Meson build to be compatible with newer python version

.github/workflows/python-app.yml

@@ -1,59 +1,82 @@
-# This workflow will install Python dependencies, run tests and lint with a single version of Python
+# This workflow will install Python dependencies, run tests and lint with a variety of Python versions
 # For more information see: https://help.github.com/actions/language-and-framework-guides/using-python-with-github-actions
 
-name: Python application
+name: Python package
 
 on:
   push:
-    branches: [ Fast_LANCZOS ]
+    branches: [ master ]
   pull_request:
-    branches: [ Fast_LANCZOS ]
+    branches: [ master ]
 
 jobs:
   build:
 
     runs-on: ubuntu-latest
 
+    strategy:
+      matrix:
+        python-version: [3.8]
+
+    services:
+      rabbitmq:
+          image: rabbitmq:latest
+          ports:
+          -   5672:5672
+
     steps:
     - uses: actions/checkout@v2
-    - name: Set up Python 3.9
+
+    - name: Set up Python ${{ matrix.python-version }}
       uses: actions/setup-python@v2
       with:
-        python-version: 3.9
+        python-version: ${{ matrix.python-version }}
+
     - name: Install dependencies
       run: |
         python -m pip install --upgrade pip
-        pip install flake8 pytest
-        pip install ase spglib==2.2 julia
-        python -c 'import julia; julia.install()'
+        pip install flake8 pytest~=6.0 pgtest~=1.3 aiida-core~=2.3 aiida-quantumespresso~=4.3
+        if [ ${{matrix.python-version}} -eq 2.7 ]; then pip install -r requirements2.txt;
+        else pip install -r requirements.txt; fi
+        aiida-pseudo install
+
     - name: Lint with flake8
       run: |
         # stop the build if there are Python syntax errors or undefined names
         flake8 . --count --select=E9,F63,F7,F82 --show-source --statistics
         # exit-zero treats all errors as warnings. The GitHub editor is 127 chars wide
         flake8 . --count --exit-zero --max-complexity=10 --max-line-length=127 --statistics
-    - name: Prepare the installation
+
+    - name: Install
       run: |
         sudo apt-get update
-        # Install the fortran compiler with lapack and blas
-        sudo apt-get install gfortran libblas-dev liblapack-dev build-essential \
-                             mpich libopenmpi-dev libgl1-mesa-glx  libglib2.0-0 \
-                             libboost-all-dev
+        sudo apt-get install git gfortran libblas-dev liblapack-dev mpich
 
-        pip install mpi4py
-
-
         git clone https://github.com/SSCHAcode/CellConstructor.git
-        cd CellConstructor && python setup.py install --user && cd ..
-        rm -r CellConstructor
-
         git clone https://github.com/SSCHAcode/python-sscha.git
-        cd python-sscha && python setup.py install --user && cd ..
-        rm -r python-sscha
-
-        MPICC=mpicc python setup.py install --user
-
-        cd CModules; make; cd ..
+
+        pip install meson meson-python ninja
+        pip install mpi4py
+
+        cd CellConstructor
+        pip install --no-build-isolation .
+        cd ..
+
+        # Install the python-sscha
+        cd python-sscha
+        pip install --no-build-isolation .
+        cd ..
+
+        # Install the tdscha package
+        pip install --no-build-isolation .
+
+        # Install julia requirements
+        python -c 'import julia; julia.install()'
     - name: Test with pytest
+      env:
+        OMP_NUM_THREADS: 1
       run: |
-        pytest
+        cd tests
+        rm -rf __pycache__
+        # Test excluding very long running tests
+        pytest -v -m "not release"

CModules/odd_corr_module.c

@@ -150,16 +150,16 @@ static PyObject *ApplyV3ToDyn(PyObject * self, PyObject * args) {
   }
 
   // Retrive the pointer to the data from the python object
-  X = (double*) PyArray_DATA(npy_X);
-  Y = (double*) PyArray_DATA(npy_Y);
-  rho = (double*) PyArray_DATA(npy_rho);
-  w = (double*) PyArray_DATA(npy_omega);
-  input = (double*) PyArray_DATA(npy_input);
-  output = (double*) PyArray_DATA(npy_output);
+  X = (double*) PyArray_DATA((PyArrayObject*)npy_X);
+  Y = (double*) PyArray_DATA((PyArrayObject*)npy_Y);
+  rho = (double*) PyArray_DATA((PyArrayObject*)npy_rho);
+  w = (double*) PyArray_DATA((PyArrayObject*)npy_omega);
+  input = (double*) PyArray_DATA((PyArrayObject*)npy_input);
+  output = (double*) PyArray_DATA((PyArrayObject*)npy_output);
 
