From e3e05cb7d684a3350210077bb6dc5f7e2deb9b7c Mon Sep 17 00:00:00 2001 From: Pacu Date: Wed, 8 Oct 2025 20:32:19 -0300 Subject: [PATCH 01/17] Update gitignore to future project structure --- .gitignore | 39 +++++++++++++++++++++++++++++++++++++-- 1 file changed, 37 insertions(+), 2 deletions(-) diff --git a/.gitignore b/.gitignore index 99daa86..a35445f 100644 --- a/.gitignore +++ b/.gitignore @@ -1,2 +1,37 @@ -/target -results.csv +# Rust +/analyzer/target/ +/analyzer/Cargo.lock +**/*.rs.bk + +# Python +__pycache__/ +*.py[cod] +*$py.class +.Python +venv/ +env/ +*.egg-info/ + +# Results +/results/* +!/results/.gitkeep +!/results/README.md + +# IDE +.vscode/ +.idea/ +*.swp +*.swo +*~ + +# OS +.DS_Store +Thumbs.db + +# Build artifacts +*.so +*.dylib +*.dll + +# Logs +*.log From e8e030068706608462e096f151b826a3e261c97f Mon Sep 17 00:00:00 2001 From: Pacu Date: Wed, 8 Oct 2025 20:33:48 -0300 Subject: [PATCH 02/17] Implement a statistical analysis throughout series of block ranges co-authored with Claude AI. Use with caution. --- .github/ISSUE_TEMPLATE/bug_report.md | 29 + .github/ISSUE_TEMPLATE/feature_request.md | 19 + .github/workflows/python-ci.yml | 36 + .github/workflows/rust-ci.yml | 58 + Cargo.lock | 1998 ---------------- Cargo.toml | 19 - LICENSE | 21 + NETWORK_UPGRADES.md | 160 ++ PROJECT_SUMMARY.md | 73 + QUICKSTART.md | 239 ++ README.md | 208 +- analyzer/Cargo.toml | 28 + analyzer/README.md | 508 +++++ build.rs => analyzer/build.rs | 2 +- .../proto}/compact_formats.proto | 34 +- {proto => analyzer/proto}/service.proto | 16 +- analyzer/quick_results.csv | 2001 +++++++++++++++++ {src => analyzer/src}/main.rs | 177 +- analyzer/src/sampling.rs | 406 ++++ docs/architecture.md | 58 + docs/sampling-strategies.md | 53 + examples/era_comparison.sh | 37 + examples/quick_analysis.sh | 7 + examples/recommended_analysis.sh | 7 + proto/darkside.proto | 148 -- results/.gitkeep | 0 results/README.md | 24 + scripts/fetch_protos.sh | 23 + scripts/run_all_analyses.sh | 34 + scripts/setup.sh | 26 + visualization/README.md | 23 + visualization/charts/bandwidth_impact.png | Bin 0 -> 247118 bytes visualization/charts/by_era.png | Bin 0 -> 331250 bytes visualization/charts/correlations.png | Bin 0 -> 413037 bytes visualization/charts/cumulative.png | Bin 0 -> 214605 bytes visualization/charts/distribution.png | Bin 0 -> 203063 bytes visualization/charts/heatmap.png | Bin 0 -> 307824 bytes visualization/charts/statistical_report.txt | 74 + visualization/charts/time_series.png | Bin 0 -> 415543 bytes visualization/requirements.txt | 5 + visualization/visualize.py | 606 +++++ 41 files changed, 4912 insertions(+), 2245 deletions(-) create mode 100644 .github/ISSUE_TEMPLATE/bug_report.md create mode 100644 .github/ISSUE_TEMPLATE/feature_request.md create mode 100644 .github/workflows/python-ci.yml create mode 100644 .github/workflows/rust-ci.yml delete mode 100644 Cargo.lock delete mode 100644 Cargo.toml create mode 100644 LICENSE create mode 100644 NETWORK_UPGRADES.md create mode 100644 PROJECT_SUMMARY.md create mode 100644 QUICKSTART.md create mode 100644 analyzer/Cargo.toml create mode 100644 analyzer/README.md rename build.rs => analyzer/build.rs (79%) rename {proto => analyzer/proto}/compact_formats.proto (74%) rename {proto => analyzer/proto}/service.proto (94%) create mode 100644 analyzer/quick_results.csv rename {src => analyzer/src}/main.rs (63%) create mode 100644 analyzer/src/sampling.rs create mode 100644 docs/architecture.md create mode 100644 docs/sampling-strategies.md create mode 100755 examples/era_comparison.sh create mode 100755 examples/quick_analysis.sh create mode 100755 examples/recommended_analysis.sh delete mode 100644 proto/darkside.proto create mode 100644 results/.gitkeep create mode 100644 results/README.md create mode 100755 scripts/fetch_protos.sh create mode 100755 scripts/run_all_analyses.sh create mode 100755 scripts/setup.sh create mode 100644 visualization/README.md create mode 100644 visualization/charts/bandwidth_impact.png create mode 100644 visualization/charts/by_era.png create mode 100644 visualization/charts/correlations.png create mode 100644 visualization/charts/cumulative.png create mode 100644 visualization/charts/distribution.png create mode 100644 visualization/charts/heatmap.png create mode 100644 visualization/charts/statistical_report.txt create mode 100644 visualization/charts/time_series.png create mode 100644 visualization/requirements.txt create mode 100644 visualization/visualize.py diff --git a/.github/ISSUE_TEMPLATE/bug_report.md b/.github/ISSUE_TEMPLATE/bug_report.md new file mode 100644 index 0000000..e59cd50 --- /dev/null +++ b/.github/ISSUE_TEMPLATE/bug_report.md @@ -0,0 +1,29 @@ +--- +name: Bug report +about: Create a report to help us improve +title: '[BUG] ' +labels: bug +assignees: '' +--- + +**Describe the bug** +A clear and concise description of what the bug is. + +**To Reproduce** +Steps to reproduce the behavior: +1. Run command '...' +2. With parameters '...' +3. See error + +**Expected behavior** +A clear and concise description of what you expected to happen. + +**Environment:** + - OS: [e.g. Ubuntu 22.04] + - Rust version: [e.g. 1.75.0] + - Python version: [e.g. 3.10] + - Zebrad version: [e.g. 1.5.0] + - Lightwalletd version: [e.g. 0.4.14] + +**Additional context** +Add any other context about the problem here. diff --git a/.github/ISSUE_TEMPLATE/feature_request.md b/.github/ISSUE_TEMPLATE/feature_request.md new file mode 100644 index 0000000..b0a0adb --- /dev/null +++ b/.github/ISSUE_TEMPLATE/feature_request.md @@ -0,0 +1,19 @@ +--- +name: Feature request +about: Suggest an idea for this project +title: '[FEATURE] ' +labels: enhancement +assignees: '' +--- + +**Is your feature request related to a problem? Please describe.