def readReferenceMatrix(self, storage, filename):
from pysgpp import DataVector, DataMatrix
# read reference matrix
try:
fd = tools.gzOpen(filename, 'r')
except IOError as e:
fd = None
if not fd:
fd = tools.gzOpen('tests/' + filename, 'r')
dat = fd.read().strip()
fd.close()
dat = dat.split('\n')
dat = [l.strip().split(None) for l in dat]
# right number of entries?
self.assertEqual(storage.getSize(), len(dat))
self.assertEqual(storage.getSize(), len(dat[0]))
m_ref = DataMatrix(len(dat), len(dat[0]))
for i in range(len(dat)):
for j in range(len(dat[0])):
m_ref.set(i, j, float(dat[i][j]))
return m_ref
def readDataVector(filename):
from pysgpp import DataVector
try:
fin = tools.gzOpen(filename, 'r')
except IOError, e:
fin = None
def readReferenceMatrix(self, storage, filename):
from pysgpp import DataVector, DataMatrix
# read reference matrix
try:
fd = tools.gzOpen(filename, 'r')
except IOError, e:
fd = None
def readDataVector(filename):
from pysgpp import DataVector
try:
fin = tools.gzOpen(filename, 'r')
except IOError, e:
fin = None
def readReferenceMatrix(self, storage, filename):
from pysgpp import DataVector, DataMatrix
# read reference matrix
try:
fd = tools.gzOpen(filename, 'r')
except IOError, e:
fd = None
def readDataVector(filename):
from pysgpp import DataVector
try:
fin = tools.gzOpen(filename, 'r')
except IOError as e:
fin = None
if not fin:
fin = tools.gzOpen('tests/' + filename, 'r')
data = []
classes = []
hasclass = False
# get the different section of ARFF-File
for line in fin:
sline = line.strip().lower()
if sline.startswith("%") or len(sline) == 0:
continue
if sline.startswith("@data"):
break
if sline.startswith("@attribute"):
value = sline.split()
if value[1].startswith("class"):
hasclass = True
else:
data.append([])
# read in the data stored in the ARFF file
for line in fin:
sline = line.strip()
if sline.startswith("%") or len(sline) == 0:
continue
values = sline.split(",")
if hasclass:
classes.append(float(values[-1]))
values = values[:-1]
for i in range(len(values)):
data[i].append(float(values[i]))
# cleaning up and return
fin.close()
return {"data": data, "classes": classes, "filename": filename}
def getminmax(filename, separator=None):
"""Computes min and max for each parameter"""
fd = tools.gzOpen(filename, 'r')
mmax = [-10e10 for d in range(dim)]
mmin = [10e10 for d in range(dim)]
for line in fd.readlines():
line = line.split(separator)
for d in range(len(line) - 1):
mmax[d] = max(float(line[d]), mmax[d])
mmin[d] = min(float(line[d]), mmin[d])
fd.close()
return (mmin, mmax)
def getminmax(filename, separator=None):
"""Computes min and max for each parameter"""
fd = tools.gzOpen(filename, 'r')
mmax = [-10e10 for d in range(dim)]
mmin = [10e10 for d in range(dim)]
for line in fd.readlines():
line = line.split(separator)
for d in range(len(line)-1):
mmax[d] = max(float(line[d]), mmax[d])
mmin[d] = min(float(line[d]), mmin[d])
fd.close()
return (mmin, mmax)
p[0] = random.uniform(0, 100)
p[1] = random.uniform(40 * math.pi, 560 * math.pi)
p[2] = random.uniform(0, 1)
p[3] = random.uniform(1, 11)
eps = random.normalvariate(0.0, 0.1)
# $ \atan \left( \left( x_1 x_2 - (x_1 x_3)^{-1} \right) / x_0 \right) + \epsilon $
p[4] = math.atan((p[1] * p[2] - 1.0 / (p[1] * p[3])) / p[0]) + eps
X.setRow(i, p)
else:
sys.exit(1)
if options.outfile and ".csv" in options.outfile:
from numpy import savetxt
#header = ','.join(['x%d'%i for i in xrange(X.getNcols()-1)] + ['classes'])
savetxt(options.outfile, X.array(), fmt='%.12f', delimiter=',')
sys.exit(1)
elif options.outfile:
fd = tools.gzOpen(options.outfile, 'w')
else:
fd = sys.stdout
fd.write("""@RELATION "%s"\n\n""" % (namestring))
for d in range(X.getNcols() - 1):
fd.write("""@ATTRIBUTE x%d NUMERIC\n""" % (d))
fd.write("""@ATTRIBUTE class NUMERIC\n\n@Data\n""")
for i in xrange(X.getNrows()):
X.getRow(i, p)
fd.write(','.join([str(p[d]) for d in range(X.getNcols())]) + "\n")
if options.outfile:
fd.close()
# Sets the column in m
m.setColumn(i, erg)
return m
def readReferenceMatrix(self, storage, filename):
from pysgpp import DataVector, DataMatrix
# read reference matrix
try:
fd = tools.gzOpen(filename, 'r')
except IOError, e:
fd = None
if not fd:
fd = tools.gzOpen('tests/' + filename, 'r')
dat = fd.read().strip()
fd.close()
dat = dat.split('\n')
dat = map(lambda l: l.strip().split(None), dat)
