linopy.expressions.LinearExpression#

class linopy.expressions.LinearExpression(data, model)#

A linear expression consisting of terms of coefficients and variables.

The LinearExpression class is a subclass of xarray.Dataset which allows to apply most xarray functions on it. However most arithmetic operations are overwritten. Like this you can easily expand and modify the linear expression.

Examples

>>> from linopy import Model
>>> import pandas as pd
>>> m = Model()
>>> x = m.add_variables(pd.Series([0, 0]), 1, name="x")
>>> y = m.add_variables(4, pd.Series([8, 10]), name="y")

Combining expressions:

>>> expr = 3 * x
>>> type(expr)
<class 'linopy.expressions.LinearExpression'>

>>> other = 4 * y
>>> type(expr + other)
<class 'linopy.expressions.LinearExpression'>

Multiplying:

>>> type(3 * expr)
<class 'linopy.expressions.LinearExpression'>

Summation over dimensions

>>> type(expr.sum(dims="dim_0"))
<class 'linopy.expressions.LinearExpression'>
__init__(data, model)#

Methods

__init__(data, model)

assign([variables])

Wrapper for the xarray <function Dataset.assign at 0x7fbd830c2430> function for linopy.Variable

assign_attrs(*args, **kwargs)

Wrapper for the xarray <function DataWithCoords.assign_attrs at 0x7fbd83275280> function for linopy.Variable

assign_coords([coords])

Wrapper for the xarray <function DataWithCoords.assign_coords at 0x7fbd832751f0> function for linopy.Variable

astype(dtype, *[, order, casting, subok, ...])

Wrapper for the xarray <function DataWithCoords.astype at 0x7fbd83275820> function for linopy.Variable

bfill(dim[, limit])

Wrapper for the xarray <function Dataset.bfill at 0x7fbd830c2160> function for linopy.Variable

broadcast_like(other[, exclude])

Wrapper for the xarray <function Dataset.broadcast_like at 0x7fbd830bc940> function for linopy.Variable

chunk([chunks, name_prefix, token, lock, ...])

Wrapper for the xarray <function Dataset.chunk at 0x7fbd830bc3a0> function for linopy.Variable

cumsum([dim, skipna, keep_attrs])

Cumulated sum along a given axis.

densify_terms()

Move all non-zero term entries to the front and cut off all-zero entries in the term-axis.

diff(dim[, n])

Calculate the n-th order discrete difference along given axis.

drop([labels, dim, errors])

Wrapper for the xarray <function Dataset.drop at 0x7fbd830c0c10> function for linopy.Variable

drop_isel([indexers])

Wrapper for the xarray <function Dataset.drop_isel at 0x7fbd830c0d30> function for linopy.Variable

drop_sel([labels, errors])

Wrapper for the xarray <function Dataset.drop_sel at 0x7fbd830c0ca0> function for linopy.Variable

empty()

Get whether the linear expression is empty.

equals(other)

ffill(dim[, limit])

Wrapper for the xarray <function Dataset.ffill at 0x7fbd830c20d0> function for linopy.Variable

fillna(value)

Wrapper for the xarray <function Dataset.fillna at 0x7fbd830c0f70> function for linopy.Variable with default arguments: {'value': {'vars': -1, 'coeffs': nan, 'const': 0}}

from_rule(model, rule, coords)

Create a linear expression from a rule and a set of coordinates.

from_tuples(*tuples[, model, chunk])

Create a linear expression by using tuples of coefficients and variables.

groupby(group[, squeeze, restore_coord_dims])

Returns a LinearExpressionGroupBy object for performing grouped operations.

isel([indexers, drop, missing_dims])

Wrapper for the xarray <function Dataset.isel at 0x7fbd830bc5e0> function for linopy.Variable

print([display_max_rows, display_max_terms])

Print the linear expression.

reindex([indexers, method, tolerance, copy, ...])

Wrapper for the xarray <function Dataset.reindex at 0x7fbd830bcaf0> function for linopy.Variable with default arguments: {'fill_value': {'vars': -1, 'coeffs': nan, 'const': 0}}

reindex_like(other[, method, tolerance, ...])

Wrapper for the xarray <function Dataset.reindex_like at 0x7fbd830bca60> function for linopy.Variable with default arguments: {'fill_value': {'vars': -1, 'coeffs': nan, 'const': 0}}

rename([name_dict])

Wrapper for the xarray <function Dataset.rename at 0x7fbd830c0040> function for linopy.Variable

rename_dims([dims_dict])

Wrapper for the xarray <function Dataset.rename_dims at 0x7fbd830c00d0> function for linopy.Variable

reset_const()

Reset the constant of the linear expression to zero.

roll([shifts, roll_coords])

Wrapper for the xarray <function Dataset.roll at 0x7fbd830c2ee0> function for linopy.Variable

rolling([dim, min_periods, center])

Rolling window object.

sanitize()

Sanitize LinearExpression by ensuring int dtype for variables.

sel([indexers, method, tolerance, drop])

Wrapper for the xarray <function Dataset.sel at 0x7fbd830bc700> function for linopy.Variable

shift([shifts, fill_value])

Wrapper for the xarray <function Dataset.shift at 0x7fbd830c2e50> function for linopy.Variable

sum([dims, drop_zeros])

Sum the expression over all or a subset of dimensions.

to_constraint(sign, rhs)

Convert a linear expression to a constraint.

to_quadexpr()

Convert LinearExpression to QuadraticExpression.

where(cond[, other])

Filter variables based on a condition.

Attributes

attrs

coeffs

const

coord_dims

coords

data

dims

fill_value

flat

Convert the expression to a pandas DataFrame.

indexes

loc

mask

model

ndim

non_helper_dims

Deprecated since version Use: coord_dims instead

nterm

Get the number of terms in the linear expression.

shape

Get the total shape of the linear expression.

size

Get the total size of the linear expression.

sizes

type

vars