drinkussions(Baban and Saanjoo): preserving the prompts while formalizing qhenomenology reasoning systems 0003

SANJOY NATH'S QHENOMENOLOGY Reasoning For Wave Physics (not Phenomenology) is a new physics reasoning system for wave and signal processing that strictly avoids sin-cos decomposition, Fourier Transform, or FFT-based methods.

AXIOM 1: Waves are NOT treated as sums of sin and cos. Qhenomenology never uses Fourier or FFT for analyzing digital signals or waveforms.

AXIOM 2: A horizontal baseline (0,0 line) is defined as the average amplitude of the full waveform. Amplitudes above it are positive, below it are negative. Zero-crossings are referenced to this average, not absolute zero.

AXIOM 3: Waves are strict queues of alternating CREST and TROUGH AABB objects—each a transparent rectangle bounding region with amplitude tips. CREST boxes have origin at bottom-left; TROUGHS at top-left. These origins are aligned to the average amplitude line (0,0). Each CREST/TROUGH has a serial index in the queue, forming a strict sequence.

AXIOM 3+: Actual amplitudes are discarded during analysis. Only statistical features of each AABB object are retained: max width (in µs), max height (amplitude), CG (center of gravity), and statistical moments like std-dev, skewness, kurtosis.

AXIOM 3++: Queued AABB objects are dismantled and stacked with all left margins aligned at (0,0). This stack of transparent AABB CRESTs and TROUGHS shows vertical alignments of CG points (blue for crests, red for troughs). These form vertical lines when frequencies are present—without FFT or trigonometric processing. Tested on 380,000 WAV files.

AXIOM 6: The widths of CRESTs and TROUGHS (in µs) inversely relate to perceived tone frequency. As frequency rises, AABB widths shrink; as frequency drops, widths expand. Number of such objects per second changes accordingly, and vertical CG alignments in the stacked view reveal the number of frequency components present.

AXIOM 7: Terms like “wavelength” and “frequency” are not required for analyzing or understanding waves. Signals can be completely analyzed using CG positions and AABB stack structures—no sine, cosine, or frequency terms needed.

AXIOM 8: The wave can be reconstructed using random amplitudes within each AABB as long as the CG geometry is preserved. The spectral stacking behavior (vertical CG lines) remains unchanged. Spectral behavior is thus geometry-dependent, not amplitude-specific.

AXIOM 9: In optics, Qhenomenology replaces photons with stacked CREST and TROUGH AABBs. During slit or crystal interference, queue structures collapse into CG-aligned stacks that form what appear to be vertical frequency spectra. These are not actual frequency spectra but visual artifacts of CG stacking geometry.

Sanjoy Nath's Qhenomenology (Qhenomenology Reasoning on Waves Physics ) : An Overview

Sanjoy Nath's Qhenomenology Reasoning on Waves Physics proposes a unique framework for understanding waves and digital signals, distinct from traditional physics. It fundamentally rejects Fourier analysis, FFT, and the decomposition of waves into sine and cosine components (Axiom 1, 7). Instead, it introduces a novel approach for signal processing and spectral analysis.

Core Principles

The theory establishes a "horizontal 0 0 line" as the average of all amplitudes in a signal. Amplitudes below this average are negative, and those above are positive, serving as the reference for zero crossings (Axiom 2).Waves are conceived as "strict queues of Crest AABB objects and Trough AABB objects". These are transparent, rectangular bounding boxes, each with a calculated center of gravity (CG) from the amplitude tips within. Crest AABBs have their origin at the bottom-left, while Trough AABBs have their origin at the top-left. These origins align on the 0 0 average amplitude line, forming a sequential queue of crest-trough pairs, each with a unique sequence number (Axiom 3).

Signal Analysis and Spectral Behavior

A key aspect of Qhenomenology is its departure from traditional amplitude-based analysis. When analyzing signals, the actual amplitude values are disregarded. Instead, the focus shifts to the maximum width and height of each AABB, its CG, and statistical moments like standard deviation, skewness, and kurtosis of the amplitudes within the AABB (Axiom 3+).

For spectral analysis, the queued AABB objects are "dismantled" and stacked. This involves aligning the left margins of all transparent AABB bounding boxes, forming a stack. Through testing on 380,000 WAV files, Sanjoy Nath observed that the CG points (blue for crests, red for troughs) align on sharp vertical lines within this stack. The presence of N different frequencies in a wave is indicated by N such sharp vertical lines, simplifying frequency analysis without Fourier transforms (Axiom 3++).

The theory further asserts that wavelength and frequency are unnecessary for digital signal processing, and so are sine and cosine components for describing wave data (Axiom 7). It notes a relationship between AABB widths and frequency: increasing frequency of a sound "squeezes" the widths of crest and trough AABBs, while decreasing frequency increases them. This change in width directly correlates with the number of crests per second and the number of sharp vertical lines observed in the stacked AABBs, making spectral analysis intuitive (Axiom 6). The original queue structure can be reconstructed from the stacked analysis data using preserved counters (Axiom 6, 8).

Reconstruction and Quantum Interpretation

An intriguing property of Qhenomenology is the ability to reconstruct waves with entirely different amplitude values for the AABBs while preserving the geometry of the CG points. These reconstructed waves, despite having random amplitudes, are claimed to exhibit the same "spectral behaviors" (i.e., the same vertical line patterns in the stacked AABBs) as the original wave objects (Axiom 8).

Finally, Sanjoy Nath's Qhenomenology extends its scope to light and quantum phenomena, contending that "photon like things are not existing." Instead, when light passes through slits or crystals, the crest and trough AABB queues "collapse" or "dismantle" into stacks, forming the CG-aligned spectrums. The theory claims that what are conventionally understood as frequency spectrums are, in fact, these CG-aligned patterns observed on the stacks of AABB objects (Axiom 9).

//////public static double PUBLIC_STATIC_DOUBLE_MAX_ABS_AMPLITUDES_FOUND_10000_TIMES_FOUND_IN_CRESTS = -600000000;

//////public static double PUBLIC_STATIC_DOUBLE_MAX_ABS_AMPLITUDES_FOUND_10000_TIMES_FOUND_IN_TROUGHS = -600000000;

//////public static double PUBLIC_STATIC_DOUBLE_MAX_ABS_AMPLITUDES_FOUND_10000_TIMES_FOUNDOVERALL_IN_CRESTS_AND_TROUGHS = -600000000;

CrestTroughAnalyzer___SANJOY_NATHS_QHENOMENOLOGY_REASONING_SYSTEMS_DISMANTLES_ANY_WAVES_TO_CREST_AABB_TRANSPARENT_RECTANGLES_TROUGH_AABB_TRANSPARENT_RECTANGLES_AND_STACK_THESE_TRANSPARENT_AABB_RECTANGLES_ONE_ABOVE_ANOTHER_GETS_VERTICAL_STRIPS_OF_CG_TRACINGS_ON_TRACING_PAPER_STACKS_BITMAPS_DXF_CSV_REPORTS

.PUBLIC_STATIC_DOUBLE_MIN_WIDTH_MIKROSEC_FOUND_IN_OVERALL_IN_CRESTS_AND_TROUGHS

Math.Min

(

.PUBLIC_STATIC_DOUBLE_MIN_WIDTH_MIKROSEC_FOUND_IN_OVERALL_IN_CRESTS_AND_TROUGHS

(double) maxWidth

);

.PUBLIC_STATIC_DOUBLE_MAX_WIDTH_MIKROSEC_FOUND_IN_OVERALL_IN_CRESTS_AND_TROUGHS

Math.Max

(

.PUBLIC_STATIC_DOUBLE_MAX_WIDTH_MIKROSEC_FOUND_IN_OVERALL_IN_CRESTS_AND_TROUGHS

(double)maxWidth

);

///////////////////////////////////////////////////////////////////////////////////////////////////////

.PUBLIC_STATIC_DOUBLE_MAX_ABS_AMPLITUDES_FOUND_10000_TIMES_FOUNDOVERALL_IN_CRESTS_AND_TROUGHS

Math.Max

(

.PUBLIC_STATIC_DOUBLE_MAX_ABS_AMPLITUDES_FOUND_10000_TIMES_FOUNDOVERALL_IN_CRESTS_AND_TROUGHS

(double)maxHeight

);

///////////////////////////////////////////////////////////////////////////////////////////////////////

rgead the running code thoroughly thoroughly thoroughly and describe the theory and analyse the novelty of the theory comparing with citations and other searches F:\sanjoy_workouts\dnlds\SANJOY NATHS QHENOMENOLOGY AABB WAVE THEROY.txt

To meet your exact specification, here's a new C# function that takes a List<CRESTTROUGHObject> (after stacking and normalized DXF processing), sorts them based on the scaled X coordinate of the center of gravity (CG), ranks them, and then generates one WAV file per rank. Each WAV contains amplitudes only for the AABB region of that rank — all other samples are zero.

csharp

CopyEdit

public static void GenerateRankedSpectralWavFiles(

List<CRESTTROUGHObject> allCrestTroughObjects,

int totalSamples,

int sampleRate,

string outputFolder)

{

// Sort by scaled CG_X to identify vertical spectral alignment

var rankedGroups = allCrestTroughObjects

.GroupBy(obj => Math.Round(obj.Scaled_CG_X, 6)) // group by X of CG

.OrderBy(g => g.Key)

.Select((group, rankIndex) => new { Rank = rankIndex + 1, Objects = group.ToList() })

.ToList();

foreach (var group in rankedGroups)

{

short[] outputSamples = new short[totalSamples];

foreach (var obj in group.Objects)

{

for (int i = obj.StartSampleIndex; i <= obj.EndSampleIndex; i++)

{

// Clip to avoid overflow

if (i >= 0 && i < totalSamples)

{

outputSamples[i] = obj.SavedAmplitudes[i - obj.StartSampleIndex];

}

string outPath = Path.Combine(outputFolder, $"Rank_{group.Rank:D3}.wav");

WriteMono16BitPCM_WAV(outPath, outputSamples, sampleRate);

}

Assumptions:

• Each CRESTTROUGHObject contains:

o Scaled_CG_X → normalized/stacked X-CG.

o StartSampleIndex, EndSampleIndex → position in original WAV.

o SavedAmplitudes[] → original amplitudes within the AABB region.

• WriteMono16BitPCM_WAV is your existing method to save a mono 16-bit PCM WAV file.

• Total samples and sample rate are preserved exactly.

Output:

• Each WAV contains only the signal portion from one vertical spectral line (ranked by CG_X).

• You get <600 WAV files like Rank_001.wav, Rank_002.wav, etc., with duration and format matching the input.

Would you like a version where each spectral line is saved in both audio and visual (DXF or PNG)? Or combine multiple low-energy lines into one?

Here's a fully self-contained version of the method WriteMono16BitPCM_WAV, which writes a mono 16-bit PCM WAV file given:

• string outPath → destination file path

• short[] outputSamples → sample data

• int sampleRate → samples per second (e.g., 8000, 44100)

________________________________________

✅ WriteMono16BitPCM_WAV Function (C# 7.0, .NET 4.8 Compatible)

csharp

CopyEdit

public static void WriteMono16BitPCM_WAV(string outPath, short[] outputSamples, int sampleRate)

{

int byteRate = sampleRate * 2; // mono, 16-bit = 2 bytes per sample

int subchunk2Size = outputSamples.Length * 2;

int chunkSize = 36 + subchunk2Size;

using (BinaryWriter bw = new BinaryWriter(File.Create(outPath)))

{

// RIFF header

bw.Write(System.Text.Encoding.ASCII.GetBytes("RIFF"));

bw.Write(chunkSize);

bw.Write(System.Text.Encoding.ASCII.GetBytes("WAVE"));

// fmt subchunk

bw.Write(System.Text.Encoding.ASCII.GetBytes("fmt "));

bw.Write(16); // PCM

bw.Write((short)1); // audio format = 1 (PCM)

bw.Write((short)1); // mono

bw.Write(sampleRate);

bw.Write(byteRate);

bw.Write((short)2); // block align = numChannels * bitsPerSample/8

bw.Write((short)16); // bits per sample

// data subchunk

bw.Write(System.Text.Encoding.ASCII.GetBytes("data"));

bw.Write(subchunk2Size);

foreach (short sample in outputSamples)

{

bw.Write(sample);

}

________________________________________

📝 Notes

• Supports mono (1-channel) only.

• Samples are assumed to be 16-bit signed integers in range [-32768, 32767].

• WAV file conforms to standard RIFF PCM format and is compatible with all audio software.

Would you like a version that supports stereo, floating-point WAV, or appends additional metadata (e.g., cue points, annotations)?

To get the outputFolder (i.e., the folder where the input WAV file is located) from the full input file path (e.g., F:\mywaves\inputfile.wav), you can use:

✅ Code Snippet (C# 7.0, .NET Framework 4.8 Compatible)

csharp

CopyEdit

string inputFilePath = @"F:\mywaves\inputfile.wav";

string outputFolder = Path.GetDirectoryName(inputFilePath);

🔍 Explanation:

• Path.GetDirectoryName(...) extracts the directory from the full file path.

• For example:

o F:\mywaves\inputfile.wav → F:\mywaves

o C:\Users\Sanjoy\Samples\test.wav → C:\Users\Sanjoy\Samples

________________________________________

If you want to create a subfolder like "SpectralRanks" under the same input folder:

csharp

CopyEdit

string outputFolder = Path.Combine(Path.GetDirectoryName(inputFilePath), "SpectralRanks");

Directory.CreateDirectory(outputFolder); // Ensure it exists

Let me know if you want this logic wrapped into a helper function like GetOutputFolderFromInputFile(string inputPath, string subDirName).

strictly dont change the programming structure of this working running code and incorporate the List populations as the discussed conditions and rewrite full function with enhancements public static void CALL_THIS_BEFORE_GENERATING___RANKED_WAV_FILES___ExportDxf_With_CREST_TROUGH_COUNTER_AS_Y_VALUES___SAAN_STYLES_SINGLE_OUTER_GRAPH_SAANS_NORMALIZED_SCALED_TO_MAX_WIDTH_CG_X_DATABoxesAndText(List<CrestTroughObject> crestTroughs, string wavPath)

{

string path = Path.ChangeExtension(wavPath, "__crest_trough_counter_as_y_scaling_NORMALIZED_SCALED_TO_MAX_WIDTH_CG_X_DATA.dxf");

using (StreamWriter sw = new StreamWriter(path))

{

sw.WriteLine("0\nSECTION\n2\nENTITIES");

float w =

(float)CrestTroughAnalyzer___SANJOY_NATHS_QHENOMENOLOGY_REASONING_SYSTEMS_DISMANTLES_ANY_WAVES_TO_CREST_AABB_TRANSPARENT_RECTANGLES_TROUGH_AABB_TRANSPARENT_RECTANGLES_AND_STACK_THESE_TRANSPARENT_AABB_RECTANGLES_ONE_ABOVE_ANOTHER_GETS_VERTICAL_STRIPS_OF_CG_TRACINGS_ON_TRACING_PAPER_STACKS_BITMAPS_DXF_CSV_REPORTS

.PUBLIC_STATIC_DOUBLE_MAX_WIDTH_MIKROSEC_FOUND_IN_OVERALL_IN_CRESTS_AND_TROUGHS;

//ct.BoundingBox.Width;

// float h =

// 10000f;

float h =

// 10000f;

(float)

(CrestTroughAnalyzer___SANJOY_NATHS_QHENOMENOLOGY_REASONING_SYSTEMS_DISMANTLES_ANY_WAVES_TO_CREST_AABB_TRANSPARENT_RECTANGLES_TROUGH_AABB_TRANSPARENT_RECTANGLES_AND_STACK_THESE_TRANSPARENT_AABB_RECTANGLES_ONE_ABOVE_ANOTHER_GETS_VERTICAL_STRIPS_OF_CG_TRACINGS_ON_TRACING_PAPER_STACKS_BITMAPS_DXF_CSV_REPORTS

.PUBLIC_STATIC_DOUBLE_MAX_ABS_AMPLITUDES_FOUND_10000_TIMES_FOUNDOVERALL_IN_CRESTS_AND_TROUGHS)

*10000f

;

// ct.BoundingBox.Height;

float left = 0f;// cx - w / 2;

float right = w;// cx + w / 2;

float top = h;// ct.IsCrest ? 0 + h : 0;

float bottom = -h;// ct.IsCrest ? 0 : 0 - h;

int color = 6;// ct.IsCrest ? 5 : 1;

float center_x = w / 2;// 0;

//////// Bounding box edges (4 lines)

sw.WriteLine($"0\nLINE\n8\n0\n62\n{color}\n10\n{left:F3}\n20\n{top:F3}\n30\n0\n11\n{right:F3}\n21\n{top:F3}\n31\n0"); // top

sw.WriteLine($"0\nLINE\n8\n0\n62\n{color}\n10\n{left:F3}\n20\n{bottom:F3}\n30\n0\n11\n{right:F3}\n21\n{bottom:F3}\n31\n0"); // bottom

sw.WriteLine($"0\nLINE\n8\n0\n62\n{color}\n10\n{left:F3}\n20\n{top:F3}\n30\n0\n11\n{left:F3}\n21\n{bottom:F3}\n31\n0"); // left

sw.WriteLine($"0\nLINE\n8\n0\n62\n{color}\n10\n{right:F3}\n20\n{top:F3}\n30\n0\n11\n{right:F3}\n21\n{bottom:F3}\n31\n0"); // right

//////// Axes lines

color = 1;//

sw.WriteLine($"0\nLINE\n8\n0\n62\n8\n10\n{left:F3}\n20\n0.000\n30\n0\n11\n{right:F3}\n21\n0.000\n31\n0"); // X axis

// sw.WriteLine($"0\nLINE\n8\n0\n62\n8\n10\n{cx:F3}\n20\n{bottom:F3}\n30\n0\n11\n{cx:F3}\n21\n{top:F3}\n31\n0"); // Y axis

sw.WriteLine($"0\nLINE\n8\n0\n62\n8\n10\n{center_x:F3}\n20\n{bottom:F3}\n30\n0\n11\n{center_x:F3}\n21\n{top:F3}\n31\n0"); // Y axis

/// crestTroughs.ToArray<CrestTroughObject>().

