From 6b21d1a5a39c6eccc0d78092f27ad1fa2042eea5 Mon Sep 17 00:00:00 2001
From: lorenz <stu203404@mail.uni-kiel.de>
Date: Thu, 11 Mar 2021 01:56:53 +0100
Subject: [PATCH] Fixed old python scripts
---
slope-evaluator/api.py | 36 +++++++++++++++++--------
slope-evaluator/trend_slope_computer.py | 3 ++-
2 files changed, 27 insertions(+), 12 deletions(-)
diff --git a/slope-evaluator/api.py b/slope-evaluator/api.py
index e3fa5b74c..927c454fe 100644
--- a/slope-evaluator/api.py
+++ b/slope-evaluator/api.py
@@ -1,25 +1,30 @@
-from fastapi import FastAPI
+from fastapi import FastAPI,Request
import trend_slope_computer as trend_slope_computer
import logging
import os
import pandas as pd
+import json
+import numpy as np
+from fastapi.encoders import jsonable_encoder
app = FastAPI()
+def execute(results, threshold):
-@app.get("/evaluate-slope")
-def evaluate_slope(total_lag):
- print("request received")
- print(total_lag)
- execute(total_lag, 1000)
- return {"suitable" : "false"}
-
+ d = []
+ for result in results:
+ #print(results)
+ group = result['metric']['group']
+ for value in result['values']:
+ # print(value)
+ d.append({'group': group, 'timestamp': int(
+ value[0]), 'value': int(value[1]) if value[1] != 'NaN' else 0})
+ df = pd.DataFrame(d)
-def execute(total_lag, threshold):
- df = pd.DataFrame(total_lag)
+ print(df)
try:
- trend_slope = trend_slope_computer.compute(df, 60)
+ trend_slope = trend_slope_computer.compute(df, 0)
except Exception as e:
err_msg = 'Computing trend slope failed'
print(err_msg)
@@ -30,3 +35,12 @@ def execute(total_lag, threshold):
print(f"Trend Slope: {trend_slope}")
return trend_slope < threshold
+
+@app.post("/evaluate-slope",response_model=bool)
+async def evaluate_slope(request: Request):
+ print("request received")
+ x = json.loads(await request.body())
+ #x = np.array(x['total_lag'])
+ y = execute(x['total_lag'], 1000)
+ print(print(y))
+ return y
diff --git a/slope-evaluator/trend_slope_computer.py b/slope-evaluator/trend_slope_computer.py
index ea6e7bacd..c128d9f48 100644
--- a/slope-evaluator/trend_slope_computer.py
+++ b/slope-evaluator/trend_slope_computer.py
@@ -2,7 +2,8 @@ from sklearn.linear_model import LinearRegression
import pandas as pd
import os
-def compute(input, warmup_sec):
+def compute(x, warmup_sec):
+ input = x
input['sec_start'] = input.loc[0:, 'timestamp'] - input.iloc[0]['timestamp']
regress = input.loc[input['sec_start'] >= warmup_sec] # Warm-Up
--
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