- Update to 1.10.0:

* Breaking Changes
    + renamed MatrixProductState.partial_trace and MatrixProductState.ptr to
      MatrixProductState.partial_trace_to_mpo to avoid confusion with other
      partial_trace methods that usually produce a dense matrix.
  * Enhancements:
    + tensor network fitting: add method="tree" for when ansatz is a tree -
      tensor_network_fit_tree
    + tensor network fitting: fix method="als" for complex networks
    + tensor network fitting: allow method="als" to use a iterative solver
      suited to much larger tensors, by default a custom conjugate gradient
      implementation.
    + tensor_network_distance and fitting: support hyper indices explicitly
      via output_inds kwarg
    + add tn.make_overlap and tn.overlap for computing the overlap between
      two tensor networks, ⟨ O | T ⟩ , with explicit handling of outer
      indices to address hyper networks. Add output_inds to tn.norm and
      tn.make_norm also, as well as the squared kwarg.
    + replace all numba based paralellism (prange and parallel vectorize)
      with explicit thread pool based parallelism. Should be more reliable
      and no need to set NUMBA_NUM_THREADS anymore. Remove env var
      QUIMB_NUMBA_PAR.
    + Circuit: add dtype and convert_eager options. dtype specifies what the
      computation should be performed in. convert_eager specifies whether to
      apply this (and any to_backend calls) as soon as gates are applied
      (the default for MPS circuit simulation) or just prior to contraction
      (the default for exact contraction simulation).
    + tn.full_simplify: add check_zero (by default set of "auto") option
      which explicitly checks for zero tensor norms when equalizing norms to
      avoid log10(norm) resulting in -inf or nan. Since it creates a data

OBS-URL: https://build.opensuse.org/package/show/devel:languages:python:numeric/python-quimb?expand=0&rev=23

.gitattributes

@@ -0,0 +1,23 @@
+## Default LFS
+*.7z filter=lfs diff=lfs merge=lfs -text
+*.bsp filter=lfs diff=lfs merge=lfs -text
+*.bz2 filter=lfs diff=lfs merge=lfs -text
+*.gem filter=lfs diff=lfs merge=lfs -text
+*.gz filter=lfs diff=lfs merge=lfs -text
+*.jar filter=lfs diff=lfs merge=lfs -text
+*.lz filter=lfs diff=lfs merge=lfs -text
+*.lzma filter=lfs diff=lfs merge=lfs -text
+*.obscpio filter=lfs diff=lfs merge=lfs -text
+*.oxt filter=lfs diff=lfs merge=lfs -text
+*.pdf filter=lfs diff=lfs merge=lfs -text
+*.png filter=lfs diff=lfs merge=lfs -text
+*.rpm filter=lfs diff=lfs merge=lfs -text
+*.tbz filter=lfs diff=lfs merge=lfs -text
+*.tbz2 filter=lfs diff=lfs merge=lfs -text
+*.tgz filter=lfs diff=lfs merge=lfs -text
+*.ttf filter=lfs diff=lfs merge=lfs -text
+*.txz filter=lfs diff=lfs merge=lfs -text
+*.whl filter=lfs diff=lfs merge=lfs -text
+*.xz filter=lfs diff=lfs merge=lfs -text
+*.zip filter=lfs diff=lfs merge=lfs -text
+*.zst filter=lfs diff=lfs merge=lfs -text