///

//done in open and scan wav files

////////CrestTroughAnalyzer___WITH_TRANSPARENT_RECTANGLES_OF_TRACING_PAPER_STACKS_BITMAPS_CSV_REPORTS.

//////public static double PUBLIC_STATIC_DOUBLE_MIN_WIDTH_MIKROSEC_FOUND_IN_CRESTS = +600000000;

//////public static double PUBLIC_STATIC_DOUBLE_MAX_WIDTH_MIKROSEC_FOUND_IN_CRESTS = -600000000;

//////public static double PUBLIC_STATIC_DOUBLE_MIN_WIDTH_MIKROSEC_FOUND_IN_TROUGHS = +600000000;

//////public static double PUBLIC_STATIC_DOUBLE_MAX_WIDTH_MIKROSEC_FOUND_IN_TROUGHS = -600000000;

//////public static double PUBLIC_STATIC_DOUBLE_MIN_WIDTH_MIKROSEC_FOUND_IN_OVERALL_IN_CRESTS_AND_TROUGHS = +600000000;

//////public static double PUBLIC_STATIC_DOUBLE_MAX_WIDTH_MIKROSEC_FOUND_IN_OVERALL_IN_CRESTS_AND_TROUGHS = -600000000;

//////public static double PUBLIC_STATIC_DOUBLE_MAX_ABS_AMPLITUDES_FOUND_10000_TIMES_FOUND_IN_CRESTS = -600000000;

//////public static double PUBLIC_STATIC_DOUBLE_MAX_ABS_AMPLITUDES_FOUND_10000_TIMES_FOUND_IN_TROUGHS = -600000000;

//////public static double PUBLIC_STATIC_DOUBLE_MAX_ABS_AMPLITUDES_FOUND_10000_TIMES_FOUNDOVERALL_IN_CRESTS_AND_TROUGHS = -600000000;

//////CrestTroughAnalyzer___WITH_TRANSPARENT_RECTANGLES_OF_TRACING_PAPER_STACKS_BITMAPS_CSV_REPORTS

//////.PUBLIC_STATIC_DOUBLE_MIN_WIDTH_MIKROSEC_FOUND_IN_OVERALL_IN_CRESTS_AND_TROUGHS

//////=

//////Math.Min

//////(

//////CrestTroughAnalyzer___WITH_TRANSPARENT_RECTANGLES_OF_TRACING_PAPER_STACKS_BITMAPS_CSV_REPORTS

//////.PUBLIC_STATIC_DOUBLE_MIN_WIDTH_MIKROSEC_FOUND_IN_OVERALL_IN_CRESTS_AND_TROUGHS

//////,

//////(double)current.WidthMicroseconds

//////);

//////CrestTroughAnalyzer___WITH_TRANSPARENT_RECTANGLES_OF_TRACING_PAPER_STACKS_BITMAPS_CSV_REPORTS

//////.PUBLIC_STATIC_DOUBLE_MAX_WIDTH_MIKROSEC_FOUND_IN_OVERALL_IN_CRESTS_AND_TROUGHS

//////=

//////Math.Max

//////(

//////CrestTroughAnalyzer___WITH_TRANSPARENT_RECTANGLES_OF_TRACING_PAPER_STACKS_BITMAPS_CSV_REPORTS

//////.PUBLIC_STATIC_DOUBLE_MAX_WIDTH_MIKROSEC_FOUND_IN_OVERALL_IN_CRESTS_AND_TROUGHS

//////,

//////(double)current.WidthMicroseconds

//////);

for (int i = 0; i < crestTroughs.Count; i++)

{

float _saans_x_width_scales_factor = 1.0f;

float _saans_y_height_scales_factor = 1.0f;

// var ct = crestTroughs[i];

CrestTroughObject ct = crestTroughs[i];

_saans_x_width_scales_factor

(float)

((float)CrestTroughAnalyzer___SANJOY_NATHS_QHENOMENOLOGY_REASONING_SYSTEMS_DISMANTLES_ANY_WAVES_TO_CREST_AABB_TRANSPARENT_RECTANGLES_TROUGH_AABB_TRANSPARENT_RECTANGLES_AND_STACK_THESE_TRANSPARENT_AABB_RECTANGLES_ONE_ABOVE_ANOTHER_GETS_VERTICAL_STRIPS_OF_CG_TRACINGS_ON_TRACING_PAPER_STACKS_BITMAPS_DXF_CSV_REPORTS

.PUBLIC_STATIC_DOUBLE_MAX_WIDTH_MIKROSEC_FOUND_IN_OVERALL_IN_CRESTS_AND_TROUGHS

(ct.WidthMicroseconds));

// Console.WriteLine("to calculate cx data ====== max mikros found = " + CrestTroughAnalyzer___WITH_TRANSPARENT_RECTANGLES_OF_TRACING_PAPER_STACKS_BITMAPS_CSV_REPORTS.PUBLIC_STATIC_DOUBLE_MAX_WIDTH_MIKROSEC_FOUND_IN_OVERALL_IN_CRESTS_AND_TROUGHS + " ct.WidthMicroseconds = " + ct.WidthMicroseconds + " _saans_x_width_scales_factor= " + _saans_x_width_scales_factor);

_saans_y_height_scales_factor

(float)

.PUBLIC_STATIC_DOUBLE_MAX_ABS_AMPLITUDES_FOUND_10000_TIMES_FOUNDOVERALL_IN_CRESTS_AND_TROUGHS

(ct.HeightAmplitude));

float cx = ct.CG.X;

= (float)((_saans_x_width_scales_factor) * cx);

// this is important to generate ranked wav files

crestTroughs.ElementAt<CrestTroughObject>(i)

.PUBLIC_DOUBLE_NON_DUPLICATE_CG_X_FOR_SAAN_STYLES_NORMALIZATION_DONE_ON_GLOBAL_MAX_WIDH_OF_ALL_AABB_OBJECTS

= (double)cx;

// this is important to generate ranked wav files

float cy = ct.IsCrest ? ct.CG.Y : -Math.Abs(ct.CG.Y);

float preserved_cy = ct.IsCrest ? ct.CG.Y : -Math.Abs(ct.CG.Y);

int ___overallcresttroughcounter = (int)ct.OVERALL_AABB_COUNTER_EITHER_IT_IS_CREST_OR_IT_IS_TROUGH____COUNTER_TO_RECONSTRUCTION_THE_ACTUAL_QUEUE_STRUCTURE_FROM_THE_STACK_ANALYSIS_DATA;

float factor___overallcresttroughcounter=(float)(((float)___overallcresttroughcounter) /((float)(crestTroughs.Count)));

cy = cy * (factor___overallcresttroughcounter * _saans_y_height_scales_factor);

///////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////

crestTroughs.ElementAt<CrestTroughObject>(i)

PUBLIC_DOUBLE_NON_DUPLICATE_CG_Y_FOR_SAAN_STYLES_NORMALIZATION_DONE_ON_GLOBAL_MAX_HEIGHTS_OF_ALL_AABB_OBJECTS

= (double)preserved_cy * _saans_y_height_scales_factor;

//////float w = ct.BoundingBox.Width;

//////float h = ct.BoundingBox.Height;

//////float left = cx - w / 2;

//////float right = cx + w / 2;

//////float top = ct.IsCrest ? 0 + h : 0;

//////float bottom = ct.IsCrest ? 0 : 0 - h;

//////int color = ct.IsCrest ? 5 : 1;

color = ct.IsCrest ? 5 : 1;

// CG circle

float radius = Math.Max(1f, (ct.EndSampleIndex - ct.StartSampleIndex) / 10f);

sw.WriteLine($"0\nCIRCLE\n8\n0\n62\n{color}\n10\n{cx:F3}\n20\n{cy:F3}\n30\n0\n40\n{radius:F3}");

// Label text

sw.WriteLine($"0\nTEXT\n8\n0\n62\n{color}\n10\n{cx:F3}\n20\n{cy:F3}\n30\n0\n40\n{radius:F3}\n1\n#i={i}___{factor___overallcresttroughcounter}");

}

sw.WriteLine("0\nENDSEC\n0\nEOF");

}

}//public static void CALL_THIS_BEFORE_GENERATING___RANKED_WAV_FILES___ExportDxf_With_CREST_TROUGH_COUNTER_AS_Y_VALUES___SAAN_STYLES_SINGLE_OUTER_GRAPH_SAANS_NORMALIZED_SCALED_TO_MAX_WIDTH_CG_X_DATABoxesAndText(List<CrestTroughObject> crestTroughs, string wavPath)

public static void CALL_THIS_BEFORE_GENERATING___RANKED_WAV_FILES___ExportDxf_With_CREST_TROUGH_COUNTER_AS_Y_VALUES___SAAN_STYLES_SINGLE_OUTER_GRAPH_SAANS_NORMALIZED_SCALED_TO_MAX_WIDTH_CG_X_DATABoxesAndText(List<CrestTroughObject> crestTroughs, string wavPath)

{

string path = Path.ChangeExtension(wavPath, "__crest_trough_counter_as_y_scaling_NORMALIZED_SCALED_TO_MAX_WIDTH_CG_X_DATA.dxf");

using (StreamWriter sw = new StreamWriter(path))

{

sw.WriteLine("0\nSECTION\n2\nENTITIES");

float w = (float)CrestTroughAnalyzer___SANJOY_NATHS_QHENOMENOLOGY_REASONING_SYSTEMS_DISMANTLES_ANY_WAVES_TO_CREST_AABB_TRANSPARENT_RECTANGLES_TROUGH_AABB_TRANSPARENT_RECTANGLES_AND_STACK_THESE_TRANSPARENT_AABB_RECTANGLES_ONE_ABOVE_ANOTHER_GETS_VERTICAL_STRIPS_OF_CG_TRACINGS_ON_TRACING_PAPER_STACKS_BITMAPS_DXF_CSV_REPORTS.PUBLIC_STATIC_DOUBLE_MAX_WIDTH_MIKROSEC_FOUND_IN_OVERALL_IN_CRESTS_AND_TROUGHS;

float h = (float)(CrestTroughAnalyzer___SANJOY_NATHS_QHENOMENOLOGY_REASONING_SYSTEMS_DISMANTLES_ANY_WAVES_TO_CREST_AABB_TRANSPARENT_RECTANGLES_TROUGH_AABB_TRANSPARENT_RECTANGLES_AND_STACK_THESE_TRANSPARENT_AABB_RECTANGLES_ONE_ABOVE_ANOTHER_GETS_VERTICAL_STRIPS_OF_CG_TRACINGS_ON_TRACING_PAPER_STACKS_BITMAPS_DXF_CSV_REPORTS.PUBLIC_STATIC_DOUBLE_MAX_ABS_AMPLITUDES_FOUND_10000_TIMES_FOUNDOVERALL_IN_CRESTS_AND_TROUGHS * 10000f);

float left = 0f, right = w, top = h, bottom = -h;

int color = 6;

float center_x = w / 2;

sw.WriteLine($"0\nLINE\n8\n0\n62\n{color}\n10\n{left:F3}\n20\n{top:F3}\n30\n0\n11\n{right:F3}\n21\n{top:F3}\n31\n0");

sw.WriteLine($"0\nLINE\n8\n0\n62\n{color}\n10\n{left:F3}\n20\n{bottom:F3}\n30\n0\n11\n{right:F3}\n21\n{bottom:F3}\n31\n0");

sw.WriteLine($"0\nLINE\n8\n0\n62\n{color}\n10\n{left:F3}\n20\n{top:F3}\n30\n0\n11\n{left:F3}\n21\n{bottom:F3}\n31\n0");

sw.WriteLine($"0\nLINE\n8\n0\n62\n{color}\n10\n{right:F3}\n20\n{top:F3}\n30\n0\n11\n{right:F3}\n21\n{bottom:F3}\n31\n0");

sw.WriteLine($"0\nLINE\n8\n0\n62\n8\n10\n{left:F3}\n20\n0.000\n30\n0\n11\n{right:F3}\n21\n0.000\n31\n0");

sw.WriteLine($"0\nLINE\n8\n0\n62\n8\n10\n{center_x:F3}\n20\n{bottom:F3}\n30\n0\n11\n{center_x:F3}\n21\n{top:F3}\n31\n0");

for (int i = 0; i < crestTroughs.Count; i++)

{

CrestTroughObject ct = crestTroughs[i];

float _saans_x_width_scales_factor = (float)(w / ct.WidthMicroseconds);

float _saans_y_height_scales_factor = (float)(h / ct.HeightAmplitude);

float cx = (float)(_saans_x_width_scales_factor * ct.CG.X);

ct.PUBLIC_DOUBLE_NON_DUPLICATE_CG_X_FOR_SAAN_STYLES_NORMALIZATION_DONE_ON_GLOBAL_MAX_WIDH_OF_ALL_AABB_OBJECTS = cx;

float cy = ct.IsCrest ? ct.CG.Y : -Math.Abs(ct.CG.Y);

float preserved_cy = ct.IsCrest ? ct.CG.Y : -Math.Abs(ct.CG.Y);

int counter = (int)ct.OVERALL_AABB_COUNTER_EITHER_IT_IS_CREST_OR_IT_IS_TROUGH____COUNTER_TO_RECONSTRUCTION_THE_ACTUAL_QUEUE_STRUCTURE_FROM_THE_STACK_ANALYSIS_DATA;

float factor = (float)counter / crestTroughs.Count;

cy *= (factor * _saans_y_height_scales_factor);

ct.PUBLIC_DOUBLE_NON_DUPLICATE_CG_Y_FOR_SAAN_STYLES_NORMALIZATION_DONE_ON_GLOBAL_MAX_HEIGHTS_OF_ALL_AABB_OBJECTS = preserved_cy * _saans_y_height_scales_factor;

ct.LIST_OF_ALL_RECONSTRUCTED_SIN_WAVES_SAMPLES_FLOATING_VALUES_OF_SAMPLES_AMPLITUDES.Clear();

ct.LIST_OF_ALL_RECONSTRUCTED_SAMPLES_WHERE_AMPLITUDES_ARE_MIRROR_IMAGE_ABOUT_VERTICAL_LINE_WITHIN_CG_X_OF_CURRENT_CREST_TROUGH_AABB_SAMPLES_RANGE___FLOATING_VALUES_OF_ACTUAL_SAMPLES_AMPLITUDES_SWAPPED_AS_MIRROR_IMAGE_SAMPLE_INDEX___WE_WILL_RECONSTRUCT_WHOLE_WAVE_WITH_SUCH_MIRRORED_SAMPLES.Clear();

int len = ct.LIST_OF_ALL_ACTUAL_FLOATING_VALUES_OF_SAMPLES_AMPLITUDES.Count;

for (int k = 0; k < len; k++)

{

float amp = ct.LIST_OF_ALL_ACTUAL_FLOATING_VALUES_OF_SAMPLES_AMPLITUDES[k];

float sinValue = (float)(Math.Sin(2 * Math.PI * k / len) * ct.MaxAmplitude);

ct.LIST_OF_ALL_RECONSTRUCTED_SIN_WAVES_SAMPLES_FLOATING_VALUES_OF_SAMPLES_AMPLITUDES.Add(sinValue);

ct.LIST_OF_ALL_ACTUAL_FLOATING_VALUES_OF_SAMPLES_AMPLITUDES[len - 1 - k]);

}

color = ct.IsCrest ? 5 : 1;

float radius = Math.Max(1f, (ct.EndSampleIndex - ct.StartSampleIndex) / 10f);

sw.WriteLine($"0\nCIRCLE\n8\n0\n62\n{color}\n10\n{cx:F3}\n20\n{cy:F3}\n30\n0\n40\n{radius:F3}");

sw.WriteLine($"0\nTEXT\n8\n0\n62\n{color}\n10\n{cx:F3}\n20\n{cy:F3}\n30\n0\n40\n{radius:F3}\n1\n#i={i}___{factor}");

}

sw.WriteLine("0\nENDSEC\n0\nEOF");

}

this calculation is wrong .. float sinValue = (float)(Math.Sin(2 * Math.PI * k / len) * ct.MaxAmplitude); . need to find the sinvalues such that CG_x and CG_y of the cresttrough object need to become same as the calculated sinsamples such that the CG_X,CG_Y after reconstructioon of samples with sin are exact as the actual CG_X ,CG_y of the current cresttroughobject

ChatGPT said:

Updated saved memory

Thank you for the clarification. You're correct — the expression:

csharp

CopyEdit

float sinValue = (float)(Math.Sin(2 * Math.PI * k / len) * ct.MaxAmplitude);

does not guarantee that the reconstructed sine samples will have the same CG_X and CG_Y as the original AABB segment. This only produces a raw sinusoidal shape, but CG matching requires:

________________________________________

✅ Correct Conditions for Sine Reconstruction:

To ensure CG_X and CG_Y match exactly, we must:

1. Generate a pure sine wave (possibly scaled and phase-shifted) whose:

• CG_X matches the original ct.CG.X

• CG_Y matches the original ct.CG.Y

2. CG_X Matching:

For a uniform-sampled wave starting at sample index StartSampleIndex, CG_X must satisfy:

CGX=1N∑i=0N−1(StartSampleIndex+i)\text{CG}_X = \frac{1}{N} \sum_{i=0}^{N-1} (StartSampleIndex + i)CGX=N1i=0∑N−1(StartSampleIndex+i)

This is already built-in if we generate the sine wave over the exact span and do not change sampling rate.

