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Merge pull request #53 from phylax2020/master
Missing string conversion of value in log_data function.
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commit
82e2c1b61a
1 changed files with 19 additions and 8 deletions
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@ -42,7 +42,7 @@ class LogController:
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self.datalogger[name] = data_logger
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formatted_time = strftime("%Y-%m-%d %H:%M:%S", localtime())
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self.datalogger[name].info("%s,%s" % (formatted_time, value))
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self.datalogger[name].info("%s,%s" % (formatted_time, str(value)))
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if self.influxdb == "Yes":
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self.influxdbcloud = self.cbpi.config.get("INFLUXDBCLOUD", "No")
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self.influxdbaddr = self.cbpi.config.get("INFLUXDBADDR", None)
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@ -116,28 +116,36 @@ class LogController:
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for name in names:
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# get all log names
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all_filenames = glob.glob('./logs/sensor_%s.log*' % name)
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# concat all logs
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df = pd.concat([pd.read_csv(f, parse_dates=True, date_parser=dateparse, index_col='DateTime', names=['DateTime', name], header=None) for f in all_filenames])
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logging.info("Read all files for {}".format(names))
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# resample if rate provided
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if sample_rate is not None:
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df = df[name].resample(sample_rate).max()
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logging.info("Sampled now for {}".format(names))
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df = df.dropna()
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# if sample_rate is not None:
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# df = df[name].resample(sample_rate).max()
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# logging.info("Sampled now for {}".format(names))
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df = df[name].dropna()
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# take every nth row so that total number of rows does not exceed max_rows * 2
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max_rows = 500
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total_rows = df.shape[0]
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if (total_rows > 0) and (total_rows > max_rows):
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nth = int(total_rows/max_rows)
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if nth > 1:
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df = df.iloc[::nth]
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if result is None:
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result = df
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else:
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result = pd.merge(result, df, how='outer', left_index=True, right_index=True)
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data = {"time": df.index.tolist()}
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if len(names) > 1:
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for name in names:
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data[name] = result[name].interpolate(limit_direction='both', limit=10).tolist()
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else:
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data[name] = result.interpolate().tolist()
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logging.info("Send Log for {}".format(names))
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return data
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async def get_data2(self, ids) -> dict:
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@ -146,7 +154,10 @@ class LogController:
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result = dict()
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for id in ids:
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df = pd.read_csv("./logs/sensor_%s.log" % id, parse_dates=True, date_parser=dateparse, index_col='DateTime', names=['DateTime',"Values"], header=None)
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# df = pd.read_csv("./logs/sensor_%s.log" % id, parse_dates=True, date_parser=dateparse, index_col='DateTime', names=['DateTime',"Values"], header=None)
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# concat all logs
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all_filenames = glob.glob('./logs/sensor_%s.log*' % id)
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df = pd.concat([pd.read_csv(f, parse_dates=True, date_parser=dateparse, index_col='DateTime', names=['DateTime', 'Values'], header=None) for f in all_filenames])
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result[id] = {"time": df.index.astype(str).tolist(), "value":df.Values.tolist()}
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return result
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