VAE_without_KLD_Loss.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Variational Auto-Encoder without the KL Divergence Loss\n",
    "\n",
    "## Importing required packages"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import torch\n",
    "from torch.autograd import Variable\n",
    "import numpy as np\n",
    "import torch.nn.functional as F\n",
    "import torchvision\n",
    "from torchvision import transforms\n",
    "import torch.optim as optim\n",
    "from torch import nn\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Defining the model\n",
    "\n",
    "Model is same as that in [this notebook](https://github.com/ac-alpha/VAEs-using-Pytorch/blob/master/VAE_two_latent_variables.ipynb)\n",
    "\n",
    "<img src=\"Architecture_2_latent.png\" width=\"800\" />"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "class VAE(nn.Module):\n",
    "  \n",
    "    def __init__(self):\n",
    "        super(VAE, self).__init__()\n",
    "        \n",
    "        self.fc1 = nn.Linear(28*28, 400)\n",
    "        self.fc2_mu = nn.Linear(400, 2)\n",
    "        self.fc2_sig = nn.Linear(400, 2)\n",
    "        self.fc3 = nn.Linear(2, 400)\n",
    "        self.fc4 = nn.Linear(400, 784)\n",
    "  \n",
    "    def encode(self,x):\n",
    "        a1 = F.relu(self.fc1(x))\n",
    "        a_mu = self.fc2_mu(a1)\n",
    "        a_logvar = self.fc2_sig(a1)\n",
    "        return a_mu, a_logvar\n",
    "  \n",
    "    def decode(self,z):\n",
    "        a3 = F.relu(self.fc3(z))\n",
    "        return torch.sigmoid(self.fc4(a3))\n",
    "  \n",
    "    def reparameterize(self, mu, logvar):\n",
    "        std = torch.exp(0.5*logvar)\n",
    "        eps = torch.randn_like(std)\n",
    "        return eps.mul(std).add_(mu)\n",
    "  \n",
    "    def forward(self,x):\n",
    "        mu, logvar = self.encode(x.view(-1, 784))\n",
    "        z = self.reparameterize(mu, logvar)\n",
    "        return self.decode(z), mu, logvar\n",
    "    "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Getting the Dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "train_dataset = torchvision.datasets.MNIST(root='./data',train=True, transform=transforms.ToTensor(), download=True)\n",
    "test_dataset = torchvision.datasets.MNIST(root='./data',train=False, transform=transforms.ToTensor(),download = True)\n",
    "\n",
    "train_loader = torch.utils.data.DataLoader(dataset=train_dataset, batch_size=100, shuffle=True)\n",
    "test_loader = torch.utils.data.DataLoader(dataset=test_dataset,  batch_size=100, shuffle=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Instantiating the model and optimizer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "model = VAE()\n",
    "optimizer = optim.Adam(model.parameters(), lr=1e-3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Loss function\n",
    "\n",
    "Note that here we are not using the KL Divergence loss which tries to make the learned distribution similar to a known distribution."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "def loss_function(recon_x, x, mu, logvar):\n",
    "    BCE = F.binary_cross_entropy(recon_x, x.view(-1, 784), reduction='sum')\n",
    "\n",
    "    KLD = -0.5 * torch.sum(1 + logvar - mu.pow(2) - logvar.exp())\n",
    "\n",
    "    return BCE #+ KLD"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Training"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch : 1 , Minibatch : 0 Loss = 55040.9453\n",
      "Epoch : 1 , Minibatch : 100 Loss = 2241288.2871\n",
      "Epoch : 1 , Minibatch : 200 Loss = 1799062.6445\n",
      "Epoch : 1 , Minibatch : 300 Loss = 1745574.5010\n",
      "Epoch : 1 , Minibatch : 400 Loss = 1712695.8926\n",
      "Epoch : 1 , Minibatch : 500 Loss = 1674243.9424\n",
      "Epoch 1 : Loss = (10851618.1094) \n",
      "Epoch : 2 , Minibatch : 0 Loss = 15566.7969\n",
      "Epoch : 2 , Minibatch : 100 Loss = 1618999.1943\n",
      "Epoch : 2 , Minibatch : 200 Loss = 1615607.1182\n",
      "Epoch : 2 , Minibatch : 300 Loss = 1601520.3428\n",
      "Epoch : 2 , Minibatch : 400 Loss = 1584125.4404\n",
      "Epoch : 2 , Minibatch : 500 Loss = 1575959.9180\n",
      "Epoch 2 : Loss = (9564680.2617) \n",
      "Epoch : 3 , Minibatch : 0 Loss = 16401.4082\n",
      "Epoch : 3 , Minibatch : 100 Loss = 1556360.7490\n",
      "Epoch : 3 , Minibatch : 200 Loss = 1559325.3047\n",
      "Epoch : 3 , Minibatch : 300 Loss = 1549976.8145\n",
      "Epoch : 3 , Minibatch : 400 Loss = 1553301.0576\n",
      "Epoch : 3 , Minibatch : 500 Loss = 1538436.6943\n",
