From fb73758a020f2b188e15cb62bff8b26c300d1a49 Mon Sep 17 00:00:00 2001
From: ada-3e212e610b <z2720629308@gmail.com>
Date: Fri, 31 Jul 2026 22:34:18 +0100
Subject: [PATCH 01/25] polish the feedback generated

---
 evaluation_function/compare_MIDI.py | 232 +++++++++++++++++++++++++++-
 1 file changed, 231 insertions(+), 1 deletion(-)

diff --git a/evaluation_function/compare_MIDI.py b/evaluation_function/compare_MIDI.py
index 445aefb..1f42e7f 100644
--- a/evaluation_function/compare_MIDI.py
+++ b/evaluation_function/compare_MIDI.py
@@ -12,6 +12,7 @@
     Step 3 -- event_level_feedback      (note/chord-level feedback)
     Step 4 -- compute_stats             (summary counts)
     Step 5 -- generate_feedback_message (human-readable text)
+              polished_feedback_message (polished version of human-readable text)
     Step 6 -- is_correct                (overall pass/fail judgement)
 """
 
@@ -1062,6 +1063,235 @@ def generate_feedback_message(event_details, response_events, ref_events, stats,
     return "\n".join(all_messages)
 
 
+def polished_feedback_message(event_details, response_events, ref_events, stats,
+                               global_slow_threshold=GLOBAL_SLOW_THRESHOLD,
+                               global_fast_threshold=GLOBAL_FAST_THRESHOLD):
+    """
+    Generate concise, practice-oriented feedback that aims to:
+        1. summarise current performance level qualitatively
+        2. suggest a measurable goal for the next attempt with a main focus area
+        3. provide encouraging actionable advice for improvement
+    Individual note and chord errors remain available in event_details but
+    will not list each of them in the message.
+
+    Args:
+        event_details: list of dicts, output of event_level_feedback()
+        response_events: list of event dicts from group_notes_into_events
+        ref_events: list of event dicts from group_notes_into_events
+        stats: dict, output of compute_stats()
+        global_slow_threshold: timing_scale above this triggers "too slow" message
+        global_fast_threshold: timing_scale below this triggers "too fast" message
+
+    Returns:
+        feedback_message (str)
+    """
+    note_events  = [n for n in event_details if n["event_type"] == "note"]
+    chord_events = [ch for ch in event_details if ch["event_type"] == "chord"]
+
+    paired_notes  = [
+        n for n in note_events
+        if n["operation_type"] in ("match", "replacement")
+    ]
+    paired_chords = [
+        ch for ch in chord_events
+        if ch["operation_type"] in ("match", "replacement")
+    ]
+
+    total_reference_notes = stats["total_notes_in_reference"]
+    total_reference_chords = stats["total_chords_in_reference"]
+    total_aligned_events = len(paired_notes) + len(paired_chords)
+
+    timing_scale = stats["timing_scale"]
+    timing_offset = stats["timing_offset"]
+    duration_scale = stats["duration_scale"]
+
+    # -------------- summarise current performance level --------------
+    # tempo: acceptable / too slow / too fast
+    # ------------------------------------------------------------------
+    timing_pct = abs(timing_scale - 1.0) * 100
+    duration_pct = abs(duration_scale - 1.0) * 100
+    if timing_scale > 1:
+        timing_direction = "behind"
+    elif timing_scale < 1:
+        timing_direction = "ahead of"
+    else:
+        timing_direction = "the same as"
+
+    if duration_scale > 1:
+        duration_direction = "longer than"
+    elif duration_scale < 1:
+        duration_direction = "shorter than"
+    else:
+        duration_direction = "the same as"
+
+    if timing_scale > global_slow_threshold:
+        tempo_message = (
+            f"Overall, your tempo is slower than the reference "
+            f"(timing is about {timing_pct:.0f}% {timing_direction} the reference in general while "
+            f"notes are held about {duration_pct:.0f}% {duration_direction} the reference). "
+            f"No worries! You will get better when you practice more to get more familiar with it!"
+        )
+    elif timing_scale < global_fast_threshold:
+        tempo_message = (
+            f"Overall, your tempo is faster than the reference "
+            f"(timing is about {timing_pct:.0f}% {timing_direction} the reference in general while "
+            f"notes are held about {duration_pct:.0f}% {duration_direction} the reference). "
+            f"Don't rush even if you are confident in your performance." 
+            f"Slow down and give each note its full value."
+        )
+    else:
+        tempo_message = (
+            f"Timing: your overall tempo is within an acceptable range. Good job! "
+            f"The timing is about {timing_pct:.0f}% {timing_direction} the reference in general while "
+            f"notes are held about {duration_pct:.0f}% {duration_direction} than the reference."
+        )
+
+    # missing and extra
+    # ------------------------------------------------------------------
+    total_missing_events = stats["total_notes_missing"] + stats["total_chords_missing"]
+    total_extra_events = stats["total_notes_extra"] + stats["total_chords_extra"]
+    if total_missing_events == 0 and total_extra_events == 0:
+        completeness_messages = "Great! You did not miss or play any extra notes or chords. "
+    else:
+        completeness_messages = "No worries! Slow down and mind your fingering and hand position in your next try. "
+
+    # qualitative feedback on performance accuracy 
+    # ------------------------------------------------------------------
+    if total_reference_notes > 0:
+        note_pitch_correct = (total_reference_notes 
+                              - stats["total_notes_wrong_pitch"] - stats["total_notes_missing"])
+        note_pitch_accuracy = note_pitch_correct / total_reference_notes
+
+        timing_correct = (total_reference_notes 
+                          - stats["total_notes_wrong_timing"] - stats["total_notes_missing"])
+        note_timing_accuracy = timing_correct / total_reference_notes
+     
+        duration_correct = (total_reference_notes
+                            - stats["total_notes_wrong_duration"] - stats["total_notes_missing"])
+        note_duration_accuracy = duration_correct / total_reference_notes 
+    else:
+        note_pitch_accuracy = None
+        note_timing_accuracy = None
+        note_duration_accuracy = None
+ 
+    if total_reference_chords > 0:
+        sum_chord_accuracy = sum(
+            event["chord_accuracy"]
+            for event in paired_chords
+            if event["chord_accuracy"] is not None
+        )
+        mean_chord_accuracy = sum_chord_accuracy / total_reference_chords
+    else:
+        mean_chord_accuracy = None
+
+    current_performance_messages = []
+
+    if note_pitch_accuracy is not None:
+        if note_pitch_accuracy >= 0.90:
+            current_performance_messages.append(f"Great! Most notes were played correctly. \n")
+        elif note_pitch_accuracy >= 0.70:
+            current_performance_messages.append(
+                f"Many notes were correct, although some passages " \
+                f"still need more careful practice. \n"
+            )
+        else:
+            current_performance_messages.append(
+                f"Note accuracy needs more focused practice. " \
+                f"Practise the most difficult passage slowly, " \
+                f"check each note carefully, and then speed up to the correct tempo. \n"
+            )
+
+    if note_timing_accuracy is not None:
+        if note_timing_accuracy >= 0.90:
+            current_performance_messages.append(
+                f"Great timing consistency between notes! \n"
+            )
+        elif note_timing_accuracy >= 0.70:
+            current_performance_messages.append(
+                f"Timing of some passages need more careful practice, good overall! \n" 
+            )
+        else:
+            current_performance_messages.append(
+                f"Timing consistency needs more practice, " \
+                f"you may find it helpful to practice with a metronome. \n"
+            )
+        # do not comment on duration for now, as it may be due to transcription errors
+
+    if mean_chord_accuracy is not None:
+        if mean_chord_accuracy >= 0.90:
+            current_performance_messages.append(
+                f"Well done on the chords!"
+            )
+        elif mean_chord_accuracy >= 0.70:
+            current_performance_messages.append(
+                f"Many chord notes were correct, but some chords contained "
+                f"missing or additional notes."
+            )
+        else:
+            current_performance_messages.append(
+                f"Chord accuracy needs more focused practice, " 
+                f"they are often hard to play correctly at the beginning. " 
+                f"Pay attention to the fingering and hand position when playing chords."
+                f"You may find it helpful to practise each chord separately before reconnecting the surrounding passage."
+            )
+
+    # -------------- suggest a measurable goal and a focus area --------------
+    scores = {}
+    if note_pitch_accuracy is not None:
+        scores["pitch"] = note_pitch_accuracy
+    if note_timing_accuracy is not None:
+        scores["timing"] = note_timing_accuracy
+    if note_duration_accuracy is not None:
+        scores["duration"] = note_duration_accuracy
+    if mean_chord_accuracy is not None:
+        scores["chords"] = mean_chord_accuracy
+
+    if scores:
+        main_focus = min(scores, key=scores.get)
+        main_focus_score = scores[main_focus]
+    else:
+        main_focus = None
+        main_focus_score = None
+
+    if main_focus == "pitch":
+        focus_message = (
+            f"Your current pitch accuracy is {main_focus_score:.2f}. Aiming to improve by 5% in your next practice. ")
+
+    elif main_focus == "timing":
+        focus_message = (
+            f"Your current timing accuracy is {main_focus_score:.2f}. Aiming to improve by 5% in your next practice. ")
+
+    elif main_focus == "duration":
+        focus_message = (
+            f"Your current duration accuracy is {main_focus_score:.2f}. Aiming to improve by 5% in your next practice. ")
+
+    elif main_focus == "chords":
+        focus_message = (
+            f"Your current chord accuracy is {main_focus_score:.2f}. Aiming to improve by 5% in your next practice. ")
+
+    else:
+        focus_message = ("Practice the most challenging section you find during practice.")
+
+    all_messages = [
+        "Practice Summary",
+        "",
+        " ".join(current_performance_messages),
+        "",
+        "Tempo",
+        tempo_message,
+        "",
+        "Performance Completeness",
+        " ".join(completeness_messages),
+        "",
+        "Main Practice Focus",
+        focus_message,
+        "",
+        "Practice makes perfect! Keep up the good work and enjoy your music journey!",
+    ]
+        
+    return "\n".join(all_messages)
+
+
 # FeedbackResult class
 # ------------------------------------------------------------------------------
 class FeedbackResult:
@@ -1173,7 +1403,7 @@ def compare_performance_ED(responseMIDI, refMIDI,
     )
 
     # Step 5: Generate human-readable feedback
-    feedback_message = generate_feedback_message(
+    feedback_message = polished_feedback_message(
         event_details, response_events, ref_events, stats,
         global_slow_threshold=global_slow_threshold,
         global_fast_threshold=global_fast_threshold,

From ddf61e605ad822da26029f1f8fa13950d0f93594 Mon Sep 17 00:00:00 2001
From: ada-3e212e610b <z2720629308@gmail.com>
Date: Sat, 1 Aug 2026 13:38:00 +0100
Subject: [PATCH 02/25] adjust feedback

---
 evaluation_function/compare_MIDI.py | 146 ++++++++++++----------------
 1 file changed, 64 insertions(+), 82 deletions(-)

diff --git a/evaluation_function/compare_MIDI.py b/evaluation_function/compare_MIDI.py
index 1f42e7f..605f410 100644
--- a/evaluation_function/compare_MIDI.py
+++ b/evaluation_function/compare_MIDI.py
@@ -1102,61 +1102,11 @@ def polished_feedback_message(event_details, response_events, ref_events, stats,
     total_aligned_events = len(paired_notes) + len(paired_chords)
 
     timing_scale = stats["timing_scale"]
-    timing_offset = stats["timing_offset"]
     duration_scale = stats["duration_scale"]
 
-    # -------------- summarise current performance level --------------
-    # tempo: acceptable / too slow / too fast
-    # ------------------------------------------------------------------
-    timing_pct = abs(timing_scale - 1.0) * 100
-    duration_pct = abs(duration_scale - 1.0) * 100
-    if timing_scale > 1:
-        timing_direction = "behind"
-    elif timing_scale < 1:
-        timing_direction = "ahead of"
-    else:
-        timing_direction = "the same as"
-
-    if duration_scale > 1:
-        duration_direction = "longer than"
-    elif duration_scale < 1:
-        duration_direction = "shorter than"
-    else:
-        duration_direction = "the same as"
-
-    if timing_scale > global_slow_threshold:
-        tempo_message = (
-            f"Overall, your tempo is slower than the reference "
-            f"(timing is about {timing_pct:.0f}% {timing_direction} the reference in general while "
-            f"notes are held about {duration_pct:.0f}% {duration_direction} the reference). "
-            f"No worries! You will get better when you practice more to get more familiar with it!"
-        )
-    elif timing_scale < global_fast_threshold:
-        tempo_message = (
-            f"Overall, your tempo is faster than the reference "
-            f"(timing is about {timing_pct:.0f}% {timing_direction} the reference in general while "
-            f"notes are held about {duration_pct:.0f}% {duration_direction} the reference). "
-            f"Don't rush even if you are confident in your performance." 
-            f"Slow down and give each note its full value."
-        )
-    else:
-        tempo_message = (
-            f"Timing: your overall tempo is within an acceptable range. Good job! "
-            f"The timing is about {timing_pct:.0f}% {timing_direction} the reference in general while "
-            f"notes are held about {duration_pct:.0f}% {duration_direction} than the reference."
-        )
-
-    # missing and extra
-    # ------------------------------------------------------------------
-    total_missing_events = stats["total_notes_missing"] + stats["total_chords_missing"]
-    total_extra_events = stats["total_notes_extra"] + stats["total_chords_extra"]
-    if total_missing_events == 0 and total_extra_events == 0:
-        completeness_messages = "Great! You did not miss or play any extra notes or chords. "
-    else:
-        completeness_messages = "No worries! Slow down and mind your fingering and hand position in your next try. "
-
-    # qualitative feedback on performance accuracy 
-    # ------------------------------------------------------------------
+    # --------------- summarise current performance level ---------------
+    # compute note-level accuracy metrics for pitch, timing, and duration
+    # -------------------------------------------------------------------
     if total_reference_notes > 0:
         note_pitch_correct = (total_reference_notes 
                               - stats["total_notes_wrong_pitch"] - stats["total_notes_missing"])
@@ -1184,65 +1134,95 @@ def polished_feedback_message(event_details, response_events, ref_events, stats,
     else:
         mean_chord_accuracy = None
 
+    # summary qualitative feedback messages based on the accuracy metrics
+    # -------------------------------------------------------------------
     current_performance_messages = []
 
     if note_pitch_accuracy is not None:
         if note_pitch_accuracy >= 0.90:
-            current_performance_messages.append(f"Great! Most notes were played correctly. \n")
+            current_performance_messages.append("Great! Most notes were played correctly.")
         elif note_pitch_accuracy >= 0.70:
             current_performance_messages.append(
-                f"Many notes were correct, although some passages " \
-                f"still need more careful practice. \n"
+                "Many notes were correct, although a few passages "
+                "still need more careful practice."
             )
         else:
             current_performance_messages.append(
-                f"Note accuracy needs more focused practice. " \
-                f"Practise the most difficult passage slowly, " \
-                f"check each note carefully, and then speed up to the correct tempo. \n"
+                "Note accuracy needs more focused practice. " 
+                "Practise the most difficult passage slowly, " 
+                "check each note carefully, and then speed up to the correct tempo. "
             )
 
     if note_timing_accuracy is not None:
         if note_timing_accuracy >= 0.90:
             current_performance_messages.append(
-                f"Great timing consistency between notes! \n"
+                "Great timing consistency between notes! "
             )
         elif note_timing_accuracy >= 0.70:
             current_performance_messages.append(
-                f"Timing of some passages need more careful practice, good overall! \n" 
+                "Timing of a few passages need more careful practice, good overall! " 
             )
         else:
             current_performance_messages.append(
-                f"Timing consistency needs more practice, " \
-                f"you may find it helpful to practice with a metronome. \n"
+                "Timing consistency needs more practice, "
+                "you may find it helpful to practice with a metronome. "
             )
         # do not comment on duration for now, as it may be due to transcription errors
 
     if mean_chord_accuracy is not None:
         if mean_chord_accuracy >= 0.90:
-            current_performance_messages.append(
-                f"Well done on the chords!"
-            )
+            current_performance_messages.append("Well done on the chords!")
         elif mean_chord_accuracy >= 0.70:
             current_performance_messages.append(
-                f"Many chord notes were correct, but some chords contained "
-                f"missing or additional notes."
+                "Many chord notes were correct, but some chords contained "
+                "missing or additional notes."
             )
         else:
             current_performance_messages.append(
-                f"Chord accuracy needs more focused practice, " 
-                f"they are often hard to play correctly at the beginning. " 
-                f"Pay attention to the fingering and hand position when playing chords."
-                f"You may find it helpful to practise each chord separately before reconnecting the surrounding passage."
+                "Chord accuracy needs more focused practice, " 
+                "they are often hard to play correctly at the beginning. " 
+                "Pay attention to the fingering and hand position when playing chords. "
+                "You may find it helpful to practise each chord separately before reconnecting the surrounding passage."
             )
 
+    # overall tempo feedback based on timing and duration scale factors
+    # -------------------------------------------------------------------
+    if timing_scale > global_slow_threshold:
+        tempo_message = (
+            "Your overall tempo was slower than the reference. It is a good idea to "
+            "play slowly while learning, so focus on maintaining a steady tempo "
+            "before gradually increasing the speed."
+        )
+    elif timing_scale < global_fast_threshold:
+        tempo_message = (
+            "Your overall tempo was faster than the reference. Try slowing "
+            "down slightly so that each note can be played clearly."
+        )
+    else:
+        tempo_message = (
+            "Well done! Your overall tempo was close to the reference, keep on the good work!"
+        )
+
+    # missing and extra
+    # ------------------------------------------------------------------
+    total_missing_events = stats["total_notes_missing"] + stats["total_chords_missing"]
+    total_extra_events = stats["total_notes_extra"] + stats["total_chords_extra"]
+    if total_missing_events == 0 and total_extra_events == 0:
+        completeness_messages = "Great! You did not miss or play any extra notes or chords. "
+    else:
+        completeness_messages = (
+            "No worries! It is common to miss or play extra notes when learning a new piece, " 
+            "especially difficult passages. You can slow down in your next practice and pay "
+            "more attention to your fingering and hand position. ")
+
     # -------------- suggest a measurable goal and a focus area --------------
     scores = {}
     if note_pitch_accuracy is not None:
         scores["pitch"] = note_pitch_accuracy
     if note_timing_accuracy is not None:
         scores["timing"] = note_timing_accuracy
-    if note_duration_accuracy is not None:
-        scores["duration"] = note_duration_accuracy
+    # if note_duration_accuracy is not None:
+        # scores["duration"] = note_duration_accuracy
     if mean_chord_accuracy is not None:
         scores["chords"] = mean_chord_accuracy
 
@@ -1255,19 +1235,21 @@ def polished_feedback_message(event_details, response_events, ref_events, stats,
 
     if main_focus == "pitch":
         focus_message = (
-            f"Your current pitch accuracy is {main_focus_score:.2f}. Aiming to improve by 5% in your next practice. ")
-
+            "Choose one short challenging passage and practice it slowly. "
+            "Aim to play this phrase correctly three times in a row before increasing the tempo."
+        )
     elif main_focus == "timing":
         focus_message = (
-            f"Your current timing accuracy is {main_focus_score:.2f}. Aiming to improve by 5% in your next practice. ")
-
-    elif main_focus == "duration":
-        focus_message = (
-            f"Your current duration accuracy is {main_focus_score:.2f}. Aiming to improve by 5% in your next practice. ")
+            "Practice with a slower steady beat, better with a metronome. "
+            "Repeat it until you can keep the spacing between the notes evenly three times in a row. "
+            "Then gradually increase the tempo to the correct speed."
+        )
 
     elif main_focus == "chords":
         focus_message = (
-            f"Your current chord accuracy is {main_focus_score:.2f}. Aiming to improve by 5% in your next practice. ")
+            "Practice the difficult chords separately. Adjust your hand position and "
+            "to make all required notes sound together, then practice the short passage ."
+        )
 
     else:
         focus_message = ("Practice the most challenging section you find during practice.")

From 593c5547d5ec856ed8deb3810f3b0535bf59f3aa Mon Sep 17 00:00:00 2001
From: ada-3e212e610b <z2720629308@gmail.com>
Date: Sat, 1 Aug 2026 23:26:21 +0100
Subject: [PATCH 03/25] update feedback

---
 evaluation_function/compare_MIDI.py | 149 ++++++++++++++++------------
 1 file changed, 86 insertions(+), 63 deletions(-)

diff --git a/evaluation_function/compare_MIDI.py b/evaluation_function/compare_MIDI.py
index 605f410..0351a6f 100644
--- a/evaluation_function/compare_MIDI.py
+++ b/evaluation_function/compare_MIDI.py
@@ -1069,8 +1069,8 @@ def polished_feedback_message(event_details, response_events, ref_events, stats,
     """
     Generate concise, practice-oriented feedback that aims to:
         1. summarise current performance level qualitatively
-        2. suggest a measurable goal for the next attempt with a main focus area
-        3. provide encouraging actionable advice for improvement
+        2. provide encouraging actionable advice for improvement
+        3. suggest a measurable goal for the next attempt with a main focus area
     Individual note and chord errors remain available in event_details but
     will not list each of them in the message.
 
@@ -1099,10 +1099,7 @@ def polished_feedback_message(event_details, response_events, ref_events, stats,
 
     total_reference_notes = stats["total_notes_in_reference"]
     total_reference_chords = stats["total_chords_in_reference"]
-    total_aligned_events = len(paired_notes) + len(paired_chords)
-
-    timing_scale = stats["timing_scale"]
-    duration_scale = stats["duration_scale"]
+    total_reference_events = total_reference_notes + total_reference_chords
 
     # --------------- summarise current performance level ---------------
     # compute note-level accuracy metrics for pitch, timing, and duration
@@ -1112,27 +1109,27 @@ def polished_feedback_message(event_details, response_events, ref_events, stats,
                               - stats["total_notes_wrong_pitch"] - stats["total_notes_missing"])
         note_pitch_accuracy = note_pitch_correct / total_reference_notes
 
-        timing_correct = (total_reference_notes 
+        note_timing_correct = (total_reference_notes 
                           - stats["total_notes_wrong_timing"] - stats["total_notes_missing"])
-        note_timing_accuracy = timing_correct / total_reference_notes
+        note_timing_accuracy = note_timing_correct / total_reference_notes
      
-        duration_correct = (total_reference_notes
+        note_duration_correct = (total_reference_notes
                             - stats["total_notes_wrong_duration"] - stats["total_notes_missing"])
-        note_duration_accuracy = duration_correct / total_reference_notes 
+        note_duration_accuracy = note_duration_correct / total_reference_notes 
     else:
         note_pitch_accuracy = None
         note_timing_accuracy = None
         note_duration_accuracy = None
  
-    if total_reference_chords > 0:
-        sum_chord_accuracy = sum(
-            event["chord_accuracy"]
-            for event in paired_chords
-            if event["chord_accuracy"] is not None
-        )
-        mean_chord_accuracy = sum_chord_accuracy / total_reference_chords
+    paired_chord_accuracies = [event["chord_accuracy"] 
+                               for event in paired_chords 
+                               if event["chord_accuracy"] is not None]
+    # Missing chords were never matched, treat as 0 accuracy for the purpose of computing median chord accuracy
+    paired_chord_accuracies = paired_chord_accuracies + [0.0] * stats["total_chords_missing"]
+    if paired_chord_accuracies:
+        median_chord_accuracy = float(np.median(paired_chord_accuracies))
     else:
-        mean_chord_accuracy = None
+        median_chord_accuracy = None
 
     # summary qualitative feedback messages based on the accuracy metrics
     # -------------------------------------------------------------------
@@ -1140,17 +1137,22 @@ def polished_feedback_message(event_details, response_events, ref_events, stats,
 
     if note_pitch_accuracy is not None:
         if note_pitch_accuracy >= 0.90:
-            current_performance_messages.append("Great! Most notes were played correctly.")
+            current_performance_messages.append(
+                "Great! Most notes were played correctly, " \
+                "you've got a good grasp of the melody.")
         elif note_pitch_accuracy >= 0.70:
             current_performance_messages.append(
-                "Many notes were correct, although a few passages "
-                "still need more careful practice."
+                "Many notes were correct, although a few passages " \
+                "still need more careful practice. Try slowing down in " \
+                "these sections and checking each note before gradually " \
+                "returning to the intended tempo."
             )
         else:
             current_performance_messages.append(
                 "Note accuracy needs more focused practice. " 
-                "Practise the most difficult passage slowly, " 
-                "check each note carefully, and then speed up to the correct tempo. "
+                "Practice one short passage at slower tempo, " 
+                "check each note carefully, and then speed up to the correct tempo. " \
+                "Move on to the next passage when you feel confident with current one."
             )
 
     if note_timing_accuracy is not None:
@@ -1160,59 +1162,82 @@ def polished_feedback_message(event_details, response_events, ref_events, stats,
             )
         elif note_timing_accuracy >= 0.70:
             current_performance_messages.append(
-                "Timing of a few passages need more careful practice, good overall! " 
+                "The spacing between notes was mostly consistent, although " \
+                "a few passages were less steady. Practicing these sections " \
+                "with a slower, regular beat may help make the rhythm more even."
             )
         else:
             current_performance_messages.append(
-                "Timing consistency needs more practice, "
-                "you may find it helpful to practice with a metronome. "
+                "Timing consistency needs more practice, listen carefully " \
+                "for notes that arrive too early or too late. " \
+                "You may find it helpful to practice with a metronome. "
             )
         # do not comment on duration for now, as it may be due to transcription errors
 
-    if mean_chord_accuracy is not None:
-        if mean_chord_accuracy >= 0.90:
-            current_performance_messages.append("Well done on the chords!")
-        elif mean_chord_accuracy >= 0.70:
+    if total_reference_chords > 0:
+        if median_chord_accuracy is None or median_chord_accuracy < 0.70:
+            current_performance_messages.append(
+                            "Simultaneous notes are often hard to play correctly at the beginning. " \
+                            "Pay attention to the fingering and hand position when playing these chords. " \
+                            "Practice those sections slowly and carefully, and check that all required notes sound together. " \
+                            "You may find it helpful to practice each chord separately before reconnecting the surrounding passage."
+                        )
+        elif median_chord_accuracy >= 0.90:
             current_performance_messages.append(
-                "Many chord notes were correct, but some chords contained "
-                "missing or additional notes."
+                "Nice! The chord notes were accurate overall."
             )
-        else:
+        elif median_chord_accuracy >= 0.70:
             current_performance_messages.append(
-                "Chord accuracy needs more focused practice, " 
-                "they are often hard to play correctly at the beginning. " 
-                "Pay attention to the fingering and hand position when playing chords. "
-                "You may find it helpful to practise each chord separately before reconnecting the surrounding passage."
+                "Many chord notes were correct, although some chords included " \
+                "missing or additional notes. Practice each difficult chord " \
+                "separately and check that all required notes sound together."
             )
 
     # overall tempo feedback based on timing and duration scale factors
     # -------------------------------------------------------------------
+    timing_scale = stats["timing_scale"]
+    duration_scale = stats["duration_scale"]
     if timing_scale > global_slow_threshold:
         tempo_message = (
-            "Your overall tempo was slower than the reference. It is a good idea to "
-            "play slowly while learning, so focus on maintaining a steady tempo "
+            "Your overall tempo was slower than the reference. It is a good idea to " \
+            "play slowly while learning, so focus on maintaining a steady tempo " \
             "before gradually increasing the speed."
         )
     elif timing_scale < global_fast_threshold:
         tempo_message = (
-            "Your overall tempo was faster than the reference. Try slowing "
-            "down slightly so that each note can be played clearly."
+            "Your overall tempo was faster than the reference. Try slowing " \
+            "down slightly so that each note can be played clearly and the rhythm remains controlled."
         )
     else:
         tempo_message = (
-            "Well done! Your overall tempo was close to the reference, keep on the good work!"
+            "Well done! Your overall tempo was close to the reference. Keep up the good work!"
         )
 
     # missing and extra
     # ------------------------------------------------------------------
-    total_missing_events = stats["total_notes_missing"] + stats["total_chords_missing"]
-    total_extra_events = stats["total_notes_extra"] + stats["total_chords_extra"]
-    if total_missing_events == 0 and total_extra_events == 0:
-        completeness_messages = "Great! You did not miss or play any extra notes or chords. "
+    total_missing_events = (stats["total_notes_missing"] + stats["total_chords_missing"])
+    total_extra_events = (stats["total_notes_extra"] + stats["total_chords_extra"])
+    total_completeness_errors = (total_missing_events + total_extra_events)
+    if total_reference_events > 0:
+        completeness_error_rate = total_completeness_errors / total_reference_events
     else:
+        completeness_error_rate = 0.0
+
+    if total_completeness_errors == 0:
         completeness_messages = (
-            "No worries! It is common to miss or play extra notes when learning a new piece, " 
-            "especially difficult passages. You can slow down in your next practice and pay "
+            "You completed the performance without missing or adding any " \
+            "notes or chords. Well done!"
+        )
+    elif completeness_error_rate <= 0.10:
+        completeness_messages = (
+            "The performance was mostly complete, with only a few missing " \
+            "or additional notes or chords. Review the affected passages " \
+            "slowly and check your fingering before playing them again."
+        )
+    else:
+        completeness_messages = (
+            "No worries! It is common to miss or play extra notes when learning a new piece, " \
+            "especially difficult passages. You can slow down in your next practice and pay " \
             "more attention to your fingering and hand position. ")
 
     # -------------- suggest a measurable goal and a focus area --------------
@@ -1223,36 +1248,34 @@ def polished_feedback_message(event_details, response_events, ref_events, stats,
         scores["timing"] = note_timing_accuracy
     # if note_duration_accuracy is not None:
         # scores["duration"] = note_duration_accuracy
-    if mean_chord_accuracy is not None:
-        scores["chords"] = mean_chord_accuracy
+    if median_chord_accuracy is not None:
+        scores["chords"] = median_chord_accuracy
 
     if scores:
         main_focus = min(scores, key=scores.get)
-        main_focus_score = scores[main_focus]
     else:
         main_focus = None
-        main_focus_score = None
 
     if main_focus == "pitch":
         focus_message = (
-            "Choose one short challenging passage and practice it slowly. "
+            "For your next attempt, choose one short challenging passage and practice it slowly. " \
             "Aim to play this phrase correctly three times in a row before increasing the tempo."
         )
     elif main_focus == "timing":
         focus_message = (
-            "Practice with a slower steady beat, better with a metronome. "
-            "Repeat it until you can keep the spacing between the notes evenly three times in a row. "
+            "Practice with a slower, steady beat, preferably using a metronome. " \
+            "Aim to keep the spacing between the notes evenly three times in a row. " \
             "Then gradually increase the tempo to the correct speed."
         )
-
     elif main_focus == "chords":
         focus_message = (
-            "Practice the difficult chords separately. Adjust your hand position and "
-            "to make all required notes sound together, then practice the short passage ."
+            "For your next attempt, choose one difficult chord and aim to make " \
+            "all required notes sound together correctly three times in a row. " \
+            "Then gradually connect it to the surrounding passage."
         )
-
     else:
-        focus_message = ("Practice the most challenging section you find during practice.")
+        focus_message = ("For your next attempt, choose one short challenging section and " \
+            "aim to play it confidently three times in a row.")
 
     all_messages = [
         "Practice Summary",
@@ -1262,13 +1285,13 @@ def polished_feedback_message(event_details, response_events, ref_events, stats,
         "Tempo",
         tempo_message,
         "",
-        "Performance Completeness",
-        " ".join(completeness_messages),
+        "Performance Completeness", 
+        completeness_messages,
         "",
         "Main Practice Focus",
         focus_message,
         "",
-        "Practice makes perfect! Keep up the good work and enjoy your music journey!",
+        "Keep up the good work and enjoy your music journey!",
     ]
         
     return "\n".join(all_messages)

From cbfd5200b98f8ae5b8c950079006fca6b9c0275d Mon Sep 17 00:00:00 2001
From: ada-3e212e610b <z2720629308@gmail.com>
Date: Sun, 2 Aug 2026 17:44:01 +0100
Subject: [PATCH 04/25] update main focus feedback

---
 evaluation_function/compare_MIDI.py | 37 +++++++++++++++++++----------
 1 file changed, 24 insertions(+), 13 deletions(-)

diff --git a/evaluation_function/compare_MIDI.py b/evaluation_function/compare_MIDI.py
index 0351a6f..a1558ea 100644
--- a/evaluation_function/compare_MIDI.py
+++ b/evaluation_function/compare_MIDI.py
@@ -1150,9 +1150,9 @@ def polished_feedback_message(event_details, response_events, ref_events, stats,
         else:
             current_performance_messages.append(
                 "Note accuracy needs more focused practice. " 
-                "Practice one short passage at slower tempo, " 
+                "Practice one short passage at a slower tempo, " 
                 "check each note carefully, and then speed up to the correct tempo. " \
-                "Move on to the next passage when you feel confident with current one."
+                "Move on to the next passage when you feel confident with the current one."
             )
 
     if note_timing_accuracy is not None:
@@ -1253,29 +1253,40 @@ def polished_feedback_message(event_details, response_events, ref_events, stats,
 
     if scores:
         main_focus = min(scores, key=scores.get)
+        main_focus_score = scores[main_focus]
     else:
         main_focus = None
+        main_focus_score = None
 
-    if main_focus == "pitch":
+    if main_focus_score is not None and main_focus_score >= 0.90:
         focus_message = (
-            "For your next attempt, choose one short challenging passage and practice it slowly. " \
-            "Aim to play this phrase correctly three times in a row before increasing the tempo."
+            "Excellent work! You already have a good understanding of the melody and the rhythm. " \
+            "For your next attempt, choose one short challenging section and " \
+            "aim to play it confidently three times in a row.")
+    elif main_focus == "pitch":
+        overall_message = "You've got a good understanding of the rhythm. " if main_focus_score >= 0.70 else "Good progress! "
+        focus_message = (
+            overall_message + "Let's focus on note accuracy next. Choose one short challenging " \
+            "passage and practice it slowly. Aim to play this phrase correctly " \
+            "three times in a row before increasing the tempo and moving on."
         )
     elif main_focus == "timing":
+        overall_message = "You've got a good understanding of the melody. " if main_focus_score >= 0.70 else "Good progress! "
         focus_message = (
-            "Practice with a slower, steady beat, preferably using a metronome. " \
-            "Aim to keep the spacing between the notes evenly three times in a row. " \
-            "Then gradually increase the tempo to the correct speed."
+            overall_message + "Let's focus on timing next. Practice with a slower, steady beat, " \
+            "preferably using a metronome. Aim to keep the spacing between the " \
+            "notes even three times in a row, then gradually increase the tempo."
         )
     elif main_focus == "chords":
+        overall_message = "You've got a good understanding of the melody and the rhythm. " if main_focus_score >= 0.70 else "Good progress! "
         focus_message = (
-            "For your next attempt, choose one difficult chord and aim to make " \
-            "all required notes sound together correctly three times in a row. " \
-            "Then gradually connect it to the surrounding passage."
+            overall_message + "Let's focus on chord accuracy next. Choose one difficult chord " \
+            "and adjust your hand position. Aim to make all required notes " \
+            "sound together correctly three times in a row."
         )
     else:
-        focus_message = ("For your next attempt, choose one short challenging section and " \
-            "aim to play it confidently three times in a row.")
+        # scores was empty: no reference notes/chords to evaluate at all.
+        focus_message = "No reference notes or chords were found to evaluate."
 
     all_messages = [
         "Practice Summary",

From 0d3c959e9608038ca026bb349c285590ecc402c9 Mon Sep 17 00:00:00 2001
From: ada-3e212e610b <z2720629308@gmail.com>
Date: Sun, 2 Aug 2026 21:37:43 +0100
Subject: [PATCH 05/25] fix the spacing

---
 evaluation_function/compare_MIDI.py | 3 +--
 1 file changed, 1 insertion(+), 2 deletions(-)

diff --git a/evaluation_function/compare_MIDI.py b/evaluation_function/compare_MIDI.py
index a1558ea..23db750 100644
--- a/evaluation_function/compare_MIDI.py
+++ b/evaluation_function/compare_MIDI.py
@@ -1290,8 +1290,7 @@ def polished_feedback_message(event_details, response_events, ref_events, stats,
 
     all_messages = [
         "Practice Summary",
-        "",
-        " ".join(current_performance_messages),
+        "\n".join(current_performance_messages),
         "",
         "Tempo",
         tempo_message,

From f67c1022170b8ce6e4e83e30c929f972dc382ba2 Mon Sep 17 00:00:00 2001
From: ada-3e212e610b <z2720629308@gmail.com>
Date: Sun, 2 Aug 2026 22:28:52 +0100
Subject: [PATCH 06/25] add examples of feedback messages

---
 notebooks/Phase1-1.5_summary.ipynb | 233 +++++++++++++++++++++++------
 1 file changed, 186 insertions(+), 47 deletions(-)

diff --git a/notebooks/Phase1-1.5_summary.ipynb b/notebooks/Phase1-1.5_summary.ipynb
index 1b7b587..b32e5a8 100644
--- a/notebooks/Phase1-1.5_summary.ipynb
+++ b/notebooks/Phase1-1.5_summary.ipynb
@@ -35,23 +35,27 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 1,
    "id": "c3152f6b",
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Import\n",
     "from evaluation_function.compare_MIDI import (\n",
     "    normalize_start_times,\n",
     "    group_notes_into_events,\n",
     "    event_alignment_ED,\n",
     "    estimate_global_timing,\n",
     "    estimate_global_duration_scale,\n",
+    "    event_level_feedback,      \n",
+    "    compute_stats,            \n",
+    "    generate_feedback_message,\n",
+    "    polished_feedback_message,\n",
     "    compare_performance_ED,\n",
     ")\n",
+    "\n",
     "from notebooks.utils.alignment_visualisation import (\n",
     "    plot_edit_distance_alignment,\n",
-    "    )"
+    ")"
    ]
   },
   {
@@ -367,15 +371,7 @@
    "execution_count": 6,
    "id": "5c08f1c6",
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "asap-dataset already exists, skipping download.\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "import pandas as pd\n",
     "\n",
@@ -386,17 +382,49 @@
     "    load_typical_midi_test_case,\n",
     "    plot_typical_alignment_cases,\n",
     "    print_alignment_case_summary\n",
-    ")\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "531d8ed9",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "asap-dataset already exists, skipping download.\n",
+      "ASAP_PATH = /Users/jz7125/compareMusic/data/asap-dataset\n"
+     ]
+    }
+   ],
+   "source": [
+    "from pathlib import Path\n",
+    "import subprocess\n",
+    "\n",
+    "# find the project root directory by looking for the pyproject.toml file\n",
+    "path = Path.cwd().resolve()\n",
+    "while not (path / \"pyproject.toml\").exists():\n",
+    "    path = path.parent\n",
+    "PROJECT_ROOT = path\n",
+    "\n",
+    "DATA_DIR = PROJECT_ROOT / \"data\"\n",
+    "ASAP_PATH = DATA_DIR / \"asap-dataset\"\n",
     "\n",
-    "import os\n",
     "# Note: use CPJKU version (not fosfrancesco) because only CPJKU has\n",
-    "# the note_alignments TSV files are needed for ground truth comparison.\n",
-    "if not os.path.exists(\"asap-dataset\"):\n",
-    "    os.system(\"git clone https://github.com/CPJKU/asap-dataset.git\")\n",
+    "# the note_alignments TSV files needed for ground truth comparison.\n",
+    "if not ASAP_PATH.exists():\n",
+    "    DATA_DIR.mkdir(parents=True, exist_ok=True)\n",
+    "    subprocess.run(\n",
+    "        [\"git\", \"clone\", \"https://github.com/CPJKU/asap-dataset.git\", str(ASAP_PATH)],\n",
+    "        check=True,\n",
+    "    )\n",
     "else:\n",
     "    print(\"asap-dataset already exists, skipping download.\")\n",
     "\n",
-    "ASAP_PATH = \"asap-dataset\""
+    "print(f\"ASAP_PATH = {ASAP_PATH}\")"
    ]
   },
   {
@@ -469,7 +497,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 8,
    "id": "3c7e5ffb",
    "metadata": {},
    "outputs": [
@@ -539,7 +567,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 9,
    "id": "63075a46",
    "metadata": {},
    "outputs": [
@@ -602,7 +630,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 10,
    "id": "8aafbdfb",
    "metadata": {},
    "outputs": [
@@ -661,7 +689,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 11,
    "id": "3999499b",
    "metadata": {},
    "outputs": [
@@ -678,7 +706,7 @@
    ],
    "source": [
     "twinkle_data = load_typical_midi_test_case(\n",
-    "    json_path=\"../data/longMIDIsequence.json\",\n",
+    "    json_path=str(DATA_DIR / \"longMIDIsequence.json\"),\n",
     "    case_name=\"twinkle_scattered_errors\",\n",
     ")\n",
     "\n",
@@ -719,7 +747,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 12,
    "id": "3f97b847",
    "metadata": {},
    "outputs": [
@@ -753,7 +781,7 @@
    "id": "06deb2d0",
    "metadata": {},
    "source": [
-    "### 3-6. Evaluation and feedback generation"
+    "### 3-5. Evaluation and feedback generation"
    ]
   },
   {
@@ -771,15 +799,85 @@
     "    - Duration: The expected duration is predicted from the global duration scale, then the relative difference in duration is calculated by ∣response_duration − predicted_duration∣ / ref_duration, a note is considered correct if this relative difference is within a threshold."
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "id": "9ac8519b",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Step 3: Evaluate each aligned event pair\n",
+    "event_details = event_level_feedback(\n",
+    "    operations, response_events, ref_events,\n",
+    "    timing_scale=timing_scale,\n",
+    "    timing_offset=timing_offset,\n",
+    "    duration_scale=duration_scale,\n",
+    ")"
+   ]
+  },
   {
    "cell_type": "markdown",
-   "id": "f6f8ed5d",
+   "id": "e0d9e7c0",
    "metadata": {},
    "source": [
     "Step 4: summary\n",
-    "- Compute the summary statistics to provide overview feedback, including total notes/chords missing, extra, wrong pitch, wrong timing, and wrong duration, as well as boolean flags indicating whether all paired notes are correct on each dimension. The global trend parameters (timing_scale, timing_offset, duration_scale) are also included. \n",
-    "\n",
+    "- Compute the summary statistics to provide overview feedback, including total notes/chords missing, extra, wrong pitch, wrong timing, and wrong duration, as well as boolean flags indicating whether all paired notes are correct on each dimension. The global trend parameters (timing_scale, timing_offset, duration_scale) are also included. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "id": "af66298b",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'pitch_all_aligned_correct': False,\n",
+       " 'timing_all_correct': False,\n",
+       " 'duration_all_correct': True,\n",
+       " 'total_notes_in_reference': 5,\n",
+       " 'total_notes_missing': 0,\n",
+       " 'total_notes_extra': 0,\n",
+       " 'total_notes_wrong_pitch': 1,\n",
+       " 'total_notes_wrong_timing': 1,\n",
+       " 'total_notes_wrong_duration': 0,\n",
+       " 'total_notes_correct': 3,\n",
+       " 'timing_scale': 1.1962552426602757,\n",
+       " 'timing_offset': -0.10813361294188076,\n",
+       " 'duration_scale': 1.1999999999999997,\n",
+       " 'total_chords_in_reference': 2,\n",
+       " 'total_chords_missing': 0,\n",
+       " 'total_chords_extra': 0,\n",
+       " 'total_chords_correct': 1,\n",
+       " 'total_chords_imperfect': 1,\n",
+       " 'total_chords_wrong': 0}"
+      ]
+     },
+     "execution_count": 14,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Step 4: Compute summary statistics\n",
+    "stats = compute_stats(\n",
+    "    event_details, ref_events,\n",
+    "    timing_scale=timing_scale,\n",
+    "    timing_offset=timing_offset,\n",
+    "    duration_scale=duration_scale,\n",
+    ")\n",
+    "stats"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "1a84cacc",
+   "metadata": {},
+   "source": [
     "Step 5: generate human-readable feedback message from step 3 and step 4\n",
+    "\n",
+    "Old version:\n",
     "- Overview provides a summary of the student's overall performance:\n",
     "    - Tempo judgement based on timing_scale: explicitly states whether the overall tempo is acceptable, too slow, or too fast, along with the duration_scale as supplementary context\n",
     "    - Total count of pitch errors, missing notes, and extra notes\n",
@@ -787,23 +885,13 @@
     "    - Missing/extra notes: identifies the specific note and pitch\n",
     "    - Pitch errors: states the expected and played pitch, and the semitone difference\n",
     "    - Local timing anomalies: reports the absolute and relative deviation after the global trend has been removed\n",
-    "    - Local duration anomalies: reports the deviation direction and magnitude after the global duration scale has been removed\n",
-    "\n",
-    "Step 6: provide an additional overall pass/fail judgement based on step 3 and step 4"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "720a022a",
-   "metadata": {},
-   "source": [
-    "### Example feedback message:"
+    "    - Local duration anomalies: reports the deviation direction and magnitude after the global duration scale has been removed"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
-   "id": "7bcb2de3",
+   "execution_count": 15,
+   "id": "8015d6b2",
    "metadata": {},
    "outputs": [
     {
@@ -827,9 +915,62 @@
     }
    ],
    "source": [
-    "# Calling compare_performance_ED() runs all steps in one call.\n",
-    "result = compare_performance_ED(responseMIDI, referenceMIDI)\n",
-    "print(result.feedback_message)"
+    "# Step 5: Generate feedback messages\n",
+    "# Old version: lists every error individually\n",
+    "old_feedback_message = generate_feedback_message(\n",
+    "    event_details, response_events, ref_events, stats,\n",
+    ")\n",
+    "print(old_feedback_message)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "286ba90a",
+   "metadata": {},
+   "source": [
+    "New version:\n",
+    "- Practice Summary: summarise current performance level qualitatively, covers pitch accuracy, timing, chords, and provide some practice suggestions for improvement.\n",
+    "- Tempo: general overview of tempo\n",
+    "- Performance Completeness: general overview of extra or missing notes or chords\n",
+    "- Main Practice Focus: suggest a measurable goal for the next attempt with a main focus area\n",
+    "\n",
+    "Individual note and chord errors remain available in event_details but will not list each of them in the message."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "id": "6fe717a0",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Practice Summary\n",
+      "Many notes were correct, although a few passages still need more careful practice. Try slowing down in these sections and checking each note before gradually returning to the intended tempo.\n",
+      "The spacing between notes was mostly consistent, although a few passages were less steady. Practicing these sections with a slower, regular beat may help make the rhythm more even.\n",
+      "Many chord notes were correct, although some chords included missing or additional notes. Practice each difficult chord separately and check that all required notes sound together.\n",
+      "\n",
+      "Tempo\n",
+      "Your overall tempo was slower than the reference. It is a good idea to play slowly while learning, so focus on maintaining a steady tempo before gradually increasing the speed.\n",
+      "\n",
+      "Performance Completeness\n",
+      "You completed the performance without missing or adding any notes or chords. Well done!\n",
+      "\n",
+      "Main Practice Focus\n",
+      "You've got a good understanding of the rhythm. Let's focus on note accuracy next. Choose one short challenging passage and practice it slowly. Aim to play this phrase correctly three times in a row before increasing the tempo and moving on.\n",
+      "\n",
+      "Keep up the good work and enjoy your music journey!\n"
+     ]
+    }
+   ],
+   "source": [
+    "# New version: with integrated, practice-oriented summary (current default)\n",
+    "new_feedback_message = polished_feedback_message(\n",
+    "    event_details, response_events, ref_events, stats,\n",
+    ")\n",
+    "print(new_feedback_message)"
    ]
   },
   {
@@ -845,9 +986,7 @@
    "id": "71a6e28f",
    "metadata": {},
    "source": [
-    "visualise the feedback, maybe try the visualisation tool such as LilyPond, music21, or simply use matplotlib to plot PianoRoll.\n",
-    "\n",
-    "Improve the feedback generation parts, maybe do not need to list all the mistakes, learners' always make lots of mistakes during practice, all they need to do is practice more, consider giving integrated feedback, e.g. current performance level, what should it be in the next practice (8/10 notes within tolerance, 9/10 notes correct pitch, keep practicing and compare with last time), some comments/information to motivate learners to try again\n"
+    "visualise the feedback, maybe try the visualisation tool such as LilyPond, music21, or simply use matplotlib to plot PianoRoll.\n"
    ]
   }
  ],

From f7122138db167a5802ff228fb8e733d192acdbc5 Mon Sep 17 00:00:00 2001
From: ada-3e212e610b <z2720629308@gmail.com>
Date: Sun, 2 Aug 2026 22:32:05 +0100
Subject: [PATCH 07/25] ignore large datasets and outputs

---
 .gitignore | 8 +++++---
 1 file changed, 5 insertions(+), 3 deletions(-)

diff --git a/.gitignore b/.gitignore
index ce62690..a2b1253 100644
--- a/.gitignore
+++ b/.gitignore
@@ -134,7 +134,9 @@ dmypy.json
 # Test reports
 reports/
 
-# PianoVAM dataset
-notebooks/data/
+# output data
+/outputs
 
-notebooks/outputs
\ No newline at end of file
+# large dataset
+/data/asap-dataset
+/data/PianoVAM_v1
\ No newline at end of file

From 2103ded3de1473a7258ac9f0a92f819a7f2f2b79 Mon Sep 17 00:00:00 2001
From: ada-3e212e610b <z2720629308@gmail.com>
Date: Mon, 3 Aug 2026 08:56:48 +0100
Subject: [PATCH 08/25] update results

---
 notebooks/Phase2_summary.ipynb | 91 +++++++++++++++++++++-------------
 1 file changed, 57 insertions(+), 34 deletions(-)

diff --git a/notebooks/Phase2_summary.ipynb b/notebooks/Phase2_summary.ipynb
index 483e4ab..16c4136 100644
--- a/notebooks/Phase2_summary.ipynb
+++ b/notebooks/Phase2_summary.ipynb
@@ -28,10 +28,25 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 34,
+   "execution_count": 1,
    "id": "ed89d516",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "scikit-learn version 1.9.0 is not supported. Minimum required version: 0.17. Maximum required version: 1.5.1. Disabling scikit-learn conversion API.\n",
+      "WARNING:root:tflite-runtime is not installed. If you plan to use a TFLite Model, reinstall basic-pitch with `pip install 'basic-pitch tflite-runtime'` or `pip install 'basic-pitch[tf]'\n",
+      "WARNING:root:onnxruntime is not installed. If you plan to use an ONNX Model, reinstall basic-pitch with `pip install 'basic-pitch[onnx]'`\n",
+      "WARNING:root:Tensorflow is not installed. If you plan to use a TF Saved Model, reinstall basic-pitch with `pip install 'basic-pitch[tf]'`\n",
+      "/Users/jz7125/compareMusic/.venv/lib/python3.11/site-packages/resampy/filters.py:50: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.\n",
+      "  import pkg_resources\n",
+      "/Users/jz7125/compareMusic/.venv/lib/python3.11/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n",
+      "  from .autonotebook import tqdm as notebook_tqdm\n"
+     ]
+    }
+   ],
    "source": [
     "from pathlib import Path\n",
     "\n",
@@ -74,20 +89,28 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 2,
    "id": "4a46f481",
    "metadata": {},
    "outputs": [],
    "source": [
+    "from pathlib import Path\n",
+    "\n",
+    "# Find the project root directory by looking for the pyproject.toml file\n",
+    "path = Path.cwd().resolve()\n",
+    "while not (path / \"pyproject.toml\").exists():\n",
+    "    path = path.parent\n",
+    "PROJECT_ROOT = path\n",
+    "\n",
     "# PianoVAM paths\n",
-    "DATA_ROOT = Path(\"data/PianoVAM_v1\")\n",
+    "DATA_ROOT = PROJECT_ROOT / \"data\" / \"PianoVAM_v1\"\n",
     "AUDIO_DIR = DATA_ROOT / \"Audio\"\n",
     "MIDI_DIR = DATA_ROOT / \"MIDI\"\n",
     "TSV_DIR = DATA_ROOT / \"TSV\"\n",
     "METADATA_PATH = DATA_ROOT / \"metadata.json\"\n",
     "\n",
     "# Output paths used for cached predictions and search progress\n",
-    "OUTPUT_DIR = Path(\"outputs/phase2_baseline\")\n",
+    "OUTPUT_DIR = PROJECT_ROOT / \"outputs\" / \"phase2_baseline\"\n",
     "OUTPUT_DIR.mkdir(parents=True, exist_ok=True)\n",
     "RAW_PREDICTIONS_DIR = OUTPUT_DIR / \"raw_predictions\"\n",
     "RAW_PREDICTIONS_DIR.mkdir(parents=True, exist_ok=True)\n",
@@ -379,7 +402,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 6,
    "id": "a438732d",
    "metadata": {},
    "outputs": [
@@ -752,7 +775,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 8,
    "id": "236795e1",
    "metadata": {},
    "outputs": [
@@ -2225,7 +2248,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 9,
    "id": "c9cbad6f",
    "metadata": {},
    "outputs": [],
@@ -2237,7 +2260,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 10,
    "id": "aeeaf819",
    "metadata": {},
    "outputs": [
@@ -2277,7 +2300,7 @@
        "dtype: object"
       ]
      },
-     "execution_count": 13,
+     "execution_count": 10,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -2296,7 +2319,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 11,
    "id": "ff896e42",
    "metadata": {},
    "outputs": [
@@ -2336,7 +2359,7 @@
        "dtype: object"
       ]
      },
-     "execution_count": 14,
+     "execution_count": 11,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -2397,7 +2420,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 12,
    "id": "f9d3d883",
    "metadata": {},
    "outputs": [],
@@ -2417,7 +2440,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 13,
    "id": "2b584385",
    "metadata": {},
    "outputs": [
@@ -2425,7 +2448,7 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "Random search: 100%|██████████| 53/53 [54:02<00:00, 61.18s/it]   \n"
+      "Random search: 100%|██████████| 53/53 [1:00:57<00:00, 69.01s/it] \n"
      ]
     },
     {
@@ -3114,7 +3137,7 @@
        "39           0.632116             0.232620      9777.169811  "
       ]
      },
-     "execution_count": 16,
+     "execution_count": 13,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -3141,7 +3164,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 14,
    "id": "8502b6c1",
    "metadata": {},
    "outputs": [
@@ -3149,7 +3172,7 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "Evaluating configuration: 100%|██████████| 53/53 [11:43<00:00, 13.27s/it]\n"
+      "Evaluating configuration: 100%|██████████| 53/53 [11:50<00:00, 13.41s/it]\n"
      ]
     },
     {
@@ -3161,7 +3184,7 @@
        " 'melodia_trick': False}"
       ]
      },
-     "execution_count": 17,
+     "execution_count": 14,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -3184,7 +3207,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 15,
    "id": "e3a000b2",
    "metadata": {},
    "outputs": [
@@ -3277,7 +3300,7 @@
        "1         26.169811          433.679245  "
       ]
      },
-     "execution_count": 18,
+     "execution_count": 15,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -3293,7 +3316,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": 16,
    "id": "41e143e1",
    "metadata": {},
    "outputs": [
@@ -3693,7 +3716,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 20,
+   "execution_count": 17,
    "id": "dc3d1fb7",
    "metadata": {},
    "outputs": [
@@ -3701,7 +3724,7 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "FP/FN summary: 100%|██████████| 53/53 [02:42<00:00,  3.06s/it]\n"
+      "FP/FN summary: 100%|██████████| 53/53 [02:53<00:00,  3.28s/it]\n"
      ]
     },
     {
@@ -5500,7 +5523,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 21,
+   "execution_count": 18,
    "id": "8cb7dddc",
    "metadata": {},
    "outputs": [
@@ -5508,7 +5531,7 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "Post-processing evaluation: 100%|██████████| 53/53 [08:14<00:00,  9.32s/it]\n"
+      "Post-processing evaluation: 100%|██████████| 53/53 [08:16<00:00,  9.36s/it]\n"
      ]
     },
     {
@@ -5600,7 +5623,7 @@
        "1         25.452830          441.830189  "
       ]
      },
-     "execution_count": 21,
+     "execution_count": 18,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -5636,7 +5659,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 22,
+   "execution_count": 19,
    "id": "99efb174",
    "metadata": {},
    "outputs": [
@@ -5674,7 +5697,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 20,
    "id": "7d57783a",
    "metadata": {},
    "outputs": [
@@ -5682,8 +5705,8 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "Evaluating configuration: 100%|██████████| 9/9 [01:04<00:00,  7.22s/it]\n",
-      "Post-processing evaluation: 100%|██████████| 9/9 [00:39<00:00,  4.39s/it]\n"
+      "Evaluating configuration: 100%|██████████| 9/9 [01:04<00:00,  7.12s/it]\n",
+      "Post-processing evaluation: 100%|██████████| 9/9 [00:39<00:00,  4.38s/it]\n"
      ]
     },
     {
@@ -5775,7 +5798,7 @@
        "1         28.111111          171.333333  "
       ]
      },
-     "execution_count": 23,
+     "execution_count": 20,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -5830,7 +5853,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 21,
    "id": "edb228ba",
    "metadata": {},
    "outputs": [
@@ -5850,7 +5873,7 @@
        "{'matched': 35, 'missing': 7, 'extra': 16}"
       ]
      },
-     "execution_count": 35,
+     "execution_count": 21,
      "metadata": {},
      "output_type": "execute_result"
     }

From 9b722f68e39ff8ceb37537b742390a597d26b190 Mon Sep 17 00:00:00 2001
From: ada-3e212e610b <z2720629308@gmail.com>
Date: Mon, 3 Aug 2026 22:49:46 +0100
Subject: [PATCH 09/25] ignore recordings

---
 .gitignore | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/.gitignore b/.gitignore
index a2b1253..1d25edb 100644
--- a/.gitignore
+++ b/.gitignore
@@ -139,4 +139,5 @@ reports/
 
 # large dataset
 /data/asap-dataset
-/data/PianoVAM_v1
\ No newline at end of file
+/data/PianoVAM_v1
+/data/real_recordings
\ No newline at end of file

From 0aebb5fab69100c5aeec38eaa21d84825b973de1 Mon Sep 17 00:00:00 2001
From: ada-3e212e610b <z2720629308@gmail.com>
Date: Mon, 3 Aug 2026 23:04:59 +0100
Subject: [PATCH 10/25] refine feedback messages

---
 evaluation_function/compare_MIDI.py | 47 +++++++++++++++++------------
 1 file changed, 27 insertions(+), 20 deletions(-)

diff --git a/evaluation_function/compare_MIDI.py b/evaluation_function/compare_MIDI.py
index 23db750..4c80bf1 100644
--- a/evaluation_function/compare_MIDI.py
+++ b/evaluation_function/compare_MIDI.py
@@ -1149,28 +1149,32 @@ def polished_feedback_message(event_details, response_events, ref_events, stats,
             )
         else:
             current_performance_messages.append(
-                "Note accuracy needs more focused practice. " 
-                "Practice one short passage at a slower tempo, " 
-                "check each note carefully, and then speed up to the correct tempo. " \
-                "Move on to the next passage when you feel confident with the current one."
+                "Note accuracy needs more practice. " 
+                "Practice each short passage at a slower tempo, " 
+                "check each note carefully, mind the fingering during practice. " \
+                "Then move on to the next passage when you feel confident with the current one."
             )
 
     if note_timing_accuracy is not None:
         if note_timing_accuracy >= 0.90:
             current_performance_messages.append(
-                "Great timing consistency between notes! "
+                "Great timing consistency between notes, you've got a " \
+                "good sense of onset time and rhythm!"
             )
         elif note_timing_accuracy >= 0.70:
             current_performance_messages.append(
                 "The spacing between notes was mostly consistent, although " \
                 "a few passages were less steady. Practicing these sections " \
-                "with a slower, regular beat may help make the rhythm more even."
+                "with a slower, regular beat may help you play each note at the right time " \
+                "and hence make the rhythm more steady."
             )
         else:
             current_performance_messages.append(
-                "Timing consistency needs more practice, listen carefully " \
+                "Timing consistency needs more practice. You can slow down in your " \
+                "next practice session and listen carefully " \
                 "for notes that arrive too early or too late. " \
-                "You may find it helpful to practice with a metronome. "
+                "A metronome can help you play each note at the right time " \
+                "and hence make the rhythm more steady." 
             )
         # do not comment on duration for now, as it may be due to transcription errors
 
@@ -1179,18 +1183,19 @@ def polished_feedback_message(event_details, response_events, ref_events, stats,
             current_performance_messages.append(
                             "Simultaneous notes are often hard to play correctly at the beginning. " \
                             "Pay attention to the fingering and hand position when playing these chords. " \
-                            "Practice those sections slowly and carefully, and check that all required notes sound together. " \
-                            "You may find it helpful to practice each chord separately before reconnecting the surrounding passage."
+                            "You may find it helpful to practice each chord separately first and make sure " \
+                            "all required notes sound together. Then you can reconnect the chords to" \
+                            "their surronding sections and practice at a slower tempo carefully. "
                         )
         elif median_chord_accuracy >= 0.90:
             current_performance_messages.append(
-                "Nice! The chord notes were accurate overall."
+                "Nice! The chords were played accurately overall."
             )
         elif median_chord_accuracy >= 0.70:
             current_performance_messages.append(
-                "Many chord notes were correct, although some chords included " \
-                "missing or additional notes. Practice each difficult chord " \
-                "separately and check that all required notes sound together."
+                "Most chord notes were played correctly, although some chords contain " \
+                "missing or additional notes. It's a good idea to practice each difficult chord " \
+                "separately and make sure that all required notes sound together."
             )
 
