ci: Remove unused dependency from demo image (#113)

* ci: Remove unused dependency from demo image

* linter

Author: xeniape

demos/signal-processing/requirements.txt

@@ -1,3 +1,2 @@
 psycopg2-binary==2.9.9
-tsfresh==0.20.1
-alibi-detect==0.11.4
+alibi-detect==0.11.4

stacks/signal-processing/tsdb.ipynb

@@ -10,7 +10,6 @@
     "# The following libraries have already been included in the jupyter image: see here demos/signal-processing/Dockerfile-jupyter\n",
     "# These are just left in as examples to show how other libraries can be added.\n",
     "#!pip install psycopg2-binary\n",
-    "#!pip install -U tsfresh\n",
     "#!pip install alibi-detect"
    ]
   },
@@ -103,18 +102,18 @@
     "while True:\n",
     "    clear_output(wait=True)\n",
     "    display('Iteration: '+str(i))\n",
-    "    \n",
+    "\n",
     "    sql = f\"\"\"\\\n",
     "            SELECT time, {', '.join(cols)}\n",
-    "            from conditions \n",
+    "            from conditions\n",
     "            where (timestamp '{last_time}' = timestamp '1970-01-01' or time > timestamp '{last_time}') and time < now()\n",
-    "            order by time asc \n",
+    "            order by time asc\n",
     "            limit 1000\n",
     "    \"\"\"\n",
-    "    \n",
+    "\n",
     "    df = pd.read_sql_query(sql, engine)\n",
     "    df_scores = df[['time']].copy()\n",
-    "    \n",
+    "\n",
     "    od = SpectralResidual(\n",
     "        threshold=1.,\n",
     "        window_amp=20,\n",
@@ -125,21 +124,21 @@
     "        n_est_points=10,\n",
     "        n_grad_points=5\n",
     "    )\n",
-    "    \n",
+    "\n",
     "    for col in cols:\n",
     "        result = od.predict(\n",
     "            df[col].to_numpy(),\n",
     "            t=None,\n",
     "            return_instance_score=True\n",
     "        )\n",
     "        df_scores[col+'_score'] = result['data']['instance_score'].tolist()\n",
-    "    \n",
+    "\n",
     "    df_scores.to_sql('scores_sr', engine, index=False, if_exists='append')\n",
-    "    \n",
+    "\n",
     "    # get last timestamp to use for next offset\n",
     "    last_time = pd.to_datetime(df.time.tail(1).values[0]).strftime('%Y-%m-%d %H:%M:%S.%f %Z')\n",
     "    print(f'Next offset: {last_time}, fetched: {df_scores.r1_score.size}')\n",
-    "    \n",
+    "\n",
     "    time.sleep(12)\n",
     "    i += 1"
    ]