Docstrings added and updated

src/copapy/_basic_types.py

@@ -32,6 +32,14 @@ def transl_type(t: str) -> str:
 
 
 class Node:
+    """A Node represents an computational operation like ADD or other operations 
+    like read and write from or to the memory or IOs. In the computation graph
+    Nodes are connected via Nets.
+
+    Attributes:
+        args (list[Net]): The input Nets to this Node.
+        name (str): The name of the operation this Node represents.
+    """
     def __init__(self) -> None:
         self.args: list[Net] = []
         self.name: str = ''
@@ -40,11 +48,14 @@ class Node:
         return f"Node:{self.name}({', '.join(str(a) for a in self.args) if self.args else (self.value if isinstance(self, CPConstant) else '')})"
 
 
-class Device():
-    pass
-
-
 class Net:
+    """A Net represents a variable in the computation graph - or more generally it
+    connects Nodes together.
+
+    Attributes:
+        dtype (str): The data type of this Net.
+        source (Node): The Node that produces the value for this Net.
+    """
     def __init__(self, dtype: str, source: Node):
         self.dtype = dtype
         self.source = source
@@ -58,7 +69,19 @@ class Net:
 
 
 class variable(Generic[TNum], Net):
+    """A "variable" represents a typed variable. It supports arithmetic and
+    comparison operations.
+
+    Attributes:
+        dtype (str): Data type of this variable.
+    """
     def __init__(self, source: TNum | Node, dtype: str | None = None):
+        """Instance a variable.
+
+        Args:
+            source: A numeric value or Node object.
+            dtype: Data type of this variable. Required if source is a Node.
+        """
         if isinstance(source, Node):
             self.source = source
             assert dtype, 'For source type Node a dtype argument is required.'

src/copapy/_compiler.py

@@ -144,6 +144,8 @@ def add_write_ops(net_node_list: list[tuple[Net | None, Node]], const_nets: list
 
 
 def get_nets(*inputs: Iterable[Iterable[Any]]) -> list[Net]:
+    """Get all unique nets from the provided inputs
+    """
     nets: set[Net] = set()
 
     for input in inputs:
@@ -156,6 +158,16 @@ def get_nets(*inputs: Iterable[Iterable[Any]]) -> list[Net]:
 
 
 def get_data_layout(variable_list: Iterable[Net], sdb: stencil_database, offset: int = 0) -> tuple[list[tuple[Net, int, int]], int]:
+    """Get memory layout for the provided variables
+    
+    Arguments:
+        variable_list: Variables to layout
+        sdb: Stencil database for size lookup
+        offset: Starting offset for layout
+
+    Returns:
+        Tuple of list of (variable, start_offset, length) and total length"""
+
     object_list: list[tuple[Net, int, int]] = []
 
     for variable in variable_list:
@@ -171,17 +183,37 @@ def get_data_layout(variable_list: Iterable[Net], sdb: stencil_database, offset:
 
 
 def get_section_layout(section_indexes: Iterable[int], sdb: stencil_database, offset: int = 0) -> tuple[list[tuple[int, int, int]], int]:
+    """Get memory layout for the provided sections
+    
+    Arguments:
+        section_indexes: Sections (by index) to layout
+        sdb: Stencil database for size lookup
+        offset: Starting offset for layout
+
+    Returns:
+        Tuple of list of (section_id, start_offset, length) and total length
+    """
     section_list: list[tuple[int, int, int]] = []
 
-    for id in section_indexes:
-        lengths = sdb.get_section_size(id)
-        section_list.append((id, offset, lengths))
+    for index in section_indexes:
+        lengths = sdb.get_section_size(index)
+        section_list.append((index, offset, lengths))
         offset += (lengths + 3) // 4 * 4
 
     return section_list, offset
 
 
 def get_aux_function_mem_layout(function_names: Iterable[str], sdb: stencil_database, offset: int = 0) -> tuple[list[tuple[str, int, int]], int]:
+    """Get memory layout for the provided auxiliary functions
+
+    Arguments:
+        function_names: Function names to layout
+        sdb: Stencil database for size lookup
+        offset: Starting offset for layout
+    
+    Returns:
+        Tuple of list of (function_name, start_offset, length) and total length
+    """
     function_list: list[tuple[str, int, int]] = []
 
     for name in function_names:
@@ -193,6 +225,15 @@ def get_aux_function_mem_layout(function_names: Iterable[str], sdb: stencil_data
 
 
 def compile_to_dag(node_list: Iterable[Node], sdb: stencil_database) -> tuple[binw.data_writer, dict[Net, tuple[int, int, str]]]:
+    """Compiles a DAG identified by provided end nodes to binary code
+
+    Arguments:
+        node_list: List of end nodes of the DAG to compile
+        sdb: Stencil database
+
+    Returns:
+        Tuple of data writer with binary code and variable layout dictionary
+    """
     variables: dict[Net, tuple[int, int, str]] = {}
     data_list: list[bytes] = []
     patch_list: list[tuple[int, int, int, binw.Command]] = []

src/copapy/_math.py

@@ -10,7 +10,14 @@ def sqrt(x: float | int) -> float: ...
 @overload
 def sqrt(x: variable[Any]) -> variable[float]: ...
 def sqrt(x: NumLike) -> variable[float] | float:
-    """Square root function"""
+    """Square root function
+    
+    Arguments:
+        x: Input value
+        
+    Returns:
+        Square root of x
+    """
     if isinstance(x, variable):
         return add_op('sqrt', [x, x])  # TODO: fix 2. dummy argument
     return float(x ** 0.5)
@@ -33,7 +40,14 @@ def get_42() -> variable[float]:
 