   // Read the symmetries
-  symmetries = (double*)PyArray_DATA(npy_symmetries);
-  n_deg = (int*)PyArray_DATA(npy_n_deg);
+  symmetries = (double*)PyArray_DATA((PyArrayObject*)npy_symmetries);
+  n_deg = (int*)PyArray_DATA((PyArrayObject*)npy_n_deg);
 
   // Build the degeneracy space
   good_deg_space = (int **) malloc(sizeof(int*) * N_modes);
@@ -169,7 +169,7 @@ static PyObject *ApplyV3ToDyn(PyObject * self, PyObject * args) {
   for (i = 0; i < N_modes;++i) {
     good_deg_space[i] = (int*) malloc(sizeof(int) * n_deg[i]);
     for (j = 0; j < n_deg[i]; ++j) {
-      good_deg_space[i][j] = ((int*) PyArray_DATA(npy_deg_space))[counter++];
+      good_deg_space[i][j] = ((int*) PyArray_DATA((PyArrayObject*)npy_deg_space))[counter++];
     }
   }
 
@@ -252,16 +252,16 @@ static PyObject *ApplyV3_FT(PyObject * self, PyObject * args) {
   }
 
   // Retrive the pointer to the data from the python object
-  X = (double*) PyArray_DATA(npy_X);
-  Y = (double*) PyArray_DATA(npy_Y);
-  rho = (double*) PyArray_DATA(npy_rho);
-  w = (double*) PyArray_DATA(npy_omega);
-  input = (double*) PyArray_DATA(npy_input);
-  output = (double*) PyArray_DATA(npy_output);
+  X = (double*) PyArray_DATA((PyArrayObject*)npy_X);
+  Y = (double*) PyArray_DATA((PyArrayObject*)npy_Y);
+  rho = (double*) PyArray_DATA((PyArrayObject*)npy_rho);
+  w = (double*) PyArray_DATA((PyArrayObject*)npy_omega);
+  input = (double*) PyArray_DATA((PyArrayObject*)npy_input);
+  output = (double*) PyArray_DATA((PyArrayObject*)npy_output);
 
   // Read the symmetries
-  symmetries = (double*)PyArray_DATA(npy_symmetries);
-  n_deg = (int*)PyArray_DATA(npy_n_deg);
+  symmetries = (double*)PyArray_DATA((PyArrayObject*)npy_symmetries);
+  n_deg = (int*)PyArray_DATA((PyArrayObject*)npy_n_deg);
 
   // Build the degeneracy space
   good_deg_space = (int **) malloc(sizeof(int*) * N_modes);
@@ -275,7 +275,7 @@ static PyObject *ApplyV3_FT(PyObject * self, PyObject * args) {
     good_deg_space[i] = (int*) malloc(sizeof(int) * n_deg[i]);
       if (DEB) printf("Mode %d -> ", i);
     for (j = 0; j < n_deg[i]; ++j) {
-      good_deg_space[i][j] = ((int*) PyArray_DATA(npy_deg_space))[counter++];
+      good_deg_space[i][j] = ((int*) PyArray_DATA((PyArrayObject*)npy_deg_space))[counter++];
       if (DEB) printf(" %d ", good_deg_space[i][j]);
     }
     if (DEB) printf("\n");
@@ -339,12 +339,12 @@ static PyObject *GetWeights(PyObject * self, PyObject * args) {
   }
 
   // Retrive the pointer to the data from the python object
-  X = (double*) PyArray_DATA(npy_X);
-  R1 = (double*) PyArray_DATA(npy_R1);
-  Y1 = (double*) PyArray_DATA(npy_Y1);
-  w = (double*) PyArray_DATA(npy_omega);
+  X = (double*) PyArray_DATA((PyArrayObject*)npy_X);
+  R1 = (double*) PyArray_DATA((PyArrayObject*)npy_R1);
+  Y1 = (double*) PyArray_DATA((PyArrayObject*)npy_Y1);
+  w = (double*) PyArray_DATA((PyArrayObject*)npy_omega);
 