** +A clear and concise description of what the problem is. + +**Describe the solution you'd like** +A clear and concise description of what you want to happen. + +**Describe alternatives you've considered** +A clear and concise description of any alternative solutions or features you've considered. + +**Additional context** +Add any other context or screenshots about the feature request here. diff --git a/.github/workflows/python-ci.yml b/.github/workflows/python-ci.yml new file mode 100644 index 0000000..c3dcbdc --- /dev/null +++ b/.github/workflows/python-ci.yml @@ -0,0 +1,36 @@ +name: Python CI + +on: + push: + branches: [ main, develop ] + pull_request: + branches: [ main ] + +jobs: + lint: + runs-on: ubuntu-latest + + steps: + - uses: actions/checkout@v3 + + - name: Set up Python + uses: actions/setup-python@v4 + with: + python-version: '3.10' + + - name: Install dependencies + working-directory: ./visualization + run: | + python -m pip install --upgrade pip + pip install -r requirements.txt + pip install flake8 black + + - name: Lint with flake8 + working-directory: ./visualization + run: | + flake8 . --count --select=E9,F63,F7,F82 --show-source --statistics + flake8 . --count --exit-zero --max-complexity=10 --max-line-length=127 --statistics + + - name: Check formatting with black + working-directory: ./visualization + run: black --check . diff --git a/.github/workflows/rust-ci.yml b/.github/workflows/rust-ci.yml new file mode 100644 index 0000000..ee16f7a --- /dev/null +++ b/.github/workflows/rust-ci.yml @@ -0,0 +1,58 @@ +name: Rust CI + +on: + push: + branches: [ main, develop ] + pull_request: + branches: [ main ] + +jobs: + build: + runs-on: ubuntu-latest + + steps: + - uses: actions/checkout@v3 + + - name: Install Rust + uses: actions-rs/toolchain@v1 + with: + toolchain: stable + override: true + components: rustfmt, clippy + + - name: Cache cargo registry + uses: actions/cache@v3 + with: + path: ~/.cargo/registry + key: ${{ runner.os }}-cargo-registry-${{ hashFiles('**/Cargo.lock') }} + + - name: Cache cargo index + uses: actions/cache@v3 + with: + path: ~/.cargo/git + key: ${{ runner.os }}-cargo-git-${{ hashFiles('**/Cargo.lock') }} + + - 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-[build-dependencies] -tonic-build = "0.11" diff --git a/LICENSE b/LICENSE new file mode 100644 index 0000000..2d59335 --- /dev/null +++ b/LICENSE @@ -0,0 +1,21 @@ +MIT License + +Copyright (c) 2025 Zcash Community + +Permission is hereby granted, free of charge, to any person obtaining a copy +of this software and associated documentation files (the "Software"), to deal +in the Software without restriction, including without limitation the rights +to use, copy, modify, merge, publish, distribute, sublicense, and/or sell +copies of the Software, and to permit persons to whom the Software is +furnished to do so, subject to the following conditions: + +The above copyright notice and this permission notice shall be included in all +copies or substantial portions of the Software. + +THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE +AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER +LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, +OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE +SOFTWARE. diff --git a/NETWORK_UPGRADES.md b/NETWORK_UPGRADES.md new file mode 100644 index 0000000..13e3eb6 --- /dev/null +++ b/NETWORK_UPGRADES.md @@ -0,0 +1,160 @@ +# Zcash Network Upgrades Reference + +This document provides context for the protocol eras used in sampling and analysis. + +## Network Upgrade Timeline + +| Era | Activation Block | Date | Key Features | +|-----|-----------------|------|--------------| +| **Sapling** | 419,200 - 653,599 | Oct 2018 - Dec 2019 | New shielded pool, improved performance | +| **Blossom** | 653,600 - 903,799 | Dec 2019 - Jul 2020 | Block time 150s → 75s | +| **Heartwood** | 903,800 - 1,046,399 | Jul 2020 - Nov 2020 | Shielded coinbase, FlyClient | +| **Canopy** | 1,046,400 - 1,687,103 | Nov 2020 - May 2022 | Dev fund activation | +| **NU5** | 1,687,104 - 2,726,399 | May 2022 - Apr 2024 | Orchard pool, unified addresses | +| **NU6** | 2,726,400 - current | Apr 2024 - present | Current protocol | + +## Why These Eras Matter for Analysis + +### Sapling (419,200 - 653,599) +**Characteristics:** +- New efficient shielded pool introduced +- Gradual adoption of shielded transactions +- Transparent still common but declining +- Block time: 150 seconds + +**Relevance to Analysis:** +- Transition period from transparent to shielded +- Mixed usage patterns +- Baseline for early shielded adoption + +### Blossom (653,600 - 903,799) +**Characteristics:** +- **Block time reduced to 75 seconds** +- Twice as many blocks per day (from ~576 to ~1152) +- Continued Sapling adoption +- More blocks = more overhead for initial sync + +**Relevance to Analysis:** +- **Critical**: Block time change affects bandwidth calculations +- Must account for 2x blocks per day after Blossom +- Same MB/block but different MB/day after this upgrade + +### Heartwood (903,800 - 1,046,399) +**Characteristics:** +- Shielded coinbase enabled (miners can receive directly to Sapling) +- FlyClient support for light clients +- ZIP 213 (shielded coinbase) + +**Relevance to Analysis:** +- Shielded coinbase reduces transparent coinbase outputs +- May show decrease in transparent transactions +- Short era but important transition + +### Canopy (1,046,400 - 1,687,103) +**Characteristics:** +- Dev fund activation (20% of block rewards) +- Mature Sapling usage +- Longest single-upgrade era +- Stable protocol period + +**Relevance to Analysis:** +- Good baseline for "normal" modern usage +- Large sample available +- Represents stable state before Orchard + +### NU5 (1,687,104 - 2,726,399) +**Characteristics:** +- **Orchard pool introduced** (new shielded pool) +- **Unified addresses** (single address for all pools) +- Halo 2 proving system +- Transaction version 5 + +**Relevance to Analysis:** +- Introduction of Orchard changes transaction mix +- Unified addresses may affect usage patterns +- Large era, represents recent "stable" state + +### NU6 (2,726,400 - current) +**Characteristics:** +- Current protocol version +- Most recent upgrade (April 2024) +- Active development and adoption + +**Relevance to Analysis:** +- **Most relevant for current decisions** +- Represents actual current usage +- Should be heavily sampled +- Ongoing changes as ecosystem adapts + +## Impact on Compact Block Analysis + +### Transparent Usage Trends + +``` +Sapling: ████████████░░░░░░░░ (High → Medium) +Blossom: ████████░░░░░░░░░░░░ (Medium) +Heartwood: ██████░░░░░░░░░░░░░░ (Medium → Low) +Canopy: ████░░░░░░░░░░░░░░░░ (Low) +NU5: ███░░░░░░░░░░░░░░░░░ (Low) +NU6: ███░░░░░░░░░░░░░░░░░ (Low, current) +``` + +### Block Frequency (Important!) + +**Before Blossom:** +- Block time: 150 seconds +- Blocks per day: ~576 +- Daily bandwidth = avg_block_size × 576 + +**After Blossom:** +- Block time: 75 seconds +- Blocks per day: ~1,152 +- Daily bandwidth = avg_block_size × 1,152 + +⚠️ **When calculating daily bandwidth, account for this doubling after block 653,600!