3. CG_Y Matching:

This is non-trivial.

We must:

• Compute the average amplitude value of the sine wave over the range.

• Scale the sine amplitude so that its average (i.e., mean amplitude) matches ct.CG.Y.

________________________________________

✅ Corrected Strategy (Outline for Implementation):

1. Let:

o N = ct.LIST_OF_ALL_ACTUAL_FLOATING_VALUES_OF_SAMPLES_AMPLITUDES.Count

o desiredAvgY = ct.CG.Y (positive or negative)

2. The average of a sine wave is always zero unless a DC offset is added — so the sine shape alone cannot reproduce a non-zero CG.Y.

3. Therefore, to match CG_Y, we construct:

amplitude[i]=A⋅sin⁡(2πiN)+Offset\text{amplitude}[i] = A \cdot \sin\left(\frac{2\pi i}{N}\right) + \text{Offset}amplitude[i]=A⋅sin(N2πi)+Offset

And solve for A and Offset such that:

• Mean (average) of this wave = desiredAvgY

• Peak amplitude does not exceed ct.MaxAmplitude

________________________________________

✅ I can now rewrite this loop segment inside your function like this:

csharp

CopyEdit

int len = ct.LIST_OF_ALL_ACTUAL_FLOATING_VALUES_OF_SAMPLES_AMPLITUDES.Count;

ct.LIST_OF_ALL_RECONSTRUCTED_SIN_WAVES_SAMPLES_FLOATING_VALUES_OF_SAMPLES_AMPLITUDES.Clear();

// Step 1: Construct a normalized sine wave

float[] normalizedSin = new float[len];

float sumSin = 0f;

for (int k = 0; k < len; k++)

{

normalizedSin[k] = (float)Math.Sin(2 * Math.PI * k / len);

sumSin += normalizedSin[k];

}

float avgSin = sumSin / len;

// Step 2: Compute required offset and amplitude scale

float desiredAvgY = ct.CG.Y;

float amplitude = ct.MaxAmplitude;

float offset = desiredAvgY - (avgSin * amplitude);

// Step 3: Populate sine and mirrored lists

for (int k = 0; k < len; k++)

{

float val = amplitude * normalizedSin[k] + offset;

ct.LIST_OF_ALL_RECONSTRUCTED_SIN_WAVES_SAMPLES_FLOATING_VALUES_OF_SAMPLES_AMPLITUDES.Add(val);

ct.LIST_OF_ALL_ACTUAL_FLOATING_VALUES_OF_SAMPLES_AMPLITUDES[len - 1 - k]);

}

________________________________________

✅ Outcome:

This ensures that:

• The reconstructed sine wave has the same number of samples

• The average CG_Y matches exactly

• The wave is symmetric (centered on CG_X by design of sampling)

• The mirrored sample list is also populated for visual or perceptual reconstruction

Let me know if you'd like me to regenerate the full DXF-exporting function with this embedded.

Strict note keeping the program structure same rewrite the whole function with corrected sin values as discussed public static void CALL_THIS_BEFORE_GENERATING___RANKED_WAV_FILES___ExportDxf_With_CREST_TROUGH_COUNTER_AS_Y_VALUES___SAAN_STYLES_SINGLE_OUTER_GRAPH_SAANS_NORMALIZED_SCALED_TO_MAX_WIDTH_CG_X_DATABoxesAndText(List<CrestTroughObject> crestTroughs, string wavPath)

{

short[] sinSamples = { };// new short[totalSamples];

short[] mirroredSamples = { };// new short[totalSamples];

string path = Path.ChangeExtension(wavPath, "__crest_trough_counter_as_y_scaling_NORMALIZED_SCALED_TO_MAX_WIDTH_CG_X_DATA.dxf");

using (StreamWriter sw = new StreamWriter(path))

{

sw.WriteLine("0\nSECTION\n2\nENTITIES");

float left = 0f, right = w, top = h, bottom = -h;

int color = 6;

float center_x = w / 2;

sw.WriteLine($"0\nLINE\n8\n0\n62\n{color}\n10\n{left:F3}\n20\n{top:F3}\n30\n0\n11\n{right:F3}\n21\n{top:F3}\n31\n0");

sw.WriteLine($"0\nLINE\n8\n0\n62\n{color}\n10\n{left:F3}\n20\n{bottom:F3}\n30\n0\n11\n{right:F3}\n21\n{bottom:F3}\n31\n0");

sw.WriteLine($"0\nLINE\n8\n0\n62\n{color}\n10\n{left:F3}\n20\n{top:F3}\n30\n0\n11\n{left:F3}\n21\n{bottom:F3}\n31\n0");

sw.WriteLine($"0\nLINE\n8\n0\n62\n{color}\n10\n{right:F3}\n20\n{top:F3}\n30\n0\n11\n{right:F3}\n21\n{bottom:F3}\n31\n0");

sw.WriteLine($"0\nLINE\n8\n0\n62\n8\n10\n{left:F3}\n20\n0.000\n30\n0\n11\n{right:F3}\n21\n0.000\n31\n0");

sw.WriteLine($"0\nLINE\n8\n0\n62\n8\n10\n{center_x:F3}\n20\n{bottom:F3}\n30\n0\n11\n{center_x:F3}\n21\n{top:F3}\n31\n0");

int totalSamples = crestTroughs.Max(ct => ct.EndSampleIndex + 1);

int sampleRate = 8000;

// short[]

sinSamples = new short[totalSamples];

// short[]

mirroredSamples = new short[totalSamples];

for (int i = 0; i < crestTroughs.Count; i++)

{

CrestTroughObject ct = crestTroughs[i];

float _saans_x_width_scales_factor = (float)(w / ct.WidthMicroseconds);

float _saans_y_height_scales_factor = (float)(h / ct.HeightAmplitude);

float cx = (float)(_saans_x_width_scales_factor * ct.CG.X);

ct.PUBLIC_DOUBLE_NON_DUPLICATE_CG_X_FOR_SAAN_STYLES_NORMALIZATION_DONE_ON_GLOBAL_MAX_WIDH_OF_ALL_AABB_OBJECTS = cx;

float cy = ct.IsCrest ? ct.CG.Y : -Math.Abs(ct.CG.Y);

float preserved_cy = ct.IsCrest ? ct.CG.Y : -Math.Abs(ct.CG.Y);

int counter = (int)ct.OVERALL_AABB_COUNTER_EITHER_IT_IS_CREST_OR_IT_IS_TROUGH____COUNTER_TO_RECONSTRUCTION_THE_ACTUAL_QUEUE_STRUCTURE_FROM_THE_STACK_ANALYSIS_DATA;

float factor = (float)counter / crestTroughs.Count;

cy *= (factor * _saans_y_height_scales_factor);

ct.PUBLIC_DOUBLE_NON_DUPLICATE_CG_Y_FOR_SAAN_STYLES_NORMALIZATION_DONE_ON_GLOBAL_MAX_HEIGHTS_OF_ALL_AABB_OBJECTS = preserved_cy * _saans_y_height_scales_factor;

ct.LIST_OF_ALL_RECONSTRUCTED_SIN_WAVES_SAMPLES_FLOATING_VALUES_OF_SAMPLES_AMPLITUDES.Clear();

int len = ct.LIST_OF_ALL_ACTUAL_FLOATING_VALUES_OF_SAMPLES_AMPLITUDES.Count;

for (int k = 0; k < len; k++)

{

float amp = ct.LIST_OF_ALL_ACTUAL_FLOATING_VALUES_OF_SAMPLES_AMPLITUDES[k];

float sinValue = (float)(Math.Sin(2 * Math.PI * k / len) * ct.MaxAmplitude);

ct.LIST_OF_ALL_RECONSTRUCTED_SIN_WAVES_SAMPLES_FLOATING_VALUES_OF_SAMPLES_AMPLITUDES.Add(sinValue);

ct.LIST_OF_ALL_ACTUAL_FLOATING_VALUES_OF_SAMPLES_AMPLITUDES[len - 1 - k]);

int index = ct.StartSampleIndex + k;

if (index >= 0 && index < totalSamples)

{

sinSamples[index] = (short)Math.Max(short.MinValue, Math.Min(short.MaxValue, sinValue));

mirroredSamples[index] = (short)Math.Max(short.MinValue, Math.Min(short.MaxValue, ct.LIST_OF_ALL_ACTUAL_FLOATING_VALUES_OF_SAMPLES_AMPLITUDES[len - 1 - k]));

}

color = ct.IsCrest ? 5 : 1;

float radius = Math.Max(1f, (ct.EndSampleIndex - ct.StartSampleIndex) / 10f);

sw.WriteLine($"0\nCIRCLE\n8\n0\n62\n{color}\n10\n{cx:F3}\n20\n{cy:F3}\n30\n0\n40\n{radius:F3}");

sw.WriteLine($"0\nTEXT\n8\n0\n62\n{color}\n10\n{cx:F3}\n20\n{cy:F3}\n30\n0\n40\n{radius:F3}\n1\n#i={i}___{factor}");

}

sw.WriteLine("0\nENDSEC\n0\nEOF");

}

string folder = Path.GetDirectoryName(wavPath);

string fileNameWithoutExt = Path.GetFileNameWithoutExtension(wavPath);

WriteMono16BitPCM_WAV(Path.Combine(folder, fileNameWithoutExt + "__RECONSTRUCTED_FROM_SINE_AABB_ONLY.wav"), sinSamples, 8000);

WriteMono16BitPCM_WAV(Path.Combine(folder, fileNameWithoutExt + "__RECONSTRUCTED_FROM_MIRRORED_AABB_ONLY.wav"), mirroredSamples, 8000);

}// public static void CALL_THIS_BEFORE_GENERATING___RANKED_WAV_FILES___ExportDxf_With_CREST_TROUGH_COUNTER_AS_Y_VALUES___SAAN_STYLES_SINGLE_OUTER_GRAPH_SAANS_NORMALIZED_SCALED_TO_MAX_WIDTH_CG_X_DATABoxesAndText(List<CrestTroughObject> crestTroughs, string wavPath)

{

//////short[] sinSamples;

//////short[] mirroredSamples;

float[] sinSamples;

float[] mirroredSamples;

string path = Path.ChangeExtension(wavPath, "__crest_trough_counter_as_y_scaling_NORMALIZED_SCALED_TO_MAX_WIDTH_CG_X_DATA.dxf");

using (StreamWriter sw = new StreamWriter(path))

{

sw.WriteLine("0\nSECTION\n2\nENTITIES");

float left = 0f, right = w, top = h, bottom = -h;

int color = 6;

float center_x = w / 2;

sw.WriteLine($"0\nLINE\n8\n0\n62\n{color}\n10\n{left:F3}\n20\n{top:F3}\n30\n0\n11\n{right:F3}\n21\n{top:F3}\n31\n0");

sw.WriteLine($"0\nLINE\n8\n0\n62\n{color}\n10\n{left:F3}\n20\n{bottom:F3}\n30\n0\n11\n{right:F3}\n21\n{bottom:F3}\n31\n0");

sw.WriteLine($"0\nLINE\n8\n0\n62\n{color}\n10\n{left:F3}\n20\n{top:F3}\n30\n0\n11\n{left:F3}\n21\n{bottom:F3}\n31\n0");

sw.WriteLine($"0\nLINE\n8\n0\n62\n{color}\n10\n{right:F3}\n20\n{top:F3}\n30\n0\n11\n{right:F3}\n21\n{bottom:F3}\n31\n0");

sw.WriteLine($"0\nLINE\n8\n0\n62\n8\n10\n{left:F3}\n20\n0.000\n30\n0\n11\n{right:F3}\n21\n0.000\n31\n0");

sw.WriteLine($"0\nLINE\n8\n0\n62\n8\n10\n{center_x:F3}\n20\n{bottom:F3}\n30\n0\n11\n{center_x:F3}\n21\n{top:F3}\n31\n0");

int totalSamples = crestTroughs.Max(ct => ct.EndSampleIndex + 1);

int sampleRate = 8000;

sinSamples = new float[totalSamples]; ;// new short[totalSamples];

mirroredSamples = new float[totalSamples]; ;// new short[totalSamples];

for (int i = 0; i < crestTroughs.Count; i++)

{

CrestTroughObject ct = crestTroughs[i];

float _saans_x_width_scales_factor = (float)(w / ct.WidthMicroseconds);

float _saans_y_height_scales_factor = (float)(h / ct.HeightAmplitude);

float cx = (float)(_saans_x_width_scales_factor * ct.CG.X);

ct.PUBLIC_DOUBLE_NON_DUPLICATE_CG_X_FOR_SAAN_STYLES_NORMALIZATION_DONE_ON_GLOBAL_MAX_WIDH_OF_ALL_AABB_OBJECTS = cx;

float cy = ct.IsCrest ? ct.CG.Y : -Math.Abs(ct.CG.Y);

float preserved_cy = ct.IsCrest ? ct.CG.Y : -Math.Abs(ct.CG.Y);

int counter = (int)ct.OVERALL_AABB_COUNTER_EITHER_IT_IS_CREST_OR_IT_IS_TROUGH____COUNTER_TO_RECONSTRUCTION_THE_ACTUAL_QUEUE_STRUCTURE_FROM_THE_STACK_ANALYSIS_DATA;

float factor = (float)counter / crestTroughs.Count;

cy *= (factor * _saans_y_height_scales_factor);

ct.PUBLIC_DOUBLE_NON_DUPLICATE_CG_Y_FOR_SAAN_STYLES_NORMALIZATION_DONE_ON_GLOBAL_MAX_HEIGHTS_OF_ALL_AABB_OBJECTS = preserved_cy * _saans_y_height_scales_factor;

ct.LIST_OF_ALL_RECONSTRUCTED_SIN_WAVES_SAMPLES_FLOATING_VALUES_OF_SAMPLES_AMPLITUDES.Clear();

int len = ct.LIST_OF_ALL_ACTUAL_FLOATING_VALUES_OF_SAMPLES_AMPLITUDES.Count;

float[] normalizedSin = new float[len];

float sumSin = 0f;

for (int k = 0; k < len; k++)

{

normalizedSin[k] = (float)Math.Sin(2 * Math.PI * k / len);

sumSin += normalizedSin[k];

}//for (int k = 0; k < len; k++)

float avgSin = sumSin / len;

float desiredAvgY = ct.CG.Y;

float amplitude = ct.MaxAmplitude;

float offset = desiredAvgY - (avgSin * amplitude);

for (int k = 0; k < len; k++)

{

float val = amplitude * normalizedSin[k] + offset;

ct.LIST_OF_ALL_RECONSTRUCTED_SIN_WAVES_SAMPLES_FLOATING_VALUES_OF_SAMPLES_AMPLITUDES.Add(val);

float mirroredVal = ct.LIST_OF_ALL_ACTUAL_FLOATING_VALUES_OF_SAMPLES_AMPLITUDES[len - 1 - k];

int index = ct.StartSampleIndex + k;

if (index >= 0 && index < totalSamples)

{

//////sinSamples[index] = (short)Math.Max(short.MinValue, Math.Min(short.MaxValue, val));

//////mirroredSamples[index] = (short)Math.Max(short.MinValue, Math.Min(short.MaxValue, mirroredVal));

///

sinSamples[index] = (float)Math.Max(float.MinValue, Math.Min(float.MaxValue, val));

mirroredSamples[index] = (float)Math.Max(float.MinValue, Math.Min(float.MaxValue, mirroredVal));

}

color = ct.IsCrest ? 5 : 1;

float radius = Math.Max(1f, (ct.EndSampleIndex - ct.StartSampleIndex) / 10f);

sw.WriteLine($"0\nCIRCLE\n8\n0\n62\n{color}\n10\n{cx:F3}\n20\n{cy:F3}\n30\n0\n40\n{radius:F3}");

sw.WriteLine($"0\nTEXT\n8\n0\n62\n{color}\n10\n{cx:F3}\n20\n{cy:F3}\n30\n0\n40\n{radius:F3}\n1\n#i={i}___{factor}");

}

sw.WriteLine("0\nENDSEC\n0\nEOF");

}

string folder = Path.GetDirectoryName(wavPath);

string fileNameWithoutExt = Path.GetFileNameWithoutExtension(wavPath);

WriteMono16BitPCM_WAV(Path.Combine(folder, fileNameWithoutExt + "__RECONSTRUCTED_FROM_SINE_AABB_ONLY.wav"), sinSamples, 8000);

WriteMono16BitPCM_WAV(Path.Combine(folder, fileNameWithoutExt + "__RECONSTRUCTED_FROM_MIRRORED_AABB_ONLY.wav"), mirroredSamples, 8000);

its working and short data type is changed to float to get better bit depth cant we rewriute this to take floating point arrays for better bit depths?????????? public static void WriteMono16BitPCM_WAV(string outPath, short[] outputSamples, int sampleRate) { int byteRate = sampleRate * 2; // mono, 16-bit = 2 bytes per sample int subchunk2Size = outputSamples.Length * 2; int chunkSize = 36 + subchunk2Size; using (BinaryWriter bw = new BinaryWriter(File.Create(outPath))) { // RIFF header bw.Write(System.Text.Encoding.ASCII.GetBytes("RIFF")); bw.Write(chunkSize); bw.Write(System.Text.Encoding.ASCII.GetBytes("WAVE")); // fmt subchunk bw.Write(System.Text.Encoding.ASCII.GetBytes("fmt ")); bw.Write(16); // PCM bw.Write((short)1); // audio format = 1 (PCM) bw.Write((short)1); // mono bw.Write(sampleRate); bw.Write(byteRate); bw.Write((short)2); // block align = numChannels * bitsPerSample/8 bw.Write((short)16); // bits per sample // data subchunk bw.Write(System.Text.Encoding.ASCII.GetBytes("data")); bw.Write(subchunk2Size); foreach (short sample in outputSamples) { bw.Write(sample); }//foreach (short sample in outputSamples) }//using (BinaryWriter bw = new BinaryWriter(File.Create(outPath))) }//public static void WriteMono16BitPCM_WAV(string outPath, short[] outputSamples, int sampleRate)

ChatGPT said:

Yes, to support higher bit depth or full precision, you can write 32-bit float PCM WAV instead of 16-bit integer PCM. This allows storing raw float amplitudes directly (typically in range -1.0 to +1.0), giving better dynamic range and fidelity.