-  weights = (double*) PyArray_DATA(npy_weights);
+  weights = (double*) PyArray_DATA((PyArrayObject*)npy_weights);
 
   get_weights(X, w, R1, Y1, T, N_modes, N_configs, weights);
 
@@ -389,12 +389,12 @@ static PyObject *Get_D2DR2_PertV(PyObject * self, PyObject * args) {
   }
 
   // Retrive the pointer to the data from the python object
-  X = (double*) PyArray_DATA(npy_X);
-  Y = (double*) PyArray_DATA(npy_Y);
-  rho = (double*) PyArray_DATA(npy_rho);
-  w = (double*) PyArray_DATA(npy_omega);
-  weights = (double*) PyArray_DATA(npy_weights);
-  d2vdr2 = (double*) PyArray_DATA(npy_d2vdr2);
+  X = (double*) PyArray_DATA((PyArrayObject*)npy_X);
+  Y = (double*) PyArray_DATA((PyArrayObject*)npy_Y);
+  rho = (double*) PyArray_DATA((PyArrayObject*)npy_rho);
+  w = (double*) PyArray_DATA((PyArrayObject*)npy_omega);
+  weights = (double*) PyArray_DATA((PyArrayObject*)npy_weights);
+  d2vdr2 = (double*) PyArray_DATA((PyArrayObject*)npy_d2vdr2);
 
   // Apply the method
   get_d2v_dR2_pert(X, Y, w, weights, rho, T, N_modes, N_configs, d2vdr2);
@@ -578,8 +578,8 @@ static PyObject * Get_Perturb_AveragesSym(PyObject * self, PyObject * args) {
   //printf("I'm here, %s:%d\n", __FILE__, __LINE__);
 
   for (i = 0; i < n_blocks; ++i) {
-    good_deg_space[i] = (int*)  PyArray_DATA( PyList_GetItem(sym_basis_list, i)); //malloc(sizeof(int) * n_deg[i]);
-    good_syms[i] = (double*) PyArray_DATA( PyList_GetItem(sym_list, i)) ;  // malloc(sizeof(double) * n_deg[i] * n_deg[i] * N_syms);
+    good_deg_space[i] = (int*)  PyArray_DATA((PyArrayObject*) PyList_GetItem(sym_basis_list, i)); //malloc(sizeof(int) * n_deg[i]);
+    good_syms[i] = (double*) PyArray_DATA( (PyArrayObject*)PyList_GetItem(sym_list, i)) ;  // malloc(sizeof(double) * n_deg[i] * n_deg[i] * N_syms);
 
     /*
     printf("Block:\n");
@@ -1081,9 +1081,9 @@ static PyObject * GetV3(PyObject * self, PyObject * args) {
   // Convert the array
   //numpy_array = PyArray_FROM_OTF(bare_array, NPY_DOUBLE, NPY_ARRAY_IN_ARRAY);
 
-  X = (double*) PyArray_DATA(npy_X);
-  Y = (double*) PyArray_DATA(npy_Y);
-  v3 = (double*) PyArray_DATA(npy_v3);
+  X = (double*) PyArray_DATA((PyArrayObject*)npy_X);
+  Y = (double*) PyArray_DATA((PyArrayObject*)npy_Y);
+  v3 = (double*) PyArray_DATA((PyArrayObject*)npy_v3);
 
 
   int i;
@@ -1169,11 +1169,11 @@ static PyObject * ApplyV4(PyObject * self, PyObject * args) {
   // Convert the array
   //numpy_array = PyArray_FROM_OTF(bare_array, NPY_DOUBLE, NPY_ARRAY_IN_ARRAY);
 
-  X = (double*) PyArray_DATA(npy_X);
-  Y = (double*) PyArray_DATA(npy_Y);
-  Lambda = (double*) PyArray_DATA(npy_Lambda);
-  v_in = (double*) PyArray_DATA(npy_vin);
-  v_out = (double*) PyArray_DATA(npy_vout);
+  X = (double*) PyArray_DATA((PyArrayObject*)npy_X);
+  Y = (double*) PyArray_DATA((PyArrayObject*)npy_Y);
+  Lambda = (double*) PyArray_DATA((PyArrayObject*)npy_Lambda);
+  v_in = (double*) PyArray_DATA((PyArrayObject*)npy_vin);
+  v_out = (double*) PyArray_DATA((PyArrayObject*)npy_vout);
 
   int i;
   int a, b, c, d;
@@ -1273,11 +1273,11 @@ static PyObject * GetV4(PyObject * self, PyObject * args) {
   // Convert the array
   //numpy_array = PyArray_FROM_OTF(bare_array, NPY_DOUBLE, NPY_ARRAY_IN_ARRAY);
 
