Merge branch 'develop'

Author: pkalivas

crates/radiate-python/src/bindings/metric.rs

@@ -24,6 +24,16 @@ impl PyMetricSet {
         )
     }
 
+    pub fn __dict__<'py>(&self, py: Python<'py>) -> PyResult<Bound<'py, PyDict>> {
+        let dict = PyDict::new(py);
+        let rows = self.to_rows(py, true)?;
+        for row in rows {
+            dict.set_item(row.get_item("name")?, row)?;
+        }
+
+        Ok(dict)
+    }
+
     pub fn __getitem__<'py>(
         &self,
         py: Python<'py>,

crates/radiate-python/src/bindings/mod.rs

@@ -24,7 +24,7 @@ pub use functions::*;
 pub use genome::*;
 pub use gp::{PyGraph, PyTree};
 pub use inputs::{PyEngineInput, PyEngineInputType};
-pub use metric::PyMetricSet;
+pub use metric::{PyMetric, PyMetricSet};
 pub use subscriber::{PyEngineEvent, PySubscriber};
 
 use crate::{AnyChromosome, PyAnyObject};

py-radiate/radiate/__init__.py

@@ -31,6 +31,7 @@
 )
 from .handlers import EventHandler, EventType, EngineEvent
 from .gp import Op, Graph, Tree
+from .metrics import MetricSet, Metric
 
 from .inputs.executor import Executor
 from .fitness import Regression, NoveltySearch, BatchFitness
@@ -81,7 +82,12 @@
 
 from .inputs.limit import SecondsLimit, GenerationsLimit, ScoreLimit, ConvergenceLimit
 
-from .dependancies import _NUMPY_AVAILABLE, _GIL_ENABLED
+from .dependancies import (
+    _NUMPY_AVAILABLE,
+    _GIL_ENABLED,
+    _PANDAS_AVAILABLE,
+    _POLARS_AVAILABLE,
+)
 
 
 __all__ = [
@@ -91,6 +97,8 @@
     # Dependencies
     "_NUMPY_AVAILABLE",
     "_GIL_ENABLED",
+    "_PANDAS_AVAILABLE",
+    "_POLARS_AVAILABLE",
     # Random
     "random",
     # Codecs
@@ -174,4 +182,7 @@
     # Engine
     "GeneticEngine",
     "Generation",
+    # Metrics
+    "MetricSet",
+    "Metric",
 ]

py-radiate/radiate/codec/float.py

@@ -16,7 +16,7 @@ def __init__(
         Initialize the float codec with a PyFloatCodec instance.
         :param codec: An instance of PyFloatCodec.
         """
-        self.codec = self._create_encoding(encoding, use_numpy)
+        self.codec = self.__create_encoding(encoding, use_numpy)
 
     def encode(self) -> Genotype[float]:
         """
@@ -35,7 +35,7 @@ def decode(self, genotype: Genotype[float]) -> T:
             raise TypeError("genotype must be an instance of Genotype.")
         return self.codec.decode_py(genotype=genotype.__backend__())
 
-    def _create_encoding(
+    def __create_encoding(
         self, encoding: FloatEncoding, use_numpy: bool
     ) -> PyFloatCodec:
         """
@@ -124,20 +124,21 @@ def matrix(
         Create a matrix codec with specified rows and columns.
         Args:
             shape: A tuple (rows, cols) or a list of integers specifying the shape of the matrix.
-            value_range: Minimum and maximum value for the Gene's Allele to be init with.
-            bound_range: Minimum and maximum values the allele is allowed to be within during evolution
+            init_range: Minimum and maximum value for the Gene's Allele to be init with.
+            bounds: Minimum and maximum values the allele is allowed to be within during evolution.
+            use_numpy: Whether or not to decode the Genotype into a numpy array.
         Returns:
             A new FloatCodec instance with matrix configuration.
 
         Example
         --------
         Create a codec that will produce a Genotype with 2 Chromosomes both containing 3 FloatGenes
         Alleles between 0.0 and 1.0, and bounds between -1.0 and 2.0:
-        >>> rd.FloatCodec.matrix(shape=(2, 3), value_range=(0.0, 1.0), bound_range=(-1.0, 2.0))
+        >>> rd.FloatCodec.matrix(shape=(2, 3), init_range=(0.0, 1.0), bounds=(-1.0, 2.0))
         FloatCodec(...)
 
