Version 0.3

API_scheme.md

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+<h2>PINA Code Structure</h2>
+
+
+Here is a high-level overview of PINA’s main modules. For full details, refer to the
+<a href="https://mathlab.github.io/PINA/"><b>documentation</b></a>.
+
+```mermaid
+flowchart TB
+    PINA["<h1>pina</h1>The basic module including `Condition`, <tt>LabelTensor</tt>, `Graph` and `Trainer` API"]
+
+    subgraph R1[" "]
+        direction LR
+        PROB["<h2>pina.problem</h2> Module for defining problems via base class inheritance"]
+        MODEL["<h2>pina.model</h2> Module for built-in PyTorch models full architectures"]
+        SOLVER["<h2>pina.solver</h2> Module for built-in solvers and abstract interfaces"]
+        CALLBACK["<h2>pina.callback</h2> Module for built-in callbacks to integrate training pipelines"]
+    end
+
+    subgraph R2[" "]
+        direction LR
+        DOMAIN["<h2>pina.domain</h2> Module for defining geometries and set operations"]
+        BLOCK["<h2>pina.block</h2> Module for built-in PyTorch models layers only"]
+        OPTIM["<h2>pina.optim</h2> Module for build or import optimizers and schedulers"]
+        DATA["<h2>pina.data</h2> Module for DataModules for data processing"]
+    end
+
+    subgraph R3[" "]
+        direction LR
+        OPERATOR["<h2>pina.operator</h2> Module for differential operators"]
+        ADAPT["<h2>pina.adaptive_function</h2> Module for PyTorch learnable activations"]
+        LOSS["<h2>pina.loss</h2> Module for losses and weighting strategies"]
+        CONDITION["<h2>pina.condition</h2> Module for model training constraints"]
+    end
+
+    PINA --> PROB
+    PINA --> MODEL
+    PINA --> SOLVER
+    PINA --> CALLBACK
+
+    PROB --> DOMAIN
+    MODEL --> BLOCK
+    SOLVER --> OPTIM
+    CALLBACK --> DATA
+
+    DOMAIN --> OPERATOR
+    BLOCK --> ADAPT
+    OPTIM --> LOSS
+    DATA --> CONDITION
+```