Add object calibration

Makefile

@@ -121,7 +121,7 @@ DEPFILES := $(sort $(SWEEP_ORCH_OBJS:.o=.d) $(PREPROCESSOR_OBJS:.o=.d) $(DATA_PR
 NATIVE_TEST_SOURCES := $(COMMON_SOURCES) $(LOCATOR_SOURCES) \
 	data_acq_and_processing/tests/native_regressions.cpp \
 	data_acq_and_processing/processing/data_processor/src/processing_live_config.cpp \
-	data_acq_and_processing/preprocessing/calibration_master/src/channel_bundle_support.cpp \
+	$(filter-out %/main.cpp,$(PREPROC_SOURCES)) \
 	data_acq_and_processing/sweep_orchestrator/src/sweep_orchestrator.cpp \
 	$(KAMIL_COLLECTOR_DIR)/src/capture_file_writer.cpp \
 	$(KAMIL_COLLECTOR_DIR)/src/tty_protocol_writer.cpp

README.md

@@ -21,7 +21,8 @@ simply skips to the freshest frame:
    configures the radar, performs the frequency sweep, and publishes raw S11/S21
    traces.
 2. **Preprocessing** — `data_preprocessor` applies through/OSL calibration,
-   reference subtraction, and optional frequency-domain notch filtering.
+   reference subtraction, optional frequency-domain notch filtering, and an
+   optional object-based MIMO correction of S21.
 3. **Processing** — `data_processor` runs the selected processing mode and emits
    results (pass-through traces, B-scan images, GPR images with detected objects,
    or 3D SAR views). Detected objects are additionally broadcast to subscribers
@@ -223,13 +224,29 @@ result count or Stop; Stop and closing the window flush accepted data. Acquisiti
 rings use latest-wins delivery, so disk recording cannot recover sweeps overwritten
 before the GUI receives them. NumPy datasets preserve both S-parameters, capture
 windows, every supported result payload, and processing time. Failed exports remove
-their staging files, leaving existing datasets intact.
+their staging files, leaving existing datasets intact. Companion profiles retain
+the radar, antenna layout and preprocessing used for acquisition, including when
+another profile is loaded after Stop.
 
 Calibration and reference sets keep their trace arrays and metadata together in one
 atomically replaced NPZ archive, with a readable JSON sidecar. Earlier NPZ/JSON pairs
 remain supported. Invalid trace shapes, duplicate combinations and non-finite
 calibration/reference values are rejected before a saved set is replaced.
 Median captures also require identical frequency axes and channel coverage.
+In **Preprocessing Panel**, create or select the ordinary S21 calibration and
+empty-scene reference first. **Create…** in the **Object Calibration** row opens a separate step:
+take fresh sweeps, then enter the measured reflector centre X/Y/Z in metres.
+Height above ground, radar pitch and sphere radius follow `mimo_calibration.py`;
+several reflector positions may contribute to one calibration. The calculation
+shows each pair's phase at the target before/after correction and its coherence.
+The selected reference is already subtracted, and the previous object correction
+is disabled while these sweeps are acquired. Saved object corrections apply on the
+next **Start**, after notch filtering and before any processor; **Off** disables
+them. Changing antenna geometry disables an incompatible correction and reloads
+acquisition without restarting the application. **Import…** in that row
+accepts the example's `cal_*.npy` / `cal_meta.json` format; the example and GUI share
+one numerical implementation.
+
 Dataset replay restores both recorded S-parameters and orders long recordings by
 their numeric index; older S21-only datasets still replay with zero S11. Offline
 JSON conversion and the GUI share the same sweep-matching code.

data_acq_and_processing/common_cpp/config/include/run_config.hpp

@@ -81,6 +81,7 @@ struct PreprocessAssetConfig {
 struct S21PreprocessConfig {
     PreprocessAssetConfig calibration{};
     PreprocessAssetConfig reference{};
+    PreprocessAssetConfig object_calibration{};
 };
 
 struct S11CalibrationPreprocessConfig {

data_acq_and_processing/common_cpp/config/src/run_config.cpp

@@ -555,6 +555,10 @@ auto load_run_config(const std::string& path) -> RunConfig {
         const auto* s21_obj = as_object(required_field(*preprocess_obj, "s21"), "preprocess.s21");
         config.preprocess.s21.calibration = parse_preprocess_asset(*s21_obj, "calibration", "preprocess.s21");
         config.preprocess.s21.reference = parse_preprocess_asset(*s21_obj, "reference", "preprocess.s21");
+        if (optional_field(*s21_obj, "object_calibration") != nullptr) {
+            config.preprocess.s21.object_calibration =
+                parse_preprocess_asset(*s21_obj, "object_calibration", "preprocess.s21");
+        }
 
         const auto* s11_obj = as_object(required_field(*preprocess_obj, "s11"), "preprocess.s11");
         const auto* s11_calibration_obj =

data_acq_and_processing/preprocessing/calibration_master/include/channel_bundle_support.hpp

@@ -50,6 +50,18 @@ class S21ReferenceBundle {
     std::unordered_map<ipc::ComboKey, ChannelTrace, ipc::ComboKeyHash> traces_by_combo_{};
 };
 
+// Object-derived MIMO correction, exported on each pair's runtime frequency grid.
+// An empty path disables it; enabled bundles must cover every active pair.
+class S21ObjectCalibrationBundle {
+  public:
+    void load(const std::string& path);
+    void validate_combos(const std::vector<ipc::ComboKey>& combos) const;
+    void apply(ipc::SweepTraceBlock& trace) const;
+
+  private:
+    std::unordered_map<ipc::ComboKey, ChannelTrace, ipc::ComboKeyHash> factors_by_combo_{};
+};
+
 class S11CalibrationBundle {
   public:
     struct Coefficients {

data_acq_and_processing/preprocessing/calibration_master/src/channel_bundle_support.cpp

@@ -8,6 +8,7 @@
 #include <fstream>
 #include <iostream>
 #include <iterator>
+#include <limits>
 #include <span>
 #include <stdexcept>
 #include <string>
@@ -197,11 +198,11 @@ template <typename TValue>
 auto resolve_required(
     const std::unordered_map<ipc::ComboKey, TValue, ipc::ComboKeyHash>& values_by_combo,
     const ipc::ComboKey& combo,
-    const std::string& value_label
+    const char* value_label
 ) -> const TValue& {
     const auto found = values_by_combo.find(combo);
     if (found == values_by_combo.end()) {
-        throw std::runtime_error(value_label + " is missing for combo " + combo_to_string(combo));
+        throw std::runtime_error(std::string(value_label) + " is missing for combo " + combo_to_string(combo));
     }
     return found->second;
 }
@@ -345,6 +346,38 @@ auto S21ReferenceBundle::resolve(const ipc::ComboKey& combo) const -> const Chan
     return resolve_required(traces_by_combo_, combo, "S21 reference trace");
 }
 
+void S21ObjectCalibrationBundle::load(const std::string& path) {
+    if (path.empty()) {
+        factors_by_combo_.clear();
+        return;
+    }
+    factors_by_combo_ = load_channel_traces(path, "S21 object calibration", RawTraceChannel::S21);
+}
+
+void S21ObjectCalibrationBundle::validate_combos(const std::vector<ipc::ComboKey>& combos) const {
+    validate_bundle_combos(factors_by_combo_, combos, "S21 object calibration bundle");
+}
+
+void S21ObjectCalibrationBundle::apply(ipc::SweepTraceBlock& trace) const {
+    if (factors_by_combo_.empty()) { return; }
+    const auto& factors = resolve_required(factors_by_combo_, trace.combo, "S21 object calibration");
+    ensure_frequency_axis_match(factors.frequency_hz, trace.frequency_hz, "S21 object calibration");
+    if (trace.s21.size() != factors.samples.size()) {
+        throw std::runtime_error("S21 object calibration vector size mismatch");
+    }
+    for (std::size_t index = 0; index < trace.s21.size(); ++index) {
+        const auto value = trace.s21[index];
+        const auto factor = factors.samples[index];
+        const auto corrected = std::complex<double>(value.re, value.im) * std::complex<double>(factor.re, factor.im);
+        if (!std::isfinite(corrected.real()) || !std::isfinite(corrected.imag()) ||
+            std::abs(corrected.real()) > std::numeric_limits<float>::max() ||
+            std::abs(corrected.imag()) > std::numeric_limits<float>::max()) {
+            throw std::runtime_error("S21 object calibration result must fit finite float32");
+        }
+        trace.s21[index] = {.re = static_cast<float>(corrected.real()), .im = static_cast<float>(corrected.imag())};
+    }
+}
+
 void S11CalibrationBundle::load(
     const std::string& open_path,
     const std::string& short_path,

data_acq_and_processing/preprocessing/data_preprocessor/include/data_preprocessor.hpp

@@ -39,6 +39,7 @@ class DataPreprocessor {
     const config::RunConfig& config_;
     CalibrationMaster& calibration_master_;
     ReferenceMaster& reference_master_;
+    S21ObjectCalibrationBundle object_calibration_;
     ipc::ShmRing& raw_ring_;
     ipc::ShmRing& preprocessed_ring_;
     ipc::ShmRing* preprocessed_tap_ring_ = nullptr;

data_acq_and_processing/preprocessing/data_preprocessor/src/data_preprocessor.cpp

@@ -8,6 +8,7 @@
 #include <span>
 #include <stdexcept>
 #include <string_view>
+#include <utility>
 #include <vector>
 
 namespace radar::preprocessing {
@@ -104,11 +105,14 @@ DataPreprocessor::DataPreprocessor(
       reference_master_(reference_master),
       raw_ring_(raw_ring),
       preprocessed_ring_(preprocessed_ring),
-      preprocessed_tap_ring_(preprocessed_tap_ring) {}
+      preprocessed_tap_ring_(preprocessed_tap_ring) {
+    object_calibration_.load(config_.preprocess.s21.object_calibration.bundle_path);
+}
 
 void DataPreprocessor::validate_startup_prerequisites() const {
     calibration_master_.validate_combos(config_.run_combos);
     reference_master_.validate_combos(config_.run_combos);
+    object_calibration_.validate_combos(config_.run_combos);
 }
 
 auto DataPreprocessor::try_pop_raw_collection(
@@ -188,10 +192,12 @@ auto DataPreprocessor::preprocess_collection(const ipc::RawSweepCollection& raw_
     preprocessed.traces.reserve(raw_collection.traces.size());
 
     for (const auto& raw_trace : raw_collection.traces) {
-        // Pipeline order is fixed: calibration first, then reference subtraction.
+        // Object-derived corrections act on the completed preprocessing output.
         const auto calibrated = calibration_master_.apply_to_trace(raw_trace);
         const auto referenced = reference_master_.apply_to_trace(calibrated);
-        preprocessed.traces.push_back(apply_notch_filter(referenced, config_.preprocess.notch));
+        auto filtered = apply_notch_filter(referenced, config_.preprocess.notch);
+        object_calibration_.apply(filtered);
+        preprocessed.traces.push_back(std::move(filtered));
     }
 
     return preprocessed;

data_acq_and_processing/tests/native_regressions.cpp

@@ -1,5 +1,6 @@
 #include "capture_file_writer.h"
 #include "channel_bundle_support.hpp"
+#include "data_preprocessor.hpp"
 #include "locator/tcp_server.hpp"
 #include "processing_live_config.hpp"
 #include "runtime_wait.hpp"
@@ -16,6 +17,7 @@
 #include <atomic>
 #include <chrono>
 #include <cstring>
+#include <exception>
 #include <filesystem>
 #include <fstream>
 #include <iostream>
@@ -60,11 +62,23 @@ struct Workspace {
 };
 
 struct RingName {
-    std::string name = "/radar_native_test_" + std::to_string(::getpid());
+    std::string name;
-    RingName() { ipc::ShmRing::unlink_ring(name); }
+    explicit RingName(const std::string& suffix = {})
+        : name("/radar_native_test_" + std::to_string(::getpid()) + suffix) {
+        ipc::ShmRing::unlink_ring(name);
+    }
     ~RingName() { ipc::ShmRing::unlink_ring(name); }
 };
 
+auto save_bundle(const Workspace& workspace, const char* name, const ipc::RawSweepCollection& collection)
+    -> std::string {
+    const auto path = workspace.path / name;
+    const auto bytes = ipc::serialize_raw_collection(collection);
+    std::ofstream(path, std::ios::binary).write(
+        reinterpret_cast<const char*>(bytes.data()), static_cast<std::streamsize>(bytes.size()));
+    return path.string();
+}
+
 void write_u32(std::vector<std::uint8_t>& bytes, std::size_t offset, std::uint32_t value) {
     require(offset + sizeof(value) <= bytes.size(), "invalid test offset");
     std::memcpy(bytes.data() + offset, &value, sizeof(value));
@@ -137,6 +151,22 @@ void test_configuration(const std::string& seed_path, const Workspace& workspace
     const auto save = [&](const Json& config) { std::ofstream(config_path) << config; };
     save(seed);
     const auto config = config::load_run_config(config_path.string());
+    auto with_object_calibration = seed;
+    with_object_calibration["preprocess"]["s21"]["object_calibration"] =
+        Json{{"set_name", "reflector"}, {"bundle_path", "corrections.bin"}};
+    save(with_object_calibration);
+    const auto selected = config::load_run_config(config_path.string()).preprocess.s21.object_calibration;
+    require(selected.set_name == "reflector" && selected.bundle_path == "corrections.bin",
+        "object calibration asset did not load");
+    with_object_calibration["preprocess"]["s21"].erase("object_calibration");
+    save(with_object_calibration);
+    require(config::load_run_config(config_path.string()).preprocess.s21.object_calibration.bundle_path.empty(),
+        "absent object calibration was not disabled");
+    for (const auto& invalid_asset : {Json(nullptr), Json{{"bundle_path", true}}}) {
+        with_object_calibration["preprocess"]["s21"]["object_calibration"] = invalid_asset;
+        save(with_object_calibration);
+        expect_error([&] { (void)config::load_run_config(config_path.string()); });
+    }
     for (const auto& [pointer, value] : std::array<std::pair<const char*, double>, 8>{{
         {"/radar/sweep/start_hz", -1}, {"/radar/sweep/stop_hz", 1e100},
         {"/radar/sweep/if_bandwidth_hz", 0}, {"/radar/sweep/points", 0},
@@ -297,12 +327,8 @@ void test_csv_failures(const Workspace& workspace) {
 
 void test_asset_reload_preserves_data(const Workspace& workspace) {
     const auto save = [&](const char* name, float sample) {
-        const auto path = workspace.path / name;
+        return save_bundle(workspace, name, {.traces = {
-        const auto bytes = ipc::serialize_raw_collection({.traces = {
             {.frequency_hz = {1}, .s11 = {{sample, 0}}, .s21 = {{sample, 0}}}}});
-        std::ofstream(path, std::ios::binary).write(
-            reinterpret_cast<const char*>(bytes.data()), static_cast<std::streamsize>(bytes.size()));
-        return path.string();
     };
     const auto open = save("open.bin", 1);
     const auto short_standard = save("short.bin", -1);
@@ -328,6 +354,105 @@ void test_asset_reload_preserves_data(const Workspace& workspace) {
         "failed OSL reload lost previous calibration");
 }
 
+void test_object_calibration(const Workspace& workspace) {
+    const ipc::SweepTraceBlock first{.combo = {7, 3}, .frequency_hz = {1e9F, 2e9F},
+        .s11 = {{1, 2}, {3, 4}}, .s21 = {{2, 3}, {4, 5}}, .capture_start_ns = 5, .capture_end_ns = 15};
+    const ipc::SweepTraceBlock second{.combo = {1, 9}, .frequency_hz = {3e9F, 4e9F, 5e9F},
+        .s11 = {{}, {}, {}}, .s21 = {{6, 7}, {8, 9}, {10, 11}}};
+    auto factors_first = first;
+    factors_first.s21 = {{0, 2}, {2, 0}};
+    auto factors_second = second;
+    factors_second.s21 = {{1, -1}, {-1, 0}, {0, 1}};
+    preprocessing::S21ObjectCalibrationBundle correction;
+    auto trace = first;
+    correction.apply(trace);
+    require(ipc::serialize_raw_collection({.traces = {trace}}) == ipc::serialize_raw_collection({.traces = {first}}),
+        "disabled object calibration changed a trace");
+    correction.load(save_bundle(workspace, "object.bin", {.traces = {factors_second, factors_first}}));
+    correction.validate_combos({first.combo, second.combo});
+    expect_error([&] { correction.validate_combos({{0, 0}}); });
+    for (auto invalid : {first, second}) {
+        invalid.combo = {0, 0};
+        expect_error([&] { correction.apply(invalid); });
+    }
+    auto mismatch = second;
+    mismatch.frequency_hz[1] += 1e8F;  // Same endpoints and count; interior grid differs.
+    expect_error([&] { correction.apply(mismatch); });
+    mismatch = second;
+    mismatch.s21.pop_back();
+    expect_error([&] { correction.apply(mismatch); });
+    auto nonfinite = factors_first;
+    nonfinite.s21[0].re = std::numeric_limits<float>::quiet_NaN();
+    expect_error([&] { correction.load(save_bundle(workspace, "object_nan.bin", {.traces = {nonfinite}})); });
+    expect_error([&] { correction.load(save_bundle(workspace, "object_duplicate.bin", {.traces = {factors_first, factors_first}})); });
+    auto expected = first;
+    expected.s21 = {{-6, 4}, {8, 10}};
+    trace = first;
+    correction.apply(trace);
+    require(ipc::serialize_raw_collection({.traces = {trace}}) == ipc::serialize_raw_collection({.traces = {expected}}),
+        "object calibration changed S11, timing, pair identity, or multiplication after a failed reload");
+    trace = second;
+    correction.apply(trace);
+    require(trace.s21[0].re == 13 && trace.s21[0].im == 1 && trace.s21[1].re == -8 && trace.s21[1].im == -9 &&
+            trace.s21[2].re == -11 && trace.s21[2].im == 10, "object calibration mixed pairs or frequency grids");
+    trace = first;
+    trace.s21[0] = {std::numeric_limits<float>::max(), std::numeric_limits<float>::max()};
+    expect_error([&] { correction.apply(trace); });
+    correction.load("");
+    trace = first;
+    correction.apply(trace);
+    require(trace.s21[0].re == 2 && trace.s21[0].im == 3, "clearing object calibration left stale factors");
+}
+
+void test_object_calibration_pipeline(const Workspace& workspace) {
+    const ipc::SweepTraceBlock trace{.combo = {7, 3}, .frequency_hz = {1e9F, 2e9F},
+        .s11 = {{7, 3}, {8, 4}}, .s21 = {{2, 4}, {6, 8}}, .capture_start_ns = 5, .capture_end_ns = 15};
+    auto standard = trace;
+    standard.s21 = {{2, 0}, {2, 0}};
+    auto reference = trace;
+    reference.s21 = {{1, 2}, {2, 2}};
+    auto factors = trace;
+    factors.s21 = {{0, 2}, {5, 1}};
+    preprocessing::CalibrationMaster calibration(preprocessing::make_s21_through_calibrator());
+    calibration.load_s21_calibration_bundle(save_bundle(workspace, "pipeline_through.bin", {.traces = {standard}}));
+    preprocessing::ReferenceMaster references;
+    references.load_s21_reference_bundle(save_bundle(workspace, "pipeline_reference.bin", {.traces = {reference}}));
+    references.prepare_calibrated(calibration, {trace.combo});
+    config::RunConfig config;
+    config.run_combos = {trace.combo};
+    config.preprocess.s21.object_calibration.bundle_path =
+        save_bundle(workspace, "pipeline_object.bin", {.traces = {factors}});
+    config.preprocess.notch = {.enabled = true, .bands_hz = {{2e9F, 2e9F}}, .taper_type = "hard"};
+    RingName raw_name("_object_raw"), pre_name("_object_pre");
+    auto raw_ring = ipc::ShmRing::open_or_create(raw_name.name, 2, 4096);
+    auto pre_ring = ipc::ShmRing::open_or_create(pre_name.name, 2, 4096);
+    preprocessing::DataPreprocessor preprocessor(config, calibration, references, raw_ring, pre_ring);
+    require(raw_ring.push(ipc::serialize_raw_collection({.collection_id = 41, .capture_start_ns = 5,
+        .capture_end_ns = 15, .traces = {trace}})), "test raw ring could not hold a sweep");
+    std::atomic<bool> stop{false};
+    std::exception_ptr error;
+    std::jthread worker([&] { try { preprocessor.run(stop); } catch (...) { error = std::current_exception(); } });
+    std::vector<std::uint8_t> bytes;
+    const auto deadline = std::chrono::steady_clock::now() + std::chrono::seconds(2);
+    while (bytes.empty() && std::chrono::steady_clock::now() < deadline) {
+        (void)pre_ring.pop(bytes);
+        std::this_thread::sleep_for(std::chrono::milliseconds(1));
+    }
+    stop.store(true);
+    worker.join();
+    if (error) { std::rethrow_exception(error); }
+    require(!bytes.empty(), "object-corrected preprocessed collection was not published");
+    const auto result = ipc::deserialize_preprocessed_collection(bytes);
+    const auto& output = result.traces.at(0);
+    require(result.collection_id == 41 && result.capture_start_ns == 5 && result.capture_end_ns == 15 &&
+            output.combo == trace.combo && output.capture_start_ns == 5 && output.capture_end_ns == 15,
+        "object calibration lost capture identity or timing");
+    require(output.s21[0].re == -2 && output.s21[0].im == 1 && output.s21[1].re == 0 && output.s21[1].im == 0,
+        "object calibration ran before existing preprocessing or was applied more than once");
+    require(output.s11[0].re == 7 && output.s11[0].im == 3 && output.s11[1].re == 0 && output.s11[1].im == 0,
+        "object calibration changed S11 or bypassed the notch filter");
+}
+
 void test_locator_packet_errors() {
     int sockets[2]{};
     require(::socketpair(AF_UNIX, SOCK_STREAM, 0, sockets) == 0, "socketpair failed");
@@ -384,6 +509,8 @@ int main(int argc, char** argv) {
         test_wire_decoders();
         test_configuration(argv[1], workspace);
         test_asset_reload_preserves_data(workspace);
+        test_object_calibration(workspace);
+        test_object_calibration_pipeline(workspace);
         test_ring();
         test_partial_driver_open();
         test_interruptible_wait();

mimo_calibration.py

@@ -1,8 +1,8 @@
 #!/usr/bin/env python3
 """Фазовая калибровка MIMO-радара по точечному отражателю (шару) и применение её к данным.
 
-Расчёт тот же, что в MIMO_calibration.ipynb, без графиков и диагностики. Формат файлов
+Пример использует общий расчёт с интерфейсом программы. Формат файлов калибровки
-калибровки (cal_*.npy, cal_meta.json) и папки postprocessed — тот же.
+(cal_*.npy, cal_meta.json) и папки postprocessed сохранён.
 
 Запуск целиком:  python mimo_calibration.py   (работает по параметрам из блока ниже)
 Из другого кода:
@@ -13,19 +13,14 @@
     s21_corr = mc.apply_calibration(s21, freq, cal)        # массив (TX, RX, Nf) в памяти
     mc.apply_to_measurement(meas_dir, cal)                 # preprocessed -> postprocessed
 """
-import datetime
-import json
-import re
-import shutil
-from dataclasses import dataclass
 from pathlib import Path
+from statistics import mean
 
-import numpy as np
+from python_app.workflows.mimo_calibration import (
-from scipy.optimize import minimize
+    Settings, apply_calibration, apply_to_measurement, calibration_on_grid,
-
+    compute_calibration, find_config_profile, load_calibration, load_geometry,
-# ╔══════════════════════════════════════════════════════════════════════════════════════╗
+    load_s21, save_calibration,
-# ║                                 ЗАДАВАЕМЫЕ ПАРАМЕТРЫ                                 ║
+)
-# ╚══════════════════════════════════════════════════════════════════════════════════════╝
 
 # --- что делать -------------------------------------------------------------------------
 RUN_CALIBRATION = True       # True -> посчитать калибровку по CAL_SETS и записать в CAL_DIR;
@@ -43,17 +38,14 @@ APPLY_TO_DATA = False        # True -> записать исправленные
 CAL_ROOT = Path('/Users/ivan_root/Downloads/Telegram_dwnld/2026-09-31 balls calib/'
                 'librevna_multi_0.5-6GHz_1031pts_-3dBm_big_ball_h_0cm_z_5m_x_0cm/preprocessed')
 CAL_SETS = [
-    dict(path=CAL_ROOT, snapshots=['0000'], target_scene_m=(0.0, 0.16, 5.20)), # Здесь нужно указывать координаты, измернные
+    dict(path=CAL_ROOT, snapshots=[f'{index:04d}'], target_scene_m=(0.0, 0.16, 5.20))
-    dict(path=CAL_ROOT, snapshots=['0001'], target_scene_m=(0.0, 0.16, 5.20)), # в системе координат земли (x,y,z)
+    for index in range(5)
-    dict(path=CAL_ROOT, snapshots=['0002'], target_scene_m=(0.0, 0.16, 5.20)), # X - поеперчная координата от центра радара
+]
-    dict(path=CAL_ROOT, snapshots=['0003'], target_scene_m=(0.0, 0.16, 5.20)), # y - выота от поверхности земли
-    dict(path=CAL_ROOT, snapshots=['0004'], target_scene_m=(0.0, 0.16, 5.20)), # z - длина вдоль земли от вертикальной плоскости, про
-]                                                                              # проходящей через нижние антенны до центра шара (до переднего края + радиус)
 SPHERE_RADIUS_M = 0.16       # радиус шара-отражателя [м]; 0 -> точечная цель
 EMPTY_SCENE_PATH = Path('/Users/ivan_root/Downloads/Telegram_dwnld/2026-09-31 balls calib/'
                         'librevna_multi_0.5-6GHz_1031pts_-3dBm_bkgd_h_0cm/preprocessed')
-                             # папка снимков той же сцены БЕЗ отражателя (вычитается их среднее);
+                             # Дополнительная пустая сцена для архивного примера.
-                             # None -> без вычитания
+                             # Если референс уже удалил фон, задайте None.
 
