Debug = SIMP(statut="f", typ = "I", into=(0, 1), defaut=0),
AlgorithmParameters = F_AlgorithmParameters("o", ({check_names}), AlgorithmParametersInNS),
CheckingPoint = F_CheckingPoint("o", CheckingPointInNS),
+ Background = F_Background("f", BackgroundInNS),
BackgroundError = F_BackgroundError("f", BackgroundErrorInNS),
Observation = F_Observation("f", ObservationInNS),
ObservationError = F_ObservationError("f", ObservationErrorInNS),
vector_in_string=vector_in_string.replace("array","numpy.array")
vector_in_string=vector_in_string.replace("matrix","numpy.matrix")
exec("vector="+vector_in_string)
- vector = numpy.matrix(vector)
+ vector = numpy.array(vector)
else:
vector_in_string=vector_in_string.replace("'","").replace('"','')
- vector = numpy.matrix(vector_in_string)
+ vector_in_list = eval(str(vector_in_string),{},{})
+ vector = numpy.array(vector_in_list)
type = "VectorSerie"
logging.debug("VectorSerie is %s"%vector)
]]></code></script>
import gzip, bz2
from daCore.PlatformInfo import PathManagement ; PathManagement()
-from daCore.PlatformInfo import has_gnuplot
+from daCore.PlatformInfo import has_gnuplot, PlatformInfo
+mfp = PlatformInfo().MaximumPrecision()
if has_gnuplot:
import Gnuplot
élémentaires numpy.
"""
try:
- return [numpy.array(item).mean() for item in self.__values]
+ return [numpy.mean(item, dtype=mfp) for item in self.__values]
except:
raise TypeError("Base type is incompatible with numpy")
"""
try:
if self.__basetype in [int, float]:
- return float( numpy.array(self.__values).mean() )
+ return float( numpy.mean(self.__values, dtype=mfp) )
else:
- return numpy.array(self.__values).mean(axis=0)
+ return numpy.mean(self.__values, axis=0, dtype=mfp)
except:
raise TypeError("Base type is incompatible with numpy")