.gitignore

@@ -0,0 +1 @@
+.osc

_multibuild

@@ -0,0 +1,3 @@
+<multibuild>
+  <package>test</package>
+</multibuild>

python-quimb.changes

@@ -0,0 +1,453 @@
+-------------------------------------------------------------------
+Wed Feb 26 03:56:01 UTC 2025 - Steve Kowalik <steven.kowalik@suse.com>
+
+- Update to 1.10.0:
+  * Breaking Changes
+    + renamed MatrixProductState.partial_trace and MatrixProductState.ptr to
+      MatrixProductState.partial_trace_to_mpo to avoid confusion with other
+      partial_trace methods that usually produce a dense matrix.
+  * Enhancements:
+    + tensor network fitting: add method="tree" for when ansatz is a tree -
+      tensor_network_fit_tree
+    + tensor network fitting: fix method="als" for complex networks
+    + tensor network fitting: allow method="als" to use a iterative solver
+      suited to much larger tensors, by default a custom conjugate gradient
+      implementation.
+    + tensor_network_distance and fitting: support hyper indices explicitly
+      via output_inds kwarg
+    + add tn.make_overlap and tn.overlap for computing the overlap between
+      two tensor networks, ⟨ O | T ⟩ , with explicit handling of outer
+      indices to address hyper networks. Add output_inds to tn.norm and
+      tn.make_norm also, as well as the squared kwarg.
+    + replace all numba based paralellism (prange and parallel vectorize)
+      with explicit thread pool based parallelism. Should be more reliable
+      and no need to set NUMBA_NUM_THREADS anymore. Remove env var
+      QUIMB_NUMBA_PAR.
+    + Circuit: add dtype and convert_eager options. dtype specifies what the
+      computation should be performed in. convert_eager specifies whether to
+      apply this (and any to_backend calls) as soon as gates are applied
+      (the default for MPS circuit simulation) or just prior to contraction
+      (the default for exact contraction simulation).
+    + tn.full_simplify: add check_zero (by default set of "auto") option
+      which explicitly checks for zero tensor norms when equalizing norms to
+      avoid log10(norm) resulting in -inf or nan. Since it creates a data
+      dependency that breaks e.g. jax tracing, it is optional.
+    + schematic.Drawing: add shorten kwarg to line drawing and curve drawing
+      and examples to {ref}schematic.
+    + TensorNetwork: add .backend and .dtype_name properties.
+    + add Circuit.sample_gate_by_gate and related methods
+      CircuitMPS.reordered_gates_dfs_clustered and
+      CircuitMPS.get_qubit_distances for sampling a circuit using the
+      'gate by gate' method introduced in https://arxiv.org/abs/2112.08499.
+    + add Circuit.draw for drawing a very simple circuit schematic.
+    + Circuit: by default turn on simplify_equalize_norms and use a
+      group_size=10 for sampling. This should result in faster and more
+      stable sampling.
+    + Circuit: use numpy.random.default_rng for random number generation.
+    + add qtn.circ_a2a_rand for generating random all-to-all circuits.
+    + expose qtn.edge_coloring as top level function and allow layers to be
+      returned grouped.
+    + add docstring for tn.contract_compressed and by default pick up
+      important settings from the supplied contraction path optimizer
+      (max_bond and compress_late)
+    + add Tensor.rand_reduce for randomly removing a tensor index by
+      contracting a random vector into it. One can also supply the value "r"
+      to isel selectors to use this.
+    + add fit-zipup and fit-projector shorthand methods to the general 1d
+      tensor network compression function
+    + add MatrixProductState.compute_local_expectation for computing many