 # --- геометрия (как в софте построения изображений) ---------------------------------------
 INPUT_IDX = [0, 1, 2, 3]     # физические входы  (Rx), input_pos
@@ -87,449 +79,18 @@ APPLY_TO_MEASUREMENTS = [
 OVERWRITE_POSTPROCESSED = False  # True -> пересоздать postprocessed (только созданный этой калибровкой:
                                  # папка без calibration_applied.json не удаляется никогда)
 
-# ╔══════════════════════════════════════════════════════════════════════════════════════╗
+def main() -> None:
-# ║                               КОНЕЦ ЗАДАВАЕМЫХ ПАРАМЕТРОВ                              ║
-# ╚══════════════════════════════════════════════════════════════════════════════════════╝
-
-C_LIGHT = 299_792_458.0
-
-
-@dataclass
-class Settings:
-    """Настройки расчёта; значения по умолчанию — из блока параметров выше."""
-    sphere_radius_m: float = SPHERE_RADIUS_M
-    input_idx: tuple = tuple(INPUT_IDX)
-    output_idx: tuple = tuple(OUTPUT_IDX)
-    antenna_height_m: float = ANTENNA_HEIGHT_M
-    pitch_deg: float = PITCH_DEG
-    f_min: float = CAL_F_MIN
-    f_max: float = CAL_F_MAX
-    gate_half_m: float = GATE_HALF_M
-    gate_taper_m: float = GATE_TAPER_M
-    coarse_range_search_m: float = COARSE_RANGE_SEARCH_M
-    refine_axes: tuple = tuple(REFINE_AXES)
-    refine_range_m: float = REFINE_RANGE_M
-    apply_amplitude: bool = APPLY_AMPLITUDE
-    phase_model: str = PHASE_MODEL
-
-
-# ══════════════════════════════════════════════════════
-# ЗАГРУЗКА
-# ══════════════════════════════════════════════════════
-def find_config_profile(start, max_levels=8):
-    p = Path(start)
-    for _ in range(max_levels):
-        if (p / 'config_profile.json').exists():
-            return p / 'config_profile.json'
-        p = p.parent
-    raise FileNotFoundError(f'config_profile.json не найден выше {start}')
-
-
-def load_geometry(config_path, input_idx, output_idx):
-    """Координаты антенн в осях радара [м], массивы (N,3) в порядке сортировки физических портов."""
-    gpr = json.load(open(config_path, encoding='utf-8'))['gpr']
-    tx = {int(e['output_pos']): (e['x_m'], e.get('y_m', 0.0), e.get('z_m', 0.0)) for e in gpr['tx_geometry']}
-    rx = {int(e['input_pos']): (e['x_m'], e.get('y_m', 0.0), e.get('z_m', 0.0)) for e in gpr['rx_geometry']}
-    return (np.array([tx[k] for k in sorted(output_idx)], float),
-            np.array([rx[k] for k in sorted(input_idx)], float))
-
-
-def list_snapshots(root, prefixes=None):
-    dirs = sorted(p for p in Path(root).iterdir() if p.is_dir() and (p / 'meta.json').exists())
-    if prefixes is None:
-        return dirs
-    out = [d for d in dirs if any(d.name.startswith(str(pr)) for pr in prefixes)]
-    if len(out) != len(prefixes):
-        raise FileNotFoundError(f'В {root} найдены не все снимки {prefixes}')
-    return out
-
-
-def load_s21(snapshot_dir, input_idx, output_idx):
-    """S21 (TX, RX, Nf) и частоты. Индексы — порядок сортировки физических портов."""
-    s21, freq = None, None
-    for a, o in enumerate(sorted(output_idx)):
-        for b, i in enumerate(sorted(input_idx)):
-            s = np.load(Path(snapshot_dir) / f'i{i}_o{o}_s21.npy')
-            f = np.load(Path(snapshot_dir) / f'i{i}_o{o}_freq.npy')
-            if s21 is None:
-                s21 = np.zeros((len(output_idx), len(input_idx), s.size), complex); freq = f
-            elif not np.allclose(f, freq):
-                raise ValueError(f'Разные частотные сетки у пар в {snapshot_dir}')
-            s21[a, b] = s
-    return s21, freq
-
-
-# ══════════════════════════════════════════════════════
-# РАСЧЁТ КАЛИБРОВКИ
-# ══════════════════════════════════════════════════════
-def best_phases(Z):
-    """max |Σ Z_ij·e^{-j(t_i+r_j)}| по фазам антенн, t_0 = r_0 = 0."""
-    t = np.zeros(Z.shape[0]); r = np.zeros(Z.shape[1])
-    for _ in range(100):
-        t = np.angle((Z * np.exp(-1j * r)[None, :]).sum(axis=1))
-        r = np.angle((Z * np.exp(-1j * t)[:, None]).sum(axis=0))
-        t = t - t[0]; r = r - r[0]
-    return t, r
-
-
-def coherence(Z, t=None, r=None):
-    """Сфазированность вкладов пар: |Σ| / Σ|·| (1 — все в фазе)."""
-    if t is not None:
-        Z = Z * np.exp(-1j * (t[:, None] + r[None, :]))
-    return float(np.abs(Z.sum()) / (np.abs(Z).sum() + 1e-30))
-
-
-def circular_median(phases):
-    """Круговая медиана по первой оси: значение с минимальной суммой угловых расстояний до остальных."""
-    d = np.abs(np.angle(np.exp(1j * (phases[:, None] - phases[None, :]))))
-    best = np.argmin(d.sum(axis=1), axis=0)
-    return np.take_along_axis(phases, best[None], axis=0)[0]
-
-
-def combine(sets):
-    """Добавки антенн по всем калибровочным точкам: круговая медиана фаз и медиана усиления."""
-    out = []
-    for key in ('T', 'R'):
-        Z = np.array([s[key] for s in sets])                      # (точки, антенны, частоты)
-        out.append(np.exp(np.median(np.log(np.abs(Z)), axis=0)) * np.exp(1j * circular_median(np.angle(Z))))
-    return tuple(out)
-
-
-class _Estimator:
-    """Геометрия, полоса и окно одной калибровки."""
-
-    def __init__(self, st, tx, rx, freq):
-        self.st, self.tx, self.rx, self.freq = st, tx, rx, freq
-        self.n_tx, self.n_rx = len(tx), len(rx)
-        self.band = (freq >= st.f_min) & (freq <= st.f_max)
-        self.fb = freq[self.band]
-        self.win = np.hanning(self.fb.size)
-        self.ok = self.win > 0.2                                  # края полосы после деления на окно ненадёжны
-        self.nfft = 1 << int(np.ceil(np.log2(self.fb.size * 8)))
-        self.dpath = np.fft.fftfreq(self.nfft, self.fb[1] - self.fb[0]) * C_LIGHT     # ось «лишний путь», м
-        self.gate = np.clip(np.minimum((self.dpath + st.gate_half_m) / st.gate_taper_m,
-                                       (st.gate_half_m - self.dpath) / st.gate_taper_m) + 0.5, 0, 1)
-
-    def scene_to_radar(self, q):
-        """(X, Y над землёй, Z вдоль земли) -> оси радара (x, y, z)."""
-        p = np.radians(self.st.pitch_deg); y0 = q[1] - self.st.antenna_height_m
-        return np.array([q[0], y0 * np.cos(p) + q[2] * np.sin(p), -y0 * np.sin(p) + q[2] * np.cos(p)])
-
-    def pair_paths(self, q_scene):
-        """Бистатический путь каждой пары до цели (TX, RX). Для шара радиуса a (q_scene — центр)
-        путь короче на 2a·cos(beta/2), beta — угол между направлениями из центра на Tx и на Rx."""
-        a = self.st.sphere_radius_m
-        pr = self.scene_to_radar(np.asarray(q_scene, float))
-        vt = self.tx - pr; vr = self.rx - pr
-        dt = np.linalg.norm(vt, axis=1); dr = np.linalg.norm(vr, axis=1)
-        paths = dt[:, None] + dr[None, :]
-        if a:
-            cos_beta = (vt @ vr.T) / (dt[:, None] * dr[None, :])
-            paths = paths - 2 * a * np.sqrt((1 + cos_beta) / 2)
-        return paths
-
-    def _unwound(self, s21_band, paths):
-        return s21_band * np.exp(2j * np.pi * self.fb[None, None, :] * paths[:, :, None] / C_LIGHT)
-
-    def target_echo(self, s21_band, paths):
-        """Эхо цели E (TX, RX, Nb) со снятым путём: окно ±gate_half_m вокруг заданной точки."""
-        h = np.fft.ifft(self._unwound(s21_band, paths) * self.win, self.nfft, axis=2)
-        return np.fft.fft(h * self.gate, axis=2)[:, :, :self.fb.size] / np.maximum(self.win, 1e-3)
-
-    def broadband(self, E):
-        """Вклад пары в изображение в точке: сумма эха по надёжной части полосы."""
-        return E[:, :, self.ok].sum(axis=2)
-
-    def coarse_range(self, s21, q_nominal):
-        """Грубая привязка по дальности: максимум суммарной огибающей всех пар в пределах
-        ±coarse_range_search_m по пути; заданная дальность Z сдвигается под него."""
-        q = q_nominal.copy()
-        if not self.st.coarse_range_search_m:
-            return q
-        s = np.mean(s21, axis=0)[:, :, self.band]; sel = np.abs(self.dpath) <= self.st.coarse_range_search_m
-        for _ in range(3):
-            env = np.abs(np.fft.ifft(self._unwound(s, self.pair_paths(q)) * self.win, self.nfft, axis=2)).sum(axis=(0, 1))
-            q[2] += self.dpath[sel][np.argmax(env[sel])] / 2
-        return q
-
-    def refine_target(self, s21, q0):
-        """Положение цели и широкополосные фазы антенн, максимизирующие сфазированность."""
-        P0 = self.pair_paths(q0)
-        E0 = np.mean([self.target_echo(s[:, :, self.band], P0) for s in s21], axis=0)
-        axes = [('xyz').index(a) for a in self.st.refine_axes]
-
-        def E_at(v):
-            q = q0.copy(); q[axes] += v
-            dP = self.pair_paths(q) - P0
-            return E0 * np.exp(2j * np.pi * self.fb[None, None, :] * dP[:, :, None] / C_LIGHT), q
-
-        def score(v, t, r):
-            if np.any(np.abs(v) > self.st.refine_range_m):
-                return 0.0
-            return coherence(self.broadband(E_at(v)[0]), t, r)
-
-        v = np.zeros(len(axes))
-        if axes:
-            for _ in range(6):
-                t, r = best_phases(self.broadband(E_at(v)[0]))
-                simplex = np.vstack([v] + [v + 0.03 * np.eye(len(axes))[k] for k in range(len(axes))])
-                v = minimize(lambda w: -score(w, t, r), v, method='Nelder-Mead',
-                             options=dict(xatol=5e-4, fatol=1e-7, initial_simplex=simplex)).x
-        return E_at(v)
-
-    def factorize(self, E):
-        """E_ij(f) ≈ g(f)·T_i(f)·R_j(f) на каждой частоте: фазы — best_phases, амплитуды — МНК по log|E|."""
-        nb = E.shape[2]
-        T = np.ones((self.n_tx, nb), complex); R = np.ones((self.n_rx, nb), complex)
-        L = np.log(np.abs(E) + 1e-30)
-        for k in range(nb):
-            t, r = best_phases(E[:, :, k])
-            tt = L[:, :, k].mean(axis=1) - L[:, :, k].mean(); rr = L[:, :, k].mean(axis=0) - L[:, :, k].mean()
-            T[:, k] = np.exp(tt + 1j * t); R[:, k] = np.exp(rr + 1j * r)
-        return T, R
-
-    def antenna_params(self, Z):
-        """Фаза, продолженная к 0 Гц, задержка (эквивалентный лишний путь) и усиление антенны."""
-        ph = np.unwrap(np.angle(Z[self.ok])); f = self.fb[self.ok]
-        slope, ph0 = np.polyfit(f, ph, 1)
-        return dict(phase0_deg=float(np.degrees(ph0)), delay_path_m=float(-slope * C_LIGHT / (2 * np.pi)),
-                    gain_db=float(20 * np.log10(np.mean(np.abs(Z[self.ok])))),
-                    phase_rms_after_linear_deg=float(np.degrees(np.std(ph - (slope * f + ph0)))))
-
-    def phase_model(self, Z):
-        """Фаза добавки антенны по модели phase_model (подгонка по надёжной части полосы)."""
-        model = self.st.phase_model
-        if model == 'raw':
-            return Z
-        ph = np.unwrap(np.angle(Z)); f = (self.fb - self.fb.mean()) / 1e9
-        if model == 'const':
-            u = np.exp(1j * np.angle(Z[self.ok])).mean()
-            return np.abs(Z) * np.exp(1j * np.angle(u))
-        deg = {'linear': 1, 'poly3': 3}.get(model)
-        if deg is None:
-            raise ValueError(f"phase_model должен быть 'const', 'linear', 'poly3' или 'raw', а не {model!r}")
-        return np.abs(Z) * np.exp(1j * np.polyval(np.polyfit(f[self.ok], ph[self.ok], deg), f))
-
-    def pair_correction(self, T, R):
-        """Поправка пары C_ij(f) = 1/(T_i·R_j); без apply_amplitude — только фаза."""
-        Z = T[:, None, :] * R[None, :, :]
-        return np.conj(Z) / np.abs(Z) if not self.st.apply_amplitude else 1.0 / Z
-
-    def to_full_grid(self, Z_band, params):
-        """На полную сетку частот: внутри надёжной полосы — оценка, вне её — продолжение с наклоном
-        линейной модели фазы антенны, пристыкованное к краю полосы без скачка."""
-        idx = np.flatnonzero(self.band)[self.ok]
-        ph_in = np.unwrap(np.angle(Z_band[self.ok])); mag_in = np.abs(Z_band[self.ok])
-        slope = -2 * np.pi * params['delay_path_m'] / C_LIGHT               # рад/Гц
-        ph = np.empty(self.freq.size); mag = np.empty(self.freq.size)
-        ph[idx] = ph_in; mag[idx] = mag_in
-        lo, hi = idx[0], idx[-1]
-        ph[:lo] = ph_in[0] + slope * (self.freq[:lo] - self.freq[lo]); mag[:lo] = mag_in[0]
-        ph[hi + 1:] = ph_in[-1] + slope * (self.freq[hi + 1:] - self.freq[hi]); mag[hi + 1:] = mag_in[-1]
-        return mag * np.exp(1j * ph)
-
-
-def compute_calibration(cal_sets, empty_scene_path=None, settings=None):
-    """Калибровка по набору измерений отражателя. Возвращает словарь в том же виде, что load_calibration."""
-    st = settings or Settings()
-    cal_sets = list(cal_sets)
-    config_path = find_config_profile(cal_sets[0]['path'])
-    tx, rx = load_geometry(config_path, st.input_idx, st.output_idx)
-
-    freq = None
-    empty = None
-    if empty_scene_path is not None:
-        loaded = [load_s21(d, st.input_idx, st.output_idx) for d in list_snapshots(empty_scene_path)]
-        empty = np.mean([s for s, _ in loaded], axis=0); freq = loaded[0][1]
-
-    sets = []
-    for n, cs in enumerate(cal_sets):
-        snaps = list_snapshots(cs['path'], cs.get('snapshots'))
-        data = []
-        for d in snaps:
-            s21, f = load_s21(d, st.input_idx, st.output_idx)
-            if freq is None:
-                freq = f
-            elif f.shape != freq.shape or not np.allclose(f, freq):
-                raise ValueError(f'Частотная сетка в {d} отличается от остальных калибровочных данных')
-            cfg = find_config_profile(d)
-            if cfg != config_path:
-                tx_d, rx_d = load_geometry(cfg, st.input_idx, st.output_idx)
-                if not (np.allclose(tx_d, tx) and np.allclose(rx_d, rx)):
-                    raise ValueError(f'Геометрия в {d} отличается от {config_path}')
-            data.append(s21 - empty if empty is not None else s21)
-        sets.append(dict(n=n, snaps=[d.name for d in snaps], s21=np.array(data),
-                         q_nominal=np.array(cs['target_scene_m'], float)))
-
-    est = _Estimator(st, tx, rx, freq)
-    for s in sets:
-        s['E'], s['q'] = est.refine_target(s['s21'], est.coarse_range(s['s21'], s['q_nominal']))
-        s['T'], s['R'] = est.factorize(s['E'])
-
-    T_all, R_all = combine(sets)
-    T_all = np.array([est.phase_model(z) for z in T_all]); R_all = np.array([est.phase_model(z) for z in R_all])
-    ant = {f'Tx{k}': est.antenna_params(T_all[k]) for k in range(est.n_tx)}
-    ant.update({f'Rx{k}': est.antenna_params(R_all[k]) for k in range(est.n_rx)})
-
-    # качество: сфазированность пар в точке цели без поправки и с ней
-    coh_with = lambda s, C: coherence(est.broadband(s['E'] * C))
-    quality = dict(coherence_before=[], coherence_own=[], coherence_leave_one_out=[], coherence_final=[])
-    for s in sets:
-        others = [o for o in sets if o is not s]
-        quality['coherence_before'].append(coh_with(s, 1.0))
-        quality['coherence_own'].append(coh_with(s, est.pair_correction(s['T'], s['R'])))
-        quality['coherence_leave_one_out'].append(coh_with(s, est.pair_correction(*combine(others))) if others else float('nan'))
-        quality['coherence_final'].append(coh_with(s, est.pair_correction(T_all, R_all)))
-
-    T_full = np.array([est.to_full_grid(T_all[k], ant[f'Tx{k}']) for k in range(est.n_tx)])
-    R_full = np.array([est.to_full_grid(R_all[k], ant[f'Rx{k}']) for k in range(est.n_rx)])
-    Z_full = T_full[:, None, :] * R_full[None, :, :]
-    unit = (lambda Z: np.conj(Z) / np.abs(Z)) if not st.apply_amplitude else (lambda Z: 1.0 / Z)
-    valid = np.zeros(freq.size, bool); valid[np.flatnonzero(est.band)[est.ok]] = True
-
-    meta = dict(
-        created=datetime.datetime.now().isoformat(timespec='seconds'), name=None,
-        convention=dict(apply='S21_corrected[tx, rx, f] = S21[tx, rx, f] * cal_pair[tx, rx, f]',
-                        index_order='tx = номер в cal_tx_output_pos (output_pos по возрастанию), rx = cal_rx_input_pos',
-                        files='S21 пары в данных: i{input_pos}_o{output_pos}_s21.npy',
-                        phase_reference='фазы относительно Tx0 и Rx0; общая фаза/задержка не входит',
-                        amplitude='выравнивается' if st.apply_amplitude else 'не меняется (только фаза)',
-                        outside_band='вне cal_valid: продолжение линейной моделью фазы антенны'),
-        geometry=dict(config=str(config_path), tx_xyz_m=tx.tolist(), rx_xyz_m=rx.tolist(),
-                      antenna_height_m=st.antenna_height_m, pitch_deg=st.pitch_deg),
-        estimation=dict(band_hz=[st.f_min, st.f_max], gate_half_m=st.gate_half_m, refine_axes=list(st.refine_axes),
-                        phase_model=st.phase_model, sphere_radius_m=st.sphere_radius_m, empty_scene=str(empty_scene_path)),
-        targets=[dict(path=str(cal_sets[s['n']]['path']), snapshots=s['snaps'], nominal_scene_m=s['q_nominal'].tolist(),
-                      refined_scene_m=s['q'].tolist()) for s in sets],
-        antennas=ant, quality=quality)
-    return dict(
-        freq_hz=freq.astype(np.float64),
-        pair=unit(Z_full).astype(np.complex64),             # (TX, RX, Nf): S21_corr = S21 * pair
-        tx=unit(T_full).astype(np.complex64),               # (TX, Nf): pair = tx[:,None] * rx[None,:]
-        rx=unit(R_full).astype(np.complex64),               # (RX, Nf)
-        valid=valid,                                        # (Nf,) True — внутри полосы калибровки
-        tx_output_pos=np.array(sorted(st.output_idx), np.int32),   # индекс -> физический выход
-        rx_input_pos=np.array(sorted(st.input_idx), np.int32),     # индекс -> физический вход
-        antenna_params=np.array([[np.radians(a['phase0_deg']), a['delay_path_m'], a['gain_db']] for a in ant.values()],
-                                np.float64),                # (TX+RX, 3): фаза к 0 Гц [рад], путь [м], усиление [дБ]
-        meta=meta, dir=None)
-
-
-# ══════════════════════════════════════════════════════
-# ФАЙЛЫ КАЛИБРОВКИ
-# ══════════════════════════════════════════════════════
-_CAL_ARRAYS = ('freq_hz', 'pair', 'tx', 'rx', 'valid', 'tx_output_pos', 'rx_input_pos', 'antenna_params')
-
-
-def save_calibration(cal, cal_dir, overwrite=False):
-    cal_dir = Path(cal_dir)
-    cal_dir.mkdir(parents=True, exist_ok=True)
-    existing = [p.name for p in cal_dir.glob('cal_*')]
-    if existing and not overwrite:
-        raise FileExistsError(f'В {cal_dir} уже есть файлы калибровки ({existing[:3]}...). '
-                              f'Задайте новое имя или overwrite=True.')
-    for k in _CAL_ARRAYS:
-        np.save(cal_dir / f'cal_{k}.npy', cal[k])
-    cal['meta']['name'] = cal_dir.name; cal['dir'] = cal_dir
-    json.dump(cal['meta'], open(cal_dir / 'cal_meta.json', 'w', encoding='utf-8'), ensure_ascii=False, indent=2)
-    return cal_dir
-
-
-def load_calibration(cal_dir):
-    cal_dir = Path(cal_dir)
-    cal = {k: np.load(cal_dir / f'cal_{k}.npy') for k in _CAL_ARRAYS}
-    cal['meta'] = json.load(open(cal_dir / 'cal_meta.json', encoding='utf-8'))
-    cal['dir'] = cal_dir
-    return cal
-
-
-# ══════════════════════════════════════════════════════
-# ПРИМЕНЕНИЕ
-# ══════════════════════════════════════════════════════
-def calibration_on_grid(cal, freq):
-    """Поправка пар (TX, RX, Nf) на частотной сетке freq. Совпадает с сеткой калибровки — берётся как есть;
-    иначе фаза и модуль поправок антенн интерполируются, вне сетки калибровки — линейная модель фазы."""
-    fc = cal['freq_hz']
-    if freq.shape == fc.shape and np.allclose(freq, fc):
-        return cal['pair']
-
-    def interp(Z, par):
-        ph = np.unwrap(np.angle(Z)); mag = np.abs(Z)
-        out_ph = np.interp(freq, fc, ph); out_mag = np.interp(freq, fc, mag)
-        lin = -(par[0] - 2 * np.pi * freq * par[1] / C_LIGHT)          # поправка = −добавка
-        outside = (freq < fc[0]) | (freq > fc[-1])
-        out_ph[outside] = lin[outside] + np.round((out_ph[outside] - lin[outside]) / (2 * np.pi)) * 2 * np.pi
-        return out_mag * np.exp(1j * out_ph)
-
-    n_tx = cal['tx'].shape[0]
-    tx = np.array([interp(cal['tx'][k], cal['antenna_params'][k]) for k in range(n_tx)])
-    rx = np.array([interp(cal['rx'][k], cal['antenna_params'][n_tx + k]) for k in range(cal['rx'].shape[0])])
-    return (tx[:, None, :] * rx[None, :, :]).astype(cal['pair'].dtype)
-
-
-def apply_calibration(s21, freq, cal):
-    """s21 (TX, RX, Nf) в порядке cal['tx_output_pos'] x cal['rx_input_pos'] -> исправленный массив."""
-    return s21 * calibration_on_grid(cal, np.asarray(freq))
-
-
-def apply_to_measurement(meas_dir, cal, overwrite=False):
-    """<измерение>/preprocessed -> <измерение>/postprocessed: S21 пар умножаются на поправку,
-    остальные файлы копируются. Возвращает (папка, снимков, исправлено S21, скопировано файлов)."""
-    meas_dir = Path(meas_dir); pre = meas_dir / 'preprocessed'; post = meas_dir / 'postprocessed'
-    if not pre.is_dir():
-        raise FileNotFoundError(f'Нет {pre}')
-    # калибровка годится только для той же сборки антенн
-    tx_m, rx_m = load_geometry(find_config_profile(pre), cal['rx_input_pos'].tolist(), cal['tx_output_pos'].tolist())
-    if not (np.allclose(tx_m, cal['meta']['geometry']['tx_xyz_m']) and np.allclose(rx_m, cal['meta']['geometry']['rx_xyz_m'])):
-        raise ValueError(f'Геометрия антенн в {meas_dir.name} отличается от геометрии калибровки — применять нельзя')
-    if post.exists():
-        if not overwrite:
-            raise FileExistsError(f'{post} уже существует. overwrite=True, чтобы пересоздать.')
-        if not (post / 'calibration_applied.json').exists():
-            raise FileExistsError(f'{post} существует, но создан не калибровкой (нет calibration_applied.json) — '
-                                  f'удалять не буду, разберитесь вручную.')
-        shutil.rmtree(post)
-    tx_of = {int(p): k for k, p in enumerate(cal['tx_output_pos'])}
-    rx_of = {int(p): k for k, p in enumerate(cal['rx_input_pos'])}
-    pat = re.compile(r'^i(\d+)_o(\d+)_s21\.npy$')
-    n_snap = n_fix = n_copy = 0
-    grid_cache = {}
-    post.mkdir()
-    for item in sorted(pre.iterdir()):
-        if item.is_file():
-            shutil.copy2(item, post / item.name); n_copy += 1
-            continue
-        out = post / item.name; out.mkdir(); n_snap += 1
-        for f in sorted(item.iterdir()):
-            m = pat.match(f.name)
-            if f.is_dir() or m is None or int(m.group(2)) not in tx_of or int(m.group(1)) not in rx_of:
-                if f.is_dir():
-                    shutil.copytree(f, out / f.name)
-                else:
-                    shutil.copy2(f, out / f.name)
-                n_copy += 1
-                continue
-            s21 = np.load(f); freq = np.load(item / f'i{m.group(1)}_o{m.group(2)}_freq.npy')
-            key = (freq.size, float(freq[0]), float(freq[-1]))
-            if key not in grid_cache:
-                grid_cache[key] = calibration_on_grid(cal, freq)
-            corr = grid_cache[key][tx_of[int(m.group(2))], rx_of[int(m.group(1))]]
-            np.save(out / f.name, (s21 * corr).astype(s21.dtype)); n_fix += 1
-    json.dump(dict(calibration=cal['meta']['name'], calibration_dir=str(Path(cal['dir']).resolve()),
-                   created=datetime.datetime.now().isoformat(timespec='seconds'), source=str(pre),
-                   rule='postprocessed i*_o*_s21 = preprocessed i*_o*_s21 * cal_pair[tx(o), rx(i)]; остальные файлы скопированы',
-                   frequency_grids=[list(k) for k in grid_cache]),
-              open(post / 'calibration_applied.json', 'w', encoding='utf-8'), ensure_ascii=False, indent=2)
-    return post, n_snap, n_fix, n_copy
-
-
-def main():
     if RUN_CALIBRATION:
-        cal = compute_calibration(CAL_SETS, EMPTY_SCENE_PATH, Settings())
+        cal = compute_calibration(CAL_SETS, EMPTY_SCENE_PATH, Settings(
+            sphere_radius_m=SPHERE_RADIUS_M, input_idx=tuple(INPUT_IDX), output_idx=tuple(OUTPUT_IDX),
+            antenna_height_m=ANTENNA_HEIGHT_M, pitch_deg=PITCH_DEG, f_min=CAL_F_MIN, f_max=CAL_F_MAX,
+            gate_half_m=GATE_HALF_M, gate_taper_m=GATE_TAPER_M, coarse_range_search_m=COARSE_RANGE_SEARCH_M,
+            refine_axes=tuple(REFINE_AXES), refine_range_m=REFINE_RANGE_M,
+            apply_amplitude=APPLY_AMPLITUDE, phase_model=PHASE_MODEL))
         save_calibration(cal, CAL_DIR, overwrite=OVERWRITE)
         q = cal['meta']['quality']
         print(f'Калибровка записана в {CAL_DIR}: сфазированность пар на отражателе '
-              f'{np.mean(q["coherence_before"]):.2f} -> {np.mean(q["coherence_final"]):.2f}')
+              f'{mean(q["coherence_before"]):.2f} -> {mean(q["coherence_final"]):.2f}')
     if APPLY_TO_DATA:
         cal = load_calibration(CAL_DIR)
         targets = APPLY_TO_MEASUREMENTS

python_app/gui/app_window.py

@@ -791,6 +791,9 @@ class AppWindow(
             # 0) Stop the GPIO button watcher so a late press cannot start work.
             self._stop_control_button_watcher()
             self._resume_pipeline_after_capture = False
+            controller = getattr(self, "_object_calibration_controller", None)
+            if controller is not None:
+                controller.shutdown()
             # 0) Drop the B-scan replay writer so a pending debounce cannot push into a
             # ring we are about to tear down.
             self._bscan_reprocess_timer.stop()

python_app/gui/controllers/app_window_config/live_processing_mixin.py

@@ -17,6 +17,7 @@ from PyQt6.QtWidgets import (
 
 from python_app.gui.runtime.constraints import validate_processing_mode_constraints
 from python_app.gui.antenna_geometry_editor import AntennaGeometryEditor
+from python_app.models.run_config_model import GprRxGeometryModel, GprTxGeometryModel
 from python_app.orchestration.live_processing_config import ProcessingLiveConfig
 
 _GPR_MODES = ("gpr", "legacy_gpr")
@@ -320,6 +321,10 @@ class AppWindowLiveProcessingMixin:
                 reprocess_current_result=not self._can_reprocess_history(),
             )
         )
+        active = getattr(self, "_active_run_config", None)
+        if active is not None and self._supervisor.is_running():
+            active.gpr.tx_geometry = [GprTxGeometryModel(**entry) for entry in self._gpr_tx_geometry_input.records()]
+            active.gpr.rx_geometry = [GprRxGeometryModel(**entry) for entry in self._gpr_rx_geometry_input.records()]
         if getattr(self, "_await_processing_revision", False):
             self._required_processing_revision = self._processing_settings_revision
 
@@ -379,6 +384,8 @@ class AppWindowLiveProcessingMixin:
             finally:
                 self._suppress_live_settings_handler = False
             self._sync_socket_speed_controls()
+            if {"tx_geometry", "rx_geometry"} & settings.keys():
+                self._invalidate_object_calibration_after_geometry_change()
             if {"tx_geometry", "rx_geometry", "relative_permittivity"} & settings.keys():
                 self._await_processing_revision = True
             if "processor_mode" in settings:
@@ -395,9 +402,49 @@ class AppWindowLiveProcessingMixin:
     def _on_gpr_geometry_changed(self) -> None:
         if getattr(self, "_suppress_live_settings_handler", False):
             return
+        self._invalidate_object_calibration_after_geometry_change()
         self._await_processing_revision = True
         self._on_processing_live_settings_changed()
 
+    def _invalidate_object_calibration_after_geometry_change(self) -> None:
+        """Disable a correction tied to another antenna layout and reload the preprocessor."""
+        selected = self._selected_preprocess_sets.get("s21_object_calibration", "")
+        was_running = self._supervisor.is_running()
+        active_config = getattr(self, "_active_run_config", None)
+        active = active_config.preprocess.s21.object_calibration.set_name if was_running and active_config else ""
+        if not selected and not active:
+            return
+        from python_app.workflows.mimo_calibration import validate_for_config
+
+        geometry = {"gpr": {
+            "tx_geometry": self._gpr_tx_geometry_input.records(),
+            "rx_geometry": self._gpr_rx_geometry_input.records(),
+        }}
+        selections = [(selected, self._selected_preprocess_radar_key)]
+        if active:
+            selections.append((active, self._radar_key(active_config)))
+        invalid = set()
+        for name, radar_key in dict.fromkeys(selections):
+            if not name:
+                continue
+            try:
+                validate_for_config(self._store.load_object_calibration(radar_key, name), geometry)
+            except Exception as exc:  # noqa: BLE001 - reject unavailable or incompatible saved corrections
+                invalid.add(name)
+                self._log_warning(f"Object calibration {name} disabled for changed antenna geometry: {exc}")
+        if not invalid:
+            return
+        resume_seq = getattr(self, "_stop_request_seq", 0) + 1
+        if active in invalid:
+            self._stop_run()
+        if selected in invalid:
+            self._selected_preprocess_sets["s21_object_calibration"] = ""
+            self._refresh_preprocess_summary_labels()
+            if self._preprocess_dialog is not None:
+                self._preprocess_dialog.set_selected_sets(self._selected_preprocess_sets, emit_signal=False)
+        if active in invalid and self._pipeline_resume_allowed(resume_seq):
+            self._start_run()
+
     def _on_processing_live_settings_changed(self, *_args) -> None:
         """Handle live-processing setting changes and trigger redraw when needed."""
         # Web-apply sets many widgets at once; their individual change signals are

python_app/gui/controllers/app_window_config/profile_io_mixin.py

@@ -4,6 +4,7 @@ from __future__ import annotations
 
 from collections import deque
 from contextlib import ExitStack
+from copy import deepcopy
 import json
 from pathlib import Path
 
@@ -23,12 +24,23 @@ from python_app.orchestration.preprocess_assets import (
 class AppWindowConfigProfileIOMixin:
     """Persist and restore full GUI profiles without restarting the app."""
 