 
 def abs(x: T) -> T:
-    """Absolute value function"""
+    """Absolute value function
+    
+    Arguments:
+        x: Input value
+        
+    Returns:
+        Absolute value of x
+    """
     ret = (x < 0) * -x + (x >= 0) * x
     return ret  # pyright: ignore[reportReturnType]
 

src/copapy/_stencils.py

@@ -170,6 +170,13 @@ class stencil_database():
         return strip_function(self.elf.symbols[name])
 
     def get_sub_functions(self, names: Iterable[str]) -> set[str]:
+        """Return recursively all functions called by stencils or by other functions
+        Args:
+            names: function or stencil names
+        
+        Returns:
+            set of all sub function names
+        """
         name_set: set[str] = set()
         for name in names:
             if name not in name_set:
@@ -182,16 +189,27 @@ class stencil_database():
         return name_set
 
     def get_symbol_size(self, name: str) -> int:
+        """Returns the size of a specified symbol name."""
         return self.elf.symbols[name].fields['st_size']
 
-    def get_section_size(self, id: int) -> int:
-        return self.elf.sections[id].fields['sh_size']
+    def get_section_size(self, index: int) -> int:
+        """Returns the size of a section specified by index."""
+        return self.elf.sections[index].fields['sh_size']
 
-    def get_section_data(self, id: int) -> bytes:
-        return self.elf.sections[id].data
+    def get_section_data(self, index: int) -> bytes:
+        """Returns the data of a section specified by index."""
+        return self.elf.sections[index].data
 
     def get_function_code(self, name: str, part: Literal['full', 'start', 'end'] = 'full') -> bytes:
-        """Returns machine code for a specified function name."""
+        """Returns machine code for a specified function name.
+        
+        Args:
+            name: function name
+            part: part of the function to return ('full', 'start', 'end')
+
+        Returns:
+            Machine code bytes of the specified part of the function
+        """
         func = self.elf.symbols[name]
         assert func.info == 'STT_FUNC', f"{name} is not a function"
 

src/copapy/_target.py

@@ -16,11 +16,24 @@ def add_read_command(dw: binw.data_writer, variables: dict[Net, tuple[int, int,
 
 
 class Target():
+    """Target device for compiling for and running on copapy code.
+    """
     def __init__(self, arch: str = 'native', optimization: str = 'O3') -> None:
+        """Initialize Target object
+        
+        Arguments:
+            arch: Target architecture
+            optimization: Optimization level
+        """
         self.sdb = stencil_db_from_package(arch, optimization)
         self._variables: dict[Net, tuple[int, int, str]] = {}
 
     def compile(self, *variables: int | float | variable[int] | variable[float] | variable[bool] | Iterable[int | float | variable[int] | variable[float] | variable[bool]]) -> None:
+        """Compiles the code to compute the given variables.
+        
+        Arguments:
+            variables: Variables to compute
+        """
         nodes: list[Node] = []
         for s in variables:
             if isinstance(s, Iterable):
@@ -35,7 +48,8 @@ class Target():
         assert coparun(dw.get_data()) > 0
 
     def run(self) -> None:
-        # set entry point and run code
+        """Runs the compiled code on the target device.
+        """
         dw = binw.data_writer(self.sdb.byteorder)
         dw.write_com(binw.Command.RUN_PROG)
         dw.write_com(binw.Command.END_COM)
@@ -58,8 +72,16 @@ class Target():
         ...
 
     def read_value(self, net: NumLike) -> float | int | bool:
+        """Reads the value of a variable.
+
+        Arguments:
+            net: Variable to read
+        
+        Returns:
+            Value of the variable
+        """
         assert isinstance(net, Net), "Variable must be a copapy variable object"
-        assert net in self._variables, f"Variable {net} not found"
+        assert net in self._variables, f"Variable {net} not found. It might not have been compiled for the target."
         addr, lengths, var_type = self._variables[net]
         print('...', self._variables[net], net.dtype)
         assert lengths > 0
@@ -87,6 +109,7 @@ class Target():
             raise ValueError(f"Unsupported variable type: {var_type}")
 
     def read_value_remote(self, net: Net) -> None:
+        """Reads the raw data of a variable by the runner."""
         dw = binw.data_writer(self.sdb.byteorder)
         add_read_command(dw, self._variables, net)
         assert coparun(dw.get_data()) > 0

src/copapy/_vectors.py

@@ -11,11 +11,16 @@ epsilon = 1e-20
 
 
 class vector(Generic[T]):
-    """Type-safe vector supporting numeric promotion between vector types."""
+    """Mathematical vector class supporting basic operations and interactions with variables.
+    """
     def __init__(self, values: Iterable[T | variable[T]]):
+        """Create a vector with given values and variables.
+
+        Args:
+            values: iterable of constant values and variables
+        """
         self.values: tuple[variable[T] | T, ...] = tuple(values)
 
-    # ---------- Basic dunder methods ----------
     def __repr__(self) -> str:
         return f"vector({self.values})"
 
@@ -143,14 +148,17 @@ class vector(Generic[T]):
     @overload
     def sum(self: 'vector[float]') -> float | variable[float]: ...
     def sum(self) -> Any:
+        """Sum of all vector elements."""
         return sum(a for a in self.values if isinstance(a, variable)) +\
                sum(a for a in self.values if not isinstance(a, variable))
 
     def magnitude(self) -> 'float | variable[float]':
+        """Magnitude (length) of the vector."""
         s = sum(a * a for a in self.values)
         return sqrt(s) if isinstance(s, variable) else sqrt(s)
 
     def normalize(self) -> 'vector[float]':
+        """Returns a normalized (unit length) version of the vector."""
         mag = self.magnitude() + epsilon
         return self / mag