55 lines
1.7 KiB
Python
55 lines
1.7 KiB
Python
import pandas as pd
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import numpy as np
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class DiagramParser:
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def __init__(self, scaler = 1):
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self.data = pd.DataFrame({})
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self.scaler = scaler
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def setData(self, path):
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self.data = pd.read_csv(path)
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def getBoolDict (self):
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boolDict = {}
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for signalName in self.data.columns:
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if type (self.data[signalName].iloc[0]) == np.bool:
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boolDict[signalName] = self._getBoolChanges(signalName)
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return boolDict
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def getFloatDict (self):
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floatDict = {}
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for signalName in self.data.columns:
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if type (self.data[signalName].iloc[0]) == np.float64:
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floatDict[signalName] = self._getFloatChanges(signalName)
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return floatDict
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def _getBoolChanges(self, signalName):
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timeCode = self.data['time']
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signal_values = self.data[signalName]
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changes = []
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if len(signal_values) > 0:
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changes.append([float(timeCode.iloc[0]), 'high' if bool(signal_values.iloc[0]) else 'low'])
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for i in range(1, len(signal_values)):
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if signal_values.iloc[i] != signal_values.iloc[i - 1]:
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changes.append([float(timeCode.iloc[i])*self.scaler, 'high' if bool(signal_values.iloc[i]) else 'low'])
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return changes
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def _getFloatChanges(self, signalName):
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timeCode = self.data['time']
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signal_values = self.data[signalName]
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changes = []
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if len(signal_values) > 0:
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for i in range (len(signal_values)):
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changes.append([float(timeCode.iloc[i]), float(signal_values.iloc[i])])
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return changes
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