     # overall tempo feedback based on timing and duration scale factors
@@ -1199,18 +1204,20 @@ def polished_feedback_message(event_details, response_events, ref_events, stats,
     duration_scale = stats["duration_scale"]
     if timing_scale > global_slow_threshold:
         tempo_message = (
-            "Your overall tempo was slower than the reference. It is a good idea to " \
-            "play slowly while learning, so focus on maintaining a steady tempo " \
-            "before gradually increasing the speed."
+            "Your overall tempo was slower than the reference. This is not necessarily " \
+            "a problem, and it is a good idea to play slowly while learning. " \
+            "Whatever tempo you choose, aim to keep the rhythm steady throughout the performance."
         )
     elif timing_scale < global_fast_threshold:
         tempo_message = (
-            "Your overall tempo was faster than the reference. Try slowing " \
-            "down slightly so that each note can be played clearly and the rhythm remains controlled."
+            "Your overall tempo was faster than the reference. This is not necessarily " \
+            "a problem. Althogh you are confident in this piece, remember to play each " \
+            "note clearly and make surethe rhythm remains steady."
         )
     else:
         tempo_message = (
-            "Well done! Your overall tempo was close to the reference. Keep up the good work!"
+            "Well done! Your overall tempo was close to the reference. Keep up the good work! " \
+            "Don't forget to keep the rhythm steady throughout the performance."
         )
 
     # missing and extra

From 432965a069baa13bc88477f9d8de69a5f1ba18cd Mon Sep 17 00:00:00 2001
From: ada-3e212e610b <z2720629308@gmail.com>
Date: Mon, 3 Aug 2026 23:06:00 +0100
Subject: [PATCH 11/25] update result, add future work

---
 notebooks/Phase1-1.5_summary.ipynb | 11 +++++++----
 1 file changed, 7 insertions(+), 4 deletions(-)

diff --git a/notebooks/Phase1-1.5_summary.ipynb b/notebooks/Phase1-1.5_summary.ipynb
index b32e5a8..3e40058 100644
--- a/notebooks/Phase1-1.5_summary.ipynb
+++ b/notebooks/Phase1-1.5_summary.ipynb
@@ -949,11 +949,11 @@
      "text": [
       "Practice Summary\n",
       "Many notes were correct, although a few passages still need more careful practice. Try slowing down in these sections and checking each note before gradually returning to the intended tempo.\n",
-      "The spacing between notes was mostly consistent, although a few passages were less steady. Practicing these sections with a slower, regular beat may help make the rhythm more even.\n",
-      "Many chord notes were correct, although some chords included missing or additional notes. Practice each difficult chord separately and check that all required notes sound together.\n",
+      "The spacing between notes was mostly consistent, although a few passages were less steady. Practicing these sections with a slower, regular beat may help you play each note at the right time and hence make the rhythm more steady.\n",
+      "Most chord notes were played correctly, although some chords contain missing or additional notes. It's a good idea to practice each difficult chord separately and make sure that all required notes sound together.\n",
       "\n",
       "Tempo\n",
-      "Your overall tempo was slower than the reference. It is a good idea to play slowly while learning, so focus on maintaining a steady tempo before gradually increasing the speed.\n",
+      "Your overall tempo was slower than the reference. This is not necessarily a problem, and it is a good idea to play slowly while learning. Whatever tempo you choose, aim to keep the rhythm steady throughout the performance.\n",
       "\n",
       "Performance Completeness\n",
       "You completed the performance without missing or adding any notes or chords. Well done!\n",
@@ -986,7 +986,10 @@
    "id": "71a6e28f",
    "metadata": {},
    "source": [
-    "visualise the feedback, maybe try the visualisation tool such as LilyPond, music21, or simply use matplotlib to plot PianoRoll.\n"
+    "- Visualise the feedback: Can try to display the mistakes by annotating or coloring the corresponding notes on the music score, maybe try the visualisation tool such as LilyPond, music21, or simply use matplotlib to plot PianoRoll.\n",
+    "- Progress tracking across practice sessions: The current system evaluates each performance independently. A future extension could compare a student's current attempt with previous attempts on the same piece to identify improvements or recurring difficulties over time. This would help provide more personalised feedback, su that students can monitor their progress more effectively.\n",
+    "- Improve feedback quality: Interviewing more music teachers and students, ask their opions about what makes a feedback useful, clear and motivated. Can also introduce more feedback componets, such as dynamics, phrasing, expression.\n",
+    "- Improve feedback accuracy by reducing the effect of transcription error: May introduce a `confidence level` metrics, estimating the reliability of the automatic transcription, do not provide the feedback if the confidence level is low."
    ]
   }
  ],

From f25cafb10f32cb75ce3d023625cfda2889a3eddf Mon Sep 17 00:00:00 2001
From: ada-3e212e610b <z2720629308@gmail.com>
Date: Mon, 3 Aug 2026 23:50:24 +0100
Subject: [PATCH 12/25] add a notebook to show the pipeline result on
 self-recorded audio

---
 notebooks/Demonstration.ipynb | 388 ++++++++++++++++++++++++++++++++++
 1 file changed, 388 insertions(+)
 create mode 100644 notebooks/Demonstration.ipynb

diff --git a/notebooks/Demonstration.ipynb b/notebooks/Demonstration.ipynb
new file mode 100644
index 0000000..cb31634
--- /dev/null
+++ b/notebooks/Demonstration.ipynb
@@ -0,0 +1,388 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "a025b041",
+   "metadata": {},
+   "source": [
+    "# Overview\n",
+    "\n",
+    "The objective of this project is to design an automated feedback system which provides music students with formative, elaborated feedback for music practice. \n",
+    "\n",
+    "This notebook shows how the full compareMusic pipeline works on a real practice recording:\n",
+    "1. load the reference audio and the response audio files recorded during practice\n",
+    "2. transcribe the audio files into MIDI format using the transcription and post-processing pipeline developed in Phase2 \n",
+    "3. pass the reference MIDI and response MIDI into the MIDI comparison pipeline developed in Phase1 to get the feedback messages\n",
+    "- additionally provides visualisation plots to show the alignment result between the reference and the performance(response)\n",
+    "\n",
+    "Evaluation and analysis of the pipeline's performance are in the other summary notebooks."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "ef8ddb5b",
+   "metadata": {},
+   "source": [
+    "## 1. Setup and Load the audio"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "f77def2e",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "scikit-learn version 1.9.0 is not supported. Minimum required version: 0.17. Maximum required version: 1.5.1. Disabling scikit-learn conversion API.\n",
+      "WARNING:root:tflite-runtime is not installed. If you plan to use a TFLite Model, reinstall basic-pitch with `pip install 'basic-pitch tflite-runtime'` or `pip install 'basic-pitch[tf]'\n",
+      "WARNING:root:onnxruntime is not installed. If you plan to use an ONNX Model, reinstall basic-pitch with `pip install 'basic-pitch[onnx]'`\n",
+      "WARNING:root:Tensorflow is not installed. If you plan to use a TF Saved Model, reinstall basic-pitch with `pip install 'basic-pitch[tf]'`\n",
+      "/Users/jz7125/compareMusic/.venv/lib/python3.11/site-packages/resampy/filters.py:50: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.\n",
+      "  import pkg_resources\n"
+     ]
+    }
+   ],
+   "source": [
+    "from pathlib import Path\n",
+    "\n",
+    "import pandas as pd\n",
+    "import matplotlib.pyplot as plt\n",
+    "\n",
+    "from evaluation_function.audio_processing import (\n",
+    "    load_basic_pitch_model,\n",
+    "    transcription_pipeline,\n",
+    ")\n",
+    "from evaluation_function.compare_MIDI import (\n",
+    "    compare_performance_ED,\n",
+    "    normalize_start_times,\n",
+    "    group_notes_into_events,\n",
+    "    DEFAULT_CHORD_ONSET_WINDOW,\n",
+    ")\n",
+    "\n",
+    "from notebooks.utils.nasap_alignment_evaluation import plot_alignment"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "8d9d98d4",
+   "metadata": {},
+   "source": [
+    "Load the data:\n",
+    "\n",
+    "- Response: 2 audio files of the same song recorded by my supervisor during daily practice.\n",
+    "- Reference: using a tool called 'soundslice' to generate audio file from the music score provided by my supervisor."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "11838aa7",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Practice1 file: /Users/jz7125/compareMusic/data/real_recordings/practice_01.m4a\n",
+      "Practice2 file: /Users/jz7125/compareMusic/data/real_recordings/practice_02.m4a\n",
+      "Reference score: /Users/jz7125/compareMusic/data/real_recordings/reference_score.m4a\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Find the project root directory by looking for the pyproject.toml file\n",
+    "path = Path.cwd().resolve()\n",
+    "while not (path / \"pyproject.toml\").exists():\n",
+    "    path = path.parent\n",
+    "PROJECT_ROOT = path\n",
+    "DATA_ROOT = PROJECT_ROOT / \"data\" / \"real_recordings\"\n",
+    "\n",
+    "# path to the audio files and reference MIDI file\n",
+    "PRACTICE01_PATH = DATA_ROOT / \"practice_01.m4a\"\n",
+    "PRACTICE02_PATH = DATA_ROOT / \"practice_02.m4a\"\n",
+    "REFERENCE_AUDIO_PATH = DATA_ROOT / \"reference_score.m4a\"\n",
+    "\n",
+    "assert PRACTICE01_PATH.exists(), f\"Audio file not found: {PRACTICE01_PATH}\"\n",
+    "assert PRACTICE02_PATH.exists(), f\"Audio file not found: {PRACTICE02_PATH}\"\n",
+    "assert REFERENCE_AUDIO_PATH.exists(), f\"Reference MIDI not found: {REFERENCE_AUDIO_PATH}\"\n",
+    "\n",
+    "print(\"Practice1 file:\", PRACTICE01_PATH)\n",
+    "print(\"Practice2 file:\", PRACTICE02_PATH)\n",
+    "print(\"Reference score:\", REFERENCE_AUDIO_PATH)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "a872e18c",
+   "metadata": {},
+   "source": [
+    "## 2. Audio-to-MIDI Transcription"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "d37d0534",
+   "metadata": {},
+   "source": [
+    "Both the practice recording and the reference audio are transcribed using the same audio-to-MIDI pipeline, therefore transcrition error may occur in either side. A manually-inspected reference MIDI generated directly from the music score would be preferable."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "c96f63b5",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Transcribed practice recording 01: 94 notes in 1.4s\n",
+      "Transcribed practice recording 02: 80 notes in 0.6s\n",
+      "Transcribed reference recording: 162 notes in 0.4s\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Load the Basic Pitch model once, reuse it for both files\n",
+    "basic_pitch_model = load_basic_pitch_model()\n",
+    "\n",
+    "# Transcribe the practice recording 01\n",
+    "response1, predicted_notes1, response_runtime_seconds1 = transcription_pipeline(\n",
+    "    PRACTICE01_PATH,\n",
+    "    basic_pitch_model,\n",
+    "    apply_postprocessing=True,\n",
+    ")\n",
+    "\n",
+    "# Transcribe the practice recording 02\n",
+    "response2, predicted_notes2, response_runtime_seconds2 = transcription_pipeline(\n",
+    "    PRACTICE02_PATH,\n",
+    "    basic_pitch_model,\n",
+    "    apply_postprocessing=True,\n",
+    ")\n",
+    "\n",
+    "# Transcribe the reference recording\n",
+    "reference, reference_notes, reference_runtime_seconds = transcription_pipeline(\n",
+    "    REFERENCE_AUDIO_PATH,\n",
+    "    basic_pitch_model,\n",
+    "    apply_postprocessing=True,\n",
+    ")\n",
+    "\n",
+    "print(f\"Transcribed practice recording 01: {len(predicted_notes1)} notes \"\n",
+    "      f\"in {response_runtime_seconds1:.1f}s\")\n",
+    "print(f\"Transcribed practice recording 02: {len(predicted_notes2)} notes \"\n",
+    "      f\"in {response_runtime_seconds2:.1f}s\")\n",
+    "print(f\"Transcribed reference recording: {len(reference_notes)} notes \"\n",
+    "      f\"in {reference_runtime_seconds:.1f}s\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "a296a402",
+   "metadata": {},
+   "source": [
+    "Visualise the transcribed MIDI using Piano Roll"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "bd6898ce",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1400x600 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "def plot_piano_roll_comparison(predicted_notes, reference_notes, title=\"Piano roll comparison\"):\n",
+    "    fig, ax = plt.subplots(figsize=(14, 6))\n",
+    "\n",
+    "    for note in reference_notes:\n",
+    "        offset = note[\"start\"] + note[\"duration\"]\n",
+    "        ax.plot(\n",
+    "            [note[\"start\"], offset],\n",
+    "            [note[\"pitch\"], note[\"pitch\"]],\n",
+    "            linewidth=4,\n",
+    "            alpha=0.6,\n",
+    "            color=\"lightgray\",\n",
+    "            label=\"Reference\",\n",
+    "        )\n",
+    "\n",
+    "    for note in predicted_notes:\n",
+    "        offset = note[\"onset\"] + note[\"duration\"]\n",
+    "        ax.plot(\n",
+    "            [note[\"onset\"], offset],\n",
+    "            [note[\"pitch\"], note[\"pitch\"]],\n",
+    "            linewidth=2,\n",
+    "            alpha=0.9,\n",
+    "            color=\"tab:blue\",\n",
+    "            label=\"Practice\",\n",
+    "        )\n",
+    "\n",
+    "    handles, labels = ax.get_legend_handles_labels()\n",
+    "    unique = dict(zip(labels, handles))\n",
+    "    ax.legend(unique.values(), unique.keys(), loc=\"upper right\")\n",
+    "\n",
+    "    ax.set_xlabel(\"Time (s)\")\n",
+    "    ax.set_ylabel(\"MIDI pitch\")\n",
+    "    ax.set_title(title)\n",
+    "    ax.grid(alpha=0.15)\n",
+    "    plt.tight_layout()\n",
+    "    plt.show()\n",
+    "\n",
+    "plot_piano_roll_comparison(predicted_notes1, reference[\"notes\"], title=\"practice 01 vs. reference\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "19b1447b",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1400x600 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plot_piano_roll_comparison(predicted_notes2, reference[\"notes\"], title=\"practice 02 vs. reference\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "edf24a31",
+   "metadata": {},
+   "source": [
+    "## 3. Compare reference and response to generate feedback messages"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "c748d0de",
+   "metadata": {},
+   "source": [
+    "The two practice recordings were recorded on the same day, the level of performance is the same (similar patterns observed from the piano roll), therefore here just generate the feedback for practice 01 for presentation."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "2afb8b23",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Practice Summary\n",
+      "Note accuracy needs more practice. Practice each short passage at a slower tempo, check each note carefully, mind the fingering during practice. Then move on to the next passage when you feel confident with the current one.\n",
+      "Timing consistency needs more practice. You can slow down in your next practice session and listen carefully for notes that arrive too early or too late. A metronome can help you play each note at the right time and hence make the rhythm more steady.\n",
+      "Simultaneous notes are often hard to play correctly at the beginning. Pay attention to the fingering and hand position when playing these chords. You may find it helpful to practice each chord separately first and make sure all required notes sound together. Then you can reconnect the chords totheir surronding sections and practice at a slower tempo carefully. \n",
+      "\n",
+      "Tempo\n",
+      "Your overall tempo was slower than the reference. This is not necessarily a problem, and it is a good idea to play slowly while learning. Whatever tempo you choose, aim to keep the rhythm steady throughout the performance.\n",
+      "\n",
+      "Performance Completeness\n",
+      "No worries! It is common to miss or play extra notes when learning a new piece, especially difficult passages. You can slow down in your next practice and pay more attention to your fingering and hand position. \n",
+      "\n",
+      "Main Practice Focus\n",
+      "Good progress! Let's focus on timing next. Practice with a slower, steady beat, preferably using a metronome. Aim to keep the spacing between the notes even three times in a row, then gradually increase the tempo.\n",
+      "\n",
+      "Keep up the good work and enjoy your music journey!\n"
+     ]
+    }
+   ],
+   "source": [
+    "result1 = compare_performance_ED(response1, reference)\n",
+    "print(result1.feedback_message)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "28e44b6b",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 1500x800 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Selected operations: 114\n",
+      "Note connectors: 94\n",
+      "Missing note markers: 29\n",
+      "Extra note markers: 0\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Regenerate the grouped events compare_performance_ED used internally --\n",
+    "# same two calls as its own Step 0, with the same default chord_onset_window\n",
+    "# (change this if you passed a custom chord_onset_window to compare_performance_ED above)\n",
+    "response_events = group_notes_into_events(\n",
+    "    normalize_start_times(response1[\"notes\"]), DEFAULT_CHORD_ONSET_WINDOW\n",
+    ")\n",
+    "ref_events = group_notes_into_events(\n",
+    "    normalize_start_times(reference[\"notes\"]), DEFAULT_CHORD_ONSET_WINDOW\n",
+    ")\n",
+    "\n",
+    "# Zoom into the whole piece: 0 to the last reference note's end time\n",
+    "ref_end = max(\n",
+    "    note[\"start\"] + note[\"duration\"]\n",
+    "    for event in ref_events\n",
+    "    for note in event[\"notes\"]\n",
+    ")\n",
+    "\n",
+    "# Usage\n",
+    "plot_alignment(ref_events, response_events, result1.event_details, ref_start=0.0, ref_end=ref_end)"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": ".venv",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.15"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

From ccbd19c27c87d45099c36ae95c736c1a1c5f25cb Mon Sep 17 00:00:00 2001
From: ada-3e212e610b <z2720629308@gmail.com>
Date: Sat, 8 Aug 2026 21:50:16 +0100
Subject: [PATCH 13/25] handle audio input

---
 evaluation_function/evaluation.py | 32 +++++++++++++++++++++++++++++--
 1 file changed, 30 insertions(+), 2 deletions(-)

diff --git a/evaluation_function/evaluation.py b/evaluation_function/evaluation.py
index 6344161..a8485d9 100755
--- a/evaluation_function/evaluation.py
+++ b/evaluation_function/evaluation.py
@@ -19,6 +19,14 @@
     GLOBAL_FAST_THRESHOLD,
     DEFAULT_CHORD_ONSET_WINDOW
 )
+from .audio_processing import (
+    is_audio_input,
+    load_basic_pitch_model,
+    transcription_pipeline,
+)
+# Load the Basic Pitch model once, when this file is first imported.
+BASIC_PITCH_MODEL = load_basic_pitch_model()
+
 
 def parse_json_input(data: Any) -> Any:
     """
@@ -29,6 +37,26 @@ def parse_json_input(data: Any) -> Any:
     return data
 
 
+def prepare_input(raw_input: Any) -> Any:
+    """
+    Turn one raw input (either response or answer) into the
+    format that compare_performance_ED expects.
+
+    There are two possible cases:
+      - raw_input is an audio file path
+        -> run it through the AMT (audio-to-MIDI) transcription pipeline
+      - raw_input is already MIDI (a dict, or a JSON string of a dict)
+        -> just parse it as JSON, no transcription needed
+    """
+    if is_audio_input(raw_input):
+        compare_midi_input, predicted_notes, runtime_seconds = transcription_pipeline(
+            raw_input, BASIC_PITCH_MODEL
+        )
+        return compare_midi_input
+
+    return parse_json_input(raw_input)
+
+
 def evaluation_function(
     response: Any,
     answer: Any,
@@ -61,8 +89,8 @@ def evaluation_function(
 
     # The Lambda Feedback app sends response/answer as JSON strings,
     # convert them into Python object first
-    response = parse_json_input(response)
-    answer = parse_json_input(answer)
+    response = prepare_input(response)
+    answer = prepare_input(answer)
 
     result = compare_performance_ED(
         response,

From 4f1f2ac271903f4f19bd59b7a0ad30d84796e9d3 Mon Sep 17 00:00:00 2001
From: ada-3e212e610b <z2720629308@gmail.com>
Date: Wed, 19 Aug 2026 23:55:32 -0400
Subject: [PATCH 14/25] fix typo in feedback messages

---
 evaluation_function/compare_MIDI.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/evaluation_function/compare_MIDI.py b/evaluation_function/compare_MIDI.py
index 4c80bf1..41d5471 100644
--- a/evaluation_function/compare_MIDI.py
+++ b/evaluation_function/compare_MIDI.py
@@ -346,7 +346,7 @@ def event_alignment_ED(response_events, ref_events, gap_penalty=DEFAULT_GAP_PENA
         gap_penalty: cost of leaving an event unaligned (insertion/deletion)
 
     Returns:
-        operations: list of operation dicts, same format as event_alignment_ED()
+        operations: list of operation dicts
         D: accumulated cost matrix, shape (N+1, M+1)
     """
     # if a raw note dict with "pitch"/"start"/"duration" but no "event_type" is
@@ -1184,7 +1184,7 @@ def polished_feedback_message(event_details, response_events, ref_events, stats,
                             "Simultaneous notes are often hard to play correctly at the beginning. " \
                             "Pay attention to the fingering and hand position when playing these chords. " \
                             "You may find it helpful to practice each chord separately first and make sure " \
-                            "all required notes sound together. Then you can reconnect the chords to" \
+                            "all required notes sound together. Then you can reconnect the chords to " \
                             "their surronding sections and practice at a slower tempo carefully. "
                         )
         elif median_chord_accuracy >= 0.90:

From fbfc4902f7c57095c7aa1ffa67d8ee43f47281fa Mon Sep 17 00:00:00 2001
From: ada-3e212e610b <z2720629308@gmail.com>
Date: Fri, 21 Aug 2026 21:18:14 +0100
Subject: [PATCH 15/25] add comments

---
 evaluation_function/audio_processing.py | 23 +++++++++++++++++------
 1 file changed, 17 insertions(+), 6 deletions(-)

diff --git a/evaluation_function/audio_processing.py b/evaluation_function/audio_processing.py
index 4447f12..dc32ce5 100644
--- a/evaluation_function/audio_processing.py
+++ b/evaluation_function/audio_processing.py
@@ -77,7 +77,7 @@ def is_audio_input(response):
 # ------------------------------------------------------------------------------
 def load_basic_pitch_model(model_path=ICASSP_2022_MODEL_PATH):
     """
-    Load the Basic Pitch model once.
+    Load the pretrained Basic Pitch model once.
     """
     return Model(model_path)
 
@@ -162,25 +162,33 @@ def remove_leading_extra_notes(notes,
       - at least min_following_notes remain after the gap;
       - the possible performance start is within max_search_seconds.
     """
+    # if there are no notes, return an empty list
     if len(notes) == 0:
         return []
 
+    # sort the notes by onset time
     sorted_notes = sorted(notes, key=lambda note: note["onset"])
     start_index = 0
 
+    # find the first index where the gap to the next note is large enough
     for i in range(len(sorted_notes) - 1):
         current_onset = sorted_notes[i]["onset"]
         next_onset = sorted_notes[i + 1]["onset"]
         gap = next_onset - current_onset
 
-        leading_note_count = i + 1
-        following_note_count = len(sorted_notes) - leading_note_count
+        leading_note_count = i + 1 # number of notes before the gap
+        following_note_count = len(sorted_notes) - leading_note_count # number of notes after the gap
 
+        # check if the gap is large enough
         is_large_gap = gap >= min_gap_seconds
+        # ensure no. of leading notes does not exceed the maximum allowed
         has_few_leading_notes = leading_note_count <= max_leading_notes
+        # ensure no. of following notes meets the minimum required
         has_enough_following_notes = following_note_count >= min_following_notes
+        # search the first few seconds only, to avoid removing valid early notes in long performances
         is_near_beginning = next_onset <= max_search_seconds
 
+        # if all conditions are met, move on to the next note
         if (
             is_large_gap
             and has_few_leading_notes
@@ -189,9 +197,9 @@ def remove_leading_extra_notes(notes,
         ):
             start_index = i + 1
 
-    processed_notes = []
+    processed_notes = [] # create a new list to hold the processed notes i.e. notes to be kept
 
-    for note in sorted_notes[start_index:]:
+    for note in sorted_notes[start_index:]: # iterate over the notes starting from the determined start index
         processed_notes.append(note.copy())
 
     return processed_notes
@@ -218,7 +226,7 @@ def merge_same_pitch_notes(notes,
     notes_by_pitch = {}
     for note in notes:
         pitch = note["pitch"]
-        # initialize the list for this pitch if it doesn't exist
+        # create a new list for this pitch if it doesn't exist in the dictionary yet
         if pitch not in notes_by_pitch: 
             notes_by_pitch[pitch] = []
         # append a copy of the note to avoid modifying the original
@@ -226,6 +234,7 @@ def merge_same_pitch_notes(notes,
 
     merged_notes = []
     for pitch_notes in notes_by_pitch.values():
+        # sort the notes by onset time to ensure they are processed in order
         pitch_notes = sorted(pitch_notes, key=lambda note: note["onset"])
         current_note = pitch_notes[0].copy()
 
@@ -243,9 +252,11 @@ def merge_same_pitch_notes(notes,
             should_merge = is_close_in_time and looks_like_fragment
 
             if should_merge:
+                # Merge the two notes by updating the offset and duration of the current note
                 new_offset = max(current_note["offset"], next_note["offset"])
                 current_note["offset"] = new_offset
                 current_note["duration"] = new_offset - current_note["onset"]
+                # If both notes have a velocity, take the maximum to represent the merged note
                 if ("velocity" in current_note) and ("velocity" in next_note):
                     current_note["velocity"] = max(current_note["velocity"], next_note["velocity"])
             else:

From af880b9425c54f6bea4940e4bb899a339ef92f3b Mon Sep 17 00:00:00 2001
From: ada-3e212e610b <z2720629308@gmail.com>
Date: Fri, 21 Aug 2026 23:01:27 +0100
Subject: [PATCH 16/25] fix typo in feedback message

---
 evaluation_function/compare_MIDI.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/evaluation_function/compare_MIDI.py b/evaluation_function/compare_MIDI.py
index 41d5471..3334ce1 100644
--- a/evaluation_function/compare_MIDI.py
+++ b/evaluation_function/compare_MIDI.py
@@ -1185,7 +1185,7 @@ def polished_feedback_message(event_details, response_events, ref_events, stats,
                             "Pay attention to the fingering and hand position when playing these chords. " \
                             "You may find it helpful to practice each chord separately first and make sure " \
                             "all required notes sound together. Then you can reconnect the chords to " \
-                            "their surronding sections and practice at a slower tempo carefully. "
+                            "their surrounding sections and practice at a slower tempo carefully. "
                         )
         elif median_chord_accuracy >= 0.90:
             current_performance_messages.append(

From 8cf3c75a15701889b7f6c49c0ef21e72af195382 Mon Sep 17 00:00:00 2001
From: ada-3e212e610b <z2720629308@gmail.com>
Date: Sun, 23 Aug 2026 00:31:26 +0100
Subject: [PATCH 17/25] update results on test set

