From 452dddc19cad85b6bdaae6e88225e6d20b8e80bb Mon Sep 17 00:00:00 2001
From: Brendan Haines <brendan.haines@gmail.com>
Date: Mon, 7 Jul 2025 23:22:36 -0600
Subject: [PATCH] functional 1 port calibration

---
 charon_vna/vna.py     | 46 +++++++++++++++++++++++++++++++++++++++++++
 charon_vna/vna_dev.py | 37 ++++++++++++++++++++++++++++++----
 2 files changed, 79 insertions(+), 4 deletions(-)

diff --git a/charon_vna/vna.py b/charon_vna/vna.py
index 3ea3552..fb2bc99 100644
--- a/charon_vna/vna.py
+++ b/charon_vna/vna.py
@@ -1,5 +1,6 @@
 # %% imports
 import copy
+import pickle
 from enum import IntEnum, unique
 from pathlib import Path
 from typing import Any, Callable, Dict, List, Literal, Tuple
@@ -360,6 +361,51 @@ class Charon:
 
         return s
 
+    def calibrate_sol(self, prompt: Callable[[str], None] | None = None, **kwargs) -> rf.calibration.Calibration:
+        if len(self.ports) != 1:
+            raise ValueError(
+                f"SOL calibration needs only one port but {len(self.ports)} ports are enabled. "
+                "Did you mean to use SOLT?"
+            )
+
+        if prompt is None:
+            prompt = lambda s: input(f"{s}\nENTER to continue...")
+
+        ideal = rf.media.DefinedGammaZ0(frequency=rf.media.Frequency.from_f(self.frequency, unit="Hz"))
+        ideals = [ideal.short(), ideal.open(), ideal.load(0)]
+
+        names = ["short", "open", "load"]
+
+        measured = list()
+        for name in names:
+            prompt(f"Connect standard: {name} to port {self.ports[0]}")
+            measured.append(self.capture(**kwargs))
+
+        cal = rf.OnePort(ideals=ideals, measured=[s2net(m) for m in measured])
+
+        self.calibration = cal
+
+        return cal
+
+    def save_calibration(self, path: Path | str):
+        path = Path(path)
+        if path.suffix.lower() == ".pkl":
+            with open(str(path), "wb") as f:
+                pickle.dump(self.calibration, f)
+        else:
+            raise NotImplementedError(f"Unknown calibration file extension: {path.suffix}")
+
+    def load_calibration(self, path: Path | str):
+        path = Path(path)
+        if path.suffix.lower() == ".pkl":
+            with open(str(path), "rb") as f:
+                cal = pickle.load(f)
+                if not isinstance(cal, rf.calibration.Calibration):
+                    raise ValueError(f"Expected {rf.calibration.Calibration}, got {type(cal)}")
+                self.calibration = cal
+        else:
+            raise NotImplementedError(f"Unknown calibration file extension: {path.suffix}")
+
 
 # %%
 if __name__ == "__main__":
diff --git a/charon_vna/vna_dev.py b/charon_vna/vna_dev.py
index 3acff13..9f51118 100644
--- a/charon_vna/vna_dev.py
+++ b/charon_vna/vna_dev.py
@@ -2,23 +2,52 @@
 import numpy as np
 from matplotlib import pyplot as plt
 
+from charon_vna.util import db20, net2s, s2net
 from charon_vna.vna import Charon
 
 # %%
-frequency = np.linspace(80e6, 280e6, 31)
+frequency = np.linspace(80e6, 280e6, 301)
 
 # %%
-vna = Charon(frequency=frequency, ports=2)
+vna = Charon(frequency=frequency, ports=1)
 
 # %%
-s = vna.capture(measurements=[(2, 1), (2, 2)])
+s = vna.capture()
 
 # %%
 for m in s.m.data:
     for n in s.n.data:
-        plt.plot(s.frequency, 20 * np.log10(np.abs(s.sel(m=m, n=n))), label="$S_{" + str(m) + str(n) + "}$")
+        plt.plot(s.frequency, db20(s.sel(m=m, n=n)), label="$S_{" + str(m) + str(n) + "}$")
 plt.grid(True)
 plt.legend()
+plt.show()
 
 
+# %%
+vna.calibrate_sol()
+
+# %%
+vna.load_calibration("./calibration.pkl")
+
+# %%
+s2 = net2s(vna.calibration.apply_cal(s2net(s)))
+
+for m in s.m.data:
+    for n in s.n.data:
+        plt.plot(s.frequency, db20(s.sel(m=m, n=n)), label="$S_{" + str(m) + str(n) + "}$ (uncalibrated)")
+        plt.plot(s2.frequency, db20(s2.sel(m=m, n=n)), label="$S_{" + str(m) + str(n) + "}$ (calibrated)")
+plt.grid(True)
+plt.legend()
+plt.ylabel("Magnitude [dB]")
+plt.show()
+
+for m in s.m.data:
+    for n in s.n.data:
+        plt.plot(s.frequency, np.angle(s.sel(m=m, n=n), deg=True), label="$S_{" + str(m) + str(n) + "}$ (uncalibrated)")
+        plt.plot(s2.frequency, np.angle(s2.sel(m=m, n=n), deg=True), label="$S_{" + str(m) + str(n) + "}$ (calibrated)")
+plt.grid(True)
+plt.legend()
+plt.ylabel("Phase [deg]")
+plt.show()
+
 # %%