      "Epoch 3 : Loss = (9296820.6152) \n",
      "Epoch : 4 , Minibatch : 0 Loss = 14562.6650\n",
      "Epoch : 4 , Minibatch : 100 Loss = 1529751.6143\n",
      "Epoch : 4 , Minibatch : 200 Loss = 1528058.3838\n",
      "Epoch : 4 , Minibatch : 300 Loss = 1529120.1611\n",
      "Epoch : 4 , Minibatch : 400 Loss = 1520833.2881\n",
      "Epoch : 4 , Minibatch : 500 Loss = 1524602.1328\n",
      "Epoch 4 : Loss = (9149690.6836) \n",
      "Epoch : 5 , Minibatch : 0 Loss = 15056.2744\n",
      "Epoch : 5 , Minibatch : 100 Loss = 1513673.1523\n",
      "Epoch : 5 , Minibatch : 200 Loss = 1513642.1396\n",
      "Epoch : 5 , Minibatch : 300 Loss = 1501770.2441\n",
      "Epoch : 5 , Minibatch : 400 Loss = 1506215.0820\n",
      "Epoch : 5 , Minibatch : 500 Loss = 1501897.0527\n",
      "Epoch 5 : Loss = (9041990.2998) \n"
     ]
    }
   ],
   "source": [
    "num_epochs = 5\n",
    "print_per = 100\n",
    "model.train()\n",
    "for epoch in range(num_epochs):\n",
    "    train_loss = 0\n",
    "    print_loss = 0\n",
    "    loss_record = []\n",
    "    for i, (images, _) in enumerate(train_loader):\n",
    "        images = images.reshape(-1, 28*28)\n",
    "        optimizer.zero_grad()\n",
    "        recon_batch, mu, logvar = model(images)\n",
    "        loss = loss_function(recon_batch, images, mu, logvar)\n",
    "        loss.backward()\n",
    "        train_loss += loss.item()\n",
    "        print_loss += loss.item()\n",
    "        optimizer.step()\n",
    "        if (i%print_per == 0):\n",
    "            print(\"Epoch : {} , Minibatch : {} Loss = {:.4f}\".format(epoch+1, i, print_loss))\n",
    "            loss_record.append(print_loss)\n",
    "            print_loss = 0\n",
    "    print(\"Epoch {} : Loss = ({:.4f}) \".format(epoch+1, train_loss))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(784,)\n",
      "torch.Size([784])\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(model(images)[0].data[0].numpy().shape)\n",
    "image1 = images[8]\n",
    "print(image1.shape)\n",
    "plt.imshow(model(images)[0].data[8].numpy().reshape(28, 28), cmap='gray')\n",
    "plt.show(block=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Testing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "test_loss = 0\n",
    "print_per = 10\n",
    "with torch.no_grad():\n",
    "    for i, (images, _) in enumerate(test_loader):\n",
    "        images = images.reshape(-1, 28*28)\n",
    "        recon_batch, mu, logvar = model(images)\n",
    "        test_loss += loss_function(recon_batch, images, mu, logvar).item()\n",
    "        if (i%print_per == 0):\n",
    "            plt.imshow(model(images)[0].data[0].numpy().reshape(28, 28), cmap='gray')\n",
    "            plt.show(block=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "torch.Size([784])\n"
     ]
    }
   ],
   "source": [
    "image2 = images[1]\n",
    "print(image2.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.imshow(model(images)[0].data[1].numpy().reshape(28, 28), cmap='gray')\n",
    "plt.show(block=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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RfiCo/wJoRYsGzyE3jwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.imshow(images[1].numpy().reshape(28, 28), cmap='gray')\n",
    "plt.show(block=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Experiments"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "with torch.no_grad():\n",
    "    mu1, logvar1 = model.encode(image1)\n",
    "    std1 = torch.exp(0.5*logvar1)\n",
    "    mu2, logvar2 = model.encode(image2)\n",
    "    std2 = torch.exp(0.5*logvar2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "with torch.no_grad():\n",
    "    recon_images1 = []\n",
    "    for ctr in range(0, 100, 5):\n",
    "        eps_val = torch.full_like(mu1, fill_value = ctr * 0.01 )\n",
    "        z_val1 = eps_val.mul(std1).add_(mu1)\n",
    "        recon_image1 = model.decode(z_val1)\n",
    "        recon_images1.append(recon_image1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 6. Here we see that,  the values of z constructed the same image\n",
    "\n",
    "See other experiments [here](https://github.com/ac-alpha/VAEs-using-Pytorch/blob/master/VAE.ipynb) and [here](https://github.com/ac-alpha/VAEs-using-Pytorch/blob/master/VAE_two_latent_variables.ipynb)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "tensor([ 0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,\n",
      "         0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,\n",