** + +### Sampling Recommendations + +**For Current State Analysis:** +- Focus on NU6 (current) and NU5 (recent stable) +- 60-70% of samples from these eras + +**For Historical Context:** +- Sapling through Canopy shows evolution of usage patterns +- Important to understand how transparent usage declined + +**For Bandwidth Calculations:** +- Separate pre-Blossom and post-Blossom blocks +- Use correct blocks/day multiplier +- Daily sync = avg_size × (576 or 1,152) depending on era + +## Querying Specific Eras + +```bash +# Sapling (transition period) +cargo run --release -- http://127.0.0.1:9067 http://127.0.0.1:8232 range 500000 501000 sapling.csv + +# Blossom (block time change) +cargo run --release -- http://127.0.0.1:9067 http://127.0.0.1:8232 range 750000 751000 blossom.csv + +# Heartwood (shielded coinbase) +cargo run --release -- http://127.0.0.1:9067 http://127.0.0.1:8232 range 950000 951000 heartwood.csv + +# Canopy (mature Sapling) +cargo run --release -- http://127.0.0.1:9067 http://127.0.0.1:8232 range 1300000 1301000 canopy.csv + +# NU5 (Orchard introduction) +cargo run --release -- http://127.0.0.1:9067 http://127.0.0.1:8232 range 2000000 2001000 nu5.csv + +# NU6 (current) +cargo run --release -- http://127.0.0.1:9067 http://127.0.0.1:8232 range 2800000 2801000 nu6.csv +``` + +## References + +- [Zcash Network Upgrade Timeline](https://z.cash/upgrade/) +- [ZIP 200: Network Upgrade Mechanism](https://zips.z.cash/zip-0200) +- [ZIP 206: Deployment of the Blossom Network Upgrade](https://zips.z.cash/zip-0206) +- [ZIP 221: FlyClient - Consensus-Layer Changes](https://zips.z.cash/zip-0221) +- [ZIP 224: Orchard Shielded Protocol](https://zips.z.cash/zip-0224) +- [Zcash Protocol Specification](https://zips.z.cash/protocol/protocol.pdf) diff --git a/PROJECT_SUMMARY.md b/PROJECT_SUMMARY.md new file mode 100644 index 0000000..9cf3a95 --- /dev/null +++ b/PROJECT_SUMMARY.md @@ -0,0 +1,73 @@ +# Project Summary: Compact Block Analyzer + +## What We Built + +A complete statistical analysis tool for evaluating the bandwidth impact of adding transparent transaction data to Zcash's compact block protocol. + +## Components + +### 1. Rust Analyzer (`src/main.rs`) +**Purpose**: Data collection and size estimation + +**Features**: +- Multiple sampling strategies (6 different modes) +- Fetches real compact blocks from lightwalletd via gRPC +- Fetches full blocks from Zebrad via JSON-RPC +- Estimates protobuf overhead for new transparent fields +- Era tracking (pre-Sapling, Sapling, Canopy, NU5) +- Configurable via command-line +- Reproducible results (fixed random seed) + +**Sampling Strategies**: +- `quick`: Fast overview (~1500 blocks, 15min) +- `recommended`: Balanced hybrid approach (~5000 blocks, 30min) +- `thorough`: Comprehensive analysis (~11000 blocks, 2hr) +- `equal`: Equal samples per era +- `proportional`: Proportional to blockchain distribution +- `weighted`: Custom weights per era +- `range`: Analyze specific block range + +### 2. Python Visualizer (`visualize.py`) +**Purpose**: Statistical analysis and visualization + +**Generates 7 Types of Charts**: +1. **Distribution**: Histogram + KDE + box plot +2. **Time Series**: Overhead over blockchain height with era markers +3. **Era Comparison**: Box plots, violin plots, bar charts by era +4. **Correlations**: Overhead vs inputs/outputs/tx count +5. **Cumulative Distribution**: CDF with percentile markers +6. **Bandwidth Impact**: Daily sync, full sync, costs, time projections +7. **Heatmaps**: Overhead by era and transaction characteristics + +**Statistical Report Includes**: +- Summary statistics (mean, median, std dev, percentiles) +- Confidence intervals (95%) +- Statistics broken down by era +- Bandwidth impact calculations +- Correlation analysis +- Decision framework recommendations + +### 3. Documentation + +**README.md**: Complete user guide +- Installation instructions +- Usage examples +- Sampling strategy explanations +- Troubleshooting +- Decision criteria + +**QUICKSTART.md**: 5-minute getting started guide +- Step-by-step setup +- First analysis in minutes +- Common issues and solutions + +**AI_DISCLAIMER.md**: Transparency about AI assistance +- What was AI-generated +- Required validations +- Appropriate/inappropriate uses +- Contribution guidelines + +**.claude_project_context.md**: Technical reference +- Architecture decisions +- Proto structure details +- Common pitfalls diff --git a/QUICKSTART.md b/QUICKSTART.md new file mode 100644 index 0000000..8005589 --- /dev/null +++ b/QUICKSTART.md @@ -0,0 +1,239 @@ +# Quick Start Guide + +Get started analyzing Zcash compact block overhead in 5 minutes. + +## Prerequisites Check + +```bash +# Check Rust is installed +rustc --version + +# Check Python is installed +python --version # Should be 3.8+ + +# Check Zebrad is running +curl -X POST http://127.0.0.1:8232 -d '{"method":"getblockcount","params":[],"id":1}' + +# Check lightwalletd is running +grpcurl -plaintext localhost:9067 list +``` + +## Setup (5 minutes) + +### 1. Get the Project + +```bash +cargo new compact_block_analyzer +cd compact_block_analyzer +mkdir proto +``` + +### 2. Get Protocol Buffers + +```bash +# Clone the lightwallet-protocol repo +git clone https://github.com/zcash/lightwallet-protocol.git