-    def _write_gui_profile_to_path(self, output_path: Path, *, allow_overwrite: bool = True) -> GuiProfileModel:
+    def _write_gui_profile_to_path(
-        """Serialize current full GUI profile to `output_path` and return the persisted model."""
+        self, output_path: Path, *, allow_overwrite: bool = True, dataset: bool = False,
+    ) -> GuiProfileModel:
+        """Save UI settings, preserving the acquisition provenance for recorded data."""
         if not allow_overwrite and output_path.exists():
             raise FileExistsError(f"Config profile output already exists: {output_path}")
 
         profile = self._build_gui_profile()
+        active = getattr(self, "_active_run_config", None)
+        if dataset and active is not None:
+            profile.run_config.radar = deepcopy(active.radar)
+            profile.run_config.input_switch = deepcopy(active.input_switch)
+            profile.run_config.output_switch = deepcopy(active.output_switch)
+            profile.run_config.combos = deepcopy(active.combos)
+            profile.run_config.preprocess = deepcopy(active.preprocess)
+            profile.run_config.gpr.tx_geometry = deepcopy(active.gpr.tx_geometry)
+            profile.run_config.gpr.rx_geometry = deepcopy(active.gpr.rx_geometry)
         atomic_write_json(output_path, profile.to_dict(), durable=True)
         return profile
 
@@ -206,6 +218,9 @@ class AppWindowConfigProfileIOMixin:
         capture sequence or the pipeline is active — the operator must stop first.
         Shared by the desktop dialog and the web loader so both honor the same rule.
         """
+        if getattr(self, "_object_capture_job", None) is not None:
+            self._show_error("Wait for object-calibration capture to finish")
+            return False
         if self._capture_session is not None:
             self._show_error(
                 "Cannot load config during active capture sequence",

python_app/gui/controllers/app_window_pipeline_mixin.py

@@ -57,13 +57,16 @@ class AppWindowPipelineMixin:
         """Start acquisition in single-capture mode."""
         self._start_run(single_capture=True)
 
-    def _start_run(self, *, single_capture: bool = False) -> None:
+    def _start_run(self, *, single_capture: bool = False, config_override: RunConfigModel | None = None) -> None:
         """Start pipeline processes and ring readers."""
         if getattr(self, "_closing", False) or getattr(self, "_close_after_stop", False):
             return
         if getattr(self, "_stopping_run", False):
             self._show_error("Wait for pipeline shutdown before starting again")
             return
+        if config_override is None and getattr(self, "_object_capture_job", None) is not None:
+            self._show_error("Wait for object-calibration capture to finish")
+            return
         if self._capture_session is not None:
             self._show_error(
                 "Cannot start pipeline during active capture sequence",
@@ -88,7 +91,7 @@ class AppWindowPipelineMixin:
 
         try:
             processor_was_running = self._supervisor.is_processor_running()
-            config = self._build_config()
+            config = config_override.clone() if config_override is not None else self._build_config()
             validate_acquisition_config(config)
             run_signature = self._build_run_history_signature(config)
             processor_signature = self._build_processor_run_signature(config)
@@ -101,7 +104,8 @@ class AppWindowPipelineMixin:
             if not processor_was_running:
                 self._reset_runtime_history()
 
-            self._validate_processing_mode_constraints(config)
+            if config_override is None:
+                self._validate_processing_mode_constraints(config)
             radar_key = self._radar_key(config)
 
             missing_assets = [
@@ -145,14 +149,12 @@ class AppWindowPipelineMixin:
                 f"{', ' + combo_preview if combo_preview else ''}, radar_key={radar_key}"
             )
 
-            if not single_capture:
+            if self._history_run_signature is not None and self._history_run_signature != run_signature:
-                should_reset_history = (
+                if processor_was_running:
-                    self._history_run_signature is not None and self._history_run_signature != run_signature
-                )
-                if should_reset_history:
                     self._reset_runtime_history()
-                    self._log("History reset because run settings changed")
+                    self._write_live_processing_config(history_command="clear_all", bump_history_seq=True)
-                self._history_run_signature = run_signature
+                self._log("History reset because run settings changed")
+            self._history_run_signature = run_signature
 
             # Open the single-capture acquisition window BEFORE the producer can emit:
             # any collection the one-shot orchestrator publishes is then strictly newer
@@ -211,6 +213,9 @@ class AppWindowPipelineMixin:
 
     def _apply_radar_settings(self) -> None:
         """Apply current radar settings by preconfiguring native device."""
+        if getattr(self, "_object_capture_job", None) is not None:
+            self._show_error("Wait for object-calibration capture to finish")
+            return
         if self._capture_session is not None:
             self._show_error(
                 "Finish or abort capture sequence before applying radar settings",

python_app/gui/controllers/app_window_preprocess_mixin.py

@@ -5,6 +5,7 @@ from __future__ import annotations
 from PyQt6.QtCore import QTimer
 
 from python_app.gui.preprocess_dialog import PreprocessDialog
+from python_app.gui.controllers.object_calibration_controller import ObjectCalibrationController
 from python_app.gui.trace_png_export import export_trace_png
 from python_app.orchestration.preprocess_assets import (
     PREPROCESS_ASSET_SPECS,
@@ -124,6 +125,9 @@ class AppWindowPreprocessMixin:
         """Capture, save, and select a temporary S21 reference with current sweep settings."""
         if getattr(self, "_closing", False) or getattr(self, "_stopping_run", False):
             return
+        if getattr(self, "_object_capture_job", None) is not None:
+            self._show_error("Wait for object-calibration capture to finish")
+            return
         if self._capture_session is not None:
             self._show_error(
                 "Cannot capture tmp reference during active capture sequence",
@@ -227,6 +231,9 @@ class AppWindowPreprocessMixin:
         dialog.finalize_sequence_requested.connect(self._finalize_capture_sequence)
         dialog.abort_sequence_requested.connect(self._abort_capture_sequence)
         dialog.create_neutral_sets_requested.connect(self._create_neutral_sets)
+        self._object_calibration_controller = ObjectCalibrationController(self)
+        dialog.import_object_calibration_requested.connect(self._object_calibration_controller.import_calibration)
+        dialog.create_object_calibration_requested.connect(self._object_calibration_controller.open_creation)
         dialog.set_neutral_sets_visible(supports_neutral_preprocess_sets(self._defaults_config))
         dialog.set_radar_config_summary(
             directory_path=self._preprocess_radar_scan_summary.directory_path,
@@ -340,6 +347,9 @@ class AppWindowPreprocessMixin:
         """Start sequential capture session for requested preprocess asset."""
         if getattr(self, "_closing", False) or getattr(self, "_stopping_run", False):
             return
+        if getattr(self, "_object_capture_job", None) is not None:
+            self._show_error("Wait for object-calibration capture to finish")
+            return
         if self._capture_session is not None:
             self._show_error("Another capture sequence is already active", details=self._capture_state_details())
             return
@@ -410,6 +420,9 @@ class AppWindowPreprocessMixin:
         """Save neutral S21 calibration/reference sets for the current radar settings."""
         if getattr(self, "_closing", False) or getattr(self, "_stopping_run", False):
             return
+        if getattr(self, "_object_capture_job", None) is not None:
+            self._show_error("Wait for object-calibration capture to finish")
+            return
         if self._capture_session is not None:
             self._show_error(
                 "Cannot create neutral sets during active capture sequence",

python_app/gui/controllers/app_window_recording_mixin.py

@@ -71,6 +71,9 @@ class AppWindowRecordingMixin:
         path/name. Refuses to start a second recording while one is in progress, and
         reports a name clash up front (before any data is collected).
         """
+        if getattr(self, "_object_capture_job", None) is not None:
+            self._show_error("Wait for object-calibration capture to finish")
+            return
         if self._recording_active:
             self._show_error(
                 "A recording is already in progress; wait for it to finish before starting another",
@@ -100,7 +103,8 @@ class AppWindowRecordingMixin:
             )
             # Adjacent config profile, mirroring the manual save (fail if it clashes).
             self._write_gui_profile_to_path(
-                self._snapshot_config_profile_path(writer.directory), allow_overwrite=False
+                self._snapshot_config_profile_path(writer.directory), allow_overwrite=False,
+                dataset=self._supervisor.is_running(),
             )
         except Exception as exc:  # noqa: BLE001
             if writer is not None:
@@ -148,6 +152,14 @@ class AppWindowRecordingMixin:
                         shutil.rmtree(writer.directory)
                 self._log("Disk recording canceled because acquisition did not start")
                 return
+            try:
+                self._write_gui_profile_to_path(
+                    self._snapshot_config_profile_path(writer.directory), dataset=True,
+                )
+            except Exception as exc:  # noqa: BLE001 - keep any accepted data and the initial profile
+                self._finalize_recording_on_stop()
+                self._show_exception("Failed to update disk recording config profile", exc)
+                return
 
         self._log(f"Disk recording armed: streaming the next {target} measurement(s) to {writer.directory}")
 

python_app/gui/controllers/app_window_snapshot_mixin.py

@@ -41,6 +41,9 @@ class AppWindowSnapshotMixin:
 
     def _save_snapshot(self) -> None:
         """Save up to 1000 recent runtime measurements as a numpy snapshot."""
+        if getattr(self, "_object_capture_job", None) is not None:
+            self._show_error("Wait for object-calibration capture to finish")
+            return
         self._drain_runtime_rings_for_snapshot()
         if getattr(self, "_closing", False):
             return
@@ -100,7 +103,7 @@ class AppWindowSnapshotMixin:
             )
             config_profile_path = self._snapshot_config_profile_path(snapshot_dir)
             try:
-                self._write_gui_profile_to_path(config_profile_path, allow_overwrite=False)
+                self._write_gui_profile_to_path(config_profile_path, allow_overwrite=False, dataset=True)
             except Exception as exc:  # noqa: BLE001
                 self._show_error(
                     "Snapshot data was saved, but the adjacent config profile could not be written",
@@ -130,6 +133,9 @@ class AppWindowSnapshotMixin:
 
     def _save_vna_history_json(self) -> None:
         """Save one VNA-history JSON per available combo in runtime history."""
+        if getattr(self, "_object_capture_job", None) is not None:
+            self._show_error("Wait for object-calibration capture to finish")
+            return
         self._drain_runtime_rings_for_snapshot()
         if getattr(self, "_closing", False):
             return
@@ -164,7 +170,7 @@ class AppWindowSnapshotMixin:
             try:
                 # Snapshot and VNA JSON exports intentionally share the same output directory stem.
                 # Refresh the companion GUI profile in place so a prior dataset save does not block JSON export.
-                self._write_gui_profile_to_path(config_profile_path, allow_overwrite=True)
+                self._write_gui_profile_to_path(config_profile_path, allow_overwrite=True, dataset=True)
             except Exception as exc:  # noqa: BLE001
                 exported_preview = "\n".join(str(path) for path in output_paths[:8])
                 if len(output_paths) > 8:
@@ -212,6 +218,9 @@ class AppWindowSnapshotMixin:
 
     def _apply_runtime_history_deletion(self, *, remove_last_only: bool) -> None:
         """Apply destructive runtime-history deletion across readers, caches, and processor replay state."""
+        if getattr(self, "_object_capture_job", None) is not None:
+            self._show_error("Wait for object-calibration capture to finish")
+            return
         if self._capture_session is not None:
             self._show_error(
                 "Cannot modify runtime history during active capture sequence",

python_app/gui/controllers/object_calibration_capture.py

@@ -0,0 +1,140 @@
+"""Acquire fresh object-calibration sweeps through the existing native preprocessor."""
+
+from __future__ import annotations
+
+import time
+
+from PyQt6.QtCore import QObject, QTimer, pyqtSignal
+
+from python_app.models.dataset_model import SweepCollection
+from python_app.models.run_config_model import ComboModel
+
+
+class ObjectSweepCapture(QObject):
+    """Temporarily acquire the full antenna matrix without applying an object correction."""
+
+    finished = pyqtSignal()
+
+    def __init__(self, owner, dialog) -> None:
+        if getattr(owner, "_object_capture_job", None) is not None:
+            raise RuntimeError("Object-calibration capture is already in progress")
+        super().__init__(dialog)
+        owner._object_capture_job = self
+        self._owner = owner
+        self._dialog = dialog
+        self._timer = QTimer(self)
+        self._timer.timeout.connect(self._poll)
+        self._done = False
+        self._paused = False
+        self._started = False
+        self._resume = False
+        self._collections: list[SweepCollection] = []
+        self._seen: set[tuple[int, int]] = set()
+        self._stop_seq = getattr(owner, "_stop_request_seq", 0)
+        QTimer.singleShot(0, self._start)
+
+    def _start(self) -> None:
+        if self._done:
+            return
+        owner = self._owner
+        try:
+            if not owner._pipeline_resume_allowed(self._stop_seq):
+                self.cancel()
+                return
+            if getattr(owner, "_closing", False) or owner._capture_session is not None or owner._preprocess_capture_busy:
+                raise RuntimeError("Finish the active capture before taking object-calibration data")
+            if owner._single_capture_active or getattr(owner, "_recording_active", False):
+                raise RuntimeError("Finish the single capture or disk recording before taking calibration data")
+            self._config = owner._build_config()
+            if self._config.radar.replay.dataset_dir.strip():
+                raise RuntimeError("Object-calibration capture requires live acquisition; disable archive replay")
+            self._config.preprocess.s21.object_calibration.set_name = ""
+            self._config.preprocess.s21.object_calibration.bundle_path = ""
+            tx = sorted({entry.output_pos for entry in self._config.gpr.tx_geometry})
+            rx = sorted({entry.input_pos for entry in self._config.gpr.rx_geometry})
+            if not tx or not rx:
+                raise RuntimeError("Configure Tx/Rx antenna positions before taking calibration data")
+            self._config.combos = [ComboModel(input=i, output=o) for o in tx for i in rx]
+            self._count = owner._ensure_preprocess_dialog().median_sweep_count()
+            self._resume = owner._supervisor.is_running()
+            if self._resume:
+                self._paused = True
+                owner._stop_run()
+                self._stop_seq += 1
+                if not owner._pipeline_resume_allowed(self._stop_seq):
+                    self.cancel()
+                    return
+            self._source_config = self._config.to_dict()
+            self._start_ns = time.monotonic_ns()
+            owner._start_run(config_override=self._config)
+            self._started = owner._supervisor.is_running()
+            if not self._started:
+                raise RuntimeError("Calibration acquisition did not start; check the preprocessing sets and log")
+            self._dialog.set_status(f"Taking calibration data: 0 / {self._count} sweeps")
+            self._timer.start(50)
+        except Exception as exc:
+            self._finish(error=str(exc))
+
+    def _poll(self) -> None:
+        owner = self._owner
+        try:
+            if not owner._pipeline_resume_allowed(self._stop_seq):
+                self.cancel()
+                return
+            if not owner._supervisor.is_running():
+                raise RuntimeError("Calibration acquisition stopped before all sweeps were received")
+            for collection in owner._pre_history:
+                identity = (collection.collection_id, collection.monotonic_ns)
+                starts = [collection.capture_start_ns, *(trace.capture_start_ns for trace in collection.traces)]
+                acquired_ns = min((start for start in starts if start > 0), default=collection.monotonic_ns)
+                if acquired_ns < self._start_ns or identity in self._seen:
+                    continue
+                self._seen.add(identity)
+                self._collections.append(collection)
+                if len(self._collections) == self._count:
+                    self._finish()
+                    return
+            self._dialog.set_status(f"Taking calibration data: {len(self._collections)} / {self._count} sweeps")
+            if time.monotonic_ns() - self._start_ns > owner._SINGLE_CAPTURE_TIMEOUT_S * 1e9:
+                raise TimeoutError("Timed out waiting for preprocessed calibration sweeps")
+        except Exception as exc:
+            self._finish(error=str(exc))
+
+    def cancel(self) -> None:
+        """Cancel this capture and restore the previous acquisition when it is still allowed."""
+        self._finish(error="Calibration capture cancelled")
+
+    def _finish(self, *, error: str | None = None) -> None:
+        if self._done:
+            return
+        self._done = True
+        self._timer.stop()
+        owner = self._owner
+        resume_allowed = owner._pipeline_resume_allowed(self._stop_seq)
+        try:
+            if self._started and resume_allowed:
+                owner._stop_run()
+                self._stop_seq += 1
+            if not owner._pipeline_resume_allowed(self._stop_seq):
+                error = "Calibration capture cancelled"
+            if error is None:
+                self._dialog.add_capture(self._collections, self._source_config)
+            else:
+                self._dialog.set_status(error)
+        except Exception as exc:
+            self._dialog.set_status(f"Calibration capture failed: {exc}")
+        finally:
+            if getattr(owner, "_object_capture_job", None) is self:
+                owner._object_capture_job = None
+            if self._resume and (self._paused or self._started) and resume_allowed and owner._pipeline_resume_allowed(self._stop_seq):
+                owner._start_run()
+            self._dialog.set_capture_pending(False)
+            self.finished.emit()
+            self.deleteLater()
+
+
+def capture_object_sweeps(owner, dialog) -> ObjectSweepCapture:
+    """Start an asynchronous capture; the dialog receives sweeps or a visible error."""
+    capture = ObjectSweepCapture(owner, dialog)
+    dialog.set_capture_pending(True)
+    return capture

python_app/gui/controllers/object_calibration_controller.py

@@ -0,0 +1,183 @@
+"""GUI coordination for importing and estimating optional object calibration."""
+
+from __future__ import annotations
+
+import queue
+import threading
+from pathlib import Path
+
+from PyQt6.QtCore import QObject, QTimer
+from PyQt6.QtWidgets import QFileDialog
+
+from python_app.gui.object_calibration_dialog import ObjectCalibrationDialog
+
+
+def _calculate(groups, config, settings, cancelled, messages, result) -> None:
+    """The worker handles only Python data; every Qt action stays on the GUI thread."""
+    try:
+        from python_app.workflows.mimo_calibration import Settings, compute_from_collections
+
+        calibration = compute_from_collections(
+            groups, config, settings=Settings(**settings),
+            progress=messages.put, cancelled=cancelled.is_set,
+        )
+        result.put(("cancelled", None) if cancelled.is_set() else ("ready", calibration))
+    except InterruptedError:
+        result.put(("cancelled", None))
+    except Exception as exc:  # noqa: BLE001 - report worker failures on the GUI thread
+        result.put(("error", exc))
+
+
+class ObjectCalibrationController(QObject):
+    """Own one modeless editor and cancellable calculation for an AppWindow."""
+
+    def __init__(self, owner) -> None:
+        super().__init__(owner)
+        self._owner = owner
+        self._dialog: ObjectCalibrationDialog | None = None
+        self._capture = None
+        self._worker: threading.Thread | None = None
+        self._cancel = threading.Event()
+        self._messages: queue.Queue = queue.Queue()
+        self._result: queue.Queue = queue.Queue(maxsize=1)
+        self._poll = QTimer(self)
+        self._poll.setInterval(100)
+        self._poll.timeout.connect(self._poll_calculation)
+        self._save_name = ""
+
+    def import_calibration(self) -> None:
+        """Validate and copy a legacy cal_*.npy folder into the app's own store."""
+        if getattr(self._owner, "_closing", False):
+            return
+        if getattr(self._owner, "_object_capture_job", None) is not None or self._worker is not None:
+            self._owner._show_error("Wait for the object-calibration operation to finish")
+            return
+        panel = self._owner._ensure_preprocess_dialog()
+        name = panel.set_name()
+        if not name:
+            self._owner._show_error("Set name is required")
+            return
+        directory = QFileDialog.getExistingDirectory(panel, "Import MIMO calibration")
+        if not directory:
+            return
+        try:
+            from python_app.workflows.mimo_calibration import load_calibration, validate_for_config
+
+            config = self._owner._build_config()
+            calibration = load_calibration(Path(directory))
+            validate_for_config(calibration, config.to_dict())
+            radar_key = self._owner._radar_key(config)
+            self._owner._store.save_object_calibration(radar_key, name, calibration)
+            self._select_saved(name)
+            panel.set_status(f"Object calibration imported: {name}. Applies on the next Start.")
+        except Exception as exc:  # noqa: BLE001
+            self._owner._show_exception("Failed to import object calibration", exc)
+
+    def open_creation(self) -> None:
+        if getattr(self._owner, "_closing", False):
+            return
+        if self._dialog is None:
+            self._dialog = ObjectCalibrationDialog(self._owner._ensure_preprocess_dialog().set_name(), self._owner)
+            self._dialog.capture_requested.connect(self._capture_data)
+            self._dialog.calculate_requested.connect(self._start_calculation)
+            self._dialog.cancel_requested.connect(self.cancel)
+        self._dialog.show()
+        self._dialog.raise_()
+        self._dialog.activateWindow()
+
+    def _capture_data(self) -> None:
+        if (getattr(self._owner, "_closing", False) or self._capture is not None
+                or self._worker is not None or self._dialog is None):
+            return
+        from python_app.gui.controllers.object_calibration_capture import capture_object_sweeps
+
+        try:
+            self._capture = capture_object_sweeps(self._owner, self._dialog)
+            self._capture.finished.connect(self._capture_finished)
+        except Exception as exc:  # noqa: BLE001
+            self._dialog.set_capture_pending(False)
+            self._dialog.set_status(str(exc))
+            self._owner._show_exception("Failed to capture object-calibration data", exc)
+
+    def _capture_finished(self) -> None:
+        self._capture = None
+
+    def _start_calculation(self) -> None:
+        if getattr(self._owner, "_closing", False) or self._worker is not None or self._capture is not None or self._dialog is None:
+            return
+        try:
+            name = self._dialog.set_name()
+            if not name:
+                raise ValueError("Set name is required")
+            groups, config, settings = self._dialog.calculation_inputs()
+            self._save_name = name
+            self._cancel = threading.Event()
+            self._messages = queue.Queue()
+            self._result = queue.Queue(maxsize=1)
+            self._worker = threading.Thread(
+                target=_calculate,
+                args=(groups, config, settings, self._cancel, self._messages, self._result),
+                name="object-calibration", daemon=True,
+            )
+            self._dialog.set_calculating(True)
+            self._dialog.set_status("Расчёт калибровки…")
+            self._worker.start()
+            self._poll.start()
+        except Exception as exc:  # noqa: BLE001
+            self._worker = None
+            self._dialog.set_calculating(False)
+            self._dialog.set_status(f"Ошибка расчёта: {exc}")
+            self._owner._show_exception("Failed to calculate object calibration", exc)
+
+    def _poll_calculation(self) -> None:
+        if self._dialog is None or getattr(self._owner, "_closing", False):
+            self._poll.stop()
+            return
+        while not self._messages.empty():
+            self._dialog.set_status(self._messages.get_nowait())
+        try:
+            state, payload = self._result.get_nowait()
+        except queue.Empty:
+            return
+        self._poll.stop()
+        self._worker = None
+        self._dialog.set_calculating(False)
+        if self._cancel.is_set() or state == "cancelled":
+            self._dialog.set_status("Расчёт отменён. Снятые данные сохранены в этом окне.")
+            return
+        if state == "error":
+            self._dialog.set_status(f"Ошибка расчёта: {payload}")
+            self._owner._show_exception("Failed to calculate object calibration", payload)
+            return
+        try:
+            from python_app.workflows.mimo_calibration import validate_for_config
+
+            current_config = self._owner._build_config()
+            validate_for_config(payload, current_config.to_dict())
+            radar_key = self._owner._radar_key(current_config)
+            self._owner._store.save_object_calibration(radar_key, self._save_name, payload)
+            self._select_saved(self._save_name)
+            self._owner._ensure_preprocess_dialog().set_set_name(self._save_name)
+            self._dialog.show_calibration(payload)
+            self._dialog.set_status(f"Калибровка сохранена: {self._save_name}. Применится при следующем Start.")
+        except Exception as exc:  # noqa: BLE001
+            self._dialog.set_status(f"Калибровка не сохранена: {exc}")
+            self._owner._show_exception("Failed to save object calibration", exc)
+
+    def _select_saved(self, name: str) -> None:
+        self._owner._selected_preprocess_sets["s21_object_calibration"] = name
+        self._owner._refresh_sets()
+        self._owner._log(f"Selected object calibration: {name}")
+
+    def cancel(self) -> None:
+        self._cancel.set()
+        if self._capture is not None:
+            self._capture.cancel()
+        if self._worker is not None and self._dialog is not None:
+            self._dialog.set_status("Отмена расчёта…")
+
+    def shutdown(self) -> None:
+        self.cancel()
+        self._poll.stop()
+        if self._dialog is not None:
+            self._dialog.close()

