================] - 0s 11ms/step - loss: 0.4825 - val_loss: 0.4865\n", - "Epoch 22/100\n", - "31/31 [==============================] - 0s 11ms/step - loss: 0.4673 - val_loss: 0.4604\n", - "Epoch 23/100\n", - "31/31 [==============================] - 0s 11ms/step - loss: 0.4668 - val_loss: 0.4692\n", - "Epoch 24/100\n", - "31/31 [==============================] - 0s 11ms/step - loss: 0.4539 - val_loss: 0.4742\n", - "Epoch 25/100\n", - "31/31 [==============================] - 0s 11ms/step - loss: 0.4543 - val_loss: 0.4518\n", - "Epoch 26/100\n", - "31/31 [==============================] - 0s 11ms/step - loss: 0.4346 - val_loss: 0.5006\n", - "Epoch 27/100\n", - "31/31 [==============================] - 0s 11ms/step - loss: 0.4386 - val_loss: 0.4675\n", - "Epoch 28/100\n", - "31/31 [==============================] - 0s 11ms/step - loss: 0.4193 - val_loss: 0.4110\n", - "Epoch 29/100\n", - "31/31 [==============================] - 0s 11ms/step - loss: 0.3904 - val_loss: 0.4073\n", - "Epoch 30/100\n", - "31/31 [==============================] - 0s 11ms/step - loss: 0.3771 - val_loss: 0.4544\n", - "Epoch 31/100\n", - "31/31 [==============================] - 0s 11ms/step - loss: 0.4221 - val_loss: 0.3631\n", - "Epoch 32/100\n", - "31/31 [==============================] - 0s 11ms/step - loss: 0.3835 - val_loss: 0.4450\n", - "Epoch 33/100\n", - "31/31 [==============================] - 0s 11ms/step - loss: 0.3701 - val_loss: 0.3619\n", - "Epoch 34/100\n", - "31/31 [==============================] - 0s 11ms/step - loss: 0.3512 - val_loss: 0.5325\n", - "Epoch 35/100\n", - "31/31 [==============================] - 0s 11ms/step - loss: 0.3333 - val_loss: 0.3666\n", - "Epoch 36/100\n", - "31/31 [==============================] - 0s 11ms/step - loss: 0.3341 - val_loss: 0.3528\n", - "Epoch 37/100\n", - "31/31 [==============================] - 0s 10ms/step - loss: 0.3603 - val_loss: 0.3043\n", - "Epoch 38/100\n", - "31/31 [==============================] - 1s 12ms/step - loss: 0.3415 - val_loss: 0.3639\n", - "Epoch 39/100\n", - "31/31 [==============================] - 1s 14ms/step - loss: 0.3067 - val_loss: 0.3534\n", - "Epoch 40/100\n", - "31/31 [==============================] - 1s 13ms/step - loss: 0.3201 - val_loss: 0.3305\n", - "Epoch 41/100\n", - "31/31 [==============================] - 1s 13ms/step - loss: 0.3122 - val_loss: 0.2938\n", - "Epoch 42/100\n", - "31/31 [==============================] - 1s 14ms/step - loss: 0.3042 - val_loss: 0.4223\n", - "Epoch 43/100\n", - "31/31 [==============================] - 1s 16ms/step - loss: 0.3006 - val_loss: 0.3197\n", - "Epoch 44/100\n", - "31/31 [==============================] - 0s 10ms/step - loss: 0.2987 - val_loss: 0.3670\n", - "Epoch 45/100\n", - "31/31 [==============================] - 0s 10ms/step - loss: 0.2902 - val_loss: 0.2699\n", - "Epoch 46/100\n", - "31/31 [==============================] - 0s 11ms/step - loss: 0.2986 - val_loss: 0.3271\n", - "Epoch 47/100\n", - "31/31 [==============================] - 0s 11ms/step - loss: 0.2984 - val_loss: 0.3315\n", - "Epoch 48/100\n", - "31/31 [==============================] - 0s 11ms/step - loss: 0.2937 - val_loss: 0.3079\n", - "Epoch 49/100\n", - "31/31 [==============================] - 0s 11ms/step - loss: 0.2728 - val_loss: 0.4172\n", - "Epoch 50/100\n", - "31/31 [==============================] - 0s 10ms/step - loss: 0.2756 - val_loss: 0.2905\n", - "Epoch 51/100\n", - "31/31 [==============================] - 0s 11ms/step - loss: 0.2711 - val_loss: 0.3424\n", - "Epoch 52/100\n", - "31/31 [==============================] - 0s 11ms/step - loss: 0.2782 - val_loss: 0.2830\n", - "Epoch 53/100\n", - "31/31 [==============================] - 0s 11ms/step - loss: 0.2633 - val_loss: 0.2602\n", - "Epoch 54/100\n", - "31/31 [==============================] - 0s 11ms/step - loss: 0.2495 - val_loss: 0.2567\n", - "Epoch 55/100\n", - "31/31 [==============================] - 0s 11ms/step - loss: 0.2516 - val_loss: 0.2790\n", - "Epoch 56/100\n", - "31/31 [==============================] - 0s 11ms/step - loss: 0.2542 - val_loss: 0.3367\n", - "Epoch 57/100\n", - "31/31 [==============================] - 0s 11ms/step - loss: 0.2849 - val_loss: 0.3025\n", - "Epoch 58/100\n", - "31/31 [==============================] - 0s 11ms/step - loss: 0.2731 - val_loss: 0.3701\n", - "Epoch 59/100\n", - "31/31 [==============================] - 0s 11ms/step - loss: 0.2503 - val_loss: 0.2528\n", - "Epoch 60/100\n", - "31/31 [==============================] - 0s 11ms/step - loss: 0.2465 - val_loss: 0.2510\n", - "Epoch 61/100\n", - "31/31 [==============================] - 0s 11ms/step - loss: 0.2415 - val_loss: 0.3628\n", - "Epoch 62/100\n", - "31/31 [==============================] - 0s 11ms/step - loss: 0.2479 - val_loss: 0.4407\n", - "Epoch 63/100\n", - "31/31 [==============================] - 0s 10ms/step - loss: 0.2556 - val_loss: 0.3024\n", - "Epoch 64/100\n", - "31/31 [==============================] - 0s 11ms/step - loss: 0.2384 - val_loss: 0.3015\n", - "Epoch 65/100\n", - "31/31 [==============================] - 0s 11ms/step - loss: 0.2519 - val_loss: 0.2719\n", - "Epoch 66/100\n", - "31/31 [==============================] - 0s 11ms/step - loss: 0.2301 - val_loss: 0.2762\n", - "Epoch 67/100\n", - "31/31 [==============================] - 0s 12ms/step - loss: 0.2325 - val_loss: 0.2538\n", - "Epoch 68/100\n", - "31/31 [==============================] - 0s 11ms/step - loss: 0.2289 - val_loss: 0.2546\n", - "Epoch 69/100\n", - "31/31 [==============================] - 0s 11ms/step - loss: 0.2397 - val_loss: 0.3348\n", - "Epoch 70/100\n", - "31/31 [==============================] - 0s 11ms/step - loss: 0.2296 - val_loss: 0.2834\n", - "Epoch 71/100\n", - "31/31 [==============================] - 0s 11ms/step - loss: 0.2294 - val_loss: 0.2862\n", - "Epoch 72/100\n", - "31/31 [==============================] - 1s 18ms/step - loss: 0.2300 - val_loss: 0.3016\n", - "Epoch 73/100\n", - "31/31 [==============================] - 1s 13ms/step - loss: 0.2278 - val_loss: 0.2465\n", - "Epoch 74/100\n", - "31/31 [==============================] - 1s 17ms/step - loss: 0.2184 - val_loss: 0.2455\n", - "Epoch 75/100\n", - "31/31 [==============================] - 1s 17ms/step - loss: 0.2287 - val_loss: 0.2663\n", - "Epoch 76/100\n", - "31/31 [==============================] - 1s 15ms/step - loss: 0.2384 - val_loss: 0.2666\n", - "Epoch 77/100\n", - "31/31 [==============================] - 1s 17ms/step - loss: 0.2348 - val_loss: 0.2387\n", - "Epoch 78/100\n", - "31/31 [==============================] - 0s 10ms/step - loss: 0.2226 - val_loss: 0.2759\n", - "Epoch 79/100\n", - "31/31 [==============================] - 0s 11ms/step - loss: 0.2258 - val_loss: 0.2828\n", - "Epoch 80/100\n", - "31/31 [==============================] - 0s 11ms/step - loss: 0.2256 - val_loss: 0.3349\n", - "Epoch 81/100\n", - "31/31 [==============================] - 0s 11ms/step - loss: 0.2248 - val_loss: 0.2931\n", - "Epoch 82/100\n", - "31/31 [==============================] - 0s 11ms/step - loss: 0.2210 - val_loss: 0.2789\n", - "Epoch 83/100\n", - "31/31 [==============================] - 0s 11ms/step - loss: 0.2402 - val_loss: 0.2776\n", - "Epoch 84/100\n", - "31/31 [==============================] - 0s 10ms/step - loss: 0.2220 - val_loss: 0.2546\n", - "Epoch 85/100\n", - "31/31 [==============================] - 0s 10ms/step - loss: 0.2228 - val_loss: 0.2482\n", - "Epoch 86/100\n", - "31/31 [==============================] - 0s 11ms/step - loss: 0.2112 - val_loss: 0.2354\n", - "Epoch 87/100\n", - "31/31 [==============================] - 0s 11ms/step - loss: 0.2068 - val_loss: 0.2480\n", - "Epoch 88/100\n", - "31/31 [==============================] - 0s 11ms/step - loss: 0.2376 - val_loss: 0.2814\n", - "Epoch 89/100\n", - "31/31 [==============================] - 0s 10ms/step - loss: 0.2102 - val_loss: 0.2668\n", - "Epoch 90/100\n", - "31/31 [==============================] - 0s 10ms/step - loss: 0.2125 - val_loss: 0.2338\n", - "Epoch 91/100\n", - "31/31 [==============================] - 0s 11ms/step - loss: 0.2132 - val_loss: 0.2378\n", - "Epoch 92/100\n", - "31/31 [==============================] - 0s 11ms/step - loss: 0.2103 - val_loss: 0.2466\n", - "Epoch 93/100\n", - "31/31 [==============================] - 0s 10ms/step - loss: 0.2177 - val_loss: 0.3040\n", - "Epoch 94/100\n", - "31/31 [==============================] - 0s 10ms/step - loss: 0.2221 - val_loss: 0.2353\n", - "Epoch 95/100\n", - "31/31 [==============================] - 0s 10ms/step - loss: 0.2076 - val_loss: 0.2572\n", - "Epoch 96/100\n", - "31/31 [==============================] - 0s 11ms/step - loss: 0.2213 - val_loss: 0.2525\n", - "Epoch 97/100\n", - "31/31 [==============================] - 0s 10ms/step - loss: 0.2065 - val_loss: 0.2394\n", - "Epoch 98/100\n", - "31/31 [==============================] - 0s 10ms/step - loss: 0.1994 - val_loss: 0.2730\n", - "Epoch 99/100\n", - "31/31 [==============================] - 0s 10ms/step - loss: 0.1980 - val_loss: 0.2792\n", - "Epoch 100/100\n", - "31/31 [==============================] - 0s 11ms/step - loss: 0.2008 - val_loss: 0.2288\n" - ] - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "TRAIN_MODEL = True\n", - "\n", - "validation_set_size = 256\n", - "validation_set = [dataset.update().resolve() for _ in range(validation_set_size)]\n", - "validation_labels = [get_label(image) for image in validation_set]\n", - "\n", - "if TRAIN_MODEL:\n", - " generator = dt.generators.ContinuousGenerator(\n", - " dataset & (dataset >> get_label),\n", - " min_data_size=int(2e3),\n", - " max_data_size=int(2e4),\n", - " batch_size=64,\n", - " max_epochs_per_sample=33\n", - " )\n", - "\n", - " with generator:\n", - " h = model.fit(\n", - " generator,\n", - " validation_data=(\n", - " np.array(validation_set), \n", - " np.array(validation_labels)\n", - " ),\n", - " epochs=100,\n", - " )\n", - " \n", - " plt.plot(h.history[\"val_loss\"])\n", - " \n", - "else:\n", - " model_path = datasets.load_model(\"ParticleSizing\")\n", - " model.load_weights(model_path)" + "data": { + "image/png": "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", + "text/plain": [ + "
" ] + }, + "metadata": {}, + "output_type": "display_data" }, { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 5. Evaluating the network\n", - "\n", - "We show the the error as a function of some properties." + "data": { + "image/png": "iVBORw0KGgoAAAANSUhEUgAABEEAAAGGCAYAAACUtJ9/AAAAOnRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjExLjAsIGh0dHBzOi8vbWF0cGxvdGxpYi5vcmcvlcelbwAAAAlwSFlzAAAPYQAAD2EBqD+naQAAZ8BJREFUeJzt3Qm8jPX///+XXcgWIfsue8kakZIiiXZLKdoL0ULbhyiJ+qgorWQphSRKiySlFFIhyydkX1LZd+Z/e76//2t+M8ecY84x55xZHvfbbZi55rquua5r5sz7Na/3lsXn8/kMAAAAAAAgzmXN7AMAAAAAAADICCRBAAAAAABAQiAJAgAAAAAAEgJJEAAAAAAAkBBIggAAAAAAgIRAEgQAAAAAACQEkiAAAAAAACAhkAQBAAAAAAAJgSQIAAAAAABICCRBAIQld+7c1rt3b//jnTt3WpYsWWzEiBFxeQV1Xjo/neepTJkyxa27aNGiqDkmAEBimT59utWuXduV19FUVnTr1s1KlSoVV6/9+OOPu2t87NgxizefffaZO7fvvvvulOsuW7bMrTthwoSoOSYgHCRBgBh14403ugLBu+XKlcsqVKjgEhW7du3K7MMDAAAh1K1bN6j8PuOMM6xGjRo2ePBgO3LkSJqu2datW+2mm26ytm3b2u7du83n81mRIkUyNCYpV65chr0eAJyO7Ke1NYBMd/ToUcuePbvt2bPHZsyYYbfddpv99NNPNn/+fBdcpRcFVwqy4pWSSYEtXwAAiJSKFSvaH3/84e6rxcbbb79tjzzyiK1Zs8bGjBmT6v2p3D948KBdf/31rlIkmowdOzYhXztWXX755XEd3wFCSxAgTuTPn986d+5st9xyi/3www/p3jUDAABEplLh4YcftmbNmtm4ceNcS47U8rq+qFUJACBlJEGAOFO5cmX3/6ZNm4KWq7WI1/Q2Z86cruvMQw89ZPv37w9ab/v27dalSxcrWLCgu918882ulUlSocYEmTt3rlumvptJ6fUffPDBoGUvvvii1apVy/Lly2fnnHOOXX311bZkyZIUz081Z3qNN99809577z3XhDhHjhw2c+ZM9/y6devcMRcvXtydp2rbBg0aZMePH/fvY9u2bdajRw8rXbq0CxirVatm/fr1C+pGlNz4G1999ZU1aNDA9bkuX768jR49OuRxav+hmiJPmjTJ7feXX345aZl30/Vo1KiRvf/++ylei3DPBQAQG+X3iRMnbMuWLUHLf/zxR7vyyiutcOHCruzRuB/vvPOO/3l976sckHPPPdeVI9dee617rHJVz6u7jJYVKFDAWrRo4Z5TWeGVO1mzZrVChQrZZZdd5lqSJqVjaN++vSvX8ubN68qoDz/80D3nlVfr168PKssOHToUclwOxR4qt3VMST311FPuWLSvcM8/tWOCeNdE5ft1111nZ555pjuve+65xw4fPnzSPt566y23vl67Tp06IWOccI/13XffddfmhRdeCNpOLYG0/NVXX03xfLxYSvFWw4YN3WsMHz7cPffPP/9Yr169XLckxT8lS5a0nj172t69e/3bHzhwwF1/xUaKGRQL3n777UExY3LjbyxdutRatWplefLkcTHWE0884T6vSel4QsVPinu0XDFP0mWBXcN0zRSDnao1SjjnAiSHJAgQZ1atWuX+L1OmTNByDd6lAkW3v//+20aNGmUTJ060e++917+OApZLLrnEvv/+e9e1ZsOGDXbNNdfYXXfdFfHjfO2111zhpcHFFAipcFUQ5xXmp/LJJ5/Yt99+a7NmzbKFCxfaWWedZatXr7YLLrjANm7c6ApxBQQ6T926d+/u31ZBz+LFi90+/v33X5dAUQCk65ESvZ6aiVapUsVWrlzpWtyo6fKptgunL7X33iig0HlcccUVrn/3F198keK2aT0XAED0ld/ZsmVzlQIelWVqIaLvdZV1qqhQV80777zTXwmh8uiNN95w91esWOHKEg3YHVj+a32V96oo8MrDZ5991l/2aCwS7b9EiRKunFu7dq1/e5UrTZs2dT+4v/nmG3cML730kitn1GplwYIFdsMNN1jZsmX9+9NN64eisl7HpFYvgbSNuq9ceumlbl/hnn9a6PV1Pe677z6XdFLyQZUrQ4YMCVpPy3W8KqcVW0ybNs0lRQIrMlLzXnXq1Mnuvvtu1/XJSzJoXzoWtebVc6ei91jXf/z48e4zU716dVf+N27c2GbPnu2SLop/dKyquFE84VUEKUmi981bR+9nkyZN7JVXXknxNfW50bnpc6KY4/fff7eiRYu6SqbTHR8n8DOjBMb999/vEnSK3VKS1nMBHB+AmHTDDTcoRe47evSoe7x7927fuHHjfDly5PBdcsklYe1j5MiRvqxZs/oOHDjgHr/22mtun19//XXQeqNHj3bLe/Xq5V/2119/uWX//e9//cu0nZbNmjXrpNfKli2br2/fvv7HN954o+/cc89N9Xn/73//c69Rq1atk55r166d7+yzz/bt2rUraPmECRPcNkuXLvUdOXLElyVLFt/TTz+d4uvovLSNztPTrFkzX9myZf3X3NO0aVO37sKFC/3Lunfv7jvrrLNO2u97773n1l2yZMkpz7VRo0a+a6+9NtljCvdcAADRo06dOr6KFSv6H+s7/ZlnnnHf7/fee69/+fHjx12Zo7LgxIkTQft48MEHffnz5/ft37/fPX7jjTfc9itWrAhar3379m75559/HtaxHTt2zJc3b17f4MGD/Y9LlSrlq1ev3knHkDQm0bGGcsstt/hKlix5UrlZpUqVoGWzZ892xzpp0qRUn39yQr22d03mzZsXtPy6667zlShRwv/48OHDrhxv27Zt0HqKmRRrBMZgqTlW7bd+/fq+c845x7dy5UpfhQoVfNWrV/ft27fPdyqKpQoWLHjSug899JAve/bsvtWrVwctX7RokTvOyZMnu8eVKlXyde3aNcXXUAynbb799lv/sttvv913xhln+Hbs2BG0bo8ePdy648eP9y8bNmzYSfGTKO7RcsVBp9KtWzdfzZo1UzymcM4FSA4tQYAYpyalakKoJq7qBtK6dWvXiiMptShQM1e1mFBTU22jGhC1PPBqfFRjoGahXlPZwKajkaYmparNUC2JahUCu6uE46qrrgp6rNqJzz//3J2jrkUg1SqJagl0vVRr8vLLL9vrr79umzdvDuv11EpGLWTatGnjmqNG8vpocNtnnnnGNQFVM1OvWahq17yB80JJ67kAADKXWhF63/WqUX/00UddDbhq+D1qIaluIerGknSgc5Vr6qp6qi6kohYZKhuTUu25ymB1J9BgqnoNlW/qJuuVPb/99purnVfLxEgOtq7WKGr1GNjlQl1C1I3EK1PDPX91Sw3sUqHbqbqEKtZRy4ZANWvWdC1TNcCs/Prrr67lbNJ4Q10vkl7P1LxX6qoyefJkF1eoJcSOHTts6tSprptRONRiN+m6ivu0L69LtKdevXqum5PiHy/20ms999xz9r///c/CpfhQ3Z70WY10fKgWOOrao/fEe//UIiil+Od0zgUQkiBAjNMPaDUhVCGqIErNVhVIBJo3b55rDql+ovphrQLea3bq7UNU2BcrVuyk1zj77LNd4uR0JO3b2bdvXxswYIBNnz7ddWFRckbBw88//xzW/tTXNZCagioRoqaRCuLUpFg3Hbf6rnrnJx9//LELfvr06eP6CitoUNPLlAajU0ClRE2o6xNqWXJC9XFV4KsmpWoeqyDK67qkwMl7b5KTlnMBAGQuJR68LpDqeqqxuPRjPrALpMZ8Eg2amrRcU5eVwHItJYHdawJpOl39iFSXD3Xd0LF4U+t6ZY9ii1Bl7unSLDYa0F1dS7wyVmOM6Dp4s9tE6vxDUbefpHQ84pWf3r7DKfdTe6zq7qMyXokQb4yScIV6L/T6qlDSa3uv71V4KT7yXltdkbt27eoSB+raq8+GuuucahyN5OLD041/1E3ojjvucF17VTHmxbSqpDtV/JPWcwGEJAgQJ5Sdf/rpp61jx47uB7E3NohMmDDB1VwowNKPZC/AUB/PQEpEeAFPIC0LNfhVUl4LjMBBuLzCOen2asXwn//8xx2Dbv/9739t2bJldtFFF4VVgGn7pK+tgl8FoJIISljo5gV1uj355JNuXQ2e9cEHH7jAQNMKqoZLr6/+uMnRILEKKhQoJhVqmY5n3759Jy0P1VpD/XpVkOv19T7qdUK9P6Gk5VwAANFBP1