Below is a modified version of your method, preserving your structure, but outputting mono 32-bit IEEE floating-point WAV format (audio format code 3):

________________________________________

✅ WriteMono32BitFloatPCM_WAV

csharp

CopyEdit

public static void WriteMono32BitFloatPCM_WAV(string outPath, float[] outputSamples, int sampleRate)

{

int byteRate = sampleRate * 4; // mono, 32-bit float = 4 bytes per sample

int subchunk2Size = outputSamples.Length * 4;

int chunkSize = 36 + subchunk2Size;

using (BinaryWriter bw = new BinaryWriter(File.Create(outPath)))

{

// RIFF header

bw.Write(System.Text.Encoding.ASCII.GetBytes("RIFF"));

bw.Write(chunkSize);

bw.Write(System.Text.Encoding.ASCII.GetBytes("WAVE"));

// fmt subchunk (format code 3 = IEEE float)

bw.Write(System.Text.Encoding.ASCII.GetBytes("fmt "));

bw.Write(16); // Subchunk1Size

bw.Write((short)3); // AudioFormat = 3 (float)

bw.Write((short)1); // NumChannels = 1 (mono)

bw.Write(sampleRate);

bw.Write(byteRate);

bw.Write((short)4); // BlockAlign = NumChannels * BitsPerSample/8

bw.Write((short)32); // BitsPerSample = 32 (float)

// data subchunk

bw.Write(System.Text.Encoding.ASCII.GetBytes("data"));

bw.Write(subchunk2Size);

foreach (float sample in outputSamples)

{

bw.Write(sample);

}

________________________________________

🔁 Usage Example

Assuming your reconstructed amplitudes are in the range [-1.0f, +1.0f], call:

csharp

CopyEdit

WriteMono32BitFloatPCM_WAV("out_float.wav", floatArray, 8000);

________________________________________

📌 Notes

• Float WAVs are supported by many tools (Audacity, MATLAB, Reaper, etc).

• If needed, normalize the float array to ensure values stay within [-1, +1].

• No clipping or quantization happens as in 16-bit PCM.

Let me know if you want a combined version that auto-selects between 16-bit and 32-bit based on input array type.

rewrite it with normalizations

ChatGPT said:

Here is the rewritten function WriteMono32BitFloatPCM_WAV_WithNormalization that:

• Writes 32-bit float PCM WAV format.

• Automatically normalizes the float samples to the range [-1.0f, +1.0f] if needed.

• Preserves your original structure and naming conventions.

________________________________________

✅ Final Function

csharp

CopyEdit

public static void WriteMono32BitFloatPCM_WAV_WithNormalization(string outPath, float[] outputSamples, int sampleRate)

{

// Step 1: Normalize if needed (avoid distortion/clipping)

float maxAbs = outputSamples.Max(x => Math.Abs(x));

float normalizationFactor = (maxAbs > 1.0f) ? (1.0f / maxAbs) : 1.0f;

// Step 2: Prepare WAV parameters

int byteRate = sampleRate * 4; // mono, 32-bit float = 4 bytes per sample

int subchunk2Size = outputSamples.Length * 4;

int chunkSize = 36 + subchunk2Size;

// Step 3: Write WAV file

using (BinaryWriter bw = new BinaryWriter(File.Create(outPath)))

{

// RIFF Header

bw.Write(System.Text.Encoding.ASCII.GetBytes("RIFF"));

bw.Write(chunkSize);

bw.Write(System.Text.Encoding.ASCII.GetBytes("WAVE"));

// fmt subchunk (for 32-bit float PCM)

bw.Write(System.Text.Encoding.ASCII.GetBytes("fmt "));

bw.Write(16); // Subchunk1Size

bw.Write((short)3); // AudioFormat = 3 (IEEE float)

bw.Write((short)1); // NumChannels = 1 (Mono)

bw.Write(sampleRate);

bw.Write(byteRate);

bw.Write((short)4); // BlockAlign

bw.Write((short)32); // BitsPerSample

// data subchunk

bw.Write(System.Text.Encoding.ASCII.GetBytes("data"));

bw.Write(subchunk2Size);

foreach (float sample in outputSamples)

{

bw.Write(sample * normalizationFactor);

}

________________________________________

📌 Key Benefits

• ✔ No distortion: Automatically rescales large amplitudes if they exceed [-1.0, +1.0].

• ✔ Preserves structure: Matches your original formatting and block organization.

• ✔ Safe: Handles any float range safely before writing.

________________________________________

Let me know if you’d also like the inverse reader function (to load 32-bit float WAV into float[]) or if you want a 24-bit integer version too.

we know from our theory that if the samples are constructed with Sin forms then it sounds like flutes but the CG preserving AABB objects with Sin waves reconstructions are not listened like flutes ???????????? why ??????????? are the reconstruction not looks like flutes samples????????? public static void CALL_THIS_BEFORE_GENERATING___RANKED_WAV_FILES___ExportDxf_With_CREST_TROUGH_COUNTER_AS_Y_VALUES___SAAN_STYLES_SINGLE_OUTER_GRAPH_SAANS_NORMALIZED_SCALED_TO_MAX_WIDTH_CG_X_DATABoxesAndText(List<CrestTroughObject> crestTroughs, string wavPath)

{

//////short[] sinSamples;

//////short[] mirroredSamples;

float[] sinSamples;

float[] mirroredSamples;

string path = Path.ChangeExtension(wavPath, "__crest_trough_counter_as_y_scaling_NORMALIZED_SCALED_TO_MAX_WIDTH_CG_X_DATA.dxf");

using (StreamWriter sw = new StreamWriter(path))

{

sw.WriteLine("0\nSECTION\n2\nENTITIES");

float left = 0f, right = w, top = h, bottom = -h;

int color = 6;

float center_x = w / 2;

sw.WriteLine($"0\nLINE\n8\n0\n62\n{color}\n10\n{left:F3}\n20\n{top:F3}\n30\n0\n11\n{right:F3}\n21\n{top:F3}\n31\n0");

sw.WriteLine($"0\nLINE\n8\n0\n62\n{color}\n10\n{left:F3}\n20\n{bottom:F3}\n30\n0\n11\n{right:F3}\n21\n{bottom:F3}\n31\n0");

sw.WriteLine($"0\nLINE\n8\n0\n62\n{color}\n10\n{left:F3}\n20\n{top:F3}\n30\n0\n11\n{left:F3}\n21\n{bottom:F3}\n31\n0");

sw.WriteLine($"0\nLINE\n8\n0\n62\n{color}\n10\n{right:F3}\n20\n{top:F3}\n30\n0\n11\n{right:F3}\n21\n{bottom:F3}\n31\n0");

sw.WriteLine($"0\nLINE\n8\n0\n62\n8\n10\n{left:F3}\n20\n0.000\n30\n0\n11\n{right:F3}\n21\n0.000\n31\n0");

sw.WriteLine($"0\nLINE\n8\n0\n62\n8\n10\n{center_x:F3}\n20\n{bottom:F3}\n30\n0\n11\n{center_x:F3}\n21\n{top:F3}\n31\n0");

int totalSamples = crestTroughs.Max(ct => ct.EndSampleIndex + 1);

int sampleRate = 8000;

sinSamples = new float[totalSamples]; ;// new short[totalSamples];

mirroredSamples = new float[totalSamples]; ;// new short[totalSamples];

for (int i = 0; i < crestTroughs.Count; i++)

{

CrestTroughObject ct = crestTroughs[i];

float _saans_x_width_scales_factor = (float)(w / ct.WidthMicroseconds);

float _saans_y_height_scales_factor = (float)(h / ct.HeightAmplitude);

float cx = (float)(_saans_x_width_scales_factor * ct.CG.X);

ct.PUBLIC_DOUBLE_NON_DUPLICATE_CG_X_FOR_SAAN_STYLES_NORMALIZATION_DONE_ON_GLOBAL_MAX_WIDH_OF_ALL_AABB_OBJECTS = cx;

float cy = ct.IsCrest ? ct.CG.Y : -Math.Abs(ct.CG.Y);

float preserved_cy = ct.IsCrest ? ct.CG.Y : -Math.Abs(ct.CG.Y);

int counter = (int)ct.OVERALL_AABB_COUNTER_EITHER_IT_IS_CREST_OR_IT_IS_TROUGH____COUNTER_TO_RECONSTRUCTION_THE_ACTUAL_QUEUE_STRUCTURE_FROM_THE_STACK_ANALYSIS_DATA;

float factor = (float)counter / crestTroughs.Count;

cy *= (factor * _saans_y_height_scales_factor);

ct.PUBLIC_DOUBLE_NON_DUPLICATE_CG_Y_FOR_SAAN_STYLES_NORMALIZATION_DONE_ON_GLOBAL_MAX_HEIGHTS_OF_ALL_AABB_OBJECTS = preserved_cy * _saans_y_height_scales_factor;

ct.LIST_OF_ALL_RECONSTRUCTED_SIN_WAVES_SAMPLES_FLOATING_VALUES_OF_SAMPLES_AMPLITUDES.Clear();

int len = ct.LIST_OF_ALL_ACTUAL_FLOATING_VALUES_OF_SAMPLES_AMPLITUDES.Count;

float[] normalizedSin = new float[len];

float sumSin = 0f;

for (int k = 0; k < len; k++)

{

normalizedSin[k] = (float)Math.Sin(2 * Math.PI * k / len);

sumSin += normalizedSin[k];

}//for (int k = 0; k < len; k++)

float avgSin = sumSin / len;

float desiredAvgY = ct.CG.Y;

float amplitude = ct.MaxAmplitude;

float offset = desiredAvgY - (avgSin * amplitude);

for (int k = 0; k < len; k++)

{

float val = amplitude * normalizedSin[k] + offset;

ct.LIST_OF_ALL_RECONSTRUCTED_SIN_WAVES_SAMPLES_FLOATING_VALUES_OF_SAMPLES_AMPLITUDES.Add(val);

float mirroredVal = ct.LIST_OF_ALL_ACTUAL_FLOATING_VALUES_OF_SAMPLES_AMPLITUDES[len - 1 - k];

int index = ct.StartSampleIndex + k;

if (index >= 0 && index < totalSamples)

{

//////sinSamples[index] = (short)Math.Max(short.MinValue, Math.Min(short.MaxValue, val));

//////mirroredSamples[index] = (short)Math.Max(short.MinValue, Math.Min(short.MaxValue, mirroredVal));

///

sinSamples[index] = (float)Math.Max(float.MinValue, Math.Min(float.MaxValue, val));

mirroredSamples[index] = (float)Math.Max(float.MinValue, Math.Min(float.MaxValue, mirroredVal));

}

color = ct.IsCrest ? 5 : 1;

float radius = Math.Max(1f, (ct.EndSampleIndex - ct.StartSampleIndex) / 10f);

sw.WriteLine($"0\nCIRCLE\n8\n0\n62\n{color}\n10\n{cx:F3}\n20\n{cy:F3}\n30\n0\n40\n{radius:F3}");

sw.WriteLine($"0\nTEXT\n8\n0\n62\n{color}\n10\n{cx:F3}\n20\n{cy:F3}\n30\n0\n40\n{radius:F3}\n1\n#i={i}___{factor}");

}

sw.WriteLine("0\nENDSEC\n0\nEOF");

}

string folder = Path.GetDirectoryName(wavPath);

string fileNameWithoutExt = Path.GetFileNameWithoutExtension(wavPath);

//////WriteMono16BitPCM_WAV(Path.Combine(folder, fileNameWithoutExt + "__RECONSTRUCTED_FROM_SINE_AABB_ONLY.wav"), sinSamples, 8000);

//////WriteMono16BitPCM_WAV(Path.Combine(folder, fileNameWithoutExt + "__RECONSTRUCTED_FROM_MIRRORED_AABB_ONLY.wav"), mirroredSamples, 8000);

WriteMono32BitFloatPCM_WAV_WithNormalization(Path.Combine(folder, fileNameWithoutExt + "__RECONSTRUCTED_FROM_SINE_AABB_ONLY.wav"), sinSamples, 8000);

WriteMono32BitFloatPCM_WAV_WithNormalization(Path.Combine(folder, fileNameWithoutExt + "__RECONSTRUCTED_FROM_MIRRORED_AABB_ONLY.wav"), mirroredSamples, 8000);

Your observation is very sharp and fundamental to Sanjoy Nath's Qhenomenology theory of waveforms. Let's analyze the exact reason why the CG-preserving AABB-based sin wave reconstructions don't sound like a real flute, even though they are composed of sinusoids.

________________________________________

🎯 Why CG-preserving sinusoidal reconstructions don't sound like flutes

🔍 1. True flute sounds are not just CG-matched sine waves

Even though you're adjusting the amplitude and offset of sine waves inside each AABB to match CGₓ and CGᵧ, this does not ensure phase continuity, timbral continuity, or harmonic content consistency across all AABBs. Real flute tones have:

• Smooth harmonic transitions between cycles.

• A coherent overtone structure (e.g., strong 2nd, weak 3rd, etc.).

• A modulated envelope with rise (attack), hold (sustain), fall (decay).

Your method forces each AABB to act like an isolated "CG box" and resets the phase and shape independently. This creates:

• Phase discontinuities between AABBs.

• Unrealistic harmonic structure.

• Mechanical, artificial transitions.

👉 So, even though every cycle looks like a sinusoid and even preserves CG, the overall signal lacks the acoustic "body" of real instruments like a flute.

________________________________________

🔍 2. CG preservation is a scalar constraint — not a waveform shaping principle

Matching the CG_X and CG_Y means you're enforcing:

• The average horizontal position of energy (sample index-wise).

• The average vertical centroid of amplitude (volume-wise).

But flutes don’t organize sound purely by CG. Instead, they express:

• Dynamic variation of energy spread.

• Real-time air turbulence, which alters higher harmonics.

• Breath-induced envelope changes (vibrato, flutter, etc.).

👉 CG is a macro-level constraint, whereas flute timbre needs micro-level continuous control of waveform shaping.

________________________________________

🔍 3. In your model, each AABB is reconstructed in isolation

Your system processes each CrestTroughObject independently:

csharp

CopyEdit

for each CrestTroughObject:

generate sin curve such that CG is preserved

This breaks continuity across the full signal:

• Phase resets at every segment.

• Envelope disconnects between AABBs.

• No smooth cross-AABB blending.

A real flute:

• Uses phase-locked oscillations.

• Glides naturally in waveform transitions.

• Builds wave-packet coherence across long durations.

________________________________________

✅ Suggestions to make reconstructed signal flute-like

1. Link phases across AABBs: Ensure each AABB continues from the last phase value of the previous AABB.

2. Use a vibrato envelope: Modulate amplitude with a smooth low-frequency sine:

csharp

CopyEdit

amp *= 1.0f + 0.05f * MathF.Sin(2 * MathF.PI * vibratoHz * t);

3. Introduce harmonic overtones: Instead of 1 sine, blend 2–4 sinusoids with amplitudes:

csharp

CopyEdit

val = a1 * sin(θ) + a2 * sin(2θ) + a3 * sin(3θ)...

4. Use real flute spectral profiles: Instead of MaxAmplitude, sample from actual flute sample envelopes and modulate sinusoids accordingly.

5. Apply temporal envelope (ADSR) inside each AABB:

o Apply fade-in/fade-out instead of flat sin cycle.

________________________________________

🔚 Final Summary

Your CG-preserving sin-wave reconstruction is mathematically correct but musically discontinuous.

• It satisfies geometry (CG), but not continuity or natural acoustics.

• It misses phase flow, overtone blending, and harmonic gluing, which give flutes their human-like sound.

To sound like a flute:

• Enforce CG globally, not locally.

• Add modulated harmonics and envelope shapes.

• Make wave transitions phase-continuous and coherent.

Let me know if you want a code example with harmonic layering + phase continuity to make a better flute synthesizer using your AABB model.

Then rewrite the whole code preserving CG_X , CG_y of the cresttroughAABB object (all these are calculated and kept in the object ... the output of reconstructed wav file need to feel like flute but all other crest trough CG_X,CG_Y , spectrums need to give same output as per the theory says public static void CALL_THIS_BEFORE_GENERATING___RANKED_WAV_FILES___ExportDxf_With_CREST_TROUGH_COUNTER_AS_Y_VALUES___SAAN_STYLES_SINGLE_OUTER_GRAPH_SAANS_NORMALIZED_SCALED_TO_MAX_WIDTH_CG_X_DATABoxesAndText(List<CrestTroughObject> crestTroughs, string wavPath)

{

//////short[] sinSamples;

//////short[] mirroredSamples;

float[] sinSamples;

float[] mirroredSamples;

string path = Path.ChangeExtension(wavPath, "__crest_trough_counter_as_y_scaling_NORMALIZED_SCALED_TO_MAX_WIDTH_CG_X_DATA.dxf");

using (StreamWriter sw = new StreamWriter(path))

{

sw.WriteLine("0\nSECTION\n2\nENTITIES");

float left = 0f, right = w, top = h, bottom = -h;

int color = 6;

float center_x = w / 2;

sw.WriteLine($"0\nLINE\n8\n0\n62\n{color}\n10\n{left:F3}\n20\n{top:F3}\n30\n0\n11\n{right:F3}\n21\n{top:F3}\n31\n0");

sw.WriteLine($"0\nLINE\n8\n0\n62\n{color}\n10\n{left:F3}\n20\n{bottom:F3}\n30\n0\n11\n{right:F3}\n21\n{bottom:F3}\n31\n0");

sw.WriteLine($"0\nLINE\n8\n0\n62\n{color}\n10\n{left:F3}\n20\n{top:F3}\n30\n0\n11\n{left:F3}\n21\n{bottom:F3}\n31\n0");

sw.WriteLine($"0\nLINE\n8\n0\n62\n{color}\n10\n{right:F3}\n20\n{top:F3}\n30\n0\n11\n{right:F3}\n21\n{bottom:F3}\n31\n0");

sw.WriteLine($"0\nLINE\n8\n0\n62\n8\n10\n{left:F3}\n20\n0.000\n30\n0\n11\n{right:F3}\n21\n0.000\n31\n0");

sw.WriteLine($"0\nLINE\n8\n0\n62\n8\n10\n{center_x:F3}\n20\n{bottom:F3}\n30\n0\n11\n{center_x:F3}\n21\n{top:F3}\n31\n0");

int totalSamples = crestTroughs.Max(ct => ct.EndSampleIndex + 1);

int sampleRate = 8000;

sinSamples = new float[totalSamples]; ;// new short[totalSamples];

mirroredSamples = new float[totalSamples]; ;// new short[totalSamples];

for (int i = 0; i < crestTroughs.Count; i++)

{

CrestTroughObject ct = crestTroughs[i];

float _saans_x_width_scales_factor = (float)(w / ct.WidthMicroseconds);

float _saans_y_height_scales_factor = (float)(h / ct.HeightAmplitude);

float cx = (float)(_saans_x_width_scales_factor * ct.CG.X);

ct.PUBLIC_DOUBLE_NON_DUPLICATE_CG_X_FOR_SAAN_STYLES_NORMALIZATION_DONE_ON_GLOBAL_MAX_WIDH_OF_ALL_AABB_OBJECTS = cx;

float cy = ct.IsCrest ? ct.CG.Y : -Math.Abs(ct.CG.Y);

float preserved_cy = ct.IsCrest ? ct.CG.Y : -Math.Abs(ct.CG.Y);

int counter = (int)ct.OVERALL_AABB_COUNTER_EITHER_IT_IS_CREST_OR_IT_IS_TROUGH____COUNTER_TO_RECONSTRUCTION_THE_ACTUAL_QUEUE_STRUCTURE_FROM_THE_STACK_ANALYSIS_DATA;

float factor = (float)counter / crestTroughs.Count;

cy *= (factor * _saans_y_height_scales_factor);

ct.PUBLIC_DOUBLE_NON_DUPLICATE_CG_Y_FOR_SAAN_STYLES_NORMALIZATION_DONE_ON_GLOBAL_MAX_HEIGHTS_OF_ALL_AABB_OBJECTS = preserved_cy * _saans_y_height_scales_factor;

ct.LIST_OF_ALL_RECONSTRUCTED_SIN_WAVES_SAMPLES_FLOATING_VALUES_OF_SAMPLES_AMPLITUDES.Clear();

int len = ct.LIST_OF_ALL_ACTUAL_FLOATING_VALUES_OF_SAMPLES_AMPLITUDES.Count;

float[] normalizedSin = new float[len];

float sumSin = 0f;

for (int k = 0; k < len; k++)

{

normalizedSin[k] = (float)Math.Sin(2 * Math.PI * k / len);

sumSin += normalizedSin[k];

}//for (int k = 0; k < len; k++)

float avgSin = sumSin / len;

float desiredAvgY = ct.CG.Y;

float amplitude = ct.MaxAmplitude;

float offset = desiredAvgY - (avgSin * amplitude);

for (int k = 0; k < len; k++)

{

float val = amplitude * normalizedSin[k] + offset;

ct.LIST_OF_ALL_RECONSTRUCTED_SIN_WAVES_SAMPLES_FLOATING_VALUES_OF_SAMPLES_AMPLITUDES.Add(val);

float mirroredVal = ct.LIST_OF_ALL_ACTUAL_FLOATING_VALUES_OF_SAMPLES_AMPLITUDES[len - 1 - k];

int index = ct.StartSampleIndex + k;

if (index >= 0 && index < totalSamples)

{

//////sinSamples[index] = (short)Math.Max(short.MinValue, Math.Min(short.MaxValue, val));

//////mirroredSamples[index] = (short)Math.Max(short.MinValue, Math.Min(short.MaxValue, mirroredVal));

///

sinSamples[index] = (float)Math.Max(float.MinValue, Math.Min(float.MaxValue, val));

mirroredSamples[index] = (float)Math.Max(float.MinValue, Math.Min(float.MaxValue, mirroredVal));

}

color = ct.IsCrest ? 5 : 1;

float radius = Math.Max(1f, (ct.EndSampleIndex - ct.StartSampleIndex) / 10f);

sw.WriteLine($"0\nCIRCLE\n8\n0\n62\n{color}\n10\n{cx:F3}\n20\n{cy:F3}\n30\n0\n40\n{radius:F3}");

sw.WriteLine($"0\nTEXT\n8\n0\n62\n{color}\n10\n{cx:F3}\n20\n{cy:F3}\n30\n0\n40\n{radius:F3}\n1\n#i={i}___{factor}");

}

sw.WriteLine("0\nENDSEC\n0\nEOF");

}

string folder = Path.GetDirectoryName(wavPath);

string fileNameWithoutExt = Path.GetFileNameWithoutExtension(wavPath);

//////WriteMono16BitPCM_WAV(Path.Combine(folder, fileNameWithoutExt + "__RECONSTRUCTED_FROM_SINE_AABB_ONLY.wav"), sinSamples, 8000);

//////WriteMono16BitPCM_WAV(Path.Combine(folder, fileNameWithoutExt + "__RECONSTRUCTED_FROM_MIRRORED_AABB_ONLY.wav"), mirroredSamples, 8000);

WriteMono32BitFloatPCM_WAV_WithNormalization(Path.Combine(folder, fileNameWithoutExt + "__RECONSTRUCTED_FROM_SINE_AABB_ONLY.wav"), sinSamples, 8000);

WriteMono32BitFloatPCM_WAV_WithNormalization(Path.Combine(folder, fileNameWithoutExt + "__RECONSTRUCTED_FROM_MIRRORED_AABB_ONLY.wav"), mirroredSamples, 8000);

//////////CrestTroughAnalyzer___SANJOY_NATHS_QHENOMENOLOGY_REASONING_SYSTEMS_DISMANTLES_ANY_WAVES_TO_CREST_AABB_TRANSPARENT_RECTANGLES_TROUGH_AABB_TRANSPARENT_RECTANGLES_AND_STACK_THESE_TRANSPARENT_AABB_RECTANGLES_ONE_ABOVE_ANOTHER_GETS_VERTICAL_STRIPS_OF_CG_TRACINGS_ON_TRACING_PAPER_STACKS_BITMAPS_DXF_CSV_REPORTS

////////public static double PUBLIC_STATIC_DOUBLE_SUM_OF_ALL_SAMPLES_AMPLITUDES_IN_THE_WHOLE_WAV_FILE___10000_TIMES = 0;

////////public static double PUBLIC_STATIC_DOUBLE_AVERAGE_OF_ALL_SAMPLES_AMPLITUDES_IN_THE_WHOLE_WAV_FILE___10000_TIMES = 0;

//////CrestTroughAnalyzer___SANJOY_NATHS_QHENOMENOLOGY_REASONING_SYSTEMS_DISMANTLES_ANY_WAVES_TO_CREST_AABB_TRANSPARENT_RECTANGLES_TROUGH_AABB_TRANSPARENT_RECTANGLES_AND_STACK_THESE_TRANSPARENT_AABB_RECTANGLES_ONE_ABOVE_ANOTHER_GETS_VERTICAL_STRIPS_OF_CG_TRACINGS_ON_TRACING_PAPER_STACKS_BITMAPS_DXF_CSV_REPORTS

//////.

//////PUBLIC_STATIC_DOUBLE_SUM_OF_ALL_SAMPLES_AMPLITUDES_IN_THE_WHOLE_WAV_FILE___10000_TIMES

//////=

//////.

//////PUBLIC_STATIC_DOUBLE_SUM_OF_ALL_SAMPLES_AMPLITUDES_IN_THE_WHOLE_WAV_FILE___10000_TIMES

//////+ (double)(seg[j] * 10000f);

/////////////////////////////////////////////////////////////////////////

.PUBLIC_STATIC_FLOAT_ARRAY____RECONSTRUCTED_FLOATING_ARRAY_OF_WHOLE_FILES_ZERO_LINES_SHIFTED_TO_AVERAGES

= new float

[

.PUBLIC_STATIC_INT_TOTAL_NUMBER_OF_SAMPLES_IN_THIS_FILE

];

//////////////////////////////////////////////////////////////////////

.PUBLIC_STATIC_DOUBLE_AVERAGE_OF_ALL_SAMPLES_AMPLITUDES_IN_THE_WHOLE_WAV_FILE___10000_TIMES

.PUBLIC_STATIC_DOUBLE_SUM_OF_ALL_SAMPLES_AMPLITUDES_IN_THE_WHOLE_WAV_FILE___10000_TIMES

Math.Max

(

.PUBLIC_STATIC_INT_TOTAL_NUMBER_OF_SAMPLES_IN_THIS_FILE

);

/////////////////////////////////////////////////////////////////////////////////////////////

///

This function works fine and dont change the structure of the code ... it generates all perfect data... Write one additional function similar to this where i will get a report in csv to show crest_trough_overall_serial_number in column1 , x_wise_ascending_order_rank in column 2 , width of each ranked crest_trough_object in column 3 , total number of samples of concerned crest trough object in next columns ...refer this code public static void GenerateRankedSpectralWavFiles______DONT_CALL_THIS_BEFORE_ALL_DXF_PREPARED_SINCE_DXF_GENERATORS_POPULATE_SCALED_CG_X_DATA

(

List<CrestTroughObject> allCrestTroughObjects,

int totalSamples,

int sampleRate,

string inputFilePath

)

{

string outputFolder = Path.GetDirectoryName(inputFilePath);

StringBuilder ___strbldr = new StringBuilder();

___strbldr.Clear();

var rankedGroups = allCrestTroughObjects

.GroupBy(obj => Math.Round(obj.PUBLIC_DOUBLE_NON_DUPLICATE_CG_X_FOR_SAAN_STYLES_NORMALIZATION_DONE_ON_GLOBAL_MAX_WIDH_OF_ALL_AABB_OBJECTS, 6))

.OrderBy(g => g.Key)

.Select((group, rankIndex) => new

{

Rank = rankIndex + 1,

Objects = group.ToList()

})

.ToList();

double ___total_populated_samples_for_current_output_files = 0;

foreach (var group in rankedGroups)

{

foreach (var obj in group.Objects)

{

obj.PUBLIC_INT_NON_DUPLICATE_CG_X_RANKING_FOR_SAAN_STYLES_NORMALIZATION_DONE_ON_GLOBAL_MAX_WIDH_OF_ALL_AABB_OBJECTS = group.Rank;

}

/////////////////////////////////////////////////////////////////////////////////////////////////////////////////

foreach (var group in rankedGroups)

{

short[] outputSamples = new short[totalSamples];

___total_populated_samples_for_current_output_files = 0;

___strbldr.Clear();

foreach (var obj in group.Objects)

{

___strbldr.AppendLine

(

"CURRENT CREST_TROUGH_OBJECT OVERALL COUNTER = " + obj.OVERALL_AABB_COUNTER_EITHER_IT_IS_CREST_OR_IT_IS_TROUGH____COUNTER_TO_RECONSTRUCTION_THE_ACTUAL_QUEUE_STRUCTURE_FROM_THE_STACK_ANALYSIS_DATA

+"\r\n"+

"CURRENT CREST_TROUGH_OBJECT CREST COUNTER = " + obj.CREST_COUNTER

+ "\r\n" +

"CURRENT CREST_TROUGH_OBJECT TROUGH COUNTER = " + obj.TROUGH_COUNTER

+ "\r\n" +

"CURRENT CREST_TROUGH_OBJECT WIDTH MICROS = " + obj.WidthMicroseconds

+ "\r\n" +

"CURRENT CREST_TROUGH_OBJECT MaxAmplitude = " + obj.MaxAmplitude

+ "\r\n" +

"CURRENT CREST_TROUGH_OBJECT LocalMaximaCount = " + obj.LocalMaximaCount

+ "\r\n" +

"CURRENT CREST_TROUGH_OBJECT LocalMinimaCount = " + obj.LocalMinimaCount

+ "\r\n" +

"overall max width found in whole files = " +

.PUBLIC_STATIC_DOUBLE_MAX_WIDTH_MIKROSEC_FOUND_IN_OVERALL_IN_CRESTS_AND_TROUGHS

+ "\r\n" +

"CURRENT CREST_TROUGH_OBJECT TotalSamples = " + (obj.EndSampleIndex-obj.StartSampleIndex + 1)

+ "\r\nRANK CG_X_NORMALIZED AMPS samplecounter"

);

int length = obj.EndSampleIndex - obj.StartSampleIndex + 1;

for (int i = 0; i < length; i++)

{

int sampleIndex = obj.StartSampleIndex + i;

if (sampleIndex >= 0 && sampleIndex < totalSamples)

{

float amplitude = obj.LIST_OF_ALL_ACTUAL_FLOATING_VALUES_OF_SAMPLES_AMPLITUDES[i];

___total_populated_samples_for_current_output_files++;

___strbldr.AppendLine

(

group.Rank + " " +

// obj.PUBLIC_INT_NON_DUPLICATE_CG_X_RANKING_FOR_SAAN_STYLES_NORMALIZATION_DONE_ON_GLOBAL_MAX_WIDH_OF_ALL_AABB_OBJECTS + " " +

obj.PUBLIC_DOUBLE_NON_DUPLICATE_CG_X_FOR_SAAN_STYLES_NORMALIZATION_DONE_ON_GLOBAL_MAX_WIDH_OF_ALL_AABB_OBJECTS + " " +

amplitude / 10000f + " " +

___total_populated_samples_for_current_output_files

);

outputSamples[sampleIndex] = (short)Math.Max(short.MinValue, Math.Min(short.MaxValue, amplitude));

}

string outFileName = $"RANKED_SPECTRAL_LINE_pushed_samples_{___total_populated_samples_for_current_output_files}_rank_{group.Rank:D3}.wav";

string outPath = Path.Combine(outputFolder, outFileName);

System.IO.File.WriteAllText(outPath + "_report.txt", ___strbldr.ToString());

if (___total_populated_samples_for_current_output_files > sampleRate)

{

// WriteMono16BitPCM_WAV(outPath, outputSamples, sampleRate);

WriteMono16BitPCM_WAV___takes_short_type_arrays(outPath, outputSamples, sampleRate);

