[Scipy-svn] r2381 - trunk/Lib/sandbox/timeseries
scipy-svn at scipy.org
scipy-svn at scipy.org
Sat Dec 9 12:24:56 EST 2006
Author: mattknox_ca
Date: 2006-12-09 11:24:53 -0600 (Sat, 09 Dec 2006)
New Revision: 2381
Modified:
trunk/Lib/sandbox/timeseries/timeseries.py
Log:
general code cleanup
Modified: trunk/Lib/sandbox/timeseries/timeseries.py
===================================================================
--- trunk/Lib/sandbox/timeseries/timeseries.py 2006-12-09 17:15:02 UTC (rev 2380)
+++ trunk/Lib/sandbox/timeseries/timeseries.py 2006-12-09 17:24:53 UTC (rev 2381)
@@ -1,6 +1,5 @@
import numpy
from numpy import ma
-import types
import corelib
import shiftingarray as sa
@@ -10,7 +9,7 @@
import copy
class TimeSeries(sa.ShiftingArray):
- def __init__(self,values=[], dtype=numpy.float64, freq=None, observed='END', startIndex=None,mask=ma.nomask):
+ def __init__(self, values=[], dtype=numpy.float64, freq=None, observed='END', startIndex=None, mask=ma.nomask):
if freq is None: raise ValueError("freq not specified")
@@ -30,7 +29,7 @@
def __setitem__(self, key, value):
if isinstance(key, tsdate.Date):
key = int(key)
- super(TimeSeries, self).__setitem__(key,value)
+ super(TimeSeries, self).__setitem__(key, value)
def convert(self, freq, observed=None):
@@ -44,7 +43,7 @@
firstIndex = sa.first_unmasked(self.data)
if firstIndex is None:
- return TimeSeries([],dtype=self.dtype,freq=toFreq,observed=observed)
+ return TimeSeries([], dtype=self.dtype, freq=toFreq, observed=observed)
startIndexAdj = self.firstValue()
@@ -54,13 +53,13 @@
tempMask = tempData.mask
tempData = tempData.filled()
- cRetVal = cseries.reindex(tempData, fromFreq, toFreq, observed, startIndexAdj,tempMask)
+ cRetVal = cseries.reindex(tempData, fromFreq, toFreq, observed, startIndexAdj, tempMask)
_values = cRetVal['values']
_mask = cRetVal['mask']
startIndex = cseries.convert(startIndexAdj, fromFreq, toFreq)
- return TimeSeries(_values,dtype=self.data.dtype,freq=toFreq,observed=observed,startIndex=startIndex, mask=_mask)
+ return TimeSeries(_values, dtype=self.data.dtype, freq=toFreq, observed=observed, startIndex=startIndex, mask=_mask)
else:
return copy.deepcopy(self)
@@ -81,71 +80,71 @@
### DATA
def __add__(self, other):
- validOpInputs(self,other)
- return SAtoTS(super(TimeSeries, self).__add__(other),self.freq,self.observed)
+ validOpInputs(self, other)
+ return SAtoTS(super(TimeSeries, self).__add__(other), self.freq, self.observed)
def __radd__(self, other):
- validOpInputs(self,other)
- return SAtoTS(super(TimeSeries, self).__add__(other),self.freq,self.observed)
+ validOpInputs(self, other)
+ return SAtoTS(super(TimeSeries, self).__add__(other), self.freq, self.observed)
def __sub__(self, other):
- validOpInputs(self,other)
- return SAtoTS(super(TimeSeries, self).__sub__(other),self.freq,self.observed)
+ validOpInputs(self, other)
+ return SAtoTS(super(TimeSeries, self).__sub__(other), self.freq, self.observed)
def __rsub__(self, other):
- validOpInputs(self,other)
- return SAtoTS(super(TimeSeries, self).__rsub__(other),self.freq,self.observed)
+ validOpInputs(self, other)
+ return SAtoTS(super(TimeSeries, self).__rsub__(other), self.freq, self.observed)
def __mul__(self, other):
- validOpInputs(self,other)
- return SAtoTS(super(TimeSeries, self).__mul__(other),self.freq,self.observed)
+ validOpInputs(self, other)
+ return SAtoTS(super(TimeSeries, self).__mul__(other), self.freq, self.observed)
def __rmul__(self, other):
- validOpInputs(self,other)
- return SAtoTS(super(TimeSeries, self).__rmul__(other),self.freq,self.observed)
+ validOpInputs(self, other)
