Refactor models module

.github/workflows/push_event_workflow.yml

@@ -13,6 +13,6 @@ jobs:
     - name : Install Packages 
       run : pip install -r requirements.txt
 
-    - name : Run tests hamiltonians
-      run : pytest tests/test.py
+    - name : Run tests hamiltonians models
+      run : pytest tests/model_test.py
 

quantumsim/__init__.py

@@ -1,8 +1,8 @@
 from quantumsim.ansatz import *
-from quantumsim.variational import *
+from quantumsim.models import *
 from quantumsim.optimizers import *
 from quantumsim.lattice import *
 from quantumsim.beginstate import *
 
 
-package_version = '1.0.0'
+package_version = '1.0.0'

quantumsim/variational/vqe/base.py → quantumsim/models/base.py

@@ -1,22 +1,15 @@
 import numpy as np
 
 """
-Clase base del VQE.
+Clase base de los modelos
 """
-class vqe_base():
+class model_base():
     """
     Variables de la clase
     """
     hamiltonian= None
     qubits = 0
 
-    #def cost_function(self, params, ansatz, estimator) -> float:
-    #    if self.hamiltonian is None:
-    #        return 0.0
-    #    result = estimator.run(pubs=[ (ansatz, [self.hamiltonian], [params]) ]).result()
-    #    energy = result[0].data.evs[0]        
-    #    return energy
-
     def energies_and_states(self):
         if self.hamiltonian is None:
             return [], []
@@ -27,4 +20,6 @@ def get_matrix(self):
         if self.hamiltonian is None:
             return None
         return self.hamiltonian.to_matrix()
-
+
+    def get_hamiltonian(self):
+        return self.hamiltonian

quantumsim/variational/vqe/fermihubbard.py → quantumsim/models/fermihubbard.py

@@ -1,4 +1,4 @@
-from .base import vqe_base
+from .base import model_base
 from qiskit_nature.second_q.mappers import JordanWignerMapper
 import numpy as np
 from qiskit_nature.second_q.operators import FermionicOp
@@ -8,7 +8,7 @@
 Clase para construir el hamiltoniano usado en el proceso de VQE, hereda metodos de la clase
 vqe_base
 """
-class fermihubbard_model(vqe_base):
+class fermihubbard_model(model_base):
 
     """
     Constructor de la clase

quantumsim/models/molecular.py

@@ -0,0 +1,60 @@
+from .base import model_base
+from qiskit_nature.units import DistanceUnit
+from qiskit_nature.second_q.drivers import PySCFDriver
+from qiskit_nature.second_q.mappers import JordanWignerMapper
+import numpy as np
+
+
+class molecule_model(model_base):
+    mapper = JordanWignerMapper()
+    params = {}
+
+    """
+    Constructor de la clase
+        params: diccionario con los parametros del hamiltoniano
+    """
+    def __init__(self, params):
+
+        self.params = params
+
+        if "coordinates" not in params:
+            return
+
+        coor = params['coordinates']
+        atom_string = ""
+        for i,s in enumerate(params['symbols']):
+            atom_string += f"{s} {coor[3*i]} {coor[3*i + 1]} {coor[3*i +2]};"
+
+        driver = PySCFDriver(
+            atom=atom_string,
+            unit=DistanceUnit.ANGSTROM,
+            basis=params['basis'],
+            charge=params['charge'],
+            spin=params['spin']
+        )
+
+        problem = driver.run()
+        second_q_op, _ = problem.second_q_ops()
+        self.hamiltonian = self.mapper.map(second_q_op)
+        return 
+
+
+    def set_hamiltonian(self, dist):
+        atom_string = ""
+        for i,s in enumerate( self.params['symbols'] ):
+            atom_string += f"{s} {dist[3*i]} {dist[3*i + 1]} {dist[3*i +2]};"
+
+        driver = PySCFDriver(
+            atom=atom_string,
+            unit=DistanceUnit.ANGSTROM,
+            basis=self.params['basis'],
+            charge=self.params['charge'],
+            spin=self.params['spin']
+        )
+
+        problem = driver.run()
+        second_q_op, _ = problem.second_q_ops()
+        self.hamiltonian = self.mapper.map( second_q_op ) 
+        return self.hamiltonian
+
+

quantumsim/variational/vqe/spin.py → quantumsim/models/spin.py

@@ -1,11 +1,11 @@
-from .base import vqe_base
+from .base import model_base
 from qiskit.quantum_info import SparsePauliOp
 
 """
 Clase para construir el hamiltoniano usado en el proceso de VQE, hereda metodos de la clase
 vqe_base
 """
-class spin_model(vqe_base):
+class spin_model(model_base):
 
     """
     Constructor de la clase