python_app/gui/object_calibration_dialog.py

@@ -0,0 +1,293 @@
+"""Live reflector measurements and target-phase diagnostics for MIMO calibration."""
+
+from __future__ import annotations
+
+import copy
+import math
+
+import numpy as np
+import pyqtgraph as pg
+from PyQt6.QtCore import Qt, pyqtSignal
+from PyQt6.QtWidgets import (
+    QCheckBox, QComboBox, QDialog, QDoubleSpinBox, QFormLayout, QGroupBox,
+    QHBoxLayout, QHeaderView, QLabel, QLineEdit, QPushButton, QTableWidget, QTableWidgetItem,
+    QVBoxLayout, QWidget,
+)
+
+from python_app.models.dataset_model import SweepCollection
+
+
+class ObjectCalibrationDialog(QDialog):
+    """Collect full-matrix sweeps, then associate each group with measured XYZ."""
+
+    capture_requested = pyqtSignal()
+    calculate_requested = pyqtSignal()
+    cancel_requested = pyqtSignal()
+
+    def __init__(self, set_name: str, parent=None) -> None:
+        super().__init__(parent)
+        self.setWindowTitle("MIMO Object Calibration")
+        self.resize(1000, 850)
+        self._captures: list[dict] = []
+        self._config: dict | None = None
+        self._capture_pending = self._calculating = False
+        self._calibration: dict | None = None
+        layout = QVBoxLayout(self)
+        name_row = QHBoxLayout()
+        name_row.addWidget(QLabel("Set name", self))
+        self._set_name_input = QLineEdit(set_name, self)
+        name_row.addWidget(self._set_name_input)
+        layout.addLayout(name_row)
+        explanation = QLabel(
+            "Снимите данные, затем введите физически измеренные координаты центра отражателя: "
+            "X — поперёк, Y — высота над землёй, Z — вдоль земли. "
+            "Обычные S21-калибровка и выбранный референс уже применены; "
+            "существующая MIMO-поправка при съёмке отключена.", self,
+        )
+        explanation.setWordWrap(True)
+        layout.addWidget(explanation)
+        self._table = QTableWidget(0, 5, self)
+        self._table.setHorizontalHeaderLabels(["Набор", "Свипов", "X (м)", "Y (м)", "Z (м)"])
+        horizontal, vertical = self._table.horizontalHeader(), self._table.verticalHeader()
+        assert horizontal is not None and vertical is not None
+        horizontal.setSectionResizeMode(QHeaderView.ResizeMode.Stretch)
+        vertical.hide()
+        self._table.setSelectionBehavior(QTableWidget.SelectionBehavior.SelectRows)
+        self._table.itemChanged.connect(self._measurements_changed)
+        layout.addWidget(self._table)
+        actions = QHBoxLayout()
+        self._capture_button = QPushButton("Снять данные", self)
+        self._capture_button.clicked.connect(self.capture_requested.emit)
+        self._remove_button = QPushButton("Удалить выбранный набор", self)
+        self._remove_button.clicked.connect(self._remove_capture)
+        actions.addWidget(self._capture_button)
+        actions.addWidget(self._remove_button)
+        actions.addStretch(1)
+        layout.addLayout(actions)
+        self._settings: dict[str, QDoubleSpinBox | QCheckBox | QComboBox] = {}
+        form = QFormLayout()
+        for key, title, default, low, high in (
+            ("sphere_radius_m", "Радиус шара, м (0 — точка)", .16, 0, 100),
+            ("antenna_height_m", "Высота начала координат антенн над землёй, м", .92, 0, 100),
+            ("pitch_deg", "Наклон радара вниз, °", 10, -90, 90),
+        ):
+            form.addRow(title, self._number(key, default, low, high))
+        layout.addLayout(form)
+        advanced = QGroupBox("Параметры расчёта", self)
+        advanced.setFlat(True)
+        advanced.setCheckable(True)
+        advanced.setChecked(False)
+        advanced_layout = QVBoxLayout(advanced)
+        advanced_content = QWidget(advanced)
+        advanced_form = QFormLayout(advanced_content)
+        for key, title, default, low, high in (
+            ("f_min", "Нижняя частота оценки, МГц", 2000, 0, 100000),
+            ("f_max", "Верхняя частота оценки, МГц", 6000, 0, 100000),
+            ("gate_half_m", "Полуширина окна эха по пути, м", .15, .000001, 100),
+            ("gate_taper_m", "Плавный край окна, м", .03, .000001, 100),
+            ("coarse_range_search_m", "Грубый поиск по пути, ±м (0 — выкл.)", .6, 0, 100),
+            ("refine_range_m", "Уточнение координат, ±м", .1, 0, 100),
+        ):
+            advanced_form.addRow(title, self._number(key, default, low, high))
+        axes = QWidget(advanced_content)
+        axes_layout = QHBoxLayout(axes)
+        axes_layout.setContentsMargins(0, 0, 0, 0)
+        self._refine_axes = {}
+        for axis in "xyz":
+            checkbox = QCheckBox(axis.upper(), axes)
+            checkbox.setChecked(True)
+            checkbox.toggled.connect(self._measurements_changed)
+            self._refine_axes[axis] = checkbox
+            axes_layout.addWidget(checkbox)
+        advanced_form.addRow("Уточнять координаты", axes)
+        phase_model = QComboBox(advanced_content)
+        phase_model.addItems(["const", "linear", "poly3", "raw"])
+        phase_model.setCurrentText("linear")
+        phase_model.currentTextChanged.connect(self._measurements_changed)
+        self._settings["phase_model"] = phase_model
+        advanced_form.addRow("Модель фазы антенны", phase_model)
+        amplitude = QCheckBox("Выравнивать также амплитуды", advanced_content)
+        amplitude.toggled.connect(self._measurements_changed)
+        self._settings["apply_amplitude"] = amplitude
+        advanced_form.addRow(amplitude)
+        advanced_content.hide()
+        advanced.toggled.connect(advanced_content.setVisible)
+        advanced_layout.addWidget(advanced_content)
+        layout.addWidget(advanced)
+        self._target_combo = QComboBox(self)
+        self._target_combo.currentIndexChanged.connect(self._draw_phase_effect)
+        layout.addWidget(self._target_combo)
+        self._phase_plot = pg.PlotWidget(background="#0f141c", enableMenu=False)
+        self._phase_plot.setLabel("left", "Target phase relative to first pair", units="deg")
+        self._phase_plot.setLabel("bottom", "Tx / Rx pair")
+        self._phase_plot.showGrid(x=True, y=True, alpha=.2)
+        self._phase_plot.setMinimumHeight(220)
+        self._phase_plot.addLegend()
+        layout.addWidget(self._phase_plot)
+        self._quality_label = QLabel("Фазы вкладов пар появятся после расчёта.", self)
+        self._quality_label.setWordWrap(True)
+        layout.addWidget(self._quality_label)
+        self._status_label = QLabel("Готово к съёмке", self)
+        self._status_label.setWordWrap(True)
+        layout.addWidget(self._status_label)
+        footer = QHBoxLayout()
+        self._calculate_button = QPushButton("Рассчитать и сохранить", self)
+        self._calculate_button.clicked.connect(self.calculate_requested.emit)
+        self._cancel_button = QPushButton("Отменить операцию", self)
+        self._cancel_button.clicked.connect(self.cancel_requested.emit)
+        close_button = QPushButton("Закрыть", self)
+        close_button.clicked.connect(self.reject)
+        footer.addWidget(self._calculate_button)
+        footer.addWidget(self._cancel_button)
+        footer.addStretch(1)
+        footer.addWidget(close_button)
+        layout.addLayout(footer)
+        self._update_actions()
+
+    def _number(self, key: str, value: float, low: float, high: float) -> QDoubleSpinBox:
+        field = QDoubleSpinBox(self)
+        field.setDecimals(6)
+        field.setRange(low, high)
+        field.setSingleStep(100 if key in {"f_min", "f_max"} else .1 if key == "pitch_deg" else .01)
+        field.setValue(value)
+        field.valueChanged.connect(self._measurements_changed)
+        self._settings[key] = field
+        return field
+
+    def add_capture(self, collections: list[SweepCollection], config: dict) -> None:
+        """Freeze a captured group before the operator enters its target coordinates."""
+        if not collections:
+            raise ValueError("Не получены свипы отражателя")
+        if self._config is not None and any(
+            config.get(key) != self._config.get(key) for key in ("radar", "gpr", "preprocess")
+        ):
+            raise ValueError("Параметры радара, геометрия или препроцессинг изменились между наборами")
+        self._config = copy.deepcopy(config)
+        self._captures.append({"collections": copy.deepcopy(collections)})
+        row = self._table.rowCount()
+        self._table.insertRow(row)
+        for column, value in enumerate((str(row + 1), str(len(collections)), "", "", "")):
+            item = QTableWidgetItem(value)
+            if column < 2:
+                item.setFlags(item.flags() & ~Qt.ItemFlag.ItemIsEditable)
+            self._table.setItem(row, column, item)
+        self._table.setCurrentCell(row, 2)
+        self.set_status("Данные сняты. Введите координаты центра отражателя для нового набора.")
+        self._update_actions()
+
+    def calculation_inputs(self) -> tuple[list[dict], dict, dict]:
+        """Validate XYZ after capture; expose a frozen recipe to the worker."""
+        if not self._captures or self._config is None:
+            raise ValueError("Сначала снимите данные отражателя")
+        groups = []
+        for row, capture in enumerate(self._captures):
+            try:
+                coordinates = []
+                for column in (2, 3, 4):
+                    item = self._table.item(row, column)
+                    assert item is not None
+                    coordinates.append(float(item.text().strip()))
+                target = tuple(coordinates)
+            except ValueError as exc:
+                raise ValueError(f"Введите X, Y и Z центра отражателя для набора {row + 1}") from exc
+            if not all(math.isfinite(value) for value in target):
+                raise ValueError(f"Координаты набора {row + 1} должны быть конечными числами")
+            groups.append({**capture, "target_scene_m": target})
+        settings: dict[str, float | bool | str | tuple[str, ...] | tuple[int, ...]] = {
+            key: field.value() * (1e6 if key in {"f_min", "f_max"} else 1) if isinstance(field, QDoubleSpinBox) else
+            field.isChecked() if isinstance(field, QCheckBox) else field.currentText()
+            for key, field in self._settings.items()
+        }
+        settings["refine_axes"] = tuple(axis for axis, field in self._refine_axes.items() if field.isChecked())
+        traces = self._captures[0]["collections"][0].traces
+        settings["input_idx"] = tuple(sorted({trace.combo.input for trace in traces}))
+        settings["output_idx"] = tuple(sorted({trace.combo.output for trace in traces}))
+        return groups, copy.deepcopy(self._config), settings
+
+    def set_name(self) -> str:
+        return self._set_name_input.text().strip()
+
+    def set_capture_pending(self, pending: bool) -> None:
+        self._capture_pending = pending
+        self._update_actions()
+
+    def set_calculating(self, calculating: bool) -> None:
+        self._calculating = calculating
+        self._update_actions()
+
+    def set_status(self, message: str) -> None:
+        self._status_label.setText(message)
+
+    def show_calibration(self, calibration: dict) -> None:
+        self._calibration = calibration
+        self._target_combo.clear()
+        for index, target in enumerate(calibration.get("meta", {}).get("targets", [])):
+            xyz = target.get("nominal_scene_m", [])
+            self._target_combo.addItem(f"Набор {index + 1}: {xyz}")
+        self._draw_phase_effect()
+
+    def _draw_phase_effect(self, *_args) -> None:
+        self._phase_plot.clear()
+        if self._calibration is None:
+            return
+        diagnostics = self._calibration.get("meta", {}).get("diagnostics", [])
+        index = self._target_combo.currentIndex()
+        if not 0 <= index < len(diagnostics):
+            self._quality_label.setText("У этого набора нет диагностики фаз в точке цели.")
+            return
+        diagnostic = diagnostics[index]
+        phases = np.array([diagnostic["phase_before_deg"], diagnostic["phase_after_deg"]]).reshape(2, -1)
+        before, after = (phases - phases[0, 0] + 180) % 360 - 180
+        pairs = [(output, input_pos) for output in self._calibration["tx_output_pos"]
+                 for input_pos in self._calibration["rx_input_pos"]]
+        xx = np.arange(len(pairs))
+        for values, color, label in ((before, "#ed7d31", "До"), (after, "#42c7a5", "После")):
+            self._phase_plot.plot(xx, values, pen=pg.mkPen(color, width=1.5), symbol="o",
+                                  symbolBrush=color, symbolPen=color, name=label)
+        step = max(1, len(pairs) // 16)
+        self._phase_plot.getAxis("bottom").setTicks([[
+            (k, f"o{pairs[k][0]}/i{pairs[k][1]}") for k in range(0, len(pairs), step)
+        ]])
+        self._quality_label.setText(
+            f"Согласованность фаз в точке цели: {diagnostic['coherence_before']:.3f} "
+            f"→ {diagnostic['coherence_after']:.3f} (1 — все вклады в фазе)."
+        )
+
+    def _remove_capture(self) -> None:
+        row = self._table.currentRow()
+        if row >= 0:
+            self._captures.pop(row)
+            self._table.removeRow(row)
+            for index in range(self._table.rowCount()):
+                item = self._table.item(index, 0)
+                assert item is not None
+                item.setText(str(index + 1))
+            if not self._captures:
+                self._config = None
+            self._measurements_changed()
+
+    def _measurements_changed(self, *_args) -> None:
+        self._calibration = None
+        if hasattr(self, "_phase_plot"):
+            self._phase_plot.clear()
+            self._target_combo.clear()
+            self._quality_label.setText("Параметры изменены — требуется новый расчёт.")
+
+    def _update_actions(self) -> None:
+        busy = self._capture_pending or self._calculating
+        self._capture_button.setEnabled(not busy)
+        self._remove_button.setEnabled(not busy and bool(self._captures))
+        self._calculate_button.setEnabled(not busy and bool(self._captures))
+        self._cancel_button.setEnabled(busy)
+        self._table.setEnabled(not busy)
+        self._set_name_input.setEnabled(not busy)
+        for field in [*self._settings.values(), *self._refine_axes.values()]:
+            field.setEnabled(not busy)
+
+    def reject(self) -> None:
+        self.cancel_requested.emit()
+        super().reject()
+
+    def closeEvent(self, event) -> None:  # noqa: N802
+        self.cancel_requested.emit()
+        super().closeEvent(event)

python_app/gui/preprocess_dialog.py

@@ -26,7 +26,9 @@ import pyqtgraph as pg
 
 from python_app.models.dataset_model import TraceData
 from python_app.orchestration.preprocess_assets import (
+    CAPTURABLE_PREPROCESS_ASSET_KEYS,
     PREPROCESS_ASSET_SPECS,
+    REQUIRED_PREPROCESS_ASSET_KEYS,
     VISIBLE_PREPROCESS_ASSET_KEYS,
     preprocess_asset_display_name,
 )
@@ -47,6 +49,8 @@ class PreprocessDialog(QDialog):
     finalize_sequence_requested = pyqtSignal()
     abort_sequence_requested = pyqtSignal()
     create_neutral_sets_requested = pyqtSignal()
+    import_object_calibration_requested = pyqtSignal()
+    create_object_calibration_requested = pyqtSignal()
 
     def __init__(self, parent=None) -> None:
         """Initialize window metadata and compose dialog UI."""
@@ -165,10 +169,25 @@ class PreprocessDialog(QDialog):
         for key in keys:
             combo = QComboBox(group)
             combo.setPlaceholderText("<not selected>")
-            combo.setCurrentIndex(-1)
+            combo.setProperty("optional", key not in REQUIRED_PREPROCESS_ASSET_KEYS)
-            combo.currentTextChanged.connect(self._emit_selection_changed)
+            self._set_combo_items(combo, [], "")
+            combo.currentIndexChanged.connect(self._emit_selection_changed)
             self._set_combos[key] = combo
-            form.addRow(self._asset_row_label(key), combo)
+            field = combo
+            if key == "s21_object_calibration":
+                field = QWidget(group)
+                row = QHBoxLayout(field)
+                row.setContentsMargins(0, 0, 0, 0)
+                row.addWidget(combo, stretch=1)
+                self._import_object_calibration_button = QPushButton("Import…", field)
+                self._import_object_calibration_button.setToolTip("Import an existing cal_*.npy MIMO calibration folder.")
+                self._import_object_calibration_button.clicked.connect(self.import_object_calibration_requested.emit)
+                self._create_object_calibration_button = QPushButton("Create…", field)
+                self._create_object_calibration_button.setToolTip("Calculate a MIMO calibration from reflector measurements.")
+                self._create_object_calibration_button.clicked.connect(self.create_object_calibration_requested.emit)
+                row.addWidget(self._import_object_calibration_button)
+                row.addWidget(self._create_object_calibration_button)
+            form.addRow(self._asset_row_label(key), field)
         return group
 
     def _build_sequence_group(self) -> QGroupBox:
@@ -199,7 +218,7 @@ class PreprocessDialog(QDialog):
     def _build_sequence_button_grid(self, parent: QGroupBox) -> QGridLayout:
         """Build per-asset capture start buttons."""
         layout = QGridLayout()
-        for index, key in enumerate(VISIBLE_PREPROCESS_ASSET_KEYS):
+        for index, key in enumerate(CAPTURABLE_PREPROCESS_ASSET_KEYS):
             button = QPushButton(f"Start {preprocess_asset_display_name(key)}", parent)
             button.clicked.connect(lambda _checked=False, asset_key=key: self.start_sequence_requested.emit(asset_key))
             layout.addWidget(button, index // 2, index % 2)
@@ -316,7 +335,7 @@ class PreprocessDialog(QDialog):
 
     def selection_snapshot(self) -> dict[str, str]:
         """Return currently selected set names keyed by preprocess asset key."""
-        return {key: self._set_combos[key].currentText().strip() for key in VISIBLE_PREPROCESS_ASSET_KEYS}
+        return {key: self._set_combos[key].currentData() or "" for key in VISIBLE_PREPROCESS_ASSET_KEYS}
 
     def clear_capture_log(self) -> None:
         """Clear capture history text box."""
@@ -398,7 +417,7 @@ class PreprocessDialog(QDialog):
         for key in VISIBLE_PREPROCESS_ASSET_KEYS:
             combo = self._set_combos[key]
             with QSignalBlocker(combo):
-                self._set_combo_items(combo, available_sets.get(key, []), combo.currentText().strip())
+                self._set_combo_items(combo, available_sets.get(key, []), combo.currentData() or "")
 
     def set_selected_sets(self, selected_sets: dict[str, str], *, emit_signal: bool = True) -> None:
         """Apply selected set names to all comboboxes and optionally emit update."""
@@ -406,13 +425,10 @@ class PreprocessDialog(QDialog):
             selected_value = selected_sets.get(key, "")
             combo = self._set_combos[key]
             with QSignalBlocker(combo):
-                if not selected_value:
+                index = combo.findData(selected_value)
-                    combo.setCurrentIndex(-1)
+                if index < 0 and selected_value:
-                    continue
+                    combo.addItem(selected_value, selected_value)
-                index = combo.findText(selected_value)
+                    index = combo.count() - 1
-                if index < 0:
-                    combo.addItem(selected_value)
-                    index = combo.findText(selected_value)
                 combo.setCurrentIndex(index)
         if emit_signal:
             self._emit_selection_changed()
@@ -538,12 +554,15 @@ class PreprocessDialog(QDialog):
     def _set_combo_items(combo: QComboBox, names: list[str], current_text: str) -> None:
         """Replace combo contents and keep previous value when still available."""
         combo.clear()
-        combo.addItems(names)
+        if combo.property("optional"):
+            combo.addItem("Off", "")
+        for name in names:
+            combo.addItem(name, name)
         if not current_text:
-            combo.setCurrentIndex(-1)
+            combo.setCurrentIndex(combo.findData(""))
             return
-        index = combo.findText(current_text)
+        index = combo.findData(current_text)
         if index < 0:
-            combo.addItem(current_text)
+            combo.addItem(current_text, current_text)
-            index = combo.findText(current_text)
+            index = combo.count() - 1
         combo.setCurrentIndex(index)

python_app/models/run_config_codec.py

@@ -326,6 +326,10 @@ def run_config_from_dict(payload: dict[str, Any]) -> RunConfigModel:
         _as_dict(s21_preprocess_payload.get("reference"), "preprocess.s21.reference"),
         model.preprocess.s21.reference,
     )
+    _load_preprocess_asset(
+        _as_dict(s21_preprocess_payload.get("object_calibration"), "preprocess.s21.object_calibration"),
+        model.preprocess.s21.object_calibration,
+    )
 
     s11_preprocess_payload = _as_dict(preprocess_payload.get("s11"), "preprocess.s11")
     s11_calibration_payload = _as_dict(s11_preprocess_payload.get("calibration"), "preprocess.s11.calibration")
@@ -577,6 +581,10 @@ def run_config_to_dict(model: RunConfigModel) -> dict[str, Any]:
                     "set_name": model.preprocess.s21.reference.set_name,
                     "bundle_path": model.preprocess.s21.reference.bundle_path,
                 },
+                "object_calibration": {
+                    "set_name": model.preprocess.s21.object_calibration.set_name,
+                    "bundle_path": model.preprocess.s21.object_calibration.bundle_path,
+                },
             },
             "s11": {
                 "calibration": {

python_app/models/run_config_schema.py

@@ -275,6 +275,7 @@ class S21PreprocessModel:
 
     calibration: PreprocessAssetModel = field(default_factory=PreprocessAssetModel)
     reference: PreprocessAssetModel = field(default_factory=PreprocessAssetModel)
+    object_calibration: PreprocessAssetModel = field(default_factory=PreprocessAssetModel)
 
 
 @dataclass(slots=True)

python_app/orchestration/config_writer.py

@@ -41,7 +41,10 @@ class ConfigWriter:
             asset = preprocess_asset_model(config, key)
             bundle_path = self._runtime_dir / spec.runtime_filename
             logger.debug("Exporting preprocess bundle %s (set=%s) -> %s", key, asset.set_name, bundle_path)
-            store.export_set_bundle(spec.set_kind, radar_key, asset.set_name, bundle_path)
+            if key == "s21_object_calibration":
+                store.export_object_calibration_bundle(radar_key, asset.set_name, bundle_path, config)
+            else:
+                store.export_set_bundle(spec.set_kind, radar_key, asset.set_name, bundle_path)
             asset.bundle_path = str(bundle_path)
 
     def write(self, config: RunConfigModel, output_path: Path) -> Path:

python_app/orchestration/preprocess_assets.py

@@ -20,6 +20,7 @@ class PreprocessAssetSpec:
 PREPROCESS_ASSET_SPECS = {
     "s21_calibration": PreprocessAssetSpec("S21 Calibration", "s21_calibration", "s21_calibration_bundle.bin", "s21"),
     "s21_reference": PreprocessAssetSpec("S21 Reference", "s21_reference", "s21_reference_bundle.bin", "s21"),
+    "s21_object_calibration": PreprocessAssetSpec("Object Calibration", "s21_object_calibration", "s21_object_calibration_bundle.bin", "s21"),
     "s11_open": PreprocessAssetSpec("S11 Open", "s11_open", "s11_open_calibration_bundle.bin", "s11"),
     "s11_short": PreprocessAssetSpec("S11 Short", "s11_short", "s11_short_calibration_bundle.bin", "s11"),
     "s11_load": PreprocessAssetSpec("S11 Load", "s11_load", "s11_load_calibration_bundle.bin", "s11"),
@@ -30,7 +31,8 @@ PREPROCESS_ASSET_KEYS = tuple(PREPROCESS_ASSET_SPECS.keys())
 S21_PREPROCESS_ASSET_KEYS = ("s21_calibration", "s21_reference")
 S11_PREPROCESS_ASSET_KEYS = ("s11_open", "s11_short", "s11_load", "s11_reference")
 S11_PREPROCESS_CALIBRATION_KEYS = ("s11_open", "s11_short", "s11_load")
-VISIBLE_PREPROCESS_ASSET_KEYS = S21_PREPROCESS_ASSET_KEYS
+VISIBLE_PREPROCESS_ASSET_KEYS = (*S21_PREPROCESS_ASSET_KEYS, "s21_object_calibration")
+CAPTURABLE_PREPROCESS_ASSET_KEYS = S21_PREPROCESS_ASSET_KEYS
 REQUIRED_PREPROCESS_ASSET_KEYS = S21_PREPROCESS_ASSET_KEYS
 
 
@@ -40,6 +42,8 @@ def preprocess_asset_model(config: RunConfigModel, key: str) -> PreprocessAssetM
         return config.preprocess.s21.calibration
     if key == "s21_reference":
         return config.preprocess.s21.reference
+    if key == "s21_object_calibration":
+        return config.preprocess.s21.object_calibration
     if key == "s11_open":
         return config.preprocess.s11.calibration.open
     if key == "s11_short":
@@ -68,7 +72,9 @@ def preprocess_asset_set_name(config: RunConfigModel, key: str) -> str:
 
 def runtime_preprocess_asset_keys(config: RunConfigModel) -> tuple[str, ...]:
     """Return preprocess assets that should be exported and validated for runtime."""
-    enabled_keys = list(REQUIRED_PREPROCESS_ASSET_KEYS)
+    enabled_keys: list[str] = list(REQUIRED_PREPROCESS_ASSET_KEYS)
+    if preprocess_asset_set_name(config, "s21_object_calibration"):
+        enabled_keys.append("s21_object_calibration")
 
     has_full_s11_calibration = all(
         preprocess_asset_set_name(config, key)

python_app/storage/npz/store.py

@@ -16,6 +16,7 @@ from zipfile import BadZipFile
 import numpy as np
 
 from python_app.models.dataset_model import ComboKey, ResultCollection, SweepCollection, TraceData
+from python_app.models.run_config_model import RunConfigModel
 from python_app.storage.npz.paths import radar_key_from_config, sanitize_path_component
 from python_app.storage.npz.serialize import PREPROC_MAGIC, RAW_MAGIC, serialize_trace_collection, validate_trace_collection
 from python_app.storage.npz.snapshot_numpy import (
@@ -300,10 +301,34 @@ class NpzStore(StoreApi):
         set_dir = self._set_dir(kind, radar_key)
         if not set_dir.exists():
             return []
+        if kind == "s21_object_calibration":
+            return sorted(path.name for path in set_dir.iterdir()
+                          if not path.name.startswith(".") and (path / "cal_meta.json").is_file())
         return sorted(path.stem for path in set_dir.glob("*.npz"))
 
+    def save_object_calibration(self, radar_key: str, set_name: str, calibration: dict[str, Any]) -> None:
+        """Save an object calibration in its shared archive format without overwriting a set."""
+        from python_app.workflows.mimo_calibration import save_calibration
+
+        self._validate_set_name(set_name)
+        destination = self._set_dir("s21_object_calibration", radar_key) / set_name
+        if destination.exists():
+            raise FileExistsError(f"Object calibration already exists: {set_name}")
+        save_calibration(calibration, destination)
+
+    def load_object_calibration(self, radar_key: str, set_name: str) -> dict[str, Any]:
+        """Load and validate a saved object calibration, retaining all estimation metadata."""
+        from python_app.workflows.mimo_calibration import load_calibration
+
+        self._validate_set_name(set_name)
+        return load_calibration(self._set_dir("s21_object_calibration", radar_key) / set_name)
+
     def has_combo_coverage(self, kind: str, radar_key: str, set_name: str, combos: list[ComboKey]) -> bool:
         """Validate that named set covers all required switch combinations."""
+        if kind == "s21_object_calibration":
+            calibration = self.load_object_calibration(radar_key, set_name)
+            return all(combo.input in calibration["rx_input_pos"] and combo.output in calibration["tx_output_pos"]
+                       for combo in combos)
         collection = self.load_set(kind, radar_key, set_name)
         existing = {(trace.combo.input, trace.combo.output) for trace in collection.traces}
         required = {(combo.input, combo.output) for combo in combos}
@@ -312,6 +337,36 @@ class NpzStore(StoreApi):
     def export_set_bundle(self, kind: str, radar_key: str, set_name: str, output_path: Path) -> Path:
         """Export named set as binary collection bundle for C++ preprocessing stage."""
         collection = self.load_set(kind, radar_key, set_name)
+        return self._export_collection_bundle(collection, output_path)
+
+    def export_object_calibration_bundle(
+        self, radar_key: str, set_name: str, output_path: Path, config: RunConfigModel,
+    ) -> Path:
+        """Resample pair multipliers on the through-calibration grids used by the acquisition."""
+        from python_app.workflows.mimo_calibration import calibration_on_grid, validate_for_config
+
+        calibration = self.load_object_calibration(radar_key, set_name)
+        validate_for_config(calibration, config.to_dict())
+        tx_indices = {int(port): index for index, port in enumerate(calibration["tx_output_pos"])}
+        rx_indices = {int(port): index for index, port in enumerate(calibration["rx_input_pos"])}
+        source = self.load_set("s21_calibration", radar_key, config.preprocess.s21.calibration.set_name)
+        by_combo = {trace.combo: trace for trace in source.traces}
+        grids: dict[bytes, np.ndarray] = {}
+        traces: list[TraceData] = []
+        for combo in config.combos:
+            key = ComboKey(input=combo.input, output=combo.output)
+            trace = by_combo[key]
+            frequency = trace.frequency_hz
+            grid_key = frequency.tobytes()
+            if grid_key not in grids:
+                grids[grid_key] = calibration_on_grid(calibration, frequency)
+            correction = grids[grid_key][tx_indices[key.output], rx_indices[key.input]]
+            traces.append(TraceData(key, frequency, np.zeros(frequency.size, np.complex64), correction))
+        return self._export_collection_bundle(SweepCollection(0, 0, traces), output_path)
+
+    def _export_collection_bundle(self, collection: SweepCollection, output_path: Path) -> Path:
+        """Publish a complete binary trace bundle using one atomic replacement."""
+        validate_trace_collection(collection, require_finite=True)
         output_path.parent.mkdir(parents=True, exist_ok=True)
         temporary = self._temporary_file(output_path)
         try:
@@ -319,7 +374,7 @@ class NpzStore(StoreApi):
             temporary.replace(output_path)
         finally:
             temporary.unlink(missing_ok=True)
-        logger.info("Exported set %s/%s/%s bundle to %s", kind, radar_key, set_name, output_path)
+        logger.info("Exported %d traces to bundle %s", len(collection.traces), output_path)
         return output_path
 
     def save_runtime_snapshot(

python_app/tests/test_gui_action_lifecycle.py

@@ -17,12 +17,14 @@ from PyQt6.QtCore import QTimer  # noqa: E402
 
 from python_app.gui.app_window import AppWindow  # noqa: E402
 from python_app.gui.controllers.app_window_config.profile_io_mixin import AppWindowConfigProfileIOMixin  # noqa: E402
+from python_app.gui.controllers.app_window_config.live_processing_mixin import AppWindowLiveProcessingMixin  # noqa: E402
 from python_app.gui.controllers.app_window_pipeline_mixin import AppWindowPipelineMixin  # noqa: E402
 from python_app.gui.controllers.app_window_preprocess_mixin import AppWindowPreprocessMixin  # noqa: E402
 from python_app.gui.controllers.app_window_snapshot_mixin import AppWindowSnapshotMixin  # noqa: E402
+from python_app.gui.controllers.app_window_recording_mixin import AppWindowRecordingMixin  # noqa: E402
 from python_app.models.dataset_model import ResultCollection, SweepCollection  # noqa: E402
-from python_app.models.gui_profile_model import GuiProfileModel  # noqa: E402
+from python_app.models.gui_profile_model import GuiProfileModel, GuiStateModel  # noqa: E402
-from python_app.models.run_config_model import RunConfigModel  # noqa: E402
+from python_app.models.run_config_model import ComboModel, GprRxGeometryModel, GprTxGeometryModel, RunConfigModel  # noqa: E402
 from python_app.storage.npz_store import NpzStore  # noqa: E402
 from python_app.workflows.kamil_adc_neutral_preprocess import build_neutral_s21_sets  # noqa: E402
 
@@ -264,6 +266,111 @@ class CaptureBatchControlTest(unittest.TestCase):
 
 
 class GuiProfileWriteTest(unittest.TestCase):
+    def test_dataset_profile_uses_actual_preprocessing_and_preserves_current_gui(self) -> None:
+        for applied, selected in (("", "next_run"), ("applied", "")):
+            with self.subTest(applied=applied), tempfile.TemporaryDirectory() as folder:
+                pending = GuiProfileModel(gui=GuiStateModel())
+                pending.gui.processing.bscan.max_depth_m = 7.5
+                pending.run_config.gpr.tx_geometry = [GprTxGeometryModel(output_pos=0, x_m=.4, y_m=.2, z_m=.1)]
+                pending.run_config.preprocess.s21.object_calibration.set_name = selected
+                active = pending.run_config.clone()
+                active.gpr.tx_geometry[0].x_m = -.4
+                active.radar.serial = "acquired_A"
+                active.radar.sweep.points = 129
+                active.input_switch.positions = 2
+                active.output_switch.positions = 2
+                active.combos = [ComboModel(input=1, output=1)]
+                pending.run_config.radar.serial = "pending_B"
+                pending.run_config.radar.sweep.points = 257
+                active.preprocess.s21.object_calibration.set_name = applied
+                active.preprocess.s21.object_calibration.bundle_path = "/bundles/object" if applied else ""
+                active.preprocess.s21.calibration.set_name = "actual_through"
+                active.preprocess.s21.calibration.bundle_path = "/bundles/through"
+                active.preprocess.s21.reference.set_name = "actual_reference"
+                active.preprocess.s21.reference.bundle_path = "/bundles/reference"
+                active.preprocess.s11.calibration.open.set_name = "actual_open"
+                active.preprocess.s11.calibration.open.bundle_path = "/bundles/open"
+                active.preprocess.s11.reference.set_name = "actual_s11_reference"
+                active.preprocess.notch.enabled = True
+                active.preprocess.notch.bands_hz = [(2e9, 2.1e9)]
+                writer = AppWindowConfigProfileIOMixin()
+                writer._build_gui_profile = pending.clone
+                writer._active_run_config = active
+                dataset_path, settings_path = Path(folder) / "dataset.json", Path(folder) / "settings.json"
+                saved = writer._write_gui_profile_to_path(dataset_path, dataset=True)
+                writer._write_gui_profile_to_path(settings_path)
+                dataset = GuiProfileModel.load_from_path(dataset_path).to_dict()
+                expected = pending.to_dict()
+                acquired = active.to_dict()
+                for key in ("radar", "switches", "run", "preprocess"):
+                    expected[key] = acquired[key]
+                expected["gpr"]["tx_geometry"] = acquired["gpr"]["tx_geometry"]
+                expected["gpr"]["rx_geometry"] = acquired["gpr"]["rx_geometry"]
+                self.assertEqual(dataset, expected)
+                self.assertEqual(GuiProfileModel.load_from_path(settings_path).to_dict(), pending.to_dict())
+                saved.run_config.preprocess.s21.calibration.set_name = "mutated_return_value"
+                self.assertEqual(active.preprocess.s21.calibration.set_name, "actual_through")
+
+    def test_dataset_profile_retains_original_device_and_geometry_after_loading_another_profile(self) -> None:
+        acquired = GuiProfileModel()
+        acquired.run_config.ensure_combos()
+        acquired.run_config.radar.serial = "device_A"
+        acquired.run_config.gpr.tx_geometry = [GprTxGeometryModel(output_pos=0, x_m=-.4)]
+        acquired.run_config.gpr.rx_geometry = [GprRxGeometryModel(input_pos=0, x_m=.4)]
+        pending = acquired.clone()
+        pending.run_config.radar.model = "librevna_multi"
+        pending.run_config.radar.serial = "device_B"
+        pending.run_config.gpr.tx_geometry[0].x_m = 2.
+        pending.run_config.gpr.rx_geometry[0].x_m = -2.
+        writer = AppWindowConfigProfileIOMixin()
+        writer._build_gui_profile = pending.clone
+        writer._active_run_config = acquired.run_config
+        with tempfile.TemporaryDirectory() as folder:
+            path = Path(folder) / "dataset.json"
+            writer._write_gui_profile_to_path(path, dataset=True)
+            saved = GuiProfileModel.load_from_path(path)
+            self.assertEqual(saved.run_config.radar, acquired.run_config.radar)
+            self.assertEqual(saved.run_config.gpr, acquired.run_config.gpr)
+            self.assertEqual(saved.run_config.combos, acquired.run_config.combos)
+
+    def test_applied_geometry_tracks_successful_live_writes_only_while_acquiring(self) -> None:
+        for running, failed_write in ((True, False), (False, False), (True, True)):
+            with self.subTest(running=running, failed_write=failed_write):
+                active = RunConfigModel()
+                active.gpr.tx_geometry = [GprTxGeometryModel(output_pos=0, x_m=-.4)]
+                active.gpr.rx_geometry = [GprRxGeometryModel(input_pos=0, x_m=.4)]
+                original = active.clone()
+                writer = SimpleNamespace(
+                    _active_run_config=active,
+                    _supervisor=SimpleNamespace(is_running=lambda: running),
+                    _live_config_writer=SimpleNamespace(write=mock.Mock(side_effect=OSError("disk full") if failed_write else None)),
+                    _live_processing_config=mock.Mock(return_value=object()),
+                    _can_reprocess_history=lambda: False,
+                    _gpr_tx_geometry_input=SimpleNamespace(records=lambda: [dict(output_pos=0, x_m=1., y_m=2., z_m=3.)]),
+                    _gpr_rx_geometry_input=SimpleNamespace(records=lambda: [dict(input_pos=0, x_m=-1., y_m=-2., z_m=-3.)]),
+                )
+                if failed_write:
+                    with self.assertRaises(OSError):
+                        AppWindowLiveProcessingMixin._write_live_processing_config(writer)
+                else:
+                    AppWindowLiveProcessingMixin._write_live_processing_config(writer)
+                if running and not failed_write:
+                    self.assertEqual(active.gpr.tx_geometry, [GprTxGeometryModel(0, 1., 2., 3.)])
+                    self.assertEqual(active.gpr.rx_geometry, [GprRxGeometryModel(0, -1., -2., -3.)])
+                else:
+                    self.assertEqual(active.gpr, original.gpr)
+
+    def test_dataset_profile_without_active_run_preserves_ui_selection(self) -> None:
+        writer = AppWindowConfigProfileIOMixin()
+        pending = GuiProfileModel()
+        pending.run_config.preprocess.s21.object_calibration.set_name = "selected"
+        writer._build_gui_profile = pending.clone
+        writer._active_run_config = None
+        with tempfile.TemporaryDirectory() as folder:
+            path = Path(folder) / "dataset.json"
+            writer._write_gui_profile_to_path(path, dataset=True)
+            self.assertEqual(GuiProfileModel.load_from_path(path).to_dict(), pending.to_dict())
+
     def test_failed_profile_replace_preserves_existing_profile_and_cleans_temporary(self) -> None:
         writer = AppWindowConfigProfileIOMixin()
         writer._build_gui_profile = lambda: GuiProfileModel()
@@ -293,5 +400,95 @@ class HistoryCommandRestoreTest(unittest.TestCase):
             self.assertEqual(AppWindow._load_history_command_seq(path), 9876543210)
 
 
+class PreprocessHistoryRestartTest(unittest.TestCase):
+    def _runtime(self):
+        w = _Runtime()
+        config = RunConfigModel.from_dict({"radar": {"model": "librevna", "driver_mode": "mock"}})
+        config.input_switch.driver = config.output_switch.driver = "h7992"
+        config.input_switch.radar_port, config.output_switch.radar_port = 1, 2
+        config.preprocess.s21.calibration.set_name = "through"
+        config.preprocess.s21.reference.set_name = "empty"
+        w._build_config.return_value = config
+        w._processor_run_signature = w._build_processor_run_signature(config)
+        w._history_run_signature = w._build_run_history_signature(config)
+        w._project_root = Path("/tmp/object-calibration-test")
+        w._store = mock.Mock()
+        w._store.has_combo_coverage.return_value = True
+        w._config_writer = mock.Mock()
+        w._config_writer.write.return_value = w._project_root / "runtime.json"
+        w._radar_key = mock.Mock(return_value="radar")
+        w._supervisor.pids.return_value = {}
+        w._bscan_reprocess_timer = mock.Mock()
+        for name in ("_validate_processing_mode_constraints", "_prepare_radar_for_native_acquisition",
+                     "_close_replay_ring_writer", "_discard_bscan_replay_results", "_close_readers",
+                     "_drop_pending_ring_payloads", "_reset_runtime_history", "_stop_all_processes",
+                     "_write_live_processing_config"):
+            setattr(w, name, mock.Mock())
+        return w, config
+
+    def test_changed_preprocess_clears_native_history_before_both_start_modes(self) -> None:
+        for single_capture in (False, True):
+            with self.subTest(single_capture=single_capture):
+                w, config = self._runtime()
+                config.preprocess.s21.object_calibration.set_name = "sphere"
+                events = []
+                w._write_live_processing_config.side_effect = lambda **_kwargs: events.append("clear")
+                w._supervisor.start.side_effect = lambda *_args, **_kwargs: events.append("start")
+                with mock.patch("python_app.gui.controllers.app_window_pipeline_mixin.ShmRingReader"):
+                    w._start_run(single_capture=single_capture)
+                w._show_exception.assert_not_called()
+                w._write_live_processing_config.assert_called_once_with(
+                    history_command="clear_all", bump_history_seq=True)
+                self.assertEqual(events, ["clear", "start"])
+                w._reset_runtime_history.assert_called_once()
+                self.assertEqual(w._history_run_signature, w._build_run_history_signature(config))
+
+    def test_unchanged_preprocess_retains_history_and_existing_processor(self) -> None:
+        w, config = self._runtime()
+        with mock.patch("python_app.gui.controllers.app_window_pipeline_mixin.ShmRingReader"):
+            w._start_run(single_capture=True)
+        w._show_exception.assert_not_called()
+        w._write_live_processing_config.assert_not_called()
+        w._reset_runtime_history.assert_not_called()
+        w._stop_all_processes.assert_not_called()
+
+    def test_capture_override_is_cloned_and_skips_display_mode_constraints(self) -> None:
+        w, config = self._runtime()
+        w._object_capture_job = object()
+        with mock.patch("python_app.gui.controllers.app_window_pipeline_mixin.ShmRingReader"):
+            w._start_run(config_override=config)
+        w._show_exception.assert_not_called()
+        w._build_config.assert_not_called()
+        w._validate_processing_mode_constraints.assert_not_called()
+        exported = w._config_writer.prepare_preprocess_bundles.call_args.args[2]
+        self.assertIsNot(exported, config)
+        self.assertFalse(config.runtime.continuous)
+        self.assertTrue(exported.runtime.continuous)
+
+    def test_regular_start_and_other_hardware_actions_wait_for_object_capture(self) -> None:
+        for action, args in (("_start_run", ()), ("_capture_tmp_reference", ()),
+                             ("_create_neutral_sets", ()), ("_start_capture_sequence", ("s21_reference",)),
+                             ("_apply_radar_settings", ()), ("_save_snapshot", ()),
+                             ("_save_vna_history_json", ()), ("_remove_last_runtime_history", ()),
+                             ("_clear_all_runtime_history", ())):
+            with self.subTest(action=action):
+                w, _ = self._runtime()
+                w._object_capture_job = object()
+                getattr(w, action)(*args)
+                w._build_config.assert_not_called()
+                w._show_error.assert_called_once()
+
+    def test_profile_load_and_recording_wait_for_object_capture_even_before_pipeline_start(self) -> None:
+        for action in (AppWindowConfigProfileIOMixin._ensure_ready_to_load_config,
+                       AppWindowRecordingMixin._start_run_with_recording):
+            with self.subTest(action=action.__name__):
+                w, _ = self._runtime()
+                w._object_capture_job = object()
+                self.assertFalse(action(w))
+                w._build_config.assert_not_called()
+                w._supervisor.is_running.assert_not_called()
+                w._show_error.assert_called_once()
+
+
 if __name__ == "__main__":
     unittest.main()

python_app/tests/test_mimo_calibration.py

@@ -0,0 +1,384 @@
+"""Physical MIMO estimation, legacy archives and failure-preserving writes."""
+
+from __future__ import annotations
+
+import copy
+import json
+from pathlib import Path
+import tempfile
+import unittest
+from unittest import mock
+from typing import Any
+
+import numpy as np
+
+from python_app.models.dataset_model import ComboKey, SweepCollection, TraceData
+from python_app.workflows import mimo_calibration as mc
+
+
+class MimoCalibrationTest(unittest.TestCase):
+    def setUp(self):
+        self.settings = mc.Settings(input_idx=(2, 7), output_idx=(1, 5), sphere_radius_m=0.,
+                                    antenna_height_m=1., f_min=2e9, f_max=6e9,
+                                    refine_axes=(), coarse_range_search_m=0.)
+        self.freq = np.linspace(2e9, 6e9, 129)
+        self.target = (.2, .25, 4.)
+        self.tx = np.array([[-.6, 0., 0.], [.6, 0., 0.]])
+        self.rx = np.array([[-.3, .1, 0.], [.3, .1, 0.]])
+        self.config = {
+            'radar': {'model': 'librevna_multi', 'serial': 'master', 'multi_device': {'slave_serials': ['slave']}},
+            'preprocess': {'s21': {'calibration': {'set_name': 'through'}, 'reference': {'set_name': 'empty'}}},
+            'gpr': {
+                'tx_geometry': [dict(output_pos=port, x_m=xyz[0], y_m=xyz[1], z_m=xyz[2]) for port, xyz in zip((1, 5), self.tx)],
+                'rx_geometry': [dict(input_pos=port, x_m=xyz[0], y_m=xyz[1], z_m=xyz[2]) for port, xyz in zip((2, 7), self.rx)],
+            },
+            'run': {'combos': [dict(input=input_, output=output) for output in (1, 5) for input_ in (2, 7)]},
+        }
+
+    def signal(self, target=None, *, gains=False):
+        target = self.target if target is None else target
+        pitch = np.radians(self.settings.pitch_deg)
+        y0 = target[1] - self.settings.antenna_height_m
+        radar_target = np.array([target[0], y0 * np.cos(pitch) + target[2] * np.sin(pitch),
+                                 -y0 * np.sin(pitch) + target[2] * np.cos(pitch)])
+        vt, vr = self.tx - radar_target, self.rx - radar_target
+        dt, dr = np.linalg.norm(vt, axis=1), np.linalg.norm(vr, axis=1)
+        paths = dt[:, None] + dr[None, :]
+        if self.settings.sphere_radius_m:
+            cosine = (vt @ vr.T) / (dt[:, None] * dr[None, :])
+            paths -= 2 * self.settings.sphere_radius_m * np.sqrt((1 + cosine) / 2)
+        tx_phase = np.array([0., .7])[:, None] - 2 * np.pi * self.freq * np.array([0., .02])[:, None] / mc.C_LIGHT
+        rx_phase = np.array([0., -.5])[:, None] - 2 * np.pi * self.freq * np.array([0., -.013])[:, None] / mc.C_LIGHT
+        signal = np.exp(-2j * np.pi * self.freq * paths[:, :, None] / mc.C_LIGHT)
+        signal *= np.exp(1j * (tx_phase[:, None, :] + rx_phase[None, :, :] + 1.1))
+        if gains:
+            signal *= np.array([1., 2.])[:, None, None] * np.array([1., .5])[None, :, None]
+        return signal, paths
+
+    def collection(self, samples=None, *, freq=None, identity=1):
+        samples = self.signal()[0] if samples is None else samples
+        freq = self.freq if freq is None else freq
+        traces = [TraceData(ComboKey(input_, output), freq.copy(), np.zeros(freq.size, np.complex64), samples[t, r].copy())
+                  for t, output in enumerate((1, 5)) for r, input_ in enumerate((2, 7))]
+        return SweepCollection(identity, identity, traces)
+
+    def calibration(self):
+        return mc.compute_from_collections([{'collections': [self.collection()], 'target_scene_m': self.target}],
+                                           self.config, settings=self.settings)
+
+    def archive(self, root, collection, *, name='0000_id1_ns1'):
+        snapshot = root / 'preprocessed' / name
+        snapshot.mkdir(parents=True)
+        (root / 'config_profile.json').write_text(json.dumps(self.config))
+        (snapshot / 'meta.json').write_text('{}')
+        for trace in collection.traces:
+            suffix = f'i{trace.combo.input}_o{trace.combo.output}'
+            np.save(snapshot / f'{suffix}_s21.npy', trace.s21)
+            np.save(snapshot / f'{suffix}_freq.npy', trace.frequency_hz)
+            np.save(snapshot / f'{suffix}_s11.npy', trace.s11)
+        return snapshot
+
+    def test_point_and_sphere_recover_relative_antenna_phases(self):
+        for radius in (0., .16):
+            with self.subTest(radius=radius):
+                self.settings.sphere_radius_m = radius
+                signal, paths = self.signal()
+                cal = self.calibration()
+                corrected = mc.apply_calibration(signal, self.freq, cal)
+                contributions = corrected * np.exp(2j * np.pi * self.freq * paths[:, :, None] / mc.C_LIGHT)
+                phases = np.angle(contributions.mean(axis=2))
+                np.testing.assert_allclose(phases, np.full((2, 2), 1.1), atol=.004)
+                np.testing.assert_allclose(np.abs(cal['pair']), 1., atol=2e-7)
+                self.assertGreater(cal['meta']['quality']['coherence_final'][0], .9999)
+                self.assertLess(cal['meta']['quality']['coherence_before'][0], .98)
+                diagnostic = cal['meta']['diagnostics'][0]
+                self.assertEqual(np.shape(diagnostic['phase_before_deg']), (2, 2))
+                np.testing.assert_allclose(diagnostic['phase_after_deg'], np.full((2, 2), np.degrees(1.1)), atol=.25)
+                self.assertIsNone(cal['meta']['quality']['coherence_leave_one_out'][0])
+
+    def test_amplitude_equalization_is_explicit(self):
+        self.settings.apply_amplitude = True
+        signal, paths = self.signal(gains=True)
+        cal = mc.compute_from_collections([{'collections': [self.collection(signal)], 'target_scene_m': self.target}],
+                                          self.config, settings=self.settings)
+        corrected = mc.apply_calibration(signal, self.freq, cal)
+        # Compare amplitudes after removing the physical propagation phase.
+        levels = np.abs((corrected * np.exp(2j * np.pi * self.freq * paths[:, :, None] / mc.C_LIGHT)).mean(axis=2))
+        self.assertLess(levels.max() / levels.min(), 1.01)
+        self.assertGreater(np.max(np.abs(cal['pair'])), 1.5)
+
+    def test_archive_and_live_estimation_share_the_same_math(self):
+        with tempfile.TemporaryDirectory() as directory:
+            root = Path(directory)
+            signal = self.signal()[0]
+            self.archive(root, self.collection(signal), name='0000_id1_ns1')
+            self.archive(root, self.collection(signal * 2), name='0001_id2_ns2')
+            archived = mc.compute_calibration([{'path': root / 'preprocessed', 'target_scene_m': self.target}], settings=self.settings)
+            live = mc.compute_from_collections([{'collections': [self.collection(signal), self.collection(signal * 2)],
+                                                'target_scene_m': self.target}], self.config, settings=self.settings)
+            np.testing.assert_array_equal(archived['pair'], live['pair'])
+
+    def test_frequency_geometry_channel_and_signal_failures_are_explicit(self):
+        cases = []
+        incomplete = self.collection(); incomplete.traces.pop(); cases.append(incomplete)
+        duplicate = self.collection(); duplicate.traces.append(duplicate.traces[0]); cases.append(duplicate)
+        mismatched = self.collection(); mismatched.traces[0].frequency_hz += 10000; cases.append(mismatched)
+        nonuniform = self.collection(); nonuniform.traces[0].frequency_hz[20] += 1e6; cases.append(nonuniform)
+        zero = self.collection(np.zeros((2, 2, self.freq.size), complex)); cases.append(zero)
+        invalid = self.collection(); invalid.traces[0].s21[0] = np.nan; cases.append(invalid)
+        for index, collection in enumerate(cases):
+            with self.subTest(collection=index):
+                with self.assertRaises(ValueError):
+                    mc.compute_from_collections([{'collections': [collection], 'target_scene_m': self.target}], self.config, settings=self.settings)
+        with self.assertRaisesRegex(ValueError, 'at least one'):
+            mc.compute_from_collections([], self.config, settings=self.settings)
+
+    def test_config_checks_phase_base_and_geometry_but_allows_new_reference(self):
+        cal = self.calibration()
+        updated = copy.deepcopy(self.config)
+        updated['preprocess']['s21']['reference']['set_name'] = 'new_background'
+        mc.validate_for_config(cal, updated)
+        for edit in ('geometry', 'through', 'combo', 'serial'):
+            updated = copy.deepcopy(self.config)
+            if edit == 'geometry':
+                updated['gpr']['tx_geometry'][0]['x_m'] += .01
+            elif edit == 'through':
+                updated['preprocess']['s21']['calibration']['set_name'] = 'new_through'
+            elif edit == 'serial':
+                updated['radar']['serial'] = 'another_device'
+            else:
+                updated['run']['combos'].append({'input': 999, 'output': 1})
+            with self.subTest(edit=edit), self.assertRaises(ValueError):
+                mc.validate_for_config(cal, updated)
+
+    def test_object_corrected_sources_are_rejected_for_live_and_archives(self):
+        for field in ('set_name', 'bundle_path'):
+            self.config['preprocess']['s21']['object_calibration'] = {field: 'active'}
+            with self.subTest(field=field), self.assertRaisesRegex(ValueError, 'already active'):
+                self.calibration()
+            with tempfile.TemporaryDirectory() as directory:
+                root = Path(directory)
+                self.archive(root, self.collection())
+                with self.assertRaisesRegex(ValueError, 'already active'):
+                    mc.compute_calibration([{'path': root / 'preprocessed', 'target_scene_m': self.target}], settings=self.settings)
+
+    def test_cancel_is_checked_inside_refinement(self):
+        self.settings.refine_axes = ('z',)
+        state = {'estimating': False, 'checks': 0}
+
+        def progress(message):
+            state['estimating'] |= message.startswith('Estimating')
+
+        def cancelled():
+            if state['estimating']:
+                state['checks'] += 1
+            return state['checks'] >= 6
+
+        with self.assertRaises(InterruptedError):
+            mc.compute_from_collections([{'collections': [self.collection()], 'target_scene_m': self.target}],
+                                        self.config, settings=self.settings, progress=progress, cancelled=cancelled)
+        self.assertEqual(state['checks'], 6)
+
+    def test_apply_rejects_broadcasting_and_corrupted_archives(self):
+        cal = self.calibration()
+        with self.assertRaisesRegex(ValueError, 'invalid shape'):
+            mc.apply_calibration(np.ones(self.freq.size), self.freq, cal)
+        cal['pair'][0, 0, 0] *= 2
+        with self.assertRaisesRegex(ValueError, 'disagree'):
+            mc.validate_calibration(cal)
+
+    def test_interpolation_is_continuous_at_nonlinear_archive_edges(self):
+        self.settings.phase_model = 'raw'
+        cal = self.calibration()
+        # Keep a consistent separable archive with a deliberately nonlinear phase.
+        phase = .4 * ((self.freq - self.freq.mean()) / 1e9) ** 3
+        cal['tx'][1] *= np.exp(1j * phase)
+        cal['pair'] = cal['tx'][:, None] * cal['rx'][None]
+        edge = mc.calibration_on_grid(cal, [self.freq[-1], self.freq[-1] + 1])
+        self.assertLess(abs(np.angle(edge[1, 0, 1] / edge[1, 0, 0])), 1e-6)
+        shifted = mc.calibration_on_grid(cal, self.freq + 10000)
+        self.assertIsNot(shifted, cal['pair'])
+
+    def test_save_roundtrip_and_write_failure_preserve_the_previous_archive(self):
+        cal = self.calibration()
+        with tempfile.TemporaryDirectory() as directory:
+            destination = Path(directory) / 'cal'
+            destination.mkdir()
+            (destination / 'notes.txt').write_text('preserve user notes')
+            mc.save_calibration(cal, destination)
+            np.testing.assert_array_equal(mc.load_calibration(destination)['pair'], cal['pair'])
+            original = {path.name: path.read_bytes() for path in destination.iterdir()}
+            save = np.save
+
+            def fail_second(path, *args, **kwargs):
+                if Path(path).name == 'cal_pair.npy':
+                    raise OSError('disk full')
+                return save(path, *args, **kwargs)
+
+            with mock.patch.object(mc.np, 'save', side_effect=fail_second), self.assertRaises(OSError):
+                mc.save_calibration(cal, destination, overwrite=True)
+            self.assertEqual(original, {path.name: path.read_bytes() for path in destination.iterdir()})
+            self.assertEqual(list(Path(directory).glob('.cal.*')), [])
+            with self.assertRaises(FileExistsError):
+                mc.save_calibration(cal, destination)
+
+    def test_non_overwriting_save_preserves_archive_published_during_staging(self):
+        with tempfile.TemporaryDirectory() as directory:
+            destination = Path(directory) / 'cal'
+            with self.assertRaises(FileExistsError):
+                with mc._staged_directory(destination, False) as stage:
+                    (stage / 'cal_pair.npy').write_bytes(b'new correction')
+                    destination.mkdir()
+                    (destination / 'cal_pair.npy').write_bytes(b'concurrent correction')
+                    (destination / 'cal_meta.json').write_bytes(b'concurrent metadata')
+            self.assertEqual({path.name: path.read_bytes() for path in destination.iterdir()}, {
+                'cal_pair.npy': b'concurrent correction', 'cal_meta.json': b'concurrent metadata',
+            })
+            self.assertEqual(list(Path(directory).glob('.cal.*')), [])
+
+    def test_failed_commit_restores_old_archive_and_failed_rollback_keeps_backups(self):
+        cal = self.calibration()
+        with tempfile.TemporaryDirectory() as directory:
+            destination = Path(directory) / 'cal'
+            mc.save_calibration(cal, destination)
+            original = (destination / 'cal_pair.npy').read_bytes()
+            replace = Path.replace
+
+            def fail_commit(path, target):
+                if path.name.startswith('.cal.new-'):
+                    raise OSError('rename failed')
+                return replace(path, target)
+
+            with mock.patch.object(Path, 'replace', autospec=True, side_effect=fail_commit), self.assertRaises(OSError):
+                mc.save_calibration(cal, destination, overwrite=True)
+            self.assertEqual((destination / 'cal_pair.npy').read_bytes(), original)
+
+            def fail_rollback(path, target):
+                if path.name.startswith(('.cal.new-', '.cal.old-')):
+                    raise OSError('filesystem unavailable')
+                return replace(path, target)
+
+            with mock.patch.object(Path, 'replace', autospec=True, side_effect=fail_rollback), self.assertRaisesRegex(RuntimeError, 'originals retained'):
+                mc.save_calibration(cal, destination, overwrite=True)
+            backup = next(Path(directory).glob('.cal.old-*'))
+            self.assertEqual((backup / 'cal_pair.npy').read_bytes(), original)
+
+    def test_offline_failure_preserves_previous_postprocessed_and_original_data(self):
+        cal = self.calibration()
+        with tempfile.TemporaryDirectory() as directory:
+            root = Path(directory)
+            snapshot = self.archive(root, self.collection())
+            post = root / 'postprocessed'; post.mkdir()
+            (post / 'calibration_applied.json').write_text('{}')
+            (post / 'old_data.bin').write_bytes(b'old data')
+            original = {path.name: path.read_bytes() for path in snapshot.iterdir()}
+            with mock.patch.object(mc.np, 'save', side_effect=OSError('disk full')), self.assertRaises(OSError):
+                mc.apply_to_measurement(root, cal, overwrite=True)
+            self.assertEqual((post / 'old_data.bin').read_bytes(), b'old data')
+            self.assertEqual(original, {path.name: path.read_bytes() for path in snapshot.iterdir()})
+            self.assertEqual(list(root.glob('.postprocessed.*')), [])
+
+    def test_object_corrected_archive_is_rejected_even_when_source_profile_has_object_off(self):
+        with tempfile.TemporaryDirectory() as directory:
+            root = Path(directory)
+            snapshot = self.archive(root, self.collection())
+            post, *_ = mc.apply_to_measurement(root, self.calibration())
+            for prefixes in (None, [snapshot.name[:4]]):
+                with self.subTest(prefixes=prefixes), self.assertRaisesRegex(ValueError, 'already applied'):
+                    mc.compute_calibration([{'path': post, 'snapshots': prefixes, 'target_scene_m': self.target}],
+                                           settings=self.settings)
+            # A corrected sibling does not change the original preprocessing data.
+            original = mc.compute_calibration([{'path': root / 'preprocessed', 'target_scene_m': self.target}],
+                                              settings=self.settings)
+            np.testing.assert_array_equal(original['pair'], self.calibration()['pair'])
+
+    def test_snapshot_local_correction_marker_is_checked_for_target_and_empty_scene(self):
+        with tempfile.TemporaryDirectory() as directory:
+            root = Path(directory)
+            snapshot = self.archive(root, self.collection())
+            (snapshot / 'calibration_applied.json').write_text('{}')
+            targets = [{'path': root / 'preprocessed', 'snapshots': [snapshot.name[:4]],
+                        'target_scene_m': self.target}]
+            with self.assertRaisesRegex(ValueError, 'already applied'):
+                mc.compute_calibration(targets, settings=self.settings)
+            untouched = root / 'untouched'
+            self.archive(untouched, self.collection())
+            targets = [{'path': untouched / 'preprocessed', 'target_scene_m': self.target}]
+            with self.assertRaisesRegex(ValueError, 'already applied'):
+                mc.compute_calibration(targets, root / 'preprocessed', self.settings)
+
+    def test_offline_grid_cache_uses_the_entire_axis_and_preserves_s11_and_dtype(self):
+        cal = self.calibration()
+        collection = self.collection(np.ones((2, 2, self.freq.size), np.complex64))
+        alternate = self.freq.copy()
+        alternate[64] += 1e7
+        collection.traces[2].frequency_hz = alternate
+        with tempfile.TemporaryDirectory() as directory:
+            root = Path(directory)
+            snapshot = self.archive(root, collection)
+            original_s11 = (snapshot / 'i2_o5_s11.npy').read_bytes()
+            post, count, fixed, _ = mc.apply_to_measurement(root, cal)
+            self.assertEqual((count, fixed), (1, 4))
+            corrected = np.load(post / snapshot.name / 'i2_o5_s21.npy')
+            self.assertEqual(corrected.dtype, np.complex64)
+            expected = mc.calibration_on_grid(cal, alternate)[1, 0]
+            np.testing.assert_allclose(corrected, expected, atol=1e-7)
+            self.assertGreater(abs(corrected[64] - cal['pair'][1, 0, 64]), .001)
+            self.assertEqual((post / snapshot.name / 'i2_o5_s11.npy').read_bytes(), original_s11)
+
+    def test_empty_scene_grids_and_geometry_are_checked_before_subtraction(self):
+        with tempfile.TemporaryDirectory() as directory:
+            root = Path(directory)
+            target_root, empty_root = root / 'target', root / 'empty'
+            self.archive(target_root, self.collection())
+            zero = np.zeros((2, 2, self.freq.size), complex)
+            self.archive(empty_root, self.collection(zero))
+            self.archive(empty_root, self.collection(zero, freq=self.freq + 10000), name='0001_id2_ns2')
+            targets = [{'path': target_root / 'preprocessed', 'target_scene_m': self.target}]
+            with self.assertRaisesRegex(ValueError, 'frequency grids differ'):
+                mc.compute_calibration(targets, empty_root / 'preprocessed', self.settings)
+            profile = copy.deepcopy(self.config)
+            profile['gpr']['rx_geometry'][0]['z_m'] += .1
+            (empty_root / 'config_profile.json').write_text(json.dumps(profile))
+            with self.assertRaisesRegex(ValueError, 'antenna geometry differs'):
+                mc.compute_calibration(targets, empty_root / 'preprocessed', self.settings)
+
+    def test_snapshot_prefixes_must_select_one_distinct_complete_snapshot(self):
+        with tempfile.TemporaryDirectory() as directory:
+            root = Path(directory)
+            self.archive(root, self.collection())
+            self.archive(root, self.collection(), name='0001_id2_ns2')
+            for prefixes in (['000'], ['0000', 'missing'], ['0000', '0000']):
+                with self.subTest(prefixes=prefixes), self.assertRaises(ValueError):
+                    mc.list_snapshots(root / 'preprocessed', prefixes)
+
+    def test_multiple_snapshots_are_averaged_before_one_gated_fft(self):
+        collections = [self.collection(identity=index + 1) for index in range(8)]
+        with mock.patch.object(mc.np.fft, 'ifft', wraps=np.fft.ifft) as transform:
+            mc.compute_from_collections([{'collections': collections, 'target_scene_m': self.target}],
+                                        self.config, settings=self.settings)
+        self.assertEqual(transform.call_count, 1)
+
+    def test_original_scipy_refinement_finishes_with_valid_diagnostics(self):
+        self.settings.refine_axes = ('z',)
+        self.settings.coarse_range_search_m = .1
+        cal = self.calibration()
+        self.assertGreater(cal['meta']['diagnostics'][0]['coherence_after'], .999)
+        refined = cal['meta']['targets'][0]['refined_scene_m']
+        self.assertTrue(np.all(np.isfinite(refined)))
+
+    def test_bad_settings_and_duplicate_geometry_fail_early(self):
+        invalid_settings: tuple[dict[str, Any], ...] = (
+            {'input_idx': (0, 0)}, {'output_idx': (True,)}, {'gate_taper_m': 0.},
+            {'f_max': 0.}, {'refine_axes': ('z', 'z')}, {'phase_model': 'unknown'},
+        )
+        for fields in invalid_settings:
+            with self.subTest(fields=fields), self.assertRaises(ValueError):
+                mc.Settings(**fields)
+        self.config['gpr']['tx_geometry'].append(self.config['gpr']['tx_geometry'][0])
+        with self.assertRaisesRegex(ValueError, 'duplicate antenna geometry'):
+            self.calibration()
+
+
+if __name__ == '__main__':
+    unittest.main()

python_app/tests/test_object_calibration_gui.py

@@ -0,0 +1,304 @@
+"""Optional selection, live sample input and real target-phase diagnostics."""
+
+from __future__ import annotations
+
+import copy
+import os
+import queue
+import threading
+import time
+import unittest
+from types import SimpleNamespace
+from unittest import mock
+
+import numpy as np
+
+os.environ.setdefault("QT_QPA_PLATFORM", "offscreen")
+from PyQt6.QtCore import QTimer  # noqa: E402
+from PyQt6.QtWidgets import QApplication, QPushButton, QWidget  # noqa: E402
+
+from python_app.gui.controllers.object_calibration_controller import ObjectCalibrationController, _calculate  # noqa: E402
+from python_app.gui.object_calibration_dialog import ObjectCalibrationDialog  # noqa: E402
+from python_app.gui.preprocess_dialog import PreprocessDialog  # noqa: E402
+from python_app.tests import test_mimo_calibration as numeric_fixture  # noqa: E402
+
+
+def setUpModule() -> None:
+    global app
+    app = QApplication.instance() or QApplication([])
+
+
+class ObjectCalibrationSelectorTest(unittest.TestCase):
+    def setUp(self) -> None:
+        self.dialog = PreprocessDialog()
+        self.addCleanup(self.dialog.close)
+
+    def test_optional_off_is_distinct_from_a_saved_set_named_off(self) -> None:
+        self.dialog.set_available_sets({"s21_object_calibration": ["Off", "sphere"]})
+        changes = mock.Mock()
+        self.dialog.selection_changed.connect(changes)
+        combo = self.dialog._set_combos["s21_object_calibration"]
+        self.assertEqual(combo.currentText(), "Off")
+        self.assertEqual(self.dialog.selection_snapshot()["s21_object_calibration"], "")
+        combo.setCurrentIndex(combo.findData("Off"))
+        self.assertEqual(self.dialog.selection_snapshot()["s21_object_calibration"], "Off")
+        changes.assert_called_once()
+        self.dialog.set_available_sets({"s21_object_calibration": ["Off", "sphere"]})
+        self.assertEqual(self.dialog.selection_snapshot()["s21_object_calibration"], "Off")
+        self.dialog.set_selected_sets({"s21_object_calibration": ""}, emit_signal=False)
+        self.assertEqual(combo.currentText(), "Off")
+        self.assertEqual(combo.currentData(), "")
+
+    def test_object_actions_do_not_start_a_sequential_hardware_capture(self) -> None:
+        capture, imported, created = mock.Mock(), mock.Mock(), mock.Mock()
+        self.dialog.start_sequence_requested.connect(capture)
+        self.dialog.import_object_calibration_requested.connect(imported)
+        self.dialog.create_object_calibration_requested.connect(created)
+        self.dialog._import_object_calibration_button.click()
+        self.dialog._create_object_calibration_button.click()
+        imported.assert_called_once()
+        created.assert_called_once()
+        capture.assert_not_called()
+        self.assertEqual([button.text() for button in self.dialog.findChildren(QPushButton)
+                          if button.text().startswith("Start ")],
+                         ["Start S21 Calibration", "Start S21 Reference"])
+
+
+class ObjectCalibrationDialogTest(unittest.TestCase):
+    def setUp(self) -> None:
+        self.fixture = numeric_fixture.MimoCalibrationTest()
+        self.fixture.setUp()
+        self.dialog = ObjectCalibrationDialog("sphere")
+        self.addCleanup(self.dialog.close)
+
+    def _capture_with_target(self) -> None:
+        self.dialog.add_capture([self.fixture.collection()], self.fixture.config)
+        for column, coordinate in enumerate(self.fixture.target, start=2):
+            self.dialog._table.item(0, column).setText(str(coordinate))
+
+    def test_capture_is_frozen_and_xyz_must_be_entered_after_measurement(self) -> None:
+        collection = self.fixture.collection()
+        self.dialog.add_capture([collection], self.fixture.config)
+        expected = collection.traces[0].s21.copy()
+        collection.traces[0].s21.fill(0)
+        with self.assertRaisesRegex(ValueError, "X, Y и Z"):
+            self.dialog.calculation_inputs()
+        for column, coordinate in enumerate(self.fixture.target, start=2):
+            self.dialog._table.item(0, column).setText(str(coordinate))
+        groups, config, settings = self.dialog.calculation_inputs()
+        np.testing.assert_array_equal(groups[0]["collections"][0].traces[0].s21, expected)
+        self.assertEqual(groups[0]["target_scene_m"], self.fixture.target)
+        self.assertEqual(config, self.fixture.config)
+        self.assertEqual(settings["input_idx"], (2, 7))
+        self.assertEqual(settings["output_idx"], (1, 5))
+        self.dialog._table.item(0, 2).setText("nan")
+        with self.assertRaisesRegex(ValueError, "конечными"):
+            self.dialog.calculation_inputs()
+
+    def test_changed_geometry_is_rejected_without_appending_a_capture(self) -> None:
+        self._capture_with_target()
+        changed = copy.deepcopy(self.fixture.config)
+        changed["gpr"]["tx_geometry"][0]["x_m"] += 1
+        with self.assertRaisesRegex(ValueError, "изменились"):
+            self.dialog.add_capture([self.fixture.collection()], changed)
+        self.assertEqual(self.dialog._table.rowCount(), 1)
+
+    def test_actual_numeric_output_draws_both_target_phase_curves(self) -> None:
+        calibration = self.fixture.calibration()
+        self.dialog.show_calibration(calibration)
+        curves = self.dialog._phase_plot.listDataItems()
+        self.assertEqual(len(curves), 2)
+        diagnostic = calibration["meta"]["diagnostics"][0]
+        phases = np.array([diagnostic["phase_before_deg"], diagnostic["phase_after_deg"]]).reshape(2, -1)
+        expected = (phases - phases[0, 0] + 180) % 360 - 180
+        for curve, phases in zip(curves, expected):
+            np.testing.assert_allclose(curve.getData()[1], phases)
+        self.assertLess(np.ptp(curves[1].getData()[1]), .5)
+        self.assertIn(f"{diagnostic['coherence_before']:.3f}", self.dialog._quality_label.text())
+        self.assertIn(f"{diagnostic['coherence_after']:.3f}", self.dialog._quality_label.text())
+
+    def test_phase_wrap_uses_the_same_first_pair_baseline_for_both_curves(self) -> None:
+        calibration = self.fixture.calibration()
+        diagnostic = calibration["meta"]["diagnostics"][0]
+        diagnostic["phase_before_deg"] = [[179, -179], [178, -178]]
+        diagnostic["phase_after_deg"] = [[-179, -179], [-179, -179]]
+        self.dialog.show_calibration(calibration)
+        before, after = self.dialog._phase_plot.listDataItems()
+        np.testing.assert_allclose(before.getData()[1], [0, 2, -1, 3])
+        np.testing.assert_allclose(after.getData()[1], [2, 2, 2, 2])
+
+    def test_capture_and_calculation_disable_edits_but_keep_cancel_available(self) -> None:
+        self._capture_with_target()
+        for setter in (self.dialog.set_capture_pending, self.dialog.set_calculating):
+            setter(True)
+            self.assertFalse(self.dialog._capture_button.isEnabled())
+            self.assertFalse(self.dialog._table.isEnabled())
+            self.assertTrue(self.dialog._cancel_button.isEnabled())
+            setter(False)
+            self.assertTrue(self.dialog._capture_button.isEnabled())
+            self.assertTrue(self.dialog._table.isEnabled())
+
+
+class ObjectCalibrationWorkerTest(unittest.TestCase):
+    def _controller_with_data(self):
+        fixture = numeric_fixture.MimoCalibrationTest()
+        fixture.setUp()
+        owner = QWidget()
+        self.addCleanup(owner.close)
+        panel = SimpleNamespace(set_name=lambda: "sphere", set_set_name=mock.Mock(), set_status=mock.Mock())
+        current_config = SimpleNamespace(to_dict=lambda: copy.deepcopy(fixture.config))
+        owner._ensure_preprocess_dialog = mock.Mock(return_value=panel)
+        owner._build_config = mock.Mock(return_value=current_config)
+        owner._radar_key = mock.Mock(return_value="current-config-key")
+        owner._store = mock.Mock()
+        owner._selected_preprocess_sets = {}
+        for name in ("_show_exception", "_show_error", "_refresh_sets", "_log"):
+            setattr(owner, name, mock.Mock())
+        controller = ObjectCalibrationController(owner)
+        controller.open_creation()
+        self.addCleanup(controller.shutdown)
+        dialog = controller._dialog
+        dialog.add_capture([fixture.collection()], fixture.config)
+        for column, coordinate in enumerate(fixture.target, start=2):
+            dialog._table.item(0, column).setText(str(coordinate))
+        for key in ("sphere_radius_m", "antenna_height_m", "pitch_deg", "coarse_range_search_m"):
+            dialog._settings[key].setValue(getattr(fixture.settings, key))
+        for field in dialog._refine_axes.values():
+            field.setChecked(False)
+        return owner, controller, fixture, current_config
+
+    def _wait_for_completion(self, controller) -> None:
+        deadline = time.monotonic() + 5
+        while controller._worker is not None and time.monotonic() < deadline:
+            app.processEvents()
+            time.sleep(.005)
+        self.assertIsNone(controller._worker, "Background calculation did not complete")
+
+    def test_actual_calculation_runs_off_gui_thread_and_saves_under_current_config(self) -> None:
+        owner, controller, _, current_config = self._controller_with_data()
+        from python_app.workflows.mimo_calibration import compute_from_collections
+
+        worker_threads, gui_ticks = [], []
+
+        def compute(*args, **kwargs):
+            worker_threads.append(threading.get_ident())
+            return compute_from_collections(*args, **kwargs)
+
+        timer = QTimer()
+        timer.timeout.connect(lambda: gui_ticks.append(threading.get_ident()))
+        timer.start(1)
+        self.addCleanup(timer.stop)
+        with mock.patch("python_app.workflows.mimo_calibration.compute_from_collections", side_effect=compute):
+            controller._start_calculation()
+            self.assertTrue(controller._dialog._calculating)
+            self._wait_for_completion(controller)
+        owner._show_exception.assert_not_called()
+        self.assertEqual(len(worker_threads), 1)
+        self.assertNotEqual(worker_threads[0], threading.get_ident())
+        self.assertTrue(gui_ticks)
+        self.assertEqual(set(gui_ticks), {threading.get_ident()})
+        owner._radar_key.assert_called_once_with(current_config)
+        key, name, calibration = owner._store.save_object_calibration.call_args.args
+        self.assertEqual((key, name), ("current-config-key", "sphere"))
+        self.assertEqual(owner._selected_preprocess_sets["s21_object_calibration"], name)
+        self.assertEqual(len(controller._dialog._phase_plot.listDataItems()), 2)
+        self.assertGreater(calibration["meta"]["diagnostics"][0]["coherence_after"], .999)
+
+    def test_cancelled_background_calculation_keeps_samples_and_creates_no_saved_set(self) -> None:
+        owner, controller, _, _ = self._controller_with_data()
+        entered = threading.Event()
+
+        def compute(*_args, cancelled, progress, **_kwargs):
+            entered.set()
+            progress("Safe cancellation boundary")
+            while not cancelled():
+                time.sleep(.005)
+            raise InterruptedError
+
+        with mock.patch("python_app.workflows.mimo_calibration.compute_from_collections", side_effect=compute):
+            controller._start_calculation()
+            self.assertTrue(entered.wait(1))
+            controller.cancel()
+            self._wait_for_completion(controller)
+        owner._store.save_object_calibration.assert_not_called()
+        owner._show_exception.assert_not_called()
+        self.assertEqual(controller._dialog._table.rowCount(), 1)
+        self.assertTrue(controller._dialog._capture_button.isEnabled())
+        self.assertIn("отменён", controller._dialog._status_label.text())
+
+    def test_thread_start_failure_restores_editor_without_saving(self) -> None:
+        owner, controller, _, _ = self._controller_with_data()
+        with mock.patch("python_app.gui.controllers.object_calibration_controller.threading.Thread.start",
+                        side_effect=RuntimeError("thread limit")):
+            controller._start_calculation()
+        self.assertIsNone(controller._worker)
+        self.assertFalse(controller._dialog._calculating)
+        self.assertTrue(controller._dialog._capture_button.isEnabled())
+        owner._store.save_object_calibration.assert_not_called()
+        owner._show_exception.assert_called_once()
+        self.assertIn("thread limit", controller._dialog._status_label.text())
+
+    def test_capture_registration_failure_is_visible_and_does_not_leave_busy_dialog(self) -> None:
+        owner, controller, _, _ = self._controller_with_data()
+        with mock.patch("python_app.gui.controllers.object_calibration_capture.capture_object_sweeps",
+                        side_effect=RuntimeError("Capture already running")):
+            controller._capture_data()
+        self.assertIsNone(controller._capture)
+        self.assertTrue(controller._dialog._capture_button.isEnabled())
+        self.assertIn("Capture already running", controller._dialog._status_label.text())
+        owner._show_exception.assert_called_once()
+
+    def test_import_waits_for_capture_or_calculation_before_opening_file_picker(self) -> None:
+        owner, controller, _, _ = self._controller_with_data()
+        for busy in ("capture", "calculation"):
+            with self.subTest(busy=busy):
+                owner._object_capture_job = object() if busy == "capture" else None
+                controller._worker = mock.Mock() if busy == "calculation" else None
+                with mock.patch("python_app.gui.controllers.object_calibration_controller.QFileDialog.getExistingDirectory") as picker:
+                    controller.import_calibration()
+                picker.assert_not_called()
+                owner._show_error.assert_called()
+        controller._worker = None
+        owner._object_capture_job = None
+
+    def test_worker_uses_only_data_and_honours_cancellation_without_subtracting_another_background(self) -> None:
+        fixture = numeric_fixture.MimoCalibrationTest()
+        fixture.setUp()
+        cancelled, messages, result = threading.Event(), queue.Queue(), queue.Queue()
+        cancelled.set()
+        with mock.patch("python_app.workflows.mimo_calibration.compute_from_collections",
+                        side_effect=InterruptedError) as compute:
+            _calculate([{"collections": [fixture.collection()], "target_scene_m": fixture.target}],
+                       fixture.config, {}, cancelled, messages, result)
+        self.assertEqual(result.get_nowait(), ("cancelled", None))
+        self.assertNotIn("empty_collections", compute.call_args.kwargs)
+
+    def test_calculate_rejects_invalid_xyz_before_starting_a_worker(self) -> None:
+        owner = QWidget()
+        self.addCleanup(owner.close)
+        owner._ensure_preprocess_dialog = mock.Mock(return_value=SimpleNamespace(set_name=lambda: "sphere"))
+        owner._show_exception = mock.Mock()
+        controller = ObjectCalibrationController(owner)
+        controller.open_creation()
+        self.addCleanup(controller.shutdown)
+        fixture = numeric_fixture.MimoCalibrationTest()
+        fixture.setUp()
+        controller._dialog.add_capture([fixture.collection()], fixture.config)
+        with mock.patch("python_app.gui.controllers.object_calibration_controller.threading.Thread") as thread:
+            controller._start_calculation()
+        thread.assert_not_called()
+        owner._show_exception.assert_called_once()
+        self.assertFalse(controller._dialog._calculating)
+
+    def test_closing_cancels_capture_and_worker_without_waiting_for_a_thread(self) -> None:
+        owner = QWidget()
+        self.addCleanup(owner.close)
+        controller = ObjectCalibrationController(owner)
+        controller._dialog = ObjectCalibrationDialog("sphere", owner)
+        controller._capture = mock.Mock()
+        controller._worker = mock.Mock()
+        controller.shutdown()
+        self.assertTrue(controller._cancel.is_set())
+        controller._capture.cancel.assert_called_once()
+        controller._worker.join.assert_not_called()
+        self.assertFalse(controller._poll.isActive())

