chore: post-review quick wins — deps slimming, TRP docstring, dead-code removal

Safe S-effort fixes from the 2026-05 multi-perspective review (docs/REVIEW_2026-05.md):

- deps: move openai to the [ai] extra; drop keyring + cryptography from core
  (imported nowhere after the v5.0.0 AI removal); remove pyinstaller from the
  runtime requirements.txt (it's in the [exe] extra). Closes #16, #17.
- numpy: raise the ceiling <2.0.0 -> <3.0.0; the suite already runs green on
  numpy 2.2.4 and uses no 2.0-removed APIs. Closes #18.
- calculations.calculate_trp: clarify the docstring — the per-angle input is
  EIRP and the 1/(4pi) is the canonical CTIA discrete TRP (an isotropic 0 dBm
  EIRP pattern integrates to ~0 dBm, NOT -11 dB). Prevents future false-alarm
  "bugs". Closes #11.
- groupdelay: remove the dead, undefined-name-referencing variance/std block;
  the real metric is tracked in #8.

No behavior change; full suite 327 passed / 148 skipped.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

Author: RFingAdam

plot_antenna/calculations.py

@@ -6,16 +6,23 @@
 
 def calculate_trp(power_dBm_2d, theta_angles_rad, inc_theta, inc_phi):
     """
-    Calculate Total Radiated Power (TRP) using IEEE-correct solid angle integration.
+    Calculate Total Radiated Power (TRP) using the CTIA/IEEE-149 discrete
+    solid-angle integration.
 
-    The TRP is calculated by integrating radiated power density over a closed sphere:
-        TRP = (1/4π) ∫∫ P(θ,φ) · sin(θ) dθ dφ
+    The per-angle input is EIRP — the isotropic-referenced power measured in
+    each direction (after path-loss calibration). For EIRP, TRP is the
+    sphere average of EIRP, i.e. the standard CTIA discrete form:
 
-    For discrete measurements, this becomes:
-        TRP = Σ P(θ,φ) · sin(θ) · Δθ · Δφ / (4π)
+        TRP = (1/4π) ∫∫ EIRP(θ,φ) · sin(θ) dθ dφ
+            ≈ Σ EIRP(θ,φ) · sin(θ) · Δθ · Δφ / (4π)
+
+    The 1/(4π) is correct *because the input is EIRP*, not radiation intensity
+    U (W/sr); for an isotropic radiator with EIRP = P0 in every direction this
+    integrates back to TRP = P0 (verified by the golden-reference test). Do not
+    remove the 1/(4π) — see docs/REVIEW_2026-05.md (finding R7/R8).
 
     Parameters:
-        power_dBm_2d: 2D array of power values in dBm (theta x phi)
+        power_dBm_2d: 2D array of per-angle EIRP in dBm (theta x phi)
         theta_angles_rad: 1D array of theta angles in radians
         inc_theta: Theta increment in degrees
         inc_phi: Phi increment in degrees

plot_antenna/groupdelay.py

@@ -155,15 +155,10 @@ def plot_group_delay_error(data_dict, min_freq=None, max_freq=None):
         difference_data.append(difference_at_freq * 1e12)
         error_at_freq = (difference_at_freq) * 29979245800
         error_data.append(error_at_freq)
-        """
-        # TODO Calculate the variance in picoseconds
-        variance_at_freq = np.var(group_delays_at_freq_ps)
-        variance_data.append(variance_at_freq)
-
-        # TODO Calculate the standard deviation
-        std_dev_at_freq = np.std(group_delays_at_freq_ps)
-        std_dev_data.append(std_dev_at_freq)
-        """
+        # NOTE: per-frequency group-delay variance/std across theta is a planned
+        # metric (tracked issue: group-delay dispersion). The previous dead
+        # block referenced an undefined name and is removed to avoid confusion;
+        # implement it with a dedicated test alongside group-delay test coverage.
     # Plot Group Delay difference
     plt.figure(figsize=(10, 6))
     plt.plot(freq_points, difference_data, label="Max Group Delay Difference over Theta")

pyproject.toml

@@ -28,18 +28,15 @@ classifiers = [
 ]
 
 dependencies = [
-    "numpy>=1.26.0,<2.0.0",
+    "numpy>=1.26.0,<3.0.0",
     "scipy>=1.14.0,<2.0.0",
     "matplotlib>=3.10.0,<4.0.0",
     "pandas>=2.0.0,<3.0.0",
     "python-docx>=1.2.0,<2.0.0",
-    "openai>=1.38.0,<2.0.0",
-    "keyring>=25.0.0,<26.0.0",
     "python-dotenv>=1.0.0,<2.0.0",
     "tqdm>=4.65.0,<5.0.0",
     "requests>=2.31.0,<3.0.0",
     "Pillow>=10.0.0,<11.0.0",
-    "cryptography>=43.0.0,<44.0.0",
 ]
 
 [project.optional-dependencies]
@@ -52,7 +49,10 @@ dev = [
     "mypy>=1.8.0",
     "bump2version>=1.0.0",
 ]
+# Optional: only needed if you wire RFlect's data into an external LLM yourself.
+# RFlect's own report/analysis path is fully deterministic and needs none of these.
 ai = [
+    "openai>=1.38.0,<2.0.0",
     "anthropic>=0.40.0",
     "ollama>=0.4.0",
 ]

requirements.txt

@@ -1,17 +1,17 @@
+# RFlect runtime dependencies (deterministic core — no LLM/API key needed).
+# Optional extras live in pyproject.toml: [ai] (openai/anthropic/ollama),
+# [dev] (pytest/black/flake8/mypy), [exe] (pyinstaller).
+
 # Core scientific computing
-numpy>=1.26.0,<2.0.0
+numpy>=1.26.0,<3.0.0
 scipy>=1.14.0,<2.0.0
 matplotlib>=3.10.0,<4.0.0
 pandas>=2.0.0,<3.0.0
 
 # Document generation
 python-docx>=1.2.0,<2.0.0
 
-# AI/ML integration
-openai>=1.38.0,<2.0.0
-
-# Security & configuration
-keyring>=25.0.0,<26.0.0
+# Configuration
 python-dotenv>=1.0.0,<2.0.0
 
 # CLI utilities
@@ -20,10 +20,3 @@ requests>=2.31.0,<3.0.0
 
 # Image processing (for logo display)
 Pillow>=10.0.0,<11.0.0
-
-# Encryption (for API key storage)
-cryptography>=43.0.0,<44.0.0
-
-# PyInstaller for executable builds
-pyinstaller>=6.18.0,<7.0.0
-pyinstaller-hooks-contrib>=2026.0