def __init__(self, x, y, z, kind='linear'):
if isinstance(x, list):
x = NDArray(ArrayUtil.array(x))
if isinstance(y, list):
y = NDArray(ArrayUtil.array(y))
if isinstance(z, list):
z = NDArray(ArrayUtil.array(z))
self._func = InterpUtil.getBiInterpFunc(x.asarray(), y.asarray(),
z.asarray())
def dimvalue(self, idx, convert=False):
'''
Get dimension values.
:param idx: (*int*) Dimension index.
:param convert: (*boolean*) If convert to real values (i.e. datetime). Default
is ``False``.
:returns: (*array_like*) Dimension values
'''
dim = self.dims[idx]
if convert:
if dim.getDimType() == DimensionType.T:
return miutil.nums2dates(dim.getDimValue())
else:
return np.array(ArrayUtil.array(self.dims[idx].getDimValue()))
else:
return np.array(ArrayUtil.array(self.dims[idx].getDimValue()))
def expfit(x, y, func=False):
'''
Exponent fitting.
:param x: (*array_like*) x data array.
:param y: (*array_like*) y data array.
:param func: (*boolean*) Return fit function (for predict function) or not. Default is ``False``.
:returns: Fitting parameters and function (optional).
'''
if isinstance(x, list):
x = NDArray(ArrayUtil.array(x))
if isinstance(y, list):
y = NDArray(ArrayUtil.array(y))
r = FittingUtil.expFit(x.asarray(), y.asarray())
if func:
return r[0], r[1], r[2], r[3]
else:
return r[0], r[1], r[2]
def polyfit(x, y, degree, func=False):
'''
Polynomail fitting.
:param x: (*array_like*) x data array.
:param y: (*array_like*) y data array.
:param degree: (*int*) Degree of the fitting polynomial.
:param func: (*boolean*) Return fit function (for predict function) or not. Default is ``False``.
:returns: Fitting parameters and function (optional).
'''
if isinstance(x, list):
x = NDArray(ArrayUtil.array(x))
if isinstance(y, list):
y = NDArray(ArrayUtil.array(y))
r = FittingUtil.polyFit(x.asarray(), y.asarray(), degree)
if func:
return r[0], r[1], r[2]
else:
return r[0], r[1]
def __call__(self, x, y):
'''
Evaluate the interpolate vlaues.
:param x: (*array_like*) X to evaluate the interpolant at.
:param y: (*array_like*) Y to evaluate the interpolant at.
'''
if isinstance(x, list):
x = NDArray(ArrayUtil.array(x))
if isinstance(x, (NDArray, DimArray)):
x = x.asarray()
if isinstance(y, list):
y = NDArray(ArrayUtil.array(y))
if isinstance(y, (NDArray, DimArray)):
y = y.asarray()
r = InterpUtil.evaluate(self._func, x, y)
if isinstance(r, float):
return r
else:
return NDArray(r)
def coldata(self, key):
'''
Return column data as one dimension array.
:param key: (*string*) Column name.
:returns: (*NDArray*) Colomn data.
'''
if isinstance(key, str):
print key
values = self.data.getColumnData(key).getDataValues()
return NDArray(ArrayUtil.array(values))
return None
def predict(func, x):
'''
Predict y value using fitting function and x value.
:param func: (*Fitting function object*) Fitting function.
:param x: (*float*) x value.
:returns: (*float*) y value.
'''
if isinstance(x, (int, float, long)):
return func.predict(x)
if isinstance(x, list):
x = NDArray(ArrayUtil.array(x))
return NDArray(FittingUtil.predict(x.asarray(), func))
def __init__(self, array):
if not isinstance(array, Array):
array = ArrayUtil.array(array, None)
self._array = array
self.ndim = array.getRank()
s = array.getShape()
s1 = []
for i in range(len(s)):
s1.append(s[i])
self._shape = tuple(s1)
self.dtype = _dtype.fromjava(array.getDataType())
self.size = int(self._array.getSize())
self.iterator = array.getIndexIterator()
self.base = None
if self.ndim > 0:
self.sizestr = str(self.shape[0])
if self.ndim > 1:
for i in range(1, self.ndim):
self.sizestr = self.sizestr + '*%s' % self.shape[i]
def polyval(p, x):
"""
Evaluate a polynomial at specific values.
If p is of length N, this function returns the value:
p[0]*x**(N-1) + p[1]*x**(N-2) + ... + p[N-2]*x + p[N-1]
If x is a sequence, then p(x) is returned for each element of x. If x is another polynomial then the
composite polynomial p(x(t)) is returned.
:param p: (*array_like*) 1D array of polynomial coefficients (including coefficients equal to zero)
from highest degree to the constant term.
:param x: (*array_like*) A number, an array of numbers, or an instance of poly1d, at which to evaluate
p.
