A DataSeriesFilter is a pyalgotrade.dataseries.DataSeries instance that decorates another pyalgotrade.dataseries.DataSeries instance to make some calculations with the values from the DataSeries being decorated.
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Note
This is a base class and should not be used directly.
This method has to be overriden to add the filtering logic and return a new value.
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Returns the pyalgotrade.dataseries.DataSeries being filtered.
Returns the window size.
Creating a custom filter is easy:
from pyalgotrade import dataseries
from pyalgotrade import technical
class Accumulator(technical.DataSeriesFilter):
def __init__(self, dataSeries, windowSize):
technical.DataSeriesFilter.__init__(self, dataSeries, windowSize)
def calculateValue(self, firstPos, lastPos):
accum = 0
for value in self.getDataSeries()[firstPos:lastPos+1]:
# If any value from the wrapped DataSeries is None then we abort calculation and return None.
if value is None:
return None
accum += value
return accum
# Build a sequence based DataSeries.
ds = dataseries.SequenceDataSeries(range(0, 50))
# Wrap it with a 3 element Accumulator filter.
ds = Accumulator(ds, 3)
# Get some values.
print ds[0] # Not enough values yet.
print ds[1] # Not enough values yet.
print ds[2] # Ok, now we should have at least 3 values.
print ds[3]
# Get the last value, which should equals 49 + 48 + 47.
print ds[-1]
The output should be:
None
None
3
6
144
Simple Moving Average filter.
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Exponential Moving Average filter.
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Weighted Moving Average filter.
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Volume Weighted Average Price filter.
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Relative Strength Index filter as described in http://stockcharts.com/school/doku.php?id=chart_school:technical_indicators:relative_strength_index_rsi.
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Stochastic Oscillator filter as described in http://stockcharts.com/school/doku.php?id=chart_school:technical_indicators:stochastic_oscillato. Note that the value returned by this filter is %K. To access %D use getD().
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Returns a pyalgotrade.dataseries.DataSeries with the %D values.
Rate of change filter as described in http://stockcharts.com/school/doku.php?id=chart_school:technical_indicators:rate_of_change.
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The Slope filter calculates the slope of the least-squares regression line.
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Checks for a cross above conditions over the specified period between two DataSeries objects.
It returns the number of times ds1 crossed above ds2 during the given period.
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Checks for a cross below conditions over the specified period between two DataSeries objects.
It returns the number of times ds1 crossed below ds2 during the given period.
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A line in a line break chart.
The datetime.
The high value.
The low value.
True if the line is black (falling prices).
True if the line is white (rising prices).
Line Break filter as described in http://stockcharts.com/help/doku.php?id=chart_school:chart_analysis:three_line_break . This is a DataSeries of Line instances.
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Standard deviation filter.
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Bollinger Bands filter as described in http://stockcharts.com/school/doku.php?id=chart_school:technical_indicators:bollinger_bands.
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Returns the lower band as a pyalgotrade.dataseries.DataSeries.
Returns the middle band as a pyalgotrade.dataseries.DataSeries.
Returns the upper band as a pyalgotrade.dataseries.DataSeries.