Add DEVELOPMENT.md with JAX info

Author: Sampreet

oqupy/backends/pt_tempo_backend.py

@@ -288,7 +288,7 @@ def compute_step(self) -> None:
         return self._step < self._num_steps
 
     def get_mpo_tensor(self, step: int) -> ndarray:
-        """ToDo. """
+        """TODO. """
         n = len(self._mps.nodes)
         assert n == self._num_steps
         assert step < n

oqupy/backends/tempo_backend.py

@@ -29,7 +29,7 @@
 
 os.environ['NUMPY_EXPERIMENTAL_ARRAY_FUNCTION'] = '0'
 
-class TIBaseBackend: # ToDo: translate this numpy code into tensornetwork
+class TIBaseBackend: # TODO: translate this numpy code into tensornetwork
     """
     Backend class for TEMPO.
 
@@ -195,7 +195,7 @@ def _truncate_left(self, k) -> int:
 
 
     def initialise(self, step=None, mps=None) -> Tuple[int, ndarray]:
-        """ ToDo """
+        """ TODO """
         if mps is not None:
             self._mps = mps
             self._step = step
@@ -216,7 +216,7 @@ def initialise(self, step=None, mps=None) -> Tuple[int, ndarray]:
             self._step = 1
         return self._step, self.data[-1]
 
-    def compute_step(self) -> Tuple[int, ndarray]: # ToDo: make readout optional
+    def compute_step(self) -> Tuple[int, ndarray]: # TODO: make readout optional
         """
         Takes a step in the TEMPO tensor network computation.
 
@@ -264,7 +264,7 @@ def compute_step(self) -> Tuple[int, ndarray]: # ToDo: make readout optional
         # turn east leg at last site into north leg at new last site
         self._mps.append(self._cap)
 
-        if len(self._mps) > self._kmax + 1:  # ToDo: check this
+        if len(self._mps) > self._kmax + 1:  # TODO: check this
             # remove first site, turn into matrix
             end = self._mps.pop(0).sum(1)
             # np.dot into new first site
@@ -378,7 +378,7 @@ def step(self) -> int:
         return self._step
 
     def initialize_mps_mpo(self):
-        """ToDo"""
+        """TODO"""
         self._initial_state = copy(self._initial_state).reshape(-1)
 
         self._super_u = op.left_right_super(
@@ -588,7 +588,7 @@ def compute_system_step(self, current_step, prop_1, prop_2) -> ndarray:
 
 class TempoBackend(BaseTempoBackend):
     """
-    ToDo
+    TODO
     """
 
     def __init__(
@@ -620,7 +620,7 @@ def __init__(
 
     def initialize(self) -> Tuple[int, ndarray]:
         """
-        ToDo
+        TODO
         """
         self._step = 0
         self.initialize_mps_mpo()
@@ -629,7 +629,7 @@ def initialize(self) -> Tuple[int, ndarray]:
 
     def compute_step(self) -> Tuple[int, ndarray]:
         """
-        ToDo
+        TODO
         """
         self._step += 1
         prop_1, prop_2 = self._propagators(self._step - 1)

oqupy/control.py

@@ -112,7 +112,7 @@ def add_continuous(
             control_fct: Callable[[ndarray, float], ndarray],
             post: Optional[bool] = False) -> None:
         """
-        ToDo
+        TODO
         """
         raise NotImplementedError()
 

oqupy/pt_tempo.py

@@ -150,7 +150,7 @@ def __init__(
         self._init_pt_tempo_backend()
 
     def _init_simple_process_tensor(self):
-        """ToDo. """
+        """TODO. """
         unitary = self._bath.unitary_transform
         if not np.allclose(unitary, np.identity(self._dimension)):
             transform_in = left_right_super(unitary.conjugate().T,
@@ -169,7 +169,7 @@ def _init_simple_process_tensor(self):
             description=self.description)
 
     def _init_file_process_tensor(self, filename, overwrite):
-        """ToDo. """
+        """TODO. """
         unitary = self._bath.unitary_transform
         if not np.allclose(unitary, np.identity(self._dimension)):
             transform_in = left_right_super(unitary.conjugate().T,

oqupy/system.py

@@ -555,7 +555,7 @@ def get_propagators(
             dt: float,
             parameters: ndarray) -> Callable[[int], Tuple[ndarray,ndarray]]:
         """
-        ToDo
+        TODO
         """
         def propagators(step: int):
             """Create the system propagators (first and second half) for
@@ -597,7 +597,7 @@ def get_propagator_derivatives(
             dt: float,
             parameters: ndarray) -> Callable[[int],Tuple[ndarray,ndarray]]:
         """
-        ToDo
+        TODO
         """
         if self._propagator_derivatives is not None:
             def propagator_derivatives_a(step: int):

oqupy/system_dynamics.py

@@ -559,7 +559,7 @@ def _compute_dynamics_input_parse(
 
 
 def _get_caps(process_tensors: List[BaseProcessTensor], step: int):
-    """ToDo """
+    """TODO """
     caps = []
     for i in range(len(process_tensors)):
         try:
@@ -576,7 +576,7 @@ def _get_caps(process_tensors: List[BaseProcessTensor], step: int):
 
 
 def _get_pt_mpos(process_tensors: List[BaseProcessTensor], step: int):
-    """ToDo """
+    """TODO """
     pt_mpos = []
     for i in range(len(process_tensors)):
         pt_mpo = process_tensors[i].get_mpo_tensor(step)
@@ -628,7 +628,7 @@ def _get_pt_mpos_backprop(mpo_list:ndarray, step: int):
 
 
 def _apply_system_superoperator(current_node, current_edges, sup_op):
-    """ToDo """
+    """TODO """
     if sup_op is None:
         return current_node, current_edges
     sup_op_node = tn.Node(sup_op.T)
@@ -640,7 +640,7 @@ def _apply_system_superoperator(current_node, current_edges, sup_op):
 
 
 def _apply_caps(current_node, current_edges, caps):
-    """ToDo """
+    """TODO """
     node_dict, edge_dict = tn.copy([current_node])
     for current_edge, cap in zip(current_edges[:-1], caps):
         cap_node = tn.Node(np.array(cap))

oqupy/tempo.py

@@ -579,7 +579,7 @@ def coeffs(k):
 
 
         unitary_transform = self._bath.unitary_transform
-        # ToDo: Unitary transform is not used. Check that GibbsTempo also works
+        # TODO: Unitary transform is not used. Check that GibbsTempo also works
         #       with non-diagonal coupling operators!!!
         if not np.allclose(unitary_transform,np.identity(self.dimension)):
             raise NotImplementedError(

oqupy/util.py

@@ -72,19 +72,6 @@ def get_indices(
     # return the index matrix with shape (n_in, n_iters)
     return ((iteration_matrix / divisors).astype(int) % shape).T
 
-def increase_list_of_index(
-        a: List,
-        shape: List,
-        index: Optional[int] = -1) -> bool:
-    """Circle through a list of indices. """
-    a[index] += 1
-    if a[index] >= shape[index]:
-        if index == -len(shape):
-            return False
-        a[index] = 0
-        return increase_list_of_index(a, shape, index-1)
-    return True
-
 def add_singleton(
         tensor: ndarray,
         index: Optional[int] = -1) -> ndarray: