@@ -1936,6 +1936,39 @@ (define-public python-hyperopt
discrete, and conditional dimensions.")
(license license:bsd-3)))
+(define-public python-deepxde
+ (package
+ (name "python-deepxde")
+ (version "1.9.1")
+ (source (origin
+ (method url-fetch)
+ (uri (pypi-uri "DeepXDE" version))
+ (sha256
+ (base32
+ "0gibr0nz8xfhxwi2rgfypm653fy912n49161vqaqgpxlm2pb3bhb"))))
+ (build-system pyproject-build-system)
+ (arguments
+ (list #:tests? #f ; there are no tests
+ #:phases #~(modify-phases %standard-phases
+ (add-before 'sanity-check 'writable-home
+ ;; sanity-check writes ~/.deepxde/config.json to set
+ ;; the default backend.
+ (lambda _
+ (setenv "HOME" "/tmp"))))))
+ ;; DeepXDE supported backends are TensorFlow (v1 and v2), PyTorch, JAX and
+ ;; PaddlePaddle. We test with PyTorch because we have it up to date.
+ (native-inputs (list python-pytorch python-setuptools-scm))
+ (propagated-inputs (list python-matplotlib python-numpy
+ python-scikit-learn python-scikit-optimize
+ python-scipy))
+ (home-page "https://deepxde.readthedocs.io/en/latest/")
+ (synopsis "Library for scientific machine learning")
+ (description "DeepXDE is a library for scientific machine learning and
+physics-informed learning. It includes implementations for the PINN
+(physics-informed neural networks), DeepONet (deep operator network) and
+MFNN (multifidelity neural network) algorithms.")
+ (license license:lgpl2.1)))
+
;; There have been no proper releases yet.
(define-public kaldi
(let ((commit "be22248e3a166d9ec52c78dac945f471e7c3a8aa")