Add in notebook for simulated data

misko · Dec 29, 2023 · 2b16b92 · 2b16b92
1 parent 48c9598
commit 2b16b92
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Showing 5 changed files with 276 additions and 30 deletions.
diff --git a/spf/dataset/spf_generate.py b/spf/dataset/spf_generate.py
@@ -58,9 +58,9 @@ def generate_session(args_and_session_idx):
     detector_speed = args.detector_speed
     if args.detector_speed < 0:
         detector_speed = np.random.uniform(low=0.0, high=-args.detector_speed)
-    sigma = args.sigma
-    if args.sigma < 0:
-        sigma = np.random.uniform(low=0.0, high=-args.sigma)
+    sigma_noise = args.sigma_noise
+    if args.sigma_noise < 0:
+        sigma_noise = np.random.uniform(low=0.0, high=-args.sigma_noise)
     detector_noise = args.detector_noise
     if args.detector_noise < 0:
         detector_noise = np.random.uniform(low=0.0, high=-args.detector_noise)
@@ -111,13 +111,13 @@ def generate_session(args_and_session_idx):
     broadcasting_positions_at_t = np.zeros((args.time_steps, n_sources, 1))
     broadcasting_heading_at_t = np.zeros((args.time_steps, n_sources, 1))
     receiver_positions_at_t = np.zeros((args.time_steps, args.elements, 2))
-    source_theta_at_t = np.zeros((args.time_steps, 1, 1))
-    source_distance_at_t = np.zeros((args.time_steps, 1, 1))
+    source_theta_at_t = np.zeros((args.time_steps, 1))
+    source_distance_at_t = np.zeros((args.time_steps, 1))
 
     detector_orientation_at_t = np.ones((args.time_steps, 1))
 
     signal_matrixs_at_t = np.zeros(
-        (args.time_steps, args.elements, args.samples_per_snapshot),
+        (args.time_steps, args.elements, args.readings_per_snapshot),
         dtype=np.complex64,
     )
     beam_former_outputs_at_t = np.zeros((args.time_steps, args.beam_former_spacing))
@@ -213,7 +213,7 @@ def generate_session(args_and_session_idx):
                         current_source_positions[[tdm_source_idx]],  # x, y position
                         args.carrier_frequency,
                     ),
-                    sigma=sigma,
+                    sigma=sigma_noise,
                 )
             )
 
@@ -253,7 +253,7 @@ def generate_session(args_and_session_idx):
 
         signal_matrixs_at_t[t_idx] = d.get_signal_matrix(
             start_time=time_stamps[t_idx, 0],
-            duration=args.samples_per_snapshot / d.sampling_frequency,
+            duration=args.readings_per_snapshot / d.sampling_frequency,
         )
         thetas_at_t[t_idx], beam_former_outputs_at_t[t_idx], _ = beamformer_f(
             d.all_receiver_pos(with_offset=False),
@@ -280,12 +280,13 @@ def generate_session(args_and_session_idx):
                 t_idx
             ] = 0  # (np.arctan2(diff[[1]],diff[[0]])-d.orientation+np.pi)%(2*np.pi)-np.pi
             source_distance_at_t[t_idx] = 0  # np.sqrt(np.power(diff,2).sum())
+
     session = {
         "broadcasting_positions_at_t": broadcasting_positions_at_t,  # list of (time_steps,sources,1)
         "source_positions_at_t": source_positions_at_t,  # (time_steps,sources,2[x,y])
         "source_velocities_at_t": source_velocities_at_t,  # (time_steps,sources,2[x,y])
         "receiver_positions_at_t": receiver_positions_at_t,  # (time_steps,receivers,2[x,y])
-        "signal_matrixs_at_t": signal_matrixs_at_t,  # (time_steps,receivers,samples_per_snapshot)
+        "signal_matrixs_at_t": signal_matrixs_at_t,  # (time_steps,receivers,readings_per_snapshot)
         "beam_former_outputs_at_t": beam_former_outputs_at_t,  # (timesteps,thetas_tested_for_steering)
         "thetas_at_t": thetas_at_t,  # (timesteps,thetas_tested_for_steering)
         "detector_position_phase_offsets_at_t": detector_position_phase_offsets_at_t,  # (timesteps,1) # phase offset for orbit dynamics