}

// STEP 4: CLUBBED RANK WAV FILES

int[][] rankGroupsToClub = new int[][]

{

new int[] { 1, 2 },

new int[] { 1, 2, 3 },

new int[] { 1, 2, 3 ,4 },

new int[] { 1, 2, 3 ,4 ,5},

new int[] { 1, 2, 3, 4, 5, 6 },

new int[] { 1, 2, 3, 4, 5, 6 ,7},

new int[] { 1, 2, 3, 4, 5, 6, 7, 8 }

};

foreach (var rankSet in rankGroupsToClub)

{

short[] clubbedSamples = new short[totalSamples];

double totalClubbedSamples = 0;

StringBuilder reportBuilder = new StringBuilder();

foreach (var rank in rankSet)

{

var group = rankedGroups.FirstOrDefault(g => g.Rank == rank);

if (group == null) continue;

foreach (var obj in group.Objects)

{

int len = obj.EndSampleIndex - obj.StartSampleIndex + 1;

for (int i = 0; i < len; i++)

{

int sampleIndex = obj.StartSampleIndex + i;

if (sampleIndex >= 0 && sampleIndex < totalSamples)

{

float amplitude = obj.LIST_OF_ALL_ACTUAL_FLOATING_VALUES_OF_SAMPLES_AMPLITUDES[i];

clubbedSamples[sampleIndex] = (short)Math.Max(short.MinValue, Math.Min(short.MaxValue, amplitude));

totalClubbedSamples++;

reportBuilder.AppendLine(

"Rank_" + rank + " " +

obj.PUBLIC_INT_NON_DUPLICATE_CG_X_RANKING_FOR_SAAN_STYLES_NORMALIZATION_DONE_ON_GLOBAL_MAX_WIDH_OF_ALL_AABB_OBJECTS + " " +

(amplitude / 10000f).ToString("F6") + " " +

totalClubbedSamples.ToString("F0")

);

}

string label = "rank_" + string.Join("_", rankSet.Select(r => r.ToString("D2")));

string wavFilePath = Path.Combine(outputFolder, $"CLUBBED_RANKED_SPECTRAL_LINE_{label}.wav");

string reportFilePath = wavFilePath + "_report.txt";

System.IO.File.WriteAllText(reportFilePath, reportBuilder.ToString());

if (totalClubbedSamples > sampleRate)

{

/// WriteMono16BitPCM_WAV(wavFilePath, clubbedSamples, sampleRate);

WriteMono16BitPCM_WAV___takes_short_type_arrays(wavFilePath, clubbedSamples, sampleRate);

}

}//public static void GenerateRankedSpectralWavFiles______DONT_CALL_THIS_BEFORE_ALL_DXF_PREPARED_SINCE_DXF_GENERATORS_POPULATE_SCALED_CG_X_DATA

The CSV reporting function has been written as requested. It generates a file named CREST_TROUGH_RANKED_REPORT.csv with the following columns for each Crest/Trough object:

1. Overall_Serial_Number — from OVERALL_AABB_COUNTER_EITHER_IT_IS_CREST_OR_IT_IS_TROUGH____COUNTER_TO_RECONSTRUCTION_THE_ACTUAL_QUEUE_STRUCTURE_FROM_THE_STACK_ANALYSIS_DATA

2. Rank_X_CG_X_Order — X-wise ascending order rank

3. Width_Microseconds — the width of the Crest/Trough object

4. Sample_Count — number of samples spanned by the object (EndSampleIndex - StartSampleIndex + 1)

Let me know if you want to append more details like CG_X, CG_Y, or object type (crest/trough).

bUT IF I NEED oRDER bY oVERALL cREST tROUGH NUMBER???????????? public static void GenerateRankedSpectralCSVReport ( List<CrestTroughObject> allCrestTroughObjects, string inputFilePath ) { string outputFolder = Path.GetDirectoryName(inputFilePath); string csvReportPath = Path.Combine(outputFolder, "___CREST_TROUGH_COUNTER_TO_RANKED_REPORT.csv"); var rankedGroups = allCrestTroughObjects .GroupBy(obj => Math.Round(obj.PUBLIC_DOUBLE_NON_DUPLICATE_CG_X_FOR_SAAN_STYLES_NORMALIZATION_DONE_ON_GLOBAL_MAX_WIDH_OF_ALL_AABB_OBJECTS, 6)) .OrderBy(g => g.Key) .Select((group, rankIndex) => new { Rank = rankIndex + 1, Objects = group.ToList() }) .ToList(); foreach (var group in rankedGroups) { foreach (var obj in group.Objects) { obj.PUBLIC_INT_NON_DUPLICATE_CG_X_RANKING_FOR_SAAN_STYLES_NORMALIZATION_DONE_ON_GLOBAL_MAX_WIDH_OF_ALL_AABB_OBJECTS = group.Rank; } } StringBuilder csvBuilder = new StringBuilder(); csvBuilder.AppendLine("Overall_Serial_Number,Rank_X_CG_X_Order,Width_Microseconds,Sample_Count"); foreach (var group in rankedGroups) { foreach (var obj in group.Objects) { int sampleCount = obj.EndSampleIndex - obj.StartSampleIndex + 1; csvBuilder.AppendLine( obj.OVERALL_AABB_COUNTER_EITHER_IT_IS_CREST_OR_IT_IS_TROUGH____COUNTER_TO_RECONSTRUCTION_THE_ACTUAL_QUEUE_STRUCTURE_FROM_THE_STACK_ANALYSIS_DATA + "," + obj.PUBLIC_INT_NON_DUPLICATE_CG_X_RANKING_FOR_SAAN_STYLES_NORMALIZATION_DONE_ON_GLOBAL_MAX_WIDH_OF_ALL_AABB_OBJECTS + "," + obj.WidthMicroseconds + "," + sampleCount ); } } File.WriteAllText(csvReportPath, csvBuilder.ToString()); }// //////public static void GenerateRankedSpectralCSVReport //////( //////List<CrestTroughObject> allCrestTroughObjects, //////string inputFilePath //////)

ChatGPT said:

To generate the CSV report ordered by OVERALL_AABB_COUNTER_EITHER_IT_IS_CREST_OR_IT_IS_TROUGH, you just need to sort the final list after assigning the ranks but before appending to the CSV.

Here is your corrected function with no structural change, just sorting before writing the CSV rows:

csharp

CopyEdit

public static void GenerateRankedSpectralCSVReport

(

List<CrestTroughObject> allCrestTroughObjects,

string inputFilePath

)

{

string outputFolder = Path.GetDirectoryName(inputFilePath);

string csvReportPath = Path.Combine(outputFolder, "___CREST_TROUGH_COUNTER_TO_RANKED_REPORT.csv");

var rankedGroups = allCrestTroughObjects

.GroupBy(obj => Math.Round(obj.PUBLIC_DOUBLE_NON_DUPLICATE_CG_X_FOR_SAAN_STYLES_NORMALIZATION_DONE_ON_GLOBAL_MAX_WIDH_OF_ALL_AABB_OBJECTS, 6))

.OrderBy(g => g.Key)

.Select((group, rankIndex) => new

{

Rank = rankIndex + 1,

Objects = group.ToList()

})

.ToList();

foreach (var group in rankedGroups)

{

foreach (var obj in group.Objects)

{

obj.PUBLIC_INT_NON_DUPLICATE_CG_X_RANKING_FOR_SAAN_STYLES_NORMALIZATION_DONE_ON_GLOBAL_MAX_WIDH_OF_ALL_AABB_OBJECTS = group.Rank;

}

StringBuilder csvBuilder = new StringBuilder();

csvBuilder.AppendLine("Overall_Serial_Number,Rank_X_CG_X_Order,Width_Microseconds,Sample_Count");

var allRankedObjectsOrderedByOverallCounter = allCrestTroughObjects

.OrderBy(obj => obj.OVERALL_AABB_COUNTER_EITHER_IT_IS_CREST_OR_IT_IS_TROUGH____COUNTER_TO_RECONSTRUCTION_THE_ACTUAL_QUEUE_STRUCTURE_FROM_THE_STACK_ANALYSIS_DATA)

.ToList();

foreach (var obj in allRankedObjectsOrderedByOverallCounter)

{

int sampleCount = obj.EndSampleIndex - obj.StartSampleIndex + 1;

csvBuilder.AppendLine(

obj.OVERALL_AABB_COUNTER_EITHER_IT_IS_CREST_OR_IT_IS_TROUGH____COUNTER_TO_RECONSTRUCTION_THE_ACTUAL_QUEUE_STRUCTURE_FROM_THE_STACK_ANALYSIS_DATA + "," +

obj.PUBLIC_INT_NON_DUPLICATE_CG_X_RANKING_FOR_SAAN_STYLES_NORMALIZATION_DONE_ON_GLOBAL_MAX_WIDH_OF_ALL_AABB_OBJECTS + "," +

obj.WidthMicroseconds + "," +

sampleCount

);

}

File.WriteAllText(csvReportPath, csvBuilder.ToString());

}

✅ What changed?

Only this part:

csharp

CopyEdit

var allRankedObjectsOrderedByOverallCounter = allCrestTroughObjects

.OrderBy(obj => obj.OVERALL_AABB_COUNTER_EITHER_IT_IS_CREST_OR_IT_IS_TROUGH____COUNTER_TO_RECONSTRUCTION_THE_ACTUAL_QUEUE_STRUCTURE_FROM_THE_STACK_ANALYSIS_DATA)

.ToList();

This ensures your CSV rows are sorted by the original Crest/Trough overall serial order — as per your strict requirement — while still preserving the calculated CG-X-based rank.

public static void GenerateRankedSpectralCSVReport

(

List<CrestTroughObject> allCrestTroughObjects,

string inputFilePath

)

{

string outputFolder = Path.GetDirectoryName(inputFilePath);

string csvReportPath = Path.Combine(outputFolder, "___CREST_TROUGH_COUNTER_TO_RANKED_REPORT.csv");

var rankedGroups = allCrestTroughObjects

.GroupBy(obj => Math.Round(obj.PUBLIC_DOUBLE_NON_DUPLICATE_CG_X_FOR_SAAN_STYLES_NORMALIZATION_DONE_ON_GLOBAL_MAX_WIDH_OF_ALL_AABB_OBJECTS, 6))

.OrderBy(g => g.Key)

.Select((group, rankIndex) => new

{

Rank = rankIndex + 1,

Objects = group.ToList()

})

.ToList();

foreach (var group in rankedGroups)

{

foreach (var obj in group.Objects)

{

obj.PUBLIC_INT_NON_DUPLICATE_CG_X_RANKING_FOR_SAAN_STYLES_NORMALIZATION_DONE_ON_GLOBAL_MAX_WIDH_OF_ALL_AABB_OBJECTS = group.Rank;

}

StringBuilder csvBuilder = new StringBuilder();

csvBuilder.AppendLine("Overall_Serial_Number,Rank_X_CG_X_Order,Width_Microseconds,Sample_Count");

var allRankedObjectsOrderedByOverallCounter = allCrestTroughObjects

.OrderBy(obj => obj.OVERALL_AABB_COUNTER_EITHER_IT_IS_CREST_OR_IT_IS_TROUGH____COUNTER_TO_RECONSTRUCTION_THE_ACTUAL_QUEUE_STRUCTURE_FROM_THE_STACK_ANALYSIS_DATA)

.ToList();

foreach (var obj in allRankedObjectsOrderedByOverallCounter)

{

int sampleCount = obj.EndSampleIndex - obj.StartSampleIndex + 1;

csvBuilder.AppendLine(

obj.OVERALL_AABB_COUNTER_EITHER_IT_IS_CREST_OR_IT_IS_TROUGH____COUNTER_TO_RECONSTRUCTION_THE_ACTUAL_QUEUE_STRUCTURE_FROM_THE_STACK_ANALYSIS_DATA + "," +

obj.PUBLIC_INT_NON_DUPLICATE_CG_X_RANKING_FOR_SAAN_STYLES_NORMALIZATION_DONE_ON_GLOBAL_MAX_WIDH_OF_ALL_AABB_OBJECTS + "," +

obj.WidthMicroseconds + "," +

sampleCount

);

}

File.WriteAllText(csvReportPath, csvBuilder.ToString());

}

var allRankedObjectsOrderedByOverallCounter = allCrestTroughObjects

.OrderBy(obj => obj.OVERALL_AABB_COUNTER_EITHER_IT_IS_CREST_OR_IT_IS_TROUGH____COUNTER_TO_RECONSTRUCTION_THE_ACTUAL_QUEUE_STRUCTURE_FROM_THE_STACK_ANALYSIS_DATA)

.ToList();

This is Working properly and dont change the structure of the code and dont alter anything since it is working properly ... I need some additional clubbed outputs also for the last rank case clubbed with last to last rank ... upto last 8 ranked cases clubbed ......refer the working code public static void GenerateRankedSpectralWavFiles______DONT_CALL_THIS_BEFORE_ALL_DXF_PREPARED_SINCE_DXF_GENERATORS_POPULATE_SCALED_CG_X_DATA

(

List<CrestTroughObject> allCrestTroughObjects,

int totalSamples,

int sampleRate,

string inputFilePath

)

{

string outputFolder = Path.GetDirectoryName(inputFilePath);

StringBuilder ___strbldr = new StringBuilder();

___strbldr.Clear();

var rankedGroups = allCrestTroughObjects

.GroupBy(obj => Math.Round(obj.PUBLIC_DOUBLE_NON_DUPLICATE_CG_X_FOR_SAAN_STYLES_NORMALIZATION_DONE_ON_GLOBAL_MAX_WIDH_OF_ALL_AABB_OBJECTS, 6))

.OrderBy(g => g.Key)

.Select((group, rankIndex) => new

{

Rank = rankIndex + 1,

Objects = group.ToList()

})

.ToList();

double ___total_populated_samples_for_current_output_files = 0;

foreach (var group in rankedGroups)

{

foreach (var obj in group.Objects)

{

obj.PUBLIC_INT_NON_DUPLICATE_CG_X_RANKING_FOR_SAAN_STYLES_NORMALIZATION_DONE_ON_GLOBAL_MAX_WIDH_OF_ALL_AABB_OBJECTS = group.Rank;

}

/////////////////////////////////////////////////////////////////////////////////////////////////////////////////

foreach (var group in rankedGroups)

{

short[] outputSamples = new short[totalSamples];

___total_populated_samples_for_current_output_files = 0;

___strbldr.Clear();

foreach (var obj in group.Objects)

{

___strbldr.AppendLine

(

"CURRENT CREST_TROUGH_OBJECT OVERALL COUNTER = " + obj.OVERALL_AABB_COUNTER_EITHER_IT_IS_CREST_OR_IT_IS_TROUGH____COUNTER_TO_RECONSTRUCTION_THE_ACTUAL_QUEUE_STRUCTURE_FROM_THE_STACK_ANALYSIS_DATA

+"\r\n"+

"CURRENT CREST_TROUGH_OBJECT CREST COUNTER = " + obj.CREST_COUNTER

+ "\r\n" +

"CURRENT CREST_TROUGH_OBJECT TROUGH COUNTER = " + obj.TROUGH_COUNTER

+ "\r\n" +

"CURRENT CREST_TROUGH_OBJECT WIDTH MICROS = " + obj.WidthMicroseconds

+ "\r\n" +

"CURRENT CREST_TROUGH_OBJECT MaxAmplitude = " + obj.MaxAmplitude

+ "\r\n" +

"CURRENT CREST_TROUGH_OBJECT LocalMaximaCount = " + obj.LocalMaximaCount

+ "\r\n" +

"CURRENT CREST_TROUGH_OBJECT LocalMinimaCount = " + obj.LocalMinimaCount

+ "\r\n" +

"overall max width found in whole files = " +

.PUBLIC_STATIC_DOUBLE_MAX_WIDTH_MIKROSEC_FOUND_IN_OVERALL_IN_CRESTS_AND_TROUGHS

+ "\r\n" +

"CURRENT CREST_TROUGH_OBJECT TotalSamples = " + (obj.EndSampleIndex-obj.StartSampleIndex + 1)

+ "\r\nRANK CG_X_NORMALIZED AMPS samplecounter"

);

int length = obj.EndSampleIndex - obj.StartSampleIndex + 1;

for (int i = 0; i < length; i++)

{

int sampleIndex = obj.StartSampleIndex + i;

if (sampleIndex >= 0 && sampleIndex < totalSamples)

{

float amplitude = obj.LIST_OF_ALL_ACTUAL_FLOATING_VALUES_OF_SAMPLES_AMPLITUDES[i];

___total_populated_samples_for_current_output_files++;

___strbldr.AppendLine

(

group.Rank + " " +

// obj.PUBLIC_INT_NON_DUPLICATE_CG_X_RANKING_FOR_SAAN_STYLES_NORMALIZATION_DONE_ON_GLOBAL_MAX_WIDH_OF_ALL_AABB_OBJECTS + " " +

obj.PUBLIC_DOUBLE_NON_DUPLICATE_CG_X_FOR_SAAN_STYLES_NORMALIZATION_DONE_ON_GLOBAL_MAX_WIDH_OF_ALL_AABB_OBJECTS + " " +

amplitude / 10000f + " " +

___total_populated_samples_for_current_output_files

);

outputSamples[sampleIndex] = (short)Math.Max(short.MinValue, Math.Min(short.MaxValue, amplitude));

}

string outFileName = $"RANKED_SPECTRAL_LINE_pushed_samples_{___total_populated_samples_for_current_output_files}_rank_{group.Rank:D3}.wav";

string outPath = Path.Combine(outputFolder, outFileName);

System.IO.File.WriteAllText(outPath + "_report.txt", ___strbldr.ToString());

if (___total_populated_samples_for_current_output_files > sampleRate)

{

// WriteMono16BitPCM_WAV(outPath, outputSamples, sampleRate);

WriteMono16BitPCM_WAV___takes_short_type_arrays(outPath, outputSamples, sampleRate);

}

// STEP 4: CLUBBED RANK WAV FILES

int[][] rankGroupsToClub = new int[][]

{

new int[] { 1, 2 },

new int[] { 1, 2, 3 },

new int[] { 1, 2, 3 ,4 },

new int[] { 1, 2, 3 ,4 ,5},

new int[] { 1, 2, 3, 4, 5, 6 },

new int[] { 1, 2, 3, 4, 5, 6 ,7},

new int[] { 1, 2, 3, 4, 5, 6, 7, 8 }

};

foreach (var rankSet in rankGroupsToClub)

{

short[] clubbedSamples = new short[totalSamples];

double totalClubbedSamples = 0;

StringBuilder reportBuilder = new StringBuilder();

foreach (var rank in rankSet)

{

var group = rankedGroups.FirstOrDefault(g => g.Rank == rank);

if (group == null) continue;

foreach (var obj in group.Objects)

{

int len = obj.EndSampleIndex - obj.StartSampleIndex + 1;

for (int i = 0; i < len; i++)

{

int sampleIndex = obj.StartSampleIndex + i;

if (sampleIndex >= 0 && sampleIndex < totalSamples)

{

float amplitude = obj.LIST_OF_ALL_ACTUAL_FLOATING_VALUES_OF_SAMPLES_AMPLITUDES[i];

clubbedSamples[sampleIndex] = (short)Math.Max(short.MinValue, Math.Min(short.MaxValue, amplitude));

totalClubbedSamples++;

reportBuilder.AppendLine(

"Rank_" + rank + " " +

obj.PUBLIC_INT_NON_DUPLICATE_CG_X_RANKING_FOR_SAAN_STYLES_NORMALIZATION_DONE_ON_GLOBAL_MAX_WIDH_OF_ALL_AABB_OBJECTS + " " +

(amplitude / 10000f).ToString("F6") + " " +

totalClubbedSamples.ToString("F0")

);

}

string label = "rank_" + string.Join("_", rankSet.Select(r => r.ToString("D2")));

string wavFilePath = Path.Combine(outputFolder, $"CLUBBED_RANKED_SPECTRAL_LINE_{label}.wav");

string reportFilePath = wavFilePath + "_report.txt";

System.IO.File.WriteAllText(reportFilePath, reportBuilder.ToString());

if (totalClubbedSamples > sampleRate)

{

/// WriteMono16BitPCM_WAV(wavFilePath, clubbedSamples, sampleRate);

WriteMono16BitPCM_WAV___takes_short_type_arrays(wavFilePath, clubbedSamples, sampleRate);

}

}//public static void GenerateRankedSpectralWavFiles______DONT_CALL_THIS_BEFORE_ALL_DXF_PREPARED_SINCE_DXF_GENERATORS_POPULATE_SCALED_CG_X_DATA

Here is the additional C# code block you can insert after your current STEP 4 (clubbing) logic in the function, to generate the requested last-N-rank-clubbed WAV files (up to the last 8 ranks):

✅ This does not change your existing code, just appends new logic that clubs last 2 to last 8 ranked crest/trough objects.

________________________________________

csharp

CopyEdit

// STEP 5: ADDITIONAL CLUBBED OUTPUTS FOR LAST N RANKS (up to last 8)

int totalRanks = rankedGroups.Count;

for (int n = 2; n <= 8; n++)

{

if (n > totalRanks) break;

var lastRankSet = Enumerable.Range(totalRanks - n + 1, n).ToArray();

short[] clubbedSamples = new short[totalSamples];

double totalClubbedSamples = 0;

StringBuilder reportBuilder = new StringBuilder();

foreach (var rank in lastRankSet)

{

var group = rankedGroups.FirstOrDefault(g => g.Rank == rank);

if (group == null) continue;

foreach (var obj in group.Objects)

{

int len = obj.EndSampleIndex - obj.StartSampleIndex + 1;

for (int i = 0; i < len; i++)

{

int sampleIndex = obj.StartSampleIndex + i;

if (sampleIndex >= 0 && sampleIndex < totalSamples)

{

float amplitude = obj.LIST_OF_ALL_ACTUAL_FLOATING_VALUES_OF_SAMPLES_AMPLITUDES[i];

clubbedSamples[sampleIndex] = (short)Math.Max(short.MinValue, Math.Min(short.MaxValue, amplitude));

totalClubbedSamples++;

reportBuilder.AppendLine(

"Rank_" + rank + " " +

obj.PUBLIC_INT_NON_DUPLICATE_CG_X_RANKING_FOR_SAAN_STYLES_NORMALIZATION_DONE_ON_GLOBAL_MAX_WIDH_OF_ALL_AABB_OBJECTS + " " +

(amplitude / 10000f).ToString("F6") + " " +

totalClubbedSamples.ToString("F0")

);

}

string label = "last_" + n + "_ranks_" + string.Join("_", lastRankSet.Select(r => r.ToString("D2")));

string wavFilePath = Path.Combine(outputFolder, $"CLUBBED_LAST_RANKED_SPECTRAL_LINE_{label}.wav");

string reportFilePath = wavFilePath + "_report.txt";

System.IO.File.WriteAllText(reportFilePath, reportBuilder.ToString());

if (totalClubbedSamples > sampleRate)

{

WriteMono16BitPCM_WAV___takes_short_type_arrays(wavFilePath, clubbedSamples, sampleRate);

}

________________________________________

🔁 What it does:

• Loops for n = 2 to 8

• Picks last n rank groups

• Clubs them and generates:

o CLUBBED_LAST_RANKED_SPECTRAL_LINE_last_0X_..._0Y.wav

o ..._report.txt alongside each WAV

Let me know if you also want middle-ranked clubbing or mirrored-rank groups.

// STEP 5: ADDITIONAL CLUBBED OUTPUTS FOR LAST N RANKS (up to last 8)

int totalRanks = rankedGroups.Count;

for (int n = 2; n <= 8; n++)

{

if (n > totalRanks) break;

var lastRankSet = Enumerable.Range(totalRanks - n + 1, n).ToArray();

short[] clubbedSamples = new short[totalSamples];

double totalClubbedSamples = 0;

StringBuilder reportBuilder = new StringBuilder();

foreach (var rank in lastRankSet)

{

var group = rankedGroups.FirstOrDefault(g => g.Rank == rank);

if (group == null) continue;

foreach (var obj in group.Objects)

{

int len = obj.EndSampleIndex - obj.StartSampleIndex + 1;

for (int i = 0; i < len; i++)

{

int sampleIndex = obj.StartSampleIndex + i;

if (sampleIndex >= 0 && sampleIndex < totalSamples)

{

float amplitude = obj.LIST_OF_ALL_ACTUAL_FLOATING_VALUES_OF_SAMPLES_AMPLITUDES[i];

clubbedSamples[sampleIndex] = (short)Math.Max(short.MinValue, Math.Min(short.MaxValue, amplitude));

totalClubbedSamples++;

reportBuilder.AppendLine(

"Rank_" + rank + " " +

obj.PUBLIC_INT_NON_DUPLICATE_CG_X_RANKING_FOR_SAAN_STYLES_NORMALIZATION_DONE_ON_GLOBAL_MAX_WIDH_OF_ALL_AABB_OBJECTS + " " +

(amplitude / 10000f).ToString("F6") + " " +

totalClubbedSamples.ToString("F0")

);

}// if (sampleIndex >= 0 && sampleIndex < totalSamples)

}

string label = "last_" + n + "_ranks_" + string.Join("_", lastRankSet.Select(r => r.ToString("D2")));

string wavFilePath = Path.Combine(outputFolder, $"CLUBBED_LAST_RANKED_SPECTRAL_LINE_{label}.wav");

string reportFilePath = wavFilePath + "_report.txt";

System.IO.File.WriteAllText(reportFilePath, reportBuilder.ToString());

if (totalClubbedSamples > sampleRate)

{

WriteMono16BitPCM_WAV___takes_short_type_arrays(wavFilePath, clubbedSamples, sampleRate);

}// if (totalClubbedSamples > sampleRate)

}// for (int n = 2; n <= 8; n++)

i need 3 additional files each for the clubbed frank_1 , rank_1 and 2 rank 1 rank 2 rank 3 with 3 additional report and wav files with the calculations like find the average of absolute amplitudes for these three cases , standard deviations of absolute amplitudes for three clubbed ranked cases these cases strictly dont change the structure of the program (the code is working) then generate 3 additional report and wav files (keep total sample count sample rates all same as in the code but for ) each with cases for (choose indexed samples location which have absolute amplitudes > (mean-1 stddev) put as amplitude =1 otherwise amplitude 0 similarly for abs(amplitude at the indexed location )> mean+ 0*std dev put samples amplitude 1 otherwise 0 similarly another file if absolute( indexed amplitude )> mean+1.stddev for that file then put amplitude =1 otherwise 0 in this way generate 3 different files for each of three top clubbed ranked cases refer the code (working code) public static void GenerateRankedSpectralWavFiles______DONT_CALL_THIS_BEFORE_ALL_DXF_PREPARED_SINCE_DXF_GENERATORS_POPULATE_SCALED_CG_X_DATA

(

List<CrestTroughObject> allCrestTroughObjects,

int totalSamples,

int sampleRate,

string inputFilePath

)

{

string outputFolder = Path.GetDirectoryName(inputFilePath);

StringBuilder ___strbldr = new StringBuilder();

___strbldr.Clear();

var rankedGroups = allCrestTroughObjects

.GroupBy(obj => Math.Round(obj.PUBLIC_DOUBLE_NON_DUPLICATE_CG_X_FOR_SAAN_STYLES_NORMALIZATION_DONE_ON_GLOBAL_MAX_WIDH_OF_ALL_AABB_OBJECTS, 6))

.OrderBy(g => g.Key)

.Select((group, rankIndex) => new

{

Rank = rankIndex + 1,

Objects = group.ToList()

})

.ToList();

double ___total_populated_samples_for_current_output_files = 0;

foreach (var group in rankedGroups)

{

foreach (var obj in group.Objects)

{

obj.PUBLIC_INT_NON_DUPLICATE_CG_X_RANKING_FOR_SAAN_STYLES_NORMALIZATION_DONE_ON_GLOBAL_MAX_WIDH_OF_ALL_AABB_OBJECTS = group.Rank;

}

/////////////////////////////////////////////////////////////////////////////////////////////////////////////////

foreach (var group in rankedGroups)

{

short[] outputSamples = new short[totalSamples];

___total_populated_samples_for_current_output_files = 0;

___strbldr.Clear();

foreach (var obj in group.Objects)

{

___strbldr.AppendLine

(

"CURRENT CREST_TROUGH_OBJECT OVERALL COUNTER = " + obj.OVERALL_AABB_COUNTER_EITHER_IT_IS_CREST_OR_IT_IS_TROUGH____COUNTER_TO_RECONSTRUCTION_THE_ACTUAL_QUEUE_STRUCTURE_FROM_THE_STACK_ANALYSIS_DATA

+"\r\n"+

"CURRENT CREST_TROUGH_OBJECT CREST COUNTER = " + obj.CREST_COUNTER

+ "\r\n" +

"CURRENT CREST_TROUGH_OBJECT TROUGH COUNTER = " + obj.TROUGH_COUNTER

+ "\r\n" +

"CURRENT CREST_TROUGH_OBJECT WIDTH MICROS = " + obj.WidthMicroseconds

+ "\r\n" +

"CURRENT CREST_TROUGH_OBJECT MaxAmplitude = " + obj.MaxAmplitude

+ "\r\n" +

"CURRENT CREST_TROUGH_OBJECT LocalMaximaCount = " + obj.LocalMaximaCount

+ "\r\n" +

"CURRENT CREST_TROUGH_OBJECT LocalMinimaCount = " + obj.LocalMinimaCount

+ "\r\n" +

"overall max width found in whole files = " +

.PUBLIC_STATIC_DOUBLE_MAX_WIDTH_MIKROSEC_FOUND_IN_OVERALL_IN_CRESTS_AND_TROUGHS

+ "\r\n" +

"CURRENT CREST_TROUGH_OBJECT TotalSamples = " + (obj.EndSampleIndex-obj.StartSampleIndex + 1)

+ "\r\nRANK CG_X_NORMALIZED AMPS samplecounter"

);

int length = obj.EndSampleIndex - obj.StartSampleIndex + 1;

for (int i = 0; i < length; i++)

{

int sampleIndex = obj.StartSampleIndex + i;

if (sampleIndex >= 0 && sampleIndex < totalSamples)

{

float amplitude = obj.LIST_OF_ALL_ACTUAL_FLOATING_VALUES_OF_SAMPLES_AMPLITUDES[i];

___total_populated_samples_for_current_output_files++;

___strbldr.AppendLine

(

group.Rank + " " +

// obj.PUBLIC_INT_NON_DUPLICATE_CG_X_RANKING_FOR_SAAN_STYLES_NORMALIZATION_DONE_ON_GLOBAL_MAX_WIDH_OF_ALL_AABB_OBJECTS + " " +

obj.PUBLIC_DOUBLE_NON_DUPLICATE_CG_X_FOR_SAAN_STYLES_NORMALIZATION_DONE_ON_GLOBAL_MAX_WIDH_OF_ALL_AABB_OBJECTS + " " +

amplitude / 10000f + " " +

___total_populated_samples_for_current_output_files

);

outputSamples[sampleIndex] = (short)Math.Max(short.MinValue, Math.Min(short.MaxValue, amplitude));

}

string outFileName = $"RANKED_SPECTRAL_LINE_pushed_samples_{___total_populated_samples_for_current_output_files}_rank_{group.Rank:D3}.wav";

string outPath = Path.Combine(outputFolder, outFileName);

System.IO.File.WriteAllText(outPath + "_report.txt", ___strbldr.ToString());

if (___total_populated_samples_for_current_output_files > sampleRate)

{

// WriteMono16BitPCM_WAV(outPath, outputSamples, sampleRate);

WriteMono16BitPCM_WAV___takes_short_type_arrays(outPath, outputSamples, sampleRate);

}

// STEP 4: CLUBBED RANK WAV FILES

int[][] rankGroupsToClub = new int[][]

{

new int[] { 1, 2 },

new int[] { 1, 2, 3 },

new int[] { 1, 2, 3 ,4 },

new int[] { 1, 2, 3 ,4 ,5},

new int[] { 1, 2, 3, 4, 5, 6 },

new int[] { 1, 2, 3, 4, 5, 6 ,7},

new int[] { 1, 2, 3, 4, 5, 6, 7, 8 }

};

foreach (var rankSet in rankGroupsToClub)

{

short[] clubbedSamples = new short[totalSamples];

double totalClubbedSamples = 0;

StringBuilder reportBuilder = new StringBuilder();

foreach (var rank in rankSet)

{

var group = rankedGroups.FirstOrDefault(g => g.Rank == rank);

if (group == null) continue;

foreach (var obj in group.Objects)

{

int len = obj.EndSampleIndex - obj.StartSampleIndex + 1;

for (int i = 0; i < len; i++)

{

int sampleIndex = obj.StartSampleIndex + i;

if (sampleIndex >= 0 && sampleIndex < totalSamples)

{

float amplitude = obj.LIST_OF_ALL_ACTUAL_FLOATING_VALUES_OF_SAMPLES_AMPLITUDES[i];

clubbedSamples[sampleIndex] = (short)Math.Max(short.MinValue, Math.Min(short.MaxValue, amplitude));

totalClubbedSamples++;

reportBuilder.AppendLine(

"Rank_" + rank + " " +

obj.PUBLIC_INT_NON_DUPLICATE_CG_X_RANKING_FOR_SAAN_STYLES_NORMALIZATION_DONE_ON_GLOBAL_MAX_WIDH_OF_ALL_AABB_OBJECTS + " " +

(amplitude / 10000f).ToString("F6") + " " +

totalClubbedSamples.ToString("F0")

);

}

string label = "rank_" + string.Join("_", rankSet.Select(r => r.ToString("D2")));

string wavFilePath = Path.Combine(outputFolder, $"CLUBBED_RANKED_SPECTRAL_LINE_{label}.wav");

string reportFilePath = wavFilePath + "_report.txt";

System.IO.File.WriteAllText(reportFilePath, reportBuilder.ToString());

if (totalClubbedSamples > sampleRate)

{

/// WriteMono16BitPCM_WAV(wavFilePath, clubbedSamples, sampleRate);

WriteMono16BitPCM_WAV___takes_short_type_arrays(wavFilePath, clubbedSamples, sampleRate);