+      local expectations for a MPS at once, to match the interface for this
+      method elsewhere. These can either be computed via canonicalization
+      (method="canonical"), or via explicit left and right environment
+      contraction (method="envs")
+    + specialize CircuitMPS.local_expectation to make use of the MPS form.
+    + add PEPS.product_state for constructing a PEPS representing a product
+      state.
+    + add PEPS.vacuum for constructing a PEPS representing the vacuum
+      state | 000 … 0 ⟩ .
+    + add PEPS.zeros for constructing a PEPS whose entries are all zero.
+    + tn.gauge_all_simple: improve scheduling and add damping and
+      touched_tids options.
+    + qtn.SimpleUpdateGen: add gauge difference update checking and tol and
+      equilibrate settings. Update .plot() method. Default to a small cutoff.
+    + add psi.sample_configuration_cluster for sampling a tensor network
+      using the simple update or cluster style environment approximation.
+    + add the new doc {ref}ex-circuit-sampling
+
+-------------------------------------------------------------------
+Mon Sep 23 19:48:30 UTC 2024 - Ben Greiner <code@bnavigator.de>
+
+- Switch to testing in multibuild: The obs runtime requirement
+  resolver deals with numba/numpy blockage more gracefully than
+  trying to resolve a BuildRequires on them. Numba 0.60 is
+  restricted to Numpy < 2.1 right now.
+* Update requirements
+
+-------------------------------------------------------------------
+Sat Aug 31 11:54:18 UTC 2024 - Dirk Müller <dmueller@suse.com>
+
+- update to 1.8.4:
+  * support for numpy v2.0 and scipy v1.14
+  * add MPS sampling: `MatrixProductState.sample_configuration`
+    and `MatrixProductState.sample` (generating multiple samples)
+    and use these for `CircuitMPS.sample` and
+    `CircuitPermMPS.sample`.
+  * add basic `.plot()` method for SimpleUpdate classes
+  * add `edges_1d_chain` for generating 1D chain edges
+  * operatorbuilder: better coefficient placement for long range
+    MPO building
+  * `TNOptimizer` can now accept an arbitrary pytree (nested
+    combination of dicts, lists, tuples, etc. with
+    `TensorNetwork`, `Tensor` or raw `array_like` objects as the
+    leaves) as the target object to optimize.
+  * `TNOptimizer` can now directly optimize `Circuit` objects,
+    returning a new optimized circuit with updated parameters.
+  * `Circuit`: add `.copy()`, `.get_params()` and `.set_params()`
+    interface methods.
+  * Update generic TN optimizer docs.
+  * add `tn.gen_inds_loops` for generating all loops of indices
+    in a TN.
+  * add `tn.gen_inds_connected` for generating all connected sets
+    of indices in a TN.
+  * make SVD fallback error catching more generic ({pull}`#238`)
+  * fix some windows + numba CI issues.
+  * `approx_spectral_function` add plotting and tracking
+  * add dispatching to various tensor primitives to allow
+    overriding
+  * `CircuitMPS` now supports multi qubit gates, including
+    arbitrary multi-controls (which are treated in a low-rank
+    manner), and faster simulation via better orthogonality
+    center tracking.
+  * add `CircuitPermMPS`
+  * add `MatrixProductState.gate_nonlocal` for applying a gate,
+    supplied as a raw matrix, to a non-local and arbitrary number
+    of sites. The kwarg `contract="nonlocal"` can be used to
+    force this method, or the new option `"auto-mps"` will select
+    this method if the gate is non-local ({issue}`230`)
+  * add `MatrixProductState.gate_with_mpo` for applying an MPO to
+    an MPS, and immediately compressing back to MPS form using
+    `tensor_network_1d_compress`
+  * add `MatrixProductState.gate_with_submpo` for applying an MPO
+    acting only of a subset of sites to an MPS
+  * add `MatrixProductOperator.from_dense` for constructing MPOs
+    from dense matrices, including an only subset of sites
+  * add `MatrixProductOperator.fill_empty_sites` for 'completing'
+    an MPO which only has tensors on a subset of sites with (by
+    default) identities
+  *  `MatrixProductState` and `MatrixProductOperator`, now
+    support the ``sites`` kwarg in common constructors, enabling
+    the TN to act on a subset of the full ``L`` sites.
+  * add `TensorNetwork.drape_bond_between` for 'draping' an
+    existing bond between two tensors through a third
+  * add `Tensor.new_ind_pair_with_identity`
+  * TN2D, TN3D and arbitrary geom classical partition function
+    builders (`TN_classical_partition_function_from_edges`) now
+    all support `outputs=` kwarg specifying non-marginalized
+    variables
+  * add simple dense 1-norm belief propagation algorithm `D1BP`
+  * add `qtn.enforce_1d_like` for checking whether a tensor
+    network is 1D-like, including automatically adding strings of
+    identities between non-local bonds, expanding applicability
+    of `tensor_network_1d_compress`
+  * add `MatrixProductState.canonicalize` as (by default *non-
+    inplace*) version of `canonize`, to follow the pattern of
+    other tensor network methods. `canonize` is now an alias for
+    `canonicalize_` [note trailing underscore].
+  * add `MatrixProductState.left_canonicalize` as (by default
+    *non-inplace*) version of `left_canonize`, to follow the
+    pattern of other tensor network methods. `left_canonize` is
+    now an alias for `left_canonicalize_` [note trailing
+    underscore].
+  * add `MatrixProductState.right_canonicalize` as (by default
+    *non-inplace*) version of `right_canonize`, to follow the
+    pattern of other tensor network methods. `right_canonize` is
+    now an alias for `right_canonicalize_` [note trailing
+    underscore].
+  * add `quimb.tensor.tensor_1d_compress.py` with functions for
+    compressing generic
+  * fix scipy sparse monkey patch for scipy>=1.13 ({issue}`222`)
+  * fix autoblock bug where connected sectors were not being
+    merged ({issue}`223`)
+
+-------------------------------------------------------------------
+Tue Feb 27 20:12:07 UTC 2024 - Ben Greiner <code@bnavigator.de>
+
+- Update to 1.7.3
+ ## Enhancements:
+  * qu.randn: support dist="rademacher".
+  * support dist and other randn options in various TN builders.
+  ## Bug fixes:
+  * restore fallback (to scipy.linalg.svd with driver='gesvd')
+    behavior for truncated SVD with numpy backend.
+- Release 1.7.2
+  ## Bug fixes:
+  * removed import of deprecated numba.generated_jit decorator.
+  ## Enhancements:
+  * add normalized=True option to tensor_network_distance for
+    computing the normalized distance between tensor networks,
+    which is useful for convergence checks.
+    Tensor.distance_normalized and
+    TensorNetwork.distance_normalized added as aliases.
+  * add TensorNetwork.cut_bond for cutting a bond index
+- Release v1.7.1
+  ## Enhancements:
+  * add TensorNetwork.visualize_tensors for visualizing the actual
+    data entries of an entire tensor network.
+  * add ham.build_mpo_propagator_trotterized for building a
+    trotterized propagator from a local 1D hamiltonian. This also
+    includes updates for creating 'empty' tensor networks using
+    TensorNetwork.new, and building up gates from empty tensor
+    networks using TensorNetwork.gate_inds_with_tn.
+  * add more options to Tensor.expand_ind and Tensor.new_ind:
+    repeat tiling mode and random padding mode.
+  * tensor decomposition: make eigh_truncated backend agnostic.
+  * tensor_compress_bond: add reduced="left" and reduced="right"
+    modes for when the pair of tensors is already in a canonical
+    form.
+  * add qtn.TN2D_embedded_classical_ising_partition_function for
+    constructing 2D (triangular) tensor networks representing
+    all-to-all classical ising partition functions.
+  ## Bug fixes:
+  * fix bug in kruas_op when operator spanned multiple subsystems
+    (#214)
+  * fix bug in qr_stabilized when the diagonal of R has significant
+    imaginary parts.
+  * fix bug in quantum discord computation when the state was
+    diagonal (#217)
+  * Fix empty lines in dimacs by @jjcmoon in #215
+- Release 1.7.0
+  ## Breaking Changes
+  * Circuit : remove target_size in preparation for all contraction
+    specifications to be encapsulated at the contract level (e.g.
+    with cotengra) some TN drawing options (mainly arrow options)
+    have changed due to the backend change detailed below.
+  ## Enhancements:
+  * Multi tag drawing support
+  * TensorNetwork.draw: use quimb.schematic for main
+    backend="matplotlib" drawing. Enabling:
+    - multi tag coloring for single tensors
+    - arrows and labels on multi-edges
+    - better sizing of tensors using absolute units
+    - neater single tensor drawing, in 2D and 3D
+  * add quimb.schematic.Drawing from experimental submodule, add
+    example docs at schematic. Add methods text_between, wedge,
+    line_offset and other tweaks for future use by main TN drawing.
+  * upgrade all contraction to use cotengra as the backend
+  * Circuit : allow any gate to be controlled by any number of
+    qubits.
+  * Circuit : support for parsing openqasm2 specifications now with
+    custom and nested gate definitions etc.
+  * add is_cyclic_x, is_cyclic_y) and is_cyclic_z to
+    TensorNetwork2D and TensorNetwork3D.
+  * add TensorNetwork.compress_all_1d for compressing generic
+    tensor networks that you promise have a 1D topology, without
+    casting as a TensorNetwork1D.
+  * add MatrixProductState.from_fill_fn for constructing MPS from a
+    function that fills the tensors.
+  * add Tensor.idxmin and Tensor.idxmax for finding the index of
+    the minimum / maximum element.
+  * 2D and 3D classical partition function TN builders: allow
+    output indices.
+  * quimb.experimental.belief_propagation: add various
+    1-norm/2-norm dense/lazy BP algorithms.
+  ## Bug fixes:
+  * fixed bug where an output index could be removed by squeezing
+    when performing tensor network simplifications.
+  * Fix deprecation warnings by @king-p3nguin in #209
+- Release v1.6.0
+  ## Breaking Changes
+  * Quantum circuit RZZ definition corrected (angle changed by -1/2
+    to match qiskit).
+  ## Enhancements:
+  * add OpenQASM 2.0 parsing support:
+    :meth:Circuit.from_openqasm2_file
+  * :class:Circuit: add RXX, RYY, CRX, CRY, CRZ, toffoli, fredkin,
+    givens gates
+  * truncate TN pretty html reprentation to 100 tensors for
+    performance
+  * add :meth:Tensor.sum_reduce and :meth:Tensor.vector_reduce
+  * :meth:contract_compressed, default to 'virtual-tree' gauge
+  * add :func:TN_rand_tree
+  * experimental.operatorbuilder: fix parallel and heisenberg
+    builder
+  * make parametrized gate generation even more robost (ensure
+    matching types so e.g. tensorflow can be used)
+  ## Bug fixes:
+  * fix gauge size check for some backends
+- Release 1.5.1
+  * add various MPO-MPS gate methods, including zip-up and density
+    matrix, in the experimental submodule
+  * some PTensor refactoring
+  * Circuit: more robust parametrized gate generation
+  * various new contraction convenience interfaces (incld.
+    array_contract)
+  * add Tensor.check() and TensorNetwork.check() for diagnostics