python_app/tests/test_object_calibration_runtime.py

@@ -0,0 +1,319 @@
+"""Object correction persistence, runtime export and capture lifecycle regressions."""
+
+from __future__ import annotations
+
+from copy import deepcopy
+from dataclasses import asdict
+import os
+from pathlib import Path
+import tempfile
+from types import SimpleNamespace
+import unittest
+from unittest import mock
+
+import numpy as np
+
+os.environ.setdefault("QT_QPA_PLATFORM", "offscreen")
+from PyQt6.QtWidgets import QApplication, QDialog  # noqa: E402
+
+from python_app.gui.controllers.object_calibration_capture import ObjectSweepCapture  # noqa: E402
+from python_app.gui.controllers.app_window_config.live_processing_mixin import AppWindowLiveProcessingMixin  # noqa: E402
+from python_app.gui.runtime.history import build_processor_run_signature, build_run_history_signature  # noqa: E402
+from python_app.models.dataset_model import ComboKey, SweepCollection, TraceData  # noqa: E402
+from python_app.models.run_config_model import (  # noqa: E402
+    ComboModel, GprRxGeometryModel, GprTxGeometryModel, RunConfigModel,
+)
+from python_app.orchestration.config_writer import ConfigWriter  # noqa: E402
+from python_app.orchestration.preprocess_assets import runtime_preprocess_asset_keys  # noqa: E402
+from python_app.orchestration.shm.decoder import decode_trace_collection  # noqa: E402
+from python_app.storage.npz.store import NpzStore  # noqa: E402
+from python_app.storage.npz.serialize import RAW_MAGIC  # noqa: E402
+from python_app.workflows.mimo_calibration import C_LIGHT, calibration_on_grid  # noqa: E402
+
+
+def setUpModule() -> None:
+    global _app
+    _app = QApplication.instance() or QApplication([])
+
+
+def _config() -> RunConfigModel:
+    config = RunConfigModel()
+    config.input_switch.positions = 3
+    config.output_switch.positions = 4
+    config.combos = [ComboModel(0, 1), ComboModel(2, 3)]
+    config.gpr.tx_geometry = [GprTxGeometryModel(1, -.4), GprTxGeometryModel(3, .4)]
+    config.gpr.rx_geometry = [GprRxGeometryModel(0, -.2), GprRxGeometryModel(2, .2)]
+    config.preprocess.s21.calibration.set_name = "through"
+    config.preprocess.s21.reference.set_name = "empty"
+    return config
+
+
+def _calibration(config: RunConfigModel) -> dict:
+    frequency = np.array([1e8, 2e8, 3e8])
+    parameters = np.array([[.3, .02, 0], [-.8, -.01, 0], [.4, .03, 0], [-.1, -.02, 0]])
+    corrections = np.exp(-1j * (parameters[:, 0, None] - 2 * np.pi * frequency * parameters[:, 1, None] / C_LIGHT))
+    return dict(
+        freq_hz=frequency, tx=corrections[:2], rx=corrections[2:],
+        pair=corrections[:2, None] * corrections[None, 2:], valid=np.ones(3, bool),
+        tx_output_pos=np.array([1, 3], np.int32), rx_input_pos=np.array([0, 2], np.int32),
+        antenna_params=parameters, dir=None,
+        meta={"geometry": {
+            "tx_xyz_m": [[entry.x_m, entry.y_m, entry.z_m] for entry in config.gpr.tx_geometry],
+            "rx_xyz_m": [[entry.x_m, entry.y_m, entry.z_m] for entry in config.gpr.rx_geometry],
+        }},
+    )
+
+
+class ObjectCalibrationStoreTest(unittest.TestCase):
+    def setUp(self) -> None:
+        temporary = tempfile.TemporaryDirectory()
+        self.addCleanup(temporary.cleanup)
+        self.root = Path(temporary.name)
+        self.store = NpzStore(self.root / "sets")
+        self.config = _config()
+        self.calibration = _calibration(self.config)
+        traces = [
+            TraceData(ComboKey(0, 1), np.array([1e8, 2e8, 3e8], np.float32), np.ones(3), np.ones(3)),
+            TraceData(ComboKey(2, 3), np.array([1.2e8, 1.8e8, 2.6e8], np.float32), np.ones(3), np.ones(3)),
+        ]
+        for kind, name in (("s21_calibration", "through"), ("s21_reference", "empty")):
+            self.store.save_set(kind, "radar", name, SweepCollection(1, 10, traces))
+
+    def test_default_disabled_and_legacy_config_round_trip(self) -> None:
+        payload = self.config.to_dict()
+        del payload["preprocess"]["s21"]["object_calibration"]
+        config = RunConfigModel.from_dict(payload)
+        self.assertEqual(config.preprocess.s21.object_calibration.set_name, "")
+        self.assertNotIn("s21_object_calibration", runtime_preprocess_asset_keys(config))
+        original_run = build_run_history_signature(config)
+        original_processor = build_processor_run_signature(config)
+        config.preprocess.s21.object_calibration.set_name = "object"
+        self.assertEqual(config.clone().preprocess.s21.object_calibration.set_name, "object")
+        self.assertIn("s21_object_calibration", runtime_preprocess_asset_keys(config))
+        self.assertNotEqual(original_run, build_run_history_signature(config))
+        self.assertEqual(original_processor, build_processor_run_signature(config))
+
+    def test_saved_set_retains_coefficients_and_refuses_overwrite(self) -> None:
+        self.store.save_object_calibration("radar", "object", self.calibration)
+        self.assertEqual(self.store.list_sets("s21_object_calibration", "radar"), ["object"])
+        loaded = self.store.load_object_calibration("radar", "object")
+        np.testing.assert_array_equal(loaded["pair"], self.calibration["pair"])
+        with self.assertRaises(FileExistsError):
+            self.store.save_object_calibration("radar", "object", self.calibration)
+        self.assertTrue(self.store.has_combo_coverage("s21_object_calibration", "radar", "object", [ComboKey(2, 3)]))
+        self.assertFalse(self.store.has_combo_coverage("s21_object_calibration", "radar", "object", [ComboKey(1, 3)]))
+        with self.assertRaises(ValueError):
+            self.store.load_object_calibration("radar", "../object")
+
+    def test_writer_exports_physical_pair_factors_on_each_runtime_grid(self) -> None:
+        self.store.save_object_calibration("radar", "object", self.calibration)
+        self.config.preprocess.s21.object_calibration.set_name = "object"
+        ConfigWriter(self.root / "runtime").prepare_preprocess_bundles(self.store, "radar", self.config)
+        bundle = Path(self.config.preprocess.s21.object_calibration.bundle_path)
+        collection = decode_trace_collection(bundle.read_bytes(), RAW_MAGIC)
+        self.assertEqual([trace.combo for trace in collection.traces], [ComboKey(0, 1), ComboKey(2, 3)])
+        for index, trace in enumerate(collection.traces):
+            np.testing.assert_allclose(trace.s21, calibration_on_grid(self.calibration, trace.frequency_hz)[index, index], rtol=1e-6)
+            np.testing.assert_array_equal(trace.s11, np.zeros(3))
+        self.config.preprocess.s21.object_calibration.set_name = ""
+        ConfigWriter(self.root / "runtime").prepare_preprocess_bundles(self.store, "radar", self.config)
+        self.assertEqual(self.config.preprocess.s21.object_calibration.bundle_path, "")
+
+    def test_invalid_geometry_or_correction_keeps_previous_export(self) -> None:
+        self.store.save_object_calibration("radar", "object", self.calibration)
+        destination = self.root / "factors.bin"
+        destination.write_bytes(b"previous bundle")
+        self.config.gpr.tx_geometry[0].z_m = .1
+        with self.assertRaisesRegex(ValueError, "geometry"):
+            self.store.export_object_calibration_bundle("radar", "object", destination, self.config)
+        self.assertEqual(destination.read_bytes(), b"previous bundle")
+        broken = deepcopy(self.calibration)
+        broken["pair"][0, 0, 0] = np.nan
+        with self.assertRaises(ValueError):
+            self.store.save_object_calibration("radar", "bad", broken)
+        self.assertEqual(self.store.list_sets("s21_object_calibration", "radar"), ["object"])
+
+
+class ObjectCaptureLifecycleTest(unittest.TestCase):
+    def setUp(self) -> None:
+        self.dialog = mock.Mock()
+        self.owner = SimpleNamespace(
+            _stop_request_seq=0, _capture_session=None, _preprocess_capture_busy=False,
+            _single_capture_active=False, _recording_active=False, _closing=False,
+            _build_config=lambda: _config(), _pre_history=[], _SINGLE_CAPTURE_TIMEOUT_S=300,
+            _ensure_preprocess_dialog=lambda: SimpleNamespace(median_sweep_count=lambda: 2),
+            _supervisor=SimpleNamespace(is_running=lambda: self.running),
+        )
+        self.running = False
+        self.owner._pipeline_resume_allowed = lambda seq: not self.owner._closing and seq == self.owner._stop_request_seq
+        self.owner._stop_run = mock.Mock(side_effect=self._stop)
+        self.owner._start_run = mock.Mock(side_effect=self._start)
+
+    def _stop(self) -> None:
+        self.running = False
+        self.owner._stop_request_seq += 1
+
+    def _start(self, **_kwargs) -> None:
+        self.running = True
+
+    def _capture(self) -> ObjectSweepCapture:
+        with mock.patch("python_app.gui.controllers.object_calibration_capture.QTimer.singleShot"):
+            view = QDialog()
+            view.add_capture = self.dialog.add_capture
+            view.set_status = self.dialog.set_status
+            view.set_capture_pending = self.dialog.set_capture_pending
+            self.addCleanup(view.close)
+            self.view = view
+            return ObjectSweepCapture(self.owner, view)
+
+    def test_captures_fresh_preprocessed_matrix_without_changing_selected_object(self) -> None:
+        config = _config()
+        config.preprocess.s21.object_calibration.set_name = "existing"
+        self.owner._build_config = lambda: config.clone()
+        self.running = True
+        capture = self._capture()
+        capture._start()
+        override = self.owner._start_run.call_args.kwargs["config_override"]
+        self.assertEqual(override.preprocess.s21.object_calibration.set_name, "")
+        self.assertEqual(len(override.combos), 4)
+        self.assertEqual(config.preprocess.s21.object_calibration.set_name, "existing")
+        stale = SweepCollection(1, capture._start_ns - 1)
+        first, second = SweepCollection(2, capture._start_ns + 1), SweepCollection(3, capture._start_ns + 2)
+        self.owner._pre_history = [stale, first, first, second]
+        capture._poll()
+        self.dialog.add_capture.assert_called_once()
+        self.assertEqual([c.collection_id for c in self.dialog.add_capture.call_args.args[0]], [2, 3])
+        self.assertEqual(self.owner._start_run.call_count, 2)
+        self.assertEqual(self.owner._start_run.call_args.kwargs, {})
+        capture.cancel()
+        self.assertEqual(self.owner._stop_run.call_count, 2)
+
+    def test_stop_cancels_capture_and_prevents_automatic_resume(self) -> None:
+        self.running = True
+        capture = self._capture()
+        capture._start()
+        self.owner._stop_run()
+        capture._poll()
+        self.dialog.add_capture.assert_not_called()
+        self.assertEqual(self.owner._start_run.call_count, 1)
+        self.assertFalse(self.running)
+
+    def test_recording_is_not_interrupted(self) -> None:
+        self.owner._recording_active = True
+        capture = self._capture()
+        capture._start()
+        self.owner._start_run.assert_not_called()
+        self.owner._stop_run.assert_not_called()
+        self.dialog.add_capture.assert_not_called()
+        self.dialog.set_capture_pending.assert_called_once_with(False)
+
+    def test_stop_before_queued_start_never_opens_acquisition(self) -> None:
+        capture = self._capture()
+        self.owner._stop_run()
+        capture._start()
+        self.owner._start_run.assert_not_called()
+        self.assertIsNone(self.owner._object_capture_job)
+
+    def test_stale_capture_does_not_stop_a_new_run_after_explicit_stop(self) -> None:
+        capture = self._capture()
+        capture._start()
+        self.owner._stop_run()
+        self.owner._start_run()
+        capture._poll()
+        self.assertEqual(self.owner._stop_run.call_count, 1)
+        self.assertTrue(self.running)
+        self.dialog.add_capture.assert_not_called()
+
+    def test_second_capture_is_rejected_without_mutating_first(self) -> None:
+        first = self._capture()
+        with self.assertRaisesRegex(RuntimeError, "already in progress"):
+            self._capture()
+        self.assertIs(self.owner._object_capture_job, first)
+        first.cancel()
+
+    def test_rejected_data_still_restores_original_running_pipeline(self) -> None:
+        self.running = True
+        self.dialog.add_capture.side_effect = ValueError("configuration changed")
+        capture = self._capture()
+        capture._start()
+        self.owner._pre_history = [SweepCollection(2, capture._start_ns + 1), SweepCollection(3, capture._start_ns + 2)]
+        capture._poll()
+        self.assertTrue(self.running)
+        self.assertEqual(self.owner._start_run.call_count, 2)
+        self.assertIsNone(self.owner._object_capture_job)
+
+    def test_capture_lock_is_held_while_stop_drains_events(self) -> None:
+        capture = self._capture()
+        capture._start()
+        locks = []
+        original_stop = self.owner._stop_run.side_effect
+        self.owner._stop_run.side_effect = lambda: (locks.append(self.owner._object_capture_job), original_stop())
+        capture.cancel()
+        self.assertEqual(locks, [capture])
+        self.assertIsNone(self.owner._object_capture_job)
+
+    def test_old_acquisition_with_new_preprocessing_timestamp_is_not_captured(self) -> None:
+        capture = self._capture()
+        capture._start()
+        stale = SweepCollection(1, capture._start_ns + 100, capture_start_ns=capture._start_ns - 100)
+        self.owner._pre_history = [stale]
+        capture._poll()
+        self.assertEqual(capture._collections, [])
+        capture.cancel()
+
+    def test_replay_is_rejected_before_acquisition(self) -> None:
+        config = _config()
+        config.radar.replay.dataset_dir = "saved_scene"
+        self.owner._build_config = lambda: config
+        capture = self._capture()
+        capture._start()
+        self.owner._start_run.assert_not_called()
+
+
+class ObjectGeometryLifecycleTest(unittest.TestCase):
+    def setUp(self) -> None:
+        config = _config()
+        config.preprocess.s21.object_calibration.set_name = "object"
+        self.tx, self.rx = [asdict(entry) for entry in config.gpr.tx_geometry], [asdict(entry) for entry in config.gpr.rx_geometry]
+        self.owner = SimpleNamespace(
+            _selected_preprocess_sets={"s21_object_calibration": "object"}, _selected_preprocess_radar_key="radar",
+            _store=SimpleNamespace(load_object_calibration=mock.Mock(return_value=_calibration(config))),
+            _gpr_tx_geometry_input=SimpleNamespace(records=lambda: self.tx),
+            _gpr_rx_geometry_input=SimpleNamespace(records=lambda: self.rx),
+            _supervisor=SimpleNamespace(is_running=lambda: True), _preprocess_dialog=mock.Mock(),
+            _stop_request_seq=0, _refresh_preprocess_summary_labels=mock.Mock(), _start_run=mock.Mock(), _log_warning=mock.Mock(),
+            _active_run_config=config, _radar_key=lambda _config: "radar",
+        )
+        self.owner._pipeline_resume_allowed = lambda seq: seq == self.owner._stop_request_seq
+        self.owner._stop_run = mock.Mock(side_effect=lambda: setattr(self.owner, "_stop_request_seq", self.owner._stop_request_seq + 1))
+
+    def test_same_geometry_retains_object_correction_without_restart(self) -> None:
+        AppWindowLiveProcessingMixin._invalidate_object_calibration_after_geometry_change(self.owner)
+        self.assertEqual(self.owner._selected_preprocess_sets["s21_object_calibration"], "object")
+        self.owner._stop_run.assert_not_called()
+        self.owner._start_run.assert_not_called()
+
+    def test_changed_geometry_disables_correction_and_reloads_acquisition(self) -> None:
+        self.tx[0]["z_m"] = .1
+        AppWindowLiveProcessingMixin._invalidate_object_calibration_after_geometry_change(self.owner)
+        self.assertEqual(self.owner._selected_preprocess_sets["s21_object_calibration"], "")
+        self.owner._stop_run.assert_called_once()
+        self.owner._start_run.assert_called_once()
+        self.owner._log_warning.assert_called_once()
+
+    def test_explicit_stop_during_geometry_change_prevents_resume(self) -> None:
+        self.tx[0]["z_m"] = .1
+        self.owner._stop_run.side_effect = lambda: setattr(self.owner, "_stop_request_seq", self.owner._stop_request_seq + 2)
+        AppWindowLiveProcessingMixin._invalidate_object_calibration_after_geometry_change(self.owner)
+        self.owner._start_run.assert_not_called()
+
+    def test_pending_off_selection_still_reloads_an_incompatible_active_correction(self) -> None:
+        self.owner._selected_preprocess_sets["s21_object_calibration"] = ""
+        self.tx[0]["z_m"] = .1
+        AppWindowLiveProcessingMixin._invalidate_object_calibration_after_geometry_change(self.owner)
+        self.owner._stop_run.assert_called_once()
+        self.owner._start_run.assert_called_once()
+
+
+if __name__ == "__main__":
+    unittest.main()

python_app/tests/test_recording_mixin.py

@@ -19,7 +19,9 @@ import numpy as np
 
 from python_app.gui.controllers import app_window_recording_mixin as rec
 from python_app.gui.controllers.app_window_recording_mixin import AppWindowRecordingMixin
+from python_app.gui.controllers.app_window_config.profile_io_mixin import AppWindowConfigProfileIOMixin
 from python_app.models.dataset_model import ComboKey, SweepCollection, TraceData
+from python_app.models.gui_profile_model import GuiProfileModel
 from python_app.storage.npz.store import NpzStore
 
 
@@ -113,7 +115,7 @@ class _Harness(AppWindowRecordingMixin):
     def _snapshot_config_profile_path(self, directory):
         return Path(directory) / "config_profile.json"
 
-    def _write_gui_profile_to_path(self, path, allow_overwrite) -> None:
+    def _write_gui_profile_to_path(self, path, allow_overwrite=True, dataset=False) -> None:
         self.profiles.append((path, allow_overwrite))
 
     def _start_run(self) -> None:
@@ -162,7 +164,7 @@ class RecordingArmTest(_RecordingTestBase):
             h._save_path_input = _Text(str(Path(temporary) / "datasets"))
             destination = Path(temporary) / "datasets/pref_run"
 
-            def write_profile(path, allow_overwrite):
+            def write_profile(path, allow_overwrite=True, dataset=False):
                 path.write_text("fresh profile", encoding="utf-8")
 
             with mock.patch.object(h, "_write_gui_profile_to_path", side_effect=write_profile):
@@ -210,6 +212,57 @@ class RecordingArmTest(_RecordingTestBase):
         self.assertFalse(h.started)
         self.assertTrue(h._recording_active)
 
+    def test_running_recording_profile_uses_applied_object_calibration(self) -> None:
+        for applied, selected in (("", "next_run"), ("applied", "")):
+            with self.subTest(applied=applied), tempfile.TemporaryDirectory() as temporary:
+                h = self._make(count=3, running=True)
+                h._store = NpzStore(Path(temporary) / "sets")
+                h._save_path_input = _Text(str(Path(temporary) / "datasets"))
+                pending = GuiProfileModel()
+                pending.run_config.preprocess.s21.object_calibration.set_name = selected
+                h._active_run_config = pending.run_config.clone()
+                h._active_run_config.preprocess.s21.object_calibration.set_name = applied
+                h._active_run_config.preprocess.s21.object_calibration.bundle_path = "/bundles/applied" if applied else ""
+                h._build_gui_profile = pending.clone
+                with mock.patch.object(h, "_write_gui_profile_to_path", side_effect=lambda *args, **kwargs:
+                                       AppWindowConfigProfileIOMixin._write_gui_profile_to_path(h, *args, **kwargs)):
+                    h._start_run_with_recording()
+                path = Path(temporary) / "datasets/pref_run/config_profile.json"
+                recorded = GuiProfileModel.load_from_path(path)
+                self.assertEqual(recorded.run_config.preprocess, h._active_run_config.preprocess)
+                self.assertFalse(h.started)
+                self.assertEqual(h.exceptions, [])
+
+    def test_new_recording_profile_uses_new_run_instead_of_previous_history(self) -> None:
+        with tempfile.TemporaryDirectory() as temporary:
+            h = self._make(count=3, running=False)
+            h._store = NpzStore(Path(temporary) / "sets")
+            h._save_path_input = _Text(str(Path(temporary) / "datasets"))
+            pending = GuiProfileModel()
+            pending.run_config.preprocess.s21.object_calibration.set_name = "next_run"
+            h._active_run_config = pending.run_config.clone()
+            h._active_run_config.preprocess.s21.object_calibration.set_name = "previous_run"
+            h._build_gui_profile = pending.clone
+            path = Path(temporary) / "datasets/pref_run/config_profile.json"
+
+            def start_new_run():
+                initial = GuiProfileModel.load_from_path(path)
+                self.assertEqual(initial.run_config.preprocess, pending.run_config.preprocess)
+                h._active_run_config = pending.run_config.clone()
+                h._active_run_config.preprocess.s21.object_calibration.bundle_path = "/bundles/new_object"
+                h._active_run_config.preprocess.s21.calibration.bundle_path = "/bundles/new_through"
+                h._supervisor._running = True
+
+            with mock.patch.object(h, "_start_run", side_effect=start_new_run), mock.patch.object(
+                h, "_write_gui_profile_to_path", side_effect=lambda *args, **kwargs:
+                    AppWindowConfigProfileIOMixin._write_gui_profile_to_path(h, *args, **kwargs),
+            ):
+                h._start_run_with_recording()
+            recorded = GuiProfileModel.load_from_path(path)
+            self.assertEqual(recorded.run_config.preprocess, h._active_run_config.preprocess)
+            self.assertEqual(h.exceptions, [])
+            self.assertTrue(h._recording_active)
+
     def test_arm_refuses_when_destination_exists(self) -> None:
         h = self._make(count=3, running=True, dest_exists=True)
         h._start_run_with_recording()
@@ -248,7 +301,7 @@ class RecordingArmTest(_RecordingTestBase):
                     traces=[TraceData(ComboKey(0, 0), np.array([1e9], dtype=np.float32), samples, samples)],
                 ))
 
-            def write_profile(path, allow_overwrite):
+            def write_profile(path, allow_overwrite=True, dataset=False):
                 path.write_text('retained configuration', encoding='utf-8')
 
             with mock.patch.object(h, '_start_run', side_effect=failed_start), mock.patch.object(

