def fromXYs(cls, xys, value=None):
if (xys.interpolation not in [
standardsModule.interpolation.linlinToken,
standardsModule.interpolation.flatToken
]):
xys = xys.toPointwise_withLinearXYs(accuracy=1e-3,
lowerEps=0,
upperEps=1e-8)
try:
norm = xys.normalize()
except:
norm = xys.copy()
norm[0] = [norm[0][0], 1.0]
norm = norm.normalize()
print ' WARNGING: xs_pdf_cdf1d.fromXYs; distribution with 0 norm.'
_cdf = norm.runningIntegral()
_xs, _pdf = norm.copyDataToXsAndYs()
_xs = xs(valuesModule.values(_xs))
_pdf = pdf(valuesModule.values(_pdf))
_cdf = cdf(valuesModule.values(_cdf))
return (cls(_xs,
_pdf,
_cdf,
value=value,
interpolation=xys.interpolation))
def toMultiGroup1d( cls, style, tempInfo, _axes, data, addLabel = True ) :
"""
This function takes 1-d multi-group data as a list of floats and return to 1-d gridded instance
containing the multi-group data. The list of data must contain n values where n is the
number of groups.
"""
reactionSuite = tempInfo['reactionSuite']
axes = axesModule.axes( rank = 2 )
axes[0] = axesModule.axis( _axes[0].label, 0, _axes[0].unit )
energyInGrid = style.transportables[reactionSuite.projectile].group.boundaries.values.copy( )
axes[1] = axesModule.grid( _axes[1].label, 1, _axes[1].unit, axesModule.boundariesGridToken, energyInGrid )
shape = [ len( data ) ]
data = valuesModule.values( data )
for start, datum in enumerate( data ) :
if( datum != 0 ) : break
end = 0
for i1, datum in enumerate( data ) :
if( datum != 0 ) : end = i1
if( start > end ) : # Only happens when all values are 0.
start = 0
else :
end += 1
data = data[start:end]
starts = valuesModule.values( [ start ], valueType = standardsModule.types.integer32Token )
lengths = valuesModule.values( [ len( data ) ], valueType = standardsModule.types.integer32Token )
flattened = arrayModule.flattened( shape = shape, data = data, starts = starts, lengths = lengths )
label = None
if( addLabel ) : label = style.label
return( cls( label = label, axes = axes, array = flattened ) )
def TMs2Form( style, tempInfo, TM_1, TM_E ) :
from fudge.processing import transportables as transportablesModule
from fudge.gnd.productData.distributions import multiGroup as multiGroupModule
reactionSuite = tempInfo['reactionSuite']
productName = tempInfo['productName']
transportable = style.transportables[productName]
conserve = transportable.conserve
energyUnit = tempInfo['incidentEnergyUnit']
# BRB hardwired.
crossSectionUnit = 'b' # ?????? 'b' should not be hardwired.
axes = axesModule.axes( rank = 4 )
axes[0] = axesModule.axis( 'C_l(energy_in,energy_out)', 0, crossSectionUnit )
lMaxPlus1 = len( TM_1[0][0] )
lGrid = valuesModule.values( [ i1 for i1 in range( lMaxPlus1 ) ], valueType = standardsModule.types.integer32Token )
axes[1] = axesModule.grid( 'l', 1, '', axesModule.parametersGridToken, lGrid )
energyOutGrid = style.transportables[productName].group.boundaries.values.copy( )
axes[2] = axesModule.grid( 'energy_out', 2, energyUnit, axesModule.boundariesGridToken, energyOutGrid )
energyInGrid = style.transportables[reactionSuite.projectile].group.boundaries.values.copy( )
axes[3] = axesModule.grid( 'energy_in', 3, energyUnit, axesModule.boundariesGridToken, energyInGrid )
if( conserve == transportablesModule.conserve.number ) :
TM = TM_1
else :
raise NotImplementedError( 'Need to implement' )
n1 = len( TM )
n2 = len( TM[0] )
n3 = len( TM[0][0] )
data, starts, lengths = [], [], []
for i1 in sorted( TM.keys( ) ) :
TM_i1 = TM[i1]
start, length = None, 0
for i2 in sorted( TM_i1.keys( ) ) :
TM_i1_i2 = TM_i1[i2]
cellMin = min( TM_i1_i2 )
cellMax = max( TM_i1_i2 )
if( ( cellMin != 0 ) or ( cellMax != 0 ) ) :
if( start is None ) : start = n3 * ( n2 * i1 + i2 )
length += n3
data += TM_i1_i2
else :
if( start is not None ) :
starts.append( start )
lengths.append( length )
start, length = None, 0
if( start is not None ) :
starts.append( start )
lengths.append( length )
shape = [ n1, n2, n3 ]
data = valuesModule.values( data )
starts = valuesModule.values( starts, valueType = standardsModule.types.integer32Token )
lengths = valuesModule.values( lengths, valueType = standardsModule.types.integer32Token )
flattened = arrayModule.flattened( shape = shape, data = data, starts = starts, lengths = lengths,
dataToString = multiGroupModule.gridded3d.dataToString )
gridded3d = multiGroupModule.gridded3d( axes = axes, array = flattened )
return( multiGroupModule.form( style.label, standardsModule.frames.labToken, gridded3d ) )
def convertUnits(self, unitMap):
"""
unitMap is a dictionary of the for { 'eV' : 'MeV', 'b' : 'mb' }.
