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ci: Remove unused dependency from demo image #113

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Oct 18, 2024
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ci: Remove unused dependency from demo image #113

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ci: Remove unused dependency from demo image
xeniape Oct 18, 2024
d83e4a7
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xeniape Oct 18, 2024
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3 changes: 1 addition & 2 deletions demos/signal-processing/requirements.txt
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Original file line number Diff line number Diff line change
@@ -1,3 +1,2 @@
psycopg2-binary==2.9.9
tsfresh==0.20.1
alibi-detect==0.11.4
alibi-detect==0.11.4
19 changes: 9 additions & 10 deletions stacks/signal-processing/tsdb.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -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"
]
},
Expand Down Expand Up @@ -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",
Expand All @@ -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"
]
Expand Down