---
 notebooks/Phase2_summary.ipynb | 86 ++++++++++++++++++++++------------
 1 file changed, 55 insertions(+), 31 deletions(-)

diff --git a/notebooks/Phase2_summary.ipynb b/notebooks/Phase2_summary.ipynb
index 16c4136..be7bbe7 100644
--- a/notebooks/Phase2_summary.ipynb
+++ b/notebooks/Phase2_summary.ipynb
@@ -7,14 +7,14 @@
    "source": [
     "## Phase 2: Audio to MIDI transcription\n",
     "\n",
-    "Aim: Design a polyphonic, single-instrument, note-level AMT pipeline for converting audio recording into the MIDI dict format which can be passed into compare_performance_ED() in compare_MIDI.py.\n",
-    "\n",
-    "General sturcture of AMT pipeline:\n",
+    "General sturcture of typical AMT pipeline:\n",
     "- Step 1: read in the audio file\n",
     "- Step 2: preprocessing, prepare audio for the model, e.g. Time-frequency representation (Spectrogram), Pitch/Note/Onset estimation \n",
-    "- Step 3: AMT model (CNN/LSTM/Transformer)\n",
+    "- Step 3: AMT model, e.g. CNN, LSTM, Transformer\n",
     "- Step 4: postprocessing, convert the model output format \n",
     "\n",
+    "Aim: Design a polyphonic, single-instrument, note-level AMT pipeline for converting audio recording into the MIDI dict format which can be passed into compare_performance_ED() in compare_MIDI.py.\n",
+    "\n",
     "This notebook records the complete Phase 2 workflow: applying Basic Pitch to PianoVAM, calibrating its decoder, analysing transcription errors, designing targeted post-processing, and integrating audio input with the existing feedback pipeline."
    ]
   },
@@ -48,8 +48,6 @@
     }
    ],
    "source": [
-    "from pathlib import Path\n",
-    "\n",
     "import pandas as pd\n",
     "from sklearn.model_selection import ParameterSampler\n",
     "\n",
@@ -282,7 +280,7 @@
    ],
    "source": [
     "# The dataset has proper official `train`, `valid`, `test`, \n",
-    "# `ext-train`, and `special-purpose` splits. \n",
+    "# The `ext-train`, and `special-purpose` splits are not used in this notebook. \n",
     "train_samples = metadata_df[\n",
     "    (metadata_df[\"split\"] == \"train\")\n",
     "    & (metadata_df[\"performance_method\"] == \"Solo\")\n",
@@ -383,10 +381,11 @@
    "id": "8ce14db6",
    "metadata": {},
    "source": [
-    "Followed Rachel, 2022, using `mir_eval` to compute the following metrics: \n",
+    "Using `mir_eval` to compute the following metrics: \n",
+    "- precision\n",
+    "- recall\n",
     "- note-level F-measure (F): notes are considered correct if the pitch is within a quarter tone, the onset is within 50 ms, and the offset is within 20% of the note’s duration\n",
     "- the note-level F-measure-no-offset (Fno): same criterion as F-measure, but ignoring offsets \n",
-    "- frame-level note accuracy (Acc): computed for frames with a hop size of 10 ms. \n",
     "- overlap ratio (OR): given a reference and corresponding estimated note, their OR is defined as the ratio between the duration of the time segment in which the two notes overlap and the time segment spanned by the two notes combined\n",
     "\n",
     "The main measure of overall note estimation accuracy is the note F1 without offset (`note_f1_no_offset`) since the definition of offsets is less objective than onsets due to  pedal usage and reverberation. Also, as the TSV annotations additionally provide the frame offset information, which represents the end of the audible note (a note will still be hearable after note-off action if sustain pedal is used), the duration in the ground truth will be calculated using this frame-offset info instead of note-off info.\n",
@@ -2255,7 +2254,7 @@
    "source": [
     "# Case study: the lowest-F1 and highest-F1 samples \n",
     "lowest_f1_sample_id = \"19\"\n",
-    "highest_f1_sample_id = \"32\"\n"
+    "highest_f1_sample_id = \"32\""
    ]
   },
   {
@@ -2448,7 +2447,7 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "Random search: 100%|██████████| 53/53 [1:00:57<00:00, 69.01s/it] \n"
+      "Random search: 0it [00:00, ?it/s]\n"
      ]
     },
     {
@@ -3172,7 +3171,7 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "Evaluating configuration: 100%|██████████| 53/53 [11:50<00:00, 13.41s/it]\n"
+      "Evaluating configuration: 100%|██████████| 53/53 [14:42<00:00, 16.66s/it]\n"
      ]
     },
     {
@@ -3724,7 +3723,7 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "FP/FN summary: 100%|██████████| 53/53 [02:53<00:00,  3.28s/it]\n"
+      "FP/FN summary: 100%|██████████| 53/53 [02:41<00:00,  3.05s/it]\n"
      ]
     },
     {
@@ -5531,7 +5530,7 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "Post-processing evaluation: 100%|██████████| 53/53 [08:16<00:00,  9.36s/it]\n"
+      "Post-processing evaluation: 100%|██████████| 53/53 [08:13<00:00,  9.31s/it]\n"
      ]
     },
     {
@@ -5705,8 +5704,8 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "Evaluating configuration: 100%|██████████| 9/9 [01:04<00:00,  7.12s/it]\n",
-      "Post-processing evaluation: 100%|██████████| 9/9 [00:39<00:00,  4.38s/it]\n"
+      "Evaluating configuration: 100%|██████████| 9/9 [01:04<00:00,  7.13s/it]\n",
+      "Post-processing evaluation: 100%|██████████| 9/9 [00:40<00:00,  4.48s/it]\n"
      ]
     },
     {
@@ -5746,6 +5745,20 @@
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>0</th>\n",
+       "      <td>Default Basic Pitch</td>\n",
+       "      <td>0.699004</td>\n",
+       "      <td>0.661520</td>\n",
+       "      <td>0.775779</td>\n",
+       "      <td>0.751523</td>\n",
+       "      <td>0.725641</td>\n",
+       "      <td>0.740562</td>\n",
+       "      <td>0.238708</td>\n",
+       "      <td>4793.222222</td>\n",
+       "      <td>229.222222</td>\n",
+       "      <td>158.888889</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
        "      <td>Tuned Basic Pitch</td>\n",
        "      <td>0.813910</td>\n",
        "      <td>0.823995</td>\n",
@@ -5759,7 +5772,7 @@
        "      <td>156.444444</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1</th>\n",
+       "      <th>2</th>\n",
        "      <td>Tuned + targeted post-processing</td>\n",
        "      <td>0.816607</td>\n",
        "      <td>0.824828</td>\n",
@@ -5778,24 +5791,29 @@
       ],
       "text/plain": [
        "                      configuration  mean_note_precision_no_offset  \\\n",
-       "0                 Tuned Basic Pitch                       0.813910   \n",
-       "1  Tuned + targeted post-processing                       0.816607   \n",
+       "0               Default Basic Pitch                       0.699004   \n",
+       "1                 Tuned Basic Pitch                       0.813910   \n",
+       "2  Tuned + targeted post-processing                       0.816607   \n",
        "\n",
        "   median_note_precision_no_offset  mean_note_recall_no_offset  \\\n",
-       "0                         0.823995                    0.832767   \n",
-       "1                         0.824828                    0.829040   \n",
+       "0                         0.661520                    0.775779   \n",
+       "1                         0.823995                    0.832767   \n",
+       "2                         0.824828                    0.829040   \n",
        "\n",
        "   median_note_recall_no_offset  mean_note_f1_no_offset  \\\n",
-       "0                      0.886282                0.817995   \n",
-       "1                      0.871698                0.817358   \n",
+       "0                      0.751523                0.725641   \n",
+       "1                      0.886282                0.817995   \n",
+       "2                      0.871698                0.817358   \n",
        "\n",
        "   median_note_f1_no_offset  mean_note_f1_with_offset  mean_predicted_notes  \\\n",
-       "0                  0.815534                  0.274124           4581.555556   \n",
-       "1                  0.815204                  0.271278           4546.555556   \n",
+       "0                  0.740562                  0.238708           4793.222222   \n",
+       "1                  0.815534                  0.274124           4581.555556   \n",
+       "2                  0.815204                  0.271278           4546.555556   \n",
        "\n",
        "   mean_extra_notes  mean_missing_notes  \n",
-       "0         29.444444          156.444444  \n",
-       "1         28.111111          171.333333  "
+       "0        229.222222          158.888889  \n",
+       "1         29.444444          156.444444  \n",
+       "2         28.111111          171.333333  "
       ]
      },
      "execution_count": 20,
@@ -5805,6 +5823,14 @@
    ],
    "source": [
     "# Run this after the decoder configuration and post-processing rules are fixed.\n",
+    "test_baseline_df = evaluate_on_pianovam(\n",
+    "    \"test\", metadata_df,\n",
+    "    AUDIO_DIR, \n",
+    "    MIDI_DIR, \n",
+    "    TSV_DIR, \n",
+    "    RAW_PREDICTIONS_DIR,\n",
+    "    basic_pitch_model,\n",
+    ")\n",
     "\n",
     "test_tuned_df, test_tuned_predictions = evaluate_new_configuration_on_pianovam(\n",
     "    TUNED_CONFIG,\n",
@@ -5825,11 +5851,9 @@
     ")\n",
     "\n",
     "test_comparison = pd.DataFrame([\n",
+    "    comparison_row(\"Default Basic Pitch\", test_baseline_df),          \n",
     "    comparison_row(\"Tuned Basic Pitch\", test_tuned_df),\n",
-    "    comparison_row(\n",
-    "        \"Tuned + targeted post-processing\",\n",
-    "        test_postprocessed_df,\n",
-    "    ),\n",
+    "    comparison_row(\"Tuned + targeted post-processing\", test_postprocessed_df),\n",
     "])\n",
     "\n",
     "test_comparison"

From e3cf09f5fd66c749e63125b6818f7926bbe4a453 Mon Sep 17 00:00:00 2001
From: ada-3e212e610b <z2720629308@gmail.com>
Date: Sun, 23 Aug 2026 20:26:30 +0100
Subject: [PATCH 18/25] fix typo

---
 evaluation_function/audio_processing.py | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/evaluation_function/audio_processing.py b/evaluation_function/audio_processing.py
index dc32ce5..9af4d13 100644
--- a/evaluation_function/audio_processing.py
+++ b/evaluation_function/audio_processing.py
@@ -26,9 +26,9 @@
 # Parameters
 # ------------------------------------------------------------------------------
 # configuration values for the Basic Pitch model (decoder)
-ONSET_THRESHOLD = 0.7 # Minimum amplitude of an onset activation to be considered an onset
-FRAME_THRESHOLD = 0.2 # Minimum amplitude of a frame activation for a note to remain 'on'
-MINIMUM_NOTE_LENGTH = 75.0 # The minimum allowed note length in frames
+ONSET_THRESHOLD = 0.6 # Minimum amplitude of an onset activation to be considered an onset
+FRAME_THRESHOLD = 0.3 # Minimum amplitude of a frame activation for a note to remain 'on'
+MINIMUM_NOTE_LENGTH = 50.0 # The minimum allowed note length in frames
 MELODIA_TRICK = False # Whether to use the "Melodia trick" to improve pitch estimation for monophonic instruments
 # configuration values for the post-processing layer
 MIN_GAP_SECONDS = 0.5

From 0937a472c022a3ce1a82c53c382374d994ef96cc Mon Sep 17 00:00:00 2001
From: ada-3e212e610b <z2720629308@gmail.com>
Date: Sun, 23 Aug 2026 20:26:40 +0100
Subject: [PATCH 19/25] update result

---
 notebooks/Phase2_summary.ipynb | 12 ++++++------
 1 file changed, 6 insertions(+), 6 deletions(-)

diff --git a/notebooks/Phase2_summary.ipynb b/notebooks/Phase2_summary.ipynb
index be7bbe7..681c617 100644
--- a/notebooks/Phase2_summary.ipynb
+++ b/notebooks/Phase2_summary.ipynb
@@ -2447,7 +2447,7 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "Random search: 0it [00:00, ?it/s]\n"
+      "Random search: 100%|██████████| 53/53 [1:49:48<00:00, 124.31s/it]  \n"
      ]
     },
     {
@@ -3171,7 +3171,7 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "Evaluating configuration: 100%|██████████| 53/53 [14:42<00:00, 16.66s/it]\n"
+      "Evaluating configuration: 100%|██████████| 53/53 [11:41<00:00, 13.23s/it]\n"
      ]
     },
     {
@@ -3723,7 +3723,7 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "FP/FN summary: 100%|██████████| 53/53 [02:41<00:00,  3.05s/it]\n"
+      "FP/FN summary: 100%|██████████| 53/53 [02:41<00:00,  3.04s/it]\n"
      ]
     },
     {
@@ -5530,7 +5530,7 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "Post-processing evaluation: 100%|██████████| 53/53 [08:13<00:00,  9.31s/it]\n"
+      "Post-processing evaluation: 100%|██████████| 53/53 [08:14<00:00,  9.34s/it]\n"
      ]
     },
     {
@@ -5704,8 +5704,8 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "Evaluating configuration: 100%|██████████| 9/9 [01:04<00:00,  7.13s/it]\n",
-      "Post-processing evaluation: 100%|██████████| 9/9 [00:40<00:00,  4.48s/it]\n"
+      "Evaluating configuration: 100%|██████████| 9/9 [01:07<00:00,  7.47s/it]\n",
+      "Post-processing evaluation: 100%|██████████| 9/9 [00:38<00:00,  4.33s/it]\n"
      ]
     },
     {

From a2f59c57d219dee0f7d6ca65ca3bd075c506cf98 Mon Sep 17 00:00:00 2001
From: ada-3e212e610b <z2720629308@gmail.com>
Date: Mon, 24 Aug 2026 21:24:41 +0100
Subject: [PATCH 20/25] add some comments and fix some typo

---
 evaluation_function/audio_processing.py | 27 +++++-----
 evaluation_function/compare_MIDI.py     | 70 +++++++++++++------------
 2 files changed, 49 insertions(+), 48 deletions(-)

diff --git a/evaluation_function/audio_processing.py b/evaluation_function/audio_processing.py
index 9af4d13..2efeaac 100644
--- a/evaluation_function/audio_processing.py
+++ b/evaluation_function/audio_processing.py
@@ -6,11 +6,9 @@
 compare_performance_ED.
 
 Pipeline overview:
-    1. loading the Basic Pitch model
-    2. running the model on one audio file (or re-decoding already
-     computed raw model output) into a list of note dictionaries
-    3. post-processing 
-    4. converting notes into the format compare_performance_ED expects
+    1. run Basic Pitch
+    2. optionally apply targeted post-processing steps
+    3. return notes ready to hand to compare_MIDI.py
 """
 
 
@@ -30,6 +28,7 @@
 FRAME_THRESHOLD = 0.3 # Minimum amplitude of a frame activation for a note to remain 'on'
 MINIMUM_NOTE_LENGTH = 50.0 # The minimum allowed note length in frames
 MELODIA_TRICK = False # Whether to use the "Melodia trick" to improve pitch estimation for monophonic instruments
+
 # configuration values for the post-processing layer
 MIN_GAP_SECONDS = 0.5
 MAX_LEADING_NOTES = 3
@@ -46,7 +45,7 @@
 
 
 # Helper function to check if the response is audio
-# ------------------------------------------------------------------------------
+# ---------------------------------------------------------------------
 def is_audio_input(response):
     """
     Return True if response looks like an audio file that needs to go
@@ -74,7 +73,7 @@ def is_audio_input(response):
 
 
 # Load the model
-# ------------------------------------------------------------------------------
+# ---------------------------------------------------------------------
 def load_basic_pitch_model(model_path=ICASSP_2022_MODEL_PATH):
     """
     Load the pretrained Basic Pitch model once.
@@ -181,9 +180,9 @@ def remove_leading_extra_notes(notes,
 
         # check if the gap is large enough
         is_large_gap = gap >= min_gap_seconds
-        # ensure no. of leading notes does not exceed the maximum allowed
+        # ensure number of leading notes does not exceed the maximum allowed
         has_few_leading_notes = leading_note_count <= max_leading_notes
-        # ensure no. of following notes meets the minimum required
+        # ensure number of following notes meets the minimum required
         has_enough_following_notes = following_note_count >= min_following_notes
         # search the first few seconds only, to avoid removing valid early notes in long performances
         is_near_beginning = next_onset <= max_search_seconds
@@ -198,8 +197,8 @@ def remove_leading_extra_notes(notes,
             start_index = i + 1
 
     processed_notes = [] # create a new list to hold the processed notes i.e. notes to be kept
-
-    for note in sorted_notes[start_index:]: # iterate over the notes starting from the determined start index
+    # iterate over the notes starting from the determined start index
+    for note in sorted_notes[start_index:]: 
         processed_notes.append(note.copy())
 
     return processed_notes
@@ -244,7 +243,7 @@ def merge_same_pitch_notes(notes,
             next_duration = next_note["offset"] - next_note["onset"]
             # Check if the gap is within the allowed range
             is_close_in_time = (-max_gap_seconds <= gap <= max_gap_seconds)
-            # Check if at least one of the notes is short enough to be considered a fragment
+            # Check if both notes are short enough to be considered a fragment
             looks_like_fragment = (
                 current_duration <= max_fragment_duration
                 and next_duration <= max_fragment_duration
@@ -307,8 +306,8 @@ def build_compare_midi_input(notes, duration_key="duration"):
 # ---------------------------------------------------------------------
 def transcription_pipeline(audio_path, model, apply_postprocessing=True):
     """
-    Full production pipeline: run Basic Pitch, optionally apply Layer 2
-    post-processing, and return notes ready to hand to compare_MIDI.py.
+    Full production pipeline: run Basic Pitch, optionally apply post-processing, 
+    and return notes ready to hand to compare_MIDI.py.
 
     Returns (compare_midi_input, predicted_notes, runtime_seconds).
     """
diff --git a/evaluation_function/compare_MIDI.py b/evaluation_function/compare_MIDI.py
index 3334ce1..8d72cc4 100644
--- a/evaluation_function/compare_MIDI.py
+++ b/evaluation_function/compare_MIDI.py
@@ -11,9 +11,8 @@
               estimate_global_duration_scale
     Step 3 -- event_level_feedback      (note/chord-level feedback)
     Step 4 -- compute_stats             (summary counts)
-    Step 5 -- generate_feedback_message (human-readable text)
-              polished_feedback_message (polished version of human-readable text)
-    Step 6 -- is_correct                (overall pass/fail judgement)
+    Step 5 -- version 1: generate_feedback_message (human-readable text)
+              version 2: polished_feedback_message (polished version of human-readable text)
 """
 
 
@@ -23,7 +22,7 @@
 # Default thresholds / parameters
 # Teachers can override any of these via the params dict in evaluation_function.
 # ------------------------------------------------------------------------------
-# Gap penalty: cost of leaving a note unaligned (insertion/deletion)
+# Gap penalty: cost of leaving an event unaligned (insertion/deletion)
 DEFAULT_GAP_PENALTY = 6
 
 # Timing: |response_start - predicted_start| / Inter-Onset Interval (IOI) must be below this.
@@ -86,11 +85,12 @@ def identify_chord_name(notes):
     pitch_classes = get_pitch_class_set(notes)
  
     for root_pc in pitch_classes:
+        # Normalise the pitch classes relative to the root note, so that the root is 0.
         normalised = set((pc - root_pc) % 12 for pc in pitch_classes)
         for chord_type, template in CHORD_TEMPLATES.items():
             if normalised == template:
-                root_name = PITCH_CLASS_NAMES[root_pc]
-                return root_name + " " + chord_type
+                root_name = PITCH_CLASS_NAMES[root_pc] # convert root pitch class to name
+                return root_name + " " + chord_type # return e.g. "C major"
  
     return "unknown chord"
  
@@ -98,7 +98,7 @@ def compute_chord_accuracy(ref_notes, res_notes):
     """
     Compute the chord accuracy score A (modified Devaney's method), but
     use the actual MIDI pitch (with octave) instead of pitch class, 
-    so that the score is sensitive to octave errors.: 
+    so that the score is sensitive to octave errors:
     A = (C - I + |y|) / (2 * |y|)
     where:
         C = number of correctly matched notes
@@ -117,8 +117,8 @@ def compute_chord_accuracy(ref_notes, res_notes):
         missing_pitches: sorted list of missing MIDI pitches
         extra_pitches: sorted list of extra MIDI pitches
     """
-    ref_counts = Counter(note["pitch"] for note in ref_notes)
-    res_counts = Counter(note["pitch"] for note in res_notes)
+    ref_counts = Counter(note["pitch"] for note in ref_notes) # count each pitch in the reference chord
+    res_counts = Counter(note["pitch"] for note in res_notes) # count each pitch in the response chord
 
     correct_pitches = []
     missing_pitches = []
@@ -126,28 +126,28 @@ def compute_chord_accuracy(ref_notes, res_notes):
 
     # For every distinct pitch on either side, match up copies one-to-one.
     # Any leftover ref copies are missing; any leftover res copies are extra.
-    all_pitches = sorted(set(ref_counts) | set(res_counts))
+    all_pitches = sorted(set(ref_counts) | set(res_counts)) # union of all distinct pitches in both chords
     for pitch in all_pitches:
-        matched = min(ref_counts[pitch], res_counts[pitch])
-        correct_pitches.extend([pitch] * matched)
-        if ref_counts[pitch] > matched:
+        matched = min(ref_counts[pitch], res_counts[pitch]) # number of copies that can be matched
+        correct_pitches.extend([pitch] * matched) 
+        if ref_counts[pitch] > matched: # if there are more copies in the reference than matched, they are missing
             missing_pitches.extend(
                 [pitch] * (ref_counts[pitch] - matched)
             )
-        if res_counts[pitch] > matched:
+        if res_counts[pitch] > matched: # if there are more copies in the response than matched, they are extra
             extra_pitches.extend(
                 [pitch] * (res_counts[pitch] - matched)
             )
 
-    C = len(correct_pitches)
-    I = len(extra_pitches)
-    ref_size = len(ref_notes)   # total note count, repeats included
+    C = len(correct_pitches) # number of correctly matched notes
+    I = len(extra_pitches) # number of extra notes played
+    ref_size = len(ref_notes) # total note count, repeats included
 
     if ref_size == 0:
         accuracy = 0.0
     else:
-        accuracy = (C - I + ref_size) / (2.0 * ref_size)
-        accuracy = max(0.0, min(1.0, accuracy))
+        accuracy = (C - I + ref_size) / (2.0 * ref_size) 
+        accuracy = max(0.0, min(1.0, accuracy)) # clamp to [0, 1] in case of negative values
 
     return accuracy, correct_pitches, missing_pitches, extra_pitches
 
@@ -267,8 +267,8 @@ def group_notes_into_events(notes, chord_onset_window=DEFAULT_CHORD_ONSET_WINDOW
 def build_cost_matrix(response_events, ref_events, gap_penalty=DEFAULT_GAP_PENALTY):
     """
     Precompute the full (N x M) event-alignment cost matrix using vectorised
-    NumPy broadcasting, instead of compute event cost one at a
-    time inside a Python loop. This also removes the redundant cost
+    NumPy broadcasting, instead of computing event cost one at a
+    time inside a loop. This also removes the redundant cost
     computation that used to happen a second time during backtracking.
 
     Args:
@@ -288,6 +288,7 @@ def build_cost_matrix(response_events, ref_events, gap_penalty=DEFAULT_GAP_PENAL
     res_is_chord = np.array([event["event_type"] == "chord" for event in response_events])
     ref_is_chord = np.array([event["event_type"] == "chord" for event in ref_events])
 
+    # For note events, extract the pitch; for chords, use 0 as a placeholder.
     res_pitch = np.array([
         event["notes"][0]["pitch"] if event["event_type"] == "note" else 0
         for event in response_events
@@ -305,24 +306,24 @@ def build_cost_matrix(response_events, ref_events, gap_penalty=DEFAULT_GAP_PENAL
     # then compute Hamming distance for every pair using broadcasting.
     res_pitch_vector = np.zeros((N, 12), dtype=int)
     for i in range(N):
-        if res_is_chord[i]:
-            for note in response_events[i]["notes"]:
-                res_pitch_vector[i, note["pitch"] % 12] = 1
+        if res_is_chord[i]: # only fill in the pitch vector for chords
+            for note in response_events[i]["notes"]: # iterate over all notes in the chord
+                res_pitch_vector[i, note["pitch"] % 12] = 1 # set the corresponding pitch class to 1
 
     ref_pitch_vector = np.zeros((M, 12), dtype=int)
     for j in range(M):
         if ref_is_chord[j]:
             for note in ref_events[j]["notes"]:
-                ref_pitch_vector[j, note["pitch"] % 12] = 1
+                ref_pitch_vector[j, note["pitch"] % 12] = 1 
 
     # (N, 1, 12) vs (1, M, 12) broadcasts to (N, M, 12); summing the last
     # axis gives the Hamming distance for every (response, ref) pair at once.
-    differs = res_pitch_vector.reshape(N, 1, 12) != ref_pitch_vector.reshape(1, M, 12)
-    chord_cost_matrix = differs.sum(axis=2)
+    differs = (res_pitch_vector.reshape(N, 1, 12) != ref_pitch_vector.reshape(1, M, 12)) # shape (N, M, 12)
+    chord_cost_matrix = differs.sum(axis=2) # sum over the last axis to get the Hamming distance for each pair
 
     # Type-mismatch mask: True where one side is a note and the other a chord.
-    type_mismatch = res_is_chord.reshape(N, 1) != ref_is_chord.reshape(1, M)
-    both_chords = res_is_chord.reshape(N, 1) & ref_is_chord.reshape(1, M)
+    type_mismatch = (res_is_chord.reshape(N, 1) != ref_is_chord.reshape(1, M))
+    both_chords = (res_is_chord.reshape(N, 1) & ref_is_chord.reshape(1, M))
 
     # Combine the three cases -- np.where(condition, true, false)
     cost_matrix = np.where(
@@ -336,9 +337,9 @@ def build_cost_matrix(response_events, ref_events, gap_penalty=DEFAULT_GAP_PENAL
 
 def event_alignment_ED(response_events, ref_events, gap_penalty=DEFAULT_GAP_PENALTY):
     """
-    Same algorithm as the production event_alignment_ED(), but the N x M
-    substitution costs are looked up from a precomputed cost matrix instead
-    of being recomputed on every DP cell and again during backtracking.
+    Aligns response and reference events using edit distance. 
+    Costs are precomputed once via build_cost_matrix() for efficiency, 
+    rather than recomputed inside the loop and during backtracking
 
     Args:
         response_events: list of event dicts from group_notes_into_events
@@ -592,7 +593,7 @@ def event_level_feedback(operations, response_events, ref_events,
             "duration_abs_diff" -> float (seconds) or None
             "duration_relative_diff" -> float or None
     """
-    # Compute IOI for each reference note: ioi[m] = ref_notes[m]["start"] - ref_notes[m-1]["start"]
+    # Compute IOI for each reference note: ioi[m] = ref_events[m]["start"] - ref_events[m-1]["start"]
     # floor at 0.05s to avoid division by zero issues
     ref_ioi = [None] * len(ref_events)
     for m in range(1, len(ref_events)):
@@ -765,7 +766,8 @@ def compute_stats(event_level_results, ref_events, timing_scale=1.0,
     """
     note_events  = [n for n in event_level_results if n["event_type"] == "note"]
     chord_events = [ch for ch in event_level_results if ch["event_type"] == "chord"]
-    
+
+    # Count the total number of notes and chords in the reference events
     ref_note_count  = sum(1 for n in ref_events if n["event_type"] == "note")
     ref_chord_count = sum(1 for ch in ref_events if ch["event_type"] == "chord")
     

From 44ad4cc40844950e0443c6e55b4164f0e8d9408a Mon Sep 17 00:00:00 2001
From: ada-3e212e610b <z2720629308@gmail.com>
Date: Mon, 24 Aug 2026 21:27:34 +0100
Subject: [PATCH 21/25] regenerate the result

---
 notebooks/Demonstration.ipynb | 18 +++++++++---------
 1 file changed, 9 insertions(+), 9 deletions(-)

diff --git a/notebooks/Demonstration.ipynb b/notebooks/Demonstration.ipynb
index cb31634..fe19be8 100644
--- a/notebooks/Demonstration.ipynb
+++ b/notebooks/Demonstration.ipynb
@@ -140,9 +140,9 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Transcribed practice recording 01: 94 notes in 1.4s\n",
-      "Transcribed practice recording 02: 80 notes in 0.6s\n",
-      "Transcribed reference recording: 162 notes in 0.4s\n"
+      "Transcribed practice recording 01: 97 notes in 2.6s\n",
+      "Transcribed practice recording 02: 87 notes in 0.6s\n",
+      "Transcribed reference recording: 163 notes in 0.4s\n"
      ]
     }
    ],
@@ -195,7 +195,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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",
       "text/plain": [
        "<Figure size 1400x600 with 1 Axes>"
       ]
@@ -252,7 +252,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 1400x600 with 1 Axes>"
       ]
@@ -294,7 +294,7 @@
       "Practice Summary\n",
       "Note accuracy needs more practice. Practice each short passage at a slower tempo, check each note carefully, mind the fingering during practice. Then move on to the next passage when you feel confident with the current one.\n",
       "Timing consistency needs more practice. You can slow down in your next practice session and listen carefully for notes that arrive too early or too late. A metronome can help you play each note at the right time and hence make the rhythm more steady.\n",
-      "Simultaneous notes are often hard to play correctly at the beginning. Pay attention to the fingering and hand position when playing these chords. You may find it helpful to practice each chord separately first and make sure all required notes sound together. Then you can reconnect the chords totheir surronding sections and practice at a slower tempo carefully. \n",
+      "Simultaneous notes are often hard to play correctly at the beginning. Pay attention to the fingering and hand position when playing these chords. You may find it helpful to practice each chord separately first and make sure all required notes sound together. Then you can reconnect the chords to their surrounding sections and practice at a slower tempo carefully. \n",
       "\n",
       "Tempo\n",
       "Your overall tempo was slower than the reference. This is not necessarily a problem, and it is a good idea to play slowly while learning. Whatever tempo you choose, aim to keep the rhythm steady throughout the performance.\n",
@@ -322,7 +322,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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",
       "text/plain": [
        "<Figure size 1500x800 with 2 Axes>"
       ]
@@ -335,8 +335,8 @@
      "output_type": "stream",
      "text": [
       "Selected operations: 114\n",
-      "Note connectors: 94\n",
-      "Missing note markers: 29\n",
+      "Note connectors: 97\n",
+      "Missing note markers: 25\n",
       "Extra note markers: 0\n"
      ]
     }

From 5b2df4ec8d1b3b18448ea97c6395250db218e853 Mon Sep 17 00:00:00 2001
From: ada-3e212e610b <z2720629308@gmail.com>
Date: Mon, 24 Aug 2026 21:30:59 +0100
Subject: [PATCH 22/25] fix docstrings at the beginning

---
 evaluation_function/evaluation_test.py | 7 ++++---
 1 file changed, 4 insertions(+), 3 deletions(-)

diff --git a/evaluation_function/evaluation_test.py b/evaluation_function/evaluation_test.py
index ac23a8e..9aca78e 100755
--- a/evaluation_function/evaluation_test.py
+++ b/evaluation_function/evaluation_test.py
@@ -12,12 +12,13 @@
 1. Tests for helper functions get_pitch_class_set, identify_chord_name, compute_chord_accuracy
 2. Tests for normalize_start_times
 3. Tests for group_notes_into_events
-4. Tests for compute_note_cost and compute_event_cost
+4. Tests for build_cost_matrix
 5. Tests for event_alignment_ED  (covers note-only, chord-only cases and mixed cases)
 6. Tests for estimate_global_timing and estimate_global_duration_scale
-7. Tests for event_level_feedback and compute_stats  (covers note-only and chord-only cases)
+7. Tests for compare_performance_ED (full pipeline: alignment → event-level feedback → stats)
 8. Tests for evaluation_function (Lambda Feedback integration)
 9. Tests for parameter overrides
+10. Bulk tests using longer MIDI sequences
 """
 
 
@@ -458,7 +459,7 @@ def test_fewer_than_3_matched_returns_defaults(self):
         assert dur_scale == 1.0
 
 
-# 7. Tests for event_level_feedback and compute_stats
+# 7. Tests for compare_performance_ED (full pipeline: alignment → event-level feedback → stats)
 # ------------------------------------------------------------------------------
 class TestComparePerformanceED(unittest.TestCase):
  

From 1fd8eff4932dad33cc7b91d32c5a70d3f71617ab Mon Sep 17 00:00:00 2001
From: ada-3e212e610b <z2720629308@gmail.com>
Date: Tue, 25 Aug 2026 09:40:17 +0100
Subject: [PATCH 23/25] add comments and fix docstrings

---
 notebooks/utils/alignment_visualisation.py    |  20 ++-
 notebooks/utils/error_analysis.py             |  21 +++-
 notebooks/utils/nasap_alignment_evaluation.py | 119 ++++++++----------
 notebooks/utils/pianovam_loading.py           |   5 +-
 notebooks/utils/postprocessing_evaluation.py  |  26 ++--
 notebooks/utils/random_search.py              |  15 ++-
 notebooks/utils/transcription_evaluation.py   |  16 ++-
 7 files changed, 120 insertions(+), 102 deletions(-)

diff --git a/notebooks/utils/alignment_visualisation.py b/notebooks/utils/alignment_visualisation.py
index 3d43efd..d69b8e4 100644
--- a/notebooks/utils/alignment_visualisation.py
+++ b/notebooks/utils/alignment_visualisation.py
@@ -9,15 +9,15 @@
 def format_event_pitch(event):
     """
     Convert an event into a short pitch label for the alignment diagram.
-    A note event is shown as a single MIDI pitch, e.g.: 60
+    A note event is shown as a single MIDI pitch, e.g. 60
     A chord event is shown as a set of MIDI pitches, e.g.: {60, 64, 67}
     """
-    pitches = [note["pitch"] for note in event["notes"]]
+    pitches = [note["pitch"] for note in event["notes"]] # list of MIDI pitches in the event
 
     if len(pitches) == 1:
-        return str(pitches[0])
+        return str(pitches[0]) # single note
 
-    return "{" + ", ".join(str(pitch) for pitch in pitches) + "}"
+    return "{" + ", ".join(str(pitch) for pitch in pitches) + "}" # chord
 
 def plot_edit_distance_alignment(operations, D, response_events, ref_events):
     """
@@ -53,12 +53,12 @@ def plot_edit_distance_alignment(operations, D, response_events, ref_events):
 
     for operation in reversed(operations):
         operation_type = operation["type"]
-        if operation_type in ("match", "replacement"):
+        if operation_type in ("match", "replacement"): # both indices decrease
             n -= 1
             m -= 1
-        elif operation_type == "extra":
+        elif operation_type == "extra": # only the response index decreases
             n -= 1
-        elif operation_type == "missing":
+        elif operation_type == "missing": # only the reference index decreases
             m -= 1
         path_rows.append(n)
         path_cols.append(m)
@@ -136,7 +136,7 @@ def plot_edit_distance_alignment(operations, D, response_events, ref_events):
         pitch_label = format_event_pitch(event)
         ax.add_patch(
                     plt.Rectangle(
-                        (xpos - box_width / 2, reference_y),
+                        (xpos - box_width / 2, response_y),
                         box_width, box_height, fill=False,
                         edgecolor="black", linewidth=1.5)
                 )
@@ -187,6 +187,4 @@ def plot_edit_distance_alignment(operations, D, response_events, ref_events):
     ax.set_ylim(0, 4)
     ax.set_title("Alignment Diagram")
     plt.tight_layout()
-    plt.show()
-
-
+    plt.show()
\ No newline at end of file
diff --git a/notebooks/utils/error_analysis.py b/notebooks/utils/error_analysis.py
index 8ccff23..c6e848b 100644
--- a/notebooks/utils/error_analysis.py
+++ b/notebooks/utils/error_analysis.py
@@ -68,6 +68,7 @@ def get_note_match_info(sample_id, metadata_df, audio_dir, midi_dir,
         predicted_notes, offset_key="offset"
     )
 