+ return SAtoTS(super(TimeSeries, self).__rmul__(other), self.freq, self.observed)
def __div__(self, other):
- validOpInputs(self,other)
- return SAtoTS(super(TimeSeries, self).__div__(other),self.freq,self.observed)
+ validOpInputs(self, other)
+ return SAtoTS(super(TimeSeries, self).__div__(other), self.freq, self.observed)
def __rdiv__(self, other):
- validOpInputs(self,other)
- return SAtoTS(super(TimeSeries, self).__rdiv__(other),self.freq,self.observed)
+ validOpInputs(self, other)
+ return SAtoTS(super(TimeSeries, self).__rdiv__(other), self.freq, self.observed)
def __pow__(self, other):
- validOpInputs(self,other)
- return SAtoTS(super(TimeSeries, self).__pow__(other),self.freq,self.observed)
+ validOpInputs(self, other)
+ return SAtoTS(super(TimeSeries, self).__pow__(other), self.freq, self.observed)
### IN PLACE
def __iadd__(self, other):
- validOpInputs(self,other)
- self = SAtoTS(super(TimeSeries, self).__add__(other),self.freq,self.observed)
+ validOpInputs(self, other)
+ self = SAtoTS(super(TimeSeries, self).__add__(other), self.freq, self.observed)
return self
def __isub__(self, other):
- validOpInputs(self,other)
- self = SAtoTS(super(TimeSeries, self).__sub__(other),self.freq,self.observed)
+ validOpInputs(self, other)
+ self = SAtoTS(super(TimeSeries, self).__sub__(other), self.freq, self.observed)
return self
def __imul__(self, other):
- validOpInputs(self,other)
- self = SAtoTS(super(TimeSeries, self).__mul__(other),self.freq,self.observed)
+ validOpInputs(self, other)
+ self = SAtoTS(super(TimeSeries, self).__mul__(other), self.freq, self.observed)
return self
def __idiv__(self, other):
- validOpInputs(self,other)
- self = SAtoTS(super(TimeSeries, self).__div__(other),self.freq,self.observed)
+ validOpInputs(self, other)
+ self = SAtoTS(super(TimeSeries, self).__div__(other), self.freq, self.observed)
return self
# this overrides & and should only be used by boolean series
def __and__(self, other):
- validOpInputs(self,other)
+ validOpInputs(self, other)
return self * other
# this overrides | and should only be used by boolean series
def __or__(self, other):
- validOpInputs(self,other)
+ validOpInputs(self, other)
return ~(~self & ~other)
# this overrides ~ and should only be used by boolean series
@@ -156,57 +155,57 @@
### COMPARISON
def __eq__(self, other):
- validOpInputs(self,other)
- return SAtoTS(super(TimeSeries, self).__eq__(other),self.freq,self.observed)
+ validOpInputs(self, other)
+ return SAtoTS(super(TimeSeries, self).__eq__(other), self.freq, self.observed)
def __le__(self, other):
- validOpInputs(self,other)
- return SAtoTS(super(TimeSeries, self).__le__(other),self.freq,self.observed)
+ validOpInputs(self, other)
+ return SAtoTS(super(TimeSeries, self).__le__(other), self.freq, self.observed)
def __lt__(self, other):
- validOpInputs(self,other)
- return SAtoTS(super(TimeSeries, self).__lt__(other),self.freq,self.observed)
+ validOpInputs(self, other)
+ return SAtoTS(super(TimeSeries, self).__lt__(other), self.freq, self.observed)
def __ge__(self, other):
- validOpInputs(self,other)
- return SAtoTS(super(TimeSeries, self).__ge__(other),self.freq,self.observed)
+ validOpInputs(self, other)
+ return SAtoTS(super(TimeSeries, self).__ge__(other), self.freq, self.observed)
def __gt__(self, other):
- validOpInputs(self,other)
- return SAtoTS(super(TimeSeries, self).__gt__(other),self.freq,self.observed)
+ validOpInputs(self, other)
+ return SAtoTS(super(TimeSeries, self).__gt__(other), self.freq, self.observed)
-def tser(start,end):
+def tser(start, end):
if start.freq != end.freq:
raise ValueError("start and end dates must have same frequency!")
