libtorch.py integration

.gitignore

@@ -0,0 +1,29 @@
+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+*$py.class
+
+# Virtual environments
+.venv/
+venv/
+env/
+
+# Distribution / packaging
+build/
+dist/
+*.egg-info/
+*.egg
+
+# Jupyter Notebook checkpoints
+.ipynb_checkpoints/
+
+# OS files
+Thumbs.db
+.DS_Store
+
+# IDE
+.vscode/
+.idea/
+
+# Logs
+*.log

requirements.txt

@@ -1,7 +1,18 @@
-ipython>=8.5.0
-jupytext>=1.16.2
-matplotlib>=3.6.1
-mpmath>=1.2.1
-numpy>=1.23.3
-scipy>=1.9.0
-sympy>=1.11.1
+ipython>=8.18.1
+jupytext>=1.16.4
+matplotlib>=3.8.2
+matplotlib-inline>=0.1.6
+mpmath>=1.3.0
+numpy>=1.26.4
+scipy>=1.11.4
+sympy>=1.12.1
+
+# Used by sympy.parsing.latex.parse_latex (see libphysics/src/libsympy.py)
+antlr4-python3-runtime==4.11
+
+# Logging
+loguru>=0.7.0
+
+# Torch utilities (see libphysics/src/libsympy.py, libphysics/src/libtorch.py)
+torch>=2.0.0
+torchquad>=0.5.0

src/libsympy.py

@@ -47,8 +47,8 @@
 from sympy.parsing.latex import parse_latex
 from sympy.parsing.sympy_parser import parse_expr
 from sympy.interactive import printing
-printing.init_printing()
 
+printing.init_printing()
 
 # Sets global defaults for all plots
 plt.rcParams.update({
@@ -297,7 +297,7 @@ def get_iterated_functions(f, fixed_vals={C1:0, C2:0}, prm=alpha,
     funcs = list(map(ifunc, param_vals))
     return(funcs)
 
-def get_piecewise():
+def get_piecewise(fV, xs):
     """
     todo 
     Returns a piecewise function of the function.
@@ -318,7 +318,6 @@ def getfV(self, fV, xs):
         return(res)
     """
     xintervals = []
-    [fV, xs] = [self.V, self.xs]
     for i in range(len(xs)):
         if i == 0:
             xintervals.append((fV[i], x < xs[i]))
@@ -406,13 +405,12 @@ def tensor_to_product(expr):
     expr = TensorProduct(a, b) + TensorProduct(a, b, c)
     converted = tensor_to_product(expr)
     """
+    from sympy.physics.quantum import TensorProduct as _TensorProduct
     return expr.replace(
-        lambda x: isinstance(x, TensorProduct),
+        lambda x: isinstance(x, _TensorProduct),
         lambda x: Mul(*x.args)
     )
-
-
-#----Plotting
+    #----Plotting
 def plot_energy_levels(data, constYs=None, title="", line_width=0.025):
     """
     Plots horizontal lines at y-points grouped by x-coordinates.