temp_proto +cd temp_proto +git fetch origin pull/1/head:pr-1 +git checkout pr-1 + +# Copy proto files +cp compact_formats.proto ../proto/ +cp service.proto ../proto/ + +cd .. +rm -rf temp_proto +``` + +### 3. Setup Build System + +Create `build.rs`: +```rust +fn main() -> Result<(), Box> { + tonic_build::configure() + .build_server(false) + .compile( + &["proto/service.proto", "proto/compact_formats.proto"], + &["proto/"], + )?; + Ok(()) +} +``` + +### 4. Copy Code + +Replace `Cargo.toml` and `src/main.rs` with the provided artifacts. + +### 5. Build + +```bash +cargo build --release +``` + +## Run Your First Analysis (2 minutes) + +### Quick Test (100 blocks) + +```bash +cargo run --release -- \ + http://127.0.0.1:9067 \ + http://127.0.0.1:8232 \ + range 2400000 2400100 \ + test.csv +``` + +### Recommended Analysis (~30 minutes for 5000 blocks) + +```bash +cargo run --release -- \ + http://127.0.0.1:9067 \ + http://127.0.0.1:8232 \ + recommended \ + results.csv +``` + +This will: +- Sample 5000 blocks strategically across all eras +- Take ~30 minutes (100ms delay between blocks) +- Provide statistically significant results + +## Visualize Results (1 minute) + +```bash +# Install Python dependencies +pip install pandas matplotlib seaborn numpy scipy + +# Generate all charts +python visualize.py results.csv +``` + +Open `charts/statistical_report.txt` to see the analysis! + +## Understanding the Output + +### Key Metrics to Look At + +1. **Median overhead** (in the report) + - This is the "typical" overhead + - Most important single number + +2. **95th percentile** (in the report) + - Worst-case planning + - Important for capacity planning + +3. **Distribution chart** (`charts/distribution.png`) + - Shows the spread of overhead values + - Look for the shape (normal, skewed, bimodal?) + +4. **Bandwidth impact chart** (`charts/bandwidth_impact.png`) + - Practical impact: MB per day, sync time, cost + - This makes the numbers concrete + +### Decision Framework + +The report will tell you: + +- **< 20% median overhead**: Low impact, consider making it default +- **20-50% median overhead**: Moderate impact, consider opt-in +- **> 50% median overhead**: High impact, needs separate method + +## Common Issues + +### "Connection refused" on port 9067 +```bash +# Restart lightwalletd +lightwalletd --grpc-bind-addr=127.0.0.1:9067 --zcash-conf-path=/path/to/zebra.conf +``` + +### "Connection refused" on port 8232 +```bash +# Check zebrad is running +ps aux | grep zebrad + +# Check zebra.toml has RPC enabled +# Should have [rpc] section with listen_addr = "127.0.0.1:8232" +``` + +### Build errors about proto files +```bash +# Ensure proto files exist +ls -la proto/ + +# Clean and rebuild +cargo clean +cargo build --release +``` + +### Python import errors +```bash +# Install all dependencies +pip install -r requirements.txt +``` + +## Next Steps + +### Experiment with Different Sampling + +```bash +# Quick analysis (1500 blocks, ~15 minutes) +cargo run --release -- http://127.0.0.1:9067 http://127.0.0.1:8232 quick quick.csv + +# Thorough analysis (11000 blocks, ~2 hours) +cargo run --release -- http://127.0.0.1:9067 http://127.0.0.1:8232 thorough thorough.csv + +# Equal samples per era +cargo run --release -- http://127.0.0.1:9067 http://127.0.0.1:8232 equal equal.csv +``` + +### Compare Different Eras + +```bash +# Pre-Sapling era (heavy transparent) +cargo run --release -- http://127.0.0.1:9067 http://127.0.0.1:8232 range 100000 101000 pre_sapling.csv + +# Recent blocks +cargo run --release -- http://127.0.0.1:9067 http://127.0.0.1:8232 range 2400000 2401000 recent.csv + +# Visualize both +python visualize.py pre_sapling.csv -o charts_pre_sapling +python visualize.py recent.csv -o charts_recent +``` + +### Dive Deeper + +- Read `statistical_report.txt` for detailed analysis +- Examine correlation charts to understand what drives overhead +- Look at heatmaps to see how overhead varies by transaction patterns +- Check time series to see trends over blockchain history + +## Tips for Best Results + +1. **Use 'recommended' mode** for most analyses + - Balanced, statistically sound + - Reasonable time (~30 minutes) + +2. **Run multiple samples** if results seem unexpected + - Sampling has some variance + - Multiple runs can confirm findings + +3. **Focus on recent blocks** for current decisions + - Old blocks less relevant for current usage + - But historical context helps understand trends + +4. **Look at the whole picture** + - Don't just look at mean/median + - Check the distribution, outliers, worst-case + +5. **Consider practical impact** + - MB per day matters more than abstract percentages + - Think about mobile users, limited bandwidth + +## Getting Help + +- Check `README.md` for full documentation +- Check `.claude_project_context.md` for technical details +- Check `AI_DISCLAIMER.md` for limitations +- Open an issue if you find bugs +- Validate results against your own calculations + +Happy analyzing! 🚀 diff --git a/README.md b/README.md index a398789..5a519a1 100644 --- a/README.md +++ b/README.md @@ -100,6 +100,7 @@ zebrad start Verify RPC is accessible: ```bash curl -X POST http://127.0.0.1:8232 \ + -H "Content-Type: application/json" \ -d '{"method":"getblockcount","params":[],"id":1}' ``` @@ -120,77 +121,140 @@ grpcurl -plaintext localhost:9067 list ### Run Analysis +The tool supports multiple analysis modes: + +#### Quick Analysis (~1,500 blocks) ```bash cargo run --release -- \ - \ - \ - \ - \ - [output-csv] + http://127.0.0.1:9067 \ + http://127.0.0.1:8232 \ + quick \ + quick_results.csv ``` -**Example:** +#### Recommended Analysis (~5,000 blocks) - Best Balance ```bash -# Analyze 1000 recent blocks cargo run --release -- \ http://127.0.0.1:9067 \ http://127.0.0.1:8232 \ - 2400000 \ - 2401000 \ + recommended \ results.csv ``` -### Recommended Analysis Ranges +This uses a **hybrid sampling strategy**: +- 750 samples from each protocol era (pre-Sapling, Sapling, Canopy, NU5) +- 2,000 additional samples from recent blocks (last 100K) +- Provides