+    # Use mir_eval to match predicted notes to reference notes, allowing a small onset tolerance.
     matching = mir_eval.transcription.match_notes(
         reference_intervals,
         reference_pitches,
@@ -77,6 +78,7 @@ def get_note_match_info(sample_id, metadata_df, audio_dir, midi_dir,
         offset_ratio=None,
     )
 
+    # The matching is a list of (reference_index, predicted_index) pairs.
     matched_reference_indices = set(pair[0] for pair in matching)
     matched_predicted_indices = set(pair[1] for pair in matching)
 
@@ -119,7 +121,9 @@ def summarise_fp_fn_over_train_set(train_samples, metadata_df, audio_dir,
         matched_reference_indices = match_info["matched_reference_indices"]
         matched_predicted_indices = match_info["matched_predicted_indices"]
 
+        # Sort predicted notes by onset time
         sorted_predicted_notes = sorted(predicted_notes, key=lambda note: note["onset"])
+        # Create a list of matched predicted notes for easier pattern analysis.
         matched_predicted_notes = [predicted_notes[i] for i in matched_predicted_indices]
 
         if len(reference_notes) > 0:
@@ -147,12 +151,16 @@ def summarise_fp_fn_over_train_set(train_samples, metadata_df, audio_dir,
                     same_pitch = (other_note["pitch"] == note["pitch"])
                     is_before = (other_note["offset"] <= note["onset"])
                     gap = note["onset"] - other_note["offset"]
+                    # Check if there is a nearby predicted note with the same pitch that ends 
+                    # before this note starts, and is within max_gap_seconds.
                     if same_pitch and is_before and (0 <= gap <= max_gap_seconds):
                         has_fragment_pattern = True
 
                 has_harmonic_interval_pattern = False
                 for matched_note in matched_predicted_notes:
                     pitch_gap = abs(note["pitch"] - matched_note["pitch"])
+                    # Check if the pitch gap is a common harmonic interval (perfect fifth, octave, 
+                    # or compound intervals) and if the notes overlap in time within the onset window.
                     if pitch_gap in interval_sizes and notes_overlap(note, matched_note, tolerance=onset_window_seconds):
                         has_harmonic_interval_pattern = True
 
@@ -166,12 +174,13 @@ def summarise_fp_fn_over_train_set(train_samples, metadata_df, audio_dir,
                     neither_pattern = neither_pattern + 1
 
                 duration = note["offset"] - note["onset"]
+                # Check if the extra note is short
                 if duration < short_note_seconds:
                     short_extra = short_extra + 1
-
+                # Check if the extra note starts before the first reference note.
                 if note["onset"] < first_reference_onset:
                     extra_at_beginning = extra_at_beginning + 1
-
+                # Check if there are multiple reference notes starting near this extra note's onset.
                 nearby_reference_count = count_nearby_reference_notes(
                     reference_notes, note["onset"], onset_window_seconds
                 )
@@ -190,11 +199,15 @@ def summarise_fp_fn_over_train_set(train_samples, metadata_df, audio_dir,
                 total_missing = total_missing + 1
 
                 duration = note["frame_offset"] - note["onset"]
+                # Check if the missing note is short.
                 if duration < short_note_seconds:
                     short_missing = short_missing + 1
 
                 has_nearby_same_pitch_reference = False
                 for other_index, other_note in enumerate(reference_notes):
+                    # Check if there is another reference note with the same pitch 
+                    # that starts within max_gap_seconds of this missing note's onset,
+                    # mark this missing note as having a repeated pitch nearby.
                     if other_index != reference_index:
                         same_pitch = other_note["pitch"] == note["pitch"]
                         onset_gap = abs(other_note["onset"] - note["onset"])
@@ -203,9 +216,13 @@ def summarise_fp_fn_over_train_set(train_samples, metadata_df, audio_dir,
                 if has_nearby_same_pitch_reference:
                     repeated_pitch_missing = repeated_pitch_missing + 1
 
+                # Check if there are multiple reference notes starting near this missing note's onset, 
+                # which may indicate it's part of a chord or dense region.
                 nearby_reference_count = count_nearby_reference_notes(
                     reference_notes, note["onset"], onset_window_seconds
                 )
+                # If there are two or more reference notes starting near this missing note's onset,
+                # mark it as chord-related missing.
                 if nearby_reference_count >= 2:
                     chord_related_missing = chord_related_missing + 1
 
diff --git a/notebooks/utils/nasap_alignment_evaluation.py b/notebooks/utils/nasap_alignment_evaluation.py
index 49ae501..f4ddccb 100644
--- a/notebooks/utils/nasap_alignment_evaluation.py
+++ b/notebooks/utils/nasap_alignment_evaluation.py
@@ -2,7 +2,7 @@
 nasap_alignment_evaluation.py
 =============================
 Helper functions for evaluating the Phase 1 event-level MIDI alignment
-pipeline on the CPJKU nASAP dataset.
+pipeline on the (n)ASAP dataset.
 """
 
 import csv
@@ -31,7 +31,7 @@
 
 def load_ground_truth(tsv_path):
     """
-    Read a note_alignment.tsv file from the CPJKU nASAP dataset.
+    Read a note_alignment.tsv file from the (n)ASAP dataset.
     Returns one dictionary per TSV row. XML and MIDI identifiers are retained
     so that individual alignment errors can be traced later.
         Keys:
@@ -184,7 +184,7 @@ def build_sample(xml_path, response_path, composer, title, metadata_row):
 def load_samples(asap_path, composer):
     """
     Read metadata.csv and return MusicXML-score / MIDI-performance samples
-    for one composer.
+    for specified composer.
     """
     metadata_path = os.path.join(asap_path, "metadata.csv")
     samples = []
@@ -193,13 +193,16 @@ def load_samples(asap_path, composer):
         reader = csv.DictReader(csv_file)
 
         for row in reader:
+            # Only load samples for the specified composer.
             if row.get("composer", "").strip() != composer:
                 continue
 
             xml_path = os.path.join(asap_path, row.get("xml_score", "").strip())
             response_path = os.path.join(asap_path, row.get("midi_performance", "").strip())
             tsv_path = os.path.join(asap_path, row.get("note_alignments", "").strip())
-            
+
+            # Only load samples that have all three required files: 
+            # MusicXML score, performance MIDI, and ground-truth TSV.
             if os.path.isfile(xml_path) and os.path.isfile(response_path) and os.path.isfile(tsv_path):
                 sample = build_sample(
                 xml_path,
@@ -285,12 +288,12 @@ def convert_pipeline_output(event_details, response_events, ref_events):
         response_event = None
         reference_event = None
 
+        # Find the corresponding response and reference events, if they exist.
         if event.get("response_index") is not None:
             response_index = event["response_index"] - 1
             if (response_index < 0) or (response_index >= len(response_events)):
                 raise IndexError("response_index is outside response_events")
             response_event = response_events[response_index]
-
         if event.get("reference_index") is not None:
             reference_index = event["reference_index"] - 1
             if (reference_index < 0) or (reference_index >= len(ref_events)):
@@ -408,6 +411,8 @@ def compute_metrics(ground_truth, predictions, onset_offset=0.0):
     gt_insertions = {}
     predicted_insertions = {}
 
+    # Group insertions by pitch so onset-matching only happens within the same pitch
+    # (count_onset_matches only compares onset times, not pitch).
     for row in ground_truth:
         if (
             row["label"] == "insertion"
@@ -418,7 +423,6 @@ def compute_metrics(ground_truth, predictions, onset_offset=0.0):
             if pitch not in gt_insertions:
                 gt_insertions[pitch] = []
             gt_insertions[pitch].append(float(row["onset"]))
-
     for row in predictions:
         if (
             row["label"] == "insertion"
@@ -431,7 +435,8 @@ def compute_metrics(ground_truth, predictions, onset_offset=0.0):
             predicted_insertions[pitch].append(
                 float(row["onset"]) + onset_offset
             )
-
+    # Match onsets separately within each pitch, so an insertion can only be
+    # matched against a ground-truth insertion of the same pitch.
     for pitch in set(gt_insertions) | set(predicted_insertions):
         gt_onsets = gt_insertions.get(pitch, [])
         predicted_onsets = predicted_insertions.get(pitch, [])
@@ -482,6 +487,7 @@ def compute_metrics(ground_truth, predictions, onset_offset=0.0):
 
 
 def get_note_centre(note):
+    """Find the centre of a note for plotting a connector line."""
     return (
         note["start"] + note["duration"] / 2,
         note["pitch"],
@@ -489,6 +495,7 @@ def get_note_centre(note):
 
 
 def event_overlaps_range(event, start, end):
+    """Check if any note in an event overlaps a given time range."""
     for note in event["notes"]:
         note_start = note["start"]
         note_end = note["start"] + note["duration"]
@@ -525,7 +532,7 @@ def pair_event_notes(ref_event, response_event):
     # First pair notes with identical pitches.
     for response_index, response_note in enumerate(response_notes):
         matching_ref_index = None
-
+        # Search for a matching reference note with the same pitch that hasn't been used yet.
         for ref_index, ref_note in enumerate(ref_notes):
             ref_is_available = ref_index not in used_ref_indices
             pitches_match = ref_note["pitch"] == response_note["pitch"]
@@ -575,31 +582,29 @@ def pair_event_notes(ref_event, response_event):
 
 
 def plot_alignment(ref_events, response_events, event_details, ref_start, ref_end):
+    """Plot a piano-roll visualisation of the event-level alignment."""
     reference_positions = []
-
+    # Find the first and last positions in event_details that contain reference events
     for position, detail in enumerate(event_details):
         reference_index = detail.get("reference_index")
-
         if reference_index is not None:
             ref_event = ref_events[reference_index - 1]
-
             if event_overlaps_range(
                 ref_event,
                 ref_start,
                 ref_end,
             ):
                 reference_positions.append(position)
-
     if not reference_positions:
         raise ValueError(
             "No reference events were found in this range."
         )
-
     first_position = min(reference_positions)
     last_position = max(reference_positions)
 
+    # Select all event_details between the first and last positions, 
+    # including any extra events that may not have a reference event.
     selected_details = []
-
     for position in range(first_position, last_position + 1):
         detail = event_details[position]
         operation = detail["operation_type"]
@@ -616,9 +621,10 @@ def plot_alignment(ref_events, response_events, event_details, ref_start, ref_en
         if include_detail:
             selected_details.append(detail)
 
+    # Find the earliest start and latest end times of the response events that 
+    # correspond to the selected details.
     response_starts = []
     response_ends = []
-
     for detail in selected_details:
         response_index = detail.get("response_index")
 
@@ -636,6 +642,8 @@ def plot_alignment(ref_events, response_events, event_details, ref_start, ref_en
         response_start = ref_start
         response_end = ref_end
 
+    # Filter the response and reference events to only include 
+    # those that overlap the specified time ranges.
     visible_response_events = []
     for event in response_events:
         if event_overlaps_range(event, response_start, response_end):
@@ -771,7 +779,7 @@ def plot_alignment(ref_events, response_events, event_details, ref_start, ref_en
 
     for detail in selected_details:
         operation = detail["operation_type"]
-
+        # Draw missing note markers.
         if operation == "missing":
             reference_index = detail.get("reference_index")
 
@@ -793,7 +801,7 @@ def plot_alignment(ref_events, response_events, event_details, ref_start, ref_en
                         )
 
                         missing_count += 1
-
+        # Draw extra note markers.
         elif operation == "extra":
             response_index = detail.get("response_index")
 
@@ -848,8 +856,12 @@ def plot_alignment(ref_events, response_events, event_details, ref_start, ref_en
 
 
 def plot_case(ax_response, ax_ref, fig, ref_events, response_events, event_details, ref_start, ref_end, title):
+    """
+    Plot a piano-roll visualisation of the event-level alignment for a single case.
+    This function is similar to plot_alignment but allows for more control over the axes and figure.
+    """
     selected_details = []
-
+    # Select all event_details that have a reference event overlapping the specified range
     for detail in event_details:
         reference_index = detail.get("reference_index")
 
@@ -860,7 +872,7 @@ def plot_case(ax_response, ax_ref, fig, ref_events, response_events, event_detai
                 selected_details.append(detail)
 
     selected_positions = []
-
+    # Find the first and last positions in event_details that contain reference events
     for position, detail in enumerate(event_details):
         if detail in selected_details:
             selected_positions.append(position)
@@ -877,7 +889,8 @@ def plot_case(ax_response, ax_ref, fig, ref_events, response_events, event_detai
 
     response_starts = []
     response_ends = []
-
+    # Find the earliest start and latest end times of the response events that 
+    # correspond to the selected details.
     for detail in selected_details:
         response_index = detail.get("response_index")
 
@@ -898,7 +911,8 @@ def plot_case(ax_response, ax_ref, fig, ref_events, response_events, event_detai
     visible_ref_events = []
     visible_response_events = []
     visible_pitches = []
-
+    # Filter the response and reference events to only include those 
+    # that overlap the specified time ranges.
     for event in ref_events:
         if event_overlaps_range(event, ref_start, ref_end):
             visible_ref_events.append(event)
@@ -932,12 +946,14 @@ def plot_case(ax_response, ax_ref, fig, ref_events, response_events, event_detai
     ax_response.set_xlim(response_start, response_end)
     ax_ref.set_xlim(ref_start, ref_end)
 
+    # Set the y-axis limits based on the visible pitches, with a margin of 1 pitch above and below.
     if visible_pitches:
         pitch_min = min(visible_pitches) - 1
         pitch_max = max(visible_pitches) + 1
         ax_response.set_ylim(pitch_min, pitch_max)
         ax_ref.set_ylim(pitch_min, pitch_max)
 
+    # Draw connectors and markers for each selected detail.
     for detail in selected_details:
         operation = detail["operation_type"]
         reference_index = detail.get("reference_index")
@@ -997,10 +1013,7 @@ def plot_case(ax_response, ax_ref, fig, ref_events, response_events, event_detai
     ax_ref.set_xlabel("Time (s)")
 
 
-def evaluate_alignment_dataset(
-    asap_path,
-    composer="Bach",
-):
+def evaluate_alignment_dataset(asap_path, composer="Bach"):
     """
     Load one composer's nASAP samples, run the Phase 1 pipeline and evaluate
     the predicted note-level alignment labels against the nASAP ground truth.
@@ -1031,14 +1044,16 @@ def evaluate_alignment_dataset(
             print("TSV not found:", tsv_path)
             continue
 
+        # Load the nASAP ground-truth alignment for this sample.
         ground_truth = load_ground_truth(tsv_path)
-
+        # Convert the pipeline output into note-level labels
         predictions = convert_pipeline_output(
             result["event_details"],
             result["response_events_normalized"],
             result["ref_events_normalized"],
         )
-
+        # compute_metrics uses the normalised response event times, 
+        # restore the original MIDI onset times before comparing with nASAP.
         metrics = compute_metrics(
             ground_truth,
             predictions,
@@ -1146,48 +1161,21 @@ def prepare_alignment_case_study(samples, all_results, sample_index, asap_path=N
     metrics = compute_metrics(ground_truth, predictions)
 
     ground_truth_counts = Counter(note["label"] for note in ground_truth)
-
     prediction_counts = Counter(note["label"] for note in predictions)
 
-    ground_truth_response_note_count = (
-        ground_truth_counts["paired"]
-        + ground_truth_counts["insertion"]
-    )
+    ground_truth_response_note_count = ground_truth_counts["paired"] + ground_truth_counts["insertion"]
+    ground_truth_reference_note_count = ground_truth_counts["paired"] + ground_truth_counts["deletion"]
 
-    ground_truth_reference_note_count = (
-        ground_truth_counts["paired"]
-        + ground_truth_counts["deletion"]
-    )
+    prediction_response_note_count = prediction_counts["paired"] + prediction_counts["insertion"]
+    prediction_reference_note_count = prediction_counts["paired"] + prediction_counts["deletion"]
 
-    prediction_response_note_count = (
-        prediction_counts["paired"]
-        + prediction_counts["insertion"]
-    )
+    actual_response_note_count = sum(len(event["notes"]) for event in response_events)
+    actual_reference_note_count = sum(len(event["notes"]) for event in ref_events)
 
-    prediction_reference_note_count = (
-        prediction_counts["paired"]
-        + prediction_counts["deletion"]
-    )
-
-    actual_response_note_count = sum(
-        len(event["notes"])
-        for event in response_events
-    )
-
-    actual_reference_note_count = sum(
-        len(event["notes"])
-        for event in ref_events
-    )
-
-    response_notes_conserved = (
-        prediction_response_note_count
-        == actual_response_note_count
-    )
-
-    reference_notes_conserved = (
-        prediction_reference_note_count
-        == actual_reference_note_count
-    )
+    # Check whether every response and reference note is represented exactly 
+    # once in the converted pipeline output.
+    response_notes_conserved = (prediction_response_note_count == actual_response_note_count)
+    reference_notes_conserved = (prediction_reference_note_count == actual_reference_note_count)
 
     case_study.update({
         "paths": paths,
@@ -1208,6 +1196,7 @@ def prepare_alignment_case_study(samples, all_results, sample_index, asap_path=N
 
     return case_study
 
+
 def print_alignment_case_summary(case_study):
     """
     Print the label counts and conservation checks for one case study.
@@ -1349,4 +1338,4 @@ def plot_typical_alignment_cases(
     fig.legend(handles=legend_items, loc="lower center", ncol=5)
     fig.suptitle(title, fontsize=15)
     plt.tight_layout(rect=[0, 0.1, 1, 0.93])
-    plt.show()
+    plt.show()
\ No newline at end of file
diff --git a/notebooks/utils/pianovam_loading.py b/notebooks/utils/pianovam_loading.py
index 0322bc8..a93974a 100644
--- a/notebooks/utils/pianovam_loading.py
+++ b/notebooks/utils/pianovam_loading.py
@@ -1,8 +1,8 @@
 """
 pianovam_loading.py
 ===================
-downloading the dataset, loading metadata and ground truth, 
-computing mir_eval-based transcription metrics, 
+downloading the dataset, loading metadata and ground truth,
+converting notes into mir_eval-compatible arrays
 """
 
 
@@ -57,6 +57,7 @@ def load_pianovam_metadata(metadata_path):
 
     metadata_df = pd.DataFrame.from_dict(metadata, orient="index").reset_index(names="sample_id")
     metadata_df["sample_id"] = metadata_df["sample_id"].astype(str)
+    # Convert duration to seconds
     metadata_df["duration_seconds"] = pd.to_timedelta(metadata_df["duration"]).dt.total_seconds()
 
     return metadata_df
diff --git a/notebooks/utils/postprocessing_evaluation.py b/notebooks/utils/postprocessing_evaluation.py
index 43e8fa4..02204a3 100644
--- a/notebooks/utils/postprocessing_evaluation.py
+++ b/notebooks/utils/postprocessing_evaluation.py
@@ -28,30 +28,32 @@ def evaluate_postprocessing(postprocess_function, train_samples,
     rows = []
     postprocessed_predictions = {}
 
+    # Loop through each sample in the training set and evaluate the post-processed predictions
     for row_index, sample in tqdm(
         train_samples.iterrows(),
         total=len(train_samples),
         desc="Post-processing evaluation",
     ):
-        sample_id = str(sample["sample_id"])
-        paths = get_sample_paths(sample, audio_dir, midi_dir, tsv_dir)
+        sample_id = str(sample["sample_id"]) # convert sample_id to string for consistent dictionary key usage
+        paths = get_sample_paths(sample, audio_dir, midi_dir, tsv_dir) # get the paths for the sample's audio, MIDI, and TSV files
 
-        reference_notes = load_ground_truth_notes(paths["tsv"])
-        predicted_notes = tuned_predictions[sample_id]
-        postprocessed_notes = postprocess_function(predicted_notes)
+        reference_notes = load_ground_truth_notes(paths["tsv"]) # load the ground truth notes from the TSV file
+        predicted_notes = tuned_predictions[sample_id] # retrieve the tuned predictions for the current sample
+        postprocessed_notes = postprocess_function(predicted_notes) # apply the post-processing function to the predicted notes
 
-        metrics = evaluate_note_transcription(reference_notes, postprocessed_notes)
-        transcription_output = analyse_transcription_output(reference_notes, postprocessed_notes)
+        metrics = evaluate_note_transcription(reference_notes, postprocessed_notes) # evaluate the post-processed notes against the ground truth notes
+        transcription_output = analyse_transcription_output(reference_notes, postprocessed_notes) # analyze the transcription output for additional metrics
 
+        # create a row dictionary to store the evaluation results for the current sample
         row = {
             "sample_id": sample_id,
             "composer": sample["composer"],
             "piece": sample["piece"],
-        }
-        row.update(metrics)
-        row.update(transcription_output)
-        rows.append(row)
+        } 
+        row.update(metrics) # add the evaluation metrics to the row dictionary
+        row.update(transcription_output) # add the transcription output analysis to the row dictionary
+        rows.append(row) # append the row dictionary to the list of rows for the final results DataFrame
 
-        postprocessed_predictions[sample_id] = postprocessed_notes
+        postprocessed_predictions[sample_id] = postprocessed_notes # store the post-processed notes in the dictionary for later use
 
     return pd.DataFrame(rows), postprocessed_predictions
diff --git a/notebooks/utils/random_search.py b/notebooks/utils/random_search.py
index 7e0371d..e375553 100644
--- a/notebooks/utils/random_search.py
+++ b/notebooks/utils/random_search.py
@@ -55,11 +55,14 @@ def run_random_search(train_samples, parameter_sets, basic_pitch_model,
     Returns basic_pitch_model, since it may be replaced with a fresh
     model object partway through the search.
     """
+    # Load the sample_ids that have already been processed, so we can skip them.
     completed_sample_ids = load_completed_sample_ids(progress_path)
     remaining_samples = train_samples[
         ~train_samples["sample_id"].astype(str).isin(completed_sample_ids)
     ]
 
+    # Loop over every sample in the train split, and evaluate every
+    # parameter configuration against it.
     for sample_index, (row_index, sample) in enumerate(
         tqdm(remaining_samples.iterrows(), total=len(remaining_samples), desc="Random search")
     ):
@@ -69,9 +72,9 @@ def run_random_search(train_samples, parameter_sets, basic_pitch_model,
 
         sample_rows = []
         for config_id, config in enumerate(parameter_sets):
-            predicted_notes = decode_model_output(model_output, config)
-            metrics = evaluate_note_transcription(reference_notes, predicted_notes)
-
+            predicted_notes = decode_model_output(model_output, config) # decode the raw model output into note events using the current parameter configuration
+            metrics = evaluate_note_transcription(reference_notes, predicted_notes) # evaluate the predicted notes against the ground truth notes
+            # create a row dictionary to store the evaluation results for the current sample and configuration
             row = {"config_id": config_id, "sample_id": sample["sample_id"]}
             row.update(config)
             row.update(metrics)
@@ -85,7 +88,7 @@ def run_random_search(train_samples, parameter_sets, basic_pitch_model,
 
         # Release this sample's raw model output before moving on.
         del model_output
-        gc.collect()
+        gc.collect() # Force garbage collection to free memory used by the raw model output, which can be large and is no longer needed after evaluation.
 
         # Periodically recreate the Basic Pitch model object.
         # TensorFlow keeps caching a new computation graph every time
@@ -106,8 +109,10 @@ def summarise_random_search_results(progress_path):
     Load the full per-sample search log and aggregate it into one
     row per configuration, sorted best-first by note_f1_no_offset.
     """
-    search_details = pd.read_csv(progress_path)
+    search_details = pd.read_csv(progress_path) # load the full per-sample search log from the CSV file at progress_path
 
+    # Group by configuration parameters and compute the mean of the 
+    # evaluation metrics for each configuration across all samples
     random_search_results = (
         search_details
         .groupby([
diff --git a/notebooks/utils/transcription_evaluation.py b/notebooks/utils/transcription_evaluation.py
index c0b79af..ab8f897 100644
--- a/notebooks/utils/transcription_evaluation.py
+++ b/notebooks/utils/transcription_evaluation.py
@@ -66,8 +66,7 @@ def transcribe_audio_cached(cache_dir, sample_id, audio_path, model, **config):
     """
     Return cached predicted notes for a sample if available, otherwise
     run Basic Pitch once (optionally with non-default decoding
-    parameters passed via config, e.g. onset_threshold=0.7) and cache
-    the result.
+    parameters passed via config) and cache the result.
  
     Returns (predicted_notes, runtime_seconds). runtime_seconds is
     None when the result came from the cache, since no transcription
@@ -122,7 +121,7 @@ def decode_model_output(model_output, config):
     """
     min_note_len = int(round(
         config["minimum_note_length"] / 1000 * AUDIO_SAMPLE_RATE / FFT_HOP
-    ))
+    )) # Convert milliseconds to frames, since model_output_to_notes expects a frame count.
  
     # model_output_to_notes does not modify the raw "note"/"onset"/
     # "contour" arrays in place as long as min_freq/max_freq are left
@@ -252,6 +251,8 @@ def evaluate_on_pianovam(split_name, metadata_df, audio_dir, midi_dir,
 
     rows = []
 
+    # Run Basic Pitch on every sample in the split, using the raw-prediction 
+    # cache to avoid re-running the model on samples already processed.
     for row_index, sample in split_samples.iterrows():
         paths = get_sample_paths(sample, audio_dir, midi_dir, tsv_dir)
         reference_notes = load_ground_truth_notes(paths["tsv"])
@@ -260,6 +261,8 @@ def evaluate_on_pianovam(split_name, metadata_df, audio_dir, midi_dir,
             **BASIC_PITCH_DEFAULT_CONFIG
         )
 
+        # Evaluate the predicted notes against the ground truth using both mir_eval metrics 
+        # and compareMusic alignment stats.
         transcription_metrics = evaluate_note_transcription(reference_notes, predicted_notes)
         transcription_output = analyse_transcription_output(reference_notes, predicted_notes)
 
@@ -291,7 +294,9 @@ def evaluate_new_configuration_on_pianovam(config, samples_df, audio_dir,
     """
     rows = []
     predictions_by_sample_id = {}
- 
+
+    # Run Basic Pitch on every sample in the split, using the specified configuration 
+    # and without caching, since the cache only stores default-configuration predictions.
     for row_index, sample in tqdm(samples_df.iterrows(), total=len(samples_df), desc="Evaluating configuration"):
         paths = get_sample_paths(sample, audio_dir, midi_dir, tsv_dir)
         reference_notes = load_ground_truth_notes(paths["tsv"])
@@ -563,7 +568,8 @@ def match_notes_for_plotting(reference_notes, predicted_notes,
         onset_tolerance=onset_tolerance,
         offset_ratio=offset_ratio,
     )
-
+    
+    # mir_eval returns a list of (reference_index, predicted_index) pairs for matched notes.
     matched_reference_indices = {pair[0] for pair in matching}
     matched_predicted_indices = {pair[1] for pair in matching}
 

From fdbb2d221b6283d79f714cff3a87cee91982fede Mon Sep 17 00:00:00 2001
From: ada-3e212e610b <z2720629308@gmail.com>
Date: Tue, 25 Aug 2026 10:46:30 +0100
Subject: [PATCH 24/25] regenerate results