I1sLUqJTSoqWZ481oxeINra4yD5Mq1pK0UwikvRa0wVCnSv39/16pBZZyOReVW4ICWXs1/pFsaqtWjxtlQiwjFDBowVAmBwPG7wj1/jVsWOK6EbjqflITTqkUxkYRT7qf2vVJcprJbLSBUeeMN7h6OUO+nXr958+butb3XD3xtXV/vnBQLKq5TzKUKKY0fc/HFF6c4EKm2S038EyoWDPUZ0rgwGm9Gg72qIsdraRtO/JPWcwGEJAgQZ4YNG+a+/BXYBFLzy8BCXwWkVyh6WrZs6Zpses0mPWqtEQ7NlqKaBxVGgU5VuKuFyq233uoGRVUz3HBbgyRt7qtRyz/99NOQyYfkAon69eu70eg7dOjgWsyktH8NOqaBWJN23Ql1fVTLp1HmkzbRTHot9F7pffESUx5v0NVwpeZcAADRRclvlYH6QaeabVH3Bv0w1I/l9JK07Ek6WKm6HOgYNBtbSj8s1T0j1MwqKdGAoyrzNbOMWoSoVai6hXoy4vxTonNX95ykXYyVrEk6aHlqjnX58uWuwkYDz2smHnVvUXfmP//8M83H2q5dOzczTeCsOilRrKbZ9ZQ4UGtUdT0JNVtPYHyopFnSGV+Si38k3Fgw6WdQx6EBXsOV2nMB3OeGywDEF7UMuO2229yo4GoZIKp9UEsBTWemZp4qINRiQAV8IBXCqolSTYwKZmXxVfgrKZK0kApFNS/q0qKaEM2kou3VvFWjpHutGzyq7dJYFmqxosBJBbdqwjQ9rAKhtFALCE2ZpunplERQMkQFoUZs1zVQzZdeR12DNJuKnlMwoz7JShqo9iAlgwcPdq1UlLBR82XVgKjriVdbFEg1XOrfqv7WGnleN9V0eF1zPEqA6HjVGuTrr792AeGcOXPsgQcecKOcp+R0zgUAEF2UyFdtvqaPVwtKlZsa70nf62otqB/P6s6qH8uaZlTrplWlSpXcmFJKvGg8C8UGqhjRj9rAriI6BnWX0fgYKtc0K4jKKZXrKu+9riMaT0MJHP1QDqflqChxr6SHkveq/AhsBeK9dnqdfzhUeaRjUxmrLqtKAKiFguIXHXtajlVxkZIfSpio67K203VXyxh1CVG33rTQTHuaFVBdnBTzqDWRurAoFtM0waogEh2HElqKHxR76b3Xe67uOEnjk0CqWFNli45RsxEpphw5cqT7Pym9hlodK+ZU3KXjULcXfW6SUmym2EfH5FWC6XPljeWWkrSeCyAkQYA4pIJHLRc0RojoR7b6TqrZqQoGFTqqNVBBHEhdZvQDXIW7BgBVIa3COzXTjWlKM/0A1/YqkDVYaahp7DQeiIIJ9YVV8kQ/+JXNV4GdXP/lU6lataobeEz/K1hTDY7ORQW1al1UKKsfrhITClY0YJgSGKqNUuJIzVNPVeAqGFIQqP6nasaqaxSq64leW4koNf9UCxltq5qiUIOIKcBUNyYds96foUOHuto4DWaWktM5FwBA9FG3ViXzlXQXJbqVWNCPPNXGq7xUywHVqoc7pXwoKm81ppRq7TWulMoptXTUj8qkY4AphlByXRULF154oRsHomfPnm66V6/rg8pY/UBW2a8f9krwKzF/Kkp8aOpZxR+qnEkqvc4/XJq6VvGTKio0FofiJ1UYqTxPy7GqjNb5aiwWbwwSdTlSaxhNlasyPS0Uc6gliN4rTR2r90hJLnUD1jEowSY6DiVENAC+jk/no/hLA5+mNPabKtj0GdA65513nks0KL5R8iUpvf+qANNnQ0ku3fRZUEuNpBSnqoJIY6noOuh6KwYKZ4yUtJ4LIFk0RQyXAgAAAAAAxDvSZAAAAAAAICGQBAEAAAAAAAmBJAgAAAAAAEgIJEEAAAAAAEBCIAkCAAAAAAASAkkQAAAAAACQELJn9gFEqxMnTtiWLVvszDPPdHOdAwCAyPD5fLZ3714755xzLGvWxKqPIb4AACBz4wuSIMlQAqR06dLp9PYAAICNGzdaqVKlEupCEF8AAJC58QVJkGSoBYh3AfPnz58+7w4A55dffrHmzZvbN998Y3Xr1uWqAHFuz549rqLBK2sTCfEFEJ+IZYDYiS9IgiTD6wKjBAhJECB95cuXz/8/f29A4kjE7qbEF0B8IpYBYie+SKyOuAAAAAAAIGGRBAEAAAAAAAmBJAgAAAAAAEgIJEEAAAAAAEBCIAkCAAAAAAASAkkQAAAAAACQEEiCAAAAAACAhEASBAAAAAAAJASSIAAAAAAAICGQBAEAAAAAAAmBJAgAAAAAAEgIJEEAAAAAAEBCyJ7ZBwAASH8th8+NyH7mPNgiIvsBAACp125au4hcthkdZnD5kbBoCQIAAAAAABICSRAAAAAAAJAQMr07zIIFC2z06NG2cuVKe+WVV+z8888Per5ly5Z24MCBk7br0KGDPfLIIyH3+dxzz9mHH34YtKxixYo2ceLECB89AAAAAACIFZmaBHnsscds9uzZ1rFjR3vnnXdsz549J60zdOhQO378uP/x77//bt27d7cHH3ww2f2uXbvW8uTJY88884x/mR4DAAAAAIDElalJkIcfftiefvpp27Rpk/Xr1y/kOvXr1w96/P7771vRokWtffv2Ke67cOHC1qhRo4geLwAAAAAAiF2ZmgQpUKBAqtY/cuSITZgwwW699VbLkSNHiusuXLjQdaXRazRr1szuu+8+y5kz52keMQAAAAAAiFWZPiZIakyfPt127txpPXr0SHE9dX3p0qWLNW/e3DZv3myDBw+2qVOn2rx58yxbtmwhtzl8+LC7eUJ1zQEAAAAAALErppIgb731lktsVKlSJcX1hgwZYrly5fI/VkuQatWq2eTJk+3GG29MdpuBAwdG/JgBAAAAAEB0iJkpcjdu3Ghffvml3X777adcNzABIpUqVbJy5crZr7/+muw2/fv3t927d/tvej0AAAAAABA/YqYlyNtvv+3G97jmmmtSve2xY8dcN5q8efOmmDhJmjwBAAAAAADxIyZagvh8PhszZox17drVcufOHbIrS+fOnf2Dp2paXf3vJUAeeeQRO3DgQJoSKAAAAAAAID5kakuQTz75xAYNGuRPWNxzzz2WP39+N/Bp4OCns2fPtvXr1yfbFWbNmjX+ri6aNWbfvn12zjnnWIkSJWzr1q1WsGBBN6jqueeem0FnBgAAAAAAok2mJkEaNGhgI0aMOGl5qVKlgh4reaEpb2vWrBlyP48++qhLfEiWLFlcYuWJJ56w//3vf1aoUCGXDNFyAAAAAACQuDI1CVK0aFF3OxUlRZImRgJVqFDhpGU5c+a0GjVqnPYxAgAAAACA+BATY4IAAAAAAACcLpIgAAAAAAAgIZAEAQAAAAAACYEkCAAAAAAASAgkQQAAAAAAQEIgCQIAAAAAABJCpk6RCwAAEC22b99u8+bNs3379lmNGjWsQYMGJ61z8OBB++yzz9y6tWrVsgsvvDBTjhUAAKQNLUEAAEDCGzZsmDVt2tQ++ugjmzt3rrVp08bdDh8+7L8227Zts7p169qTTz5p8+fPt/bt21u3bt0S/toBABBLaAkCAAASXv369e2BBx6w7Nn/LzRat26dVaxY0WbOnGnXXHONW9avXz8744wzbMGCBZY7d2777bff7LzzzrMOHTq4hAgAAIh+tAQBAAAJr0WLFv4EiBQsWNCyZv1/YdKJEyds6tSpruWHEiBSu3Zt1x3mgw8+SPjrBwBArKAlCAAAgJmtX7/epk2bZnv27HHdYrp3725XX321uzYbNmxwY4VUq1Yt6Frp8cKFC5O9fupOE9ilRvsGAACZh5YgAAAA//+gp3/++aetXr3aDXyaI0cO1wJE9u7d628hEqhQoUL+50IZMmSIFShQwH8rXbo01xoAgExESxAAAID/v1XHiBEj3LXYvHmzmyGmcuXK1qtXL8uTJ49bnjThoZYd3nOh9O/f3/r06RO0PokQAAAyDy1BAAAAkihZsqSbCWbRokXucZkyZSxXrly2Zs2aoPX0WImS5Gib/PnzB90AAEDmIQkCAAAS2tGjR09KbuzcudOWLVtmVapUcY/VNUZT5r777rv+LjIaJ0TT6XrjhgAAgOhHdxgAAJDQfD6fmwa3Zs2aVr16ddu1a5dNmjTJTZHbs2dP/3pDhw61Jk2a2BVXXGENGzZ0CZGLLrrIOnXqlKnHDwAAwkdLEAAAkNBy5sxpixcvto4dO7rBUQsXLmxvvPGGLViwwA1m6lG3F7UOad26tZvxZcCAAfbZZ59ZtmzZMvX4AQBA+GgJAgAAEp4SGUqC6JaSYsWKBQ10CgAAYgstQQAAAAAAQEIgCQIAAAAAABICSRAAAAAAAJAQSIIAAAAAAICEQBIEAAAAAAAkBJIgAAAAAAAgIZAEAQAAAAAACYEkCAAAAAAASAgkQQAAAAAAQEIgCQIAAAAAABJC9sw+AJ/PZ1999ZWtXLnSOnToYCVLlgx6fu7cubZs2bKgZWeddZbddNNNKe738OHD9sUXX9j27dutVq1a1rBhw3Q5fgAAAAAAEBsyNQkyffp0e+ihh6xQoUL2008/Wc2aNU9KgkyaNMlmz55tl19+uX/ZOeeck+J+d+zYYS1atHD369SpYw8//LB17NjR3nzzzXQ6EwAAAAAAEO0yNQmSN29e++STT+yMM86w0qVLJ7te3bp1beTIkWHvt1+/fpYjRw5bsGCB2/cvv/xi9erVs/bt21u7du0idPQAAAAAACCWZOqYIJdeeqlVrlz5lOupS8vbb79tU6dOtY0bN6a47okTJ2zKlCnWrVs3lwDxkihNmjSx999/P2LHDgAAAAAAYktMDIy6efNmNzbIK6+84pImL7zwQrLrKkmyd+9eO/fcc4OW6/Hvv/+e4hgie/bsCboBAAAAAID4kekDo55Kjx49bNSoUZYtWzb3eNy4cXbrrbdas2bNrH79+ietrwSIFCxYMGi5xh1JKbExZMgQGzhwYMSPHwBOR8vhc7mAAAAAQKK0BLngggv8CRC5+eabrWjRovbll1+GXN/rAuMlQzxKgOTJkyfZ1+nfv7/t3r3bfztVtxsAAAAAABBbor4lSCg5c+a0Xbt2hXyuTJky7vl169YFLV+7dm2K44/kypXL3QAAAAAAQHyK6pYgx48ftzVr1gQtmzdvnmul0bRpU/+yr7/+2t577z13X7PCXHHFFfbuu++az+dzyzZt2uTGFLnqqqsy+AwAAAAAAEC0yNSWICtXrrTZs2f7W3VMmzbNli1bZg0aNHA3JTE6dOjgZnepUaOGbdiwwcaOHWu33HJL0FS3EydOdNPh3nTTTe7x0KFD3WwwV155pTVs2NAmTJjgHnfu3DnTzhUAAAAAACRwEkRjbygRIvfee69r+aHHFSpU+L+Dy57dfv75Z/vwww9tyZIlVrZsWZc0ady4cdB+WrZs6d9Gqlat6pIp48ePd9PrPvrooy4Bov0BAAAAAIDElKlZAbXS0C0lSlxcf/317pacTp06nbSsRIkS9vDDD0fkOAEAAAAAQOyL6jFBAAAAAAAAIoUkCAAAAAAASAgkQQAAAAAAQEIgCQIAAAAAABICSRAAAAAAAJAQSIIAAAAAAICEQBIEAAAAAAAkBJIgAAAAAAAgIZAEAQAAAAAACYEkCAAAAAAASAjZM/sAAAAAosGGDRvsxx9/tOzZs1uDBg2sZMmSQc9/++23tnz58qBlhQsXtuuvvz6DjxQAAKQVSRAAAJDQfD6fderUySVALrjgAjtw4IB17tzZnnnmGevdu7d/vYkTJ9qXX35prVq18i9LmigBAADRjSQIAACwRE+CtG/f3iU5smb9v57C48ePt27dulm7du2sYsWK/nXPO+88Gz16dCYeLQAAOB2MCQIAABKaEh833nijPwEirVu3thMnTtiqVauC1t2xY4eNGzfOpk+fblu2bMmEowUAAKeDJAgAAEASM2fOtGzZslnt2rWDlq9fv94+++wze+GFF1wLkZdeeinFa3f48GHbs2dP0A0AAGQeusMAAAAEWLFihfXp08fdSpUq5V9+66232siRI93AqTJmzBjr0aOHXXjhhVavXr2Q13DIkCE2cOBAri+Q4NpNa5fZhwDgdFqCHD161L7//nv/459//tnuuusuGzZsmB0/fjwtuwQAAMj0mGTt2rV22WWXWZs2bezZZ58Neq5hw4b+BIiXFClSpIh98cUXye6vf//+tnv3bv9t48aNqT4mAACQyS1BFBSon2yTJk1s//79dsUVV1j16tVt1qxZtmvXLnv66acjeIgAAADpH5OsW7fOWrRo4falgVEDxwhJTu7cue3ff/9N9vlcuXK5GwAAiOGWIGr+edttt7n7miqudOnS9vXXX7v+sxpZHQAAICNEKib5888/XQKkcePGbjuNBxJIrUq0TqDvvvvONmzY4JImAAAgjluCbN++3QoXLuzuK9Bo27atu1+pUiU3ajoAAEBGiERMcujQIbv44ovd/xdddJG9+eab/ueUGKlWrZqbRlfT5davX99q1Kjhkh9vvfWWde7c2U2vCwAA4jgJomamo0aNsiuvvNImTZpk06ZN8w8kpucAAAAyQiRiErXy0JS4snTp0qDnatWq5f7XWCAab2Ty5Mm2ZMkSK1asmOty06xZs4ifEwAAiMIxQTp27GiPPPKI3XDDDf5moJomrmfPnpE+RgAAgHSLSfLmzWujR48+5Xo5cuSwTp06uRsAAEigJMgll1xiO3fudAOBnX322f7lffv2dU1EAQAAMgIxCQAASPckiFcbEpgACWwyCgAAkFGISQAAQLrODqPBwTRomEZQV59Yz+OPP25btmxJyy4BAACISQAAQPQlQUaOHGkDBgyw6667Lmjk9XLlytngwYMjeXwAAADEJAAAIHOTIBodvU+fPkHLNbL61KlTI3NkAAAAxCQAACCzkyB//vmn1a1b193PkiWLf/mZZ55pu3btitzRAQAAEJMAAIDMTIKUKVPGfvnll5OSIB999JFVrVo11fs7fvy4S54cO3Ys2XX0nMYiCcfBgwfd/gJve/fuTfVxAQCA6BbpmAQAAMS3NCVBevbsabfccosLMOTHH3+0gQMH2r333mu9evUKez8aRFVji5QtW9YKFSpk33333UnrTJ8+3Zo1a2YFCxa0vHnzuqnwfvvttxT3+8ADD7iZazRGiXdTVx0AABBfIhWTAACAxJCmKXLvv/9+O3TokN1222124sQJa9SokRUoUMAFHd27dw97P++8845r3TFlyhQ300yoFiJjxoyxZ5991i644AI7fPiw3XPPPS6hsXLlSveaybnqqqvcfgEAQPyKVEwCAAASQ5qSIPLQQw+5gVHXrl3rgo4KFSpYjhw5UrWP/v37u/83bdoU8vls2bL5a3YkV65cNnToUCtVqpSr6bnssstS3L+SJjlz5gxqHgsAAOJLJGISAACQGNLUHSYwSVG5cmXX5zajgo0NGza4/4sUKZLiejNmzLD8+fNbvnz5XLLk999/z5DjAwAAGS8zYhIAABDHLUG6desW9k7Hjh1r6UEtO9S/t0mTJnbeeeclu16tWrVs9uzZbr0dO3bYfffdZy1btrRly5YlmzzRvnXz7NmzJ13OAQAAnJ5oiEkAAECcJ0FSmrklI+j1O3XqZNu3b7f58+en2MVFg6F5SpQoYePGjbOiRYvaBx984MYUCWXIkCGu/zAAAIhumR2TAACABEiCTJgwwTKLBkjt0qWLLVy40L755hs3JkhqaFYZbbNu3boUxydRf+LAliClS5c+reMGAACRl5kxCQAASNCBUUUzu2zdutXf4iI9BiD1EiDff/+9zZ0718qXL3/SOgcPHnS1QmeeeWbIffz111+2fv16K1OmTLKvo0FXdQMAALEnI2ISAACQoAOjHj161AYMGGCFChWykiVLulvhwoXtqaeeSlUT1SNHjtiuXbv842/s27fPPdZUd6IR3m+55RabM2eOmyVGr6HnddO2gdPjeVPsalwPjf/xxRdf2ObNm+2HH36wDh06uO4wSqYAAID4EamYBAAAJIY0tQRRt5EPP/zQnn32Watfv75bpq4qCjj+/vtve/HFF8Paz5QpU/xjdBQoUMCfpOjXr5+7Kdkxc+ZMt0yJjUAvv/yyde3a1d3PkyePmwlG1Jpj0KBBbirdJUuWuKCoWbNmNnXqVHcfAADEj0jFJAAAIDGkKQkyfvx4mzVrlr/1hdSrV89q165tbdq0CTvg0ECnuiXHa/lxKi+99FLQ4wsvvNA+/vjjsI4BAADErkjFJAAAIDGkqTuMWluce+65Jy3Xsty5c0fiuAAAAIhJAABA5idBWrVqZSNGjDhpuWpb9BwAAEBGICYBAADp3h1GI7APHDjQJk+ebBdccIF7vGjRIluxYoV17tzZ7rvvPv+6I0eOTMtLAAAAEJMAQDpoN61dRPYzo8OMiOwHiPokyP79+619+/bu/u7du93/VapUcTfN8KIbAABAeiMmAQAA6Z4E0XS1AAAAmY2YBAAApPuYIAAAAAAAAAnREkQ0Bsj8+fPt33//Pem5AQMGnO5xAQAAEJMAAIDMT4I899xz1q9fP6tevboVLFjwpOdJggAAgIxATAIAANI9CfLCCy/YzJkzrU2bNmnZHAAAICKISQAAQLqPCaKR2C+66KK0bAoAABAxxCQAACDdkyCXX345o7EDAIBMR0wCAADSvTvMiy++aHXq1LEpU6ZYxYoVLUuWLEHPDx8+PC27BQAAICYBAADRlQQZNGiQmxVm27ZtdujQocgfFQAAQBiISQAAQLonQSZOnGhffPGFtWzZMi2bAwAARAQxCQAASPckSO7cua1BgwZp2RQAACBiIhmTqIXrwoULLXv27FavXj07++yzT1rn2LFj9u2339r27dutVq1aVqNGjYi8NgAAiOKBUTUzzKRJkyJ/NAAAABkck/h8Prv11ltdMuWNN96w559/3sqXL2+vvvpq0Hr//POPNWzY0G677TbXAqVx48bWu3dv3i8AAOK9JUi2bNnsjjvusMmTJ1ulSpVOGhh15MiRkTo+AACAdI1JlARp3ry5S4CoFYi89dZbduedd7rZZ5QQkUcffdQOHjxoS5cutXz58tmPP/7oEiFXXHGFtW7dmncJAIB4TYIcPnzYrrrqKnd/8+bNkT4mAACADItJsmbNat26dQta1q5dO+vRo4etWLHCJUGUKFGLk8cff9wlQEStQnR79913SYIAABDPSZCPPvoo8kcCAIh6LYfPtWgy58EWmX0IyGTpFZN89tlnLjlSs2ZN93jjxo22e/fuk8YA0fM///xzikka3Tx79uxJl+MFAADpOCYIAABAvPrjjz/sgQcesJ49e1qZMmXcMiVApGDBgkHrFi5c2P9cKEOGDLECBQr4b6VLl07nowcAABFvCSKq1Vi8eLFt2LDBjZQeqEuXLmndLQAAQKbFJNrHpZdeai1atLBhw4b5l59xxhnu//379wetv3fvXv9zofTv39/69OkT1BKERAgAADGWBFm+fLnrK6vp4Q4cOOBqNrxakGLFipEEAQAAGSKSMYm6vCj5cd5557nxP7xBUkUtQnLkyGF//vln0DZ6XLFixWT3mStXLncDAAAx3B1GTUQ7dOjgaj9k165dtmrVKjc4mJ4DAADICJGKSTZt2uQSIHXq1LEPPvjAJTwC5cyZ01q1amXvv/++f5kSL3PmzLErr7wygmcEAACiriXIwoUL3UjoGjBMU9EdPXrUqlSpYmPGjHHTxD3yyCORP1IAAIB0iEkOHTpkLVu2tH379lmbNm1s4sSJ/ucuvPBCq1y5srs/dOhQ9/j666+3Ro0audeoW7eu3XLLLbwvAADEcxJEtSxFihRx9/X/li1brGzZsq6P67Zt2yJ9jAAAAOkWk2gckSZNmrj78+fPD3quQoUK/iSIZoL59ddf7e2333atTe688043jW7SViMAACAOB0b1KGgYOHCgG0FdNSLVqlWLzJEBAABkQEySL18+Gzt2bFjrlitXzp566ineFwAAEikJ0rdvX/99NQ29+uqrXbBRvHhxmzx5ciSPDwAAgJgEAABkXhJk+PDh/vtVq1a1FStWuJHY8+fP7/rjAgAAZARiEgAAkO6zw2jQse+//97/+Oeff3YDjykQOX78eFp2CQAAQEwCAACiryXIs88+aydOnHB9b/fv3+9GX69evbrNmjXLDVD29NNPh72vtWvX2uuvv24rV660wYMHu0HHklq+fLlbR1PR1apVy+6//37X6iQladkGAADElkjGJAAAIP6lqSWIxv+47bbb3P0vv/zSjcD+9ddf28yZM4OmlTsVjSdy2WWXuVHZp0+fbjt37jxpnUWLFln9+vVdYNOqVSv7+OOPrWnTpm46u+SkZRsAABB7IhWTAACAxJCmJIhaVxQuXNjdV6DRtm1bd79SpUq2Y8eOsPfTqVMnW716tfXu3TvZdfr372+XXHKJvfnmm9a9e3f77LPPbM2aNW56ukhuAwAAYk+kYhIAAJAY0pQEUTPTUaNG2e+//26TJk2y1q1bu+UaIFXPhUu1NVmzJn8IarmhgOaaa67xLytUqJBLcKiZa6S2AQAAsSlSMQkAAEgMWdPa/1Z9bGvUqGEXX3yx64crL730kvXs2TNiB7dx40Y30KqSJYH0eN26dRHbRg4fPmx79uwJugEAgOiWUTEJAABI4IFR1apC43f8+++/dvbZZ/uX9+3b1wUhkaLEhOTJkydoeb58+ZId3yMt28iQIUNs4MCBEThqADBrOXwulwHIABkVkwAAgARuCSI5cuQICjZEs7Ck1L0ltQoUKOD+V2AT6O+//3ZdXCK1jTeOyO7du/03tSgBAADRLyNiEgAAEB+iOjooVaqUG+zs119/DVr+yy+/WO3atSO2jeTKlctNoRt4AwAAAAAA8SOqkyBZsmSxLl262FtvveVv2TFnzhxbvHixde3a1b+eBkTr1atXqrYBAAAAAACJJU1jgkSKkhMauMwbq+Pxxx+3IkWK2I033uhuMnjwYNeKo2rVqlatWjVbtGiRPfnkk9aiRQv/fpYsWWILFizwPw5nGwAAAAAAkFgyNQlSqVIl69atm7t/1113+ZcrceE588wzbe7cuS7RsX37dqtZs+ZJM7/cd9991qlTp1RtAwAAAAAAEkuakiCagWX06NE2f/58++eff056fvbs2WHtp0yZMu52Kuricv755yf7fN26dVO9DQAAiH2RikkAAEBiSFMSRC0vpk+fbh06dLAKFSpE/qgAAADCQEwCAADSPQny4YcfuvE86tSpk5bNAQAAIoKYBAAApPvsMDlz5qQFCAAAyHTEJAAAIN2TIFdccYW99957adkUAAAgYohJAABAuneHOXLkiJvNZerUqW6GFw1CGmjkyJFp2S0AAAAxCQAAiK4kyL59++yqq65y9zdv3hzpYwIAAAgLMQkAAEj3JMhHH33EVQYAAJmOmAQAAKT7mCAAAAAAAAAJ0RJEVqxYYc8//7z73+fzWfXq1a1v37527rnnRvYIAQAAiEkAAEBmtQT59NNPrXbt2rZy5Upr3LixXXjhhe6+ls2aNSsSxwUAAEBMAgAAMr8lyGOPPWbPPPOMPfTQQ0HLhw0bZo8++qibrg4AACC9EZMAAIB0bwmyfPlyu+OOO05afvvtt9vvv/+ell0CAAAQkwAAgOhLghQpUsSWLl160vLffvvNPQcAAJARiEkAAEC6d4e59dZb7frrr7cnn3zSGjRo4Jb9+OOP9tRTT1n37t3TsksAAABiEgAAEH1JECU7cuXKZQ8//LDt3bvXLTvzzDPtwQcfdH1zAQAAMgIxCQAASPckSLZs2VwrkMcff9w2btxoWbJksVKlSlnWrGnqXQMAAJAmxCQAACDdkyAeJT3Kli17OrsAAAA4bcQkAAAgokmQbt26uf/Hjh3rv58crQMAAJAe0jMm0cDvq1atsubNm1vRokWDnluyZImtWbMmaFmBAgWsVatWqXoNAAAQA0mQY8eOhbwPAACQkdIjJvn666/tiSeesK1bt9ratWvd4xYtWgSt89prr9nMmTOtUaNG/mVlypQhCQIAQDwmQSZMmOC/37t3b7vgggtCrrdo0aLIHBkAAEAGxST//vuvDRkyxMqXL2+lS5dOdj0lQKZMmcL7AgBAIo0JUr9+ffP5fKl+DgAAIJIiFZN07NjR/b9p06YU19u9e7d9+umnrhtMrVq1LH/+/Gk4agAAEJMDoya1Z88ey5cvXyR3CQAAEDUxyeLFi23EiBG2efNm27Jli7300kvWtWvXZNc/fPiwuwUeFwAAiJEkSI8ePULelxMnTthvv/3mal0AAADSU2bEJNdff7298MILlidPHvd4+PDh1r17dzvvvPOsZs2aIbdRF5uBAwdG9DgAAEDaZU3Nyvv27XO3wPve7ejRo3bFFVcE9dMFAABID5kRk7Rs2dKfAJG+ffu67jCzZs1Kdpv+/fu7LjTebePGjRE9JgAAkI4tQSZNmuT+L1KkiI0cOTKVLwUAABAZ0RCTZMmSxc4880zbsWNHsuvkypXL3QAAQAyPCUICBEC0aTl8bkT2M+fB4CkxAUS3jIpJ1MXmn3/+cUkXz5IlS2z9+vXJzk4DAADiaGBUDfKlwcE2bNhgx44dC3quS5cukTg2AACADIlJlMxYuHChS3TIN998Yzt37rTq1au72/Hjx61p06Z21VVXWY0aNdxrvfjii9a6dWu79tpreZcAAIjnJMjy5cutXbt2tn37djtw4ICbJk79XKVYsWIkQQAAQIaIVEyybt06fxeba665xpYuXepuGgxVSZAcOXK4JMmYMWNs7ty5VqhQIXvjjTesQ4cO6Xp+AAAgCpIgDzzwgCv0hw0bZtmyZbNdu3bZ6tWr7eabb454MPDRRx+dVKsj5cuXt3r16oXcRs1T16xZE7RMQVGrVq0iemwAACBzRSomadGihbulRON/9OzZMwJHDQAAYioJopqQd99917JmzeoGBdMo7FWqVHG1IxqN/ZFHHonYAU6dOtUOHjzof6xaHo3CPmDAgGSTIK+99prNnDnTGjVq5F9WpkwZkiAAAMSZjIxJAABAgiZBVMviDQym/7ds2WJly5a10qVL27Zt2yJ6gOPHjw96/Pbbb9vnn39u3bp1S3E7JUCmTJkS0WMBAADRJSNjEgAAEPuynu4OmjRpYgMHDrRffvnFHnvsMatWrZqlp7feesu16FCAkxL1B/70009t/vz5tmfPnnQ9JgAAkPkyOiYBAAAJ0hKkb9++/vtDhw61q6++2jU7LV68uE2ePNnSy8qVK+37778Pq4WHRokfMWKEbd682dUKvfTSS9a1a9cUR5bXzUPiBACA6JdZMQkAAEigJMjw4cP996tWrWorVqxwLS/y58/v+uOmZyuQs88+201PlxKN5P7CCy9Ynjx5/MfbvXt3O++886xmzZohtxkyZIirPQIAALEjs2ISAACQoN1hAmdfSc9gQwOdjRs3zo0FomnqUtKyZUt/AsSrJVIwpAFVk9O/f38XNHm3jRs3RvT4AQBAxkjvmAQAACRAS5Abb7wx7J1OmjTJIm3GjBn2119/WY8ePVK9rQIhTWu3Y8eOZNfJlSuXuwEAgOiW2TEJAABIgJYgBQsW9N+UVHj//fft559/dvd1030tS6+aF3WFadGihVWuXPmk5zT+x5dffununzhxwnbu3Bn0/JIlS2z9+vV2wQUXpMuxAQCAjJPZMQkAAEiAliCjR4/237/55ptd95Gnn37aH2D4fD43ErsGIo007VPT4iadLtfz6quv2oIFC2zZsmV2/Phxa9q0qRs3pEaNGrZhwwZ78cUXrXXr1nbttddG/NgAAEDGysyYBAAAJODAqF988YUbeCywhkX3H3roIatevbpFmpIbSmB07Ngx5PNq4aExP0TjhSxcuNCNDD937lwrVKiQvfHGG9ahQ4eIHxcAAMhcGR2TAACABEyCHDx40FavXm0NGzYMWq5lBw4csEhTKw7dknPXXXcFPdb4Hz179oz4cQAAgOiS0TEJAABIwCRI586d7brrrrMBAwZY/fr1XbPTRYsWucddu3aN/FECAAAQkwAAgMxIgowYMcIKFy5svXv3tr179/pbX/Tq1cuefPLJ0z0mAMg0LYfP5eoDMYSYBAAApHsSJGfOnDZ48GB76qmnbOPGjW5Z6dKlLWvWsCebAQAAOG3EJAAAIN2TIB4lPcqWLXs6uwAAADhtxCQAACCiSZBu3bq5/8eOHeu/nxytAwAAkB6ISQAAQLonQY4dOxbyPgAAQEYiJgEAAOmeBJkwYULI+wAAABmJmAQAAKQVI5kCAAAAAICEkOoxQcLBmCAAACC9EJMAAIAMHRMEAAAgsxCTAACADB0TBAAAILMQkwAAgLRiTBAAAAAAAJAQwm4JktThw4dt8eLFtmHDhpOapXbp0iUSxwYAAEBMAgAAMjcJsnz5cmvXrp1t377dDhw4YAUKFLDdu3e754oVK0YSBAAAZAhiEgAAkO7dYR544AHr0KGD7d271z3etWuXrVq1yho2bOieAwAAyAjEJAAAIN2TIAsXLrT+/ftb1qxZLUuWLHb06FGrUqWKjRkzxl599dW07BIAAICYBAAARF8SRC0/ihQp4u7r/y1btrj7pUuXtm3btkX2CAEAAIhJAABANMwO06RJExs4cKD98ssv9thjj1m1atUicVwAAADEJAAAIPMHRu3bt6///tChQ+3qq692XWGKFy