本文整理匯總了Python中MA.masked_array方法的典型用法代碼示例。如果您正苦於以下問題：Python MA.masked_array方法的具體用法？Python MA.masked_array怎麽用？Python MA.masked_array使用的例子？那麽, 這裏精選的方法代碼示例或許可以為您提供幫助。您也可以進一步了解該方法所在類MA的用法示例。
在下文中一共展示了MA.masked_array方法的2個代碼示例，這些例子默認根據受歡迎程度排序。您可以為喜歡或者感覺有用的代碼點讚，您的評價將有助於係統推薦出更棒的Python代碼示例。
示例1: _getMaskedArray
# 需要導入模塊: import MA [as 別名]
# 或者: from MA import masked_array [as 別名]
def _getMaskedArray(self, var, flagVar=None, flagValues=(0, 1), missingValuesToTest=(-9999.0, -32767.0)):
"""
Returns a masked array that has the values only present where the flag
values are acceptable and the data itself is not missing.
"""
if flagVar:
flagFillValue = -1
flagGTValue = max(flagValues)
flagMaskWhereUnacceptable = MA.masked_greater(flagVar, flagGTValue).mask()
flagMaskWhereMissing = MA.masked_equal(flagVar, flagFillValue).mask()
flagMask = flagMaskWhereUnacceptable + flagMaskWhereMissing
for fv in missingValuesToTest:
if fv in MV.ravel(var):
print "Setting missing value for '%s' as: %s" % (var.id, fv)
varFillValue = fv
else:
varFillValue = missingValuesToTest[0]
if flagVar:
varMask = MA.masked_array(var, mask=MA.equal(var, varFillValue), fill_value=varFillValue).mask()
fullmask = MA.bitwise_or(varMask, flagMask)
maskedArray = MA.masked_array(var, mask=fullmask, fill_value=varFillValue)
else:
maskedArray = MA.masked_array(var, mask=MA.equal(var, varFillValue), fill_value=varFillValue)
# maskedArray=cdms.createVariable(maskedArray, id=var.id, fill_value=varFillValue)
# maskedArray.missing_value=varFillValue
return maskedArray示例2: _subSampleByAveraging
# 需要導入模塊: import MA [as 別名]
# 或者: from MA import masked_array [as 別名]
def _subSampleByAveraging(self, var, timeVar, flagVar, samplingRate, flagsToUse):
"""
Returns a new variable which is 'var' sub-sampled by averaging
at the given samplingRate with data selected according to flagVar
including the flag values specified in flagsToUse (defaults are 0 and 1).
"""
maskedArray = self._getMaskedArray(var, flagVar, flagsToUse)
shape = var.shape
if shape[1] == 1:
newNumArray = MV.ravel(maskedArray)
newArrayMask = MV.ravel(maskedArray.mask())
newArray = MA.masked_array(newNumArray, mask=newArrayMask, fill_value=maskedArray.fill_value())
else:
newArray = Numeric.zeros(shape[0], "f")
for t0 in range(shape[0]):
# Set as missing if less than half are valid
t1Array = maskedArray[t0]
if samplingRate == 1:
# If half or more are good values then calculate the mean
if t1Array.count() >= (shape[1] / 2.0):
newArray[t0] = MA.average(t1Array)
# otherwise set as missing value
else:
newArray[t0] = maskedArray.fill_value()
else:
raise "Averaging for non 1Hz sampling rates not yet supported!"
# Now re-construct variable axes etc
newTimeAxis = self._flatten2DTimeAxis(timeVar, samplingRate)
newVar = self._recreateVariable(
var,
newArray,
newTimeAxis,
flagVar,
max(flagsToUse),
missingValue=maskedArray.fill_value(),
sampleBy="averaging",
)
return newVar