Cleanup matrix conversions

CHANGES.md

@@ -1,5 +1,10 @@
 # `bw2calc` Changelog
 
+## 2.0.DEV18 (2024-07-24)
+
+* [#101](https://github.com/brightway-lca/brightway2-calc/pull/101): Convert `technosphere_matrix` to `csr` when using `pypardiso` for speed boost on repeated calculations.
+* [#104](https://github.com/brightway-lca/brightway2-calc/pull/104): Explicitly set array-size in MultiLCA's `lci_calculation()`. Solves bug with a single functional unit passed to `MultiLCA`.
+
 ## 2.0.DEV17 (2024-06-05)
 
 ### New `MultiLCA` implementation

bw2calc/lca.py

@@ -170,6 +170,11 @@ def __next__(self) -> None:
  if not skip_first_iteration and hasattr(self, "after_matrix_iteration"):
  self.after_matrix_iteration()
 
+ # Avoid this conversion each time we do a calculation in the future
+ # See https://github.com/haasad/PyPardiso/issues/75#issuecomment-2186825609
+ if PYPARDISO:
+ self.technosphere_matrix = self.technosphere_matrix.tocsr()
+
  if skip_first_iteration:
  delattr(self, "keep_first_iteration_flag")
 

bw2calc/lca_base.py

@@ -1,7 +1,6 @@
 import warnings
 from collections.abc import Iterator
 from functools import partial
-from scipy.sparse import csc_matrix, csr_matrix
 from typing import Optional, Tuple
 
 import matrix_utils as mu
@@ -46,15 +45,14 @@ def load_lci_data(self, nonsquare_ok=False) -> None:
  use_distributions=use_distributions,
  seed_override=self.seed_override,
  )
-
- # explicitly set technosphere format to optimal CSR/CSC format depending on solver
- # see this link for discussion https://github.com/haasad/PyPardiso/issues/75#issuecomment-2186825609
- if PYPARDISO:
- self.technosphere_matrix = self.technosphere_mm.matrix.tocsr()
- else:
- self.technosphere_matrix = self.technosphere_mm.matrix.tocsc()
  self.dicts.product = partial(self.technosphere_mm.row_mapper.to_dict)
  self.dicts.activity = partial(self.technosphere_mm.col_mapper.to_dict)
+ self.technosphere_matrix = self.technosphere_mm.matrix
+
+ # Avoid this conversion each time we do a calculation in the future
+ # See https://github.com/haasad/PyPardiso/issues/75#issuecomment-2186825609
+ if PYPARDISO:
+ self.technosphere_matrix = self.technosphere_matrix.tocsr()
 
  if (
  len(self.technosphere_mm.row_mapper) != len(self.technosphere_mm.col_mapper)
@@ -126,8 +124,6 @@ def decompose_technosphere(self) -> None:
  if PYPARDISO:
  warnings.warn("PARDISO installed; this is a no-op")
  else:
- if isinstance(self.technosphere_matrix, csr_matrix):
- self.technosphere_matrix.tocsc()
  self.solver = factorized(self.technosphere_matrix)
 
  def solve_linear_system(self, demand: Optional[np.ndarray] = None) -> None:
@@ -154,14 +150,7 @@ def solve_linear_system(self, demand: Optional[np.ndarray] = None) -> None:
  if hasattr(self, "solver"):
  return self.solver(demand)
  else:
- if ((PYPARDISO and isinstance(self.technosphere_matrix, csr_matrix)) or
- (not PYPARDISO and isinstance(self.technosphere_matrix, csc_matrix))):
- return spsolve(self.technosphere_matrix, demand)
- elif PYPARDISO:
- return spsolve(self.technosphere_matrix.tocsr(), demand)
- else:
- return spsolve(self.technosphere_matrix.tocsc(), demand)
-
+ return spsolve(self.technosphere_matrix, demand)
 
  def lci(self, demand: Optional[dict] = None, factorize: bool = False) -> None:
  """

bw2calc/multi_lca.py

@@ -1,7 +1,6 @@
 import logging
 import warnings
 from pathlib import Path
-from scipy.sparse import csc_matrix, csr_matrix
 from typing import Iterable, Optional, Union
 
 import bw_processing as bwp
@@ -184,6 +183,11 @@ def __next__(self) -> None:
  if not skip_first_iteration and hasattr(self, "after_matrix_iteration"):
  self.after_matrix_iteration()
 
+ # Avoid this conversion each time we do a calculation in the future
+ # See https://github.com/haasad/PyPardiso/issues/75#issuecomment-2186825609
+ if PYPARDISO:
+ self.technosphere_matrix = self.technosphere_matrix.tocsr()
+
  if skip_first_iteration:
  delattr(self, "keep_first_iteration_flag")
 
@@ -350,8 +354,12 @@ def lci_calculation(self) -> None:
  """
  count = len(self.dicts.activity)
  demand_matrix = np.vstack([arr for arr in self.demand_arrays.values()]).T
- solutions = spsolve(self.technosphere_matrix, demand_matrix).reshape(count, -1)
- self.supply_arrays = {name: arr for name, arr in zip(self.demands, solutions.T)}
+ self.supply_arrays = {
+ name: arr
+ for name, arr in zip(
+ self.demands, spsolve(self.technosphere_matrix, demand_matrix).reshape(count, -1).T
+ )
+ }
  # Turn 1-d array into diagonal matrix
  self.inventories = mu.SparseMatrixDict(
  [

tests/multi_lca.py

@@ -133,7 +133,7 @@ def test_single_demand(dps, config):
  mlca = MultiLCA(demands=single_func_unit, method_config=config, data_objs=dps)
  mlca.lci()
  mlca.lcia()
- 
+
  assert mlca.scores[(("first", "category"), "γ")] == 8 + 3
  assert mlca.scores[(("second", "category"), "γ")] == 3 * 10