9ukydPjuTxAQAAEJMAAICMbwny+uuvu8FQhw8f7l9WtWpVW7Fihesio24xTZs2jcyRAQAAEJMAAIDMSoL06tXLSpQoYbfddpvNnz8/6DlNk6tBUgEAANIbMQkAAEj3JIhaejz77LO2ZMkS1+KjevXq9vzzz9tff/2VphcHAABIi/SKSVavXm0zZ860v//+O9l1li5darNnz/YPDA8AAOI0CVKoUCG77777XMCxePFiu/jii23w4MFWsmRJu/baa23WrFl24sSJ9DtaAACAdIhJvv32W7v00kvtkksusXbt2rlER1L79u1zz+u1nnjiCatYsaJ7TQAAkACzw5x//vk2atQo27p1q40dO9b+/fdfa9u2rZUrVy6yRwgAAJDOMYladTzyyCP2/fffJ7uOEh/r1q2zVatW2Q8//GAff/yxWzZv3jzeHwAAEmWK3Ny5c1udOnWsbt26blyQbdu2RebIAAAAMigmueGGG6xVq1bJjm/m8/ls/Pjx1qNHDzvrrLPcMq2vBMy4ceN4nwAAiPckyJ49e9xsMY0aNbKaNWvaJ598Yv3797dNmzZF9ggBAAAyOSbZvHmzGydESZZASrj8+uuvyW53+PBhd3yBNwAAkHmyp2Zl1YKoyefbb79tU6ZMccvU73bYsGHWrFmz9DpGAACATI1Jdu3a5f4vXLhw0HK1CvGeC2XIkCE2cOBA3j0AAGIxCVK5cmVbs2aNXXDBBW4E9k6dOln+/PnT7+gAAACiICbJmTOn+//AgQNBy/XYey4UtUjp06eP/7FagpQuXTrdjhMAAEQwCdKmTRvXF7Z27dqp2QwAACCiMjomKVOmjGXLlu2kLjYbN2608uXLJ7tdrly53A0AAMTgmCAvvfRShidAevfubfny5Qu6NWjQ4JTbqW9wjRo1rEiRIm4qO02fBwAA4kNGxyQadLV58+b24Ycf+pepG8xXX31ll19+eYYdBwAAyMCWIJnh0KFDbvR1jcjuUU1MSiZOnGg9e/Z00+Q1btzY9Q++5JJL7Pfff7dzzjknA44aAADEErXw+OWXX9zgp6IpcPft22dVqlRxN298j4suusjuvvtuF1+MHj3aTcPbvXv3TD56AACQYVPkZgQlPQJbgpxxxhkprq8g5dZbb7Ubb7zRypYt62qLtM2rr76aYccMAABix6pVq1xSY/Lkyda2bVubP3++e7xo0SL/OmqJ+tNPP7lpdKdPn26XXXaZfffdd6eMSwAAQPSI+pYgMnv2bDv77LOtQIECbsT3p59+2kqUKBFyXTVNXb58uQ0YMMC/LGvWrNayZUsXqAAAACSlFqO6nYq64LzyyitcQAAAYlTUtwTRCOpqwaEmqu+++64bCb5p06auiWooW7Zscf8raRJIj7du3Zrs6xw+fNiN2B54AwAAAAAA8SPqW4I89thj/vsaz2Pq1KlWsmRJmzRpkhsVPjlq/ZH0sc/nS7ELzcCBAyN01ED6aDl8bkT2M+fBFlFzLLJ302r3/53jFtmZc0hAIrH/tgAAAJDALUGS0mwvmqZu9er/+9GUlNcC5K+//gparsdJW4cE6t+/v+3evdt/05R3AAAAAAAgfsRcEkTdYDZv3pxsQkNJkkqVKtm8efOCln/zzTfWqFGjZPebK1cuy58/f9ANAAAAAADEj6hOgmicjq5du7qpbY8fP+5aZ3Tp0sUlLDp16uRf77777nMjtnt69+5tb731lkt8aIrdQYMG2Y4dO+yuu+7KpDMBAAAAAACZLarHBFGy48orr3SJDyVC8uTJ42aH+eGHH9z4IB4lOg4cOOB/fO+999rff/9tHTp0cF1bKleubB9//LFVrFgxk84EAAAAAABktqhOgsgNN9zgbmoJki1btpDrjBo1yk6cOBG07Mknn3S3o0ePWo4cOTLoaAEAAAAAQLSK+iSIJ7kEiNdiJDkkQAAAAAAAQNSPCQIAAAAAABApJEEAAAAAAEBCIAkCAAAAAAASQsyMCQIAAAAAGandtHZhrbd7zW73f+85va3A+gKWKMK9Pqcyo8OMiOwHCActQQAAAAAAQEIgCQIAAAAAABICSRAAAAAAAJAQSIIAAAAAAICEQBIEAAAAAAAkBGaHQVxqOXxuRPYz58EWFo8idX0AAAAAIJbQEgQAAAAAACQEkiAAAAAAACAhkAQBAAAAAAAJgSQIAAAAAABICCRBAAAAAABAQiAJAgAAAAAAEgJJEAAAAAAAkBBIggAAAAAAgIRAEgQAAAAAACQEkiAAAAAAACAhkAQBAAAAAAAJIXtmHwAAAAAAIHG1m9YuIvuZ0WFGRPaD+EZLEAAAAAAAkBBIggAAAAAAgIRAdxgAAIAwrFy50jZt2hS0LF++fNaoUSOuHwAAMYIkCJABWg6fy3UGEuBvK1LHM+fBFhHZDyJrxIgRNm3aNKtVq5Z/Wfny5UmCAAAQQ0iCAAAAhKlZs2Y2ZcoUrhcAADGKMUEAAADCdODAAfv+++9t+fLlduTIEa4bAAAxJupbgvh8Pvv0009dwJE9e3Zr2rSptWrVKsVt3n33XZs3b17QspIlS9oTTzyRzkcLAADi2ddff207d+60rVu32rFjx+zVV1+1q6++Otn1Dx8+7G6ePXv2ZNCRAgCAmEuCnDhxwurUqWPlypWzxo0bu9qXG2+80dq3b29vv/12stspAfLTTz/ZHXfc4V9WuHDhDDpqAAAQj6688kobMmSIFSpUyFXSPPnkk3bTTTfZr7/+alWqVAm5jdYfOHBghh8rkOjaTWuX2YcAIEpFdRIkS5Ys9sEHH9i5557rX3bxxRfbpZdear169XIJkuRUqFDB7rrrrgw6UgAAkAhJkMAYRcmNkSNH2owZM6xv374ht+nfv7/16dMnqCVI6dKlM+R4AQBADCZBAhMg4j3etm1bikmQ1atXu6CjQIECbhCzli1bpvvxAgCAxJE1a1bX0lRdY5KTK1cudwMAANEh5gZGffPNNy1v3rxWv379FJMnqmUpXry4/fPPP9auXTu7/fbbU9yv+uuqdibwBgAA4HXR3bt3b9DFWLFihf35558pVsoAAIDoEtUtQZL6/PPPbdCgQfbKK6+kOMbH448/7gZC9Vx33XWuNci1115rrVu3DrkNfXYBAEByjh8/bg0aNLCuXbtajRo1bMOGDfbcc8+5MctuuOEGLhwAADEiZlqCzJ071zp27GgDBgw4ZauOwASIaEaZMmXKuBlmkqM+u7t37/bfNm7cGLFjBwAAsS1Hjhxu4HXNCDN27FhbsmSJPfXUU/bNN99Yzpw5M/vwAABAPLUEUdChwcj69etnjz32WJr2cejQIVeLkxz67AIAgJQULVrUzQgDAABiV9S3BPn222+tTZs29sgjj9gTTzwRcp0JEya4bjKiGhp1mwk0ZswY27Fjh11++eUZcswAAAAAACD6RHVLkH379lnbtm3dQKibN28OmvJWfXIvvPBCf1eZBQsWuCSJBkUdNWqU697i9dldtGiRDRs2zHWLAQAAAAAAiSmqkyDZs2d3g46FctZZZwUlRC677DJ3P1u2bPbxxx/b77//7vrrFipUyOrVq2fFihXLsOMGAAAAAGSsdtPaRWQ/MzrMiMh+EJ2iOgmSO3fuoNYfyWnevPlJy6pXr+5uAAAAAAAAMTEmCAAAAAAAQNy3BIlHLYfPjch+5jzYIiL7Qca8XwAQq989lDcAACCe0BIEAAAAAAAkBJIgAAAAAAAgIZAEAQAAAAAACYEkCAAAAAAASAgkQQAAAAAAQEJgdhgAAAAgBrWb1i4i+5nRYUbUHE+kjgUAkkNLEAAAAAAAkBBIggAAAAAAgIRAEgQAAAAAACQEkiAAAAAAACAhkAQBAAAAAAAJgSQIAAAAAABICCRBAAAAAABAQiAJAgAAAAAAEkL2zD4AAAAAID21m9YuIvuZ0WFGRPYDIDHE63dPuwicV2aeE0mQBNdy+NzMPgQAAAAAADIE3WEAAAAAAEBCIAkCAAAAAAASAkkQAAAAAACQEEiCAAAAAACAhEASBAAAAAAAJASSIAAAAAAAICGQBAEAAAAAAAkhe2YfAAAAAE5Pu2ntInIJZ3SYwVsRQ+9XPB5PNB0LEG/4+/o/tAQBAAAAAAAJgSQIAAAAAABICDGTBNm4caMtWrTI9uzZk67bAAAAEF8AABCfoj4JcujQIbvmmmusatWq1rVrVytevLi9/PLLEd8GAACA+AIAgPgW9QOjDhw40H766Sdbs2aNlShRwj766CPr0KGDNWjQwBo2bBixbQAAACIdkwAAgOgS9S1BxowZYz169HDBhlx99dVWs2ZNtzyS2wAAAEQ6JgEAANElqluCbNmyxbZv32716tULWq4alyVLlkRsGzl8+LC7eXbv3u3+j/R4IscO7Y/IfiJ1XJE6HuB0HD980P8/n0kguqTHuFrePn0+n8WKaI8vjh44GpH9xOs4atF2fSJ1PIgexw4d8//P+xv7ou1vPdqOJ9bji6hOgvzzzz/u/7POOitouR57z0ViGxkyZIhr5ppU6dKlLRoVeCKzjwCIvCWje3NZgQQqb/bu3WsFChSwWJAw8YXFxvuRWbg+OJUfnviBixQHou1vPdqOJ9rP6VTxRVQnQXLkyOEf6DTQwYMHLWfOnBHbRvr37299+vTxPz5x4oQLahTcZMmSxWKFsl8KrDQzTv78+S1ecZ7xhfczviTK+5lI5xrp81QNjQKUc845x2JFoscX0SRR/u4yAteSaxmN+FxyPdM7vojqJIgKuKxZs9rmzZuDlutxmTJlIraN5MqVy90CFSxY0GKVgoJECAw4z/jC+xlfEuX9TKRzjeR5xkoLEA/xRfRJlL+7jMC15FpGIz6XXM/0ii+iemDUPHnyWJMmTezjjz/2L9u/f7/Nnj3bWrVq5V/2xx9/+PvjhrsNAABApGMSAAAQ3aK6JYgMHjzYBRdqTtq4cWN7+eWX7eyzz7Y77rjDv86zzz5rCxYssGXLloW9DQAAQKRjEgAAEN2iuiWING/e3L7++mtbv369vfjii1ajRg377rvvLF++fP51KleubOeff36qtolX6tLzn//856SuPfGG84wvvJ/xJVHez0Q610Q5z1NJ5PgimvB55FpGIz6XXMtoxWfzZFl8sTQ/HQAAAAAAQLy2BAEAAAAAAIgEkiAAAAAAACAhkAQBAAAAAAAJIepnh0HqHDlyxFauXGl58+a1cuXKWbZs2U5a58SJE7Z8+XJ3X4O6Zc0ae7mww4cP26pVq9w80GXKlLEsWbKEXG/16tW2b98+d56xOqDfli1bbO3atVa7dm03X3ooGzZssB07dliVKlWSXSdaHT9+3H0e9R7G6ucxlEOHDtnPP/9sJUqUsPLly4dcZ/fu3fa///3PihUrZqVLl7ZY9Pfff7vPn75vChUqlOy1+P333+3MM890A1nHIn3n6LtV56BzDfU51WdZs5Tpe7d69eox/VnetGmT/fnnn1atWjUrUqTISc/rWhw8eND9zebMmTNTjhHxT+WaBqEtW7asm4UnHLt27XJlSsWKFa148eIR22+s09+rvocVN1WqVOm0t9FzixcvPmmbWrVqufXjgYZN1PkfO3bMfddlz549ItukZb/xYOPGjbZ9+/ZUxaopbbNmzRrbunVr0DL9/jnvvPMs3ul77o8//nDfcaVKlQprG/3NLlmyxEqWLOm++yK135ilgVER+44cOeLr16+fr0iRIr66dev6SpQo4StXrpzvq6++Clrvl19+8ZUvX949f84557j7WhYr9uzZ4+vZs6evUKFCvtq1a/uKFSvmq1mzpu/nn38OWm/r1q2+Bg0a+AoWLOirUKGCr3Dhwr6ZM2f6YsmPP/7o69Chg69o0aIavNj37bffnrTOgQMHfO3bt/flyZPHV61aNd8ZZ5zhGzVqlC9W6H0rW7asr2TJkr7ixYv7Klas6Fu6dKkvlu3cudP34IMPur8vvR+9evUKud5LL73knj/33HPd/x07dvQdOnTIFysWLVrka9mypf87R5/BLl26nHQO06dPd3+vlSpVcn+PjRo18m3fvt0XK3Q+ej/POuss33nnnef/nCb9e1y4cKGvTJkyvlKlSrnvJZ3v8uXLfbFo165d7hz1vfPee+8FPbdhwwZfnTp13PVQ+aHvp9mzZ2fasSJ+9e7d25crVy5f9erV3f96nJI1a9b4unfv7uKbrFmz+l599dWI7DceTJ482VegQAFf5cqVffnz5/c1bdrU9/fff5/WNitWrHDfEfXr1/ddeOGF/pu+C+PBqlWrXFx19tln+0qXLu3ilO+///60t0nLfmPdwYMHXYyjWMeLVRUDne42d955pyuLAj9/Xbt29cW7YcOG+XLnzu2PH2+44Qbf4cOHk11fMZe+5/TdqO0eeeSRiOw31pEEiRO7d+/2vfjii+5LQ44fP+6766673A+UEydOuGVHjx51hVnnzp3dMt1uvPFGt+zYsWO+WKAgR+epH/9e8kfnoB8f3nnKlVde6WvYsKF/vUGDBvny5csXUz++3nrrLd+UKVN8//vf/5JNgujHmc5927Zt/qAlS5Ys7gdqtNN7pwTVLbfc4h7r/bvuuutcYafPb6xasmSJ77nnnvP99ddfvnr16oVMgixYsMC9Tx9//LF7vHnzZpc06d+/vy9W6MfxnDlz/I/XrVvnfvwHnsOWLVtcckTXQ/bv3+87//zzXXIvVuh9fOWVV/zJHX1XduvWzQWuHgUJSubpB5jo86tzrFGjRtD3Uqy4/vrrXZAUKgnSokULd/MCI62nJNe///6bSUeLeDR27Fj33eFV0ihhrqD8nXfeSXabTz/91Pf666/79u3b58ubN2/IJEha9hvr1q9f75I93g9IVSap8uimm246rW28JMjGjRt98UhJ73bt2vnjY/3gVjntxdlp3SYt+411qqRVBYFiApk2bZr77CgWOp1tdO2uueYaXyKZO3euix8///xz/9+qEmoDBw5MdpuffvrJ9/zzz7skpuKSUEmQuWnYb6wjCRLH3n33XVcb4iUC9INFXyArV670r7Ns2TK37Ouvv/bFKtVC6hz0BytKCOgPWQkEj66BgqKXX37ZF2v04zJUEkQ/rpQBHzx4cNByZXDvvfdeX7T74osv3Hn98ccf/mUKTJNL+MSi5JIgd9xxh2s9Eejxxx93SYRYpuRAs2bN/I9feOEFV4MYWJMwYcIEX7Zs2VyLmVj19ttv+3LkyOESy96PL31u9bfqUSJSy3744QdfLHnttddca529e/eelARZu3atW/bZZ5/5lyn5oWsxZsyYTDpixKOLLrrIVXAEuvbaa33NmzcPa/vkkiCnu99Y9Mwzz7hYIbCy680333R/t6pAS+s2XhJk3rx5LpmkREm80Pkk/cGtZI9iS/0YT+s2adlvPFBsM2DAgKBlSqopiXE62+h+27ZtfYsXL3axZCxXoIXr5ptvdmV00gpRVcSEI7kkyM2nud9YFLsdlhGSxhf49ttvbfz48fbkk0/aY489ZmeccYZ7Tv3A1FeuatWq/vXVFzFPnjzuuVi1cOFCdw4ae0F+/fVX19+yXr16/nV0DXSusXyeofpJajyGwPOU+vXrx8R56hjVb1j9tj116tRx4wvEwvGfDp1f0vetQYMGrt9r0v6tsUJjDWkMlMB+4zpP9Q8PHDNC56mxM3777TeLJRqDaN68eTZu3DgbNGiQDRgwwN+PW+d51llnubFCPOeff74bGySWPsvqo/7EE0/YhAkTQvZR984l8LNbsGBBN85LLJ0nYvc78nQ/Z+m132imc6tbt27QGHE656NHj/rHhzudbW666Sbr0qWL+w6866673PhJsc77POh73KPxERRnJvdZCWebtOw31mlcO8U2qfm7S802n3/+uXXr1s0aN27sxrn49NNPLZ4l9x2mMY7+/fffqNtvNEuMkXhi1Pfff+9+WCRHA/TpR2OgyZMn24wZM9xAmvoyuPbaa/3P/fPPP66QSkrL9FxmUdJi7969yT6vwQWbNGkS8jkNQvj0009bv379LEeOHG6Zdy5JzzWzz1ODtGowtpQogRHuAK4pnedPP/1k0S5aP4+Zde7eYz3nJfRiyTPPPOOSsO+9917Y5xlLdF4KtjQQmxI9V199dYrnqYF+CxcuHDPnqQHTbrjhBhs6dKhLTGow26S8c9F5JdrfLCIz0G5KVFGhwZU1WKRiglDfHXv27HFJ1FCDvp9Keu03o+3fv/+UP5jPOeccq1ChQpq/h8PZJl++fDZz5kxr27atP5a7+OKLXeWGvkdimc5Rg3B6cWU433XhbJOW/ca6tMTk4W7TunVre+qpp9zgxvr77d+/v1133XWukiWwgi2enOpvM7kB6jNrv9GMJEgUU41cShl1jdr/5ptvBi179NFH3U1fBg8//LC1aNHCBe368OpLN1Rgq+A3M0f3f/nll91MA8lRUuCrr746abnO6/LLL7d27dq5Fi8er3DRuSpRFHiegY8z2vvvv+9+RKVkypQpyY5mn1TgeUbT+xmuaP08Zta567wlFs9d30MKRPQZ16woged54MCBuDhPtfzQTT+kevfu7f9u1XdKPHyW1bpFPwCV4Pnuu+/cTGNeCxj9uFHC3fvOUbnktTCMtfNE5vjmm2/s1VdfTXGd5557zlV46HOoyo9Q35FantZERXrtN6OptaAqflJyzTXX2AMPPJDm8iacbdSCIXD2CH1H3HPPPa4lcqwnQdLynR7ONvFQVqRWWmLVcLfp0KGD/77+focMGWKvv/66ffzxx/7Pf7xJr/gxR5zFpeEgCRLFQv3wD5e+DPr06WMvvPCC/fjjjy5ZoJYh6j6hD3nu3Ln9H3A1c9I0s5klaSInHGrpohqHpk2bugI3cCpKb9qnzZs3W9GiRf3L9fiCCy6wzExq6RYp3tTAOq9AepyZ72e49D7t3LnT/djyvmBVw6VpY2Ph+E/33EO9b/ocx9qUZG+//bbde++9NnHixKCAxDvP2bNnBy3zzjtW32N1E1FwNWrUKDc9pJIhOk+18lJTcS94U82ypueOlfNUUkM1u96PK3Up9FrAqOudvqcDv1sDuz2p6fKVV16ZSUeOWNC5c2d3C4fKNU0ZHumyLb32m9G8RGW49He7aNGiVH0Pp2Ub0XTvSa9vLNL5KzZRjOJNEa7KRXXRSOmanWqbtOw31ulvTrFNav7u0rKN99tHrRfi4TOY2vhRsUe4lagZud9oxpggcUI/HpPSPM+BzZkuueQSF9gG9pdTU0Yta9mypcUKNalVAkT9/9R3PWntjfqxqnBRJtizYsUK11S/VatWFi9UA92wYcOg81RT3zlz5sTEeerzqB+Nn332mX+ZzkUFXyx9HtNC74+SA4GtJKZPn24XXnhhUA17tBs7dqzdfffd7u9QTVBDnaf6j6vFROB5qkDVWCHx8t166aWXutYRX375ZdB5KmGi76pYoAStflh5Ny8Jr9YvXqJa3zf63gn8ztGYTEqCxMJ3DmKHPk9efCL6X119Az9nCtDnz58f8f3GG52bus+oS1Lg95N+TFapUsU9Vlmkv3tVQoS7TajvRn0H1qxZ02LdRRdd5CpnAr/rFFspxgr8rOj7z+vmFc424e43nmjMPrXwCjxnfXYUAwWes8pVr5tXONvob9drqeBRnK8xLOLhM5gcnf8XX3wR1FNAf5uqkPEqYVThHdiiM1L7jTuZPTIrImPSpEluhGRN//bll1+6ac00haOmig10//33uymPNB2cbkWLFvX17NkzZt4GzfxSrlw5N0K0pnPSLCLeLXBkcs1woOndRowY4aaN1WjILVu29MUSnavOS8evP1VN06nHGzZs8K/z1Vdf+bJnz+579NFHfR999JE7R015rCkCY8Hdd9/tK168uG/cuHFudgmNRt+nTx9fLNNo+t5nsmrVqm7aX93X1LkefVY1PfBll13mmz59uhupW+/jN99844sVH3zwgZt9SrPfBP4dBk7PrBmMNOtCnTp13GxNmqJNswto+udYoe/Uq6++2n1GNaORvlP0mU06Ld/tt9/upjkcP368mz2mcOHCvocfftgXqzRdY6gpcvUeaorRUaNG+d5//333fXPVVVdl2nEiPq1Zs8ZXsGBBN2OBphLv2rWre6zlnmHDhrmZpgK/V73vIU17q5kNdD9wRrxw9htvVCZp1gfNVjZ16lTf0KFDXXkzceJE/zpLly51f++KH8PdRuVWjx49XFmga9mlSxdfzpw5fbNmzfLFgyeeeMJ9Nt544w133pquVZ+bQIqz+/btm6ptwlkn3iheV9mvaW8V81x66aW+ihUrulnIPJpiXrF6uNto1jnNhqgySTOWaXps/T6oX7++f0r7ePTPP//4ypQp42vTpo37u1PMrL+7wJnovN8N3vTVR44c8X83li9f3te5c2d3/9dff03VfuNNFv2T2YkYRK7PrbqGKAuqQbHatGnjamcDu4pooNXRo0e7mhBRE2aN5h24TjRTlvj+++8P+Zz6AQaOR/Dhhx+666Em6c2aNbO+ffu62XFihd6jZ5999qTld9xxh918883+x5oN6JVXXnHN8dUnV83ZNUhULFAzUPUT/+STT1xT5auuusqdX6x8HkPR503dz5LSDBpjxozxP962bZt7f5cuXeqaEKtLiVqCxAr1+VYNalLqzjNp0qSg2pthw4a5Glu1ItBnN3BQ0VigVhHq7qNaUQ1aq3GIOnbsGPQ51Vgh+iyrpZ2Wt2/f3nr06BGzn2XVIKlF1sCBA12rrUDqIqP3WLVwaumi7kFeF0sgUjRW2PDhw133Vw3y+eCDD7qx0Dz6DCqemTt3rn92I5UfSamlllo0hbvfeKTuefoe/uGHH9zApbfeemtQF7Z169ZZ165dbcSIEf5uw6faRj8f9F2gckDrauZBlWPxMiClzk+tHadOneq+3zUI53333RdUK65yQN+POu9wtwlnnXikGEDdSNX1Ry1BFasGdrNQTKGWo5qBLdxtND6OxhXUbwONfahYX+VuvF9LtYLzrpdiEv0uUktNj74TH3/8cZs2bZobFkADmyq+DjUY9WuvvRb2fuMNSRAAAAAAAJAQYrOKCgAAAAAAIJVIggAAAAAAgIRAEgQAAAAAACQEkiAAAAAAACAhkAQBAAAAAAAJgSQIAAAAAABICCRBAAAAAABAQiAJAiDVvv32W/vll1/8j+fMmWNLly5N6Cu5YsUK+/HHH9P9df744w93/QEAyGx///23zZo1yyZNmmQHDx7M8NefPXu2/f777zHzOnPnzk34eAmIBtkz+wAARN66dev8P8izZs1qxYoVs9q1a1uhQoUisv+hQ4datWrVrG7duu7xU089ZU2bNrVatWpZIjp69Kh16NDBRo4cme6vlTdvXvdaixcvtrJly6b76wEA4sehQ4fso48+8j8uWLCgK8/LlSuXpqR8/fr17YILLrCzzjrLLrvsMjvjjDMsvXzxxRdWunRpO/fcc/3LHn/8cbvyyiutevXq6fa6kXydwYMHW6NGjRI2XgKiBUkQIA598803duutt9oNN9xgPp/P1qxZY6tXr7ZXX33VOnfuHPHXa9mypQuiEtVbb71lBQoUsEsvvTTdX6tEiRJ2/fXXu8STXhcAgHDt2rXLbrrpJmvevLkVL17c/vnnHxcz3HbbbS5GSI3333/fJQW+/PLLDHkDHn30Ubv22muDkiCtWrWyGjVqpPtrZ9TrAMgYJEGAOKbmqZ4HHnjA7rzzTrvmmmssd+7cbtkPP/xg69evtyxZsliRIkVcyw7V5iS1e/du1wVDLUnOO++8k55XK5CiRYv6H8+YMcMFCxUqVPAvU5ClRIHXekTUtFQ1SWrRoJYqOo7knDhxwn766Sfbvn27VapU6aRgxKsh0nmoFYxqt1TbMmXKFBe8qMnu8uXL3XZVqlTxd2FZuXKlO3atmz37//tK1HVRlx/V/Gh/mzdvtjZt2riWGEmpBci999570rbt2rVzzV43btzoan0CW24E7l/r6LGubZkyZez48ePuvdF1Vy3b2WefHfR6Xbt2dYmn4cOHR6x1DwAgcfTr188uv/xyd//zzz939zt27OjKS4/KIpW7O3bscOVmYPLhq6++svnz57suMIo1VI5ecskl9tlnn7myX+W9tlWZ3LhxY/vuu+9s06ZNrpxXmaZYIFT5pbJ+4cKFrqxXmahy3Ysh/v33X/vtt9/8sY3iGSVzzjnnHPdY2x04cMAtC6QyXC1gvOUpnVdyAl9HvPNUzLRkyRLLkSOHiyNy5coVtJ2OWefuxVihpHQ82rfig6uvvtq/TNfm66+/du9VqJhN9u3b5+KIY8eOWZ06dYKO/ciRI/bhhx+693zbtm0uFtM6OnYdh15L10zvl9Y588wz3TEuWLDAf4xJYzA9p/dWSbHvv//evY9XXHHFKa8rkFlIggAJQoXRiBEjXNKhZs2a/oBBhZXoR76Ci7ffftsFFp5Fixa5QlAFqIIc/aBXsiCw5UfS7jD333+/azoamAQZMmSIe10FAWqdoh/yCryaNGniXluF7Mcff+z+T0oBwFVXXeUK7sqVK9vPP/9s9erVs8mTJ1vOnDn9NUT58uWzP//80yVUFLDotVTjpeTFqlWr3OPu3bu7fXTr1s01CdbrKxGSJ08edzylSpVy+1PSR4kNBQYKIpScaNGixUlJEL2ekitKSni8bc8//3zXVUZJJy3TtfVa4njrKKGj41bAoCDi5Zdfttdff90FkAradGwKdgKDpwYNGrj3QEGoasUAAEgr/ZjOli2b/frrr/4kyNq1a10iXypWrOhigQsvvNDee+89V/6oDFMrU/3YVlmqmEBJkAcffNAlObS9yk8tUxJEP6oVc4jiCJWb48eP97+GKD7RD3BVAKgcV0VFz549rXfv3u4HvRIK2k7lpSguCOymoh/zqvDRD3svNhCVu2rporjgVOcVbncYnae6GisG0DJVZuTPn98dpxcn6L7iD3U1UsJny5Yt7tiVLPGc6ni0z5tvvtmef/55u/3221385MURau0byqeffuq2UTJFMZXivMcee8weeugh9/yePXtcbNS2bVvXSljvk15HrYRuueUWa9iwoUsm6bh1LHqPFQfqeZ2rzksx5cSJE12Xa68ySO+X9q3zUJKEJAiimg9A3BkzZowv6Z/3K6+84suSJYtv69atyW43ceJEX5EiRXyHDh3yL6tXr56vW7duvhMnTrjHkydPdvvu27evf53mzZv7HnvsMf/jsmXL+t54442gfbdu3dq/zbJly9yxbNq0yf/8d99959uxY0fI42rSpImvd+/e/mPYv3+/r3bt2r4hQ4YEHWexYsV827Zt8y/bu3evO9ZWrVr5jhw54l8+YcIEX548eXyrVq1yjw8cOOBr3Lix77rrrvOvM378eLftf//7X19Kpk6d6suWLZv/2AK3ffPNN/3LBg8e7CtTpsxJ6+i98nTu3Nkte++99/zL2rdv77vppptOet369ev7Hn744RSPDQCAQIoBVM7MmjXLv2zt2rVu2TvvvBNUpvbr1y+oPK1WrVpQmdirVy9f27Ztg/Zfo0YNX6lSpXx//fVXihf+rbfe8hUvXtx37Ngx91hlaJ06dXxXXnml7+DBg27Z0aNHfTNnzgw6psByXxo2bOgbNGiQu79nzx7fGWec4fvoo4/8z//www8u3vjzzz/DPq9QAl/HO89KlSr5/v33X/d437597nwUa8nx48d9NWvW9N15550nlfuB8VI4x6M4QTHLypUrfc8995yvcOHCQfFToC1btvjy5cvn+/TTT/3LFHPpuvz888/usd4bHYeuta6xx4vvkl7jLl26+Bo0aOBiL/njjz/ca+g9DIxfcuTI4fvtt99SvI5AtKAlCBDH1GTUGxNEtQi9evVyfYADqVnlsmXLbOfOna6lhf5XzYRqEFQrowE433nnHX9XFbU8CGzhkRZedxzVnJQsWdLdV21DKKqlUC3GjTfeaFOnTnXno5tqGtRCQk16PRorQzUzSd11112uqWrgddF5eN1iNJBb3759Xa2KWm5466pm7J577knxXHS91PUmaVcenaPGZfGoFYlqktR02Bs4Tuuotsaj2jJ1JdK5Bi5Ti5ekVKuk1wYAILXUvUQ1+xoTRGOBqOWi17JQrUJV9vfo0cN1KfXKXbVcVLmrlhkpUSsDdf9ISi00FG+oe6q6V+jxhg0brHz58q57qFqiKN7wYgS1hFBrhXCp1YNah6iFQvv27d0y3VdLVXVHPd3zCnWeKv9FrT80QKxanYpapehcAwehVQuOwJgl3ONRy1XNwKNz0sD3aiXixU5JKV5Qy9b9+/f7YwftU+OJaWaawC7Nd999d8jWL2rN61HLFe1nzJgxbr+i+EtximIptbAJjHMY8BWxgiQIEMdU+CrQUEGrfqN9+vQ5aZYXdWVRoajkgVcYqs+nkiAKTiTpqPEKWE6HCtD//ve/rtmlgh11JVEhn7Qfr6ipqcybN88lJTxq6uolMTwq5ENJulzdaxSsJD0mXSv1gfXOT9cssEltKOrKomAjKXVn8ZqJitdP+PDhw/4kSKh1kvaR1jJ1i0lKrxmq6xAAAKeiLg36Qa0yTxUeGiPC+5Hrlbv6IR6Y4NcPfXUnPZVQZbFiDcUc6soaOM6V4g2VuV68kbRcTy0lGlQhom4ZOp8PPvjABg0aFPZ5qdLI67bj/bBPWnnkKVy4cLLltXc+gWOB6TUD46nUXGedQ9WqVe2iiy5yY7ckR/tU4kJJlUAaXyzpeYR6n9QtJrDbrxJViluSVn4pZlJcdqr9AdGKJAgQx7zBw/TjXjUI6murQa+UTFBNTP/+/d24EhdffLG/sFPAoFoD8QbcUj/cwEJRj1OiH/Zen11P0h/yapWi2gYlaKZNm+b6DX/yySfWunXrkwpkGThw4CmnpktuYNWky1VDpdqvQN7jwNqrlAZq9Shg07np2iUXKKUHBTrpMdMPACCxBkZ98cUXXSsQtcRQKwSv3NVYXmlp+Zm07NS4X//5z39cq061bvTKMK91p3gtKhSbeGNzpYXOSfGKkjqq3FFrl+uuu849F855KTEU2HpDFUJpKdu9+EmvHxhXBMZPqbnOGoNE467oGs6ZMydoHLJA2qcqWgIHxk9OqBgn6TKdh2K6UDFT0tY+4cRMQLT4f1WQAOKWkh6jR492zTPfeOMNfzcYBR+qWfAkrTnQcyrkAgMC1ZIoUEqJmmmqZimw0A/cRkGOahZUsGrATyU4NDCXBk5LSk10VWuk409Kg4ylhZrGqtuJur541NxTA7GltnWFWtGoNkij5GcUBY8KKjNiSl4AQHzT4KMayFI/tL3Bt9UqMWm5q5hh69atqd6/4g1JKd5QSwUlQsaNGxe0/K+//gpqeRmqZWQgdWdVSxB1g9FN3Wm8FpbhnJfKVSUQvJtik7TQ9dT5BMZPGjhUN0+411ndldR9SV1i1KJXrWiTq4xSEkgDz6pSKZAGOlVCJrXUukWtd5RU8miweJ2XYikgVtESBEgQqllRoKOEg2Zm8aZhU59WFagqmJMGH+qqoiaY6peqJqtKRrz00kv+2ovkaJwLjdCuwl1dPtSXNLCGQAkSvaZqZ9SkUgkSzYLiJWgCqTvKm2++6dZVIKUARWNhaCYZvY76tKaWAj2NSq99derUyfVF1swtGlE9LQkmjf2hPrqBs+qkp/fff981iQ2nWTIAAClR+fzcc8+5VqFK6GuMLpXHKh+VcNdylb/Tp093ZW7geFfhJgTUwkTJCe1TY2WoDA6kriuvvPKKiw3UZVVJEU0Pq66fY8eOdeuoG6sSE+pSovgkuTK3S5cu1qxZM7dO4OvoNSJ5XilRwkatXxR36bUUDyl+UkyUmuNRbKSY5bXXXnPnPXjwYJs9e7bdeeedruVuUpp5RokSxUz33XefSzwp5lKrG7W69VrcpMYLL7zg4iV9Trz3QOObPfLII6d9nYDMQksQIA6pf22oqdPU/UVNKNXiQuN/qGZB/V01WJay/eojrO0C++tqUFEVtCqg1QJByQI1ow0cXEv7VCsKj6ZxU9Ci9RXMKLB5+OGH/dto+rUvvvjCBSg6BjVd1eBgavURiqaPU9CkpqDfffedC4o0lWxgAkTdaJJ2l1GNkM4naZNNJXH0eqoxUcCnQETdhNQlx6NgQ92HwqGAQ81Tvf69obZVaxEdizfGSKh1lBAKnC5QFMAETjOn1isKhjTIKgAAqaGuEiqLko7foFhAZbvXIlMJBnVXVTcNTYerFhiavj0wUaAyWwn5QCqvAlt8iOIL7UM/0BVvKEHgxRuB5bMqZTQehxIFel5xhSpBPAMGDHDT3CtuUEsElYea0ldJlkBNmjRxA3Z26NDhpIFVwzmvUJK+TqjzVMsIJW88qkCaMGGCi4M09ooSMkpoBMZLpzoeVfho4HYldry45t1333UtadW6NxQNhD9z5kw32L1iHCVgNH6Hd/x6P3Ttk45BVrp06ZCJJZ2Xpu7V+6IYTLGSElSBY6Kom5NiOyBWZNEUMZl9EAAQ6zSivRJL6T1OhwJUBTfeQG8AAAAAwkcSBAAAAAAAJAS6wwAAAAAAgIRAEgQAAAAAACQEkiAAAAAAACAhkAQBAAAAAAAJgSQIAAAAAABICCRBAAAAAABAQiAJAgAAAAAAEgJJEAAAAAAAkBBIggAAAAAAgIRAEgQAAAAAACQEkiAAAAAAAMASwf8Hf+iz/AjB7sYAAAAASUVORK5CYII=", + "text/plain": [ + "