         The same can be achieved with a list of shapes:
-        >>> rd.FloatCodec.matrix(shape=[3, 3], value_range=(0.0, 1.0), bound_range=(-1.0, 2.0))
+        >>> rd.FloatCodec.matrix(shape=[3, 3], init_range=(0.0, 1.0), bounds=(-1.0, 2.0))
         FloatCodec(...)
         """
         shapes = None
@@ -180,15 +181,16 @@ def vector(
         Create a vector codec with specified length.
         Args:
             length: Length of the vector.
-            value_range: Minimum and maximum value for the Gene's Allele to be init with.
-            bound_range: Minimum and maximum values the allele is allowed to be within during evolution.
+            init_range: Minimum and maximum value for the Gene's Allele to be init with.
+            bounds: Minimum and maximum values the allele is allowed to be within during evolution.
+            use_numpy: Whether or not to decode the Genotype into a numpy array.
         Returns:
             A new FloatCodec instance with vector configuration.
 
         Example
         --------
         Create a FloatCodec that will encode a Genotype with a single Chromosome containing 5 FloatGenes
-        >>> rd.FloatCodec.vector(length=5, value_range=(0.0, 1.0), bound_range=(-1.0, 2.0))
+        >>> rd.FloatCodec.vector(length=5, init_range=(0.0, 1.0), bounds=(-1.0, 2.0), use_numpy=False)
         FloatCodec(...)
         """
         if length <= 0:
@@ -222,16 +224,16 @@ def scalar(
         """
         Create a scalar codec.
         Args:
-            value_range: Minimum and maximum value for the Gene's Allele to be init with.
-            bound_range: Minimum and maximum values the allele is allowed to be within during evolution.
+            init_range: Minimum and maximum value for the Gene's Allele to be init with.
+            bounds: Minimum and maximum values the allele is allowed to be within during evolution.
         Returns:
             A new FloatCodec instance with scalar configuration.
 
         Example:
         --------
         Create a FloatCodec that will encode a Genotype with a single Chromosome containing a single FloatGene
         with Alleles between 0.0 and 1.0, and bounds between -1.0 and 2.0:
-        >>> rd.FloatCodec.scalar(value_range=(0.0, 1.0), bound_range=(-1.0, 2.0))
+        >>> rd.FloatCodec.scalar(init_range=(0.0, 1.0), bounds=(-1.0, 2.0))
         FloatCodec(...)
         """
         if init_range is not None:

py-radiate/radiate/codec/graph.py

@@ -30,7 +30,7 @@ def weighted_directed(
         output: NodeValues | None = None,
         values: dict[str, list[Op]] | list[tuple[str, list[Op]]] | None = None,
         max_nodes: int | None = None,
-    ) -> GraphCodec[Op, Graph]:
+    ) -> GraphCodec:
         return GraphCodec.__build_common(
             name="weighted_directed",
             shape=shape,
@@ -49,7 +49,7 @@ def weighted_recurrent(
         output: NodeValues | None = None,
         values: dict[str, list[Op]] | list[tuple[str, list[Op]]] | None = None,
         max_nodes: int | None = None,
-    ) -> GraphCodec[Op, Graph]:
+    ) -> GraphCodec:
         return GraphCodec.__build_common(
             name="weighted_recurrent",
             shape=shape,
@@ -68,7 +68,7 @@ def directed(
         output: NodeValues | None = None,
         values: dict[str, list[Op]] | list[tuple[str, list[Op]]] | None = None,
         max_nodes: int | None = None,
-    ) -> GraphCodec[Op, Graph]:
+    ) -> GraphCodec:
         return GraphCodec.__build_common(
             name="directed",
             shape=shape,
@@ -87,7 +87,7 @@ def recurrent(
         output: NodeValues | None = None,
         values: dict[str, list[Op]] | list[tuple[str, list[Op]]] | None = None,
         max_nodes: int | None = None,
-    ) -> GraphCodec[Op, Graph]:
+    ) -> GraphCodec:
         return GraphCodec.__build_common(
             name="recurrent",
             shape=shape,
@@ -106,7 +106,7 @@ def gru(
         output: NodeValues | None = None,
         values: dict[str, list[Op]] | list[tuple[str, list[Op]]] | None = None,
         max_nodes: int | None = None,
-    ) -> GraphCodec[Op, Graph]:
+    ) -> GraphCodec:
         return GraphCodec.__build_common(
             name="gru",
             shape=shape,
@@ -125,7 +125,7 @@ def lstm(
         output: NodeValues | None = None,
         values: dict[str, list[Op]] | list[tuple[str, list[Op]]] | None = None,
         max_nodes: int | None = None,
-    ) -> GraphCodec[Op, Graph]:
+    ) -> GraphCodec:
         return GraphCodec.__build_common(
             name="lstm",
             shape=shape,
@@ -145,7 +145,7 @@ def __build_common(
         output: NodeValues | None = None,
         values: dict[str, list[Op]] | list[tuple[str, list[Op]]] | None = None,
         max_nodes: int | None = None,
-    ) -> GraphCodec[Op, Graph]:
+    ) -> GraphCodec:
         input_size, output_size = shape
 