python_app/workflows/mimo_calibration.py

@@ -0,0 +1,792 @@
+"""Object-based MIMO S21 corrections estimated after standard preprocessing.
+
+Archives retain the standalone script's cal_*.npy/cal_meta.json layout. Pair
+corrections multiply S21 after through calibration, reference subtraction and
+notch filtering; they never alter S11 or the original measurement files.
+"""
+
+from __future__ import annotations
+
+from contextlib import contextmanager
+from collections.abc import Callable, Iterable, Sequence
+from dataclasses import dataclass
+import datetime
+import json
+import logging
+from pathlib import Path
+import re
+import shutil
+import tempfile
+from typing import Any
+
+import numpy as np
+from numpy.typing import ArrayLike
+
+from python_app.file_io import atomic_write_json
+from python_app.models.dataset_model import SweepCollection
+
+C_LIGHT = 299_792_458.0
+_CAL_ARRAYS = ('freq_hz', 'pair', 'tx', 'rx', 'valid', 'tx_output_pos', 'rx_input_pos', 'antenna_params')
+logger = logging.getLogger(__name__)
+
+
+def _ports(values, label):
+    array = np.asarray(values)
+    if array.ndim != 1 or not array.size or array.dtype.kind not in 'iu':
+        raise ValueError(f'{label} must contain distinct nonnegative integer ports')
+    if np.any(array < 0) or np.any(array > np.iinfo(np.int32).max) or np.unique(array).size != array.size:
+        raise ValueError(f'{label} must contain distinct nonnegative integer ports')
+    return tuple(int(value) for value in array)
+
+
+def _finite_array(value, label, shape=None, *, complex_values=False):
+    array = np.asarray(value, dtype=complex if complex_values else float)
+    if (shape is not None and array.shape != shape) or not np.all(np.isfinite(array)):
+        raise ValueError(f'{label} has an invalid shape or non-finite values')
+    return array
+
+
+def _frequency(value, *, uniform=False):
+    freq = _finite_array(value, 'frequency axis')
+    if freq.ndim != 1 or freq.size < 2 or freq[0] < 0 or np.any(np.diff(freq) <= 0):
+        raise ValueError('frequency axis must be increasing with at least two samples')
+    # Dataset frequency axes are float32; account for their quantization at GHz.
+    tolerance = max(1e-3, 2 * np.finfo(np.float32).eps * float(freq[-1]))
+    if uniform and not np.allclose(np.diff(freq), np.median(np.diff(freq)), rtol=1e-5, atol=tolerance):
+        raise ValueError('calibration requires a uniform frequency grid')
+    return freq
+
+
+@dataclass
+class Settings:
+    """Target geometry and estimation options, independent of example globals."""
+    sphere_radius_m: float = .16
+    input_idx: tuple[int, ...] = (0, 1, 2, 3)
+    output_idx: tuple[int, ...] = (0, 1, 2, 3)
+    antenna_height_m: float = .92
+    pitch_deg: float = 10.
+    f_min: float = 2e9
+    f_max: float = 6e9
+    gate_half_m: float = .15
+    gate_taper_m: float = .03
+    coarse_range_search_m: float = .6
+    refine_axes: tuple[str, ...] = ('x', 'y', 'z')
+    refine_range_m: float = .10
+    apply_amplitude: bool = False
+    phase_model: str = 'linear'
+
+    def __post_init__(self):
+        self.input_idx = tuple(sorted(_ports(self.input_idx, 'input_idx')))
+        self.output_idx = tuple(sorted(_ports(self.output_idx, 'output_idx')))
+        for name in ('sphere_radius_m', 'antenna_height_m', 'pitch_deg', 'f_min', 'f_max',
+                     'gate_half_m', 'gate_taper_m', 'coarse_range_search_m', 'refine_range_m'):
+            value = getattr(self, name)
+            if isinstance(value, bool) or not np.isfinite(value):
+                raise ValueError(f'{name} must be finite')
+        if min(self.sphere_radius_m, self.antenna_height_m, self.coarse_range_search_m, self.refine_range_m, self.f_min) < 0:
+            raise ValueError('radius, height, frequencies and search ranges must be nonnegative')
+        if self.f_max <= self.f_min or min(self.gate_half_m, self.gate_taper_m) <= 0:
+            raise ValueError('calibration band and gate must have positive widths')
+        if self.phase_model not in ('const', 'linear', 'poly3', 'raw'):
+            raise ValueError('phase_model must be const, linear, poly3 or raw')
+        if len(set(self.refine_axes)) != len(self.refine_axes) or any(axis not in 'xyz' or len(axis) != 1 for axis in self.refine_axes):
+            raise ValueError('refine_axes must contain distinct x/y/z axes')
+        if not isinstance(self.apply_amplitude, bool):
+            raise ValueError('apply_amplitude must be boolean')
+
+
+def find_config_profile(start: str | Path, max_levels: int = 8) -> Path:
+    """Locate the archived acquisition profile above a stage or snapshot folder."""
+    path = Path(start)
+    for _ in range(max_levels):
+        candidate = path / 'config_profile.json'
+        if candidate.is_file():
+            return candidate
+        path = path.parent
+    raise FileNotFoundError(f'config_profile.json not found above {start}')
+
+
+def _profile(path):
+    config = json.loads(Path(path).read_text(encoding='utf-8'))
+    if not isinstance(config, dict):
+        raise ValueError('config_profile.json must contain an object')
+    return config
+
+
+def _geometry(config, input_idx, output_idx):
+    result = []
+    for key, identity, ports in (('tx_geometry', 'output_pos', output_idx), ('rx_geometry', 'input_pos', input_idx)):
+        entries = config.get('gpr', {}).get(key, [])
+        mapping = {}
+        for entry in entries:
+            port = _ports([entry[identity]], identity)[0]
+            if port in mapping:
+                raise ValueError(f'duplicate antenna geometry for {identity}={port}')
+            mapping[port] = _finite_array([entry['x_m'], entry.get('y_m', 0.), entry.get('z_m', 0.)], key, (3,))
+        missing = set(ports) - mapping.keys()
+        if missing:
+            raise ValueError(f'{key} is missing physical ports {sorted(missing)}')
+        result.append(np.array([mapping[port] for port in ports]))
+    return tuple(result)
+
+
+def load_geometry(config_path: str | Path, input_idx: Sequence[int], output_idx: Sequence[int]) -> tuple[np.ndarray, np.ndarray]:
+    """Read TX/RX radar coordinates in sorted physical port order."""
+    return _geometry(_profile(config_path), sorted(_ports(input_idx, 'input_idx')), sorted(_ports(output_idx, 'output_idx')))
+
+
+def list_snapshots(root: str | Path, prefixes: Sequence[str] | None = None) -> list[Path]:
+    """Select complete snapshot directories, requiring unambiguous prefixes."""
+    directories = sorted(path for path in Path(root).iterdir() if path.is_dir() and (path / 'meta.json').is_file())
+    if prefixes is None:
+        selected = directories
+    else:
+        selected = []
+        for prefix in prefixes:
+            matches = [path for path in directories if path.name.startswith(str(prefix))]
+            if len(matches) != 1 or matches[0] in selected:
+                raise ValueError(f'snapshot prefix {prefix!r} must select exactly one distinct snapshot in {root}')
+            selected.extend(matches)
+    if not selected:
+        raise ValueError(f'no snapshots selected in {root}')
+    return selected
+
+
+def load_s21(snapshot_dir: str | Path, input_idx: Sequence[int], output_idx: Sequence[int]) -> tuple[np.ndarray, np.ndarray]:
+    """Read a finite TX×RX×frequency matrix on one shared uniform grid."""
+    inputs = sorted(_ports(input_idx, 'input_idx'))
+    outputs = sorted(_ports(output_idx, 'output_idx'))
+    rows, freq = [], None
+    for output in outputs:
+        row = []
+        for input_ in inputs:
+            suffix = f'i{input_}_o{output}'
+            samples = np.load(Path(snapshot_dir) / f'{suffix}_s21.npy', allow_pickle=False)
+            axis = _frequency(np.load(Path(snapshot_dir) / f'{suffix}_freq.npy', allow_pickle=False), uniform=True)
+            if freq is not None and not np.array_equal(axis, freq):
+                raise ValueError(f'frequency grids differ between pairs in {snapshot_dir}')
+            freq = axis
+            row.append(_finite_array(samples, suffix, freq.shape, complex_values=True))
+        rows.append(row)
+    assert freq is not None
+    return np.array(rows), freq
+
+
+def _source_signature(config) -> dict[str, Any]:
+    radar = config.get('radar', {})
+    s21 = config.get('preprocess', {}).get('s21', {})
+    return {
+        'radar': {key: radar[key] for key in ('model', 'serial') if key in radar},
+        'slave_serials': radar.get('multi_device', {}).get('slave_serials', []),
+        's21_calibration_set': s21.get('calibration', {}).get('set_name', ''),
+        's21_reference_set': s21.get('reference', {}).get('set_name', ''),
+        'notch': config.get('preprocess', {}).get('notch', {}),
+    }
+
+
+def validate_calibration(cal: dict[str, Any]) -> None:
+    """Validate an archive before saving, applying or exporting runtime factors."""
+    freq = _frequency(cal['freq_hz'], uniform=True)
+    tx = _ports(cal['tx_output_pos'], 'tx_output_pos')
+    rx = _ports(cal['rx_input_pos'], 'rx_input_pos')
+    if tx != tuple(sorted(tx)) or rx != tuple(sorted(rx)):
+        raise ValueError('calibration physical ports must be sorted')
+    T = _finite_array(cal['tx'], 'tx corrections', (len(tx), freq.size), complex_values=True)
+    R = _finite_array(cal['rx'], 'rx corrections', (len(rx), freq.size), complex_values=True)
+    pair = _finite_array(cal['pair'], 'pair corrections', (len(tx), len(rx), freq.size), complex_values=True)
+    if np.any(np.abs(T) == 0) or np.any(np.abs(R) == 0) or np.any(np.abs(pair) == 0):
+        raise ValueError('calibration corrections must be nonzero')
+    if not np.allclose(pair, T[:, None, :] * R[None, :, :], rtol=2e-5, atol=1e-7):
+        raise ValueError('pair corrections disagree with tx/rx corrections')
+    valid = np.asarray(cal['valid'])
+    if valid.dtype.kind != 'b' or valid.shape != freq.shape or valid.sum() < 2:
+        raise ValueError('calibration valid mask must select at least two frequencies')
+    _finite_array(cal['antenna_params'], 'antenna parameters', (len(tx) + len(rx), 3))
+    geometry = cal['meta']['geometry']
+    _finite_array(geometry['tx_xyz_m'], 'TX geometry', (len(tx), 3))
+    _finite_array(geometry['rx_xyz_m'], 'RX geometry', (len(rx), 3))
+
+
+def validate_for_config(cal: dict[str, Any], config: dict[str, Any]) -> None:
+    """Require physical geometry, combo coverage and a compatible phase base."""
+    validate_calibration(cal)
+    tx, rx = _geometry(config, cal['rx_input_pos'], cal['tx_output_pos'])
+    geometry = cal['meta']['geometry']
+    if not (np.allclose(tx, geometry['tx_xyz_m'], rtol=0, atol=1e-9) and
+            np.allclose(rx, geometry['rx_xyz_m'], rtol=0, atol=1e-9)):
+        raise ValueError('antenna geometry differs from the object calibration')
+    for combo in config.get('run', {}).get('combos', []):
+        input_, output = _ports([combo['input']], 'combo input')[0], _ports([combo['output']], 'combo output')[0]
+        if input_ not in cal['rx_input_pos'] or output not in cal['tx_output_pos']:
+            raise ValueError(f'object calibration does not cover combo {combo}')
+    source = cal['meta'].get('source_preprocess', {})
+    current = _source_signature(config)
+    for key in ('radar', 'slave_serials', 's21_calibration_set'):
+        if source.get(key) and current.get(key) and source[key] != current[key]:
+            raise ValueError(f'object calibration source differs: {key}')
+
+
+@contextmanager
+def _staged_directory(destination, overwrite, *, preserve_existing=False):
+    destination = Path(destination)
+    destination.parent.mkdir(parents=True, exist_ok=True)
+    if destination.exists() and (not overwrite or not destination.is_dir() or destination.is_symlink()):
+        raise FileExistsError(f'{destination} already exists; choose another name or overwrite=True')
+    stage = Path(tempfile.mkdtemp(prefix=f'.{destination.name}.new-', dir=destination.parent))
+    backup = None
+    retain = False
+    try:
+        if preserve_existing and destination.exists():
+            shutil.copytree(destination, stage, dirs_exist_ok=True, symlinks=True)
+        yield stage
+        if destination.exists():
+            if not overwrite:
+                raise FileExistsError(f'{destination} appeared during save; choose another name or overwrite=True')
+            backup = Path(tempfile.mkdtemp(prefix=f'.{destination.name}.old-', dir=destination.parent))
+            backup.rmdir()
+            destination.replace(backup)
+        try:
+            stage.replace(destination)
+        except BaseException:
+            if backup is not None:
+                try:
+                    backup.replace(destination)
+                except OSError as error:
+                    retain = True
+                    raise RuntimeError(f'calibration rollback failed; originals retained at {backup}, new files at {stage}') from error
+            raise
+    finally:
+        if not retain:
+            for temporary in (stage, backup):
+                if temporary is not None and temporary.exists():
+                    try:
+                        shutil.rmtree(temporary)
+                    except OSError:
+                        logger.exception('Could not remove calibration temporary directory %s', temporary)
+
+
+def save_calibration(cal: dict[str, Any], cal_dir: str | Path, overwrite: bool = False) -> Path:
+    """Commit a complete legacy archive, restoring its predecessor on failure."""
+    validate_calibration(cal)
+    destination = Path(cal_dir)
+    if destination.is_dir() and any(destination.glob('cal_*')) and not overwrite:
+        raise FileExistsError(f'{destination} already contains calibration files; use overwrite=True')
+    meta: dict[str, Any] = dict(cal['meta'], name=destination.name)
+    # Older one-target archives used nonstandard JSON NaN for unavailable LOO.
+    quality = dict(meta.get('quality', {}))
+    if 'coherence_leave_one_out' in quality:
+        quality['coherence_leave_one_out'] = [value if value is None or np.isfinite(value) else None for value in quality['coherence_leave_one_out']]
+        meta['quality'] = quality
+    with _staged_directory(destination, overwrite or destination.is_dir(), preserve_existing=True) as stage:
+        for key in _CAL_ARRAYS:
+            path = stage / f'cal_{key}.npy'
+            path.unlink(missing_ok=True)
+            np.save(path, cal[key], allow_pickle=False)
+        (stage / 'cal_meta.json').unlink(missing_ok=True)
+        atomic_write_json(stage / 'cal_meta.json', meta)
+    cal['meta'], cal['dir'] = meta, destination
+    return destination
+
+
+def load_calibration(cal_dir: str | Path) -> dict[str, Any]:
+    """Load and validate cal_*.npy arrays plus cal_meta.json without pickle."""
+    directory = Path(cal_dir)
+    cal: dict[str, Any] = {key: np.load(directory / f'cal_{key}.npy', allow_pickle=False) for key in _CAL_ARRAYS}
+    cal.update(meta=json.loads((directory / 'cal_meta.json').read_text(encoding='utf-8')), dir=directory)
+    validate_calibration(cal)
+    return cal
+
+
+def calibration_on_grid(cal: dict[str, Any], freq: ArrayLike) -> np.ndarray:
+    """Interpolate separable corrections and continue phase smoothly at edges."""
+    validate_calibration(cal)
+    freq = _frequency(freq)
+    fc = np.asarray(cal['freq_hz'])
+    if np.array_equal(freq, fc):
+        return cal['pair']
+
+    def interp(correction, params):
+        phase = np.unwrap(np.angle(correction))
+        out = np.interp(freq, fc, phase)
+        slope = 2 * np.pi * params[1] / C_LIGHT
+        for selected, edge in ((freq < fc[0], 0), (freq > fc[-1], -1)):
+            out[selected] = phase[edge] + slope * (freq[selected] - fc[edge])
+        return np.interp(freq, fc, np.abs(correction)) * np.exp(1j * out)
+
+    n_tx = len(cal['tx_output_pos'])
+    tx = np.array([interp(value, cal['antenna_params'][index]) for index, value in enumerate(cal['tx'])])
+    rx = np.array([interp(value, cal['antenna_params'][n_tx + index]) for index, value in enumerate(cal['rx'])])
+    corrections = (tx[:, None, :] * rx[None, :, :]).astype(np.asarray(cal['pair']).dtype)
+    _finite_array(corrections, 'interpolated corrections', complex_values=True)
+    return corrections
+
+
+def apply_calibration(s21: ArrayLike, freq: ArrayLike, cal: dict[str, Any]) -> np.ndarray:
+    """Multiply a TX×RX×frequency S21 matrix by validated pair corrections."""
+    corrections = calibration_on_grid(cal, freq)
+    samples = _finite_array(s21, 'S21', corrections.shape, complex_values=True)
+    return _finite_array(samples * corrections, 'corrected S21', corrections.shape, complex_values=True)
+
+
+def apply_to_measurement(meas_dir: str | Path, cal: dict[str, Any], overwrite: bool = False) -> tuple[Path, int, int, int]:
+    """Stage corrected S21 and copied companion files in postprocessed safely."""
+    directory = Path(meas_dir)
+    pre, post = directory / 'preprocessed', directory / 'postprocessed'
+    if not pre.is_dir():
+        raise FileNotFoundError(f'no {pre}')
+    config = _profile(find_config_profile(pre))
+    _reject_corrected_source(config)
+    validate_for_config(cal, config)
+    if post.exists() and overwrite and not (post / 'calibration_applied.json').is_file():
+        raise FileExistsError(f'{post} has no calibration_applied.json; refusing to replace it')
+    tx = {int(port): index for index, port in enumerate(cal['tx_output_pos'])}
+    rx = {int(port): index for index, port in enumerate(cal['rx_input_pos'])}
+    pattern = re.compile(r'^i(\d+)_o(\d+)_s21\.npy$')
+    n_snap = n_fix = n_copy = 0
+    cache = {}
+    with _staged_directory(post, overwrite) as stage:
+        for item in sorted(pre.iterdir()):
+            if item.is_file():
+                shutil.copy2(item, stage / item.name)
+                n_copy += 1
+                continue
+            out = stage / item.name
+            out.mkdir()
+            n_snap += 1
+            for path in sorted(item.iterdir()):
+                match = pattern.match(path.name)
+                if path.is_dir() or match is None:
+                    if path.is_dir():
+                        shutil.copytree(path, out / path.name)
+                    else:
+                        shutil.copy2(path, out / path.name)
+                    n_copy += 1
+                    continue
+                input_, output = int(match[1]), int(match[2])
+                if input_ not in rx or output not in tx:
+                    raise ValueError(f'object calibration does not cover {path.name}')
+                freq = _frequency(np.load(item / f'i{input_}_o{output}_freq.npy', allow_pickle=False))
+                key = freq.tobytes()
+                if key not in cache:
+                    cache[key] = calibration_on_grid(cal, freq)
+                samples = np.load(path, allow_pickle=False)
+                dtype = samples.dtype
+                samples = _finite_array(samples, path.name, freq.shape, complex_values=True)
+                corrected = (samples * cache[key][tx[output], rx[input_]]).astype(dtype)
+                _finite_array(corrected, 'corrected S21', complex_values=True)
+                np.save(out / path.name, corrected, allow_pickle=False)
+                n_fix += 1
+        atomic_write_json(stage / 'calibration_applied.json', dict(
+            calibration=cal['meta'].get('name'), calibration_dir=str(cal.get('dir') or ''),
+            created=datetime.datetime.now().isoformat(timespec='seconds'), source=str(pre),
+            rule='postprocessed S21 = preprocessed S21 * cal_pair[tx(output_pos), rx(input_pos)]',
+            frequency_grids=[np.frombuffer(key, dtype=np.float64).tolist() for key in cache]))
+    return post, n_snap, n_fix, n_copy
+
+
+def _reject_corrected_source(config):
+    object_calibration = config.get('preprocess', {}).get('s21', {}).get('object_calibration', {})
+    if object_calibration.get('set_name') or object_calibration.get('bundle_path'):
+        raise ValueError('calibration sources must have no object correction; object_calibration is already active')
+
+
+def _best_phases(Z):
+    """Maximize pair _coherence by alternating antenna phases, anchored at TX0/RX0."""
+    t = np.zeros(Z.shape[0])
+    r = np.zeros(Z.shape[1])
+    for _ in range(100):
+        t = np.angle((Z * np.exp(-1j * r)[None, :]).sum(axis=1))
+        r = np.angle((Z * np.exp(-1j * t)[:, None]).sum(axis=0))
+        t = t - t[0]
+        r = r - r[0]
+    return t, r
+
+
+def _coherence(Z, t=None, r=None):
+    """Return |sum(pair contributions)| / sum(|pair contributions|)."""
+    if t is not None:
+        if r is None:
+            raise ValueError('RX phases must accompany TX phases')
+        Z = Z * np.exp(-1j * (t[:, None] + r[None, :]))
+    return float(np.abs(Z.sum()) / (np.abs(Z).sum() + 1e-30))
+
+
+def _circular_median(phases):
+    """Choose the phase minimizing circular distances along the first axis."""
+    d = np.abs(np.angle(np.exp(1j * (phases[:, None] - phases[None, :]))))
+    best = np.argmin(d.sum(axis=1), axis=0)
+    return np.take_along_axis(phases, best[None], axis=0)[0]
+
+
+def _combine(sets):
+    """Combine targets using circular phase and logarithmic gain medians."""
+    out = []
+    for key in ('T', 'R'):
+        Z = np.array([s[key] for s in sets])                      # (targets, antennas, frequencies)
+        out.append(np.exp(np.median(np.log(np.abs(Z)), axis=0)) * np.exp(1j * _circular_median(np.angle(Z))))
+    return tuple(out)
+
+
+class _Estimator:
+    """Geometry, gated target echoes and the original alternating estimator."""
+
+    def __init__(self, st, tx, rx, freq, check=lambda: None):
+        self.st, self.tx, self.rx, self.freq = st, tx, rx, freq
+        self.check = check
+        self.n_tx, self.n_rx = len(tx), len(rx)
+        self.band = (freq >= st.f_min) & (freq <= st.f_max)
+        self.fb = freq[self.band]
+        if self.fb.size < 4:
+            raise ValueError('calibration band must contain at least four frequency samples')
+        self.win = np.hanning(self.fb.size)
+        self.ok = self.win > 0.2                                  # Avoid unreliable window division at band edges.
+        if self.ok.sum() < (4 if st.phase_model == 'poly3' else 2):
+            raise ValueError('too few reliable frequencies for the requested phase model')
+        self.nfft = 1 << int(np.ceil(np.log2(self.fb.size * 8)))
+        self.dpath = np.fft.fftfreq(self.nfft, self.fb[1] - self.fb[0]) * C_LIGHT     # Excess propagation path in metres.
+        self.gate = np.clip(np.minimum((self.dpath + st.gate_half_m) / st.gate_taper_m,
+                                       (st.gate_half_m - self.dpath) / st.gate_taper_m) + 0.5, 0, 1)
+
+    def scene_to_radar(self, q):
+        """Convert ground-relative scene coordinates into radar coordinates."""
+        p = np.radians(self.st.pitch_deg)
+        y0 = q[1] - self.st.antenna_height_m
+        return np.array([q[0], y0 * np.cos(p) + q[2] * np.sin(p), -y0 * np.sin(p) + q[2] * np.cos(p)])
+
+    def pair_paths(self, q_scene):
+        """Return bistatic paths to a point, or sphere surface paths shortened by
+        2 * radius * cos(beta/2), using the measured sphere center."""
+        a = self.st.sphere_radius_m
+        pr = self.scene_to_radar(np.asarray(q_scene, float))
+        vt = self.tx - pr
+        vr = self.rx - pr
+        dt = np.linalg.norm(vt, axis=1)
+        dr = np.linalg.norm(vr, axis=1)
+        if np.any(dt <= a) or np.any(dr <= a):
+            raise ValueError('reflector intersects an antenna or has zero range')
+        paths = dt[:, None] + dr[None, :]
+        if a:
+            cos_beta = (vt @ vr.T) / (dt[:, None] * dr[None, :])
+            paths = paths - 2 * a * np.sqrt(np.clip((1 + cos_beta) / 2, 0, 1))
+        return paths
+
+    def _unwound(self, s21_band, paths):
+        return s21_band * np.exp(2j * np.pi * self.fb[None, None, :] * paths[:, :, None] / C_LIGHT)
+
+    def target_echo(self, s21_band, paths):
+        """Isolate the unwound target echo with the tapered excess-path gate."""
+        h = np.fft.ifft(self._unwound(s21_band, paths) * self.win, self.nfft, axis=2)
+        return np.fft.fft(h * self.gate, axis=2)[:, :, :self.fb.size] / np.maximum(self.win, 1e-3)
+
+    def broadband(self, E):
+        """Sum reliable-band echo contributions at the target for each pair."""
+        return E[:, :, self.ok].sum(axis=2)
+
+    def coarse_range(self, s21, q_nominal):
+        """Move nominal Z toward the strongest envelope within the path search range."""
+        q = q_nominal.copy()
+        if not self.st.coarse_range_search_m:
+            return q
+        s = s21[:, :, self.band]
+        sel = np.abs(self.dpath) <= self.st.coarse_range_search_m
+        for _ in range(3):
+            self.check()
+            env = np.abs(np.fft.ifft(self._unwound(s, self.pair_paths(q)) * self.win, self.nfft, axis=2)).sum(axis=(0, 1))
+            q[2] += self.dpath[sel][np.argmax(env[sel])] / 2
+        return q
+
+    def refine_target(self, s21, q0):
+        """Refine target coordinates and antenna phases by alternating Nelder-Mead fits."""
+        P0 = self.pair_paths(q0)
+        E0 = self.target_echo(s21[:, :, self.band], P0)
+        axes = [('xyz').index(a) for a in self.st.refine_axes]
+
+        def E_at(v):
+            q = q0.copy()
+            q[axes] += v
+            dP = self.pair_paths(q) - P0
+            return E0 * np.exp(2j * np.pi * self.fb[None, None, :] * dP[:, :, None] / C_LIGHT), q
+
+        def score(v, t, r):
+            self.check()
+            if np.any(np.abs(v) > self.st.refine_range_m):
+                return 0.0
+            return _coherence(self.broadband(E_at(v)[0]), t, r)
+
+        v = np.zeros(len(axes))
+        if axes:
+            from scipy.optimize import minimize
+
+            for _ in range(6):
+                self.check()
+                t, r = _best_phases(self.broadband(E_at(v)[0]))
+                simplex = np.vstack([v] + [v + 0.03 * np.eye(len(axes))[k] for k in range(len(axes))])
+                v = minimize(lambda w: -score(w, t, r), v, method='Nelder-Mead',
+                             options=dict(xatol=5e-4, fatol=1e-7, initial_simplex=simplex)).x
+        return E_at(v)
+
+    def factorize(self, E):
+        """Factor E(tx,rx,f) into antenna phases and least-squares log-amplitudes."""
+        nb = E.shape[2]
+        T = np.ones((self.n_tx, nb), complex)
+        R = np.ones((self.n_rx, nb), complex)
+        L = np.log(np.abs(E) + 1e-30)
+        for k in range(nb):
+            self.check()
+            t, r = _best_phases(E[:, :, k])
+            tt = L[:, :, k].mean(axis=1) - L[:, :, k].mean()
+            rr = L[:, :, k].mean(axis=0) - L[:, :, k].mean()
+            T[:, k] = np.exp(tt + 1j * t)
+            R[:, k] = np.exp(rr + 1j * r)
+        return T, R
+
+    def antenna_params(self, Z):
+        """Fit zero-frequency phase, excess delay path and gain for one antenna."""
+        ph = np.unwrap(np.angle(Z[self.ok]))
+        f = self.fb[self.ok]
+        slope, ph0 = np.polyfit(f, ph, 1)
+        return dict(phase0_deg=float(np.degrees(ph0)), delay_path_m=float(-slope * C_LIGHT / (2 * np.pi)),
+                    gain_db=float(20 * np.log10(np.mean(np.abs(Z[self.ok])))),
+                    phase_rms_after_linear_deg=float(np.degrees(np.std(ph - (slope * f + ph0)))))
+
+    def phase_model(self, Z):
+        """Fit the selected antenna phase model over reliable band samples."""
+        model = self.st.phase_model
+        if model == 'raw':
+            return Z
+        ph = np.unwrap(np.angle(Z))
+        f = (self.fb - self.fb.mean()) / 1e9
+        if model == 'const':
+            u = np.exp(1j * np.angle(Z[self.ok])).mean()
+            return np.abs(Z) * np.exp(1j * np.angle(u))
+        deg = {'linear': 1, 'poly3': 3}[model]
+        return np.abs(Z) * np.exp(1j * np.polyval(np.polyfit(f[self.ok], ph[self.ok], deg), f))
+
+    def pair_correction(self, T, R):
+        """Invert antenna factors, retaining measured amplitudes in phase-only mode."""
+        Z = T[:, None, :] * R[None, :, :]
+        return np.conj(Z) / np.abs(Z) if not self.st.apply_amplitude else 1.0 / Z
+
+    def to_full_grid(self, Z_band, params):
+        """Extend antenna factors over the full grid with continuous edge-anchored
+        linear phase and constant edge gain outside the reliable band."""
+        idx = np.flatnonzero(self.band)[self.ok]
+        ph_in = np.unwrap(np.angle(Z_band[self.ok]))
+        mag_in = np.abs(Z_band[self.ok])
+        slope = -2 * np.pi * params['delay_path_m'] / C_LIGHT               # Radians per Hz.
+        ph = np.empty(self.freq.size)
+        mag = np.empty(self.freq.size)
+        ph[idx] = ph_in
+        mag[idx] = mag_in
+        lo, hi = idx[0], idx[-1]
+        ph[:lo] = ph_in[0] + slope * (self.freq[:lo] - self.freq[lo])
+        mag[:lo] = mag_in[0]
+        ph[hi + 1:] = ph_in[-1] + slope * (self.freq[hi + 1:] - self.freq[hi])
+        mag[hi + 1:] = mag_in[-1]
+        return mag * np.exp(1j * ph)
+
+
+def _callbacks(progress, cancelled):
+    def check(message=None):
+        if cancelled is not None and cancelled():
+            raise InterruptedError('object calibration cancelled')
+        if message is not None and progress is not None:
+            progress(message)
+    return check
+
+
+def _mean_samples(samples, check, expected_freq=None):
+    mean, count, freq = None, 0, expected_freq
+    for data, axis in samples:
+        check()
+        axis = _frequency(axis, uniform=True)
+        if freq is not None and not np.array_equal(axis, freq):
+            raise ValueError('frequency grids differ between calibration measurements')
+        freq = axis
+        if mean is None:
+            mean = np.zeros_like(data, dtype=np.complex128)
+        data = _finite_array(data, 'calibration measurement', mean.shape, complex_values=True)
+        count += 1
+        mean += (data - mean) / count
+    if mean is None:
+        raise ValueError('calibration measurements must contain at least one collection')
+    return mean, freq
+
+
+def _settings(settings):
+    settings = settings or Settings()
+    settings.__post_init__()
+    return settings
+
+
+def _compute(sets, empty, freq, settings, config, config_path, check) -> dict[str, Any]:
+    tx, rx = _geometry(config, settings.input_idx, settings.output_idx)
+    est = _Estimator(settings, tx, rx, freq, check)
+    for index, record in enumerate(sets):
+        check(f'Estimating target {index + 1}/{len(sets)}')
+        data = record.pop('s21')
+        if empty is not None:
+            data = data - empty
+        nominal = _finite_array(record['target_scene_m'], 'target_scene_m', (3,))
+        echo, refined = est.refine_target(data, est.coarse_range(data, nominal))
+        if not np.all(np.any(np.abs(echo[:, :, est.ok]) > 0, axis=2)):
+            raise ValueError(f'target {index + 1} has no usable echo for one or more antenna pairs')
+        _finite_array(echo, 'target echo', complex_values=True)
+        record.update(E=echo, q=refined, q_nominal=nominal)
+        record['T'], record['R'] = est.factorize(echo)
+
+    T_all, R_all = _combine(sets)
+    T_all = np.array([est.phase_model(value) for value in T_all])
+    R_all = np.array([est.phase_model(value) for value in R_all])
+    antennas = {f'Tx{index}': est.antenna_params(value) for index, value in enumerate(T_all)}
+    antennas.update({f'Rx{index}': est.antenna_params(value) for index, value in enumerate(R_all)})
+    T_full = np.array([est.to_full_grid(value, antennas[f'Tx{index}']) for index, value in enumerate(T_all)])
+    R_full = np.array([est.to_full_grid(value, antennas[f'Rx{index}']) for index, value in enumerate(R_all)])
+    unit = (lambda value: np.conj(value) / np.abs(value)) if not settings.apply_amplitude else (lambda value: 1 / value)
+    saved_pair = unit(T_full[:, None, :] * R_full[None, :, :]).astype(np.complex64)
+    quality = dict(coherence_before=[], coherence_own=[], coherence_leave_one_out=[], coherence_final=[])
+    diagnostics = []
+    final_correction = saved_pair[:, :, est.band]
+    for record in sets:
+        check()
+        before = est.broadband(record['E'])
+        after = est.broadband(record['E'] * final_correction)
+        quality['coherence_before'].append(_coherence(before))
+        quality['coherence_own'].append(_coherence(est.broadband(record['E'] * est.pair_correction(record['T'], record['R']))))
+        others = [other for other in sets if other is not record]
+        quality['coherence_leave_one_out'].append(
+            _coherence(est.broadband(record['E'] * est.pair_correction(*_combine(others)))) if others else None)
+        quality['coherence_final'].append(_coherence(after))
+        diagnostics.append(dict(phase_before_deg=np.degrees(np.angle(before)).tolist(),
+                                phase_after_deg=np.degrees(np.angle(after)).tolist(),
+                                coherence_before=_coherence(before), coherence_after=_coherence(after)))
+
+    valid = np.zeros(freq.size, bool)
+    valid[np.flatnonzero(est.band)[est.ok]] = True
+    meta = dict(
+        created=datetime.datetime.now().isoformat(timespec='seconds'), name=None,
+        convention=dict(apply='S21_corrected[tx, rx, f] = S21[tx, rx, f] * cal_pair[tx, rx, f]',
+                        index_order='sorted physical tx_output_pos x rx_input_pos',
+                        phase_reference='relative to Tx0 and Rx0; common phase/delay is retained',
+                        amplitude='equalized' if settings.apply_amplitude else 'phase only',
+                        outside_band='linear antenna phase continuation anchored at the band edge'),
+        geometry=dict(config=str(config_path), tx_xyz_m=tx.tolist(), rx_xyz_m=rx.tolist(),
+                      antenna_height_m=settings.antenna_height_m, pitch_deg=settings.pitch_deg),
+        estimation=dict(band_hz=[settings.f_min, settings.f_max], gate_half_m=settings.gate_half_m,
+                        gate_taper_m=settings.gate_taper_m, coarse_range_search_m=settings.coarse_range_search_m,
+                        refine_axes=list(settings.refine_axes), refine_range_m=settings.refine_range_m,
+                        phase_model=settings.phase_model, sphere_radius_m=settings.sphere_radius_m),
+        source_preprocess=_source_signature(config),
+        targets=[dict(path=record.get('path', ''), snapshots=record.get('snapshots', []),
+                      nominal_scene_m=record['q_nominal'].tolist(), refined_scene_m=record['q'].tolist()) for record in sets],
+        antennas=antennas, quality=quality, diagnostics=diagnostics)
+    cal = dict(freq_hz=freq.astype(np.float64), pair=saved_pair,
+               tx=unit(T_full).astype(np.complex64), rx=unit(R_full).astype(np.complex64), valid=valid,
+               tx_output_pos=np.array(settings.output_idx, np.int32), rx_input_pos=np.array(settings.input_idx, np.int32),
+               antenna_params=np.array([[np.radians(value['phase0_deg']), value['delay_path_m'], value['gain_db']]
+                                        for value in antennas.values()]), meta=meta, dir=None)
+    validate_calibration(cal)
+    check('Object calibration complete')
+    return cal
+
+
+def _collection_samples(collection, settings):
+    from python_app.storage.npz.serialize import validate_trace_collection
+
+    validate_trace_collection(collection, require_finite=True)
+    traces = {(trace.combo.input, trace.combo.output): trace for trace in collection.traces}
+    rows, freq = [], None
+    for output in settings.output_idx:
+        row = []
+        for input_ in settings.input_idx:
+            if (input_, output) not in traces:
+                raise ValueError(f'calibration collection is missing input={input_}, output={output}')
+            trace = traces[input_, output]
+            axis = _frequency(trace.frequency_hz, uniform=True)
+            if freq is not None and not np.array_equal(axis, freq):
+                raise ValueError('frequency grids differ between collection pairs')
+            freq = axis
+            row.append(_finite_array(trace.s21, 'S21', freq.shape, complex_values=True))
+        rows.append(row)
+    return np.array(rows), freq
+
+
+def compute_from_collections(
+    cal_sets: Iterable[dict[str, Any]], config_dict: dict[str, Any],
+    empty_collections: Iterable[SweepCollection] | None = None, settings: Settings | None = None,
+    *, progress: Callable[[str], None] | None = None, cancelled: Callable[[], bool] | None = None,
+) -> dict[str, Any]:
+    """Estimate corrections from standard-preprocessed sweeps without object correction.
+
+    cal_sets contains {collections: [SweepCollection, ...], target_scene_m: XYZ}.
+    progress accepts a status string; cancelled returns bool and raises
+    InterruptedError promptly in data, refinement and factorization loops.
+    """
+    settings = _settings(settings)
+    _reject_corrected_source(config_dict)
+    check = _callbacks(progress, cancelled)
+    sets = list(cal_sets)
+    if not sets:
+        raise ValueError('at least one reflector target is required')
+    empty, freq = None, None
+    if empty_collections is not None:
+        check('Averaging empty scene')
+        empty, freq = _mean_samples((_collection_samples(value, settings) for value in empty_collections), check)
+    prepared = []
+    for index, record in enumerate(sets):
+        check(f'Averaging target {index + 1}/{len(sets)}')
+        collections = list(record['collections'])
+        mean, freq = _mean_samples((_collection_samples(value, settings) for value in collections), check, freq)
+        prepared.append(dict(s21=mean, target_scene_m=record['target_scene_m'],
+                             snapshots=[str(value.collection_id) for value in collections]))
+    return _compute(prepared, empty, freq, settings, config_dict, 'live capture', check)
+
+
+def compute_calibration(
+    cal_sets: Iterable[dict[str, Any]], empty_scene_path: str | Path | None = None, settings: Settings | None = None,
+    *, progress: Callable[[str], None] | None = None, cancelled: Callable[[], bool] | None = None,
+) -> dict[str, Any]:
+    """Legacy archive API backed by the same estimator as live collection capture."""
+    settings = _settings(settings)
+    check = _callbacks(progress, cancelled)
+    cal_sets = list(cal_sets)
+    if not cal_sets:
+        raise ValueError('at least one reflector target is required')
+    config_path = find_config_profile(cal_sets[0]['path'])
+    config = _profile(config_path)
+    _reject_corrected_source(config)
+    geometry = _geometry(config, settings.input_idx, settings.output_idx)
+    signature = _source_signature(config)
+
+    def samples(directories):
+        for directory in directories:
+            check()
+            profile_path = find_config_profile(directory)
+            path = Path(directory)
+            while True:
+                if (path / 'calibration_applied.json').is_file():
+                    raise ValueError(f'object calibration is already applied to archive {directory}')
+                if path == profile_path.parent:
+                    break
+                path = path.parent
+            source = _profile(profile_path)
+            _reject_corrected_source(source)
+            current = _geometry(source, settings.input_idx, settings.output_idx)
+            if any(not np.allclose(first, second, rtol=0, atol=1e-9) for first, second in zip(geometry, current)):
+                raise ValueError(f'antenna geometry differs in {directory}')
+            if signature != _source_signature(source):
+                raise ValueError(f'preprocessing or hardware configuration differs in {directory}')
+            yield load_s21(directory, settings.input_idx, settings.output_idx)
+
+    empty, freq = None, None
+    if empty_scene_path is not None:
+        empty, freq = _mean_samples(samples(list_snapshots(empty_scene_path)), check)
+    prepared = []
+    for record in cal_sets:
+        directories = list_snapshots(record['path'], record.get('snapshots'))
+        mean, freq = _mean_samples(samples(directories), check, freq)
+        prepared.append(dict(s21=mean, target_scene_m=record['target_scene_m'], path=str(record['path']),
+                             snapshots=[directory.name for directory in directories]))
+    cal = _compute(prepared, empty, freq, settings, config, config_path, check)
+    cal['meta']['estimation']['empty_scene'] = str(empty_scene_path) if empty_scene_path is not None else None
+    return cal

requirements.txt

@@ -1,4 +1,5 @@
 numpy>=1.26,<3
+scipy>=1.11,<2
 libusb1>=3.1
 pyserial>=3.5,<4
 # PyQt6 6.8+ ships only manylinux_2_39 aarch64 wheels (glibc >= 2.39); Jetson /