def parseKwargs(data, debug, kwargs):
"""
Parse keyword arguments
Args:
data: shared alamo data options
debug: Additional options may be specified and will be applied
to the .alm
kwargs: keyword arguments
"""
for arg in kwargs.keys():
if arg in data["pargs"]["opts"]:
data["opts"][arg] = kwargs[arg]
elif arg in data["pargs"]["lstopts"]:
data["lstopts"][arg] = list()
for term in list([kwargs[arg]]):
data["lstopts"][arg].append(term)
elif arg in data["pargs"]["stropts"]:
data["stropts"][arg] = kwargs[arg]
elif arg in data["pargs"]["set4"]:
data["set4"][arg] = kwargs[arg]
elif arg in debug["pargs"]:
debug[arg] = kwargs[arg]
else:
if arg not in (["xlabels", "zlabels", "xval", "zval"]):
sys.stdout.write("Problem with option : " + arg)
almerror("p3")
def getTrainingData(xdata, zdata, data, debug):
"""
Structure data for training the model. Modifies data['opts']
Args:
xdata: (numpy.array or list[real])
zdata: (numpy.array or list[real)
data: shared alamo data options
debug: Additional options may be specified and will be applied
to the .alm
"""
dshape = np.shape(xdata)
if len(dshape) == 0:
debug["traindata"] = False
elif len(dshape) == 1:
data["opts"]["ndata"] = np.shape(xdata)[0]
data["opts"]["ninputs"] = 1
else:
data["opts"]["ndata"] = np.shape(xdata)[0]
data["opts"]["ninputs"] = np.shape(xdata)[1]
xdata = np.asarray(xdata)
# Check training data
if len(np.shape(zdata)) == 1:
zdata = np.reshape(zdata, (data["opts"]["ndata"], 1))
data["opts"]["noutputs"] = 1
else:
data["opts"]["noutputs"] = np.shape(zdata)[1]
if np.shape(zdata)[0] != data["opts"]["ndata"]:
almerror("p1")
elif np.shape(xdata)[0] != data["opts"]["ndata"]:
almerror("p1")
zdata = np.asarray(zdata)
return xdata, zdata
def getValidationData(vargs, data, debug):
"""
Structure data for validating the model. Modifies data['opts']
Args:
vargs: validation data valxdata, valzdata
data: shared alamo data options
debug: Additional options may be specified and will be applied
to the .alm
"""
if vargs != ():
debug["validation"] = True
xvaldata = vargs[0]
zvaldata = vargs[1]
temp = np.shape(xvaldata)
data["opts"]["nvaldata"] = temp[0]
if len(np.shape(zvaldata)) == 1:
zvaldata = np.reshape(zvaldata, (data["opts"]["nvaldata"], 1))
if temp[1] != data["opts"]["ninputs"]:
writethis(
"Number of input variables inconsistent between x and xval")
almerror("p2")
temp = np.shape(zvaldata)
if temp[0] != data["opts"]["nvaldata"] or temp[1] != data["opts"][
"noutputs"]:
writethis("Problem with zval")
almerror("p2")
return xvaldata, zvaldata
def parseKwargs(data, debug, kwargs):
"""
Parse keyword arguments
Args:
data: shared alamo data options
debug: Additional options may be specified and will be applied
to the .alm
kwargs: keyword arguments
"""
for arg in kwargs.keys():
if kwargs[arg] is not None:
if arg in data["pargs"]["opts"]:
data["opts"][arg] = kwargs[arg]
elif arg in data["pargs"]["lstopts"]:
data["lstopts"][arg] = list()
for term in list([kwargs[arg]]):
data["lstopts"][arg].append(term)
elif arg in data["pargs"]["stropts"]:
data["stropts"][arg] = kwargs[arg]
elif arg in data["pargs"]["set4"]:
data["set4"][arg] = kwargs[arg]
elif arg in debug["pargs"]:
debug[arg] = kwargs[arg]
else:
if arg not in (["xlabels", "zlabels", "xval", "zval"]):
sys.stdout.write("Problem with option : " + arg)
# PYLINT-TODO-FIX use almerror correctly insted of calling it directly
# pylint: disable=not-callable
almerror("p3")