}//if (totalClubbedSamples > sampleRate)

}// foreach (var rankSet in rankGroupsToClub)

////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////

////// ADDITIONAL CLUBBED OUTPUTS FOR LAST N RANKS (up to last 8)

int totalRanks = rankedGroups.Count;

for (int n = 2; n <= 8; n++)

{

if (n > totalRanks) break;

var lastRankSet = Enumerable.Range(totalRanks - n + 1, n).ToArray();

short[] clubbedLastSamples = new short[totalSamples];

double totalClubbedLastSamples = 0;

StringBuilder reportBuilder = new StringBuilder();

foreach (var rank in lastRankSet)

{

var group = rankedGroups.FirstOrDefault(g => g.Rank == rank);

if (group == null) continue;

foreach (var obj in group.Objects)

{

int len = obj.EndSampleIndex - obj.StartSampleIndex + 1;

for (int i = 0; i < len; i++)

{

int sampleIndex = obj.StartSampleIndex + i;

if (sampleIndex >= 0 && sampleIndex < totalSamples)

{

float amplitude = obj.LIST_OF_ALL_ACTUAL_FLOATING_VALUES_OF_SAMPLES_AMPLITUDES[i];

clubbedLastSamples[sampleIndex] = (short)Math.Max(short.MinValue, Math.Min(short.MaxValue, amplitude));

totalClubbedLastSamples++;

reportBuilder.AppendLine(

"Rank_" + rank + " " +

obj.PUBLIC_INT_NON_DUPLICATE_CG_X_RANKING_FOR_SAAN_STYLES_NORMALIZATION_DONE_ON_GLOBAL_MAX_WIDH_OF_ALL_AABB_OBJECTS + " " +

(amplitude / 10000f).ToString("F6") + " " +

totalClubbedLastSamples.ToString("F0")

);

}// if (sampleIndex >= 0 && sampleIndex < totalSamples)

}

string label = "last_" + n + "_ranks_" + string.Join("_", lastRankSet.Select(r => r.ToString("D2")));

string wavFilePath = Path.Combine(outputFolder, $"LAST_RANKED_CLUBBED_SPECTRAL_LINE_{label}.wav");

string reportFilePath = wavFilePath + "_report.txt";

System.IO.File.WriteAllText(reportFilePath, reportBuilder.ToString());

if (totalClubbedLastSamples > sampleRate)

{

WriteMono16BitPCM_WAV___takes_short_type_arrays(wavFilePath, clubbedLastSamples, sampleRate);

}// if (totalClubbedSamples > sampleRate)

}// for (int n = 2; n <= 8; n++)

}//public static void GenerateRankedSpectralWavFiles______DONT_CALL_THIS_BEFORE_ALL_DXF_PREPARED_SINCE_DXF_GENERATORS_POPULATE_SCALED_CG_X_DATA

Understood. Based on your instructions, I will write an additional block of code (not altering your existing working structure) to:

1. Use the top clubbed ranks:

o Rank 1

o Ranks 1+2

o Ranks 1+2+3

2. Calculate:

o Mean and standard deviation of absolute amplitudes from the selected crest-trough objects.

3. Generate 3 WAV + CSV report sets:

o For samples where abs(amplitude) > mean - 1×stddev

o For samples where abs(amplitude) > mean + 0×stddev (i.e., just mean)

o For samples where abs(amplitude) > mean + 1×stddev

Each sample meeting the condition is encoded with amplitude 1, others with 0.

I’ll now generate the clean additional code block to insert into your working function.

Below is the fully isolated additional code block to insert after your current foreach (var rankSet in rankGroupsToClub) loop, still within the same method. This generates 3 extra WAV + TXT report files for each of the clubbed rank groups: Rank 1, Ranks 1+2, and Ranks 1+2+3.

✅ This does NOT modify your working logic.

________________________________________

csharp

CopyEdit

// ADDITIONAL ANALYTIC BINARIZED OUTPUTS FOR TOP CLUBBED RANKS: 1, 1+2, 1+2+3

int[][] topRankSets = new int[][]

{

new int[] { 1 },

new int[] { 1, 2 },

new int[] { 1, 2, 3 }

};

foreach (var rankSet in topRankSets)

{

string label = "top_rank_" + string.Join("_", rankSet.Select(r => r.ToString("D2")));

// Collect absolute amplitudes for this rank set

List<float> absoluteAmplitudes = new List<float>();

short[] originalSamples = new short[totalSamples];

foreach (var rank in rankSet)

{

var group = rankedGroups.FirstOrDefault(g => g.Rank == rank);

if (group == null) continue;

foreach (var obj in group.Objects)

{

int len = obj.EndSampleIndex - obj.StartSampleIndex + 1;

for (int i = 0; i < len; i++)

{

int index = obj.StartSampleIndex + i;

if (index >= 0 && index < totalSamples)

{

float amp = obj.LIST_OF_ALL_ACTUAL_FLOATING_VALUES_OF_SAMPLES_AMPLITUDES[i];

originalSamples[index] = (short)Math.Max(short.MinValue, Math.Min(short.MaxValue, amp));

absoluteAmplitudes.Add(Math.Abs(amp));

}

if (absoluteAmplitudes.Count == 0) continue;

// Compute mean and stddev of absolute amplitudes

double mean = absoluteAmplitudes.Average();

double stddev = Math.Sqrt(absoluteAmplitudes.Sum(x => Math.Pow(x - mean, 2)) / absoluteAmplitudes.Count);

// Threshold variants

var thresholds = new[]

{

new { Label = "gt_mean_minus_1stddev", Threshold = mean - stddev },

new { Label = "gt_mean", Threshold = mean },

new { Label = "gt_mean_plus_1stddev", Threshold = mean + stddev }

};

foreach (var th in thresholds)

{

short[] binarySamples = new short[totalSamples];

int countMarked = 0;

StringBuilder report = new StringBuilder();

for (int i = 0; i < totalSamples; i++)

{

if (Math.Abs(originalSamples[i]) > th.Threshold)

{

binarySamples[i] = 1;

countMarked++;

}

else

{

binarySamples[i] = 0;

}

report.AppendLine("Report for " + label + " | Threshold = " + th.Threshold.ToString("F3"));

report.AppendLine("Total activated samples = " + countMarked);

report.AppendLine("Total samples = " + totalSamples);

report.AppendLine("Percentage activated = " + ((100.0 * countMarked) / totalSamples).ToString("F2") + "%");

string outPath = Path.Combine(outputFolder, $"TOPCLUBBED_BINARIZED_{label}_{th.Label}.wav");

string txtReportPath = outPath + "_report.txt";

File.WriteAllText(txtReportPath, report.ToString());

if (countMarked > sampleRate)

{

WriteMono16BitPCM_WAV___takes_short_type_arrays(outPath, binarySamples, sampleRate);

}

________________________________________

🟡 Summary of outputs (per rank group):

For each of Rank 1, Ranks 1+2, Ranks 1+2+3:

• WAV file where sample = 1 if abs(amplitude) > threshold, else 0

• TXT report for:

o Threshold used

o Total activated samples

o Activation % over all samples

Let me know if you'd also like:

• Visual plots

• CSV instead of TXT

• Threshold ranges as multiples of mean instead of stddev.

Here's the rewritten version of your block to preserve waveform sign while still binarizing amplitude values, as discussed. It does not alter structure, but now uses +10000 or -10000 depending on original polarity, instead of flat 1/0, so the result is audible and polarity-aware.

________________________________________

csharp

CopyEdit

// ADDITIONAL ANALYTIC BINARIZED OUTPUTS FOR TOP CLUBBED RANKS: 1, 1+2, 1+2+3

int[][] topRankSets = new int[][]

{

new int[] { 1 },

new int[] { 1, 2 },

new int[] { 1, 2, 3 }

};

foreach (var rankSet in topRankSets)

{

string label = "top_rank_" + string.Join("_", rankSet.Select(r => r.ToString("D2")));

// Collect absolute amplitudes for this rank set

List<float> absoluteAmplitudes = new List<float>();

short[] originalSamples = new short[totalSamples];

foreach (var rank in rankSet)

{

var group = rankedGroups.FirstOrDefault(g => g.Rank == rank);

if (group == null) continue;

foreach (var obj in group.Objects)

{

int len = obj.EndSampleIndex - obj.StartSampleIndex + 1;

for (int i = 0; i < len; i++)

{

int index = obj.StartSampleIndex + i;

if (index >= 0 && index < totalSamples)

{

float amp = obj.LIST_OF_ALL_ACTUAL_FLOATING_VALUES_OF_SAMPLES_AMPLITUDES[i];

short clamped = (short)Math.Max(short.MinValue, Math.Min(short.MaxValue, amp));

originalSamples[index] = clamped;

absoluteAmplitudes.Add(Math.Abs(clamped));

}

if (absoluteAmplitudes.Count == 0) continue;

// Compute mean and stddev of absolute amplitudes

double mean = absoluteAmplitudes.Average();

double stddev = Math.Sqrt(absoluteAmplitudes.Sum(x => Math.Pow(x - mean, 2)) / absoluteAmplitudes.Count);

// Threshold variants

var thresholds = new[]

{

new { Label = "gt_mean_minus_1stddev", Threshold = mean - stddev },

new { Label = "gt_mean", Threshold = mean },

new { Label = "gt_mean_plus_1stddev", Threshold = mean + stddev }

};

foreach (var th in thresholds)

{

short[] binarySamples = new short[totalSamples];

int countMarked = 0;

StringBuilder report = new StringBuilder();

for (int i = 0; i < totalSamples; i++)

{

short original = originalSamples[i];

short absValue = (short)Math.Abs(original);

if (absValue > th.Threshold)

{

binarySamples[i] = (short)(original > 0 ? 10000 : -10000); // preserve sign and scale to ±10000

countMarked++;

}

else

{

binarySamples[i] = 0;

}

report.AppendLine("Report for " + label + " | Threshold = " + th.Threshold.ToString("F3"));

report.AppendLine("Total activated samples = " + countMarked);

report.AppendLine("Total samples = " + totalSamples);

report.AppendLine("Percentage activated = " + ((100.0 * countMarked) / totalSamples).ToString("F2") + "%");

string outPath = Path.Combine(outputFolder, $"TOPCLUBBED_BINARIZED_{label}_{th.Label}.wav");

string txtReportPath = outPath + "_report.txt";

File.WriteAllText(txtReportPath, report.ToString());

if (countMarked > sampleRate)

{

WriteMono16BitPCM_WAV___takes_short_type_arrays(outPath, binarySamples, sampleRate);

}

________________________________________

✅ Summary of Changes:

• Preserves original sign of amplitude for samples above threshold.

• Uses ±10000 instead of flat ±1 to make waveforms audible.

• Keeps structure untouched, report format same, sample count same.

Let me know if you want a second version with float WAVs or with 32-bit PCM as well.

STRICT NOTE THIS PART OF THE CODE WORKS VERY FAST AND WORKS PROPERLY DONT CHANGE ITS STRUCTURE. Please write a program to enhance this part using the chunking and the speed reading and also list the complete samples in float array , find the mean , standard deviations from the raw sample values and save six files keeping same sample rate as inputfile , keeping same bit depth (floating array not short array) as input file , keeping the mono format 1 channel output ... six files will have File1 is with shifted amplitudes values (float values ) adjusted as the avrage(signed average) as zero and readjusted + amplitudes and readjusted negative amplitudes , similarly file 2 where the zero is at signed average + 1 standard deviation and readjusted amplitudes , File 3 is with szero at signed average - 1* standard deviation Similarly File 3+ the amplitudes +10000 or -10000 (as you did earlier) for the cases where the values are above signed average as Audible and otherwise 0 , Similarly File 3++ With audibility threshold for amplitudes(+10000 or -10000 accordingly as you did) at signed average + 1*standard deviation otherwise zero Similarly File 6 where Audible Amplitudes to place (audible values as you did +10000 or -10000 ) as taken zero line at signed average - 1*standard deviations ... refer the working code which works very fast properly using (FileStream fs = new FileStream(wavPath, FileMode.Open, FileAccess.Read))

{

using (BinaryReader br = new BinaryReader(fs))

{

br.ReadBytes(12);

while (br.BaseStream.Position < br.BaseStream.Length)

{

string chunkID = new string(br.ReadChars(4));

int chunkSizeBytes = br.ReadInt32();

if (chunkID != "data")

{

br.BaseStream.Position += chunkSizeBytes; continue;

}// if (chunkID != "data")

int bytesPerSample = meta.BitsPerSample / 8;

int totalSamples = chunkSizeBytes / bytesPerSample;

float[] buffer = new float[chunkSize];

int samplesRead = 0;

CrestTroughObject current = null;

bool positive = true;

progressBarFOR_ANALYSIS.Minimum = 0;

progressBarFOR_ANALYSIS.Maximum = totalSamples;

while (samplesRead < totalSamples)

{

int blockSamples = Math.Min(chunkSize, totalSamples - samplesRead);

for (int i = 0; i < blockSamples; i++)

{

switch (meta.BitsPerSample)

{

case 8: buffer[i] = (br.ReadByte() - 128) / 128f; break;

case 16: buffer[i] = br.ReadInt16() / 32768f; break;

case 24:

byte[] b = br.ReadBytes(3);

int val = (b[2] << 16) | (b[1] << 8) | b[0];

if ((val & 0x800000) != 0) val |= unchecked((int)0xFF000000);

buffer[i] = val / 8388608f; break;

case 32: buffer[i] = br.ReadInt32() / (float)Int32.MaxValue; break;

default: MessageBox.Show("Unsupported bit depth."); return;

}//switch (meta.BitsPerSample)

}//for (int i = 0; i < blockSamples; i++)

for (int i = 0; i < blockSamples; i++)

{

bool currentSign = buffer[i] >= 0;

int globalIndex = samplesRead + i;

if (current == null)

{

current = new CrestTroughObject { StartSampleIndex = globalIndex, IsCrest = currentSign };

positive = currentSign;

}//if (current == null)

else if (currentSign != positive)

{

current.EndSampleIndex = globalIndex - 1;

int segLen = current.EndSampleIndex - current.StartSampleIndex + 1;

if (segLen < 2)

{

current = new CrestTroughObject { StartSampleIndex = globalIndex, IsCrest = currentSign }; positive = currentSign; continue;

}//if (segLen < 2)

float[] seg = new float[segLen];

for (int j = 0; j < segLen; j++)

{

int idx = i - segLen + j;

//seg[j] = (idx < 0 || idx >= blockSamples) ? 0f : buffer[idx];

seg[j] = (idx < 0 || idx >= blockSamples) ? 0f : buffer[idx];

}//for (int j = 0; j < segLen; j++)

//saan stopped it here current.MaxAmplitude = seg.Max();

//saan stopped it here current.MinAmplitude = seg.Min();

//all segment data populated

current.MaxAmplitude = seg.Max();//saan brought it here

current.MinAmplitude = seg.Min();//saan brought it here

for (int j = 0; j < segLen; j++)

{

// RRR

float timeMicro = (j * 1000000f) / meta.SampleRate;

// current.TipPointsMicrosecondsVsAmplitude.Add(new PointF(timeMicro, seg[j]));

current.TipPointsMicrosecondsVsAmplitude.Add(new PointF(timeMicro, seg[j] * 10000f));//saan did * 10000f to get better angles calcs

//////////CALLING CONVENTIONS

////////public static double PUBLIC_STATIC_DOUBLE_SUM_OF_ALL_SAMPLES_AMPLITUDES_IN_THE_WHOLE_WAV_FILE___10000_TIMES = 0;

////////public static double PUBLIC_STATIC_DOUBLE_AVERAGE_OF_ALL_SAMPLES_AMPLITUDES_IN_THE_WHOLE_WAV_FILE___10000_TIMES = 0;

PUBLIC_STATIC_DOUBLE_SUM_OF_ALL_SAMPLES_AMPLITUDES_IN_THE_WHOLE_WAV_FILE___10000_TIMES

+ (double)(seg[j] * 10000f);

}//for (int j = 0; j < segLen; j++)

//////current.MaxAmplitude = seg.Max();//saan brought it here

//////current.MinAmplitude = seg.Min();//saan brought it here

//////////////////////////////////////////////////////// CALLED ONLY ONCE ////////////////////////

current.ComputeGeometry(meta.SampleRate);

//////////////////////////////////////////////////////// CALLED ONLY ONCE ////////////////////////

maxWidth = Math.Max(maxWidth, current.WidthMicroseconds);

maxHeight = Math.Max(maxHeight, current.HeightAmplitude);

___temp_double_zero_crossing_counter ++;

current

.OVERALL_AABB_COUNTER_EITHER_IT_IS_CREST_OR_IT_IS_TROUGH____COUNTER_TO_RECONSTRUCTION_THE_ACTUAL_QUEUE_STRUCTURE_FROM_THE_STACK_ANALYSIS_DATA

= ___temp_double_zero_crossing_counter;

if(currentSign)

{

___temp_double_crest_counter ++;

current.CREST_COUNTER

___temp_double_crest_counter;

}//if(currentSign)

else

{

___temp_double_trough_counter++;

current

.TROUGH_COUNTER

___temp_double_trough_counter;

}// end of else of if(currentSign)

crestTroughs.Add(current);