Methods specific to :pypyomo.contrib.pynumero.sparse.block_vector.BlockVector
:
- :py
~pyomo.contrib.pynumero.sparse.block_vector.BlockVector.set_block
- :py
~pyomo.contrib.pynumero.sparse.block_vector.BlockVector.get_block
- :py
~pyomo.contrib.pynumero.sparse.block_vector.BlockVector.block_sizes
- :py
~pyomo.contrib.pynumero.sparse.block_vector.BlockVector.get_block_size
- :py
~pyomo.contrib.pynumero.sparse.block_vector.BlockVector.is_block_defined
- :py
~pyomo.contrib.pynumero.sparse.block_vector.BlockVector.copyfrom
- :py
~pyomo.contrib.pynumero.sparse.block_vector.BlockVector.copyto
- :py
~pyomo.contrib.pynumero.sparse.block_vector.BlockVector.copy_structure
- :py
~pyomo.contrib.pynumero.sparse.block_vector.BlockVector.set_blocks
- :py
~pyomo.contrib.pynumero.sparse.block_vector.BlockVector.pprint
Attributes specific to :pypyomo.contrib.pynumero.sparse.block_vector.BlockVector
:
- :py
~pyomo.contrib.pynumero.sparse.block_vector.BlockVector.nblocks
- :py
~pyomo.contrib.pynumero.sparse.block_vector.BlockVector.bshape
- :py
~pyomo.contrib.pynumero.sparse.block_vector.BlockVector.has_none
NumPy compatible methods:
- numpy.ndarray.dot()
- numpy.ndarray.sum()
- numpy.ndarray.all()
- numpy.ndarray.any()
- numpy.ndarray.max()
- numpy.ndarray.astype()
- numpy.ndarray.clip()
- numpy.ndarray.compress()
- numpy.ndarray.conj()
- numpy.ndarray.conjugate()
- numpy.ndarray.nonzero()
- numpy.ndarray.ptp()
- numpy.ndarray.round()
- numpy.ndarray.std()
- numpy.ndarray.var()
- numpy.ndarray.tofile()
- numpy.ndarray.min()
- numpy.ndarray.mean()
- numpy.ndarray.prod()
- numpy.ndarray.fill()
- numpy.ndarray.tolist()
- numpy.ndarray.flatten()
- numpy.ndarray.ravel()
- numpy.ndarray.argmax()
- numpy.ndarray.argmin()
- numpy.ndarray.cumprod()
- numpy.ndarray.cumsum()
- numpy.ndarray.copy()
For example,
>>> import numpy as np
>>> from pyomo.contrib.pynumero.sparse import BlockVector
>>> v = BlockVector(2)
>>> v.set_block(0, np.random.normal(size=100))
>>> v.set_block(1, np.random.normal(size=30))
>>> avg = v.mean()
NumPy compatible functions:
- numpy.log10()
- numpy.sin()
- numpy.cos()
- numpy.exp()
- numpy.ceil()
- numpy.floor()
- numpy.tan()
- numpy.arctan()
- numpy.arcsin()
- numpy.arccos()
- numpy.sinh()
- numpy.cosh()
- numpy.abs()
- numpy.tanh()
- numpy.arccosh()
- numpy.arcsinh()
- numpy.arctanh()
- numpy.fabs()
- numpy.sqrt()
- numpy.log()
- numpy.log2()
- numpy.absolute()
- numpy.isfinite()
- numpy.isinf()
- numpy.isnan()
- numpy.log1p()
- numpy.logical_not()
- numpy.expm1()
- numpy.exp2()
- numpy.sign()
- numpy.rint()
- numpy.square()
- numpy.positive()
- numpy.negative()
- numpy.rad2deg()
- numpy.deg2rad()
- numpy.conjugate()
- numpy.reciprocal()
- numpy.signbit()
- numpy.add()
- numpy.multiply()
- numpy.divide()
- numpy.subtract()
- numpy.greater()
- numpy.greater_equal()
- numpy.less()
- numpy.less_equal()
- numpy.not_equal()
- numpy.maximum()
- numpy.minimum()
- numpy.fmax()
- numpy.fmin()
- numpy.equal()
- numpy.logical_and()
- numpy.logical_or()
- numpy.logical_xor()
- numpy.logaddexp()
- numpy.logaddexp2()
- numpy.remainder()
- numpy.heaviside()
- numpy.hypot()
For example,
>>> import numpy as np
>>> from pyomo.contrib.pynumero.sparse import BlockVector
>>> v = BlockVector(2)
>>> v.set_block(0, np.random.normal(size=100))
>>> v.set_block(1, np.random.normal(size=30))
>>> inf_norm = np.max(np.abs(v))
pyomo.contrib.pynumero.sparse.block_vector.BlockVector
pyomo.contrib.pynumero.sparse.block_vector.BlockVector.set_block
pyomo.contrib.pynumero.sparse.block_vector.BlockVector.get_block
pyomo.contrib.pynumero.sparse.block_vector.BlockVector.block_sizes
pyomo.contrib.pynumero.sparse.block_vector.BlockVector.get_block_size
pyomo.contrib.pynumero.sparse.block_vector.BlockVector.is_block_defined
pyomo.contrib.pynumero.sparse.block_vector.BlockVector.copyfrom
pyomo.contrib.pynumero.sparse.block_vector.BlockVector.copyto
pyomo.contrib.pynumero.sparse.block_vector.BlockVector.copy_structure
pyomo.contrib.pynumero.sparse.block_vector.BlockVector.set_blocks
pyomo.contrib.pynumero.sparse.block_vector.BlockVector.pprint
pyomo.contrib.pynumero.sparse.block_vector.BlockVector.nblocks
pyomo.contrib.pynumero.sparse.block_vector.BlockVector.bshape
pyomo.contrib.pynumero.sparse.block_vector.BlockVector.has_none