---
 notebooks/Phase1-1.5_summary.ipynb | 5 ++---
 1 file changed, 2 insertions(+), 3 deletions(-)

diff --git a/notebooks/Phase1-1.5_summary.ipynb b/notebooks/Phase1-1.5_summary.ipynb
index 3e40058..e760cb6 100644
--- a/notebooks/Phase1-1.5_summary.ipynb
+++ b/notebooks/Phase1-1.5_summary.ipynb
@@ -21,8 +21,7 @@
     "- Step 2: estimate the overall timing and duration difference between reference and response, using linear regression.\n",
     "- Step 3: compute metrics to provide event-level feedback (note/chord-level feedback)\n",
     "- Step 4: compute the summary statistics to provide overview feedback\n",
-    "- Step 5: generate human-readable feedback message from step 3 and step 4\n",
-    "- Step 6: provide an additional overall pass/fail judgement based on step 3 and step 4"
+    "- Step 5: generate human-readable feedback message from step 3 and step 4"
    ]
   },
   {
@@ -331,7 +330,7 @@
     },
     {
      "data": {
-      "image/png": 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pjTfeyI/jWijaivfeey//HDMv5pprrrTTTjullVdeOR8P3bp1q/EeQ8eIJI6mfYU4DuJ4iOMi9O/fv9ouRKLHgAEDUpcuXbwdJSNoW0Ix6hdZIY888kjulNx8881p6aWXrvVuQU3069cv3XTTTflYiGPitddeSwsuuGBe13QkMAJa8ZzevXt7p6hL0emO9uGKK67IF1v/+te/cpZ50fmOkggxwHHllVfmLJJ1113XdHDqVq9evdJnn32WO+fRKbn66qubXSvFAF4sj4FuqHeRJRWD3C+//HL+isBULGuaXXj99dfnzPMimAX1KtqCaBNicDsG7+KaaZ555qkO8C211FLp9ttvz8GrF198sda7Cx1mttlmy4MURRmE6EMsuuiirQKzcYzELO4orUb5CNqWUOfOndN2222X7rnnnnTppZfmjKk42KARRU3OLbbYIh8LcUxsu+22+RhpKjKt4uJshRVWSAsssEDN9hU6WnzG+/Tpk4OycYG19tprN1sfnZKY6hTPiYuvCGpBvYq24YUXXkgXXXRRzqiN2RahCObG9RM0gsgmj75DdMzjKx4XJRBiYG/LLbdMCy20UJp55pnTxRdfnO8FAPUqPusx6+jCCy/MgxgxG68QpXIiEz0GwmM6ePQfIlMd6tV6662Xs2jPPffcnPi03HLLtXpOJH1EH2LeeeetyT7y1QRtSypuDhAZVNHxWGyxxWq9O1Dzi6/ImIqGpmWdnQhcRWZhLI8ba0C9iwyR4cOH5wBup06dmq2LTPMYJd9mm21yh13HnHoWn/HIPo9ZFk07IY899ljuoMQsjauuuiqXCbn77rvzTA2oV9HZjqBszLpoOuuoKI0Q017jhkvx9cQTT9R0X6GjRab5iBEj0rLLLpuPi8Icc8yRlllmmRzIirJS3/jGN5qVEoF6E32FJZZYIvcdJlViM66bolwI5SRoW1Jxc6XIJow6Iy3v+AqNpFKp5FHwddZZJ9fyfOqpp6rrYprH5Zdfngc5mo6iQ7368MMPcyBq++23z5mE77//fnVdZJM0nQobgaqYFgX1KgYlYqp3DNhFcLaobxuD3VEepLi5RnTYIws32gqoV1FOLT77MTsvZiZNSlxLqfNMPYtroEjoiAHsGKCIm44VFllkkWb1/j/44AM35qOuvfPOO7lkTtz34pprrml1k+IxY8bkY0Q5qfKaqdY7QGtx0MSBtffee+fC6Oeff356/PHH00orrVS9EVNRTD1uShPTxzfZZBMvJXVpyJAheQAjgraRSXXBBRfkEggxhSPqUUXdwuh8RIc9xECHGtDUowhIRSckglFxYRWdkqhNteeee+Zj5Nlnn0233HJLnu4X7UgEqaJUAtSjGLCIQe24GWVkGMZnPq6PNtpoozTffPPlr0Jk2UaWSRwbUI8iU3DYsGFpr732ygPaZ599dg5OxVfU7HzyySfz89599908+LfHHnvUepehw0T/OAbsIrs8+snRR9hnn31yqZDIJoxp4tG/jiz0yD78/ve/792gLkWANvoKW2+9db4OiplJUd88SugUHn300dzHLkrqUD6CtiUUHfFddtklT28KO+64Y7MRwpgiHgGr4gYDRsup5yzbuNiKulQhOtxxt9colRDHQDQwUbuzqXg+1KOowxZ1O2OqX4iBvOiARMZIZBBGfc+RI0fmC7INNtigWdAK6vF42GGHHar117baaqv0/PPP58GNlnXPY2A7Sk5BvYrg084775y/x9euu+6aMwiL66LoM8QU2SifEyWn4jlQj6K0YASnipI5MXARNZ3jWimumaLfvN9+++Wbfoc4HoobukK9ic991PePYyJE/yBqOEcwt4ghRZmpuLkr5aXFLqG4o19TUaszau8Umt4NFupZdDAic7appjcaiwGM+IJGEG1BEbAtNG0bQgSw3ESARtDyppPR+Yg6z23p16/fdNorqI2WM4yiA150wps+hnoX2YIt24KWs45i0CLuDwD1Lgasmw5ax6B2y+NDbKn81LQFAAAAACgRQVsAAAAAgBIRtAUAAAAAKBFBWwAAAACAEhG0BQAAAAAoEUFbAAAAAIASEbQFAAAAACgRQVsAAAAAgBIRtAUAAAAAKBFBWwAAAACAEhG0BQAAAAAoEUFbAAAAAIASmanWOwAAwIzrvvvuS0OGDElLLLFE+s53vlPr3SmFxx9/PN14441pmWWWSdtss03q0qVLrXcJYLoaNWpUuvrqq9M777yTjjjiiDTrrLN6B1JKv/3tb9Occ86ZvvWtb6UFF1zQawJ8JUHbknr55ZfTH/7wh/Tcc8+lVVZZJR199NFp9tlnr66/4IILciPYqVOntN1226Xvfe97Nd1f6Ei33357uvDCC9Po0aPTt7/97fSDH/yguu7+++/P615//fW09NJLpx/+8Ic5cAD16PPPP09/+9vf0k033ZS6deuWDjnkkLTmmmu2et7111+fTjnllLTvvvumXXfdtSb7SmN46qmn0je+8Y18Xl588cVbrb/11lvTo48+mpZccsl8/u7c+ctJXm+99Va+lvn444/TxhtvnAYOHDjVf/+rtl+44YYb0kMPPZT233//1KdPn3bZfnS6P/nkk1bPjzaoV69e+fGYMWPSAQcckIYNG5aPVehIjz32WPrLX/6SP28bbrhhOuyww9JMM33R1XvvvffSqaeemp544onUo0ePfCysu+663hA61A477JA++uijNGjQoFbr4ro9zs1xXbPtttumvn37VtdFm3DNNdfk58TAVwQ32zq3T6rPcPfdd7davvrqq6ctttgiPx4xYkT697//nd599900YMCA9M1vfnOK/6cp2f7k/r9YFm3f6aefnp5//vkp/tswtfbbb78cT2rp5JNPzp/ZK664Iv3xj3+sLr/00kun+jqJjqc8QglF5yACtRMmTEgHHnhgmmeeedKhhx7a7CD7v//7v5zNsvXWW+d1p512Wk33GTpKNCQxMLHCCivkzu+DDz6YBy2KhuXHP/5xWmmllfKxMnLkyLTqqqumV1991RtC3Zk4cWLO2Pvzn/+cz//RGTrqqKPS22+/3SqzJTrr0RGITgN0pEceeST1798/nX322bljWoiA5uabb56DQxFEig5q0wGECB4tt9xyOSj64osv5sDvOeecM8V/d3LbL8S299lnn3TCCSfkbK/23n7hnnvuSWeeeWaaY4458s/RLsX12p577pkDxtCRYqBuvfXWS717987XQ++//3761a9+VQ2AxeDef//739yBX3HFFdNmm22W7rrrLm8KHerhhx9Ov//97/NnsWmW7cUXX5yWX375HPyM65Qtt9wyPfvss3ldnKdjXQxAxPXMMccck9fHNdC0+PTTT/P5f/jw4fnn//f//l9ae+210x133JHeeOONnPgU11bttf3J/X/hpz/9aTr//PPTCy+8kI9V6CiRvHH88cdXvyJQG7GmuP4K0TbE8hh4jzahrcFoSqAyAxs+fHgl/oX4isf1YvXVV68cfvjhzZZ99NFH+ftnn31W6dGjR+X888+vrjvnnHMqPXv2rIwfP75SD+r1fe1o9fi6vf3225WuXbtWbr755jaPhzFjxjRbPnHixMrCCy9c+cMf/lCpB/X4nk4v9fjaXXTRRZVevXpV3n///eqyOO9/+umnzZ63/fbbV84666zKgAEDKr/5zW8q9aIe39N6eN3+/Oc/V9ZYY41Wy4855pjKCiusUBk7dmx12VNPPVV9PGjQoMpuu+1W/Tmua7p37149v0/O5LYfJkyYUFlnnXUqZ599dv7/H3vssSn+v6Zk+y2v3X70ox+1Wn7cccdVtttuu0p7czx43QrRBvTp0yef95sqjqXLLrssH1sff/xxdd2BBx5Y2XDDDSv1wLFQ3teuS5culYceeqjZsldeeSVf299www3VZXE9P2zYsPz44IMPbtamxDVP9HMvueSSab52ir5zcTw88sgjzdqZF198Mf//gwcPbpftT+7/K4wcOTL/3ejrtCfHg9ftq2ywwQaV/fffv9XyoUOH5s9jfH7ryfA66TvItC2ZyJiKTMKYshTZGTEd5Je//GUE1/P6Z555Jk+322STTaq/E49jeofpFdSbmLoUNZ9iSlRkFu60007p73//e5ptttny+rnmmqvZ88eNG5ePhfnmm69GewwdJ6YKbrXVVuncc8/NGYB77713zlacZZZZqs+55JJLcsZ5ZKXD9BDTrotzclPnnXdeOvjgg/N5/He/+12u71pkdnz22Wc5y2mXXXapPj/O7zGN9t57752iv/tV2y9EiZBFF100z0qaWlOy/ab1a+PaLTJaWorXJl4j6CgPPPBAzk6Mz+fOO++cM96jxFrRNkSb0LNnz1xSp7DQQgvlWtTTml0Ik/PBBx/kWaMt24fIQo2SB1HKLM6tca6N7L6ifEBM5V5jjTWqz49+QHy24xw8LSJjN7Jpi/1YeeWVm+1TlAuJcoOxr+2x/cn9f4XieNQ+ML3EsXXnnXfmGRfMWARtSyamaYQjjzwyT92IVPWohxPTmCJwGxdeYd55563+TvG4WAf1dDxEIPZnP/tZ2n333XNNrCiHUEz5a+mggw7KdQfdCId6PR4icDt06NBcNzNqTsW0pph+WAz6RdsRQd3ogEBHikDl4YcfnjusTeuMh5juGUGkKG8TNcfjcUzZjimocS0TP48fP77ZDViiAxuBpeI66KtMbvvh6aefTmeddVY644wzpvp/m5LtNxUlS6KGaL9+/Vqti4DxSy+9lAfir7rqqqneF5icOGaidm2US4tkjx133DGX6oiBvRABsJiiHSU8inIJUccwAkkffvihF5h2FwlHMcgctcojgNlUlAkYO3ZsHlyIc2uUnonnxCB0iOv4piVl4jMa1z3TUu4paq7HQGCUuZmU4447LgeF11prrXbZ/uT+v0LcqyaCvfF17LHHmpZOh4vrtWgPonwTMxY3IiuZmWeeOX+P7I6owRai9lSM1j355JOpa9eueVkEsooR9Lj4CsU6qKfjIS58otMcNxkrakfFxWDUgypEJzqOmcgaiRsENM08hHo6HiKLPGqHRlA2aqRFXaq//vWvuZZztBkRRIsOD0wPkTEbX5Gp1FSRsRTn7X/+85/5cXw2F1tssXTbbbdVz+ctBxfiXD4lAw6T2/4GG2yQ9thjj3zjpQgET00t2ynZfgQimgYUIsM9bhDYlqhxG21SZJ21FfCF9mgb4sZGv/nNb6o3Qor7YUTCRww8RPvwi1/8Im266aY5OBU3AIwa0tF+NM2+hfYSGdxxbozB5ZY3EIvzawRg46bbxcBd1OiP4GkMTMfgc9TdjPP4aqutlv7zn//kmzt26dJlqvcjBtTisz6pWRKRBBJB1cg+LPrgX3f7k/v/mor2Kfo505rlC1MqBukuuuiifF3EjEfQtmQiOBuNUtMpFAsssEB1+kQxWhmlEKIhKx5HJ0dHnXpTdOxbHg+jR4+udu7jQieCVZFtGAXU4yYcUK/HQwR/mga14niItiHKgsSsjAgMXXvttdUbMEWAN6ZDxQ0voD1FpkZkssaU0Oi4RlZVYe65587Byuh4F6LzOv/88+fPZdwwKTIDI0MwbjJZDEbHZ7lp9u2kTG77UUbqtddey1lQ8RWd4iLLJLKf2rqT+dRsv2nQNm5qE6/BpGZ4RHZt9+7d05VXXjnZ/wva81oprpPieik+y5HJF2Vz4vO78MIL5xkZ0TYY5KYjRIDy+9//fi5P88orr+QBr0J8/uJc2vRcH33aCCgV6yNb9V//+lcecIvPatzoK0p6TI0otxPn5z/96U9tro9jItbHzcKi/z21JrX9yf1/hRjwjIz4+PsxuxY60mWXXZYHU6IUFTMe5RFKJur2RK3CyNooRt2iQYgL/gEDBuRGIDo7cSfOuBiLr9NOOy1ttNFGeRQS6kl0rKPzHHVsQzQ2//jHP3LN5whcxfTauJt33BE5RskFbKlnUasw6mYW9cvjrso33XRTzvKItiNqhEY2VXGH2MhwieBSTOuGjhKd8ZY1+eL8HFl98XktDBs2LJfwiBICESiK65Y4nzftUMR00aLzOnjw4FyXsy2T234EsaJczlf5OttvKjLdozzEpLK0IoAcgQvoKNE/WHbZZavXSkXfYZFFFqkGuqLOZlxPxUBEtB2nn356LjcFHSWCl5Fl27J9iAzwyPaOc2ohyiEU59YYaIhZdTFbIrJuo72IbNsIAhfBzrjGiQGIrxJ96fjd7bffvtny6DsfcsgheRZFlAxpGbD9utuf3P9XiEzk6OtrH5geYtA6Sg2aXTFjkmlbQpGxEtNeF1988XyBFSf9GJ2LqU7hnHPOyYHdWB8NTzQYcaMMqDcxWBEXRd/97nfzcRF1BiM4VdQFjNHtyy+/PN9UILKnCjGK6EZM1JsIIh122GFplVVWybMuokMRbUHUt42sxZhK2FRkV0U7UczKgI4QnfK2pv3HVO0YYIuartFZjRqa2223Xa79Gk4++eQ8CB0ZqjHgFkGmGIQubuYSZQgiazw6122Z3PajtFQhsrViSmDUHSxquX3d7YcoyRODhjG9dlLitZmWab0wNeJaKWouX3fddXnQITLXYyCkENmOEUSLvkQ8Pvroo3MtTego8TmMr5btQ1yrxE0o4/waAc/I+L7//vtzxmmIhIy4tokas/E5jnNvlEUrbk4Wwc7IvI1roq+aZRoDahHobVk+MLYVGa5xM6a4SVgh6kFHf+Lrbn9y/1+heF20D3S0KLEZn8G2yjjF/Qmib1GU24wEkVlnnTX3sSdVVoTpT9C2hGI6RRxAMaUvalRF57zpqEhkkESmVRQ0j8YwOiZO+NSrGLGOgYvoGM8111xpqaWWqtbHis5+ZJi0NLVTqGBGceKJJ+abzUSttMiiitkXkxJTCqMGLnSkGEiLshwtxbn6mWeeyWUBYsAtBpw32WST6vo4d8fNZWIQLjoLkfE0cODAZpmwX5UJOLnttxzAiOm6kX3entuP/Y4SEU2n/raVaRuvEXSkGIyIG95F5zySOWKgoWn2d9wHYN99980B2+iIx6A41Kp9iGSkm2++OT322GNp+eWXz/euKJKT4rrllltuyZmwkXH7k5/8pNnNzOLcHQHdr7pxWJTEiZI9LW+SGaLfHO3BpHzd7U/u/2vaNgTtAx0taicPGTKkzSBsZHpHZnlLU1KqiumnU2UGvivCiBEjqtOhhw8frnNaJ7yvXjccC84jaBtmjDY1AkXRod5tt91yVmrTWQ9fR0zfjizYljexaS8dvf0YfI/p6pHJdcopp6S99tqrXbfvWsnrhmOh7OeRaBMi8SJukPezn/0sZ/B9XVEKKmaiFrMm2ltHb7/I9o2SDxH8jcBue9I2eN2ov+NBpi0AANMk6gHGtLuoK970JnlfV0zX60gdvf0iuyUyrCJwAdBoYuAqZitEjdf20rRETUfo6O2HyIKPe3JM6gaWAE0J2gIAMM2iznJ88aXI0urITC2AsuvRo0e7zzKoB0cddVStdwGYgXTMnDAAAAAAAKaJoC0AAAAAQIkI2gIAAAAAlIigLQAAAABAidTNjchGjhxZ612gnXgvvYY4FtqTc0p98D56DXE8OKegbdDG4lrJ9SaN1Heom6Bt//79a70LUBqOB3A8gLYBXCuBvgPoRzPjUh4BAAAAAKBEOlUqlUqaQU2cODGNGjWq1rtBB+rVq1fq3NnYwpRwPNQ3x8LUcTzUN8fDlHMs1D/Hw5RzPNQ3x8LUcTzUN8fDlHMs1L9eM3BcaYYO2gIAAAAA1JsZM9QMAAAAAFCnBG1nEBMmTki/vufX6eqhV9d6V6D2hg9P6cc/Tmno0FrvCdTc4NcHp2NuOyaNGz+u1rsCNffXR/6azn7k7FrvBtRctAnRNkQbAQ0v+gzRd4g+BDS4iClFbCliTJSf8ggziD2u3iNd9ORF+fHte9yeNlx0w1rvEtRO374pvfVWSt26pTRmTEqzzOLdoCG99cFbacHTFkyVVElr9l0z3bf3fbXeJaiZ0+87PR3+n8Pz49MGnZYOW+sw7wYNa81z10wPvPlA6typc3rjsDfSAnMuUOtdgtr47LOUevRIady4L/oQw4Z5J2hYd7x6R9rowo3y4z0G7JEu+PYFtd4lJkOm7Qxg7Gdj0z+f+Wf15+PvOL6m+wM1deedXwRsQ1x8XfTFYAY0ohPvOTEHbEN0zl8Z/UqtdwlqYmJlYjr1/lOrP8fjWAaNKNqCB998MD+O4yDaCmhY0VeIPkN4880v+hLQoI6747jq48ufvjzHmig3QdsZwFkPnpXGff7ltNe7X787PfHOEzXdJ6iZ41sMWpx44hcj6NBgRn40Mp3/+PnVnyN4G1OdoBFd8+w1adgHX2ZPxeNYBo0o2oJiQC9EWxFtBjSc6CNEX+Gr+hLQIB5/5/F0z+v3VH+OGFPEmig3QduSi5GP3937u1bLf3H3L2qyP1BTMTJ+113Nl736qmxbGtIp957SbEAvXPDEBbJtaTiRSXjCXSe0Wh7LZNvSiFm20RY0FW1FtBnQkFm20VdoKvoSsm1pQL+4q3UMKWJNsm3LTdC25GLk491x77ZaftXQq2Tb0ngmNTIu25YGExlTf3zoj62Wfz7xc9m2NJzIqH1y+JOtlscy2bY0YpZttAUtRZsh25bU6Fm2Bdm2NGCW7dXPtr6pfcSaZNuWm6DtDJJl2yl1arVeti0Nm2Vb3His8/9OYbJtaTCRMfXx+I+bLZu588z5e2RYvTqmRVYJ1KlKpdJmlm0h1sVzoBHEub/Isi3ahEK0GbJtadgs26LPUPQhZNvSYNrKsi1iTLJty03QtsSGjhxazbJddt5lq8t7duuZv9/1aotp4lDP7r77y8e9e3/xfeaZ214PdS5qm4euXbpWly0xzxL5e2RY3ffGfTXbN5ie3v/0/WqW7WI9FqsuLx7HungONIJ737i3mmVbtAlN24qi7YCG0LSkWtFnKPoQQd+BBnL3a3c3iyU1jTFFzCliT5SToG2Jrdh7xbRz/53TJotvkjZcdMPq8p+u99O0yvyrpKPXPbqm+wfT1a67prT22ikddFBKPXp8OWr+61+ntMoqKe23nzeEhnHYGoelgX0GplMGfVmjcOmeS6cdltshDVpiUNp0yU1run8wvczVda58PKy14Frp+yt9v7o8HseyWBfPgUaw2ZKb5TYg2oJoEwrRVkSbEccDNIz99/+ijxB9hSLTNvoQ0ZeIPsV3v1vrPYTp5qh1j8oxpIglFSLGFLGmiDkN6DPAu1FSnSrmjM0Qjrr1qHTSkJPy4zv3uDOtv+j6td4lqJ0BA1J68smUunVL6ePmU8Shkbz14Vup7+/75sfbLrttunLHK2u9S1Az5z56btrnun3y43O2PiftvfLe3g0a1naXb5fvgRHe/NGbaYHuC9R6l6B2ZpstpXHjUlpxxZSeeMI7QcOK2dobXLhBfnzkOkem327821rvEpMh0xYAAAAAoEQEbQEAAAAASkTQFgAAAACgRARtAQAAAABKRNAWAAAAAKBEBG0BAAAAAEpE0BYAAAAAoEQEbQEAAAAASkTQFgAAAACgRARtAQAAAABKRNAWAAAAAKBEBG0BAAAAAEpE0BYAAAAAoEQEbQEAAAAASkTQFgAAAACgRARtAQAAAABKRNAWAAAAAKBEBG0BAAAAAEpE0BYAAAAAoEQEbQEAAAAASkTQFgAAAACgRARtAQAAAABKRNAWAAAAAKBEBG0BAAAAAEpE0BYAAAAAoEQEbQEAAAAASkTQFgAAAACgRARtAQAAAABKRNAWAAAAAKBEBG0BAAAAAEpE0BYAAAAAoEQEbQEAAAAASkTQFgAAAACgRARtAQAAAABKRNAWAAAAAKBEBG0BAAAAAEpE0BYAAAAAoEQEbQEAAAAASkTQFgAAAACgRARtAQAAAABKRNAWAAAAAKBEBG0BAAAAAEpE0BYAAAAAoEQEbQEAAAAASkTQFgAAAACgRARtAQAAAABKRNAWAAAAAKBEBG0BAAAAAEpE0BYAAAAAoEQEbQEAAAAASkTQFgAAAACgRARtAQAAAABKRNAWAAAAAKBEBG0BAAAAAEpE0BYAAAAAoEQEbQEAAAAASkTQFgAAAACgRARtAQAAAABKRNAWAAAAAKBEBG0BAAAAAEpE0BYAAAAAoEQEbQEAAAAASkTQFgAAAACgRARtAQAAAABKRNAWAAAAAKBEBG0BAAAAAEpE0BYAAAAAoEQEbQEAAAAASkTQFgAAAACgRARtAQAAAABKRNAWAAAAAKBEBG0BAAAAAEpE0BYAAAAAoEQEbQEAAAAASkTQFgAAAACgRARtAQAAAABKRNAWAAAAAKBEBG0BAAAAAEpE0BYAAAAAoEQEbQEAAAAASkTQFgAAAACgRARtAQAAAABKRNAWAAAAAKBEBG0BAAAAAEpE0BYAAAAAoEQEbQEAAAAASkTQFgAAAACgRARtAQAAAABKRNAWAAAAAKBEBG0BAAAAAEpE0BYAAAAAoEQEbQEAAAAASkTQFgAAAACgRARtAQAAAABKRNAWAAAAAKBEBG1LrFKppN8N+V066taj0ucTP68uf/vDt9O+1+2b/v3Cv2u6fzBdjRmT0sEHp3Teec2XX399Svvum9Jrr3lDaBgPv/Vw2vvavdMT7zzRrM347eDfpmNuOyaNnzC+pvsH09OFj1+YfnjjD9NHn31UXRaPY1msg0YR5/5oA6ItiDahEG1FtBnRdkDDePXVL/oIN9zQfPnf/vZFn+L992u1ZzDd3fjCjTmGFLGkQsSYItYUMaembQbl0qni3SmtR99+NK1y9ir58ep9V08Pvvlgfrz43Iunl0e/nOabfb40/P+G13gvYTo58cSUfvrTLx4vvnhKL7+cUteuKX3+eUoTJqT0/e+ndP753g4awrrnrZuGvDEkzT3r3Gn0J6PzspX6rJQef+fx/Piy7S9LOy6/Y433Ejre+5+8n3qc1KPVMbBS75XS48O/eDzmyDFprlnn8nZQ9y576rK085U758cD+wxMj73zWH5ctBXrLLROGvyDwTXeS5hOom9w4YUpdemS0kwzpfTpp1/2IcKvfpXSscd6O2gIvU/pnUZ8NKIaSwqrL7B6evCtL2JMj+z7SFp5/pVrvJe0RaZtiS0050Kpa5eu+fFjb39x0RWKg2zpnkvXbN9gulu6yed9+P8GK4qAbcv1UOeK838RsA3PjXqu1Xqod3PMMkdaoPsC+XERsM2P/xew7du9b34ONIKm5/5nRz1bfVy0FdoGGkq/fl98j75C9Bma9iGCvgMNpDj/F7Gk8Og7j+bvs840a449UU6CtiU27+zzpv1W2S8/Hj+x9VTXn37jf1mH0Ai23fbLi6+P/jcFtgjY9uiR0oEH1m7fYDo7cp0jU+dOzZvwcZ+Py9+3XGrLnHEIjaBL5y7p6HWPnuT6WBfPgUYwcP6BaYultmjWJhSizThq3aNqtGdQAwcc8EUfoWmfoehDLLPMF30LaBDHfqN1VnlRgjNiThF7opwEbUvuyHWPrGbbNrXmgmumQUsMqsk+QU3E1Kaf/7ztdT/6UUpzmfpK4+jXq1/adYVd21x33PrHTff9gVrae+W9q9m2TUWW7V4r71WTfYJamVQb8N0VvivTlsYSAdvDD297XfQpom8BDWLTJTZNa/Rdo9XyyLKNZBDKS9C25KITUmTbNnX8+senTp061WSfoGZ22unLbNumF2SHHFKrPYKaidkWLbNtI8t2tb6r1WyfoBaiw9FWtm0si3XQSOI+GEW2bSHaip+uZ4YeDSj6CEW2bSGybHdU95/GErGj4zc4vtXyiDXN333+muwTU0bQdgbJtu3S6cuRwOXnXV6WLY2prWxbWbY0cLbtt5f5drNlsmxp5GzbHrN+2TGPx7JsaVQt24LvLPMdWbY0praybWXZ0sDZtsvNu1z155k6zyTLdgYgaDuDZNuut8h61Z+PWPsIWbY0drbtHP+7qUznzrJsaWg/W+9n1ceL9VhMli0NKzJqd1tht+rP8ViWLY2cbRttQlttBTScQw/9os8Qog8hy5YGzrb9ydo/qf683sLrybKdAXSqVCqVWu8Ek/fex++lXa/aNfXr2S+dsfkZXjIa2z33pHTkkSn98Icp7dp2XU9oFCcNPind8MIN6bxvnZeW7LlkrXcHambCxAlp1yu/aBMu2e4SNyCjob3w7gtpr2v3SlstvVX6yTpfdtKhIV18cUpnnZXSSSel9I1v1HpvoKYO/feh6bl3n0v/2O4fae5uc3s3Sk7QFgAAAACgRJRHAAAAAAAoEUFbAAAAAIASEbQFAAAAACgRQVsAAAAAgBIRtAUAAAAAKBFBWwAAAACAEhG0BQAAAAAoEUFbAAAAAIASEbQFAAAAACgRQVsAAAAAgBIRtAUAAAAAKBFBWwAAAACAEhG0BQAAAAAokZlqvQNMveeffz5NnDgxP15qqaVSly5dvIw0rPHjx6c333wzde3aNfXp0yd16tSp1rsENfPJJ5+kt956K80+++ypd+/e3gka3rhx49Jrr72WFllkkdStW7eGfz1oPJ9//nl68cUXmy1bbLHF8nUTNKp33303f0WfetFFF02zzjprrXcJahpXKjgeykfQdgb01FNPpc8++yw999xz6YgjjkizzTZbrXcJauKll15KN9xwQ5pzzjnT+++/n7/vtttuaeaZZ/aO0HCefvrpdOutt6Z55pknd0TmnXfetMsuu6TOnU2qoXFFGxGdkmgbFl544VrvDtRkMO+KK65ISy65ZHXZ/PPPL2hLw7r++uvTM888k/r27ZuTn+abbz5BWxrSf//735wAFSK+FIPcP/rRj2q9W7QgaFtCr7/+eu50zzHHHPnnCRMm5BHyfv365Z+33Xbb/P2EE06o6X5CR6tUKrmzvfTSS1czaD/44IP8teCCC+aRwR/84Af5WInj5K9//Wt69tln0worrODNoe58+OGHacyYMWmhhRaqLous2hi469GjR+6AH3jggXnQIjKrTjnllGrwFurNO++8kz/zc889d3XZCy+8kDNEioG76IzEYF58QT2LfkIMSswyyyzNZl0svvji+efIItx5551rvJfQ8T799NM8A6/47IdRo0blPkMEZyPpKY6Xgw46KM9KgnoW/YDoEzSdfReB2egbRP9hu+22qy5/4IEHclvhuCgf6TclFAfSkCFDqj9H4/Loo4/WdJ+gFiJQe99996WXX365uuzOO+9Mb7/9drU8SDG4ESPl0VkpOixQb+Izftlll1VHxKMDcvnll+fBjRBZVJFxPnTo0HTXXXflC7IYAIR67YjcdNNNzYK4t9xySzVgO3bs2PTQQw+lDTfcsIZ7CdNvpsUTTzxR/fnhhx/OgxiFaCfiWmrYsGF5kBvqVbQB//rXv/Igd+Haa69NH330UXXG6iqrrJIHwl999dWcXQj1Kj7fV155ZfXnjz/+OM+8mGmm1rmbjz32WBo4cOB03kOmhKBtCa288sr54itGRcIjjzyS1lhjjVrvFtTEaqutlo+BYvQ8RscHDBjQZkNTBHKhHsWI+BJLLJE7HCGy0KOOc9NMwwhcxbEQGYaRZaLmOfVq2WWXTcOHD88zL4og1eqrr15df+ONN6ZNNtlEuRwaQnz2i2ulCNBGO1AcD9E5jxkaDz74YA5e/fGPf0yjR4+u8R5Dx4iSUNGXLo6HESNG5MzzqOMcIpgbAxgR2L3tttvSmWeemTNxoR4VpXAiKTA8/vjjeUZqyySnyE6PewBEP4PyEbQtoUhJj4Ylau289957eSSw6RQPaLSOeUzxi6ypyCJZbrnlWjU0sTwyqnbddVf1O6lr0QkvZl5Eh6RpkCr0798/Hwcx7e/JJ59slqUO9dYxj4yQOB4ikySyCldcccW8LrLNI6sqvqJkTlGnLTLRoV475pFhGJm0Ue+/V69e1QG9ojRCfEUJnZiVcc8999R6l6HDRCZtDF7HjKSWA3rRh4hB8P322y/ttddeuV9x7733ejdoiL5DDOhFQlRLsT6SotwHo5wEbUueXRhfbR1Y0Cii8VhppZVyI9M0c6QQx0jU4ImbzLgpH/UubpoRnZAomxMZhk0H9CKTpBCd9+7du+dRc6jnjnkMTrQ1oNetW7ecURJfxSyNGAiHRug7tLxWairqemobqGdROi2yy2NmUgzoNZ2hF6Wj4j4AhSgjFW0E1Ku4PoqB60gI7NmzZ7MZeiEGtmOWt9II5eVGZCUVN1mK8ghxAMWoeFNx0BUXW9EQRcdcJi713jH/85//nC/AmtbojM74f/7zn7TZZpvlG/gVF2PRIEE9d8yvvvrqtPHGGzdbHjWqFllkkdwZiXYipgAW0wGhXjvmCyywQLr99tvTvvvu22yGRnwVYjr4N7/5zXyjJqhXyy+/fLrjjjvyVNimU1xjsCKmiEfZhHgc983Ycssta7qvMD2ulS655JJcKqGodR5WXXXVdMEFF+T+cywfPHhw7kdAvYpSaTETKcrj7Ljjjq3WR7wprqVaBnMpD0HbEuvXr18OzracCh51DOMGHLE+pgDGXZEFbalncWEVwdiWmSMxMhhBqcg6LMRouqAt9WyZZZbJgxUtaztvv/32Oes8BvPiwmufffaRfU5DHA8xyP1VnY24RorMW6j3jvmiiy6aO99NjRw5Mg9yx81dY6Bjhx12MKBH3YtBugjKtuw7ROmQnXbaqTpdfOutt05LL710jfYSpt+1UpSLaitmFDP31l57bW9FiXWqFLedpjSiBlvUo4rR8j322KPZFA5oNJEdEtNaYwrs/vvvX+vdgZqKtiGOhRjIaJlpC41k/PjxecAusgY33XTTHKyCRhUzK6J9iFq1MUOvZcIHNJKo7RxTwaOOeQxSQCOLJL+o7RyzMSLznBmPmrYlFDdcio5IdMgFbGl0cROyuEP4tttuW+tdgZqLtiEyBtdbb71a7wrUVMy0iE551GATsKXRjRo1Kr3yyivp29/+toAtDS9uwhp1/pU9gJRvyhelN9WsnXHJtAUAAAAAKBGZtgAAAAAAJSJoCwAAAABQIoK2AAAAAAAlImgLAAAAAFAigrYAAAAAACUiaAsAAAAAUCKCtgAAAAAAJSJoCwAAAABQIoK2AAAAAAAlImgLAAAAAFAigrYAAEyzSqWShg0blt5++22v4v+8//776eWXX06fffaZ1wRo6HPhCy+8kCZOnFjrXSmNF198Mb377ru13g1gBtGpElfalNL999+fnnvuubTyyiunFVZYodm6ESNGpNtuuy116tQpbbzxxqlXr14120/oaJ988km644470ujRo9NGG22U+vTp02z9ww8/nIYOHZr69u2b1l9//dSlSxdvCnVr+PDh6c4770zdunVLgwYNSrPOOmur57zxxhvphhtuSGuuuWZaaaWVarKfNIb33nsvrbbaavn8vPfee6eTTz652froqEdAN87bs8wyS6vfHzVqVBo3blxaaKGFpunvT277ITrHI0eOTIsttljq2rVru2w/ghATJkxo9fzFF188P+/qq69Ohx56aH5drrvuurTBBhtMw38HUy4+j3fffXf+vK6zzjr5s9jUf//73/TEE0+kHj165L5DW20HtKdjjjkmnXrqqfn8/thjj6Xu3bu3aj/iczvvvPO2+t0Y8HrrrbfSAgssMMlze1uiTYmvluaee+7Uu3fv6s8ff/xxGjNmTJp//vlzf7q9tj8lfz+uy55//vm0ww47pAsvvHCK/zZMrauuuirHjVraYost0sILL5zbhSFDhlSXf/e73211nFICEbSlXD744IPKJptsUll44YUru+66a2WNNdaonHTSSdX1gwcPrsw555yVTTfdtLLxxhtX5pprrsr9999f032GjvLEE0/kY2HVVVet7L777pXll1++cs899+R1Y8aMqay//vqVtdZaq/K9732v0q9fv7x+5MiR3hDq0tlnn13p3r17ZfPNN6/suOOOldVXX73y/vvvN3vOxIkTKxtssEFl1llnrfzmN7+p2b7SGC699NJ8jh4/fnyrdeedd15lvvnmq8w777yV+eefv3LuuedW13344YeVrbbaKn9Oe/ToUVl22WUrTz311FT97a/afmHcuHGV5ZZbLhIUKo899li7bX+11VbLbU7x1bt370qXLl0qw4cPb7aNPffcs7LPPvtM1d+FqTVs2LDKgAED8nG022675cdxbBYOOuigSs+ePXO/YuWVV64ss8wylXfeeccLTYfq1atX5aqrrmq1/JVXXqlsuOGG+fy/4IIL5rbgvffey+s+//zzysEHH1zp1q1bpW/fvrmfe84550zx3zz99NObnZvjK87/J5xwQl4f7Uz8vbiW6tOnTz7HX3TRRe22/cmtLzzyyCOVTp06VT755JMp/tswtX79619X9ttvv+rXoEGD8ufuhRdeyOtvu+22vHynnXbKn9M4NikfQdsS2nvvvSvrrrtu5aOPPmoWqC3079+/cvjhh1d/joZt4MCB030/oaN99tlnlcUXX7xyzDHHNBvUePzxx/PjUaNGVR5++OFmz19qqaUqv/zlL7051J24wJ955pmrgxZF56Po6BROO+20yne/+93caRe0paP95S9/yYPLLUVHPQaY77zzzvzzxx9/XDn11FObXbusuOKKefBtwoQJ+donrm+m1OS2X/jxj3+cA6dTG7Sd0u0XIhj2rW99q9Xy4447rrL99ttP8d+FaREDdbvssksOeBXXQ0VCx1133VWZaaaZKs8991x1YC+SQwwm0NHic/fQQw81Wxbn0iWXXLJywAEHVD799NO87MYbb8zXOEXQMwbBXn311fxznIPj2ufRRx+dpn249957K507d65uLwLA8fei3SkG52LA7cUXX2yX7U/p+kgwiXbJ4AnTU1xrRdJfS0OHDhW0LTFB25KJQO0ss8ySG5ObbrqpcvHFF1eeffbZ6voY/YgTfNNslOiExLI33nijRnsNHeO6667LI+2RuRQZI9GJHjFixFf+TmQeHn/88d4S6k6MhEd2SHQsLrjggsott9ySO+ZNRXux6KKL5gENQVumhzPOOKOyzjrrtFoe2Xw///nPcwf99ddfr3aQC/PMM0/l/PPPr/4cz4lrmSntmE9u+yEGOGL2RXSWpzZoOyXbb9r57tq1a752aykGEdsK5kJ7KTrbTz/9dOXqq6+uXHbZZZXXXnutuv7MM8/MA+BNxQy+yCCHjhIDCJHR1/K8G0HSmLkQGaZxbh07dmyz9XGdEwHdpmJG3aGHHjpN+xGz9LbYYotJro/9iKBqW+fv9tj+pNaPHj06H7fxGsD0EDPzZp999soVV1zRap2gbbm5EVnJRA3bqOHzm9/8JteFu/baa9Mqq6ySfw6vvvpq/r7oootWf6d4/Nprr9Vor6FjRJ2dovZa1OT505/+lJZeeul01113NXterDvzzDPTzjvvnOteHXTQQd4S6vJ4iHq2UYfq1ltvTYccckhuH6ImW4i6cHvssUf63e9+l3r27Fnr3aUBbi7zwAMPpMsuu6xV3eSoQx71C6OO7CKLLJJrK8dnsqjdF5/jqGW4/PLLV38nah5GHbWoTz45k9t++Oijj9Jee+2Vzj333KmuYzsl22/q/PPPz3URN91001br4p4EgwcPTjfffHOuzwgd0TbMPPPMad99903nnXdeuuSSS9Kyyy6bv4cFF1ww3yQwjrmmvxOf7zhOoL0988wz6fe//32aY445WtVWvu+++3J98bi2j3Nr1LPddttt0wcffJDXzz777NXrmkLUBo9tTq34vX/+859pv/32m+Rzov541HeO2uztvf2vWj/XXHPlmqJ/+MMf8vHoRm10tL///e/5Outb3/qWF3sGI2hbMuPHj8/fV1xxxXyjsUsvvTRdccUV6Wc/+1m+sUBxQm96o6WZZpopf2/rhhgwox8P0dH49a9/nQMDt9xySw5KRbCq5WBHdLDjxjBxc6axY8fWbJ+hI4+Hl156KXd44sIrbijz+eef5yBtOOmkk3Lga/vtt/cm0OFuv/32tNVWW6VXXnklHX744c3WxTk4ZnPFAFsEYd9888109tln5xuVxfk6bjwWokPfVHQm4uYwkzO57Ycjjjgi718EBabWlGy/EM+Ldfvss0/q3Ln1ZXUMsgwYMCBtt9126bTTTpvqfYEpaRviK879kexxzTXX5PbggAMOyH2DLbfcMg+QRJDslFNOyYMZ9957b/XzC+1tp512SkcffXQ69thj05xzztlsXQRn4/MX1/Jxbo0bp8Z59bjjjsvrd99999z3/ctf/pIeeeSR9JOf/CQnLRXtxtS44IIL8oBbHANtiRsZ77///umvf/3rNN3Ue3Lb/6r1cfOzE088MZ1xxhlp6623NoBCh4vPeZz/Y5CPGYugbclEpkb45je/WV220UYb5YuuZ599Nt+9OEQgq1BkbhS/C/V+PMRoe9OORlwYRnZJXNxFp/9HP/pRTfYXOvp4iIzGeeaZJ/8cF13rrrtuevrpp9OHH36YTjjhhJzVFx2d+Hr33XdzJuTll1/ujaHdfec738kZs6uvvno6/vjjm62LTnoMLsddiIus77hLdmRURdZp3EU7xGe0qfi5+Hx/lcltPwY2otO/22675WunF198MT8nOv6RXfh1t99UZL3HTKfoCLUlBt9jHyI4UQywwPS4VorgWATEoq2Iz20EcaPPEO1IBMLmm2++VgMn0B4ic/TGG2/MQdumGd4hzvHxmY1zaohzbJxr77zzzupAV1y3/Otf/8oDZRHc/Pa3v50WWGCBqd6PYkCtabJTIdqJmB0RGcHRVkyLr9r+5NZHP+bggw/O12vRNkX/BTrKkCFDcn8hPo/MeARtSyaypGL691NPPVVdFgdYUQZhmWWWyY1WTOUoxOOYXrHkkkvWZJ+ho0SnIy7WWh4PMV01lkdnpOV0orgYjKmtUG8iS+r555+vzsgojodoGyLDb88998wd8scffzx/RVZKDPC1zAyE9hKfuw022CBn2zYVZWoGDhyYp4YW4nMbGawREI1poXGtc/fdd1fXP/jgg7k8VDFFNTr6L7/8cpt/d3LbHzVqVG4Ldtlll9zZj2MjREZwlDL4uttvKjrc8Td69+7d5rYioBtlTOJ/ho6wxhpr5OBry2ul+BwXga44JqKzHgGqCN7+7W9/y4Ey6CgbbrhhvkZ//fXXW31eoyxH02uZONcW59ZIVIpz6r///e88i+7nP/95uuOOO9Lmm29eDXbGQNjkSnvE78QMvAj8tjVTJILDf/zjH9MPfvCDZuvaY/tTsj5KDEUZiKaDLdBR4lpls802y31oZjxfzKunVOKCKqaVxIk8sjriIIsTfhGUjUyNyOgYMWJEbgyjFs5FF12Ug1hQT5ZYYol06KGH5mml0cmITvaf//znnFUbIrM2RuoHDRqUa98+9NBDeVrg9ddfX+tdh3YX7UDU54zPe0z7jiyR6BBE6ZCoARdtRVP3339/7vgcddRR3g06TNQCjDIdLR155JH5WiWy+vr165fOOuusnGFb1H2NTL+YFRHn+Qh4HnbYYfnaJwaviwylCCzFZ7wtX7X96PzHdNPCO++8kzO7YpC7qL/7dbZfiEGRmI5+0003TfL1iddmamvqwtSYbbbZ8r0vop5/BJuiPxB1/n/xi1/kwG2IKeDRj4js2rgPQIjZGdBRIsM7BvZatg9x3R6fzajBHJ/ZGFiOadtx34oQg4BRFvDAAw/Mg89RIm2ppZaqZsNGMDVqNsd5t6064oW4Jop2oGWGbvxe1NCNcgwxOBfHTIg2IgbXvu72p3R98bpoH+ho0X+O2UdtzbyLZI+4jomZU+Hiiy/O2e9xjER7QTkI2pZQ1L2JFPY4sGLkMWrdbLPNNtX1u+66a86siuBUXJhFzbUYtYR6FDUAY7Q+pk3FxVRM8Ss63RGQigurK6+8Mjc6a621Vh70UCqEehT1mqMOXNRIi0DTOuuskzs6k7rpWHSMokMCHSk6nE0zpgpRXzMylmKgLTKK4rwdmbVFNlUERGN9BJeijm1kgBQ1DYtMweg0TMrktt9U1P6PwGsEmNtz+5EJFiV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ggw/yz7HyYvbZZ08777xzGjx4cG4P3bt3r/EeQ8eIJI6mY4VoB9Eeol2E5ZZbrtovRKLHwIEDU7du3XwcJSNoW0Ix6xdZIY8++mgelNx8881pySWXrPVuQU0MGDAg3XTTTbktRJt47bXX0vzzz5+fazoTGAGteE2/fv18UtSlGHRH/3DFFVfkk61//vOfOcu8GHxHSYSY4LjyyitzFsnaa69tOTh1q2/fvunzzz/Pg/MYlFx99dXNzpViAi8ej4luqHeRJRWT3C+//HK+RWAqHmuaXXjdddflzPMimAX1KvqC6BNicjsm7+Kcac4556xO8C2xxBLptttuy8GrF198sda7Cx2mR48eeZKiKIMQY4iFF164VWA22kis4o7SapSPoG0Jde3aNW2//fbp7rvvTpdddlnOmIrGBo0oanJuvvnmuS1Em9huu+1yG2kqMq3i5Gz55ZdP8803X832FTpafMfnmWeeHJSNE6w111yz2fMxKImlTvGaOPmKoBbUq+gbXnjhhXTxxRfnjNpYbRGKYG6cP0EjiGzyGDvEwDxucb8ogRATe1tssUVaYIEF0owzzpguueSSfC0AqFfxXY9VRxdddFGexIjVeIUolROZ6DERHsvBY/wQmepQr9ZZZ52cRXveeeflxKdlllmm1Wsi6SPGEHPNNVdN9pHJE7Qtqbg4QGRQxcBjkUUWqfXuQM1PviJjKjqalnV2InAVmYXxeFxYA+pdZIiMGDEiB3C7dOnS7LnINI9Z8q233joP2A3MqWfxHY/s81hl0XQQMmTIkDxAiVUaV111VS4Tctddd+WVGlCvYrAdQdlYddF01VFRGiGWvcYFl+L2xBNP1HRfoaNFpvk777yTll566dwuCrPOOmtaaqmlciArykp94xvfaFZKBOpNjBUWW2yxPHaYVInNOG+KciGUk6BtScXFlSKbMOqMtLziKzSSSqWSZ8HXWmutXMvzqaeeqj4Xyzz+/ve/50mOprPoUK8++eSTHIjaYYcdcibhRx99VH0uskmaLoWNQFUsi4J6FZMSsdQ7JuwiOFvUt43J7igPUlxcIwbskYUbfQXUqyinFt/9WJ0XK5MmJc6l1HmmnsU5UCR0xAR2TFDERccKCy20ULN6/x9//LEL81HXhg8fnkvmxHUvrrnmmlYXKR45cmRuI8pJldcMtd4BWotGEw1rn332yYXRL7jggvT444+nFVdcsXohpqKYelyUJpaPb7TRRt5K6tK9996bJzAiaBuZVBdeeGEugRBLOKIeVdQtjMFHDNhDTHSoAU09ioBUDEIiGBUnVjEoidpUe+21V24jzz77bPrPf/6Tl/tFPxJBqiiVAPUoJixiUjsuRhkZhvGdj/OjDTbYIM0999z5Vogs28gyibYB9SgyBYcNG5b23nvvPKF9zjnn5OBU3KJm55NPPplf9/777+fJvz333LPWuwwdJsbHMWEX2eUxTo4xwr777ptLhUQ2YSwTj/F1ZKFH9uF3v/tdnwZ1KQK0MVbYaqut8nlQrEyK+uZRQqfw2GOP5TF2UVKH8ulSiTS2Tipq0sQShxAzZrEcqB5EECqyo4oBR5xcxWAklnKEOPmKpeKFCFjFxZrqRb1+rh2tHt+3ODxFnanoZIoru7711ls5eBWlEmKAUkxgFKKWZ9PBemdWj5/p9FKP7130BfGdj6V+hQjUxiRGkUH47rvv5hOyKK9TL+2gnj/T6aFe37emfUExMHn++efzhEbLuueRkRuvq5e/vZ4/145Wr+9bfPejJEJxDYzoByKDMCbu4n60l1giG397lJyKYFW9qNfPdHqox/cuSgvGMT+CUMXFlmIlUpwnxQUsQ0xsxEW/Q7SH4oKu9aAeP9PpoV7ft5ioi0zaGEuHOG+KsXUkOBUrLiK2FG0jJjjqzeg6+VwFbSmdemlc05v3rf74TL13aA+OI+gf9Ks4V3KeibGDMReNOZZW0xYAAAAAoEQEbQEAAAAASkTQFgAAAACgRARtAQAAAABKRNAWAAAAAKBEBG0BAAAAAEpE0BYAAAAAoEQEbQEAAAAASkTQFgAAAACgRARtAQAAAABKRNAWAAAAAKBEBG0BAAAAAEpkhlrvAAAAndf999+f7r333rTYYoulbbfdtta7UwqPP/54uuGGG9JSSy2Vtt5669StW7da7xLAdPXee++lq6++Og0fPjwdccQRaZZZZvEJpJR+9atfpdlmmy1961vfSvPPP7/3BJgsQduSevnll9Pvfve79Nxzz6WVVlop/fSnP009e/asPn/hhRfmTrBLly5p++23T7vvvntN9xc60m233ZYuuuii9OGHH6Ztttkmfe9736s+98ADD+TnXn/99bTkkkum73//+zlwAPXoiy++SH/5y1/STTfdlLp3754OPfTQtPrqq7d63XXXXZdOO+20tN9++6Vdd921JvtKY3jqqafSN77xjXxcXnTRRVs9f8stt6THHnssLb744vn43bXrV4u83nrrrXwuM2bMmLThhhumQYMGTfXvn9z2C9dff316+OGH0wEHHJDmmWeedtl+DLo//fTTVq+PPqhv3775/siRI9OBBx6Yhg0bltsqdKQhQ4akP/3pT/n7tv7666fDDjsszTDDl0O9Dz74IJ1++unpiSeeSL17985tYe211/aB0KF23HHHNHr06LTxxhu3ei7O2+PYHOc12223Xerfv3/1uegTrrnmmvyamPiK4ObEju2TGjPcddddrR5fddVV0+abb57vv/POO+nGG29M77//fho4cGD65je/2ea/qS3bn9LfF49F33fmmWem559/vs2/G6bW/vvvn+NJLf3617/O39krrrgi/eEPf6g+ftlll031eRIdT3mEEorBQQRqx48fnw466KA055xzph/84AfNGtmPf/zjnM2y1VZb5efOOOOMmu4zdJToSGJiYvnll8+D34ceeihPWhQdy49+9KO04oor5rby7rvvppVXXjm9+uqrPhDqzoQJE3LG3tlnn52P/zEYOuqoo9Lbb7/dKrMlBusxEIhBA3SkRx99NC233HLpnHPOyQPTQgQ0N9tssxwciiBSDFCbTiBE8GiZZZbJQdEXX3wxB37PPffcNv/eKW2/ENved9990wknnJCzvdp7+4W77747/f73v0+zzjpr/jn6pThf22uvvXLAGDpSTNSts846qV+/fvl86KOPPkonnnhiNQAWk3v//e9/8wB+hRVWSJtuumm68847fSh0qEceeST93//9X/4uNs2yveSSS9Kyyy6bg59xnrLFFlukZ599Nj8Xx+l4LiYg4nzm6KOPzs/HOdC0+Oyzz/Lxf8SIEfnn//f//l9ac8010+23357eeOONnPgU51bttf0p/X3h2GOPTRdccEF64YUXcluFjhLJG8cff3z1FoHaiDXF+VeIviEej4n36BMmNhlNCVQ6sVGjRlXiT4hb3K8Xq666auXwww9v9tjo0aPzv59//nmld+/elQsuuKD63Lnnnlvp06dPZdy4cZV6UK+fa0erx/ft7bffrsw888yVm2++eaLtYeTIkc0enzBhQmXBBRes/O53v6vUg3r8TKeXenzvLr744krfvn0rH330UfWxOO5/9tlnzV63ww47VM4666zKwIEDK6ecckqlXtTjZ1oP79vZZ59dWW211Vo9fvTRR1eWX375Zr/zqaeeqt7feOONK7vttlv15ziv6dWrV/X4PiVT2n4YP358Za211qqcc845+e8fMmRIm/+utmy/5bnbD3/4w1aPH3fccZXtt9++0t60B+9bIfqAeeaZJx/3myra0uWXX57b1pgxY6rPHXTQQZX111+/Ug+0hfK+d926das8/PDDzR575ZVX8rn99ddfX30szueHDRuW7x9yyCHN+pQ454lx7qWXXjrN504xdi7aw6OPPtqsn3nxxRfz33/PPfe0y/an9PcV3n333fx7Y6zTnrQH79vkrLfeepUDDjig1eNDhw7N38f4/taTUXUydpBpWzKRMRWZhLFkKbIzYjnIL3/5ywiu5+efeeaZvNxuo402qv6fuB/LOyyvoN7E0qWo+RRLoiKzcOedd05//etfU48ePfLzs88+e7PXjx07NreFueeeu0Z7DB0nlgpuueWW6bzzzssZgPvss0/OVpxpppmqr7n00ktzxnlkpcP0EMuui2NyU+eff3465JBD8nH8N7/5Ta7vWmR2fP755znLaZdddqm+Po7vsYz2vvvua9Pvndz2C1EiZOGFF86rkqZWW7bftH5tnLtFRktL8d7EewQd5cEHH8zZifH9/Pa3v50z3qPEWtE3RJ/Qp0+fXFKnsMACC+Ra1NOaXQhT8vHHH+dVoy37h8hCjZIHUcosjq1xrI3svqJ8QCzlXm211aqvj3FAfLfjGDwtImM3smmL/Rg8eHCzfYpyIVFuMPa1PbY/pb+vULRH/QPTS7StO+64I6+4oHMRtC2ZWKYRjjzyyLx0I1LVox5OLGOKwG2ceIW55pqr+n+K+8VzUE/tIQKxP/vZz9Iee+yRa2JFOYRiyV9LBx98cK476EI41Gt7iMDt0KFDc93MqDkVy5pi+WEx6Rd9RwR1YwACHSkClYcffngesDatMx5iuWcEkaK8TdQcj/uxZDuWoMa5TPw8bty4ZhdgiQFsBJaK86DJmdL2w9NPP53OOuus9Nvf/naq/7a2bL+pKFkSNUQHDBjQ6rkIGL/00kt5Iv6qq66a6n2BKYk2E7Vro1xaJHvstNNOuVRHTOyFCIDFEu0o4VGUS4g6hhFI+uSTT7zBtLtIOIpJ5qhVHgHMpqJMwKhRo/LkQhxbo/RMvCYmoUOcxzctKRPf0TjvmZZyT1FzPSYCo8zNpBx33HE5KLzGGmu0y/an9PcV4lo1EeyN2zHHHGNZOh0uzteiP4jyTXQuLkRWMjPOOGP+N7I7ogZbiNpTMVv35JNPpplnnjk/FoGsYgY9Tr5C8RzUU3uIE58YNMdFxoraUXEyGPWgCjGIjjYTWSNxgYCmmYdQT+0hssijdmgEZaNGWtSl+vOf/5xrOUefEUG0GPDA9BAZs3GLTKWmioylOG7/4x//yPfju7nIIoukW2+9tXo8bzm5EMfytkw4TGn76623Xtpzzz3zhZciEDw1tWzbsv0IRDQNKESGe1wgcGKixm30SZF1NrGAL7RH3xAXNjrllFOqF0KK62FEwkdMPET/8Itf/CJtsskmOTgVFwCMGtLRfzTNvoX2EhnccWyMyeWWFxCL42sEYOOi28XEXdToj+BpTEzH5HPU3Yzj+CqrrJL+/e9/54s7duvWbar3IybU4rs+qVUSkQQSQdXIPizG4F93+1P6+5qK/inGOdOa5QttFZN0F198cT4vovMRtC2ZCM5Gp9R0CcV8881XXT5RzFZGKYToyIr7McgxUKfeFAP7lu3hww8/rA7u40QnglWRbRgF1OMiHFCv7SGCP02DWtEeom+IsiCxKiMCQ9dee231AkwR4I3lUHHBC2hPkakRmayxJDQGrpFVVZhjjjlysDIG3oUYvM4777z5exkXTIrMwMgQjItMFpPR8V1umn07KVPafpSReu2113IWVNxiUFxkmUT208SuZD41228atI2L2sR7MKkVHpFd26tXr3TllVdO8e+C9jxXivOkOF+K73Jk8kXZnPj+LrjggnlFRvQNJrnpCBGg/O53v5vL07zyyit5wqsQ3784ljY91seYNgJKxfORrfrPf/4zT7jFdzUu9BUlPaZGlNuJ4/Mf//jHiT4fbSKej4uFxfh7ak1q+1P6+wox4RkZ8fH7Y3UtdKTLL788T6ZEKSo6H+URSibq9kStwsjaKGbdokOIE/6BAwfmTiAGO3ElzjgZi9sZZ5yRNthggzwLCfUkBtYxeI46tiE6m7/97W+55nMErmJ5bVzNO66IHLPkArbUs6hVGHUzi/rlcVXlm266KWd5RN8RNUIjm6q4QmxkuERwKZZ1Q0eJwXjLmnxxfI6svvi+FoYNG5ZLeEQJgQgUxXlLHM+bDihiuWgxeL3nnntyXc6JmdL2I4gV5XIm5+tsv6nIdI/yEJPK0ooAcgQuoKPE+GDppZeunisVY4eFFlqoGuiKOptxPhUTEdF3nHnmmbncFHSUCF5Glm3L/iEywCPbO46phSiHUBxbY6IhVtXFaonIuo3+IrJtIwhcBDvjHCcmICYnxtLxf3fYYYdmj8fY+dBDD82rKKJkSMuA7dfd/pT+vkJkIsdYX//A9BCT1lFq0OqKTqrSidXL1eBaeuONNyorrLBCZcEFF8xX/44rZl599dXV55977rnKoosuWll44YUrCy20UGWJJZbIV76sF/X6uXa0en3fbrzxxsqcc86Z20R83+Nq3i+88EJ+7swzz8x/7+DBgyvrrrtu9fbHP/6xUg/q9TOdHur1vYsr2s8666yVlVdeOV+teJdddqmMGzduoq+N/uOUU06p1It6/Uw7+/t29tlnN7vSd+H555+vzD333JUtt9yy8qMf/Sgfv3feeefq848//nhlttlmq2yzzTaV/fffv9KzZ8/KOeecU33++OOPz8f2SZnS9puKq3PH3z9kyJB23f59991X6dq1a+Xll1+e5HaOO+64yg477FBpb9qD962p+G7HuGHJJZesDBgwIN+///77q8//8pe/rMw///z5XKpXr16Vk08+uVIvtIXyvnfdunWrPPzww60e33333fMxNY6tcYzt27dv5ZlnnsnPjRgxojJo0KDKQQcdVNlrr73y9/VXv/pV9f++9957eX/j+Ds5K620UuXHP/5xq8dPOOGE/P+j34njc3F79NFH22X7U/r7Cu+++27+PcOHD6+0J+3B+9bSE088kb9rTz/99ET7jhg7r7LKKvk1cT4XP0/stZ3RqDoZOyiPUEKxnCIu8BFL+qJGVZREaDorEhkkkWkVBc0jGyRq3k5LnR/oDGLGOmarI5t29tlnT0sssUS1PlYsR40Mk5amdgkVdBYnnXRSvthM1EqLLKpYfTEpsaQwauBCR4os7yjL0VIcq5955plcFiAu7HXuueemjTbaqPp8HLvj4jJRPiBq80fG06BBg5plwk4uE3BK228qlofHct3IPm/P7cd+R4mIpkt/J5ZpG+8RdHS5krjgXVz/IrL/IquvafZ3XAdgv/32y0vVo/5mrOCDWvUPUSrg5ptvTkOGDEnLLrtsvnZF1GEOcd7yn//8J2fCRsbtT37yk2YXM4tjd1w0bHIXDouSOFGyp+VFMkOMm6M/mJSvu/0p/X1N+4agf6CjRe3ke++9d6K1nSPTOzLLW2pLqSqmny4RuU2dVNSSiRPx4uAZy+ro/Hyu3je0BccR9A2do0+NQFEMqHfbbbe01VZb5Zqx7SGWb8cS1pYXsWkvHb39mHyP5ernn39+Ou2009Lee+/drtt3ruR9Q1so+3Ek+oRIvIgL5P3sZz9Ls8wyy9feZpSCilIfMVHRETp6+yEuqBwlH+I9j8Bue9I3eN+ov/Yg0xYAgGkS9QAfeOCBXFe86UXyvq7DDjusQz+Rjt5+kd0SGVYRuABoNDFxFasVosZre1l//fXbbVu12H6ILPi4JsekLmAJ0JSgLQAA02yllVbKN74SWVodmakFUHa9e/du91UG9eCoo46q9S4AnUjHrAkDAAAAAGCaCNoCAAAAAJSIoC0AAAAAQIkI2gIAAAAAlEjdXIhs9OjRtd4F2onP0nuIttCeHFPqg8/Re4j24JiCvkEfi3Ml55s00tihboK2/fr1q/UuQGloD6A9gL4BnCuBsQMYR9N5KY8AAAAAAFAiXSqVSiV1UrHrY8aMqfVu0IF69OiRunTp4j1uA+2hvmkLU0d7qG/aQ9tpC/VPe2g77aG+aQtTR3uob9pD22kL9a9HJ44rdeqgLQAAAABAvVEeAQAAAACgRARtO4nxE8ank+8+OV099Opa7wrU3ogRKf3oRykNHVrrPYGau+f1e9LRtx6dxo4bW+tdgZr786N/Tuc8ek6tdwNqLvqE6Buij4CGF2OGGDvEGAIaXMSUIrYUMSbKT3mETmLPq/dMFz95cb5/2563pfUXXr/WuwS1079/Sm+9lVL37imNHJnSTDP5NGhIb338Vpr/jPlTJVXS6v1XT/fvc3+tdwlq5sz7z0yH//vwfP+Mjc9Ih61xmE+DhrX6eaunB998MHXt0jW9cdgbab7Z5qv1LkFtfP55Sr17pzR27JdjiGHDfBI0rNtfvT1tcNEG+f6eA/dMF25zYa13iSmQadsJjPp8VPrHM/+o/nz87cfXdH+gpu6448uAbYiTr4u/nMyARnTS3SflgG2IwfkrH75S612CmphQmZBOf+D06s9xPx6DRhR9wUNvPpTvRzuIvgIaVowVYswQ3nzzy7EENKjjbj+uev/vT/89x5ooN0HbTuCsh85KY7/4atnrXa/flZ4Y/kRN9wlq5vgWkxYnnfTlDDo0mHdHv5suePyC6s8RvI2lTtCIrnn2mjTs46+yp+J+PAaNKPqCYkIvRF8RfQY0nBgjxFhhcmMJaBCPD3883f363dWfI8YUsSbKTdC25GLm4zf3/abV47+46xc12R+oqZgZv/PO5o+9+qpsWxrSafed1mxCL1z4xIWybWk4kUl4wp0ntHo8HpNtSyNm2UZf0FT0FdFnQENm2cZYoakYS8i2pQH94s7WMaSINcm2LTdB25KLmY/3x77f6vGrhl4l25bGM6mZcdm2NJjImPrDw39o9fgXE76QbUvDiYzaJ0c82erxeEy2LY2YZRt9QUvRZ8i2JTV6lm1Bti0NmGV79bOtL2ofsSbZtuUmaNtJsmy7pC6tnpdtS8Nm2RYXHuv6v0OYbFsaTGRMjRk3ptljM3adMf8bGVavjmyRVQJ1qlKpTDTLthDPxWugEcSxv8iyLfqEQvQZsm1p2CzbYsxQjCFk29JgJpZlW8SYZNuWm6BtiQ19d2g1y3bpuZauPt6ne5/8752vtlgmDvXsrru+ut+v35f/zjjjxJ+HOhe1zcPM3WauPrbYnIvlfyPD6v437q/ZvsH09NFnH1WzbBfpvUj18eJ+PBevgUZw3xv3VbNsiz6haV9R9B3QEJqWVCvGDMUYIhg70EDueu2uZrGkpjGmiDlF7IlyErQtsRX6rZC+vdy300aLbpTWX3j96uPHrnNsWmneldJP1/5pTfcPpqtdd01pzTVTOvjglHr3/mrW/OSTU1pppZT2398HQsM4bLXD0qB5BqXTNv6qRuGSfZZMOy6zY9p4sY3TJotvUtP9g+ll9plnz+1hjfnXSN9d8bvVx+N+PBbPxWugEWy6+Ka5D4i+IPqEQvQV0WdEe4CGccABX44RYqxQZNrGGCLGEjGm+M53ar2HMN0ctfZROYYUsaRCxJgi1hQxp4HzDPRplFSXijVjncJRtxyVTr331Hz/jj3vSOsuvG6tdwlqZ+DAlJ58MqXu3VMa03yJODSStz55K/X/v/75/nZLb5eu3OnKWu8S1Mx5j52X9v3Xvvn+uVudm/YZvI9Pg4a1/d+3z9fACG/+8M00X6/5ar1LUDs9eqQ0dmxKK6yQ0hNP+CRoWLFae72L1sv3j1zryPSrDX9V611iCmTaAgAAAACUiKAtAAAAAECJCNoCAAAAAJSIoC0AAAAAQIkI2gIAAAAAlIigLQAAAABAiQjaAgAAAACUiKAtAAAAAECJCNoCAAAAAJSIoC0AAAAAQIkI2gIAAAAAlIigLQAAAABAiQjaAgAAAACUiKAtAAAAAECJCNoCAAAAAJSIoC0AAAAAQIkI2gIAAAAAlIigLQAAAABAiQjaAgAAAACUiKAtAAAAAECJCNoCAAAAAJSIoC0AAAAAQIkI2gIAAAAAlIigLQAAAABAiQjaAgAAAACUiKAtAAAAAECJCNoCAAAAAJSIoC0AAAAAQIkI2gIAAAAAlIigLQAAAABAiQjaAgAAAACUiKAtAAAAAECJCNoCAAAAAJSIoC0AAAAAQIkI2gIAAAAAlIigLQAAAABAiQjaAgAAAACUiKAtAAAAAECJCNoCAAAAAJSIoC0AAAAAQIkI2gIAAAAAlIigLQAAAABAiQjaAgAAAACUiKAtAAAAAECJCNoCAAAAAJSIoC0AAAAAQIkI2gIAAAAAlIigLQAAAABAiQjaAgAAAACUiKAtAAAAAECJCNoCAAAAAJSIoC0AAAAAQIkI2gIAAAAAlIigLQAAAABAiQjaAgAAAACUiKAtAAAAAECJCNoCAAAAAJSIoC0AAAAAQIkI2gIAAAAAlIigLQAAAABAiQjaAgAAAACUiKAtAAAAAECJCNoCAAAAAJSIoC0AAAAAQIkI2gIAAAAAlIigLQAAAABAiQjaAgAAAACUiKAtAAAAAECJCNoCAAAAAJSIoC0AAAAAQIkI2gIAAAAAlIigLQAAAABAiQjaAgAAAACUiKAtAAAAAECJCNoCAAAAAJSIoC0AAAAAQIkI2gIAAAAAlIigLQAAAABAiQjaAgAAAACUiKAtAAAAAECJCNoCAAAAAJSIoC0AAAAAQIkI2gIAAAAAlIigLQAAAABAiQjaAgAAAACUiKAtAAAAAECJCNoCAAAAAJSIoC0AAAAAQIkI2gIAAAAAlIigLQAAAABAiQjaAgAAAACUiKAtAAAAAECJCNoCAAAAAJSIoC0AAAAAQIkI2gIAAAAAlIigbYlVKpX0m3t/k4665aj0xYQvqo+//cnbab9/7ZdufOHGmu4fTFcjR6Z0yCEpnX9+88evuy6l/fZL6bXXfCA0jEfeeiTtc+0+6YnhTzTrM351z6/S0bcencaNH1fT/YPp6aLHL0rfv+H7afTno6uPxf14LJ6DRhHH/ugDoi+IPqEQfUX0GdF3QMN49dUvxwjXX9/88b/85csxxUcf1WrPYLq74YUbcgwpYkmFiDFFrCliTk37DMqlS8WnU1qPvf1YWumclfL9Vfuvmh5686F8f9E5Fk0vf/hymrvn3GnEj0fUeC9hOjnppJSOPfbL+4sumtLLL6c088wpffFFSuPHp/Td76Z0wQU+DhrC2uevne594940xyxzpA8//TA/tuI8K6bHhz+e71++w+Vpp2V3qvFeQsf76NOPUu9Te7dqAyv2WzE9PuLL+yOPHJlmn2V2Hwd17/KnLk/fvvLb+f6geQalIcOH5PtFX7HWAmule753T433EqaTGBtcdFFK3bqlNMMMKX322VdjiHDiiSkdc4yPg4bQ77R+6Z3R71RjSWHV+VZND731ZYzp0f0eTYPnHVzjvWRiZNqW2AKzLZBm7jZzvj/k7S9PukLRyJbss2TN9g2muyWbfN9H/G+yogjYtnwe6lxx/C8CtuG5955r9TzUu1lnmjXN12u+fL8I2Ob7/wvY9u/VP78GGkHTY/+z7z1bvV/0FfoGGsqAAV/+G2OFGDM0HUMEYwcaSHH8L2JJ4bHhj+V/Z5lhlhx7opwEbUtsrp5zpf1X2j/fHzeh9VLXY7/xv6xDaATbbffVydfo/y2BLQK2vXundNBBtds3mM6OXOvI1LVL8y587Bdj879bLLFFzjiERtCta7f007V/Osnn47l4DTSCQfMOSpsvsXmzPqEQfcZRax9Voz2DGjjwwC/HCE3HDMUYYqmlvhxbQIM45huts8qLEpwRc4rYE+UkaFtyR659ZDXbtqnV5189bbzYxjXZJ6iJWNr0859P/Lkf/jCl2S19pXEM6Dsg7br8rhN97rh1j5vu+wO1tM/gfarZtk1Flu3eg/euyT5BrUyqD/jO8t+RaUtjiYDt4YdP/LkYU8TYAhrEJottklbrv1qrxyPLNpJBKC9B25KLQUiRbdvU8esen7p06VKTfYKa2Xnnr7Jtm56QHXporfYIaiZWW7TMto0s21X6r1KzfYJaiAHHxLJt47F4DhpJXAejyLYtRF9x7DpW6NGAYoxQZNsWIst2J3X/aSwROzp+veNbPR6xpnl7zVuTfaJtBG07SbZtty5fzQQuO9eysmxpTBPLtpVlSwNn226z1DbNHpNlSyNn2/ae5auBedyXZUujatkXbLvUtrJsaUwTy7aVZUsDZ9suM9cy1Z9n6DqDLNtOQNC2k2TbrrPQOtWfj1jzCFm2NHa27az/u6hM166ybGloP1vnZ9X7i/ReRJYtDSsyandbfrfqz3Ffli2NnG0bfcLE+gpoOD/4wZdjhhBjCFm2NHC27U/W/En153UWXEeWbSfQpVKpVGq9E0zZB2M+SLtetWsa0GdA+u1mv/WW0djuvjulI49M6fvfT2nXidf1hEZx6j2nputfuD6d/63z0+J9Fq/17kDNjJ8wPu165Zd9wqXbX+oCZDS0F95/Ie197d5pyyW3TD9Z66tBOjSkSy5J6ayzUjr11JS+8Y1a7w3U1A9u/EF67v3n0t+2/1uao/scPo2SE7QFAAAAACgR5REAAAAAAEpkhtSJRWWHMWPG1Ho36EA9evRQv7eNtIf6pi1MHe2hvmkPbact1D/toe20h/qmLUwd7aG+aQ9tpy3Uvx6dOK7UqYO2EbCdtbggEXVp1KhRqWfPnrXejU5Be6hv2sLU0R7qm/bQdtpC/dMe2k57qG/awtTRHuqb9tB22kL9G9WJ40rKIwAAAAAAlEinzrRtasSIEZ02ck5zo0ePTv369fO2fA3aQ33QFtqH9lAftIevT1uoH9rD16c91AdtoX1oD/VBe/j6tIX6MbpO4kp1E7SNgK2gLWgPoH8A50pg7ADG0iCuRGenPAIAAAAAQIkI2gIAAAAAlIigLQAAAABAiQjaAgAAAACUiKAtAAAAAECJCNoCAAAAAJSIoC0AAAAAQInMUOsdYOo9//zzacKECfn+Eksskbp16+ZtpGGNGzcuvfnmm2nmmWdO88wzT+rSpUutdwlq5tNPP01vvfVW6tmzZ+rXr59PgoY3duzY9Nprr6WFFloode/eveHfDxrPF198kV588cVmjy2yyCL5vAka1fvvv59vMaZeeOGF0yyzzFLrXYKaxpUK2kP5CNp2Qk899VT6/PPP03PPPZeOOOKI1KNHj1rvEtTESy+9lK6//vo022yzpY8++ij/u9tuu6UZZ5zRJ0LDefrpp9Mtt9yS5pxzzjwQmWuuudIuu+ySuna1qIbGFX1EDEqib1hwwQVrvTtQk8m8K664Ii2++OLVx+add15BWxrWddddl5555pnUv3//nPw099xzC9rSkP773//mBKgQ8aWY5P7hD39Y692iBUHbEnr99dfzoHvWWWfNP48fPz7PkA8YMCD/vN122+V/TzjhhJruJ3S0SqWSB9tLLrlkNYP2448/zrf5558/zwx+73vfy20l2smf//zn9Oyzz6bll1/eh0Pd+eSTT9LIkSPTAgssUH0ssmpj4q537955AH7QQQflSYvIrDrttNOqwVuoN8OHD8/f+TnmmKP62AsvvJAzRIqJuxiMxGRe3KCexTghJiVmmmmmZqsuFl100fxzZBF++9vfrvFeQsf77LPP8gq84rsf3nvvvTxmiOBsJD1Fezn44IPzqiSoZzEOiDFB09V3EZiNsUGMH7bffvvq4w8++GDuK7SL8pF+U0LRkO69997qz9G5PPbYYzXdJ6iFCNTef//96eWXX64+dscdd6S33367Wh6kmNyImfIYrBQDFqg38R2//PLLqzPiMQD5+9//nic3QmRRRcb50KFD05133plPyGICEOp1IHLTTTc1C+L+5z//qQZsR40alR5++OG0/vrr13AvYfqttHjiiSeqPz/yyCN5EqMQ/UScSw0bNixPckO9ij7gn//8Z57kLlx77bVp9OjR1RWrK620Up4If/XVV3N2IdSr+H5feeWV1Z/HjBmTV17MMEPr3M0hQ4akQYMGTec9pC0EbUto8ODB+eQrZkXCo48+mlZbbbVa7xbUxCqrrJLbQDF7HrPjAwcOnGhHUwRyoR7FjPhiiy2WBxwhstCjjnPTTMMIXEVbiAzDyDJR85x6tfTSS6cRI0bklRdFkGrVVVetPn/DDTekjTbaSLkcGkJ894tzpQjQRj9QtIcYnMcKjYceeigHr/7whz+kDz/8sMZ7DB0jSkLFWLpoD++8807OPI86ziGCuTGBEYHdW2+9Nf3+97/PmbhQj4pSOJEUGB5//PG8IrVlklNkp8c1AGKcQfkI2pZQpKRHxxK1dj744IM8E9h0iQc02sA8lvhF1lRkkSyzzDKtOpp4PDKqdt11V/U7qWsxCC9WXsSApGmQKiy33HK5HcSyvyeffLJZljrU28A8MkKiPUQmSWQVrrDCCvm5yDaPrKq4Rcmcok5bZKJDvQ7MI8MwMmmj3n/fvn2rE3pFaYS4RQmdWJVx991313qXocNEJm1MXseKpJYTejGGiEnw/fffP+299955XHHffff5NGiIsUNM6EVCVEvxfCRFuQ5GOQnaljy7MG4Ta1jQKKLzWHHFFXMn0zRzpBBtJGrwxEVmXJSPehcXzYhBSJTNiQzDphN6kUlSiMF7r1698qw51PPAPCYnJjah171795xRErdilUZMhEMjjB1anis1FXU99Q3UsyidFtnlsTIpJvSartCL0lFxHYBClJGKPgLqVZwfxcR1JAT26dOn2Qq9EBPbscpbaYTyciGykoqLLEV5hGhAMSveVDS64mQrOqIYmMvEpd4H5meffXY+AWtaozMG4//+97/Tpptumi/gV5yMRYcE9Twwv/rqq9OGG27Y7PGoUbXQQgvlwUj0E7EEsFgOCPU6MJ9vvvnSbbfdlvbbb79mKzTiVojl4N/85jfzhZqgXi277LLp9ttvz0thmy5xjcmKWCIeZRPiflw3Y4sttqjpvsL0OFe69NJLc6mEotZ5WHnlldOFF16Yx8/x+D333JPHEVCvolRarESK8jg77bRTq+cj3hTnUi2DuZSHoG2JDRgwIAdnWy4FjzqGcQGOeD6WAMZVkQVtqWdxYhXB2JaZIzEzGEGpyDosxGy6oC31bKmllsqTFS1rO++www456zwm8+LEa99995V9TkO0h5jkntxgI86RIvMW6n1gvvDCC+fBd1PvvvtunuSOi7vGRMeOO+5oQo+6F5N0EZRtOXaI0iE777xzdbn4VlttlZZccska7SVMv3OlKBc1sZhRrNxbc801fRQlJmhbQlGDLepRxVLwPffcs9XzcWENaBSRHRLLWmPpUsvi6HEiNrklgFBvom+I5eAtM0eKuoXrrrtuzfYNpqdx48blCbvIGtxkk00m+9rNN998uu0X1EKsrIj+4ZVXXkmbbbZZs+ciySNu0CiitnMsBY/AbdNSCIVYuRc3aASR5Be1nVdfffWJPm/sUH5q2pZQXHApBiKx9HViHQ00krgIWVwhfLvttqv1rkDNRd8QGYPrrLNOrXcFaipWWsSgPGqwRXYhNLL33nsvB2y32WabViv0oNHERVijzr+yB5DyRfmi9KaatZ2XTNsS6tevX166BKR8EbK4ATIGodCzZ8+J1maDRrT44ovnG5BMbEMTzpU6P5m2AAAAAAAlImgLAAAAAFAigrYAAAAAACUiaAsAAAAAUCKCtgAAAAAAJSJoCwAAAABQIoK2AAAAAAAlImgLAAAAAFAigrYAAAAAACUiaAsAAAAAUCKCtgAATLNKpZKGDRuW3n77be/i/3z00Ufp5ZdfTp9//rn3BGjoY+ELL7yQJkyYUOtdKY0XX3wxvf/++7XeDaCTmKHWO8CkPfDAA+m5555LgwcPTssvv3yz595555106623pi5duqQNN9ww9e3b11tJ3fr000/T7bffnj788MO0wQYbpHnmmafZ84888kgaOnRo6t+/f1p33XVTt27darav0NFGjBiR7rjjjtS9e/e08cYbp1lmmaXVa9544410/fXXp9VXXz2tuOKKPhQ6zAcffJBWWWWVfHzeZ5990q9//etmz8dAPQK6cdyeaaaZWv3/9957L40dOzYtsMAC0/T7p7T9EIPjd999Ny2yyCJp5plnbpftRxBi/PjxrV6/6KKL5tfddttt6Qc/+EF+X/71r3+l9dZbbxr+Omi7+D7edddd+fu61lpr5e9iU//973/TE088kXr37p3HDhPrO6A9HX300en000/Px/chQ4akXr16teo/4ns711xztfq/MeH11ltvpfnmm2+Sx/aJiT4lbi3NMcccqV+/ftWfx4wZk0aOHJnmnXfePJ5ur+235ffvsMMO6fnnn0877rhjuuiii9r8u2FqXXXVVTlu1NLmm2+eFlxwwdwv3HvvvdXHv/Od77Rqp5RApRMbNWpUJf6EuMX9evHxxx9XNtpoo8qCCy5Y2XXXXSurrbZa5dRTT60+f88991Rmm222yiabbFLZcMMNK7PPPnvlgQceqNSLev1cO1q9vm9PPPFEbgsrr7xyZY899qgsu+yylbvvvjs/N3LkyMq6665bWWONNSq77757ZcCAAfn5d999t1IP6vUznR7q9b0755xzKr169apsttlmlZ122qmy6qqrVj766KNmr5kwYUJlvfXWq8wyyyyVU045pWb72t7q9TPt7O/bZZddlo/R48aNa/Xc+eefX5l77rkrc801V2XeeeetnHfeedXnPvnkk8qWW26Zv6e9e/euLL300pWnnnpqqn735LZfGDt2bGWZZZbJf/+QIUPabfurrLJK7nOKW79+/SrdunWrjBgxotk29tprr8q+++5baW/ag/etqWHDhlUGDhyY29Fuu+2W70fbLBx88MGVPn365HHF4MGDK0sttVRl+PDhlXqgLZT3vevbt2/lqquuavX4K6+8Ull//fXz8X/++efPfcEHH3yQn/viiy8qhxxySKV79+6V/v3753Huueee2+bfeeaZZzY7Nsct/r4TTjghPx/9TPy+OJeaZ5558jH+4osvbrftT+n5wqOPPlrp0qVL5dNPP620J+3B+9bUySefXNl///2rt4033jh/71544YX8/K233pof33nnnfP3NNpmPRlVJ2MHQdsS2meffSprr712ZfTo0c0CtYXllluucvjhh1d/jo5t0KBBlXpRL41reqvH9+3zzz+vLLroopWjjz662aTG448/nu+/9957lUceeaTZ65dYYonKL3/5y0o9qMfPdHqpx/cuTvBnnHHG6qRFMfgoBjqFM844o/Kd73wnD9oFbenotvCnP/0pTy63FAP1mGC+44478s9jxoypnH766c3OXVZYYYU8+TZ+/Ph87hPnN201pe0XfvSjH+XA6dQGbdu6/UIEw771rW+1evy4446r7LDDDpX2Vo/HuOmhXt+3mKjbZZddcsCrOB8qEjruvPPOygwzzFB57rnnqhN7kRzSEZMJtVCvn2k9vHfxvXv44YebPRbH0sUXX7xy4IEHVj777LP82A033JDPcYqgZ0yCvfrqq/nnOAbHuc9jjz02Tftw3333Vbp27VrdXgSA4/dFv1NMzsWE24svvtgu22/r85FgEu97e0+eaA/et8mJc61I+mtp6NChgrYlpqZtycRSjYsvvjgvJ7n77rvTpZdemkskxDKn8Oqrr6annnoq7b333tX/873vfS8vOYnlUFBPbr755lwjMZaYXn755enqq6/OpRIGDhyYn+/Tp09aaaWVqq+fccYZ8/KjiS1Zhc7unHPOSZtsskleyhfL6W655Za05JJL5u98IfqL3/72t/kG08Nnn32WZpihdbWtE088MR122GFp1VVXzeU6oizBD3/4w+rzl1xySTr88MPT7LPPnrp27Zp+/vOf5/ObOJ9piyltP9xzzz3ppptuSscdd9xU/11t2X4hlsJeeeWV6YADDmj1XLw36trSkZ599tlcMufYY4/NpTj+/ve/53On1VZbLT//5JNP5mWw0V+EorTaNddc44Ohw8S5eNxa9g+XXXZZGj16dDrjjDNyuae4v9lmm+VygCHObbbbbru00EIL5Z+j7NnKK688zWUE/vSnP6VNN920ur0o4xO/L/qdsOuuu+a67FGuoD2239bni/dF/8D08vHHH6e//e1vEz1XodwEbUsmBtxx8D7llFNyXbhrr702B6Xi5yJoGxZeeOHq/ynuv/baazXaa+gYUWenqL0WNXn++Mc/5kHHnXfe2ex18dzvf//79O1vfzvXvTr44IN9JNRle4gBTtShikHNoYcemvuHqMkWYnC05557pt/85jd5QgM6+uIyDz74YJ5Qa1k3OSbXIvgadWRjoBq1leM7WQy643sctQyXXXbZ6v+JmodRRy3qk0/JlLYfIhAQE9znnXfeVNexbcv2m7rgggvyZEpMqrQU1ySI4HFMQkZ9RuiIviEmrffbb790/vnn54SPpZdeOv8b5p9//hzEjTbX9P/E9zvaCbS3Z555Jv3f//1fmnXWWVvVVr7//vtzffE4t49ja9SzjSBtBJRCz549q+c1hagNHtucWvH//vGPf6T9999/kq+JhJCo7xy12dt7+5N7PiYsYzLld7/7XW6PLtRGR/vrX/+az7O+9a1vebM7GUHbkhk3blz+d4UVVsgXGovZyCuuuCL97Gc/y5m0xQG96YWWipk62YXUY3uIgcbJJ5+cAwP/+c9/clAqglUtJztigB0XhomLM40aNapm+wwd2R5eeumlPOCJE6+4oMwXX3yRg7Th1FNPzYGvuMAFdLS40NaWW26ZXnnllZwx21QcgyNzKSbYIgj75ptv5kzxyHCK43VceCzEgL6pGEzEiqMpmdL2wxFHHJH3L4ICU6st2y/E6+K5fffdt5q51VRMssTqkO233z5nlkFH9A1xi2N/JHtEBm30BwceeGAeG2yxxRZ5giSCZKeddlqezLjvvvuq319obzvvvHP66U9/mo455pg022yzNXsugrPx/Ytz+Ti2xkqGOK4WKyL22GOPPPaNDNVHH300/eQnP8lJS0W/MTUuvPDCPOEWbWBi4kLGkXX45z//eZou6j2l7U/u+ch4P+mkk/LKqK222soECh0uvudx/I9JPjoXQduSiUyN8M1vfrP62AYbbJBPumL5U1y9OEQgq1BkbhT/F+q9PcRse9OBRpwYRnZJnNzFoH9SS1ihs7eHyGicc845889x0rX22munp59+On3yySfphBNOyFl9MdCJ2/vvv58zIWOpLLS3bbfdNmfMRvmA448/vtlzMUiPyeW4CnGR9R1XyY6Mqsg6LUp6xHe0qfi5+H5PzpS2HxMbMejfbbfd8rnTiy++mF8TA//ILvy6228qst5jpVPTslVNxeR77EMEJ4oJFpge50oRHIuAWPQV8b2NIG6MGaIfiUDY3HPP3WriBNpDZI7ecMMNOWjbNMM7xDE+vrNxTA1xjI1jbZT4KCa64rzln//8Z54oi+DmNttsk+abb76p3o9iQq1pslMh+olYHREZwdFXTIvJbX9Kz8c45pBDDsnna9E3xfgFOsq9996bxwvxfaTzEbQtmciSiuXfUdetEA2sKIOw1FJL5U4rlnIU4n4sr1h88cVrss/QUWLQESdrLdtDLFeNx2Mw0nI5UZwMxtJWqDeRJRU114oVGUV7iL4hMvz22muvPCB//PHH8y2yUmKCr2VmILSX+N6tt956Odu2qShTM2jQoLw0tBDf28hgjYBoLAuNc5277rqr+vxDDz2Uy0MVS1RjoP/yyy9P9PdOaftRYzb6gl122SUP9qNthMgIjlIGX3f7TcWAO35Hv379JrqtCOhGGZP4m6EjRO3aCL62PFeK73ER6Io2EYP1CFBF8PYvf/lLDpRBR1l//fXzOfrrr7/e6vsaZTmansvEsbY4tkaiUhxTb7zxxryKLuqd33777bkObRHsjImwKZX2iP8TK/Ai8DuxlSIRHP7DH/6Qrw3TVHtsvy3PR4mhKAPRdLIFOsqUai9Tbq2vHEHNxQlVLCuJA3lkdUQjiwN+EZSNTI3I6HjnnXdyZxi1cOLiZRHEgnqy2GKL5YuQxbLSGGTEIPvss8/OWbUhMmtjpn7jjTfOtW8ffvjhvCzwuuuuq/WuQ7uLfiDqc8b3PZZ9R5ZIDAiidEjUgIu+oqkHHnggD3yOOuoonwYdJmoBRpmOlo488sh8rhJZfQMGDEhnnXVWzrAt6r5Gpl+siojjfAQ846Jfce4Tk9dFhlIEluI7PjGT234M/mO5aWH48OE5sysmuYv6u19n+4WYFInl6HGxs0mJ92Zqa+rC1OjRo0e+9kXU849gU4wHos7/L37xixy4DbEEPMYRkV0b1wEIsToDOkpkeMfEXsv+Ic7b47sZNZjjOxsTy7FsO65bEWISMMoCHnTQQXnyOUqkLbHEEtVs2AimRs3mOO5OrI54Ic6Joh9omaEb/y9q6EY5hpicizYToo+IybWvu/22Pl+8L/oHOlqMn2P10cRW3kWyR5zHxMqp4iKxkf0ebST6C8pB0LaEou5NpLBHw4qZx6h1s/XWW1efj6tcRmZVBKfixCxqrhVXiIV6EzUAY7Y+lk3FyVQs8SsG3RGQihOruGp3dDprrLFGnvRQKoR6FPWaow5c1EiLQNNaa62VBzqTuuhYDIxiQAIdKQacTTOmClFfMzKWYqItMoriuB2ZtUU2VQRE4/kILkUd28gAKWoaFpmCMWiYlCltv6mo/R+B1wgwt+f2IxMsSpTEqpBJiexhg3I62ve///18PYyYtI5AbQRm11133erzcTGkmKSIUiFRSzQu3KquIbXoH2KSIc7pI4M2JqNj0i4mpHfaaaf8fEwuxP0I3H722Wc5w/bHP/5x9RouceyOYFKcA01KrIqIYGyMCVqKcXOsUI1VF8XKi3DiiSfm4/7X3X5bni/6huI9go4UY4aYJIns8ol9V2N1XogL5sUq1rhNbsKC6a9LpRNXoI+ZsKIWU3zhItOIzs/n6n1DW3AcQd/QOfrUCGTGoDqCRFFTeVrqDk5MBHEvvfTSNtW4LeP2I9Ab5UwiwzEm4yOzrD05V/K+oS2U/TgSEwkxeRABo7gY3sQu1ji1IsAbK01jmx2ho7cf4gKXkXASiSkta7t/XfoG7xv11x5k2gIAME3WWWedfDGVY489Nq+K+PWvf90u7+TkSg50hu1HzcTIHF5uueXy+wPQaKKE30knnZQzu6NkU3tcbGtSNWLbS0dvP+y+++45eBQBYoApEbQFAGCa/epXv/LutbDtttvmG0CjigtVxo3mHnnkEW8J0GZff40CAAAAAADtRtAWAAAAAKBEBG0BAAAAAEpE0BYAAAAAoETq5kJko0ePrvUu0E58lt5DtIX25JhSH3yO3kO0B8cU9A36WJwrOd+kkcYOdRO07devX613AUpDewDtAfQN4FwJjB3AOJrOS3kEAAAAAIAS6VKpVCqpk4pdHzNmTK13gw7Uo0eP1KVLF+9xG2gP9U1bmDraQ33THtpOW6h/2kPbaQ/1TVuYOtpDfdMe2k5bqH89OnFcqVMHbQEAAAAA6o3yCAAAAAAAJSJoCwAAAABQIoK2AAAAAAAlImgLAAAAAFAigrYAAAAAACUiaAsAAAAAUCKCtgAAAAAAJSJoCwAAAABQIoK2AAAAAAAlImgLAAAAAFAigrYAAAAAACUiaAsAAAAAUCKCtgAAAAAAJSJoCwAAAABQIoK2AAAAAAAlImgLAAAAAFAigrYAAAAAACUiaAsAAAAAUCKCtgAAAAAAJSJoCwAAAABQIoK2AAAAAAAlImgLAAAAAFAigrYAAAAAACUiaAsAAAAAUCKCtgAAAAAAJSJoCwAAAABQIoK2AAAAAAAlImgLAAAAAFAigrYAAAAAACUiaAsAAAAAUCKCtgAAAAAAJSJoCwAAAABQIoK2AAAAAAAlImgLAAAAAFAigrYAAAAAACUiaAsAAAAAUCKCtgAAAAAAJSJoCwAAAABQIoK2AAAAAAAlImgLAAAAAFAigrYAAAAAACUiaAsAAAAAUCKCtgAAAAAAJSJoCwAAAABQIoK2AAAAAAAlImgLAAAAAFAigrYAAAAAACUiaAsAAAAAUCKCtgAAAAAAJSJoCwAAAABQIoK2AAAAAACpPP4/Stdhn33bM4MAAAAASUVORK5CYII=",
       "text/plain": [
        "<Figure size 1400x400 with 1 Axes>"
       ]