+  * add TensorNetwork.isconnected(), TensorNetwork.istree()
+- Release 1.5.0
+  ## Enhancements
+  * refactor 'isometrize' methods including new "cayley",
+    "householder" and "torch_householder" methods. See
+    :func:quimb.tensor.decomp.isometrize.
+  * add
+    :meth:~quimb.tensor.tensor_core.TensorNetwork.compute_reduced_factor
+    and
+    :meth:~quimb.tensor.tensor_core.TensorNetwork.insert_compressor_between_regions
+    methos, for some RG style algorithms.
+  * add the mode="projector" option for 2D tensor network
+    contractions
+  * add HOTRG style coarse graining and contraction in 2D and 3D.
+    See
+    :meth:~quimb.tensor.tensor_2d.TensorNetwork2D.coarse_grain_hotrg,
+    :meth:~quimb.tensor.tensor_2d.TensorNetwork2D.contract_hotrg,
+    :meth:~quimb.tensor.tensor_3d.TensorNetwork3D.coarse_grain_hotrg,
+    and
+    :meth:~quimb.tensor.tensor_3d.TensorNetwork3D.contract_hotrg,
+  * add CTMRG style contraction for 2D tensor networks:
+    :meth:~quimb.tensor.tensor_2d.TensorNetwork2D.contract_ctmrg
+  * add 2D tensor network 'corner double line' (CDL) builders:
+    :func:~quimb.tensor.tensor_builder.TN2D_corner_double_line
+  * update the docs to use the furo <https://pradyunsg.me/furo/>_
+    theme, myst_nb <https://myst-nb.readthedocs.io/en/latest/>_ for
+    notebooks, and several other sphinx extensions.
+  * add the 'adabelief' optimizer to
+    :class:~quimb.tensor.optimize.TNOptimizer as well as a quick
+    plotter: :meth:~quimb.tensor.optimize.TNOptimizer.plot
+  * add initial 3D plotting methods for tensors networks (
+    TensorNetwork.draw(dim=3, backend='matplotlib3d') or
+    TensorNetwork.draw(dim=3, backend='plotly') ). The new
+    backend='plotly' can also be used for 2D interactive plots.
+  * Update :func:~quimb.tensor.tensor_builder.HTN_from_cnf to
+    handle more weighted model counting formats.
+  * Add :func:~quimb.tensor.tensor_builder.cnf_file_parse
+  * Add :func:~quimb.tensor.tensor_builder.random_ksat_instance
+  * Add :func:~quimb.tensor.tensor_builder.TN_from_strings
+  * Add :func:~quimb.tensor.tensor_builder.convert_to_2d
+  * Add :func:~quimb.tensor.tensor_builder.TN2D_rand_hidden_loop
+  * Add :func:~quimb.tensor.tensor_builder.convert_to_3d
+  * Add :func:~quimb.tensor.tensor_builder.TN3D_corner_double_line
+  * Add :func:~quimb.tensor.tensor_builder.TN3D_rand_hidden_loop
+  * various optimizations for minimizing computational graph size
+    and
+  * construction time.
+  * add 'lu', 'polar_left' and 'polar_right' methods to
+    :func:~quimb.tensor.tensor_core.tensor_split.
+  * add experimental arbitrary hamilotonian MPO building
+  * :class:~quimb.tensor.tensor_core.TensorNetwork: allow empty
+    constructor (i.e. no tensors representing simply the scalar 1)
+  * :meth:~quimb.tensor.tensor_core.TensorNetwork.drop_tags: allow
+    all tags to be dropped
+  * tweaks to compressed contraction and gauging
+  * add jax, flax and optax example
+  * add 3D and interactive plotting of tensors networks with via
+    plotly.
+  * add pygraphiviz layout options
+  * add :meth:~quimb.tensor.tensor_core.TensorNetwork.combine for
+    unified handling of combining tensor networks potentially with
+    structure
+  * add HTML colored pretty printing of tensor networks for
+    notebooks
+  * add quimb.experimental.cluster_update.py
+  ## Bug fixes:
+  * fix :func:~quimb.tensor.decomp.qr_stabilized bug for strictly
+    upper triangular R factors.
+- Run tests in parallel (rerun flaky precision errors)
+
+-------------------------------------------------------------------
+Thu Jun  1 07:31:29 UTC 2023 - Steve Kowalik <steven.kowalik@suse.com>
+
+- Numba now exists for Python 3.11, stop skipping it.