" ] - }, + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig, axes = plt.subplots(1, 2, figsize=(11, 4.8))\n", + "\n", + "radius_limits = [\n", + " min(true_radius_nm.min(), predicted_radius_nm.min()),\n", + " max(true_radius_nm.max(), predicted_radius_nm.max()),\n", + "]\n", + "ri_limits = [\n", + " min(true_refractive_index.min(), predicted_refractive_index.min()),\n", + " max(true_refractive_index.max(), predicted_refractive_index.max()),\n", + "]\n", + "\n", + "radius_scatter = axes[0].scatter(\n", + " true_radius_nm,\n", + " predicted_radius_nm,\n", + " c=true_refractive_index,\n", + " cmap=\"viridis\",\n", + " alpha=0.8,\n", + ")\n", + "axes[0].plot(radius_limits, radius_limits, \"k--\", linewidth=1)\n", + "axes[0].set_xlim(radius_limits)\n", + "axes[0].set_ylim(radius_limits)\n", + "axes[0].set_xlabel(\"True radius (nm)\")\n", + "axes[0].set_ylabel(\"Predicted radius (nm)\")\n", + "axes[0].set_title(\"Radius prediction\")\n", + "fig.colorbar(radius_scatter, ax=axes[0], label=\"True refractive index\")\n", + "\n", + "ri_scatter = axes[1].scatter(\n", + " true_refractive_index,\n", + " predicted_refractive_index,\n", + " c=true_radius_nm,\n", + " cmap=\"plasma\",\n", + " alpha=0.8,\n", + ")\n", + "axes[1].plot(ri_limits, ri_limits, \"k--\", linewidth=1)\n", + "axes[1].set_xlim(ri_limits)\n", + "axes[1].set_ylim(ri_limits)\n", + "axes[1].set_xlabel(\"True refractive index\")\n", + "axes[1].set_ylabel(\"Predicted refractive index\")\n", + "axes[1].set_title(\"Refractive-index prediction\")\n", + "fig.colorbar(ri_scatter, ax=axes[1], label=\"True radius (nm)\")\n", + "\n", + "plt.tight_layout()\n", + "plt.show()\n", + "\n", + "fig, axes = plt.subplots(1, 2, figsize=(11, 4))\n", + "axes[0].hist(radius_error_nm, bins=24, color=\"tab:blue\", alpha=0.85)\n", + "axes[0].axvline(0, color=\"k\", linewidth=1)\n", + "axes[0].set_xlabel(\"Radius error (nm)\")\n", + "axes[0].set_ylabel(\"Validation samples\")\n", + "axes[0].set_title(\"Radius residuals\")\n", + "\n", + "axes[1].hist(ri_error, bins=24, color=\"tab:green\", alpha=0.85)\n", + "axes[1].axvline(0, color=\"k\", linewidth=1)\n", + "axes[1].set_xlabel(\"Refractive-index error\")\n", + "axes[1].set_ylabel(\"Validation samples\")\n", + "axes[1].set_title(\"Refractive-index residuals\")\n", + "\n", + "plt.tight_layout()\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "id": "dtex203-21", + "metadata": {}, + "source": [ + "## 7. Optional experimental data\n", + "\n", + "Download the dataset from google drive." + ] + }, + { + "cell_type": "code", + "execution_count": 41, + "id": "5bd2dbb2", + "metadata": {}, + "outputs": [ { - "cell_type": "code", - "execution_count": 11, - "metadata": { - "execution": { - "iopub.execute_input": "2022-06-30T10:20:40.663553Z", - "iopub.status.busy": "2022-06-30T10:20:40.663553Z", - "iopub.status.idle": "2022-06-30T10:20:41.642550Z", - "shell.execute_reply": "2022-06-30T10:20:41.642077Z" - } - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "8/8 [==============================] - 0s 2ms/step\n" - ] - }, - { - "data": { - "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYoAAAEGCAYAAAB7DNKzAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjUuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8qNh9FAAAACXBIWXMAAAsTAAALEwEAmpwYAABdDUlEQVR4nO2deZwU1bn3f08PPUyP6IyIigwoRI2oyCKDIZlxibyIXgTHDfeYqKgxasxNUEwMIMkNCLkumJgE0ahxHRHHIcJVonGBxAjI4h5M1MAAiiCDMD3M0s/7R3X1VFefU3Wqu6q3Od/Ph5iprjp1ajvPOc9KzAyNRqPRaGSEct0BjUaj0eQ3WlBoNBqNxhEtKDQajUbjiBYUGo1Go3FECwqNRqPRONIj1x0Igj7lxAMrrTKQgH7D5QdEvwR2/gfgmOWQEFB5KBDZ37+OffYu0NmWur2kFDj4WOdjvfQxW9ej0WiKitWrV3/BzAfatxeloBhYGcKqq3t1baASgD8CKvoDY6YBQyclH3DXEKC5PLWhigjwo1X+dWxGJYBSwQ8EzHA5j5c+Zut6NBpNUUFEn4q2dw/VE3cCYKB5I7D4RmB9ffLvzZvEx8m2p0tFf2/bVfoi2p6t69FoNN2C7iEorLRHgZdmJm/LZAD3wphpQDiSvC0cMba74aWP0n6zsdqwC0qNRqNxoPsJCsBYWVjJZAD3wtBJwIR5QMUAAGT8d8K8VFWYCC99FO1rIltVaTQajYSitFEosb6+a4A2//vSTEM9I7Nl+MHQSem166WPSftuTP3dXFUFcX0ajabooGLM9VTdr4STjNkiIr2BWz7OTodyyYxKAKJnTMCMndnti0ajyWuIaDUzV9u3d0/VEwBEd+S6B9khHfvL+nrDljGjUts0NBpN/gsKItqHiB4movuJ6JJc98d3gh6Uvdpf1tcbNozmjXD0FNNoNN2GnAgKInqQiD4nonds208nog+J6CMimhrffA6Ahcw8GcBEpROUlCJhLC7dR9KJUNfg/Of/zs0MOhuDslcD+kszDRuGFZGnmEaj6TbkxEZBRCcB2A3gEWYeEt9WAuCfAMYC2ARgJYCLAJwFYCkzryWix5n5Yrf2q6uredWqeGDZn/8bWPWAtw6GI+reSJlw1xCxsbliAPCjd1K3m6yvD87w7sWmEWQ/NBpN1skrGwUzvwbAbiQ4AcBHzPxvZm4D8CQMIbEJgKlQ99bf9fXAuse9d7A9Ciy9Ra39TFYi6QTGBb0KUbVpaBWVRtNtyCcbRRUA6/R6U3zbIgDnEtHvACyWHUxEVxPRKiJatW3bNmOjSI2iSnSH86Dnx0CZjqE5aNWQqk2jUFRU2jCv0WRMPgkKIcy8h5m/x8zfZ+bHHPabz8zVzFx94IHxnFaZpqxwGvT8GCjTCfSTrkI2+jMYqto0CiFNiF71aDS+kE8Bd00ABlj+7h/fpgwRTQAw4YgjjjA2VPQX2wBAEOvhbTgNen4MlOkE+kmvCUgaDK3tmzjZFLzaG2T9MJ0E8sFm4STMvdwbjaabk08ripUAjiSiQURUCuBCAI1eGmDmxcx8dUVFhbFBNmOvviJ5xizzjHJSAfmVH2roJMNwPWOn8V+3wckpPYeJaGXjNLtOZ+Yt64dbAsZM8aJKUhXmsuvPlTecRpNn5GRFQURPADgFQB8i2gRgOjM/QETXA3gBQAmAB5n53YxOpDpjNwcK6+zTTQU0Zpr3Y/yYtdqvSbYysg+Gbqoy1Zm3rB8UigsJD214xf6cnFZPgHzVYxfmsnuz6kEk7q/9XHoFoulGFGcKD6t7rCpePvzEvhvjtS46jZWJ2zEiwZKpG66qi62T2ysg+S3+u8pAmI1UIV7diVXvubTvAsznHMSz1GhyjMw9Np9sFBmTYqPwgkqyvvX1htusNf0Hd3atJJyOl81al96iJqBkgkx1ZeM2u07X7qHavh94tQuprigd7T6Cc3mxfWg0RYBeUbhhXT04GcHdguRUZ62imanbzFhlNSRqo6QUKO0VF3wKBn7RNTrdH79n2ekGKLohujey+1ExANy8CST4jUEgnWhRU8DkVcBdwZBk5AQcB1I3byfVmbXIEO1mX1AxiNvdXiO9AWbL6ojRpYaS4GgEtrXhpdaGKkHVDRG5BFdfIT3XZ+gjbEa2XaMpdIpKUBDRBCKa39zc7E+DXgL23LKxtu1RP699QPYrZsEqUEr3AWLtth3YGCQrBoiOVjMCm22oeHCpYPVyemkmMOzi9Ao/udDQWYOavfMwqPUx1Oydh4aqH0vjSWa1nY8WTq593sKlmNV2fsb90GjykaKyUTDzYgCLq6urJ/vSoOpArJKN1T6gRnob/xWlO7cPyEHo/52Ezznz1ewemQiwdNRlzRuNlCw+r1Qa1jTh1kVvI9pueG017Yzi1kVvA+fUoE6g0lq131hM3QXc3KMe/Wg7NvMBmNMxCav3G+tbn7ozDWuaMPeFD7F5ZxT9KiOYMu4o1I2oynW3ujVFtaLwHZWBONLbezZWwJjRn3GHmiolCJWLUxyISnT2+nrDJVYEhVzTn3Q8d0NS3ELHczekHpOlNCFzX/gwISRMou2dmPvCh8L9p4w7CstKTkZt2zx8be9jqG2bh2UlJ2PKuKNcz9Wwpgk1s1/GoKnPo2b2y2hY4ymmtOgxhXbTzigYXUJb36fcUlQrCt9wNGDH/3ZzhzVxmnWreuUEUarVzVvKyQvMnOnb4yZMuNPRS6pl6TSUd7YmbevR2Wpst+6fpTQhm3eK1Yuy7ebs1uusV7pysbTZ3XES2voe5Y6iEhQZuceapKiKLEKCSoCR3wXOvFO9PTe1kWoN7XRrbTu1B6QnfFRsNw7uomXRrcJDUrZnw+UWQL/KCJoEQqFfpTwCvm5EleeBSw+C7ngV2prsUFSqp5QUHungNAhyp6Ej95LKIShPHT/wmj7ERHVGL9lvc+wAte1ZundTxh2FSLgkaVskXKKkSvLC5p1RTAwtx/LSG/HvnhdjeemNmBhargdBk/X1+HvZD5PujYmT0NYET1EJCl9wGwTNmbJqziGvFea8kos02qozesl+C0ovFXoNLSi9NHnHoO9dnLoRVZh1znGoqoyAAFRVRjDrnON8n+Vf3utNzA4vQP/QFwgR0D/0BWaHF+DyXm/6ep6MycU7FV/J98W2pHszMbQ8EKGt8YYOuLMjC+qyE45kPYWD3Rvk7mM2YNTb09X74Vd+IoEnFzNA1jAMh340rGnC8mfvw014MuE1dDcuRO3Z1+VGBZOlvE0tdwxGeXRL6vbIISi/5QPfz5cWQaWacUPy3W3FgXjjrFe1ai5L6IA7VVSys1KJszdOADMyqzfIhNByPNUyGdWrb1b3CsqkNoP9egBgwjxsivVBjAmbYn3wSOf/S/o7aWCxHV9XsgK1Z1+HC8rvx+F7H8MF5ffnVkhkqWZFucQ2I9ueE3JVkEqyku+LL7SQyAO0MdtOkpFXkpZCZsNo3uQ9w6kipiF0Ymg5ZocXoJza5DuLPrp08xPJrmfCPFxQfn+SEXh6/L9VlRGsGHqq4/F1E+ahbmoe5EVyuy9+rjayZJxPkE7fVTzNgliBZfveaDxRVCsKX4zZgMXI22wEn9l15E6RywHNyEyD58096p2FBACAk1YyDWuaEEvX1XTpLdLrufuYDVjRM9kwm6JPzveSqU73xY/VhnU11bYHCIWTfw9HgCNP898mkG7f3eqsBLUCy2enD01xCYpAEHkGOb3UAZUqNb0++tEXagfEP+CVjX/ArYvelnoauaYeEUWOx9sf9fZ0VFGXYfaO0gfwyKhPk1UFTvcjSCNpfIDmGZXYOuMI/PCnt4oD3JwGxkyFnH1Qje4wDDmR3khMPIZdbHjS+T3wptt3twE7KMHv5riga5/nFC0o0sHppXZcKqc/EEwZdxTOK/0bYl4eWXsUA96ai2h7J+Z0TErxNHKdsTl9/AI7TQR7Mer92ckfdGR/eRuLrjaqyPmNZYAmMPpiG2aFF2DkrmWpUb5pCX1F92DRoNrZZkTlmxOPDS8GM/Cm23e3ATvIIEiZu7aufa5GgMK0qGwUWUUWACeKeLaTRu2CupIVODO8AD06Y566eRAbK5DGWC3QnpyfaMtxN2OUUx+cPn5ZVHZ0R9cqpHmjkco8FBYkIAQANqrIHTpa+V4o5QESDNDl1Iabe9Sjsa02OcBNFngIIEaEkMArsCXSF+UqnVUZVIOyCWSi83cK7syFLUHX/3AnINuoiV5RuOFVSttnZDJEA4TTuV6aiR62tBcqfE5dqa8bY7VJ+Ym+s/Iw5xw6so8/0ltup7HT2Qb03NdhB1aePSvlAVpfL3Vv7kfbAaRG+dozx6785Etg8Y0IcapQbuFSzGm/IHmj7Lmp1FUPyiYQlM4/F7aELKVyKWgCtgUWlaDwPc14uh+pdQmtmrLb7VzpfBThCDYePyUl6tjEKfEdAPmgcMYdwt+kETnRL50Fi8O1WZPo/bh+nXPyPvMeStjMhp3GGuUrEj79Vs8Rrgg7OISp7Vfh4d0ndG10em4qg2qaNoGWpS4Dc1DBilkKgkxCOmHZ3z9VS6HbQAIWpkUlKHzzejLxQ0qrzsDczqW8tE8uHDRq4jWYdc5x0r0d00c4DQq231oih+BLlqwcEuocyQpLcm32QbzTogaypsJ4qmVyl3pGovJr4VLM6ZiU4pUlyr90CMQOAyEwGmO1yekk3NQiboNqmjaBspat7hlV003R4kZQ7coQfUOhMNC2O0lAtzzzA8z45XTvmWaLwQaisnrNAG2jcMIPKa2afM/tXCLbRyhsqHWiXzrqrutGVGHuCx96SnzXZQvYB/0q52HKWQJbgEWXPXb2yxjZviwlxqMNJSht22MYrkvLUws4OagtRIM4gJRYkv70haNdiAHc2n4VVu83FrNsNg2RoNzMfYw2U7YbKxKroDHKogrOaW6P36PE/Xw8in5LXk62rTjYBFoifYXR3Jv5gOJPJmi1zUT2B3pEut71tj0pHnnl1Iar2h7F2EXfBOAhI69M2C+abPwWUKS+r7hlg86QohQUH2z9CoOmPp950RO/DHcqmV9VsswCwEszwc2b8Bn6YFbr+VhVOlY8iNsMoHcfcwO+s/KwpIE3aXZt2b8l0hfL95yLprZvAVBLh715ZxRNSDaYf8n7YF9q7fqg2/ZY6nQ7CzezTRHCWJL2qOGJJTCyU8UA3POjWcK2RJlj53RMShF45opk//Jw0j34DH3QF9tS2jW2G5gpS57Ck+jX8wtsbumDu5+9EIBDNPr6erQsnYayli2IAQhZpJHZF+lqMEspSQI9n904G91hDHznzDfanlEpPKwfbUe0zZaR161/ThM/n43CgRFEKQILRaV6MmnvjPlT9CSbhjuXczWsaULNkj4Y+Nkd+FrrYxjdeg+ei9XKDbq2pfSot6fj9kHvoiSekKmECOeOjKfKthUSKo9uwUyan5S9082eYa5MrAbzKMpQSh3JO9rdQx1eZLNNe8ZVaSwJd3p+XqLMsctKTsafD5uKJu5KSTK1/SosKzkZ0yccm7SvqCxqjIEXO4Yl/l77/HzMpPlJyQBn0nysfX6+uFPx51ce3YIQGUIixkY+LbMvKSow27GuahSRTl5FT2/f58//HYzaJk1VrLnqSwhRlfvhNvHLpwBRJwJUCRaloLDiarB1IpuGO4dzWXX1QJfR2BxA3w1dgNHPndz18ks+sppP70vo+TuZ8czqJjSsaULL0mkpHlWmO6kVJ3uGaMA1vYzssKLqzowdsWdcJZkzmSVynkHYigPxwz3fQ82SPtLJgixz7KQrfoyVda/hxMginNg2z1BbCTLKrtpvLJ7uPAkxiyU/RMD5PV5PPI+r2h5NWQGZahIhgucXIqCJ+6C2bR4aY7UgQJxRVcWuJho8G64DnvuB84AqOm7Vg7mJAxkzzVidWmjjHpjTYXybCSGqcj9U8rv5YRT222CeRQN8Uaqe7KSd7z/bS3iJikqkq7fr6ftiGzqeu8F4oJKX+hAkD9zR9k78uH4dNpRuEdqZ7QO9WyEfs69mjEMryfXrK9c0uaoE60ZU4bQXn0F5NHmQpcT/2nJwHXlaQjW3mQ/AHe3nG/EjLqozWREileJEU8YdhVENa5NUQ4ARfGgatPuFxAJTtl32/KroC0wMLUdjrBYsuRYlu5po8BTFudhjFYTOAhJft0wHVhW1ry3GheN9SVKpqtyPoZOA/7wBrH5IHh+UqVE43TgH2RgUcNyEnaJfUQBpFj3JI08IkaAT6enNcqJuy3IrnczYzH0Eeyfvr1IToG5EFVZMPRUfzx6PFVNPRfkZMxFFz6R9WrgUd7RPUl7lyTOrcvLqy5IKg8Cooq56BkCGK0sH6kZUSVdO5mDUGukr/Fm2Xfb8iJC4pirZO63i/eJlEFcJDvTSDzuyWbGK27BNuPWkTvy09OnklZ/K/Vhfb7w7MiHhh7o5HQ9KpzEoyznUikpQmHEUsdYuz5q0i57kUTI7kaCT6enLoluFH1kUPRPLcjui9B4tXIpfd16gXMjHGu+QyKk0dBKmtl2ZlH7c1K8rr/JkKUAivZP1sYJUGHb1WVCV5MhlMCo/YyY6SsqSfuooKUP5GZJ3yUEVUk5tmBH+E5bRdWKVg4pdzcvsWCE40L6m6KSw88CaEA4VhjecaCBM0204JS25yv1wqmrpl7o5HQ9KpzEoy0GIRaV6YubFABb36n/UZAIy83rKo2jQKeOOwq2L3k5SP0ldOGMHoL89VTqVoIz34pZwPdAeT+dhQZTe425ciFPOuw53K9w704Zi9s/qJbVqv7Go3Vmbcky/yoi/qj3Jc7HO9n0tp2l33bSnKbEORkMnGR+a5Vp7OF2ruX3RZOHP+9NXoOhXxh92lYOK94vM1ZrIcDYQXQNgqPZWPQiraOikMDjWgR5k2RaL4a1PvsSooYLOO9WkB5LVXX6kElG5H9JvmoxJiB+k40HpNAZlOZVKUa0oTAb33Teh/nAVEpmkXwgKQaEfu8H1t6GLhauAOR2TcFvD22jorMGMPeca+3CncRwZGV7PCi1PeD+ZWL2VvBYSEtlQTFWPrB713cdsUFPtRb8UnzS6Q8lzxVSf+VpOUyUrrD3zqVeBOHSSNJo9xZxkX+m6eb+Ys/VI765tPfcFRlzmnL113eNIHtgJrRxKEhIAUEqdGPDWXPF1Oc3eTVQmY148Et3uRza+dZX+2sci2WrafIeymEqlqFYUJm83NWPg1OdRGQljxsRjHX3VpQYhlQCWbPiPSwr9NKw5CtOejeEm7ionOqdjkrE6eOM/ePwf/8Fr4UdRHkq2Y0SwF/ccuBjfPuX6lFVKJFySVq1omUpn886o0Mg9ZdxRGPXKT9QSvclmTkDyTFrwvKLoibkdk1CVaTyNHaessLd8nLw9E6OjSoJJk3RWuh2WdqM7DEEgU7NIDNnlvFfoCHEQp8aWKPdTNXGh2a9Mv7+Ag9UAuPdX9J6EwoZnl2iVF3DchJ2irJnd85Aj+ZDL7wZgLJkqysPY2dKeqoqS1ceuGGDMPJwEQVC1hT3UDm5Y04SbnlorberfPS9O8cYxIGDGTrVMrArUzH5ZGPVdVRnBiqmnig+aUQmxx4zRtwSi+2zFfFbmvktv6Qrwi/Q28lJ5eR4qwl+174D7O6bSH+s1yVBtL91+Sa6ZIU7MEgMQOuf+1HvnVpM+G/W5RWTbw9GO7L5EehsTkCz1S1YzuyhXFFZiAL5sMXTHpu581ac78NcPtuH16EbxQGo+MCcdaVCpjyUzroP4C0xZuA4zGt9Fc7RL6Dkhs2OYMzYV90/APbW3yIYiVfWYH6TMrVKmY5bo61Pul32W7MVlUHX270U/nKmta+gk4345CYp0Zr+ywVrWL6eVnYAQIP4WhKukuKtzxYDsDNAyoRDEee22LECclUB236Nfpq5SA+zj0INDwsRwRS8o7ETbO/HYG/8BA9hcKhlIQV2eFzK8DABeZiuSD3IzH4D2TsbOaJfQ++/6tfL+QZyKIsqleOfwGzDK8cgunAzVQJdKqSISRlk4JF65mbitDpx0zIka5jasg3Omwlv1eC+qCj+Mjk5CJZ3BdX09UuJQ3PolGeBJnjNY3O8sq0xSkE0G/vOG4Tmn0qfE97yxK22M6DmI0pCYmEGOQNwelV3jtKyP4RBKRbsVpTHbDfPVntMxKSmiNmkPNzdYVQOY13gMgZHKNFLbEffdIESGgXpq+1VJ7qm3tF+Fm947MmV/oXsr5Ibq2xe/m5TZdWe0Ha3tMdx1wXCpE0HL0mnpuyGqGO8ynb2rHu8lYt8Po6P0XRuQXqoG6YqO5P0SXbOTkADk/c529lkrssnAqgfVvtGk7xldsReiY9wM97F2Q60I+Guc9hKxreJcgG64orDSGKvF3bhP/KPb4KI6q/Q6y41v27ropziItyGGECKIxwN0pLq2yrhz0nDc9NRaNMZq0diWfAzZC/c4rBpkhmpTnWfF9HQyhYRVZVURCeOtmDgCXMkNUWUmmumszMvxqqoKP2bQ6RhbnVax0nebnftlv2Yne0PQxYzSxenarci+UaeB1X6MygTFXGUI3pOVh9+Am5b0webHPSQ4Fa2YFk02BJLIXqc4iSpqQREJh7C3I+Y485bp8V3LXfqUPlyk/wdq8A9chJ/j90mptGeHFwjjIOxUVUY8pRZ3cm8VZVd1wtzXLnx2Rtvlqj7VgdxtcM7Qe2Xl4TdgyOrbEMlAVSckU/23V2HjZmuRCkTFqoUmMq+sdJwIsoUXW4vo23UbWK2/e7TrWN+Tru/HuLcqGZwByAWZzF6n2MeiVD0dV1WBT2aPx6xzhqLEZq0uCRHClm2yqORpe871pzCMg4qqYU0Tpixcl1Rd7cdPr8OUp9fhB7HHhYnk7In67FiTxcliGOxGZif3VlEbDgVeE/EZIuEju9e+zTw9JnG0q9uuXjsItyiq6rKOF3WNW1YBv9Qcovt9zv2G8TUPhIRQnSqMepe80RRSj68ysf6ukmzQGstiwWny5oiTIBNlllDpI4psRUFEEwBMOOKIIwAYN7u9M3k50RljlJWW4KDyUmzeGcXq/cbiF6098IPY47Z4hG/h734UhnGY5d7e8K6wf52Qp+joF9oOAlBZHsbu1g60W5ZLBOCS0Ycm+iyLYbBfk2zVwPFjzx1Zhb9+sC3RhtMKw8xOW71rGZ4qrUc/+gKbuU9XjIctAnxB6aWYIRpU0nVXVJy9i9RtANAId1WdJ3Lhdulma/HToOx0v0XXrnLe+HGJuitt52PVfmM9uW9L1ann1KBuwrzkPhx5mhFDYheudvsD4BzbYhe29gwJdkpKjZWXgM07o5gYWh7/Vrq+ocWCLAdJuKwQYs2bcHhSrZ5JhiHfFnFvp6gEhZnCo7q6ejIgnynvaevE/5zd9dINmhrFExidsp8vuYEcPsovH39eephMJRaq6I+PZ4wHYHwMa5+fj6vaHkW/0Ha0Rvqi/GszAXR5uKlmQLW7t5o07YzimdVNSYF4srgJwFB7YX09Zpc+YGRQRarazByII+ESzBov8MaL18dIpD5v3tiVGdenQVZWPU9ESuoP1cE/C9chRMXWEpQ7qIlI/fXcD4yMr2aqE5H78fp6Y7/ONhCMrMhzw/Pxk13ArYuMFbaKsHCakddNFVz7oaO7nimFUhMEmrNx05am4vVkXlcaEfqX93oTN7cvSFE99w6XAhgvv3CXIM3NsQOSavUAQN2GF+HmmFCUAXfV1dW8atUq1wHNDAYz97NL8AWll2LGbbdn3B9ZHMLAqXJBYU8jDiA1GMnHoD+zj06rhSpL7MaUhetSVkPhEGHu+cNQ98o44UDVxH1wZsnvnF1oAbTcMViYnrwlcgjKb/nA03XJGDT1eTefHQCCaHWHe97QWZP0nP/ceS32b/8s0OsQElQwqBfcAuusWIP87hgkjBlhNt4f1W/S6fm6Rup7Caj0A7sAOfI0xFb/ESGOpezq+O4kue2GANvxLVyaSMppUlUZwYrWc2Beb/X83Vi1uTNFF1eUNgoTp4A062pBViDnNv59xmnFrUWH7FX3KiNh6XF219bN6JP6ofuY4dZMEe5kf7DOQuaeNwz7l3f1vzISNoTEiCrHBH1rpp3mmoerTJJaXLY9HWQJAisj4ZQiRkn9lNzzlqXTUp5zRVuqkAD8vQ4hHm01gZBuKnNJYCHFv8mb2+9T+iadEkCa7/FtDW8LXcKzmudNWAzqAaGQACRp99fXGwJ20WSL227MSAESzz9mzdxsZfPOqNJ1FZXqyU7diCrMaHw3EaRmxfoiyQrk9Ohs9RZpLVhazn2hj3AJfNNTa7F/eRghGNHjIqxqGgLw8VDbkjOADLduNghz+e6YcFGi+qC4Ad/qMkuElBXG5tgB6B8SZ8a9YPbLvuRtkkWTO+YGA6T3tiy6NeU5O2b4Ta/b6vilWnIqnJOOq7IIDwNwObUpfZNO6lQgOfAWsKlixkwzguGs2YBDLqnTXZBmN1CMY+iCjdWarICRlVh7Iv/YBRLtSr/KiFJOsaJeUQDAjInHKnn+SAvkqA66ksC66l3LpId82dKOkhJCZSScmMFaZ+lWhDMkaa0GyXYFRF5OdlxtNxKvmpWH35ASpPdlS3vKSmtB6aVC76iXYsPxVMtkTGw4Fi13DM5otScrgeoqgGRZamOpRaFEXl4xBv5RkpJKJz+RBYuK6mQvutqoL2F6CInegZJSY8C1YjUAJyLGXVD4Jq3PV4ZduZTkVWSvtyutv+uOk1YhrUmdWwGjpH2N9s3v2lp/fkXPG40szkkrUDFFbaMwua3hbTzxj43oZEYJES76xgD8ss5mRM00eZtDMr/Rrfc4Hmq1l9i9NQCHrK4SfS4ivTPKDyOyV1jtN5/Tgeh7zq+cZ3WCGWfNkj6uMRmm/nj5s/fhJnRlxn0pNhznl7zmbLPJBhL9/wy+Bg/tPiFl99t7PIjLSv6SlFOso6QMPc66Ny9cSEWYz/+plsnClV3CgCvDfC6AuteT3fDvhMcEiE62SjsE4OODb3EcC7wm03RMmtnzRvWVl6g/zZvgaIi23KuVjX/AkLd+nnAyAZDyDXXbpIANa5rwzOqmhNtmJzOeWd2E6sN6p1bCyiTVsGRmcDC+QCRc4uhhY52hS11aS1YAd9k+MGmtBsl2RUxPKVNoje18NaU+t2uyPbu310szUb1rAprg7N7XlZr8OlzwwpjEB7a89MaUuBKlPE5+u6dKvNiGd9YgIlB1jAml1tP2rNLMItaJSr+eYhdtRyEBJHsIOWQfsNKydBrKBUIiJTttGvEeIjWUKNPVxNBy/LT0aaBZniLdKYuBTFg4xSnh4mnGakzJtSK1P44qPtu9GvWvewGrkACUc6EVvepJOXAlUwOgrM5xRX/XJbBdrVRXsgIret6Ij8suwYqeN6Ku6X/FKgCnwiZ2vOR/MfsRX77/tPRp+SAtQ6C2mF36QKKGtQzzXpjGdfO+yeJK2GnpHlTdc0Hwm3mv7KpDWb9jOzclG1D9Jo3nDSR/L7Ja6iBn1SQAzyoVmYGfgYyN8iI14yWjD01SsU4MLccd4QXGJEhGRf+0AuFkhvV+lRHjWqqvQKrKLf53xQBpUJ60gBFgHGO/V1Kb5sbEe9KnnIQnK/oVhaM0t5OJAdBhRVI3NHmGbn3Rziv9G2bSM8CMreLgn+aN4mCY9ijQI2Kcw20VlEHxnLoRVcBzkpmlx3q/EezFzT3qUwLaEr8LbEfmbFBmGP4MfdDXQx98SQUvwboSM1V3UoM2H6CelsErGTxv63chyj6McAQYdrE4QM2KRw8huQNDH/T3oRypKJ6o+rDeiZX7T0ufRgRtkqOR+K42P97lRl9FX6ATIYQQw+aWPsD6WcL765qG/8w7k+M4VGvfiAoYWVOZmxM5cx9HBwNjInXofnSY6NeiFxQyLx7V+snK+kiFaFe7WunyXm/iNl6AHtGugCxxhKRkWRr9EjhnvrtqJdMB08d6v9Ya1lZkvu3m33OeTh20WrgUs9rPh9QClMW659b35PJeb2JZ+CmUlW1FC5eCOdkWas0GnAgCK1mR8hztcRnK3l5pPu+GNU0IESXUtEmR9KHtCJkTmQ0vGu1RCZg7wYwk9Vo6+bEWlF6Km9vvS3m+C0ovxQwP7XghSXjMuES+Y8UA47pfmol/lW0ELNfbI+6z2J++kApjpQwJTpNUt7HFPNZtgqDg3UQk1jIVvaDwVFTHhmd9pMKKJOnlvOsWoNmul/Wgq6zon5JIbO6SD1OzTWY6YKZhv2mJ9BUGzX3J+6RsI0BeCQ+IJzgci6m7ktN/zOmYhNX7jZX3O0s5/q3vycTQciOitsMY8HpRsk44xsDTnScl+bNX71oGLP5j0gfe8dwNWN5+FZravgXAQ1I4IK3nbV5Dp825pTFWi2V8MmaddZwhzKzvAXeiFT1R33kixoTWJj+X947EionO3bQyfPzVmPZsR0pp39dCNRi+psnfFZcIp0SJlvc/BMgdsxyEccqKZn19qs3RS+ZeEW4TBLvA8TDWFL2gUM13JMIxDYAfL66nma3N/GYbqJ2E2mmSQds1Q66Jx9xADWuasHzPufgf+h16UvL925daMTG0PGmgVFndGQK/LUltFQmXYJaTwM9GLWQkvyc396hPtedYCJFh4J5u2XZ76Z9SPvAena24CU9iIb6V2BZt78SP69cBcBEWaQhIWUqTEqIuj7u7xOrEMaG1qG2bl7Tda34s04FhwuKTk1PYR9uDUc/ZcXpXvMQ6qHzTmdRRd4CbN4llmLVPVoHhIXq+6I3ZQJdh1C0i2I4n+0Y6SD7clLTo4Yhh8HIw6jkJtV9EzxfGJcxpv0C9rx6yl8594UMsbPsW9iBVAJRSR1IG3PNK/4ZldJ2r0TWtuIcsRShb3weZ8dqKVf12XunfUIGvXPcz6WTu8sGXkUZ2WNk7HWPuuscK6kTTT/9fZZd4MqIDxjMuL02duyplTc0Up3fFy4ROJYbJx4wKJg1rmrCZU2N5ADhXLbS9J8zi+N+iX1Gkg6lvFrnPmfpa3OWDq6VgFtPCpXi686TEUv5z6oO+E1xiFiD/0Jt2RrEn1IFoj9KEse5L9MKM9u9g8d4TAtH/mn2pxG7h72YGXKGNxmFmpVrjO4mgk98h2Q4mrVNuwfygqyojmEnPgCTzDtmH77qqTSM7rJItz6FMLyDIT+Zxptywpkka7+Db5MwJ2bviJcq8bbcRkOhUVjUA29ncFz7EyHZB6WP0RMSpaiGQ9J78Z9d7n4p27RYrCi9YoyitmB9B/9AXCPnlammZxZj1D6a2X4XpHVegtm0evrb3MXyz9R6lj0ymvqkrWYHZ4QU4ILQbRIZRtSwuMFQN+l4x25W5V4Yq+uPj2eMxY59nUgOsMpxZ5QJrNLsoGtuKacg2gyxlGQEYwKsYIW3HdeB0WgEKXGeVapeMmYYoegqvp4RIrHZTfJ7mdyfDi/OJMH9TJnipYdHZ5l5WNYBcUpt3RoWlj6e2Xelu+/jRO2g4613U7J2HXfsdPki0W94LCiL6GhE9QEQLs3E+ma42k4/ASsqL3FkD/OgdnBhZhNq2eSlJu1Q/ENmH/pOSp6QFkFQM+ulg9kU4aFpVIFn0SgoSq1pscawWc8LXoSVyCADCDu6F7bFeSROBxlgtNu+MomFNE7ZCLEwJwAXh1w0DsoC0hbwktqSuZIW7am/oJExtuzJ5IIpfT4wZ/UNijzbh87QJq7XPz5cGpXp1PhGmysgEYYGm+ZBbtSVlVU0yKRwliY8x34fGWG1iklnbNg+rnJw94sgmx1YCVT0R0YMAzgTwOTMPsWw/HcA9AEoALGDm2bI2mPnfAK7MlqCQzdSkumcPg5qTwTkT7yxAbrTv95z44+0X2h6YcbCrL6W4dRdwa+nTOBhfGEVo9pyPVUv6YEpnE+qy5JWUDZLVYuMBGKmwJ0jSN1SWhzHl6XU4A+enxirE6dHZil/ttwgv7D4p7fciBQf9eN2P3nF9J1btNxa1guI5/SojQE/F5ykw5t7M92FHqE1Y5lcpBxe6Jnkp5QKevxR1I5xTk7u6wQu8C5+SxH4IsRuUAe8ZAxyM4FPG1aQ9fqjUZgnaRvEQgN8AeMTcQEQlAH4LYCyATQBWElEjDKExy3b8Fcz8ecB9TEKmq/2cDhRGbW5FH3xzqlrx89sXvys1OJvuoWn5zccR6fBbXhR7PLWqejylSVdfTkXDmuuTX+KdUUxZuA7/CJ+Nn/PvUwO6fPZKChK3AUY2AWht70R7jNEII1bhnvB9wrxz5dGtmHXOcRm9F0lkuIpznNCUKHqZCYSVucq1B2Oa9d9V2LwzmpJbqz+ZqcmPdfTSU3WDt+47JyQISBQmB0GqsEzHduYi5IH0xg8V+0+ggoKZXyOigbbNJwD4KL5SABE9CeAsZp4FY/WRFkR0NYCrAeDQQw9Ntxnph7Dx+Cno+/b0pAcV5VL8qv381IpRgofTsKYp2e3Pgvmg0jLWulB+xsyUZGsdJWUoPyN7dgDRjKW9k/FE52jsCXUkYiNay/sa/crDHEgiVAYY2UrvpqfWJtppjNXiZq4XG8Er+qf9XgiFWIarOGd3c8WZsmIwptuM2H59F5a9gcv4Lym5tdxSk3txg7fuKw1ItEet+zX5cRHy6b4nbqUFABdBEZ/9/4WZv+357HKqAFjf1E0AvuHQhwMA/A+AEUR0a1ygpMDM8wHMB4zssV46ZH/h7DWip4w7CqNGnA4M3D/xEWxFH/yq/fykpbKTN4qTe1+ICIMUVyWeGTrJeMiWj7dHNuo2x3HyZAGSa25URSJYMVQeeOdXf/yanasOMKIP2CooAId0GWkOMDIhVjXqBoyyTXi8nsdxQFKZKUuEVWt5X1RFIkrPRnR91/d8PEVIJHBYMXlxg7dvM99fAhIlih3TcWSCi5BP9912q90BuAgKZu4kohgRVTBzs+sZA4CZtwO4Nqj2b2t4O6WAib1GdALLR/BNSanFpp1R4aDvtLwzo2EDy/0j+Hj9HDBluHmy2AnaBTKdzJ9OZBJns395OGmFac5Op5bWox+2ZzzAyITYTe8diRUT5qU9kPny3kiC28rPmKk8URBd3yFwsBc4rJi8pPmR7csw0okb9yMgl2yHoMBM3m3rKjFVSW2g4vW0G8Dbcc+jeeY/heNkNAGwVsjoH9+WMUQ0gYjmNzerybSGNU1JQsJEJcDHyetE5HGh6qWSjeCiwLxDbDgZyawFVJaX3oiJoeWBues69cftfju5WzpmBXVh+oRjES5Jnv4upRPx5lmvKQU1uvXVMR7BQ/CkvX1f3hsfAiGFs31ZtluQ44pJyTXYYV+TkbuWYVTDSWCPGXuVXXod7ls677YVMyi5betHq0W/qwiKRQB+DuA1AKst/9JlJYAjiWgQEZUCuBBAYwbtJWDmxcx8dUVFhdL+oqA6E7dZoUolOOuDUtlf9dyZkulLpYrsOpJiUuK1kGeHF+Ck1r8Gl3bboT+y7W4Do5cBxk7diCrMPW9Ykjvq3POGpb2qs/dVRibC2Nf3Jk1hZSK6jjkdk1LiPAAysho4tO8l6l9WOc98p6voC5CHOKuVjX/AqIaT8Hr0bLxeeiNG7lrmLHwl9y3oLBKuxmxmfjg+oH89vulDZhZbZW0Q0RMATgHQh4g2AZjOzA8Q0fUAXoDh6fQgM7+bVu8zxOkmVkTEJUlN7EY92cdpzuxERsCWtg6hgTvomXXgqUniyJbpPy19GuVIje34QexxjF1UAyCYvD5eMwm72SAyySMG+Ou8oOLimJFbLbL33qgg0qsvKzkZlx0/0CjQ41Gt5uVZmPsOsqifHeOsZOdfX29UnIsnjuxPxoQJ7YZruTVlvdv71a8ygpG7liW5BbsmzfSAq6AgolMAPAzgExi+XwOI6HJmfs3tWGa+SLJ9CYAlXjqqAhFNADDhiCOOUNrfydq/p60DDS5ZK60v1+G3LknJvAkYSdVE+wPysqdBBcKZZJp6XRWZB9nBEl1yP9qOaJvcISBT/bjXWBWVgTEITzUpDtX6nAZrAnyxQ2XrvVFBJqRHjTgdwDWBnluU4ietOKuXZiaXJUWXm3DtzloMnPp8krOtk93h7mM2YMjqBYjEhVV/+gJ3hBfgnWMGAsjcQURF9fS/AE5j5pOZ+SQA4wDclfGZA8Cr6slJHdTeyc5LaluE5Hh6XbibSHiYpJXozgcyUZl4QXZ9JDEsmjmDRIOeSA005el1GDHzReV0DV7vd7o2iEDSSLhU65P1qaoy4jkZpgzl9ybN6npKWNque2UcVvzXF75dnwqyKGapfSTDmi2q9tNR/7o3ISRMItQWL3+aOSpxFGFmTvSMmf9JRM56mQLBfLHsroomZpoFYf1qW4TkHaUPAG1IiSx1KoFq9iFrM1LLOYHMgvu8nCulXUFglrWYj2jQE8ZixDihulP18vByv9OJlvfbsyqBS62BTCP7VVB6bwJKoS1rO7roekx9cg1W7Tc2sHfYikzFN6djEu4ofSB5hZBmzRZpFljzd9HqMeB0OCqCYjURLQDwaPzvSwCs8uXsPuNV9QSYRXE+lKZZEH30p/WahnJBXv5bwvVo3JtcLyFoNVK65EJAJYgPGC1Lp6GsZWuiSE1jrFZ6z1T04L7WCkHywNi0M4oSoqQZnSxeJpAaJgrBVub5gxT+ru9NUOVn19cDz14LcPK9jWAvpsRVNRkJZAe1nhXZe7g4Vot554zw5HY8p/0C3MypVf3MCZMM4eox4HQ4KoLiWgA/ABCfFuB1APf5cnafYebFABZXV1dP9nKcbDbGDOFHLysE34+2o6pSLWCo0GhY04S1z8/HVW2Pol9ou5ECRCGKWmpXGDoJ5UMnJf0uK4cKqEWPAvI4lnQxj5euEmwlTKt3TUATUvMVOQk6JduLwkCQU+FvEsTMdn29kV2AxcZ6U1WTtkD2sApytNMMHe9JGD68+wTsCLWlVG0U5bsykU4+BTEWHSVl+OWec/GwD9+DSmT2OmYeDODOtM5QAMhmYz+SqaQkycCikb5YcUuwkcV2shU4t/zZ+zCT5qM8ZMx+yqNbjI8XyCiHjurgphI9aqKSUsULslXC2ufno47+kDTAzC59ACxQQcpsCMqqqixV68uYAGa2LUunodyejt6CVVWTlgeWWyEhy0Tg7mNuwHdWHpbyPrQoOL/Y6VcZQePO2pT8VvZsUebfThMpe6LBlkhfTNtzLha2nQAg8+/B0ZjNzJ0APiSi9JMnFQhmwInVMCb7uH/deUHmFeN8IJuBczfhyRT3vx6drY5p1v30u7cboisj4ZSANTt+xYbIBp+r2h4Vlga9JZxsvHVSQSrfoyxV68uYTFJo2zCdAspaZPHCqaqatDywpKugjSkOBKPeno5HRn2KSpv7/Jct7Z6/PZlzwCWjD01yuLjrguH4RMVgb4mxGMv3YWHbt5J+zuR7UFE97Q/gXSJ6E8AecyMzeyidXpjIVFIN7TWIMacsGYOqGCcjI324ok4WMAbKfj29u//57Xcvci92i2Pxw8dfqm6Q1F/wooL0dI+yUK0vY9JNoW3DutLaXCquGtjBoUQ9DCADm6BsFUQlwpXGqH/di316zsPOaHIMlFfVV5B2pc07oynp1ud0TMJiQYp4FVQExc/TajkHpGPMdkL2IOe+8KFwyejm4eQ3aQ/EHj1T+lVGsLlFUuLTpxw66WAVHDWSug9ugZMyrEKosjyMcIjQbilmHgmXGHYagdcKRfbHitIbgbJNRo2GkmlIZFa1kU+xCb4RF2iJe/h4FP2WvOxpELROgkQJE1u4FL+ga7F6v2+DMh1kZWo9u5Awad6Eza3+TIKCsitd3utN3Nzedc/MYL7e4VIY9VIM7KrrUGS/3qL2VGwUf4jbKPKedI3ZTnp+2YPMRaCcnbQHGY+eKVPGHYW7n70QM3l+0sfaUVJmZKKVkA2XTeu5pjy9LmkwB1wCJyWrKrvd4MuWdoRLCJWRMJqj7Yl3pLxkZuoAU1IK7P0KiO4w/nYRwtm8R9kkUzfh6l3L8FRp12zYWkd+Mx+Au3EhauuuxSw/BlnZKuilmVJ7S7+yPBXw6+vRsnQapndsSalvUk5tuDn8FMyiWqJn1GO/Aw8TNdvtbRTp6PlFgVuPjPoUda+MCybISELagXMePVPqRlSh9uzrMCd8nVEGE4SWyCHocda9vuXQyZS6EVXoVZY675EGTjoEsMnqZ+zTs0fChgUANUv64Id7voetOBBs2g1KewExW1oWh5K5snsEwP+gPQuBBAVakKlFb1/8Lmpmv4wf/vRWbJ1xhDiB3vp6zC59ICkX2Pklr2FOxyR8be9juKD8ftSefV3m75EleK9l6TTM2HMuBrU+hpq984wSxQ72lmwFrXoi7h1WHt0iLdJqrdEujAkhEsoEYofIYeM4eg3ACAAFY6Oorq7mVavUQj1kKouqykhiQHDFrsoBjBcqC8bGtLye7hoimSkNMIxhBcogSep3AvDx7PHJGx3uwaDP7nBsR5Z6ZdY5x6HuuWMhrHAGMhK5KdiGHNtXGBzd3olM21dB9iyArgR6KbU3zO9F8myauA9W1r3mTx8F32wLlyZsHon7YXN/tj4vPz0O02nLfswyuk6oCk3C8o2LntGWh2/C3i0bUuRMUdko0sEXg2tQQUZBUSiulh7xpIpzWFW5tePoRODkHqpoG8rESUFF5RNYUKAFp7gX1wR6DqktVPq3svEPGPDWXBzM29BJIZQgBqoYkCyUXcqxJu7HVIEDQVzY1zVvMp73xdOMGIo0kRaZ2vhnaYJD0TFlPbdCupQAUr5x1dgkQCHXEzO/CiMhYDj+/1cCeEup9SzjtR4FkFlNgQQBh8/LSNs9tlBcLT3iSR0gM8JX9Hdtx3Fy4eQe6uavb21H1r4LKu622cgC65RHTZZAj83vRfJsZDnCrKxs/AOGrL4NfbENREAPxIyx0572WyHPkvB+uOTcsqOi4hM9s7Gdr2LIWz+Xnkd0jCz1BzOwFQemfOPCZ8QcE7XhKiiIaDKAhQD+EN9UBaDB7bhc4DUpIOBTgjyHQScIzJfvpqfWSgcF1xc0w3oA+Ygnm4jDgO7WjuPkwkkIu0wozGcmU9moTF5UhIAvkyMXRPfQjD2QJdD7DPHtGcRiDHhrbkpyvARWoeySmBKQ3A9FYQ+oT+REz+zmHvUpmWWt5xEdM6djkjC+awpfjzfOejXlGxc9o45d2z5NvWg11dMPAJwA4B8AwMwbiOggheMKAi++zFI9YhZVOSL9sh3zhfQ9MZ1i/7KRbFCGsruhi7+/UzuunkqyeAcHtZTbc1WdvKio30T9JwDfHnyga/tekKXVl7m7zmo/H/cAGcViHMTbnNUvprAWfLPW4D3zftvf5+Wtm8TNWyYB5jHW52CNafj8uQOBkl8lrkf0zNzSlouOaYzVone4FDeHn0JZdCs2xw7AgtJLUTv+aum7bH9GdOuuHaL9VATFXmZuo7ivFRH1gNhaV7CoDC7Oul9/goxUUClQYyavs+K3DlqE7B6t+nQH/vrBtvzLgZVmAFvagVIOE4q5S1Kfa2JwMXNrlcyELB7DRMXdtm5EFVZ9uiOpDDADeGZ1E6oP6x3YszHb/XF9DGhHSsBqUpEdL8/G4iAQoxBCEGpPDMyVhCDlxZz2C7B47wmJVBlAao6vzT0PQJVDPJFI4NuN932xLck2JXpmW9AHVaK6LfHzyJ7z8PFXo3yE4f7aH/AtAFjF62kOgJ0AvgPgBgDXAXiPmX/mUx98x4vXkypevKOCnFU7eZMAxssiEyRC7x8fkd0je+4avz1s8gaVaHfJPvbn6uoZ5IDK++eLt1+a+Op1JfBeYkZKDAEAz56Ionvk9lxExywvvVGYG87qgWR/ZncfswGj3p7u6Ekpes6A9wmMtZ2mB69va/v84572fVRWFFMBXAngbRilo5YAWKBwXFGhagAMrB5BHCdPBXMmJEubnqsSqxMEqQTMUo9Fg2q0u2SmbH+uaZXWjKOyQs5lWVNfU1cIbAZEQAdCKOGY3OtJAdG9aIzVAu3ALWFjNUQKlQZVqt+lPrNTgYH7O048ZKo9L2OP/Rgq6VEq2k+lZnYMwP3xf3mN3yk8rFSWh4X1rSvLk1NEBO16KFty2mdj+VJi1T4DM1MJ3LoL8KNEY9ZwWy1k6CJtf65pldb0QK5Th/iWukJyP3qAgdublWbCMmT3qDFWi8a9tcbq60enuh6zmb2nvwHgWTUqG3tmNL4rvdcqqmxArRRqwZCO15N622rbg56pqXj2ZDMi2orIg0w0My6nNtxa+nSgffEVFZfIDF2k7c/sc5IYlinkS/R/XkYW21EpqRqgx6GTiy8g/qZFx9yNC9FRUpa8YwDOLrIxZme0XeoyrzouZSJwuxXN0dTVhGh7NmZqKrOxXBSxEakUqlrFGVYPFhnq8hWV1YIPdRiSntn6PamGb6CrwluGJUazVREvbVRVeQF6HHYZ39ehUzBTFH3TovtaO+469CgZlpGzi4rdSab1MPuTSUEwZUFBROXM3KK6f7GhKgCKNcmbKikC6i7xAKoSPJU3qKwW/B6w7C6iFEopA5pp9H9eVMSToarK8ymtuR179uDdrR0p2YNl37T4vqafIl7V9uDklyRbOagWBHMVFET0LRjG614ADiWiYQCuYebr3I4tJtwEgPXFqoiEURYOYWdLe6r091AHIt9Iy5vLhwE017EZSquFDAcs8TVaBpcZleIDsxD9n5N7L7mu2M5NOHG2LWW5z3U6VLMHZ+sdlNkefly/DkCXsDC1G6I6FEmuxxbsKyDu7BBGK6q4x/4DwHkAGpl5RHzbO8w8RPE6s04Q7rFA6kfz7cEH4q8fbEPTzqiaC2gOkwdmSkYujRkIx2wksHMl4OemdI05SOSY03svud5NsT6obZsXaD9y6ToswsklPhIuwbkjqxLjkMh9t4VL8e7IX2LUxGtcz0VEq5m52r5dyZjNzPYn5m4mL0LqRnSVS50y7ig8s7op8ULZH6Sw7KCH8P98I6OyphmkC/GznGraBJwbS+kafSwx6mu/gkJwvdbI6SD7kUvXYRFO9s1oeycee+M/iXFI5jwy6l/3ZtQHFRvFxrj6iYkoDOCHAN7P6KwBkal7rJdltopbWcqLlaPkgX6Qq48nbz7aAMuQKl1jQLr4dPsVuErKcr2xnZsS0dtm2VOn/gnxsKrNteuwHTc7gnWSGpRbtcqK4loY+Z6qADQBGA4jOjvvyMQ91msmVhVPAfPFMpO9bYqJszsGlTzQT7KRSC6fzptNVK+xobMGNXvnJRfXyUG/KsvD6WUt9srQSWg45QUc2fY4atvmJQkJp/6l4DHja765Dpuu0yXCcPNkZAkXrSlG0ilYpSIojmLmS5j5YGY+iJkvBXC0UusFhJdldsOaJse8Y0ByUjHzoxJldyyUOhC5+njy7aMNApVr9DqR8aOCnahfBMO4mw2VlHnNItdUT++AR5VvruKQnKgbUYX/nTRM+DysOI0xaZclgJrq6V4AxytsK2i8qDjmvvChY76lKstSvGb2y4mPygz/NxO9hQrI6ylXfvf56O/vm9rFUgDntF5GUrqHd58gbNNLxL9faWSs917ksGHHb3WgTL1bQuRt4E5D5ZuPrsOib+Hbgw/EM6ubksaYUg5hZvkziES34jP0waw952PVkj5oaXs37awRUkFBRN8E8C0ABxLRf1t+2g+APFyxQPGil3T6ID6xJd2z79sYq0VjW62RoG9GcAn6giBXH08+fbS+5fKyeVKVR7dgRvgPmHHxscJqaV4nMn6lkTHvvcwTyIqf6sCGNU3S88WYvV2HD8GQ+YLoW6g+rHdKgN+LuC7ZruHw7FQEvNOKohRG7EQPAPtatu+C4S5bVHgJlJMJlSrBh5JvhrHuht9GV98GYY+5ofyYyGQy43c71k91oCmMZXj+dhRieXIeq5MBIuFh1WS4oXI/pTYKZn6VmW8HMJqZb7f8u5OZNyj1oIDwopf0ojfvDjr2fCUTnawM3wZhj+oQL++RinHcqw3DaTDxW4fv5FGY1rfj4t4cxHuSa1TfR9X7qWKjeIiIUlSTzFxAqT/VUFVxeNGb56OOvWhwcXkMIpOvbytEj+oQL++RShYBr+oz1azFfuA0yKV9Pgf35qAzPucC2XtaGQljn549PI9FKoLiJ5b/XwbgXAAdqh0uVrzozfNJx140KCSNC0IF41surzHTgIbrgJgliVso7OgB59dEJp2BMZsTHifVbhDny0WsThCqLnsaoXAJob0zOT/VjInHpnUelXoUq22bVhDRm57PpNH4iYKOPwj7kK8Dpt0vXsFPXhUnoZLuwOjUpp8DX7YTa2bbjhhEcTN7mzuj7QiHCPuXh8U55zyikhSwt+XPEICRAPwv+KDReEFBxx/UgOPLCvGlmUCnLf9aZ1tG2WBV8Xtg9DrwuQkVJ2EcxEw824IpCFWXqM32GKO8tAfWTDst7b6aqKieVsNwnyYYKqePYZRGzTuCrHCnyTMUdPx5bR/KIJ2LymDptI/fA2MQMR4iYax6rFdhku33JJteaX6pz1RUT4N8OVMWYObFABZXV1dPznVfNAGjmL48b+1Dafr2Ow6WJSuAl2aCmzdhFB+Ake2T0ITalAHV74ExWzEeKsemq9bJ5nsShKoraPWZ1D2WiM5x+ufL2TWadAk4o2vgpJkNVjZYrn1+fiKfEYFRFa9NPjG0PLGPmWLDb/WNbDBiIMX1NpOZr8qxeZFt2IUgXOaDdsN3WlFMcPiNASzypQcaTboEmNE1gQ+FpqRFiQDPbcsGy6vaHgVCyb+VUxtu7lGPxrbaxLFOM24gvVWGU3ZT+4xe6rZZHnY9j8qsOW+yDTsQhKoraPWZa+GiQiSowkWaboYPBYv8Lv4jS6Xx77JLEBJkYoox4Wt7HwPQlTlA5l+/tyPmuZ+mEGzaGUUJkTCBn3nuFVNPRcOaJkxZuC7JbRMAwiHC3POHuZ7L7V7mW9GhTMhFtHjahYuIqIKI7iSiVfF//0tE2utJU/z4UGjKF1XI+nqj4tuMSiyj63Be6d+Sfo6ES9Aa6Ss8dDMfkNhnyrijpDPrnVHvGWGtEc0ApEIC6JrR142owj6lqYqM9hjjx/XrHKOhVbInFEsmhHyLFlfxenoQwDsAzCnUZQD+CEDbKTTFjQ+FpjJWhQiSB84OL0Cv0h5JmWbLS2amrH6i6Im5HZOSshmbs/9M+w+oFe8ysaqHzNrOdjqZXQ3PbkbndFUw2Zi9Z1oYLZfR4iqC4nBmPtfy9+1EtDag/hQlhZxwrFvjQ9bRjL1RBKuaHp2tmFHxDGbcdrtla6rNIzJmGu6xqchkrrFl4RC+bEkdwJ36qSrsKH5ea5syYeXHYOjVgymIALhMz5FvthaVwkVRIkqUliKiGgD5YxnKc/JtCanxgA91qjNWhXhZ1SjUJpepb6ZPONZzP1WFHQOu6iEr2R4Ms+Ep5fUc+VbZUWVF8X0AD8ftEgRgB4DvBtmpfMGPlUC+LSE1HvChTnXG3igB1FJwmnF76adbLWcTe/p9s80f168T2jWyPRhmY/bu9RzZjhZ3QyXgbi2AYUS0X/zvXUF3Kh/wazmab0tIjUd8cMHNKJhLMbDQD7z20y4EK8vD2N3agfZYciI60eBmHpsPg2E2cj15PUe+ZRVQyfX0QxjG668A3E9ExwOYyswvBt25XOK2VFR9gLpwUTB0G7uPD6uaILELFy/PJV8Gw2zM3tM5Rz5lFXCNoyCidcw8jIjGAbgWwG0A/sTMeVsz2484ikFTn5fWB46ES5T9zf32o9dkeE99CKDLFd1GOOaAfPN6yhWyOAoVG4WZ+/i/ADzCzO8S+ZgPOU+RrQRKiDzZHPJl1lRMpG33Uahhka9kwzOnO5ON2Xs+rRC8opQ9loheBDAIwK1EtC+AWLDdyj2ypaLMcOdkcyjkFyQfSdvu47FOdT6hnSIKn0JYUchQcY+9EsBUAKOYuQVAKYDvBdqrPEDmRmj34DDRNofskbbroA8BdLlCO0UUNoXuJq/i9RQjooEALo3Xzl7OzM8G3rM4RFQHYDyA/QA8kE0jumwlkA+eGt2ZtI2PAbiaZgvtFFHY5MWKMAP7nEqup/tgGLHfhpHK4xoi+q1K40T0IBF9TkTv2LafTkQfEtFHRDTVqQ1mbmDmyfE+XKByXj9pWNOEmtkvY9DU51Ez+2UAcM03owkWlZw/QnwIoMsVxZLDqLuS8xWhaZ9r3giAu+xz6+uVDlfxevoAwNEc35GIQgDeY+bBro0TnQRgNwwj+JD4thIA/wQwFsAmACsBXASgBMAsWxNXMPPn8eP+F8BjzPyW23n9yh6rPZaKEO31pMkBOc9qe9cQyWp6gBHFHycTr6ePABwK4NP43wMAbFDpGzO/FldbWTkBwEfM/O94x54EcBYzzwJwpr2NuIfVbABLnYQEEV0N4GoAOPTQQ1W650peLBc1/pKNGhYBoZ0iCpecR1pnaJ+TCgoiWgwjTcu+AN4nojfjf38DwJseu2mlCoBVtG2KtynjBgD/D0AFER3BzL8X7cTM8wHMB4wVRQb9S+B5uVjAs1WNpruQi5VZzt3kM7TPOa0ofu3wW9aqHTHzPADzsnU+K54MiAXso6/RdBdyGY+S0xVhhqlgpMZsZn5V9A9AJzIzKjfBUF+Z9I9vyxgimkBE85ubm/1ozpsB0YciNxqNJlgKoaZ2IGRYY17FRgEiGgHgYgDnA/gYwDPp9heG8fpIIhoEQ0BcGG87Y5h5MYDF1dXVk/1oz9NysYB99DWa7kLOvY9ySQb2OScbxddheCNdBOALAE/B8JL6tmrjRPQEgFMA9CGiTQCmM/MDRHQ9gBdgeDo9yMzvptX7LKC8XAzYR197vGg0maPjUdLDKY7iAwCnAjiTmWuZ+V4YaidlmPkiZj6EmcPM3J+ZH4hvX8LMX2fmw5n5f9LvfjJ+q548EaCPfqFHdWo0+YKOR0kPJ0FxDoAtAP5KRPcT0Rh0JQjMS5h5MTNfXVFRkf2TZ6gDdKLb6lU1Gp9JO1izmyNVPTFzA4AGItoHwFkAbgJwEBH9DsCzxV6PIi0C8tHv1npVjcZndDyKd1xTeDDzHmZ+nJknwPBQWgPglsB7pkmQb/VzNRpN90Ile2wCZv6Smecz85igOpQJObVRBIjWq2o0mlziSVDkOzm1UQSI1qtqNJpcohRHock9Wq+q0WhyhRYUGo1GY0PHLSVTVIKCiCYAmHDEEUfkuisajaZA0fXJU9E2Co1Go7Gg45ZSKSpBodFoNJmi45ZSKSrVk0aj0WSKaj6o7mTH0CsKjUajsfDtwQem5Cqyxy11t/xrRSUoijXgTqPRZIeGNU14ZnVTUmU2AnDuyGT39O5mxygqQaGN2RqNJhNEAoAB/PWDbUnbupsdo6gEhUaj0WSCqgDobvnXtKDQaDSaOKoCoLvlX9OCQqMJkIY1TaiZ/TIGTX0eNbNfLlpjZ7GgKgC6W/417R6r0QSEjvAtPMznouL22p3yrxEzu+9VIFhSeEzesGFDrruj6ebUzH5Z6I9fVRnBiqmn5qBHwdCd4gmKHSJazczV9u1FpXrSXk+afKI7eMZ0t3iC7kpRCQqNJp/oDp4x3S2eoLuibRQaTUBMGXdUko0CEBtGC1l1U0yrpkJ+DkGjBYVGExAqhtFCN3ir5kXKdwr9OQSNFhQaTYC4ecY4qW7ycYCyz7q/PfhAPLO6yXXVlO8U2nPINtpGodHkkEJS3YgM18+sbsK5I6sKPp6gkJ5DLtArCo0mhxSS6kY26/7rB9sK3t3Xj+dQzDaOolpR6OyxmkKjkFJBFOqsWyU6PtPnUOxuwkUlKHQchabQKKRUEIXo7qs6gGf6HIrdTVirnjSaHFMoqSBU3X3zCS9G6kyeQ6GutlQpqhWFRqMJjkJa/ZhkawAvxNWWF/SKQqPRKFMoqx+TbDkLFOJqywt6RaHRaIqWbDkLFOJqywt6RaEpKorZRVHjHS9pw/04V7G+a1pQaIoGnYZBI6KYB/BsoVVPmqKh2F0UNZpcoQWFpmgodhdFjSZXaEGhKRqK3UVRo8kVRWWjsJRCTfmtvb0dmzZtQmtra/Y7pvGNsrIy9O/fH+FwOOW3YndR1GhyRVHVzDaprq7mVatWJW37+OOPse++++KAAw4AEeWoZ5pMYGZs374dX331FQYNGiTcR3s9aTTpI6uZXVQrCidaW1sxcOBALSQKGCLCAQccgG3btkn30R4uGbC+HnhpJtC8CajoD4yZBgydlOteafKAbiMoAGghUQToZxgQ6+uBxTcC7XHDf/NG429ACwuNNmZrNBoYK4l2m3dYe9TYrun2aEGR57zyyis488wzAQCNjY2YPXt2jnukKUqaN3nbrvGMSl2MfKVbqZ68ELRRlJnBzAiF1GX1xIkTMXHiRN/6oNEkqOhvqJtE2zUZo5I1IJ8dMfSKQkBQ1ao++eQTHHXUUfjOd76DIUOG4Morr0R1dTWOPfZYTJ8+PbHf//3f/2Hw4ME4/vjjsWjRosT2hx56CNdffz0A4Lvf/S4WLlyY+K1Xr14AgC1btuCkk07C8OHDMWTIELz++usZ9VnTTRgzDQjb4k3CEWO7JmPcsgbke4U8vaIQ4KXYiVc2bNiAhx9+GKNHj8aOHTvQu3dvdHZ2YsyYMVi/fj2+/vWvY/LkyXj55ZdxxBFH4IILLvDU/uOPP45x48bhZz/7GTo7O9HS0pJRfzXdBNNgrb2eAsEta0CQY44faEEhIMhUEIcddhhGjx4NAKivr8f8+fPR0dGBLVu24L333kMsFsOgQYNw5JFHAgAuvfRSzJ8/X7n9UaNG4YorrkB7ezvq6uowfPjwjPus6SYMnaQFQ0C41cXI9/QzWvUkIMhUEPvssw8AIwDw17/+NV566SWsX78e48eP9xQ13qNHD8RiMQBALBZDW1sbAOCkk07Ca6+9hqqqKnz3u9/FI488knGfNRpNZrjVxcj39DNaUAjIRrGTXbt2YZ999kFFRQU+++wzLF26FAAwePBgfPLJJ/jXv/4FAHjiiSeExw8cOBCrV68GYHhDtbe3AwA+/fRTHHzwwZg8eTKuuuoqvPXWW771WaPRpIdbYaNsFVhKF616EpCNYifDhg3DiBEjMHjwYAwYMAA1NTUAjFxG8+fPx/jx41FeXo4TTzwRX331VcrxkydPxllnnYVhw4bh9NNPT6xUXnnlFcydOxfhcBi9evXSKwqNJk9wyhqQzQJL6dBtcj29//77OProo3PUI42f6Gep0QSDLNeTVj1pNBqNxpG8FxREdDQR/Z6IFhLR93PdH41Go+luBCooiOhBIvqciN6xbT+diD4koo+IaKpTG8z8PjNfC2ASgJog+6vRaDSaVIJeUTwE4HTrBiIqAfBbAGcAOAbARUR0DBEdR0R/tv07KH7MRADPA1gScH81Go1GYyNQrydmfo2IBto2nwDgI2b+NwAQ0ZMAzmLmWQDOlLTTCKCRiJ4H8LhoHyK6GsDVAHDooYf6cwEajUajyYl7bBUAa/axTQC+IduZiE4BcA6AnnBYUTDzfADzAcPryYd+ajQajQYFYMxm5leY+UZmvoaZf5vr/mSDefPm4eijj8Yll1yScVsPPfQQNm/enPj7qquuwnvvvZdxu+m0YyYu1Gg0hUUuVhRNAAZY/u4f35YxRDQBwIQjjjgi88YCLAvplmL8vvvuw1/+8hf075+c4rmjowM9enh7ZA899BCGDBmCfv36AQAWLFiQXqdt+NWORqPJf3KxolgJ4EgiGkREpQAuBNDoR8PMvJiZr66oqMisIbMsZPNGANxVFnJ9fdpN2lOMb9y4EXPnzsWoUaMwdOjQRJrxa6+9Fv/+979xxhln4K677sKMGTNw2WWXoaamBpdddhk++eQTnHjiiTj++ONx/PHH429/+1viHHfccQeOO+44DBs2DFOnTsXChQuxatUqXHLJJRg+fDii0ShOOeUUrFq1Cr///e8xZcqUxLHWFOaPPvooTjjhBAwfPhzXXHMNOjuTs1oCSLQDGCuFn/3sZxg2bBhGjx6Nzz77DICRz+qb3/wmjjvuONx2221Jx4uu/dlnn8WYMWPAzNiyZQu+/vWvY+vWrWnfc41G4xPm7DaIfwCeALAFQDsMW8SV8e3/BeCfAP4F4Gd+n3fkyJFs57333kvZJuXOY5mn75f6785j1duw8fHHHzMR8d///ndmZn7hhRd48uTJHIvFuLOzk8ePH8+vvvoqMzMfdthhvG3bNmZmnj59Oh9//PHc0tLCzMx79uzhaDTKzMz//Oc/2bzWJUuW8De/+U3es2cPMzNv376dmZlPPvlkXrlyZaIf5t+ff/45H3744Yntp59+Or/++uv83nvv8ZlnnsltbW3MzPz973+fH3744ZTrsbYLgBsbG5mZecqUKfyLX/yCmZknTJiQOPY3v/kN77PPPq7Xfskll/C9997L48eP58cff1x4Lz09S41GowyAVSwYU4P2erpIsn0JAnB19U31FFBZSGuK8RdffBEvvvgiRowYAQDYvXs3NmzYgJNOOinluIkTJyISMbJItre34/rrr8fatWtRUlKCf/7znwCAv/zlL/je976H8vJyAEDv3r0d+3LggQfia1/7Gt544w0ceeSR+OCDD1BTU4Pf/va3WL16NUaNGgUAiEajOOiggxzbKi0tTZRrHTlyJJYtWwYAWLFiBZ555hkAwGWXXYZbbrnF9drvvfdeDBkyBKNHj8ZFFwlfH41Gk2WKKikgMy8GsLi6unpyRg0FVBbSTNwHGCu5W2+9Fddcc42n4+666y4cfPDBWLduHWKxGMrKytLuz4UXXoj6+noMHjwYZ599NogIzIzLL78cs2bNUm4nHA6DiAAAJSUl6OjoSPxmbrfidO2bNm1CKBTCZ599hlgs5qlUrEajCQb9FYrIQlnIcePG4cEHH8Tu3bsBAE1NTfj8889dj2tubsYhhxyCUCiEP/3pTwn7wdixY/HHP/4xUdFux44dAIB9991XmH0WAM4++2w899xzeOKJJ3DhhRcCAMaMGYOFCxcm+rJjxw58+umnaV1jTU0NnnzySQDAY489ltguu/aOjg5cccUVeOKJJ3D00UfjzjvvTOu8Go3GX7SgEDF0EjBhHlAxAAAZ/50wz9fqX6eddhouvvjihLH3vPPOkw7oVq677jo8/PDDGDZsGD744IPEauP000/HxIkTUV1djeHDh+PXv/41AKO29rXXXpswZlvZf//9cfTRR+PTTz/FCSecAAA45phj8Mtf/hKnnXYahg4dirFjx2LLli1pXeM999yD3/72tzjuuOPQ1NTl2Ca79l/96lc48cQTUVtbizvvvBMLFizA+++/n9a5NRqNfxRVmnGLjWLyhg0bkn7TqamLB/0sNZpg6BZpxtkv91iNRqPRJCgqQaHRaDQa/+lWgqKY1GzdFf0MNZrsU1SCgogmENH85ubmlN/Kysqwfft2PdAUMMyM7du3Z+QSrNFovFNUxmwTUc3s9vZ2bNq0Ca2trTnqlcYPysrK0L9/f4TD4Vx3RaMpOmTG7KIKuHMiHA5j0KBBue6GRqPRFBxFpXrS5DHr64G7hgAzKo3/ZpBgUaPRZJdus6LQ5BAzG297PODPzMYL+BrEqNFogqGoVhROxmxNDnlpZpeQMGmPGts1Gk3eU5TGbCLaBiC9BEWFQR8AX+S6E6qMPCQ0Uvbb6i2x1YLNBXV9aVLs11js1wcU5zUexswH2jcWpaAodoholcgzoVgo9usDiv8ai/36gO5xjSZFpXrSaDQajf9oQaHRaDQaR7SgKEzm57oDAVPs1wcU/zUW+/UB3eMaAWgbhUaj0Whc0CsKjUaj0TiiBYVGo9FoHNGCIk8hogeJ6HMiekfy+ylE1ExEa+P//CvonQWIaAAR/ZWI3iOid4noh4J9iIjmEdFHRLSeiI7PRV/TRfEaC/Y5ElEZEb1JROvi13e7YJ+eRPRU/Bn+g4gG5qCraaN4jd8lom2WZ3hVLvoaJDqFR/7yEIDfAHjEYZ/XmfnM7HTHdzoA/JiZ3yKifQGsJqJlzPyeZZ8zABwZ//cNAL+L/7dQULlGoHCf414ApzLzbiIKA1hOREuZ+Q3LPlcC+JKZjyCiCwHcAeCCXHQ2TVSuEQCeYubrc9C/rKBXFHkKM78GYEeu+xEUzLyFmd+K//+vALwPoMq221kAHmGDNwBUEtEhWe5q2iheY8ESfy6743+G4//s3jFnAXg4/v8XAhhDRJSlLmaM4jUWPVpQFDbfjC+JlxLRsbnuTLrE1REjAPzD9lMVgI2WvzehQAdah2sECvg5ElEJEa0F8DmAZcwsfYbM3AGgGcABWe1khihcIwCcG1ePLiSiAdntYfBoQVG4vAUjL8swAPcCaMhtd9KDiHoBeAbATcy8K9f9CQKXayzo58jMncw8HEB/ACcQ0ZAcd8l3FK5xMYCBzDwUwDJ0raCKBi0oChRm3mUuiZl5CYAwEfXJcbc8Edf5PgPgMWZeJNilCYB1dtY/vq1gcLvGYniOAMDMOwH8FcDptp8Sz5CIegCoALA9q53zCdk1MvN2Zt4b/3MBAGkSzEJFC4oChYj6mrpeIjoBxrMsmA8w3vcHALzPzHdKdmsE8J2499NoAM3MvCVrncwQlWss5OdIRAcSUWX8/0cAjAXwgW23RgCXx///eQBe5gKK8lW5RpvdbCIMW1RRob2e8hQiegLAKQD6ENEmANNhGNLAzL+H8dF9n4g6AEQBXFhIHyCAGgCXAXg7rv8FgJ8COBRIXOMSAP8F4CMALQC+l/1uZoTKNRbyczwEwMNEVAJDwNUz85+JaCaAVczcCENQ/omIPoLhnHFh7rqbFirXeCMRTYTh5bYDwHdz1tuA0Ck8NBqNRuOIVj1pNBqNxhEtKDQajUbjiBYUGo1Go3FECwqNRqPROKIFhUaj0eQx5JIg1GNb37YkL1xLRK1EVOd6nPZ60mg0mvyFiE4CsBtG3jPfIt+JqDcM1/P+zNzitK9eUWg0PhFPGf7n+P+fSERT02ynMz7b6xf/eyQRvR1P1T3PEqA3l4i2EtFP/LsKTb4hShBKRIcT0f8R0Woiep2IBqfR9HkAlroJCUAH3Gk0rsQHZmLmmOox8UCsxjRPGY3nFjL5HYDJMBIKLoGRQmIpM08hoj1pnkNT2MwHcC0zbyCibwC4D8CpHtu4EIAsK0ISekWh0QggooFE9CERPQLgHQAPENEqe/EaIjqdiD4gorcAnGPZ/l0i+k38/z9EROdZftsd/+8hRPRafPXwDhGdKOjHIQD2Y+Y34hHbjwCoC+iyNQVAPMnktwA8HY/4/wOMCHIQ0Tnxd8n+7wVbG4cAOA7AC1BAryg0GjlHAricmd8got7MvCOeyuElIhoK4J8A7ocxk/sIwFMe278YwAvM/D/xdssF+1TBSK9uUrCp1jW+EQKw07bqBADEE0+KEmzamQTgWWZuVz2hRqMR86mlktmk+KphDYBjARwDYDCAj5l5Q3y2/6jH9lcC+B4RzQBwXLy4kUbjSDxV/cdEdD6QKBk8zGMzFwF4QnVnLSg0Gjl7AICIBgH4CYAx8ZoDzwMo89BOB+LfGhGFAJQCCSPlSTBScT9ERN8RHNsEI726ScGlWtdkRjxB6N8BHEVEm4joSgCXALiSiNYBeBdGJUHV9gbCSP3+quoxWvWk0bizHwyh0UxEB8Oo5f0KjHTTA4nocGb+F4xZmohPYNQoqIeRhjoMAER0GIBNzHw/EfUEcDxsNdKZeQsR7YqnWf8HgO/AKHCk6SYws+y9stf+UG3vE3hUX2pBodG4wMzriGgNDMGwEcCK+PZWIroawPNE1ALgdQD7Cpq4H8Bz8dnf/yG+UoGRRn4KEbXD8JMXrSgA4DoADwGIAFga/6fRZA0dcKfR5BlEtJuZeynuOwPAbmb+dbC90nRntI1Co8k/dlkD7mQQ0VwAl6JrhaLRBIJeUWg0Go3GEb2i0Gg0Go0jWlBoNBqNxhEtKDQajUbjiBYUGo1Go3Hk/wM2tXOOVHMGPAAAAABJRU5ErkJggg==", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "properties = [\"radius\", \"refractive_index\", \"sigma\"]\n", - "\n", - "validation_prediction = model.predict(np.array(validation_set))\n", - "\n", - "validation_errors = [\n", - " np.abs(validation_prediction[:, idx] - np.array(validation_labels)[:, idx]) for idx in range(2)\n", - "]\n", - "\n", - "error_names = [\"radius\", \"refractive index\"]\n", - "\n", - "for property_name in properties:\n", - " property_values = np.array([image.get_property(property_name) for image in validation_set])\n", - " if property_values.ndim == 1:\n", - " property_values = np.expand_dims(property_values, axis=-1)\n", - " \n", - " for col in range(property_values.shape[1]):\n", - " values = property_values[:, col]\n", - "\n", - " plt.subplot(1, property_values.shape[1], col + 1)\n", - " for validation_error in validation_errors:\n", - " plt.scatter(values, validation_error, alpha=1)\n", - " plt.xlim([np.min(values), np.max(values)])\n", - " plt.ylim([np.min(validation_error), np.max(validation_error)])\n", - " plt.yscale(\"log\")\n", - " plt.ylabel(\"Absolute error\")\n", - " plt.xlabel(\"{0}[{1}]\".format(property_name, col))\n", - " \n", - " plt.legend(error_names)\n", - "\n", - " \n", - " plt.show()" - ] - }, + "name": "stderr", + "output_type": "stream", + "text": [ + "Downloading...\n", + "From (original): https://drive.google.com/uc?id=1FaygrzmEDnXjVe_W3yVfqNTM0Ir5jFkR\n", + "From (redirected): https://drive.google.com/uc?id=1FaygrzmEDnXjVe_W3yVfqNTM0Ir5jFkR&confirm=t&uuid=68bcc00e-b598-4ffb-9165-89d0cc8f8488\n", + "To: /Users/edu/DeepTrack2/tutorials/2-examples/datasets/ParticleSizing.zip\n", + "100%|██████████| 393M/393M [00:34<00:00, 11.3MB/s] \n" + ] + } + ], + "source": [ + "import zipfile\n", + "\n", + "import gdown\n", + "\n", + "file_id = \"1FaygrzmEDnXjVe_W3yVfqNTM0Ir5jFkR\"\n", + "\n", + "Path(\"datasets\").mkdir(exist_ok=True)\n", + "\n", + "zip_path = \"datasets/ParticleSizing.zip\"\n", + "\n", + "gdown.download(\n", + " id=file_id,\n", + " output=zip_path,\n", + " quiet=False,\n", + ")\n", + "\n", + "with zipfile.ZipFile(zip_path, \"r\") as zf:\n", + " zf.extractall(\"datasets\")\n", + "\n", + "Path(zip_path).unlink()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "dtex203-22-load", + "metadata": {}, + "outputs": [ { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "We estimate the size of particles using experimentally captured images. The particles were traced, so we display the average size and refractive index measured by the model over the trace." - ] - }, + "name": "stdout", + "output_type": "stream", + "text": [ + "Loaded 114 experimental tracks\n" + ] + } + ], + "source": [ + "experimental_data_path = Path(\"datasets/ParticleSizing/sizing_150nm_227nm_PSL.npy\")\n", + "\n", + "if experimental_data_path.exists():\n", + " experimental_data = np.load(experimental_data_path, allow_pickle=True)\n", + " print(f\"Loaded {len(experimental_data)} experimental tracks\")\n", + "else:\n", + " experimental_data = None\n", + " print(\"Experimental data not found.\")\n" + ] + }, + { + "cell_type": "markdown", + "id": "8d5c4ab9", + "metadata": {}, + "source": [ + "Predict radius and refractive index for the experimental data and visualize the results." + ] + }, + { + "cell_type": "code", + "execution_count": 43, + "id": "dtex203-22", + "metadata": {}, + "outputs": [ { - "cell_type": "code", - "execution_count": 12, - "metadata": { - "execution": { - "iopub.execute_input": "2022-06-30T10:20:41.645049Z", - "iopub.status.busy": "2022-06-30T10:20:41.645049Z", - "iopub.status.idle": "2022-06-30T10:20:47.928050Z", - "shell.execute_reply": "2022-06-30T10:20:47.927582Z" - } - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "1/1 [==============================] - 0s 125ms/step\n", - "1/1 [==============================] - 0s 69ms/step\n", - "1/1 [==============================] - 0s 68ms/step\n", - "1/1 [==============================] - 0s 72ms/step\n", - "1/1 [==============================] - 0s 77ms/step\n", - "1/1 [==============================] - 0s 63ms/step\n", - "1/1 [==============================] - 0s 13ms/step\n", - "1/1 [==============================] - 0s 13ms/step\n", - "1/1 [==============================] - 0s 13ms/step\n", - "1/1 [==============================] - 0s 68ms/step\n", - "2/2 [==============================] - 0s 63ms/step\n", - "2/2 [==============================] - 0s 2ms/step\n", - "1/1 [==============================] - 0s 66ms/step\n", - "1/1 [==============================] - 0s 66ms/step\n", - "2/2 [==============================] - 0s 64ms/step\n", - "1/1 [==============================] - 0s 12ms/step\n", - "1/1 [==============================] - 0s 66ms/step\n", - "3/3 [==============================] - 0s 2ms/step\n", - "2/2 [==============================] - 0s 62ms/step\n", - "3/3 [==============================] - 0s 33ms/step\n", - "1/1 [==============================] - 0s 13ms/step\n", - "1/1 [==============================] - 0s 63ms/step\n", - "1/1 [==============================] - 0s 75ms/step\n", - "2/2 [==============================] - 0s 50ms/step\n", - "1/1 [==============================] - 0s 67ms/step\n", - "3/3 [==============================] - 0s 2ms/step\n", - "3/3 [==============================] - 0s 2ms/step\n", - "3/3 [==============================] - 0s 2ms/step\n", - "1/1 [==============================] - 0s 67ms/step\n", - "2/2 [==============================] - 0s 3ms/step\n", - "1/1 [==============================] - 0s 77ms/step\n", - "2/2 [==============================] - 0s 3ms/step\n", - "4/4 [==============================] - 0s 2ms/step\n", - "1/1 [==============================] - 0s 70ms/step\n", - "1/1 [==============================] - 0s 13ms/step\n", - "5/5 [==============================] - 0s 15ms/step\n", - "2/2 [==============================] - 0s 3ms/step\n", - "5/5 [==============================] - 0s 15ms/step\n", - "1/1 [==============================] - 0s 14ms/step\n", - "1/1 [==============================] - 0s 12ms/step\n", - "1/1 [==============================] - 0s 13ms/step\n", - "2/2 [==============================] - 0s 46ms/step\n", - "2/2 [==============================] - 0s 2ms/step\n", - "2/2 [==============================] - 0s 51ms/step\n", - "2/2 [==============================] - 0s 53ms/step\n", - "2/2 [==============================] - 0s 2ms/step\n", - "2/2 [==============================] - 0s 2ms/step\n", - "3/3 [==============================] - 0s 2ms/step\n", - "3/3 [==============================] - 0s 2ms/step\n", - "3/3 [==============================] - 0s 3ms/step\n", - "3/3 [==============================] - 0s 2ms/step\n", - "3/3 [==============================] - 0s 2ms/step\n", - "4/4 [==============================] - 0s 22ms/step\n", - "5/5 [==============================] - 0s 2ms/step\n", - "1/1 [==============================] - 