# right number of entries?
self.assertEqual(storage.size(), len(dat))
self.assertEqual(storage.size(), len(dat[0]))
m_ref = DataMatrix(len(dat), len(dat[0]))
for i in xrange(len(dat)):
for j in xrange(len(dat[0])):
m_ref.set(i, j, float(dat[i][j]))
#Sets the column in m
m.setColumn(i, erg)
return m
def readReferenceMatrix(self, storage, filename):
from pysgpp import DataVector, DataMatrix
# read reference matrix
try:
fd = tools.gzOpen(filename, 'r')
except IOError, e:
fd = None
if not fd:
fd = tools.gzOpen('tests/' + filename, 'r')
dat = fd.read().strip()
fd.close()
dat = dat.split('\n')
dat = map(lambda l: l.strip().split(None), dat)
# right number of entries?
self.assertEqual(storage.size(), len(dat))
self.assertEqual(storage.size(), len(dat[0]))
m_ref = DataMatrix(len(dat), len(dat[0]))
for i in xrange(len(dat)):
for j in xrange(len(dat[0])):
m_ref.set(i, j, float(dat[i][j]))
N = 10000
X = DataMatrix(N, 11)
p = DataVector(11)
for i in xrange(N):
for d in range(10):
if d == 0 or d == 1:
p[d] = random.uniform(-0.5, 0.5)
else:
p[d] = random.random()
eps = random.normalvariate(0.0, 0.1)
p[10] = p[0]**2 * p[1]**2 + eps
p[0] += 0.5
p[1] += 0.5
X.setRow(i, p)
fd = tools.gzOpen("parabola.10000_test.arff", 'w')
fd.write("""@RELATION "Parabola %s"\n\n""" % (N))
for d in range(X.getNcols() - 1):
fd.write("""@ATTRIBUTE x%d NUMERIC\n""" % (d))
fd.write("""@ATTRIBUTE class NUMERIC\n\n@DATA\n""")
for i in xrange(X.getNrows()):
X.getRow(i, p)
fd.write(','.join([str(p[d]) for d in range(X.getNcols())]) + "\n")
fd.close()
help="Don't use colors. Only for --eps")
parser.add_option("--dotwidth",
dest="dotwidth",
action="store",
type="int",
default=None,
help="Width of dots (gnuplot lw)")
(options, args) = parser.parse_args()
# check arguments
if not options.data:
print "--data missing"
parser.parse_args(['-h'])
# read data
fd = tools.gzOpen(options.data, 'r')
data = fd.readlines()
fd.close()
if not options.datsep.strip():
options.datsep = None
gnuplot_separator = ""
else:
gnuplot_separator = 'set datafile separator "%s"' % (options.datsep)
if options.data[-3:] == ".gz":
fname = "< zcat " + options.data
else:
fname = options.data
# get dimension:
line = data[0].strip().split(options.datsep)
help="Don't plot label")
parser.add_option("--monochrome", dest="monochrome", action="store_true",
default=False,
help="Don't use colors. Only for --eps")
parser.add_option("--dotwidth", dest="dotwidth", action="store", type="int",
default=None,
help="Width of dots (gnuplot lw)")
(options,args)=parser.parse_args()
# check arguments
if not options.data:
print "--data missing"
parser.parse_args(['-h'])
# read data
fd = tools.gzOpen(options.data, 'r')
data = fd.readlines()
fd.close()
if not options.datsep.strip():
options.datsep = None
gnuplot_separator = ""
else:
gnuplot_separator = 'set datafile separator "%s"' % (options.datsep)
if options.data[-3:] == ".gz":
fname = "< zcat "+options.data
else:
fname = options.data
# get dimension: