Add requirements.txt

Timeseries_clustering.ipynb

@@ -68,16 +68,9 @@
     "from vrae.vrae import VRAE\n",
     "from vrae.utils import *\n",
     "import numpy as np\n",
-    "from sklearn.manifold import TSNE\n",
-    "from sklearn.decomposition import TruncatedSVD\n",
-    "from random import randint\n",
-    "import pandas as pd\n",
     "import torch\n",
     "\n",
-    "from plotly.graph_objs import *\n",
     "import plotly\n",
-    "import matplotlib\n",
-    "from numpy import genfromtxt\n",
     "from torch.utils.data import DataLoader, TensorDataset\n",
     "plotly.offline.init_notebook_mode()"
    ]

requirements.txt

@@ -0,0 +1,7 @@
+matplotlib==3.0.2
+numpy==1.15.4
+plotly==3.4.2
+scikit-learn==0.20.1
+scipy==1.1.0
+torch==1.0.0
+torchvision==0.2.1

vrae/utils.py

@@ -3,17 +3,11 @@
 import numpy as np
 from random import randint
 import os
-from torch.utils.data import DataLoader, TensorDataset
-import math
-import torch
-import pandas as pd
 import matplotlib.pyplot as plt
 
 from plotly.graph_objs import *
 import plotly
 
-from sklearn.metrics import mean_squared_error
-
 
 def plot_clustering(z_run, labels, engine ='plotly', download = False, folder_name ='clustering'):
     """