0s 14ms/step\n", - "1/1 [==============================] - 0s 13ms/step\n", - "1/1 [==============================] - 0s 13ms/step\n", - "1/1 [==============================] - 0s 14ms/step\n", - "1/1 [==============================] - 0s 13ms/step\n", - "1/1 [==============================] - 0s 14ms/step\n", - "2/2 [==============================] - 0s 2ms/step\n", - "1/1 [==============================] - 0s 12ms/step\n", - "2/2 [==============================] - 0s 2ms/step\n", - "3/3 [==============================] - 0s 2ms/step\n", - "1/1 [==============================] - 0s 13ms/step\n", - "1/1 [==============================] - 0s 12ms/step\n", - "1/1 [==============================] - 0s 13ms/step\n", - "2/2 [==============================] - 0s 3ms/step\n", - "1/1 [==============================] - 0s 21ms/step\n", - "2/2 [==============================] - 0s 75ms/step\n", - "2/2 [==============================] - 0s 2ms/step\n", - "2/2 [==============================] - 0s 3ms/step\n", - "2/2 [==============================] - 0s 3ms/step\n", - "2/2 [==============================] - 0s 3ms/step\n", - "1/1 [==============================] - 0s 14ms/step\n", - "1/1 [==============================] - 0s 12ms/step\n", - "3/3 [==============================] - 0s 2ms/step\n", - "1/1 [==============================] - 0s 13ms/step\n", - "7/7 [==============================] - 0s 2ms/step\n", - "3/3 [==============================] - 0s 2ms/step\n", - "1/1 [==============================] - 0s 13ms/step\n", - "3/3 [==============================] - 0s 2ms/step\n", - "3/3 [==============================] - 0s 2ms/step\n", - "1/1 [==============================] - 0s 13ms/step\n", - "1/1 [==============================] - 0s 12ms/step\n", - "2/2 [==============================] - 0s 3ms/step\n", - "2/2 [==============================] - 0s 3ms/step\n", - "2/2 [==============================] - 0s 3ms/step\n", - "2/2 [==============================] - 0s 3ms/step\n", - "1/1 [==============================] - 0s 13ms/step\n", - "7/7 [==============================] - 0s 3ms/step\n", - "1/1 [==============================] - 0s 13ms/step\n", - "9/9 [==============================] - 0s 3ms/step\n", - "1/1 [==============================] - 0s 12ms/step\n", - "1/1 [==============================] - 0s 14ms/step\n", - "9/9 [==============================] - 0s 12ms/step\n", - "1/1 [==============================] - 0s 13ms/step\n", - "4/4 [==============================] - 0s 3ms/step\n", - "2/2 [==============================] - 0s 2ms/step\n", - "1/1 [==============================] - 0s 13ms/step\n", - "1/1 [==============================] - 0s 12ms/step\n", - "5/5 [==============================] - 0s 3ms/step\n", - "3/3 [==============================] - 0s 3ms/step\n", - "5/5 [==============================] - 0s 3ms/step\n", - "1/1 [==============================] - 0s 13ms/step\n", - "1/1 [==============================] - 0s 13ms/step\n", - "9/9 [==============================] - 0s 3ms/step\n", - "1/1 [==============================] - 0s 13ms/step\n", - "1/1 [==============================] - 0s 13ms/step\n", - "4/4 [==============================] - 0s 3ms/step\n", - "2/2 [==============================] - 0s 3ms/step\n", - "1/1 [==============================] - 0s 13ms/step\n", - "1/1 [==============================] - 0s 13ms/step\n", - "6/6 [==============================] - 0s 3ms/step\n", - "2.9173846\n" - ] - }, - { - "data": { - "image/png": "iVBORw0KGgoAAAANSUhEUgAAAY4AAAEGCAYAAABy53LJAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjUuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8qNh9FAAAACXBIWXMAAAsTAAALEwEAmpwYAABCcUlEQVR4nO3de5xbdZn48c9zTpLJXHqh7VAqLbTIxVLajnQWq6tQ5SIiVFHXpaIisCL8YMUqIuiuFH+iu6iLuLIiKoJaKP64CCLgIlK6Kgu0WEqhIhcLLQU6vXdmkkly8vz+OCfTTJrJJNNcZ5736zWvSb7nkieZTJ6c71VUFWOMMaZYTq0DMMYY01gscRhjjCmJJQ5jjDElscRhjDGmJJY4jDHGlCRU6wCqYdKkSTp9+vRah2GMMQ1l1apVW1S1Pbd8VCSO6dOns3LlylqHYYwxDUVEXs5XblVVxhhjSmKJwxhjTEkscRhjjCnJqGjjyCeZTLJx40bi8XitQzFlFI1GmTp1KuFwuNahGDNijdrEsXHjRsaMGcP06dMRkVqHY8pAVdm6dSsbN25kxowZtQ7HmBFr1FZVxeNxJk6caEljBBERJk6caFeRpuq8mEfslRg9f+0h9koML+bVOqSKGrWJA7CkMQLZ39RUmxfziL8cBw/cVhc8iL8cH9HJY1QnDmOM2VeJrgROk4PT5CAi/bcTXYlah1YxljhqSET4+Mc/3n8/lUrR3t7OqaeeWtJ5pk+fzpYtW/Z5n321fv16jjrqKABWrlzJZz/72YL7f+Mb3xhw/x3veEfFYjOmUtLxNBIZeKUrESEdT9coosqzxFFDra2trF27llgsBsCDDz7IgQceWOOo9pZKpUo+prOzk+9973sF98lNHH/6059Kfhxjas2JOmhi4IJ4mlCc6Mj9eB25z6zMli6F6dPBcfzfS5eW57ynnHIKv/nNbwC49dZbWbRoUf+2bdu28cEPfpA5c+Ywf/581qxZA8DWrVs56aSTmDVrFv/0T/9E9iqOv/jFLzjmmGPo6OjgM5/5DJ5XuJ61ra2NxYsXM2vWLI4//ni6uroAWLBgAZ/73Ofo7Ozk2muvZdWqVRx33HHMmzeP9773vbz22msArFq1irlz5zJ37lyuu+66/vMuX768/8qpu7ubs88+m9mzZzNnzhzuuOMOLrvsMmKxGB0dHZx55pn9sYDfO+qLX/wiRx11FLNnz+a2227rP+eCBQv4yEc+wlve8hbOPPNMbAVLU2uR9gjpvjTpvjSq2n870h6pdWiVo6oV+QFuBDYDawfZ/kVgdfCzFvCACcG29cDTwbaVWcdMAB4Eng9+71dMLPPmzdNczz777F5lg/nFL1RbWlRhz09Li1++L1pbW/Wpp57SD3/4wxqLxXTu3Ln68MMP6/vf/35VVb3ooot0yZIlqqr60EMP6dy5c1VV9Z//+Z/1yiuvVFXVe++9VwHt6urSZ599Vk899VRNJBKqqnrBBRfozTffrKqqBx98sHZ1de0VA6C/CJ7IlVdeqRdeeKGqqh533HF6wQUXqKpqIpHQt7/97bp582ZVVV22bJmeffbZqqo6e/ZsfeSRR1RV9ZJLLtFZs2apqg54HpdeeqlefPHF/Y+5bdu2/uef+3qoqt5+++16wgknaCqV0tdff12nTZummzZt0ocffljHjh2rGzZsUM/zdP78+fo///M/ez2nUv62xpRDqjelvS/3avdz3dr7cq+melO1Dqkssj9/s38qOY7jJuD7wM/ybVTVbwHfAhCR04DFqrota5d3q2pupfxlwEOq+m8icllw/0vlDjzXV74Cvb0Dy3p7/fLgy/KwzZkzh/Xr13PrrbdyyimnDNj2hz/8gTvuuAOA97znPWzdupVdu3axYsUK7rzzTgDe//73s99++wHw0EMPsWrVKv7u7/4OgFgsxv7771/w8R3H4R//8R8B+PjHP86HPvSh/m2Z8ueee461a9dy4oknAuB5HlOmTGHHjh3s2LGDY489FoBPfOIT3H///Xs9xu9+9zuWLVvWfz8T72D+8Ic/sGjRIlzXZfLkyRx33HE88cQTjB07lmOOOYapU6cC0NHRwfr163nnO99Z8HzGVJrb7NJ8UHOtw6iaiiUOVV0hItOL3H0RcGsR+30AWBDcvhlYThUSxyuvlFZeqoULF3LJJZewfPlytm7dOuzzqCpnnXUW3/zmN4d9juzurK2trf3nnTVrFo8++uiAfXfs2DHsxxmupqam/tuu6w6r/cUYs29q3sYhIi3AycAdWcUK/LeIrBKR87LKJ6vqa8Ht14HJBc57noisFJGVmXr74TrooNLKS3XOOedwxRVXMHv27AHl73rXu1gaNKYsX76cSZMmMXbsWI499lhuueUWAO6//362b98OwPHHH8/tt9/O5s2bAb+N5OWX886K3C+dTnP77bcDcMstt+T99n7EEUfQ1dXVnziSySTPPPMM48ePZ/z48fzhD38A6I8114knnjig/SMTbzgcJplM7rX/u971Lm677TY8z6Orq4sVK1ZwzDHHFHwexpjqqXniAE4D/phTTfVOVT0aeB9woYgcm3tQUP82aMuoqt6gqp2q2tnevtc6JCW56ipoaRlY1tLil5fD1KlT83ZdXbJkCatWrWLOnDlcdtll3HzzzQBcccUVrFixglmzZnHnnXdyUJDBjjzySL7+9a9z0kknMWfOHE488cT+RuzBtLa28vjjj3PUUUfx+9//nq9+9at77ROJRLj99tv50pe+xNy5c+no6OjvAfXTn/6UCy+8kI6OjkEbqv/lX/6F7du3c9RRRzF37lwefvhhAM477zzmzJnT3ziecfrppzNnzhzmzp3Le97zHq6++moOOOCAIV5FY0y1yGD/7GU5uV9Vda+qHlVgn7uA/6eqtwyyfQnQrarfFpHngAWq+pqITAGWq+oRQ8XR2dmpuQs5rVu3jpkzZxb9XJYu9ds0XnnFv9K46qp9b9+oB21tbXR3d9c6jLIq9W9rjMlPRFapamdueU2vOERkHHAccHdWWauIjMncBk7C73UFcA9wVnD7rOzjKu3MM2H9ekin/d8jIWkYY8xwVKxxXERuxW/IniQiG4ErgDCAql4f7HY68N+q2pN16GTgrqCRNgTcoqoPBNv+DfiliJwLvAx8tFLxjxYj7WrDGFN5lexVtaiIfW7C77abXfYSMHeQ/bcCx5chPGOMMcM0atfjKMjz/CHipcy0qurXY7lu5eIyxgzKi3kkuhKk42mcqEOkPYLbbP+PlVAPvarqi+fB2WfD4sV+MiiGqr//2Wf7xxtjqmo0Tm1eS5Y4cjkOTJgA115bXPLIJI1rr/WPc+wlNabaRuPU5rVkn3K5ROCaa+Dii4dOHtlJ4+KL/eNKqN4655xz2H///funIs9YsmQJBx54IB0dHXR0dHDffff1b/vmN7/JoYceyhFHHMFvf/vbYT3FoUyfPr1/QsKTTjqJ119/HYAbb7yxv/yoo47i7rv9Tm2f+tSn+gcRGlMLo3Fq81qyNo58MskD/KQAeyeFfUwa4H/gXnTRRXzyk5/ca9vixYu55JJLBpQ9++yzLFu2jGeeeYZNmzZxwgkn8Ne//hW3Au0qDz/8MJMmTeLLX/4y3/jGN7j00ku56qqrePLJJxk3bhzd3d3s64h8Y8olM7W5NO35HxzpU5vXkr2qgyl05VGGpAFw7LHHMmHChKL3v/vuuznjjDNoampixowZHHrooTz++OOsX7+emTNn8ulPf5pZs2Zx0kkn9a/xsWDBAhYvXkxnZyczZ87kiSee4EMf+hCHHXYY//Iv/1JUjC+88AKbN29mzJgx/VOft7W1MWPGjJKfszGVMCqnNq8hSxyFDJY8ypA0hvL973+fOXPmcM455/TP7fTqq68ybdq0/n2mTp3Kq6++CsDzzz/PhRde2D+HVGZWXfCnDFm5ciXnn38+H/jAB7juuutYu3YtN91005CTKt57773Mnj2buXPnMnnyZGbMmMHZZ5/Nr3/967I/Z2OGy212iR4cBRe8Hg9ciB4ctV5VFWKJYyi5ycNxKp40LrjgAl588UVWr17NlClT+MIXvjDkMTNmzKCjowOAefPmsX79+v5tCxcuBGD27NnMmjWLKVOm0NTUxCGHHMKGDRvynu/d7343HR0d7Nq1i8svvxzXdXnggQe4/fbbOfzww1m8eDFLlizZ16dqTNlkpjZvPbyV5oOaLWlUkCWOYmS3eWRUKGkATJ48Gdd1cRyHT3/60zz++OMAHHjggQM+6Ddu3Ni/1Gyh6cYz2xzHGbCf4ziDTkv+8MMPs3r1an72s58xfvx4wJ9y/ZhjjuHyyy9n2bJlA65qjDGjhyWOYmSqp7KVMs6jRNkz2t511139va4WLlzIsmXL6Ovr429/+xvPP/981aYb37RpE08++WT//dWrV3PwwQdX5bGNMfXFelUNJV+bRuY+7NOVx6JFi1i+fDlbtmxh6tSpXHnllZx77rlceumlrF69GhFh+vTp/PCHPwRg1qxZfPSjH+XII48kFApx3XXXVaRHVT7JZJJLLrmETZs2EY1GaW9v5/rrr+/f/pnPfIbPfe5zAEybNm2vRZ+MMSNHRadVrxfDnlZ9sIbwKjWQm+GxadWNKY/BplW3K47BFEoOxYzzMMaYEcoSRz7FXFFY8jDGjFKWOHKVUg1lycOYqrCZb+uLJY5c6TTeti04F38WKSYJBMlDUdLbtuDa1OrGlFVm5lunycFtddGEEn85bgP8asgSRw5P4OwPChNa4BqgmGsHBRafDNt6hZ8K2FvZmPLJnvkW6J+PKtGVoPmg5lqGNmrZOI4cjjhMaJnItY99j8W/XcxQvc5UlcW/Xcy1j32PCS0TccReUmPKyWa+rT/2KZdDRLjmvddw8dsu5trHri2YPPYkjWu5+G0Xc817r0GKbN/YsGED7373uznyyCOZNWsW12baSIAvfvGLvOUtb2HOnDmcfvrp7NixA4ClS5f2T7Xe0dGB4zisXr16X5/yXhYsWMARRxzB3Llz+fu//3uee+45wJ+36q1vfStz587lyCOP7B9fsmTJEr797W+XPQ5jYM/Mt9ls5tsaU9WK/AA3ApuBtYNs/yKwOvhZC3jABGAa8DDwLPAMcHHWMUuAV7OOO6WYWObNm6e5nn322b3KsqXTab34/ouVJejF91+s6XS6pO1D2bRpk65atUpVVXft2qWHHXaYPvPMM6qq+tvf/laTyaSqql566aV66aWX7nX8mjVr9JBDDinpMYt13HHH6RNPPKGqqj/84Q/1tNNO00QioVOmTNENGzaoqmo8Hte//OUvqqp6xRVX6Le+9a2KxDIcQ/1tTWNJ9aa0e1239r7Uq7GNMe19qVe713VrqjdV69BGPGCl5vlMrWTKvgk4ebCNqvotVe1Q1Q7gcuARVd0GpIAvqOqRwHzgQhE5MuvQazLHqep9e5+5PApdeeg+XGlkTJkyhaOPPhqAMWPGMHPmzP6Zbk866SRCIb/5af78+WzcuHGv42+99VbOOOOM/vttbW185StfYe7cucyfP5833ngD8Nf8uOCCC5g/fz6HHHIIy5cv55xzzmHmzJl86lOfGjLOzLTqu3fvJpVKMXHiRMCf/+qII44o6TkbMxw28239qVjiUNUVwLYid18E3Boc95qqPhnc3g2sAw6sSJBDGCx57GvSyLV+/Xr+/Oc/87a3vW2vbTfeeCPve9/79iq/7bbbWLRoUf/9np4e5s+fz1NPPcWxxx7Lj370o/5t27dv59FHH+Waa65h4cKFLF68mGeeeYann356yKquX//618yePZsJEyawcOFCDj74YBYtWsTSpUtJp62O2VSHzXxbX2req0pEWvCvTC7Ks2068Fbgsazii0Tkk8BK/CuT7YOc9zzgPICDDjpoX+Ljmvf6YzWufexarn3Mb4soV9Lo7u7mwx/+MN/97ncZO3bsgG1XXXUVoVCIM888c0D5Y489RktLy4AlZyORCKeeeirgT6v+4IMP9m877bTTEBFmz57N5MmTmT17NuDPfbV+/fr+6diznXnmmTQ3NzN9+nT+8z//E4Af//jHPP300/zud7/j29/+Ng8++CA33XTTPj1/Y0zjqYfWpdOAPwbVVP1EpA24A/icqu4Kin8AvBnoAF4DvjPYSVX1BlXtVNXO9vb2fQowO3lklCNpJJNJPvzhD3PmmWfyoQ99aMC2m266iXvvvZelS5fu9TjLli0bcLUBEA6H+/crx7TqS5cuZfXq1fzqV78asHjU7NmzWbx4MQ8++KBNq27MKFUPieMMgmqqDBEJ4yeNpap6Z6ZcVd9QVU9V08CPgKrMKZ6pnspWTFfdoc557rnnMnPmTD7/+c8P2PbAAw9w9dVXc88999DS0jJgWzqd5pe//OWA9o1q6O7uZvny5f33bVp1Y0avmiYOERkHHAfcnVUmwE+Adar6Hzn7T8m6ezp+b6yKym3TSH81XVRX3aH88Y9/5Oc//zm///3v+7vX3nef39Z/0UUXsXv3bk488UQ6Ojo4//zz+49bsWIF06ZN45BDDinL8yuWqnL11VdzxBFH0NHRwRVXXDGgmurrX/86U6dO7f8xxoxg+bpaleMH/yriNSAJbATOBc4Hzs/a51PAspzj3ok/GHsNOd1ugZ8DTwfb7gGmFBPLcLrjqg7e5XZfu+KayrLuuMaUB4N0x61Y47iqLipin5vwu+1ml/2BQWb6UNVPlCO2YmiB3lO5DeZQnjYPY4xpBDXvVVWPCiWNDEsexpjRalQnDlXd64O+mKSRYcmj/ugoWNHSmFobtYkjGo2ydetWJk6cOOCDPq1ptsW2FT1OIzt5bIttI61pXLHBSbWgqmzdupVoNFrrUIwZ0UbtmuPJZJKNGzcSj8f32t9LezjilHTloKp+0nAsadRSNBpl6tSphMPhWodiTMOzNcdzhMNhZsyYUeswjDGm4dTDAEBjjDENxBKHMcaYkljiMMYYU5JR28ZhjKk9L+aR6EqQjqdxog6R9ohNmd4A7IrDGFMTXswj/nIcPHBbXfAg/nIcL+bVOjQzBEscxpiaSHQlcJocnCa/63vmdqIrUevQzBAscRhjaiIdTyORnKl8IkI6bitL1jtr4zDGVNRg7RhO1EETijTtSR6aUJyofZ+td/YXMsZUzGDtGIltfiLpea6H2N9ieL0e6b406b40kfZIrcM2Q7DEYYypmHztGCh0P9WNE3ZoPrQZRel9vpd0Mk304Kj1qmoAVlVljKmYdDztX2lkSe1OoWn1EwoOoRkh0n1pcLGk0SDsisMYUzGZdoxs3m4Pd8zABGGN4o3FEocxpmIi7ZH+tgtV9a8sHAi1DazssEbxxmJ/KWNMxbjNLtGDo+CC1+OBC21z2xBHBiQTaxRvLBVNHCJyo4hsFpG1g2z/ooisDn7WiognIhOCbSeLyHMi8oKIXJZ1zAwReSwov01E7N1mTB1zm12aD2qm9fBWmg9qJjIhslcysUbxxlLpK46bgJMH26iq31LVDlXtAC4HHlHVbSLiAtcB7wOOBBaJyJHBYf8OXKOqhwLbgXMrGL8xpky8mEfslRg9f+0h0ZUg0h7pTyaWNBrLkIlDRP6viISy7o8VkZ8Wc3JVXQFsKzKWRcCtwe1jgBdU9SVVTQDLgA+IvyTfe4Dbg/1uBj5Y5PmNMTVi81KNLMVccYSAx0RkjoicCDwBrCpnECLSgn9lckdQdCCwIWuXjUHZRGCHqqZyyvOd8zwRWSkiK7u6usoZrjGmRDYv1cgy5DgOVb1cRH4HPIZfNXSsqr5Q5jhOA/6oqsVenQxJVW8AbgB/zfFyndcYU7p84zkkIn4bh2k4xVRVHQt8D/gasBz4TxF5U5njOIM91VQArwLTsu5PDcq2AuOzqs4y5caYOpZvPId1wW1cxfzVvg38g6p+U1U/BvwI+H25AhCRccBxwN1ZxU8AhwU9qCL4ieUeVVXgYeAjwX5n5RxnjKlD+cZzWBfcxlXMlCNvV9X+60lVvVNEHinm5CJyK7AAmCQiG4ErgHBwnuuD3U4H/ltVe7IeIyUiFwG/BVzgRlV9Jtj8JWCZiHwd+DPwk2JiMcbUTmY8R6Irgdfj4UQd64LbwMT/El9gB5HDgR8Ak1X1KBGZAyxU1a9XI8By6Ozs1JUrV9Y6DGOMaSgiskpVO3PLi6mq+hH+GIskgKquwa86MsYYMwoVkzhaVPXxnLJU3j2NMcaMeMW0cWwRkTcDCiAiHwFeq2hUxpgRKbMaYGpHCq/Hw211CY0P9a8KaBpDMYnjQvzxEG8RkVeBvwEfr2hUxpiGMdjSsPn2i78cB4XUthQ4kNyeREJCvDdujeUNpJgBgC8BJ4hIK+Co6u7Kh2WMqReFEkMmGThNDm6riyaU+Mv5k0Dv873Eno/Rt7EPaRFaDm3BbXbxejwikyIkuhI0H9Rci6doSjRo4hCRzw9SDoCq/keFYjLG1ImhEkP2VCIA0uR/PuQmgcS2BDv/dyfhiWGkRUChZ00PrbNbkbDYKPIGU6hxfEzw0wlcgD8n1IHA+cDRlQ/NGFNrQ80xlY6nkYgMOCbfan69z/USmhDCjbi4TS5OxMFpcYi9FOsfVW6jyBvHoFccqnolgIisAI7OVFGJyBLgN1WJzhhTU4PNMZXcmiRGjL5NfThhh8gBe6qv8iWB1K4UkQMi9G3oI9WbItmV9IcCezCudRzpvrS/RodpCMWk+MlA9hSWiaDMGDPC5V0zfJdHcmsSPGia2uRXZ/0tjtfrDTqVSGhsiHRvGkFwm1zCE8OQBAkJEhJrGG8wxfSq+hnwuIjcFdz/IP46GMaYES7SHvF7QuFfaWhC6Xu9j8jkiF9thUPzjGb6Xu8jvjFO8yHNeZNAyxEtbPn1FpyoQ/iAMKFYiFBbiLbZbThRx5JGgymmV9VVIvIA8M6g6GxV/XNlwzLG1IN8c0yFJ4YJjQsN2Kd5ejNejzdor6jIhAitM1vpe70Pb7uH2+YyZt4YQuND1ijegIq54gBYjT/oLwQgIgep6iuVCsoYUz8ya4ZnxIiR2ukP4Mt00XVbXdy2/GM3Ml151VNaDm0hPD7cvz3dl7ZG8QY0ZOIQkX/Gn9X2DcADBH8U+ZzKhmZMYyp2QFyjcttcetb24La5OC0O6d40ya4kY+ePHbBfbldePIj9LQbTITQuhCbUGsUbVDFXHBcDR6jq1koHY0yjK2VAXCPJTobJrUmapjShSSUdS+NGXSLtEbxuDybsOSa+Ie43oqfBaXIITQzRPKOZ5A5/tLhNrd64ikkcG4CdlQ7EmJGg2AFxjSQ3GcY3xNE+pWla054uuKoD2iq8mEfsxRih8SG/Z1ZS6dvYR9OBTYQnhmk9vLVWT8eUQTGJ4yVguYj8BujLFNrIcWP2NhLX1s5NhqGxIRJvJOhd3ovb7LdtRKdFCU3c83ES3+B3z/V2+Q3h4f3C/sDBNxI0TWuq1VMxZVJM4ngl+IkEP8aMGqW2V2TGPWSuNCD/gLhGagfJTYbiCN1ru3EjLpEpEbzdHjsf38nEUycCWVcbE0KktqVI96WJb4oTnhQmHU8zpn1MrZ6KKZNiuuNeWY1AjKk3w2mvyDfuIbcBuJrtIOVIULnJsO/VPiJviiCeoH1KaEyI0H4hetb20PdKH70v9OL1eLQc0kJ4QpjYyzG8HR6JLQnGv2N83SZIU7xCkxx+V1U/JyK/JliLI5uqLqxoZMbU2HDaK4pZW7ta7SDlSlC5yTC5LelXT70pihv1z9O3vY9dj+5i3NvGkdyWJNGVYMefdhDZP0J0WhRnjANJ0LTixTx/VtwGuuoyAxW64vh58PvbwzmxiNwInApsVtWjBtlnAfBd/FlrtqjqcSJyBHBb1m6HAF9V1e8G82R9GugKtn1ZVe8bTnzGDGW47RW54x7Kdd5SlStB5SbD0LgQhCDxRoLk5iQAsU0x3DEuya4k3m4PJ+yQ7knT+0wvmlSaD2r2R5tH/AkSM8lopPU+Gy0KTXK4Kvj9yDDPfRPwffwpS/YiIuOB/wJOVtVXRGT/4PGeAzqCfVzgVeCurEOvUdVhJTMzulWqvaLU85d63uEqZ4LKToZOq8OWO7egScUZ76BxJb4+TstbWkjuTBIeH6b76W4/YTX5z9fb7RE5KkKqO4WEZET2PhtNKjZkU1VXANsK7PIx4M7MCHRV3Zxnn+OBF1X15QqEaEaR/tXnPPoHo8VfjuPFBv8QjbRH+iftU9VBJ/Ar9fylnHdf5JugsCwJyoPom6M4Yx00pv2TFPZt6CO+Po4X93DHukhEcF0XJ+TgtrnEN8XpWddDcmuS1I5UUdOxm/pUy7H+hwP7ichyEVklIp/Ms88ZwK05ZReJyBoRuVFE9hvs5CJynoisFJGVXV1dg+1mRomh1pXIJ1NFg4v/Ld1l0KqUoc7vxTxir8To+WsPia4E4f3DRZ13X1QqQaXjadw2l7FvHUvrka2g4I7xV/JL7krSt9HvtR8ZEyF6cNS/4kh5pHakcJtdwuPDfvLYmRpwXluTo3EU/VcSkZYyP3YImAe8H3gv8K8icnjW40WAhcD/yzrmB8Cb8auyXgO+M9jJVfUGVe1U1c729vYyh24aTbELDuXKVNG0Ht5K80HNg364Fzp/vquR5OYkkfbIkOfdF6Ukvnyyk13slRiJbQlir/hrcCS7kiS2Juj9ay/iCpH2CC1HtuA4DqndKTSlhA8OE9kvgqYVRxyciEPbrDZC40I0HdBE4o1Exa+6TGUUM1fVO4AfA23AQSIyF/iMqv6ffXzsjcBWVe0BeoIFo+YCfw22vw94UlXfyByQfVtEfgTcu48xmFGi0u0Khc5fy/r8oRrqB5PbI8vb5dGztofo9CjRqVHSPWl2r9yN1+v5jdueEp0WZVzHOPq6+ujb1EdkUgS3xUV2CqGonyxS21Kke9KEJoT8NTmCpGbTjzSWYv5rrsG/ItgKoKpPAceW4bHvBt4pIqHgauZtwLqs7YvIqaYSkSlZd08H1pYhDjMKVLpdodD5h3u1U0u5VW/ebn8EuNfj4ba4RKdHUfHnqlJPCY0NkdqZIrk9ibjCpJMnMeE9ExjTMYbWw1oJTwjjjvEnRdS035juRJ2iruZM/SlqWnVV3SAy4I0/ZLcMEbkVWABMEpGN+DPshoPzXa+q64J1PtYAaeDHqro2OLYVOBH4TM5prxaRDvxxJevzbDcmr2LGV1Tq/NXqRVVOuT2y0n1pfybcmJ/svF6P1pmtpHenEVdI7kz2/w6NCeHFvAHPT3OGguXeN42lqEkOg+oqFZEw/my564Y4BlVdVMQ+3wK+lae8B5iYp/wTRcRrTF7DrbbZ1/MXM5q83uQmO6fJwev1cJr9ZJCOpwmNC5HoTpDcniS5Iwnq7ze2cyyp7SlI4V+ZeH7Pq3QyDUn/3NHpUf/romlIxXzlOR+4EDgQf0xFR3DfGFOEfW2kroXcqjd3jIvXHbRnqIID2quExvvfPcP7hwmNDeGEHXr/0ovX7eH1eogIobEhfzLEJpeWN7cQPTCK4zp1fcVlCivmikNU9cyKR2LMCFbpq51y26vqrdVh7PyxeN0efa/20fdqH7Hn/YkMwxPCKEoqliJ8QJjkziRO1CG1PYUX8whPCBPfGCe1O0VEIw1xxWUKKyZx/FFE1uNPA3KHqu6oaETG1LnRMsdSdrLLPOfE6wl61vXQ9KYm0jPSeLs9el/qxYk4RKdFcce5JLcl0aT6vai2pmia2kSkPdK/3Kz1oGp8xcyOe7iIHIM/GO8rIvIssExVf1Hx6IypM8OdOLARk00m5tSOlL/q3wFN9L3e5w/o2+URjoaJjInQ1N5EbGPMbxTf7RFpjxAaH0KaBC/uke5LI44wpmNM3T9nU5yiKhlV9XFV/TxwDP40IjdXNCpjSpQ7WK3QVCL7Yjgj0Icz3UmtZcfsxT3EFRKbEyS3JnHHujgRx++Om0iDS//o8cjkCGOOHkPzIc1oWtG0NkSbjinNkIlDRMaKyFkicj/wJ/wR28dUPDJjilTND+bhjMkYTrKptUzMmlb6Xu4juSVJcnsSL+6hMYUwCEJkSgRNqt/O4SmR/SM4UQdxhMjECOPeNs7GaIxAxbRxPAX8Cviaqj5a2XCMKV01R2YPZ0xGIy4nm4771Ut9r/YhEUFEUBRBSG5PQjdoSkn2JMGD/U7Yj8iESMXGyZj6UkziOERVbbSOqVvV/GAezpiMRhwA6EQd+jb04TT57TGJ1/2ro6YpTagqsZf8No3QpBDN05pJ707DBBqq55gZviFXAATuERFbAdBUVSmNyZX8YM4XR6kj0BtxAKDb5tL7Yi8SEUJjQjhtDt5OD3eMS2privZT2v0FnQLpvrStpTGKVGwFQDOyVLNXUKk9lyr1wVwojn1ZQa9S1Tjl+ht5MY/k5iTRqVFSu1Kku9PgQOuRrbgtLrFwDHdsY1W9NZp674U35AqAQIeqXpu9TUQuBoa7MqBpMOVau7pYg7VZxDf4yaFvk7/eQ9ObmvyxAxX6YC5n20mlBwCW82+Ued7Rg6P0bfSrq1SV5A5/PqqmNzUNeoVX7x94jaDa/2/DUcy1/Fl5yj5V5jhMHat2r6B8PZfUU3qe7aHvlb7+x4+/EqfnuR68mFf0uhn7Gke9zmpbzr9R5nm7zS5NU5sQR9CkokklenCU6LRo3pmA3Ta34bod16NG6IVXqI1jEf7yrjNE5J6sTWMovCSsGWGq3SsoX5tF4o0E6ilumz+GAPCn++7xKla33kiN2uX8G2U/b7fZxZ3qku7zx2tkEnK+KzxbR7w8GqEXXqE2jsyYjUkMXGlvN/5U6GaUqPYHaL42i9TuFO4YFwnviUHCQXtGha4AGqlRe7h/o3xVS4Wed+7+mapCaIwPvEbQCF9YBo1EVV9W1eXAmcBjqvqIqj6CP6X61CrFZ+pApRdBypVvNtnmQ5oJtYbQ5J4OfppUxJWK/UM10qy2w/kbDTZwEsj7vIGCVVGZD7xs9faB1wiq/f82HMWM4/gl8I6s+x7+OuB/V5GITN2pVq+g3MfMrt7wYh7p3jTJLUm01f9w8no8wpPCFf2HKqZRux4ahIfzN0p0JdC0ktiyJ3a31e2vWsp93rFXYgWrohrpCq2e1eL/rVTFJI6Qqva3yqhqQkTqJ/WZqqj1tOBus0vLES3EW+L9vaqiB0UHVJVUU74JAN2xte0BU+rfKLXDX+rVbXJxW1w0qSS6EoRTYTho7/2HqopqhA+8RlHr/7ehFJM4ukRkoareAyAiHwC2VDYsY/bmNru0Ht5K6+GtNY0ju7tk9gSATZGm/g/JRmgQ9nr8hZb6OxtEhHQiPWibRDF17/X+gWfKo5jEcT6wVES+DwiwAfhkRaMyDa/c1TfZ3/C9Hn8lutD4UE2qhbJ7D2mf+n3tk0pqawp3qtswDcJuq0tqW4p0Iu13NEgqpNnrqiLDqqJMRjHrcbwIzBeRtuB+d8WjMg2t0AAmoD+hZCuUXDLn07SS3J5EREhtS+GEHeK95akWKiXRZVfZOFHHb6QPC+le/zk1SoNwaLy/1Ku3228/cpocIpMjOK35Y7eqKJNRzBUHIvJ+YBYQFfEvU1X1a0MccyNwKrBZVY8aZJ8FwHeBMLBFVY8Lytfjd/v1gJSqdgblE/BXIpwOrAc+qqrbi3kOpnoKjvxO4w9scoT4+jiKEp0e7e+hk++DKHO+xJYEbpM/jiOd8FefC7eH97laqNSRutlVNuEJYfpe7YOEX57pAdMI38Ij7RHivXHC7eEBVxCFOhtYVZSB4tbjuB74R+Cf8auq/gE4uIhz3wScXOC844H/Ahaq6qzgvNneraodmaQRuAx4SFUPAx4K7ps6M9iI675Ne0Z9p7alcNtcQm0hUttTBUfHZs6Xjqf7x3FIWPyV5SJCakeK2Csxdq/ZzY5Hd7B7ze6SFnMqdaRudndJJ+oQnuSvReFEnbruspurkbobm/pSzBXHO1R1joisUdUrReQ7wP1DHaSqK0RkeoFdPgbcqaqvBPtvLiKWDwALgts3A8uBLxVxnKmiwRpRgf6Eku5L47T431u8Xq9/W762gcz5+quFIn59vNPkL2Ga3JrECfvJCAe/OiskRVdjlTpwLbfKxm1zGTdjXEN+4NoVhBmOYipi48HvXhF5E5AEppThsQ8H9hOR5SKySkSyG9wV+O+g/Lys8smq+lpw+3Vg8mAnF5HzRGSliKzs6uoqQ7imWIMNYMpMjgd+dZUm/RHhqe0pel/sJbY+VvB8bquL1+eR6k75H/ZjXPpe7yMyOYK3269zD7WFcJtcvw6+yPl9hjNwrRJzY1VDtZbYNSNbMYnj10G10reAJ/HbFm4pw2OHgHnA+4H3Av8qIocH296pqkcD7wMuFJFjcw8OFpcadIEpVb1BVTtVtbO9vb0M4ZpiDVYFkj05XmhCiMSWBLGX/Cm6JSRoTEn3pvf6MMucz21zCe8XRsJCaEIIp9UhPDFMaFzIr7bKrsbKqt4aSiOM1C2HRlz73NSnglVVIuLgtynsAO4QkXuBqKruLMNjbwS2qmoP0CMiK4C5wF9V9VXwq69E5C78Nc5XAG+IyBRVfU1EpgDFVG+ZGhisCiRTxaNJf8LC5pZmHNfBcR0iMyKII3kbu/vPlzMwLUbMvzpoyqnGyqreKibW0dBbyCYhNOVS8L9KVdPAdVn3+8qUNADuBt4pIiERaQHeBqwTkVYRGQMgIq3AScDa4Jh72DPN+1nBOUwDya7iCU8I47bt3bZQyqSF/dVYY1zS8TSp7hRenz/Oo5SrhkateipFI00Tb+pbMY3jD4nIh/Ebsotee1xEbsVvyJ4kIhuBK/C73aKq16vqOhF5AH+m3TTwY1VdKyKHAHcF3X5DwC2q+kBw2n8Dfiki5wIvAx8tNh6zb3LHObhtLl63N6wBfl7MI74hzu7Vu3GjLk0HNqFppW9jH5H9Bx9HkE/21UJoQgivxyPUGsJtc20RoRyNMOuqaQwyVC4Qkd1AK5DCbygX/CaGsZUPrzw6Ozt15cqVtQ6jrhUaAJc9zkEiQmpnivj6OM0zmvvnZ8qMXRjqgzpzrsTWBOlEmuTmJChEp0VRT1FPGTe/MXso1bvcv2MpfzczOonIqpwhEUCBqioR+fvgZruqOqoaUdWxqjqmkZKGGdpQjaa54xwyXVC93V7JK5RlzkUawmPDRKdFcZod+jb1IVEhPDFsH2IVYuM2TLkUqqr6Hn6vpz8BR1cnHFMLQzWa5o5zSMf9MRjp2J668WLnZ8qcKzMmw426RKdGSfemaWpvAvsMqygbt2HKoVDiSIrIDcBUEfle7kZV/WzlwjLVlPkw92Ieqa0pv2trU7BA0kF71407UYd0bxo36h+T3JYktSuF2+L2r/89mMy5+qfqAFQVHBpmqg5jRrtCieNU4AT8MRarqhOOqQUn6o/ATmwOrjxaHLwez/+JeXvNiuq2uiS7krhtLvGNcb+6ynUIjw8XnOPJi/mN6bGXYoTGhAhNCJHamcLb5dH85uaara1hjCnNoIlDVbcAy0Rknao+VcWYTJVF2iPsfHEn4sqe6bWByORIf3VV7hQbY+ePpfe5XkiBO8YlNDGE2+x3gc03LiC7Ybb50GYSbyTo29DnJ4yjLWEY00iK6Y4bE5GH8Kf7OEpE5uBPTPj1CsdmqsRtdglPDOPFPbxefwBc04FN/pVI1upuuckgOTGJe5BLZsZkGLytI7sdxcEhNMMf7Y3rn7sell8dzez1N6UopgP3j4DL8eeoQlXXAGdUMihTfaHxIUJtIb/9Ip722y12pgr28S9ljqdCg89sKozastfflKqYxNGiqo/nlKUqEYypHbfNJb4+TjqWxmn2e0zF18f3GtmdrZQ5ngolmVKnNTflZa+/KVUxiWOLiLyZYEJBEfkI8FrhQ0yj8bo9f0Bf1EVjfjfZ5hnNeN2Df+ssZVxAoSRjU2HUlr3+plTFtHFcCNwAvEVEXgX+BpxZ0ahM1aXjadyxLqFxe94Sqkpya5IYsUHrvguNC8itNw/vH8br9vaaSNCmwqgte/1NqYpZc/wl4IRgwkEH6MVv43i5wrGZKsr34ZHamSK5NUloTGjIJVXzzWWV3JwcsBxrcnNyr2P7u+i+6E+vHpkcwXEdG9NRRbndrbOnIjEmn0JTjowVkctF5PsiciJ+wjgLeAGbXLCulGNxnnxVSYk3EjQd0DRk3Xe+xtXup7rRtBY8tr+Lbtih5bAWBCH2Qox00uZPqiabisSUqtAVx8+B7cCjwKeBr+BPcHi6qq6ufGimGNnjI4a6Kigk35oU4Ylh3LFDL6mad8qSNKS6U4THhwc9Nve45hnNA7ro1tpo6qJqU5GYUhRKHIeo6mwAEfkxfoP4QaoaL3CMqbJyLs6T++GRWSRpqLrvfGt2u2NcUrsHdr7LPbbUtb6rqVwJ2ZiRqFDrVzJzQ1U9YKMljfpTyR4xxXa3zdfVNjQmhDhS8NjhrPVdLdZF1ZjBFfoPnSsiu4Kf3cCczG0R2VWtAE1hlfzwLbbuO1+CQaBtblvBY+t5rW/romrM4ArNVWXX4w2g0j1iiqn7Lrhm94RhHldj1kXVmMEVM47D1LF6+fAdbuNqvTbKWhdVYwZniWMEqOaHb6k9jRq1Z1K9JGRj6lHFrrtF5EYR2Swiawvss0BEVovIMyLySFA2TUQeFpFng/KLs/ZfIiKvBsesFpFTKhX/aDbYuJBSJ8Nr9MnzMgm59fBWmg9qtqRhTKCSVxw3Ad8HfpZvo4iMB/4LOFlVXxGR/YNNKeALqvqkiIwBVonIg6r6bLD9GlX9dgXjrkvV+ObuxTziG+IDRnHjQc9zPbgtrr8ueFj8QYHiDNn1t5xdhY0x9aNiVxyqugLYVmCXjwF3quorwf6bg9+vqeqTwe3dwDrgwErF2Qiq8c098xjJriSh8SEc1yGxKYHX65HckiTZlUQcQRyh79W+/scu1NPIeiYZMzLVsovI4cB+IrJcRFaJyCdzdxCR6cBbgceyii8SkTVBVdh+g51cRM4TkZUisrKrq6vswVdTNcYUZB6DNGhaSW5L0vdaHzv/dycS8keCu1F/0SYn4pDc5g/zKdTTqJ7HaRhjhq+W/8EhYB7wfvx1zf9VRA7PbBSRNuAO4HOqmhk38gPgzUAH/kj27wx2clW9QVU7VbWzvb29Ms+gSqrxzT3zGIrSt7EPPAiNDZHalSLxWgJFCU0M9Y+58GLekOMu6nmchjFm+GqZODYCv1XVnmB98xXAXAARCeMnjaWqemfmAFV9Q1U9VU3jr0x4TA3irrpqfHMf8BgKiqJJxWlz0JQiKrjNLk1TmyCN/zPEZHg2eZ4xI1Mtu+PeDXxfREJABHgbcI34C1j/BFinqv+RfYCITFHVzCJSpwOD9tgaSdw2t3+2WXeMS6jNn86jnGMKMuMW0ok0TVObSG5J4nV7tMxoQdNKOulfNYgjhCeGi04A9TpOwxgzfBVLHCJyK7AAmCQiG4ErgDCAql6vqutE5AFgDf731x+r6loReSfwCeBpEVkdnO7LqnofcLWIdOCvRrge+Eyl4q8XXswjuTlJ0wFNpHan8HZ7JHoStM1tK+s398zVQXJ7knRvmuibooQmhnCbXZI7/PXHbTyDMQZAVHXovRpcZ2enrly5stZhDEvslRh49HdpBfqnHi925b1Suu5mzwqbO2LakoUxo4uIrFLVztxy695S50ptGN/XrrvWLmGMGYpNOVLnSp1srxyD7qxdwhhTiF1x1LlSu7TaoDtjTKVZ4qhzpVYd2aA7Y0ylWVVVAxiq6ii7MRzA6/UIjwvbdODGmIqwr6ENLrcx3Ak7CEI6mbbGbWNMRdgVR4PL1xgeGhcq2F3XGGP2hSWOBpeOp/1ut1kkIv7VRgkadcElY0z1WVVVgytHY3ijL7hkjKkuSxwNrhwz0FZj2nZjTHUNtpJnOVjiaHDlGOltYz+MGVkqXYtgiWMEcJtdIu0RnKhDOp4m0ZUo6Q1iYz+MGVkqXYtgnwwjwL5+u7AFl4wZWSpdi2CJYwTY128XNrGhMSNLpWsRrDvuCFCOLrk2saExI0dmYTagIjNI2BXHCGBtFMaYbJWuRbArjhGg0t8ujDGNp5K1CPaVdASwNgpjTDXZFccIYW0UxphqqegVh4jcKCKbRWRtgX0WiMhqEXlGRB7JKj9ZRJ4TkRdE5LKs8hki8lhQfpuIWJ9RY4ypokpXVd0EnDzYRhEZD/wXsFBVZwH/EJS7wHXA+4AjgUUicmRw2L8D16jqocB24NxKBW+MMWZvFU0cqroC2FZgl48Bd6rqK8H+m4PyY4AXVPUlVU0Ay4APiIgA7wFuD/a7GfhgJWI3xhiTX60bxw8H9hOR5SKySkQ+GZQfCGzI2m9jUDYR2KGqqZzyvYjIeSKyUkRWdnV1VSh8Y4wZfWrdOB4C5gHHA83AoyLyv+U4sareANwA0NnZqUPsbowxpki1Thwbga2q2gP0iMgKYG5QPi1rv6nAq8BWYLyIhIKrjky5McaYKql1VdXdwDtFJCQiLcDbgHXAE8BhQQ+qCHAGcI+qKvAw8JHg+LOCcxhjjKmSil5xiMitwAJgkohsBK4AwgCqer2qrhORB4A1QBr4saquDY69CPgt4AI3quozwWm/BCwTka8DfwZ+UsnnYIwxZiDxv8SPbJ2dnbpy5cpah2GMMQ1FRFapamduea2rqowxxjQYSxzGGGNKYonDGGNMSSxxGGOMKYklDmOMMSWxxGGMMaYkljiMMcaUxBKHMcaYkljiMMYYU5JaT3JYFxKpBCEnhOMUn0fT6TSpdIpIyBYgrDuJBIRCUMLfk3QaUimI2N/T1Dcv5pHoSpCOp3GiDpH2CG6zW9UYRv0VRyKVYOZ1M5n3o3mk0+mijkmn08z70TxmXjeTRCpR4QhNSRIJmDkT5s3zk0Ex0ml//5kz/eONqVNezCP+chw8cFtd8CD+chwv5lU1jlGfOEJOiLHRsax+fXVRySOTNFa/vpqx0bGEHLtoqyuhEIwdC6tXF5c8Mklj9Wr/uJD9PU39SnQlcJocnCYHEem/neiq7heeUZ84HMdh1adX0XFAx5DJIztpdBzQwapPryqpestUgePAqlXQ0TF08shOGh0d/nH29zR1LB1PIxEZUCYRIR0v8uq6TOy/hOKShyWNBlJM8rCkYRqQE3XQxMAZzTWhONHqvnftPyVQKHlY0mhAhZKHJQ3ToCLtEdJ9adJ9aVS1/3akvbqdOuy/JctgycOSRoMaLHlY0jANym12iR4cBRe8Hg9ciB4crXqvKlvIKY/sZJFhSaOBZSeLDEsaxgzJFnIqQebKI5sljQaWufLIZknDmGGz/5w8Mlcc2UoZ52HqTOaKI1sp4zyMMQNULHGIyI0isllE1g6yfYGI7BSR1cHPV4PyI7LKVovILhH5XLBtiYi8mrXtlHLHndum4f2rV1RXXVOncts0PK+4rrrGmEFV8orjJuDkIfb5H1XtCH6+BqCqz2XKgHlAL3BX1jHXZB1zXzkDHqwhvNhxHqbODNYQXuw4D2NMXhVLHKq6Ati2j6c5HnhRVV8uQ0gFFeo9ZcmjARXqPWXJw5h9Uus2jreLyFMicr+IzMqz/Qzg1pyyi0RkTVAVtl85giimy60ljwZSTJdbSx7GDFstE8eTwMGqOhf4T+BX2RtFJAIsBP5fVvEPgDcDHcBrwHcGO7mInCciK0VkZVdX16BBlDJOw5JHAyhlnIYlD2OGpWaJQ1V3qWp3cPs+ICwik7J2eR/wpKq+kXXMG6rqqWoa+BFwTIHz36Cqnara2d7ePmgcqXSKXfFdRY/TyE4eu+K7SKVTRT1fUyWpFOzaVfw4jezksWuXf7wxpqCaTQUqIgcAb6iqisgx+Elsa9Yui8ipphKRKar6WnD3dCBvj61SREIR1l24rqT1ODLJw9bjqEORCKxbV9p6HJnkYetxGFOUiiUOEbkVWABMEpGNwBVAGEBVrwc+AlwgIikgBpyhwTB2EWkFTgQ+k3Paq0WkA1BgfZ7twzKcD3/HcYg49iFTl4bz4e84ljSMKdKomHJERLqA4fbMmgRsKWM45VKPcdVjTFCfcdVjTFCfcdVjTFCfcZU7poNVda+6/lGROPaFiKzMN1dLrdVjXPUYE9RnXPUYE9RnXPUYE9RnXNWKqdbdcY0xxjQYSxzGGGNKYoljaDfUOoBB1GNc9RgT1Gdc9RgT1Gdc9RgT1GdcVYnJ2jiMMcaUxK44jDHGlMQShzHGmJKM+sSRb92QQut+iMjlIvKCiDwnIu+tYky3ZcWzXkRWB+XTRSSWte36SsQUPNY0EXlYRJ4VkWdE5OKgfIKIPCgizwe/9wvKRUS+F7xea0Tk6CrG9C0R+UvwuHeJyPigvOKvV4GYav2+Giyumr63RCQqIo8HE54+IyJXBuUzROSx4HW5LZi/DhFpCu6/EGyfXsWYlgZ/o7XB/2k4KM+7vlAV47pJRP6W9fgdQXll/gdVdVT/AMcCRwNrs8qWAJfk2fdI4CmgCZgBvAi41YgpZ/t3gK8Gt6cPtl8F4poCHB3cHgP8NXhNrgYuC8ovA/49uH0KcD8gwHzgsSrGdBIQCsr/PSumir9eBWKq9fsqb1y1fm8F74+24HYYeCx4v/wSf0YJgOuBC4Lb/we4Prh9BnBbFWM6Jdgm+FMiZWJaANxbw9fqJuAjefavyP/gqL/i0NLWDfkAsExV+1T1b8ALFJhosRIxiYgAH2Xv6eYrTlVfU9Ung9u7gXXAgfivy83BbjcDHwxufwD4mfr+FxgvIlOqEZOq/reqZmYs/F9gajkfdzgxFTikWu+rgnHV6r0VvD+6g7vh4EeB9wC3B+W576vM++124Pgg9orHpKr3BdsUeJwqvq8KxVXgkIr8D476xFFAvnU/DgQ2ZO2zkcIfCJXwLvzJIZ/PKpshIn8WkUdE5F3VCCKoHngr/jeeybpn8snXgcnB7aq+XjkxZTsH/1tXRtVerzwx1cX7apDXqmbvLRFxgyqyzcCD+FddO7KSf/Zr0v96Bdt3AhMrHZOqPpa1LQx8Angg65Ch1heqdFxXBe+ta0SkKSiryHvLEkd+Ra/7UQO5swa/Bhykqm8FPg/cIiJjKxmAiLQBdwCfU9Vd2duCb2JV7+M9WEwi8hUgBSwNiqr2euWJqS7eVwX+fjV7b6m/XEIH/jf4Y4C3VOJxSpEbk4gclbX5v4AVqvo/wf2C6wtVIa7L8V+zvwMmAF+q1OODJY68dPB1P14FpmXtOjUoqwoRCQEfAm7LirVPVbcGt1fhf1M7vIIxhPE/dJaq6p1B8RuZy9/g9+agvCqv1yAxISKfAk4FzgwSWtVer3wx1cP7qsBrVfP3VvA4O4CHgbfjV6tkZvDOfk36X69g+zgGLslQqZhODh7zCqAdP5lm9hlqfaGKxhVUQ6qq9gE/pcLvLUsceeTUAWav+3EPcEbQq2MGcBh+PWe1nAD8RVU3ZgpEpF1E3OD2IUFML1XiwYN65J8A61T1P7I23QOcFdw+C7g7q/yTQc+O+cDOrCqtisYkIicDlwILVbU3q7zir1eBmGr6virw94MavreCxxkf3G7GX1JhHf6H4keC3XLfV5n320eA32e+GFQ4pr+IyD8B7wUWBV8AMvsfkGlnkfzrC1U6rswXN8FvC8p+b5X/fzBfi/lo+sG/NH8NSOLX/50L/Bx4GlgTvPBTsvb/Cv43r+eA91UrpqD8JuD8nH0/DDwDrMa/XD6tgq/VO/GrodYEj7cav9fGROAh4Hngd8CEYH8Brgter6eBzirG9AJ+3W6mLNMLp+KvV4GYav2+yhtXrd9bwBzgz0Fca9nTq+sQ/AT6Av4S0k1BeTS4/0Kw/ZAqxpQK/k6Z1y9TflHwWj2F3xnjHVV+rX4fvLfWAr9gT8+rivwP2pQjxhhjSmJVVcYYY0piicMYY0xJLHEYY4wpiSUOY4wxJbHEYYwxpiSWOIwJiIgn/syia0Xk15n+8iUcv1xEOoPb95V6/CDnfKuI/GRfzxOc61QR+Vo5zmVGN0scxuwRU9UOVT0Kf5LJC4d7IlU9Rf2Rvfvqy8D3ynAegN8Ap4lIS5nOZ0YpSxzG5PcowWRwInKMiDwaTPb3JxE5IihvFpFlIrJORO4CmjMHi7+uxSTx17TIXlflEhFZEtz+rPhrY6wRkWW5AYjIGGCOqj4V3F8i/uSIy0XkJRH5bFA+Xfy1R24Skb+Kv2bECSLyR/HXSDkG+ucRW44/DYsxwxYaehdjRpdgmo3j8afnAPgL8C5VTYnICcA38EdVXwD0qupMEZmDP7q6FJcBM1S1b5BqrU72TB2R8Rbg3fjraTwnIj8Iyg8F/gF/JuAngI/hjxRfiH/V8sFgv5X4s+D+ssRYjelnicOYPZrFn676QPy5kh4MyscBN4vIYfhTdoSD8mMJqpFUdY2IrCnx8dYAS0XkV+SfTXUK0JVT9hv1J7LrE5HN7JnC/m+q+jSAiDwDPKSqKiJP4y/IlLEZeFOJcRozgFVVGbNHTP3pqg/Gn+Mn08bxf4GHg7aP0/DnSipWioH/Z9nHvh9/HqGjgSeyZoLtjyfPY/Vl3fbY8+UvuzyddT/NwC+I0eC8xgybJQ5jcqg/m+5ngS9kTdudmYr6U1m7rsCvEkL8NRHm5DndG8D+IjJR/MV1Tg32d4Bpqvow/toJ44C2nGPX4VdBldPh7F39ZUxJLHEYk4eqZmYgXYS/pvo3ReTPDPz2/gOgTUTWAV8DVuU5TzLY9jh+1ddfgk0u8IugKunPwPdye2Gp6l+AcUEjebm8G793lTHDZrPjGlPHRGQxsFtVf1yGc00GblHV4/c9MjOa2RWHMfXtBwxsv9gXBwFfKNO5zChmVxzGGGNKYlccxhhjSmKJwxhjTEkscRhjjCmJJQ5jjDElscRhjDGmJP8ffAQfPENzI6kAAAAASUVORK5CYII=", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "predictions = np.array([\n", - " np.mean(\n", - " model.predict(\n", - " np.array(experimental_data[idx])\n", - " ),\n", - " axis=0\n", - " ) for idx in range(len(experimental_data))\n", - "])\n", - "\n", - "print(np.mean(predictions))\n", - "plt.scatter([],[], c='b', alpha=1)\n", - "plt.scatter(0.227 * 1000, 1.58, marker='x', s=200, c='r')\n", - "plt.scatter(0.15 * 1000, 1.58, marker='x', s=200, c='g')\n", - "\n", - "plt.scatter(predictions[:, 0] * 100, predictions[:, 1] / 10 + 1.33, c='m', alpha=0.1)\n", - "plt.scatter(0.227 * 1000, 1.58, marker='x', s=200, c='r')\n", - "plt.scatter(0.15 * 1000, 1.58, marker='x', s=200, c='g')\n", - "\n", - "\n", - "plt.legend([\"Model prediction\", \"150nm PSL\", \"227nm PSL\"])\n", - "# plt.axis([100, 300, 1.4, 1.7])\n", - "plt.xlabel('Radius (nm)')\n", - "plt.ylabel('Refractive index')\n", - "plt.show()" + "data": { + "image/png": "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", + "text/plain": [ + "
" ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3", - "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": "3.10.5" + }, + "metadata": {}, + "output_type": "display_data" } + ], + "source": [ + "def predict_images(images):\n", + " images = np.asarray(images, dtype=np.float32)\n", + " if images.ndim == 3:\n", + " images = images[None, ...]\n", + "\n", + " if images.shape[-1] == 2:\n", + " model_images = np.stack(\n", + " [make_model_channels(image) for image in images],\n", + " axis=0,\n", + " )\n", + " elif images.shape[-1] == 4:\n", + " model_images = images\n", + " else:\n", + " raise ValueError(f\"Expected images with 2 or 4 channels, got {images.shape}\")\n", + "\n", + " tensor = torch.from_numpy(np.moveaxis(model_images, -1, 1)).to(regressor.device)\n", + " regressor.eval()\n", + " with torch.no_grad():\n", + " return regressor(tensor).cpu().numpy()\n", + "\n", + "\n", + "if experimental_data is not None:\n", + " predictions = np.array(\n", + " [np.mean(predict_images(experimental_data[idx]), axis=0) for idx in range(len(experimental_data))]\n", + " )\n", + "\n", + " radius_nm, refractive_index = decode_label(predictions)\n", + "\n", + " plt.figure(figsize=(6, 5))\n", + " plt.scatter(radius_nm, refractive_index, c=\"m\", alpha=0.1, label=\"Model prediction\")\n", + " plt.scatter(227, 1.58, marker=\"x\", s=200, c=\"r\", label=\"227 nm PSL\")\n", + " plt.scatter(150, 1.58, marker=\"x\", s=200, c=\"g\", label=\"150 nm PSL\")\n", + " plt.xlabel(\"Radius (nm)\")\n", + " plt.ylabel(\"Refractive index\")\n", + " plt.legend()\n", + " plt.show()\n", + "else:\n", + " print(\"No experimental predictions to display.\")" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": ".venv312", + "language": "python", + "name": "python3" }, - "nbformat": 4, - "nbformat_minor": 2 + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.12.13" + } + }, + "nbformat": 4, + "nbformat_minor": 5 }