-  X = (double*) PyArray_DATA(npy_X);
-  Y = (double*) PyArray_DATA(npy_Y);
-  rows = (int*) PyArray_DATA(npy_rows);
-  cols = (int*) PyArray_DATA(npy_cols);
-  v4_out = (double*) PyArray_DATA(npy_v4out);
+  X = (double*) PyArray_DATA( (PyArrayObject*)npy_X);
+  Y = (double*) PyArray_DATA( (PyArrayObject*)npy_Y);
+  rows = (int*) PyArray_DATA( (PyArrayObject*)npy_rows);
+  cols = (int*) PyArray_DATA( (PyArrayObject*)npy_cols);
+  v4_out = (double*) PyArray_DATA((PyArrayObject*)npy_v4out);
 
   int i;
   int a, b, c, d;

Modules/DynamicalLanczos.py

@@ -728,7 +728,7 @@ def prepare_symmetrization(self, no_sym = False, verbose = True, symmetries = No
 
         t1 = time.time()
         if symmetries is None:
-            super_symmetries = CC.symmetries.GetSymmetriesFromSPGLIB(spglib.get_symmetry(super_structure.get_ase_atoms()), False)
+            super_symmetries = CC.symmetries.GetSymmetriesFromSPGLIB(spglib.get_symmetry(super_structure.get_spglib_cell()), False)
 
         else:
             super_symmetries = symmetries

README.md

@@ -0,0 +1,65 @@
+
+# Introduction
+
+## What is TD-SCHA?
+
+TD-SCHA is a theory to simulate quantum nuclear motion in materials with strong anharmonicity.  
+TD-SCHA stands for Time-Dependent Self-Consistent Harmonic Approximation, and it is the dynamical extension of the SCHA theory, that can describe equilibrium properties of materials accounting for both quantum and dynamical nuclear fluctuations.  
+
+The `tdscha` Python library allows performing dynamical linear response calculations on top of the equilibrium results (computed with the `python-sscha` package).
+
+## Why would I need tdscha?
+
+### A Tool for Advanced Material Simulations
+
+**Enhanced Simulation Capabilities**  
+TD-SCHA is an essential tool for researchers and professionals in material science, particularly for simulating transport or thermal properties of materials, phase diagrams, and phonon-related properties.
+
+**Integration with python-sscha**  
+Seamless integration with `python-sscha` allows for the inclusion of both thermal and quantum phonon fluctuations in *ab initio* simulations.
+
+**Leveraging the SSCHA Method**
+
+**Quantum and Thermal Fluctuations**  
+The Stochastic Self-Consistent Harmonic Approximation (SSCHA) is a full-quantum method optimizing the nuclear wave-function or density matrix to minimize free energy, crucial for simulating highly anharmonic systems.
+
+**Efficiency and Cost-Effectiveness**  
+Despite its full quantum and thermal nature, the computational cost is comparable to classical molecular dynamics, enhanced by the algorithm's ability to exploit crystal symmetries.
+
+**User-Friendly and Versatile**
+
+**Python Library and Stand-alone Software**  
+Available both as a Python library and stand-alone software, with input scripts sharing syntax with Quantum ESPRESSO.
+
+**Broad Compatibility**  
+Can couple with any *ab initio* engine and interacts through the Atomic Simulation Environment (ASE) with an interface for automatic job submission on remote clusters.
+
+**Getting Started**
+
+**Easy to Use**  
+User-friendly with short, readable input files and comprehensive tutorials.  
+
+**Download and Explore**  
+Download and install `python-sscha`, and start exploring the tutorials to enhance your material simulation projects.
+
+# How to install
+
+You need to have installed `python-sscha` and `CellConstructor` to work with `tdscha`.  
+Please read the installation guide for those packages before proceeding further.  
+You may find all instructions on the [official website](http://www.sscha.eu).  
+
+To install from PyPI, simply type:
+
+```bash
+pip install tdscha
+```
+You can alternatively clone the repository from GitHub and install the package with:
+
+```
+pip install .
+```
+
+
+# Quick start
+Go to the [tutorials](https://sscha.eu/Tutorials/tutorial_05_ramanir/)
+