diff --git a/spf/model_training_and_inference/01_generate_data.py b/spf/model_training_and_inference/01_generate_data.py
@@ -46,10 +46,10 @@
     )
     parser.add_argument("--detector-speed", type=float, required=False, default=10.0)
     parser.add_argument("--source-speed", type=float, required=False, default=0.0)
-    parser.add_argument("--sigma", type=float, required=False, default=1.0)
+    parser.add_argument("--sigma-noise", type=float, required=False, default=1.0)
     parser.add_argument("--time-steps", type=int, required=False, default=100)
     parser.add_argument("--time-interval", type=float, required=False, default=0.3)
-    parser.add_argument("--samples-per-snapshot", type=int, required=False, default=3)
+    parser.add_argument("--readings-per-snapshot", type=int, required=False, default=3)
     parser.add_argument("--sessions", type=int, required=False, default=1024)
     parser.add_argument(
         "--output", type=str, required=False, default="sessions-default"

diff --git a/spf/model_training_and_inference/13_learn_beamformer.py b/spf/model_training_and_inference/13_learn_beamformer.py
@@ -293,9 +293,9 @@ def plot_loss(
     print("init network")
     models = []
 
-    # signal_matrix ~ (snapshots_per_sample,n_antennas,samples_per_snapshot)
+    # signal_matrix ~ (snapshots_per_sample,n_antennas,readings_per_snapshot)
 
-    _, n_receivers, samples_per_snapshot = ds_train[0]["signal_matrixs_at_t"].shape
+    _, n_receivers, readings_per_snapshot = ds_train[0]["signal_matrixs_at_t"].shape
     _, beam_former_bins = ds_train[0]["beam_former_outputs_at_t"].shape
 
     for snapshots_per_sample in [1]:
@@ -310,7 +310,7 @@ def plot_loss(
                             snapshots_per_sample,
                         ),
                         "model": ComplexFFNN(
-                            d_inputs=n_receivers * samples_per_snapshot + 2,
+                            d_inputs=n_receivers * readings_per_snapshot + 2,
                             d_outputs=beam_former_bins,
                             d_hidden=beam_former_bins * 2,
                             n_layers=n_complex_layers,
@@ -332,7 +332,7 @@ def plot_loss(
                             snapshots_per_sample,
                         ),
                         "model": HybridFFNN(
-                            d_inputs=n_receivers * samples_per_snapshot + 2,
+                            d_inputs=n_receivers * readings_per_snapshot + 2,
                             d_outputs=beam_former_bins,
                             n_complex_layers=n_complex_layers,
                             n_real_layers=8,

diff --git a/spf/notebooks/load_real_data_session.ipynb b/spf/notebooks/load_real_data_session.ipynb
@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 2,
    "id": "71dfe5c6-b68f-49a2-8275-728cdb65c529",
    "metadata": {},
    "outputs": [],
@@ -13,7 +13,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 3,
    "id": "3a95ed23-b380-4cfd-8b47-60fa14290340",
    "metadata": {},
    "outputs": [],
@@ -25,24 +25,19 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 4,
    "id": "59584a7c-1e24-4e41-9952-23e7298bc583",
    "metadata": {},
    "outputs": [],
    "source": [
     "import sys\n",
     "sys.path.append(repo_root) # go to parent dir\n",
-    "import argparse\n",
-    "import pickle\n",
-    "\n",
-    "from spf.plot.plot import filenames_to_gif, plot_full_session\n",
-    "from compress_pickle import dump, load\n",
     "from spf.dataset.spf_dataset import SessionsDatasetReal"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 5,
    "id": "18b1c02a-10ce-4b47-ae2f-98625f3bdd59",
    "metadata": {},
    "outputs": [],
@@ -57,7 +52,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 6,
    "id": "032c99f4-6b81-4082-a4d6-47af09b8009e",
    "metadata": {},
    "outputs": [
@@ -84,7 +79,15 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": null,
+   "id": "934efc57",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
    "id": "7084912d-c62f-4383-a25b-79a6a99583f5",
    "metadata": {},
    "outputs": [],
@@ -96,17 +99,17 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 8,
    "id": "21858d41-83af-4adb-b5cb-55e33b81c247",
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "<matplotlib.legend.Legend at 0x13dc55f10>"
+       "<matplotlib.legend.Legend at 0x16395b290>"
       ]
      },
-     "execution_count": 9,
+     "execution_count": 8,
      "metadata": {},
      "output_type": "execute_result"
     },
@@ -153,7 +156,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 9,
    "id": "ab349f95-e442-4b52-b1dc-b18e1748874c",
    "metadata": {},
    "outputs": [

diff --git a/spf/notebooks/load_simulated_data_session.ipynb b/spf/notebooks/load_simulated_data_session.ipynb