From a12f2e3ef5d71e07479fcadb84cfee63494dd9e1 Mon Sep 17 00:00:00 2001
From: ada-3e212e610b <z2720629308@gmail.com>
Date: Tue, 25 Aug 2026 20:31:15 +0100
Subject: [PATCH 25/25] add a readme for notebooks

---
 notebooks/README.md | 11 +++++++++++
 1 file changed, 11 insertions(+)
 create mode 100644 notebooks/README.md

diff --git a/notebooks/README.md b/notebooks/README.md
new file mode 100644
index 0000000..5ae0b37
--- /dev/null
+++ b/notebooks/README.md
@@ -0,0 +1,11 @@
+# notebooks/
+
+This folder holds only the organised summary notebooks for each phase, and `notebooks/utils/` contains the large chunks of helper functions used inside these notebooks (plotting, file
+loaders, etc.). All code for deployment is under the `/evaluation_function` directory, and all the notebooks produced during development remains on each branch respectively.
+
+
+- **`phase1-1.5_summary.ipynb`** -- Development and evaluation of the MIDI evaluator and feedback generation module (evaluation_function/compare_MIDI.py).
+
+- **`phase2_summary.ipynb`** -- Development and evaluation of the Audio-to-MIDI transcription module (evaluation_function/audio_processing.py).
+
+- **`Demostration.ipynb`** -- End-to-end demonstration of how the complete audio -> feedback process works on a real self-recorded practice audio.