balanced historical context with focus on current usage -**Recent blocks** (most relevant for current usage patterns): +#### Thorough Analysis (~11,000 blocks) ```bash -# Last ~1000 blocks cargo run --release -- \ http://127.0.0.1:9067 \ http://127.0.0.1:8232 \ - 2400000 \ - 2401000 \ - recent_blocks.csv + thorough \ + thorough_results.csv ``` -**Historical comparison** (different network usage patterns): +#### Equal Sampling Per Era (~4,000 blocks) ```bash -# Around Sapling activation (Oct 2018) cargo run --release -- \ http://127.0.0.1:9067 \ http://127.0.0.1:8232 \ - 419200 \ - 420200 \ - sapling_era.csv + equal \ + equal_results.csv +``` -# Around NU5 activation (May 2022) - Orchard introduction +#### Proportional Sampling (~5,000 blocks) +```bash +# Samples proportionally to era size cargo run --release -- \ http://127.0.0.1:9067 \ http://127.0.0.1:8232 \ - 1687104 \ - 1688104 \ - nu5_era.csv + proportional \ + proportional_results.csv ``` -## Output +#### Weighted Sampling (~5,000 blocks) +```bash +# Custom weights favoring recent blocks +cargo run --release -- \ + http://127.0.0.1:9067 \ + http://127.0.0.1:8232 \ + weighted \ + weighted_results.csv +``` -### Console Output +#### Specific Range (Original Mode) +```bash +cargo run --release -- \ + http://127.0.0.1:9067 \ + http://127.0.0.1:8232 \ + range 2400000 2401000 \ + range_results.csv +``` + +### Sampling Strategies Explained + +**Why use sampling?** The Zcash blockchain has 2.4M+ blocks. Analyzing every block would take days. Statistical sampling gives accurate results in minutes. + +| Strategy | Description | Best For | +|----------|-------------|----------| +| **Quick** | Fast overview with fewer samples | Initial exploration | +| **Recommended** | Balanced approach with recent focus | Most use cases | +| **Thorough** | Comprehensive coverage | Final analysis | +| **Equal** | Same samples per era | Era comparison | +| **Proportional** | Samples match blockchain distribution | Representing whole chain | +| **Weighted** | More recent, less historical | Current state focus | -The tool provides real-time progress and summary statistics: +### Visualize Results +After running the analysis, generate charts and statistics: + +```bash +# Install Python dependencies +pip install -r requirements.txt + +# Generate all visualizations +python visualize.py results.csv --output-dir ./charts +``` + +This creates: +- **distribution.png** - Histogram and box plot of overhead +- **time_series.png** - Overhead trends over blockchain height +- **by_era.png** - Comparison across protocol eras +- **correlations.png** - Relationship between overhead and transaction characteristics +- **cumulative.png** - Cumulative distribution functions +- **bandwidth_impact.png** - Practical bandwidth scenarios +- **heatmap.png** - Overhead by era and transaction patterns +- **statistical_report.txt** - Comprehensive statistical analysis + +### Example Output + +**Console output during analysis:** ``` -Analyzing blocks 2400000 to 2401000... -Block 2400000: current=15234 bytes, estimated=18456 bytes, delta=+3222 bytes (21.15%), tx=45, tin=12, tout=89 -Block 2400001: current=12890 bytes, estimated=14234 bytes, delta=+1344 bytes (10.43%), tx=32, tin=5, tout=43 +Current blockchain tip: 2450000 + +Sampling Strategy: HybridRecent +Total samples: 5000 + +Distribution by era: + pre_sapling: 750 samples (15.0% of total, 1 in 559 blocks) + sapling: 750 samples (15.0% of total, 1 in 836 blocks) + canopy: 750 samples (15.0% of total, 1 in 854 blocks) + nu5: 2750 samples (55.0% of total, 1 in 295 blocks) + +Analyzing 5000 blocks... +Progress: 0/5000 (0.0%) +Progress: 500/5000 (10.0%) ... === ANALYSIS SUMMARY === -Blocks analyzed: 1000 +Blocks analyzed: 5000 Current compact blocks: - Total: 15.23 MB + Total: 76.23 MB With transparent data: - Estimated total: 18.67 MB - Delta: +3.44 MB + Estimated total: 93.45 MB + Delta: +17.22 MB Overall increase: 22.58% Per-block statistics: @@ -205,17 +269,87 @@ Practical impact: Additional bandwidth per day: 9.89 MB ``` +**Statistical report snippet:** +``` +DECISION FRAMEWORK +-------------------------------------------------------------------------------- +Median overhead: 18.5% +95th percentile: 35.2% + +RECOMMENDATION: LOW IMPACT + The overhead is relatively small (<20%). Consider making transparent + data part of the default GetBlockRange method. This would: + - Simplify the API (single method) + - Provide feature parity with full nodes + - Have minimal bandwidth impact on users +``` + +## Output + +### Console Output + +The tool provides real-time progress and summary statistics during analysis. + ### CSV Output Detailed per-block analysis in CSV format: ```csv -height,current_compact_size,estimated_with_transparent,delta_bytes,delta_percent,tx_count,transparent_inputs,transparent_outputs -2400000,15234,18456,3222,21.15,45,12,89 -2400001,12890,14234,1344,10.43,32,5,43 +height,era,current_compact_size,estimated_with_transparent,delta_bytes,delta_percent,tx_count,transparent_inputs,transparent_outputs +2400000,nu5,15234,18456,3222,21.15,45,12,89 +2400001,nu5,12890,14234,1344,10.43,32,5,43 ... ``` +### Visualization Output + +The Python script generates comprehensive visualizations: + +1. **Distribution Analysis** + - Histogram with kernel density estimation + - Box plot showing quartiles and outliers + - Marked median and mean values + +2. **Time Series Analysis** + - Overhead percentage over blockchain height + - Absolute size increase over time + - Rolling averages to show trends + - Era boundaries marked + +3. **Era Comparison** + - Box plots comparing distributions across eras + - Violin plots showing density + - Bar charts with standard deviations + - Sample size distribution + +4. **Correlation Analysis** + - Overhead vs transparent inputs + - Overhead vs transparent outputs + - Overhead vs transaction count + - Overhead vs current block size + +5. **Cumulative Distribution** + - CDF of overhead percentages + - CDF of absolute byte increases + - Percentile markers (P50, P75, P90, P95, P99) + +6. **Bandwidth