prettier logging

bcipy/simulator/helpers/log_utils.py

@@ -0,0 +1,18 @@
+from typing import List
+
+import pandas as pd
+
+
+def format_alp_likelihoods(likelihoods, alp):
+    rounded = [round(lik, 3) for lik in likelihoods]
+    formatted = [f"{a} : {l}" for a, l in zip(alp, rounded)]
+    return formatted
+
+
+def format_sample_rows(sample_rows: List[pd.Series]):
+    formatted_rows = []
+    for row in sample_rows:
+        new_row = row.drop(columns=['eeg'], axis=1, inplace=False)
+        formatted_rows.append(new_row.to_string(index=False, header=True))
+
+    return ", ".join(formatted_rows)

bcipy/simulator/helpers/sampler.py

@@ -9,6 +9,7 @@
 from bcipy.helpers.parameters import Parameters
 from bcipy.helpers.symbols import alphabet
 from bcipy.simulator.helpers.data_engine import RawDataEngine
+from bcipy.simulator.helpers.log_utils import format_sample_rows
 from bcipy.simulator.interfaces import SimState
 
 log = logging.getLogger(__name__)
@@ -55,7 +56,7 @@ def sample(self, state: SimState) -> np.ndarray:
             row = filtered_data.sample(1)
             sample_rows.append(row)
 
-        log.debug(f"EEG Samples: \n {', '.join([r.to_string() for r in sample_rows])}")
+        log.debug(f"EEG Samples: \n {format_sample_rows(sample_rows)}")
         eeg_responses = [r['eeg'].to_numpy()[0] for r in sample_rows]
         sample = self.model_input_reshaper(eeg_responses)
 

bcipy/simulator/helpers/signal_helpers.py

@@ -118,4 +118,4 @@ def process_raw_data_for_model(data_folder, parameters, reshaper: InquiryReshape
     # define the training classes using integers, where 0=nontargets/1=targets
     # labels = inquiry_labels.flatten()
 
-    return ExtractedExperimentData(inquiries, trials, inquiry_labels, inquiry_timing, (trigger_targetness, trigger_timing, trigger_symbols))
+    return ExtractedExperimentData(inquiries, trials, inquiry_labels, inquiry_timing, (trigger_targetness, trigger_timing, trigger_symbols))

bcipy/simulator/sim.py

@@ -12,6 +12,7 @@
 from bcipy.simulator.helpers.sampler import Sampler
 from bcipy.simulator.helpers.state_manager import StateManager, SimState
 from bcipy.simulator.helpers.types import InquiryResult
+from bcipy.simulator.helpers.log_utils import format_alp_likelihoods
 from bcipy.simulator.interfaces import MetricReferee, ModelHandler
 from bcipy.simulator.simulator_base import Simulator
 
@@ -72,11 +73,11 @@ def run(self):
             evidence = self.model_handler.generate_evidence(curr_state,
                                                             sampled_data)  # TODO make this evidence be a dict (mapping of evidence type to evidence)
 
-            log.debug(f"Evidence for stimuli {curr_state.display_alphabet} \n {evidence}")
+            log.debug(f"Evidence for stimuli {curr_state.display_alphabet} \n {format_alp_likelihoods(evidence, self.symbol_set)}")
 
             inq_record: InquiryResult = self.state_manager.update(evidence)
             updated_state = self.state_manager.get_state()
-            log.debug(f"Fused Likelihoods {[str(round(p, 3)) for p in inq_record.fused_likelihood]}")
+            log.debug(f"Fused Likelihoods {format_alp_likelihoods(inq_record.fused_likelihood, self.symbol_set)}")
 
             if inq_record.decision:
                 log.info(f"Decided {inq_record.decision} for target {inq_record.target}")

bcipy/simulator/tests/sampler_test.py

@@ -38,13 +38,15 @@ class DummyRef(MetricReferee):
 
 if __name__ == "__main__":
     args = dict()
-    args['data_folders'] = ["/Users/srikarananthoju/cambi/tab_test_dynamic/tab_test_dynamic_RSVP_Copy_Phrase_Thu_24_Aug_2023_18hr58min16sec_-0700",
-                            # "/Users/srikarananthoju/cambi/tab_test_dynamic/tab_test_dynamic_RSVP_Copy_Phrase_Thu_24_Aug_2023_19hr07min50sec_-0700",
-                            # "/Users/srikarananthoju/cambi/tab_test_dynamic/tab_test_dynamic_RSVP_Copy_Phrase_Thu_24_Aug_2023_19hr15min29sec_-0700"
+    args['data_folders'] = ["/Users/srikarananthoju/cambi/tab_test_dynamic/16sec_-0700",
+                            "/Users/srikarananthoju/cambi/tab_test_dynamic/50sec_-0700",
+                            # "/Users/srikarananthoju/cambi/tab_test_dynamic/29sec_-0700"
                             ]
     args['out_dir'] = Path(__file__).resolve().parent
     model_file = Path(
-        "/Users/srikarananthoju/cambi/tab_test_dynamic/tab_test_dynamic_RSVP_Calibration_Thu_24_Aug_2023_18hr41min37sec_-0700/model_0.9524_200_800.pkl")
+        "/Users/srikarananthoju/cambi/tab_test_dynamic/calibr_37sec_-0700/model_0.9524_200_800.pkl"
+        # "/Users/srikarananthoju/cambi/tab_test_dynamic/calibr_37sec_-0700/model_0.9595.pkl"
+    )
     sim_parameters = load_json_parameters("bcipy/simulator/sim_parameters.json", value_cast=True)
 
     data_engine = RawDataEngine(args['data_folders'])
@@ -58,14 +60,6 @@ class DummyRef(MetricReferee):
     sampler: Sampler = SimpleLetterSampler(data_engine)
     sample: np.ndarray = sampler.sample(stateManager.get_state())
 
-    # model = PcaRdaKdeModel()
-    # model = model.load(model_file)
-    #
-    # eeg_evidence = model.predict(sample, stateManager.get_state().display_alphabet, alphabet())
-    #
-    # print(eeg_evidence.shape)
-    # print(eeg_evidence)
-
     model_handler = DummyModelHandler(model_file)
     sim = SimulatorCopyPhrase(data_engine, model_handler, sampler, stateManager, DummyRef())
     sim.run()