Refactor documentation and examples: Update contributing guidelines, enhance tooltip descriptions, and improve comment formatting in various example scripts.

Author: selimfirat

docs/contributing.rst

@@ -86,6 +86,7 @@ Development Workflow
 
        # Exclude slow tests
        pytest tests/ -m "not slow"
+
    - Run pre-commit checks: `pre-commit run -a`
 
 4. **Submitting a pull request:**

docs/examples/constraints/index.rst

@@ -27,7 +27,7 @@ Constraint handling and optimization techniques for communication systems design
 
 .. raw:: html
 
-    <div class="sphx-glr-thumbcontainer" tooltip="ax.text(0.5, 0.5, 'Spectral Mask Constraint Effects (Visualization placeholder)', ha='center', va='center', transform=ax.transAxes, fontsize=14) ax.set_title('Spectral Mask Constraint Effects', fontsize=16, fontweight='bold') plt.show()=============================================================================================================================================================== This example demonstrates how to combine multiple constraints in Kaira to satisfy complex signal requirements. We'll explore the composition utilities and see how constraints can be sequentially applied to meet practical transmission specifications.">
+    <div class="sphx-glr-thumbcontainer" tooltip="This example demonstrates how to combine multiple constraints in Kaira to satisfy complex signal requirements. We'll explore the composition utilities and see how constraints can be sequentially applied to meet practical transmission specifications.">
 
 .. only:: html
 

docs/examples/example_utils/index.rst

@@ -42,7 +42,7 @@
 # Generate QPSK Signal
 # ------------------------------------
 # QPSK Signal Generation
-# =====================
+# ==============================
 #
 # Let's use Kaira's QPSKModulator to generate QPSK symbols.
 

examples/channels/plot_fading_channels.py

@@ -1,11 +1,7 @@
 """
 ==========================================================================================================================================================================
 Composing Constraints for Complex Signal Requirements
-==========fig, ax = plt.subplots(figsize=(12, 6), constrained_layout=True)
-ax.text(0.5, 0.5, 'Spectral Mask Constraint Effects\n(Visualization placeholder)',
-        ha='center', va='center', transform=ax.transAxes, fontsize=14)
-ax.set_title('Spectral Mask Constraint Effects', fontsize=16, fontweight='bold')
-plt.show()===============================================================================================================================================================
+==========================================================================================================================================================================
 
 This example demonstrates how to combine multiple constraints in Kaira to satisfy complex
 signal requirements. We'll explore the composition utilities and see how constraints

examples/constraints/plot_constraint_composition.py

@@ -306,7 +306,7 @@ def majority_decoder(x, repeat=3):
 # Conclusion
 # ------------------
 # Data Generation Summary
-# ======================
+# ====================================
 #
 # This example demonstrated the data generation utilities in Kaira:
 #

examples/data/plot_data_generation.py

@@ -23,7 +23,7 @@
 # Setting up
 # ----------------------
 # Block-wise Processing Configuration
-# ==================================
+# ========================================================
 
 # First, we set a random seed to ensure reproducibility of results.
 torch.manual_seed(42)
@@ -371,10 +371,12 @@ def hamming_decode(codeword):
 # error correction (FEC) coding:
 #
 # Key points:
+#
 # - Block-wise processing is fundamental to many error correction schemes
 # - The `apply_blockwise` function provides a convenient way to apply operations
 #   on blocks of data
 # - We demonstrated several practical applications of block-wise processing:
+#
 #   - Simple parity-based error detection
 #   - Complex operations that return multiple values
 #   - Implementation of a (7,4) Hamming code for error correction
@@ -383,6 +385,7 @@ def hamming_decode(codeword):
 # like BCH, Reed-Solomon, and LDPC codes, which can correct multiple errors per block.
 #
 # References:
+#
 # - :cite:`lin2004error` - Provides detailed treatments of block coding and parity checks
 # - :cite:`moon2005error` - Covers mathematical methods for various error correction codes
 # - :cite:`golay1949notes` - Historical paper on efficient coding techniques

examples/models_fec/plot_fec_blockwise_processing.py

@@ -62,7 +62,7 @@
 # Belief Propagation Animation
 # --------------------------------------
 # Belief Propagation Message Passing Visualization
-# ===============================================
+# ==============================================================
 
 
 class BeliefPropagationVisualizer:
@@ -183,9 +183,9 @@ def visualize_iteration(self, iteration):
 
 # %%
 # Performance Comparison with Different Parameters
-# ------------------------------------------------
+# ---------------------------------------------------------
 # LDPC Iteration Benefits Analysis
-# ===============================
+# ============================================
 
 
 def compare_ldpc_performance():

examples/models_fec/plot_fec_ldpc_advanced_visualization.py

@@ -27,7 +27,7 @@
 # Setting up
 # --------------------------------------
 # LDPC Code Configuration and Reproducibility Setup
-# =============================================
+# ============================================================
 #
 # First, we set a random seed to ensure reproducibility and
 # configure our visualization settings.
@@ -163,7 +163,7 @@
 # Performance Analysis
 # -----------------------------------
 # Error Rate Performance Visualization
-# ===================================
+# ===============================================
 #
 # Let's visualize the performance of our LDPC code with different numbers
 # of belief propagation iterations across various SNR levels.
@@ -190,7 +190,7 @@
 # Single Message Example
 # ------------------------------------
 # Individual Message Processing Demonstration
-# =========================================
+# ===================================================
 #
 # Let's walk through the encoding, transmission, and decoding process
 # for a single message to better understand the flow.
@@ -273,6 +273,7 @@
 # improves with increased SNR and more decoding iterations.
 #
 # Key Insights:
+#
 # - LDPC codes are widely used in modern communication systems due to
 #   their excellent error-correcting capabilities that approach the
 #   Shannon limit