+
+-------------------------------------------------------------------
+Thu Mar 23 06:51:10 UTC 2023 - Ben Greiner <code@bnavigator.de>
+
+- Skip python311: no numba yet
+
+-------------------------------------------------------------------
+Thu Feb  2 09:37:02 UTC 2023 - Dirk Müller <dmueller@suse.com>
+
+- upgrade opt-einsum to requires as it is imported by tensor/
+  unconditionally
+
+-------------------------------------------------------------------
+Sat Jan 14 11:35:41 UTC 2023 - Ben Greiner <code@bnavigator.de>
+
+- Update to v1.4.2
+  * no relevant code changes for openSUSE users
+- Release v1.4.1
+  ## Enhancements
+  * unify much functionality from 1D, 2D and 3D into general
+    arbitrary geometry class
+    quimb.tensor.tensor_arbgeom.TensorNetworkGen
+  * refactor contraction, allowing using cotengra directly
+  * add visualize() for visualizing the actual data entries of an
+    arbitrarily high dimensional tensor
+  * add Gate class for more robust tracking and manipulation of
+    gates in quantum Circuit simulation
+  * tweak TN drawing style and layout
+  * tweak default gauging options of compressed contraction
+  * add compute_hierarchical_grouping()
+  * add as_network()
+  * add inds_size()
+  * add get_hyperinds()
+  * add outer_size()
+  * improve group_inds()
+  * refactor tensor decompositiona and ‘isometrization’ methods
+  * begin supporting pytree specifications in TNOptimizer, e.g. for
+    constants
+  * add experimental submodule for new sharing features
+  * register tensor and tensor network objects with jax pytree
+    interface (PR150)
+  * update CI infrastructure
+  ## Bug fixes:
+  * fix force atlas 2 and weight_attr bug (GH126)
+  * allow unpickling of PTensor objects (GH128, PR131)
+- Release v1.4.0
+  ## Enhancements
+  * Add 2D tensor network support and algorithms
+  * Add 3D tensor network infrastructure
+  * Add arbitrary geometry quantum state infrastructure
+  * Many changes to TNOptimizer
+  * Many changes to TN drawing
+  * Many changes to Circuit simulation
+  * Many improvements to TN simplification
+  * Make all tag and index operations deterministic
+  * Add tensor_network_sum(), tensor_network_distance() and fit()
+  * Various memory and performance improvements
+  * Various graph generators and TN builders
+
+-------------------------------------------------------------------
+Fri Feb  5 20:13:46 UTC 2021 - Benjamin Greiner <code@bnavigator.de>
+
+- Generalize the ExcludeArch into %ix64 %arm ppc s390x
+
+-------------------------------------------------------------------
+Thu Feb  4 22:31:53 UTC 2021 - Benjamin Greiner <code@bnavigator.de>
+
+- Disable build for armv7l and s390x
+
+-------------------------------------------------------------------
+Tue Jan 19 09:36:08 UTC 2021 - andy great <andythe_great@pm.me>
+
+- Disable build for python36 because scipy.
+
+-------------------------------------------------------------------
+Sat Aug 22 07:04:12 UTC 2020 - andy great <andythe_great@pm.me>
+
+- Clean up spec file.
+
+-------------------------------------------------------------------
+Wed Aug 19 13:39:27 UTC 2020 - andy great <andythe_great@pm.me>
+
+- Remove noarch macro from spec file.
+
+-------------------------------------------------------------------
+Wed Aug 19 07:07:33 UTC 2020 - andy great <andythe_great@pm.me>
+
+- Disable build for 32-bit arch because numba and parallel does not
+  support 32-bit arch. Tried to export variable
+  "export QUIMB_NUMBA_PARALLEL=off" does not solve the issue.
+
+-------------------------------------------------------------------
+Tue Aug 18 09:36:15 UTC 2020 - andy great <andythe_great@pm.me>
+
+- Initial package release.

python-quimb.spec

@@ -0,0 +1,110 @@
+#
+# spec file for package python-quimb
+#
+# Copyright (c) 2025 SUSE LLC
+#
+# All modifications and additions to the file contributed by third parties
+# remain the property of their copyright owners, unless otherwise agreed
+# upon. The license for this file, and modifications and additions to the
+# file, is the same license as for the pristine package itself (unless the
+# license for the pristine package is not an Open Source License, in which
+# case the license is the MIT License). An "Open Source License" is a
+# license that conforms to the Open Source Definition (Version 1.9)
+# published by the Open Source Initiative.
+
+# Please submit bugfixes or comments via https://bugs.opensuse.org/
+#
+
+
+%global flavor @BUILD_FLAVOR@%{nil}
+%if "%{flavor}" == ""
+%define psuffix %{nil}
+%bcond_with test
+BuildArch:      noarch
+%else
+%bcond_without test
+%define psuffix -%{flavor}
+# This package does not support 32 bit arch, s390x fails too
+ExcludeArch:    %{ix86} %{arm} ppc s390x
+%endif
+
+Name:           python-quimb%{psuffix}
+Version:        1.10.0
+Release:        0
+Summary:        Python library for quantum information and many-body calculations
+License:        Apache-2.0
+URL:            https://quimb.readthedocs.io/
+Source:         https://github.com/jcmgray/quimb/archive/refs/tags/v%{version}.tar.gz#/quimb-%{version}.tar.gz
+BuildRequires:  %{python_module hatch_vcs}
+BuildRequires:  %{python_module hatchling}
+BuildRequires:  %{python_module pip}
+BuildRequires:  fdupes
+BuildRequires:  python-rpm-macros
+Requires:       python-autoray >= 0.6.12
+Requires:       python-cotengra >= 0.6.1
+Requires:       python-cytoolz >= 0.8.0
+Requires:       python-numba >= 0.39
+Requires:       python-numpy >= 1.17
+Requires:       python-psutil >= 4.3.1
+Requires:       python-scipy >= 1.0.0
+Requires:       python-tqdm >= 4
+Requires(post): update-alternatives
+Requires(postun): update-alternatives
+Recommends:     python-diskcache >= 3.0
+Recommends:     python-matplotlib >= 2
+Recommends:     python-networkx >= 2.3
+Suggests:       python-mpi4py
+Suggests:       python-petsc4py
+Suggests:       python-slepc4py
+%if %{with test}
+BuildRequires:  %{python_module quimb = %{version}}
+##
+BuildRequires:  %{python_module diskcache >= 3.0}
+BuildRequires:  %{python_module matplotlib >= 2}
+BuildRequires:  %{python_module networkx >= 2.3}
+BuildRequires:  %{python_module psutil >= 4.3.1}
+BuildRequires:  %{python_module pytest-rerunfailures}
+BuildRequires:  %{python_module pytest-xdist}
+BuildRequires:  %{python_module pytest}
+%endif
+%python_subpackages
+
+%description
+quimb is an easy but fast python library for quantum information and
+many-body calculations, including with tensor networks.
+
+%prep
+%setup -q -n quimb-%{version}
+
+sed -i '/addopts/d' pyproject.toml
+
+%build
+%if !%{with test}
+export SETUPTOOLS_SCM_PRETEND_VERSION=%{version}
+%pyproject_wheel
+%endif
+
+%install
+%if !%{with test}
+%pyproject_install
+%python_expand %fdupes %{buildroot}%{$python_sitelib}
+%endif
+
+%if %{with test}
+%check
+mv quimb quimb.movedsrc
+# precision comparison slightly out of tolerance: this one is permament, others are flaky (rerun them)
+donttest="(test_subtract_update and float32) or test_contract_double_loopy_approx"
+donttest+=" or test_cyclic_solve_big_with_segmenting"
+%pytest -n auto --reruns 3 -k "not ($donttest)"
+%endif
+
+%if !%{with test}
+%files %{python_files}
+%doc README.md
+%license LICENSE.txt
+%{python_sitelib}/quimb
+%{python_sitelib}/quimb-%{version}.dist-info
+%endif
+
+%changelog

quimb-1.10.0.tar.gz

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+oid sha256:34d640ddefb0f69e053a4e86086b3a07ec078d8e304f72293598aa56eb9ec00a
+size 11575545

quimb-1.7.3.tar.gz

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+version https://git-lfs.github.com/spec/v1
+oid sha256:9f021b549a82b225f1beadcdd26e89ce8c9c9c6af21d0a6f45e0b3bb778b3d3a
+size 12202705

quimb-1.8.4.tar.gz

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+version https://git-lfs.github.com/spec/v1
+oid sha256:b12e3c4741f21435a2c530f8ee963d2d6d935eb6138cf26a2c0db7867e3b3bde
+size 11566853