Impact** + - Daily sync bandwidth comparison + - Full chain sync comparison + - Mobile data cost estimates + - Sync time projections + +7. **Heatmaps** + - Overhead by era and transaction count + - Overhead by era and transparent I/O + +8. **Statistical Report** + - Summary statistics with confidence intervals + - Statistics broken down by era + - Practical bandwidth calculations + - Correlation coefficients + - Decision framework recommendations + ## How It Works 1. **Fetch real compact block** from lightwalletd via gRPC diff --git a/analyzer/Cargo.toml b/analyzer/Cargo.toml new file mode 100644 index 0000000..056975f --- /dev/null +++ b/analyzer/Cargo.toml @@ -0,0 +1,28 @@ +[package] +name = "compact-block-analyzer" +version = "0.1.0" +edition = "2021" +authors = ["Your Name "] +license = "MIT OR Apache-2.0" +description = "Analyze bandwidth impact of transparent data in Zcash compact blocks" +repository = "https://github.com/yourusername/compact-block-analyzer" + +[dependencies] +tokio = { version = "1", features = ["full"] } +tonic = "0.11" +prost = "0.12" +prost-types = "0.12" +reqwest = { version = "0.11", features = ["json"] } +serde = { version = "1.0", features = ["derive"] } +serde_json = "1.0" +hex = "0.4" +csv = "1.3" +anyhow = "1.0" +rand = "0.8" +clap = { version = "4.0", features = ["derive"] } + +[build-dependencies] +tonic-build = "0.11" + +[dev-dependencies] +tempfile = "3.0" diff --git a/analyzer/README.md b/analyzer/README.md new file mode 100644 index 0000000..a66a3a2 --- /dev/null +++ b/analyzer/README.md @@ -0,0 +1,508 @@ +# Compact Block Analyzer for Zcash + +A tool to analyze the bandwidth impact of adding transparent transaction data (`CompactTxIn` and `TxOut`) to Zcash's compact block protocol. + +## Overview + +This analyzer helps evaluate the proposed changes to the [lightwallet-protocol](https://github.com/zcash/lightwallet-protocol/pull/1) by measuring: + +- Current compact block sizes from production lightwalletd +- Estimated sizes with transparent input/output data added +- Bandwidth impact on light clients syncing block ranges + +The tool fetches **real compact blocks** from lightwalletd and compares them against estimated sizes calculated from full block data in Zebrad, giving accurate projections of the bandwidth impact. + +## Background + +The Zcash light client protocol currently omits transparent transaction inputs and outputs from compact blocks. [PR #1](https://github.com/zcash/lightwallet-protocol/pull/1) proposes adding: + +- `CompactTxIn` - references to transparent inputs being spent +- `TxOut` - transparent outputs being created + +This analysis helps decide whether to: +- Make transparent data part of the default `GetBlockRange` RPC +- Create a separate opt-in method for clients that need it +- Use pool-based filtering (as implemented in [librustzcash PR #1781](https://github.com/zcash/librustzcash/pull/1781)) + +## Prerequisites + +- **Rust** 1.70+ ([install](https://rustup.rs/)) +- **Zebrad** - synced Zcash full node with RPC enabled +- **Lightwalletd** - connected to your Zebrad instance + +## Installation + +### 1. Clone and Setup + +```bash +# Create the project +cargo new compact_block_analyzer +cd compact_block_analyzer + +# Create proto directory +mkdir proto +``` + +### 2. Get Protocol Buffer Definitions + +```bash +# Clone the lightwallet-protocol repository +git clone https://github.com/zcash/lightwallet-protocol.git +cd lightwallet-protocol + +# Checkout the PR with transparent data additions +git fetch origin pull/1/head:pr-1 +git checkout pr-1 + +# Copy proto files to your project +cp compact_formats.proto ../compact_block_analyzer/proto/ +cp service.proto ../compact_block_analyzer/proto/ + +cd ../compact_block_analyzer +``` + +### 3. Configure Build + +Create `build.rs` in the project root: + +```rust +fn main() -> Result<(), Box> { + tonic_build::configure() + .build_server(false) // Client only + .compile( + &["proto/service.proto", "proto/compact_formats.proto"], + &["proto/"], + )?; + Ok(()) +} +``` + +### 4. Update Dependencies + +Replace `Cargo.toml` with the dependencies from the artifact, or copy `src/main.rs` from the artifact which includes the dependency list. + +### 5. Build + +```bash +cargo build --release +``` + +## Usage + +### Start Required Services + +#### Zebrad +```bash +# If not already running +zebrad start +``` + +Verify RPC is accessible: +```bash +curl -X POST http://127.0.0.1:8232 \ + -d '{"method":"getblockcount","params":[],"id":1}' +``` + +#### Lightwalletd +```bash +lightwalletd \ + --grpc-bind-addr=127.0.0.1:9067 \ + --zcash-conf-path=/path/to/zebra.conf \ + --log-file=/dev/stdout +``` + +Verify lightwalletd is running: +```bash +# With grpcurl installed +grpcurl -plaintext localhost:9067 list +# Should show: cash.z.wallet.sdk.rpc.CompactTxStreamer +``` + +### Run Analysis + +The tool supports multiple analysis modes: + +#### Quick Analysis (~1,500 blocks) +```bash +cargo run --release -- \ + http://127.0.0.1:9067 \ + http://127.0.0.1:8232 \ + quick \ + quick_results.csv +``` + +#### Recommended Analysis (~5,000 blocks) - Best Balance +```bash +cargo run --release -- \ + http://127.0.0.1:9067 \ + http://127.0.0.1:8232 \ + recommended \ + results.csv +``` + +This uses a **hybrid sampling strategy**: +- 750 samples from each protocol era (pre-Sapling, Sapling, Canopy, NU5) +- 2,000 additional samples from recent blocks (last 100K) +- Provides balanced historical context with focus on current usage + +#### Thorough Analysis (~11,000 blocks) +```bash +cargo run --release -- \ + http://127.0.0.1:9067 \ + http://127.0.0.1:8232 \ + thorough \ + thorough_results.csv +``` + +#### Equal Sampling Per Era (~4,000 blocks) +```bash +cargo run --release -- \ + http://127.0.0.1:9067 \ + http://127.0.0.1:8232 \ + equal \ + equal_results.csv +``` + +#### Proportional Sampling (~5,000 blocks) +```bash +# Samples proportionally to era size +cargo run --release -- \ + http://127.0.0.1:9067 \ + http://127.0.0.1:8232 \ + proportional \ + proportional_results.csv +``` + +#### Weighted Sampling (~5,000 blocks) +```bash +# Custom weights favoring recent blocks +cargo run --release -- \ + http://127.0.0.1:9067 \ + http://127.0.0.1:8232 \ + weighted \ + weighted_results.csv +``` + +#### Specific Range (Original Mode) +```bash +cargo run --release -- \ + http://127.0.0.1:9067 \ + http://127.0.0.1:8232 \ + range 2400000 2401000 \ + range_results.csv +``` + +### Sampling Strategies Explained + +**Why use sampling?