"""
factors = self.axes.convertUnits(unitMap)
yFactor = factors[0]
self.__Ys = valuesModule.values(
[yFactor * value for value in self.__Ys])
self.fixValuePerUnitChange(factors)
def processMultiGroup(self, style, tempInfo, indent):
reactionSuite = tempInfo['reactionSuite']
axes = self.data.axes.copy()
axes[1] = axesModule.grid(
axes[1].label,
1,
axes[1].unit,
style=axesModule.parametersGridToken,
values=valuesModule.values(
[0], valueType=standardsModule.types.integer32Token))
axes[2] = style.transportables[
reactionSuite.projectile].group.boundaries.copy([])
data = self.data.processMultiGroup(style, tempInfo, indent)
starts = valuesModule.values(
[0], valueType=standardsModule.types.integer32Token)
lengths = valuesModule.values(
[len(data)], valueType=standardsModule.types.integer32Token)
array = arrayModule.flattened(shape=(len(data), 1),
data=data,
starts=starts,
lengths=lengths)
data = gridded2d(axes=axes, array=array)
return (data)
def add_values(v1, v2):
v = set()
v.update(v1.values)
v.update(v2.values)
return valuesModule.values(sorted(v))
fluxData.append(fluxModule.LegendreSeries([C0], value=newE, axes=axes))
flux = fluxModule.flux(args.fluxID, fluxData)
if not (args.gid == None):
for gidVal in args.gid:
key, value = gidVal.split('=')
if key not in gids:
raise UserWarning(
"particle grouping specified for unknown particle name : %s " %
(key))
gids[key] = value
transportables = []
for particle in gids:
gbs = valuesModule.values([
PQUModule.PQU(boundary, 'MeV').getValueAs(args.energyUnit)
for boundary in bdfls.group(gids[particle]).gb
])
grid = axesModule.grid('energy_in', 0, args.energyUnit,
axesModule.boundariesGridToken, gbs)
group = groupModule.group(gids[particle], grid)
transportables.append(
transportablesModule.transportable(
particle, transportablesModule.conserve.number, group))
#### read in GND file
reactionSuite = reactionSuiteModule.readXML(args.gnd)
if (reactionSuite.projectile != IDsPoPsModule.neutron): tempsDefault = 0
if (args.temperatures == None): args.temperatures = [tempsDefault]
### fail on detection of existing processed data
def setUp(self):
# ...................... example matrix 'a' ......................
axes = axesModule.axes(
labelsUnits={
0: ('matrix_elements', 'b**2'),
1: ('column_energy_bounds', 'MeV'),
2: ('row_energy_bounds', 'MeV')
})
axes[2] = axesModule.grid(axes[2].label,
axes[2].index,
axes[2].unit,
style=axesModule.boundariesGridToken,
values=valuesModule.values([
1.0000E-07, 1.1109E-01, 1.3534E+00,
1.9640E+01
]))
axes[1] = axesModule.grid(axes[1].label,
axes[1].index,
axes[1].unit,
style=axesModule.linkGridToken,
values=linkModule.link(link=axes[2].values,
relative=True))
myMatrix = arrayModule.full((3, 3), [4.0, 1.0, 9.0, 0.0, 0.0, 25.0],
symmetry=arrayModule.symmetryLowerToken)
self.a = covariances.covarianceMatrix(
'eval',
matrix=griddedModule.gridded2d(axes, myMatrix),
type=covariances.tokens.relativeToken)
# ...................... example matrix 'b' ......................
axes = axesModule.axes(
labelsUnits={
0: ('matrix_elements', 'b**2'),
1: ('column_energy_bounds', 'MeV'),
2: ('row_energy_bounds', 'MeV')
})
axes[2] = axesModule.grid(axes[2].label,
axes[2].index,
axes[2].unit,
style=axesModule.boundariesGridToken,
values=valuesModule.values(
[1.0e-5, 0.100, 1.0, 20.0]))
axes[1] = axesModule.grid(axes[1].label,
axes[1].index,
axes[1].unit,
style=axesModule.linkGridToken,
values=linkModule.link(link=axes[2].values,
relative=True))
myMatrix = arrayModule.full((3, 3), [4.0, 1.0, 9.0, 0.0, 0.0, 25.0],
symmetry=arrayModule.symmetryLowerToken)
self.b = covariances.covarianceMatrix(
'eval',
matrix=griddedModule.gridded2d(axes, myMatrix),
type=covariances.tokens.relativeToken)
# ...................... example matrix 'c' ......................
axes = axesModule.axes(
labelsUnits={
0: ('matrix_elements', 'b**2'),
1: ('column_energy_bounds', 'MeV'),
2: ('row_energy_bounds', 'MeV')
})
axes[2] = axesModule.grid(axes[2].label,
axes[2].index,
axes[2].unit,
style=axesModule.boundariesGridToken,
values=valuesModule.values([
1.0000E-07, 6.7380E-02, 1.1109E-01,
1.3534E+00
]))
axes[1] = axesModule.grid(axes[1].label,
axes[1].index,
axes[1].unit,
style=axesModule.linkGridToken,
values=linkModule.link(link=axes[2].values,
relative=True))
myMatrix = arrayModule.full((3, 3), [4.0, 1.0, 9.0, 0.0, 0.0, 25.0],
symmetry=arrayModule.symmetryLowerToken)
self.c = covariances.covarianceMatrix(
'eval',
matrix=griddedModule.gridded2d(axes, myMatrix),
type=covariances.tokens.relativeToken)
# ...................... combine them for example matrix 'abc' ......................
abc = covariances.mixed.mixedForm(components=[self.a, self.b, self.c])
# FIXME: learn how to add abc to a section & to a covarianceSuite!, sumabc is built wrong!
# ...................... 'sumabc' is just a way to exercise the summed class ......................
bds = abc.getRowBounds()
self.sumabc = covariances.summed.summedCovariance(
label='test',
domainMin=float(bds[0]),
domainMax=float(bds[1]),
domainUnit=abc[0].matrix.axes[-1].unit,
pointerList=[
linkModule.link(link=abc, path=abc.toXLink(), coefficient=1.0)
])