      "         0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,\n",
      "         0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,\n",
      "         0.0000,  0.0000,  0.0000,  0.0000, -0.0000, -0.0000, -0.0000, -0.0000,\n",
      "        -0.0000, -0.0000, -0.0000, -0.0000, -0.0000, -0.0000, -0.0000, -0.0000,\n",
      "        -0.0000, -0.0000, -0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,\n",
      "         0.0000,  0.0000,  0.0000,  0.0000, -0.0000, -0.0000, -0.0000, -0.0000,\n",
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      "         0.0000,  0.0000, -0.0000, -0.0000, -0.0000, -0.0000, -0.0000, -0.0000,\n",
      "        -0.0000, -0.0000, -0.0000, -0.0000,  0.0000,  0.0000,  0.0000,  0.0000,\n",
      "         0.0000,  0.0000,  0.0000, -0.0000, -0.0000, -0.0000, -0.0000, -0.0000,\n",
      "        -0.0000, -0.0000, -0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,\n",
      "         0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,\n",
      "         0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,\n",
      "        -0.0000, -0.0000, -0.0000, -0.0000, -0.0000, -0.0000,  0.0000,  0.0000,\n",
      "         0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,\n",
      "         0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,\n",
      "         0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,\n",
      "         0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,\n",
      "         0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,\n",
      "         0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,\n",
      "         0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,\n",
      "         0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,\n",
      "         0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,\n",
      "         0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,\n",
      "         0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,\n",
      "         0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,\n",
      "         0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,\n",
      "         0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000])\n"
     ]
    }
   ],
   "source": [
    "print(recon_images1[0] - recon_images1[1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 2016x2016 with 20 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig=plt.figure(figsize=(28, 28))\n",
    "columns = 4\n",
    "rows = 5\n",
    "for i in range(1, columns*rows +1):\n",
    "    img = recon_images1[i-1].detach().numpy().reshape(28, 28)\n",
    "    fig.add_subplot(rows, columns, i)\n",
    "    plt.imshow(img, cmap=\"gray\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "eps_any = torch.randn_like(mu1)\n",
    "z1 = eps_any.mul(std1).add_(mu1)\n",
    "z2 = eps_any.mul(std2).add_(mu2)\n",
    "all_recons = []\n",
    "for i in range(20):\n",
    "    z_bet = z1 + torch.full_like(mu1, fill_value = 0.05*i).mul(z2 - z1)\n",
    "    recon_image = model.decode(z_bet)\n",
    "    all_recons.append(recon_image)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 2016x2016 with 20 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig=plt.figure(figsize=(28, 28))\n",
    "columns = 4\n",
    "rows = 5\n",
    "for i in range(1, columns*rows +1):\n",
    "    img = all_recons[i-1].detach().numpy().reshape(28, 28)\n",
    "    fig.add_subplot(rows, columns, i)\n",
    "    plt.imshow(img, cmap=\"gray\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 7. Here in the scatter plot we see that the points belonging to a single digit are pretty far from one other. So, while transitioning from one digit to another in the latent space,  we will sample a lot of noise."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "test_dataset = torchvision.datasets.MNIST(root='./data',train=False, transform=transforms.ToTensor(),download = True)\n",
    "test_loader = torch.utils.data.DataLoader(dataset=test_dataset,  batch_size=2000, shuffle=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "x_set, y_set = next(iter(test_loader))\n",
    "x_set = x_set.reshape(-1, 28*28)\n",
    "z_set = model.encode(x_set)[0].detach().numpy()\n",
    "color = y_set"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(8,6))\n",
    "plt.scatter(z_set[:, 0], z_set[:, 1], c=color, cmap = \"viridis\")\n",
    "plt.colorbar()\n",
    "plt.grid()"
   ]
  }
 ],
 "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": "3.6.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}