:returns: Polynomial value
"""
if isinstance(x, list):
x = NDArray(ArrayUtil.array(x))
return NDArray(ArrayMath.polyVal(p, x.asarray()))
def __setitem__(self, indices, value):
#print type(indices)
if isinstance(indices, NDArray):
if isinstance(value, NDArray):
value = value.asarray()
ArrayMath.setValue(self._array, indices._array, value)
return None
if not isinstance(indices, tuple):
inds = []
inds.append(indices)
indices = inds
if len(indices) < self.ndim:
for i in range(self.ndim - len(indices)):
indices.append(slice(None))
if self.ndim == 0:
self._array.setObject(0, value)
return None
if len(indices) != self.ndim:
print 'indices must be ' + str(self.ndim) + ' dimensions!'
raise IndexError()
ranges = []
flips = []
onlyrange = True
alllist = True
for i in range(0, self.ndim):
k = indices[i]
if isinstance(k, int):
sidx = k
if sidx < 0:
sidx = self._shape[i] + sidx
eidx = sidx
step = 1
alllist = False
elif isinstance(k, (list, tuple, NDArray)):
if isinstance(k, NDArray):
k = k.aslist()
onlyrange = False
ranges.append(k)
continue
else:
sidx = 0 if k.start is None else k.start
if sidx < 0:
sidx = self._shape[i] + sidx
eidx = self._shape[i] if k.stop is None else k.stop
if eidx < 0:
eidx = self._shape[i] + eidx
eidx -= 1
step = 1 if k.step is None else k.step
alllist = False
if step < 0:
step = abs(step)
flips.append(i)
if eidx < sidx:
return
rr = Range(sidx, eidx, step)
ranges.append(rr)
if isinstance(value, (list, tuple)):
value = ArrayUtil.array(value)
if isinstance(value, NDArray):
value = value.asarray()
if onlyrange:
r = ArrayMath.setSection(self._array, ranges, value)
else:
if alllist:
r = ArrayMath.setSection_List(self._array, ranges, value)
else:
r = ArrayMath.setSection_Mix(self._array, ranges, value)
self._array = r
def __getitem__(self, key):
if isinstance(key, basestring):
coldata = self.data.getColumnData(key)
if coldata.getDataType().isNumeric():
return NDArray(ArrayUtil.array(coldata.getDataValues()))
elif coldata.getDataType() == DataType.DATE:
vv = coldata.getData()
r = []
cal = Calendar.getInstance()
for v in vv:
cal.setTime(v)
year = cal.get(Calendar.YEAR)
month = cal.get(Calendar.MONTH) + 1
day = cal.get(Calendar.DAY_OF_MONTH)
hour = cal.get(Calendar.HOUR_OF_DAY)
minute = cal.get(Calendar.MINUTE)
second = cal.get(Calendar.SECOND)
dt = datetime.datetime(year, month, day, hour, minute,
second)
r.append(dt)
return r
else:
return NDArray(ArrayUtil.array(coldata.getData()))
hascolkey = True
if isinstance(key, tuple):
ridx = key[0]
cidx = key[1]
if isinstance(ridx, int) and isinstance(cidx, int):
if ridx < 0:
ridx = self.shape[0] + ridx
if cidx < 0:
cidx = self.shape[1] + cidx
return self.data.getValue(ridx, cidx)
elif isinstance(ridx, int) and isinstance(cidx, basestring):
if ridx < 0:
ridx = self.shape[0] + ridx
return self.data.getValue(ridx, cidx)
else:
key = (key, slice(None))
hascolkey = False
k = key[0]
if isinstance(k, int):
sidx = k
if sidx < 0:
sidx = self.shape[0] + sidx
eidx = sidx + 1
step = 1
rowkey = Range(sidx, eidx, step)
elif isinstance(k, slice):
if isinstance(k.start, basestring):
t = miutil.str2date(k.start)
t = miutil.jdate(t)
sidx = self.data.getTimeIndex(t)
if sidx < 0:
sidx = 0
else:
sidx = 0 if k.start is None else k.start
if sidx < 0:
sidx = self.shape[0] + sidx
if isinstance(k.stop, basestring):
t = miutil.str2date(k.stop)
t = miutil.jdate(t)
eidx = self.data.getTimeIndex(t) + 1
if eidx < 0:
eidx = self.shape[0]
else:
eidx = self.shape[0] if k.stop is None else k.stop
if eidx < 0:
eidx = self.shape[0] + eidx
step = 1 if k.step is None else k.step
rowkey = Range(sidx, eidx, step)
elif isinstance(k, list):
if isinstance(k[0], basestring):
tlist = []
for tstr in k:
t = miutil.jdate(miutil.str2date(tstr))
idx = self.data.getTimeIndex_Ex(t)
if idx >= 0:
tlist.append(idx)
rowkey = tlist
else:
rowkey = k
else:
return None
tcolname = self.data.getTimeColName()
if not hascolkey:
r = self.data.select(rowkey)
if r.findColumn(tcolname) is None:
r = TableData(r)
else:
r = TimeTableData(r, tcolname)
return PyTableData(r)
k = key[1]
if isinstance(k, int):
sidx = k
if sidx < 0:
sidx = self.shape[1] + sidx
eidx = sidx + 1
step = 1
colkey = Range(sidx, eidx, step)
elif isinstance(k, slice):
sidx = 0 if k.start is None else k.start
if sidx < 0:
sidx = self.shape[1] + sidx
eidx = self.shape[1] if k.stop is None else k.stop
if eidx < 0:
eidx = self.shape[1] + eidx
step = 1 if k.step is None else k.step
colkey = Range(sidx, eidx, step)
elif isinstance(k, list):
if isinstance(k[0], basestring):
cols = self.data.findColumns(k)
else:
cols = self.data.findColumns_Index(k)
colkey = cols
elif isinstance(k, basestring):
rows = self.data.getRows(rowkey)
coldata = self.data.getColumnData(rows, k)
if coldata.getDataType().isNumeric():
return NDArray(ArrayUtil.array(coldata.getDataValues()))
else:
return NDArray(ArrayUtil.array(coldata.getData()))
else:
return None
r = self.data.select(rowkey, colkey)
if r.findColumn(tcolname) is None:
r = TableData(r)
else:
r = TimeTableData(r, tcolname)
return PyTableData(r)