         if input_size < 1 or output_size < 1:

py-radiate/radiate/codec/tree.py

@@ -27,7 +27,7 @@ def __init__(
         leaf: NodeValues | None = None,
         root: NodeValues | None = None,
         values: dict[str, list[Op]] | list[tuple[str, list[Op]]] | None = None,
-    ) -> TreeCodec[Op, Tree]:
+    ) -> TreeCodec:
         input_size, output_size = shape
 
         if input_size < 1 or output_size < 1:

py-radiate/radiate/dependancies.py

@@ -54,9 +54,17 @@ def _lazy_import(module_name: str) -> tuple[ModuleType, bool]:
     )
 
 
-if TYPE_CHECKING:
-    import numpy as np
+_PANDAS_AVAILABLE = False
+_POLARS_AVAILABLE = False
+
 
-    _NUMPY_AVAILABLE = True
+if TYPE_CHECKING:
+    try:
+        import numpy as np
+        _NUMPY_AVAILABLE = True
+    except ModuleNotFoundError:
+        _NUMPY_AVAILABLE = False
 else:
     np, _NUMPY_AVAILABLE = _lazy_import("numpy")
+    pl, _POLARS_AVAILABLE = _lazy_import("polars")
+    pd, _PANDAS_AVAILABLE = _lazy_import("pandas")

py-radiate/radiate/generation.py

@@ -1,10 +1,9 @@
-from typing import Any
-
 from datetime import timedelta
 
 from radiate.genome.ecosystem import Ecosystem
 from radiate.genome.species import Species
 from radiate.wrapper import PyObject
+from radiate.metrics import MetricSet
 from .genome import Population
 from radiate.radiate import PyGeneration
 
@@ -39,12 +38,12 @@ def value(self) -> T:
         """
         return self.__backend__().value()
 
-    def metrics(self) -> dict[str, Any]:
+    def metrics(self) -> MetricSet:
         """
         Get the metrics of the generation.
         :return: The metrics of the generation.
         """
-        return self.__backend__().metrics()
+        return MetricSet.from_rust(self.__backend__().metrics())
 
     def objective(self) -> list[str] | str:
         """

py-radiate/radiate/handlers.py

@@ -3,6 +3,7 @@
 from typing import Any, Callable
 from radiate.radiate import PySubscriber, PyEngineEvent
 from radiate.wrapper import PyObject
+from radiate.metrics import MetricSet
 
 
 class EventType(Enum):
@@ -106,9 +107,12 @@ def value(self) -> Any:
         """
         return self.__backend__().value()
 
-    def metrics(self) -> dict[str, Any] | None:
+    def metrics(self) -> MetricSet | None:
         """
         Get the metrics of the event.
         :return: The metrics of the event.
         """
-        return self.__backend__().metrics()
+        metrics = self.__backend__().metrics()
+        if metrics is None:
+            return None
+        return MetricSet.from_rust(metrics)