- return TimeSeries(numpy.arange(int(start),int(end)+1),dtype=corelib.freqTypeMapping[start.freq],freq=start.freq,observed='END',startIndex=int(start))
+ return TimeSeries(numpy.arange(int(start), int(end)+1), dtype=corelib.freqTypeMapping[start.freq], freq=start.freq, observed='END', startIndex=int(start))
-def validOpInputs(ser1,ser2):
- if isinstance(ser1,TimeSeries) and isinstance(ser2,TimeSeries) and ser1.freq != ser2.freq:
+def validOpInputs(ser1, ser2):
+ if isinstance(ser1, TimeSeries) and isinstance(ser2, TimeSeries) and ser1.freq != ser2.freq:
raise "operation cannot be performed on series with different frequencies ("+str(ser1.freq) + " and " + str(ser2.freq)+")"
-def SAtoTS(values,freq,observed,dtype=None):
+def SAtoTS(values, freq, observed, dtype=None):
if dtype is None: _dtype = values.dtype
else: _dtype = dtype
- return TimeSeries(values.data,dtype=_dtype,freq=freq,observed=observed,startIndex=values.indexZeroRepresents)
+ return TimeSeries(values.data, dtype=_dtype, freq=freq, observed=observed, startIndex=values.indexZeroRepresents)
# math functions (two series)
-def add(ser1,ser2,fill_value=ma.masked):
- return apply_func_twoseries(ma.add,ser1,ser2,fill_value)
+def add(ser1, ser2, fill_value=ma.masked):
+ return apply_func_twoseries(ma.add, ser1, ser2, fill_value)
-def multiply(ser1,ser2,fill_value=ma.masked):
- return apply_func_twoseries(ma.multiply,ser1,ser2,fill_value)
+def multiply(ser1, ser2, fill_value=ma.masked):
+ return apply_func_twoseries(ma.multiply, ser1, ser2, fill_value)
-def divide(ser1,ser2,fill_value=ma.masked):
- return apply_func_twoseries(ma.divide,ser1,ser2,fill_value)
+def divide(ser1, ser2, fill_value=ma.masked):
+ return apply_func_twoseries(ma.divide, ser1, ser2, fill_value)
-def subtract(ser1,ser2,fill_value=ma.masked):
- return apply_func_twoseries(ma.subtract,ser1,ser2,fill_value)
+def subtract(ser1, ser2, fill_value=ma.masked):
+ return apply_func_twoseries(ma.subtract, ser1, ser2, fill_value)
# math functions (one series, return series)
def sqrt(ser):
- return apply_func_oneseries(ma.sqrt,ser)
+ return apply_func_oneseries(ma.sqrt, ser)
# math functions (one series, return scalar)
def sum(ser):
@@ -218,15 +217,15 @@
def average(ser):
return ma.average(ser.data)
-def where(condition,x,y):
- tempResult = ma.where(condition.data,x,y)
- return TimeSeries(tempResult,dtype=numpy.bool_,freq=condition.freq,observed=condition.observed,startIndex=condition.indexZeroRepresents)
+def where(condition, x, y):
+ tempResult = ma.where(condition.data, x, y)
+ return TimeSeries(tempResult, dtype=numpy.bool_, freq=condition.freq, observed=condition.observed, startIndex=condition.indexZeroRepresents)
# generic functions
-def apply_func_twoseries(func,ser1,ser2,fill_value=ma.masked):
- validOpInputs(ser1,ser2)
- return SAtoTS(doFunc(ser1,ser2,func,fill_value=fill_value),ser1.freq,ser1.observed)
+def apply_func_twoseries(func, ser1, ser2, fill_value=ma.masked):
+ validOpInputs(ser1, ser2)
+ return SAtoTS(doFunc(ser1, ser2, func, fill_value=fill_value), ser1.freq, ser1.observed)
-def apply_func_oneseries(func,ser):
- return SAtoTS(doFunc_oneseries(ser,func),ser.freq,ser.observed)
+def apply_func_oneseries(func, ser):
+ return SAtoTS(doFunc_oneseries(ser, func),ser.freq, ser.observed)
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