def arange(start, stop=None, step=1, dtype=None):
"""arange([start,] stop[, step=1])
Return evenly spaced values within a given interval.
Values are generated within the half-open interval ``[start, stop)``
(in value words, the interval including `start` but excluding `stop`).
Parameters
----------
start : number, optional
Start of interval. The interval includes this value. The default
start value is 0.
stop : number
End of interval. The interval does not include this value.
step : number, optional
Spacing between values. For any output `out`, this is the distance
between two adjacent values, ``out[i+1] - out[i]``. The default
step size is 1. If `step` is specified, `start` must also be given.
Examples:
arange(5)
arange(1, 5, 0.5)
"""
if stop is None:
# Only one number given, which is the 'stop'
stop = start
start = 0
if dtype is None:
return ndarray(NDMatrix.arange(start, stop, step))
else:
return ndarray(NDMatrix.arange(start, stop, step, dtype))
def arange(start, stop=None, step=1, dtype=None):
"""arange([start,] stop[, step=1])
Return evenly spaced values within a given interval.
Values are generated within the half-open interval ``[start, stop)``
(in value words, the interval including `start` but excluding `stop`).
Parameters
----------
start : number, optional
Start of interval. The interval includes this value. The default
start value is 0.
stop : number
End of interval. The interval does not include this value.
step : number, optional
Spacing between values. For any output `out`, this is the distance
between two adjacent values, ``out[i+1] - out[i]``. The default
step size is 1. If `step` is specified, `start` must also be given.
Examples:
arange(5)
arange(1, 5, 0.5)
"""
if stop is None:
# Only one number given, which is the 'stop'
stop = start
start = 0
if dtype is None:
return ndarray(NDMatrix.arange(start, stop, step))
else:
return ndarray(NDMatrix.arange(start, stop, step, dtype))
def dot(a, b):
"""dot(a, b):
Determine matrix 'dot' product of arrays a and b
"""
result = ndarray(NDMatrix.dot(a.nda, b.nda))
if result.ndim == 1 and len(result) == 1:
return result[0]
return result
def linspace(start, stop, num=50, dtype=float):
"""linspace(start, stop, num=50, dtype=float)
Return evenly spaced values from start to stop, including stop.
Example:
linspace(2, 10, 5)
"""
return ndarray(NDMatrix.linspace(start, stop, num, dtype))
def zeros(shape, dtype=float):
"""zeros(shape, dtype=float)
Create array of zeros, example:
zeros( (2, 3) )
"""
return ndarray(NDMatrix.zeros(dtype, __toNDShape__(shape)))
def ones(shape, dtype=float):
"""ones(shape, dtype=float)
Create array of ones, example:
ones( (2, 3) )
"""
return ndarray(NDMatrix.ones(dtype, __toNDShape__(shape)))
def dot(a, b):
"""dot(a, b):
Determine matrix 'dot' product of arrays a and b
"""
result = ndarray(NDMatrix.dot(a.nda, b.nda))
if result.ndim == 1 and len(result) == 1:
return result[0]
return result
def linspace(start, stop, num=50, dtype=float):
"""linspace(start, stop, num=50, dtype=float)
Return evenly spaced values from start to stop, including stop.
Example:
linspace(2, 10, 5)
"""
return ndarray(NDMatrix.linspace(start, stop, num, dtype))
def ones(shape, dtype=float):
"""ones(shape, dtype=float)
Create array of ones, example:
ones( (2, 3) )
"""
return ndarray(NDMatrix.ones(dtype, __toNDShape__(shape)))
def zeros(shape, dtype=float):
"""zeros(shape, dtype=float)
Create array of zeros, example:
zeros( (2, 3) )
"""
return ndarray(NDMatrix.zeros(dtype, __toNDShape__(shape)))
def transpose(a, axes=None):
"""transpose(a, axes=None):
Permute the axes of an array.
By default, they are reversed.
In a 2D array this would swap 'rows' and 'columns'
"""
if axes is None:
return a.transpose()
return ndarray(NDMatrix.transpose(a.nda, axes))
def reshape(a, shape):
"""reshape(array, shape):
Create array view with new shape
Example:
reshape(arange(6), (3, 2))
results in array([ [ 0, 1 ], [ 2, 3 ], [ 4, 5 ] ])
"""
return ndarray(NDMatrix.reshape(self.nda, __toNDShape__(shape)))
def transpose(a, axes=None):
"""transpose(a, axes=None):
Permute the axes of an array.
By default, they are reversed.
In a 2D array this would swap 'rows' and 'columns'
"""
if axes is None:
return a.transpose()
return ndarray(NDMatrix.transpose(a.nda, axes))
def reshape(a, shape):
"""reshape(array, shape):
Create array view with new shape
Example:
reshape(arange(6), (3, 2))
results in array([ [ 0, 1 ], [ 2, 3 ], [ 4, 5 ] ])
"""
return ndarray(NDMatrix.reshape(self.nda, __toNDShape__(shape)))
def transpose(self):
"""Compute transposed array, i.e. swap 'rows' and 'columns'"""
return ndarray(NDMatrix.transpose(self.nda))
def transpose(self):
"""Compute transposed array, i.e. swap 'rows' and 'columns'"""
return ndarray(NDMatrix.transpose(self.nda))