** The Zcash blockchain has 2.4M+ blocks. Analyzing every block would take days. Statistical sampling gives accurate results in minutes. + +| Strategy | Description | Best For | +|----------|-------------|----------| +| **Quick** | Fast overview with fewer samples | Initial exploration | +| **Recommended** | Balanced approach with recent focus | Most use cases | +| **Thorough** | Comprehensive coverage | Final analysis | +| **Equal** | Same samples per era | Era comparison | +| **Proportional** | Samples match blockchain distribution | Representing whole chain | +| **Weighted** | More recent, less historical | Current state focus | + +### Visualize Results + +After running the analysis, generate charts and statistics: + +```bash +# Install Python dependencies +pip install -r requirements.txt + +# Generate all visualizations +python visualize.py results.csv --output-dir ./charts +``` + +This creates: +- **distribution.png** - Histogram and box plot of overhead +- **time_series.png** - Overhead trends over blockchain height +- **by_era.png** - Comparison across protocol eras +- **correlations.png** - Relationship between overhead and transaction characteristics +- **cumulative.png** - Cumulative distribution functions +- **bandwidth_impact.png** - Practical bandwidth scenarios +- **heatmap.png** - Overhead by era and transaction patterns +- **statistical_report.txt** - Comprehensive statistical analysis + +### Example Output + +**Console output during analysis:** +``` +Current blockchain tip: 2450000 + +Sampling Strategy: HybridRecent +Total samples: 5000 + +Distribution by era: + pre_sapling: 750 samples (15.0% of total, 1 in 559 blocks) + sapling: 750 samples (15.0% of total, 1 in 836 blocks) + canopy: 750 samples (15.0% of total, 1 in 854 blocks) + nu5: 2750 samples (55.0% of total, 1 in 295 blocks) + +Analyzing 5000 blocks... +Progress: 0/5000 (0.0%) +Progress: 500/5000 (10.0%) +... + +=== ANALYSIS SUMMARY === +Blocks analyzed: 5000 +Current compact blocks: + Total: 76.23 MB +With transparent data: + Estimated total: 93.45 MB + Delta: +17.22 MB + Overall increase: 22.58% + +Per-block statistics: + Median increase: 18.45% + 95th percentile: 35.21% + Min: 5.32% + Max: 47.83% + +Practical impact: + Current daily sync (~2880 blocks): 43.86 MB + With transparent: 53.75 MB + Additional bandwidth per day: 9.89 MB +``` + +**Statistical report snippet:** +``` +DECISION FRAMEWORK +-------------------------------------------------------------------------------- +Median overhead: 18.5% +95th percentile: 35.2% + +RECOMMENDATION: LOW IMPACT + The overhead is relatively small (<20%). Consider making transparent + data part of the default GetBlockRange method. This would: + - Simplify the API (single method) + - Provide feature parity with full nodes + - Have minimal bandwidth impact on users +``` + +## Output + +### Console Output + +The tool provides real-time progress and summary statistics during analysis. + +### CSV Output + +Detailed per-block analysis in CSV format: + +```csv +height,era,current_compact_size,estimated_with_transparent,delta_bytes,delta_percent,tx_count,transparent_inputs,transparent_outputs +2400000,nu5,15234,18456,3222,21.15,45,12,89 +2400001,nu5,12890,14234,1344,10.43,32,5,43 +... +``` + +### Visualization Output + +The Python script generates comprehensive visualizations: + +1. **Distribution Analysis** + - Histogram with kernel density estimation + - Box plot showing quartiles and outliers + - Marked median and mean values + +2. **Time Series Analysis** + - Overhead percentage over blockchain height + - Absolute size increase over time + - Rolling averages to show trends + - Era boundaries marked + +3. **Era Comparison** + - Box plots comparing distributions across eras + - Violin plots showing density + - Bar charts with standard deviations + - Sample size distribution + +4. **Correlation Analysis** + - Overhead vs transparent inputs + - Overhead vs transparent outputs + - Overhead vs transaction count + - Overhead vs current block size + +5. **Cumulative Distribution** + - CDF of overhead percentages + - CDF of absolute byte increases + - Percentile markers (P50, P75, P90, P95, P99) + +6. **Bandwidth Impact** + - Daily sync bandwidth comparison + - Full chain sync comparison + - Mobile data cost estimates + - Sync time projections + +7. **Heatmaps** + - Overhead by era and transaction count + - Overhead by era and transparent I/O + +8. **Statistical Report** + - Summary statistics with confidence intervals + - Statistics broken down by era + - Practical bandwidth calculations + - Correlation coefficients + - Decision framework recommendations + +## How It Works + +1. **Fetch real compact block** from lightwalletd via gRPC + - Gets the actual production compact block size + - Includes all current fields (Sapling outputs, Orchard actions, etc.) + +2. **Fetch full block** from Zebrad via RPC + - Gets transparent input/output data + - Provides transaction details needed for estimation + +3. **Calculate overhead** using protobuf encoding rules + - Estimates size of `CompactTxIn` messages (containing `OutPoint`) + - Estimates size of `TxOut` messages (value + scriptPubKey) + - Accounts for protobuf field tags, length prefixes, and nested messages + +4. **Compare and report** + - Current size vs. estimated size with transparent data + - Per-block and aggregate statistics + +## Protobuf Size Estimation + +The estimator calculates sizes based on the proposed proto definitions: + +```protobuf +message OutPoint { + bytes txid = 1; // 32 bytes + uint32 index = 2; // varint +} + +message CompactTxIn { + OutPoint prevout = 1; +} + +message TxOut { + uint32 value = 1; // varint + bytes scriptPubKey = 2; // variable length +} +``` + +Added to `CompactTx`: +```protobuf +repeated CompactTxIn vin = 7; +repeated TxOut vout = 8; +``` + +The calculation includes: +- Field tags (1 byte per field) +- Length prefixes for bytes and nested messages (varint) +- Actual data sizes +- Nested message overhead + +## Interpreting Results + +### Decision Guidelines + +- **< 20% increase**: Consider making transparent data default + - Minimal impact on bandwidth + - Simplifies API (single method) + - Better for light client feature parity + +- **20-50% increase**: Consider separate opt-in method + - Significant but manageable overhead + - Let clients choose based on their needs + - Pool filtering could help (librustzcash PR #1781) + +- **> 50% increase**: Likely needs separate method + - Major bandwidth impact + - Important for mobile/limited bandwidth users + - Clear opt-in for clients that need transparent data + +### Key Metrics to Examine + +1. **Median increase** - typical overhead +2. **95th percentile** - worst-case for active blocks +3. **Daily bandwidth impact** - practical cost for staying synced +4. **Initial sync impact** - multiply by ~2.4M blocks +5. **Correlation with transparent usage** - understand which blocks drive overhead + +## Troubleshooting + +### Connection Errors + +**Port 9067 (lightwalletd):** +```bash +# Check if running +ps aux | grep lightwalletd +netstat -tlnp | grep 9067 + +# Test connection +grpcurl -plaintext localhost:9067 list +``` + +**Port 8232 (zebrad):** +```bash +# Check if running +ps aux | grep zebrad +netstat -tlnp | grep 8232 + +# Test RPC +curl -X POST http://127.0.0.1:8232 \ + -d '{"method":"getblockcount","params":[],"id":1}' +``` + +### Build Errors + +**Proto compilation fails:** +```bash +# Ensure proto files exist +ls -la proto/ + +# Clean and rebuild +cargo clean +cargo build --release +``` + +**"Block not found" errors:** +- Check if block height exists on mainnet +- Verify Zebrad is fully synced +- Ensure lightwalletd has indexed the blocks + +### Rate Limiting + +The tool includes a 100ms delay between blocks to avoid overwhelming your node. For faster analysis: + +1. Reduce the delay in the code +2. Run multiple instances for different ranges +3. Use a more powerful machine for Zebrad + +## Contributing + +This tool is designed for protocol analysis. Contributions welcome: + +- Improved size estimation accuracy +- Additional output formats (JSON, charts) +- Statistical analysis enhancements +- Performance optimizations + +## Related Work + +- [lightwallet-protocol PR #1](https://github.com/zcash/lightwallet-protocol/pull/1) - Proto definitions +- [librustzcash PR #1781](https://github.com/zcash/librustzcash/pull/1781) - Pool filtering implementation +- [Zcash Protocol Specification](https://zips.z.cash/) - Full protocol details + +## License + +Same license as the Zcash lightwallet-protocol project. + +## Support + +For questions or issues: +- Open an issue in this repository +- Discuss on Zcash Community Forum +- Zcash R&D Discord + +## Acknowledgments + +Built to support analysis for improving Zcash light client protocol bandwidth efficiency. diff --git a/build.rs b/analyzer/build.rs similarity index 79% rename from build.rs rename to analyzer/build.rs index 8b51f54..5179ef9 100644 --- a/build.rs +++ b/analyzer/build.rs @@ -1,6 +1,6 @@ fn main() -> Result<(), Box> { tonic_build::configure() - .build_server(false) // We only need the client + .build_server(false) .compile( &["proto/service.proto", "proto/compact_formats.proto"], &["proto/"], diff --git a/proto/compact_formats.proto b/analyzer/proto/compact_formats.proto similarity index 74% rename from proto/compact_formats.proto rename to analyzer/proto/compact_formats.proto index 09df06d..493ffed 100644 --- a/proto/compact_formats.proto +++ b/analyzer/proto/compact_formats.proto @@ -10,16 +10,18 @@ option swift_prefix = ""; // Remember that proto3 fields are all optional. A field that is not present will be set to its zero value. // bytes fields of hashes are in canonical little-endian format. -// ChainMetadata represents information about the state of the chain as of a given block. +// Information about the state of the chain as of a given block. message ChainMetadata { uint32 saplingCommitmentTreeSize = 1; // the size of the Sapling note commitment tree as of the end of this block uint32 orchardCommitmentTreeSize = 2; // the size of the Orchard note commitment tree as of the end of this block } +// A compact representation of the shielded data in a Zcash block. +// // CompactBlock is a packaging of ONLY the data from a block that's needed to: -// 1. Detect a payment to your shielded Sapling address -// 2. Detect a spend of your shielded Sapling notes -// 3. Update your witnesses to generate new Sapling spend proofs. +// 1. Detect a payment to your Shielded address +// 2. Detect a spend of your Shielded notes +// 3. Update your witnesses to generate new spend proofs. message CompactBlock { uint32 protoVersion = 1; // the version of this wire format, for storage uint64 height = 2; // the height of this block @@ -31,6 +33,8 @@ message CompactBlock { ChainMetadata chainMetadata = 8; // information about the state of the chain as of this block } +// A compact representation of the shielded data in a Zcash transaction. +// // CompactTx contains the minimum information for a wallet to know if this transaction // is relevant to it (either pays to it or spends from it) via shielded elements // only. This message will not encode a transparent-to-transparent transaction. @@ -53,25 +57,25 @@ message CompactTx { repeated CompactOrchardAction actions = 6; } +// A compact representation of a [Sapling Spend](https://zips.z.cash/protocol/protocol.pdf#spendencodingandconsensus). +// // CompactSaplingSpend is a Sapling Spend Description as described in 7.3 of the Zcash // protocol specification. message CompactSaplingSpend { - bytes nf = 1; // nullifier (see the Zcash protocol specification) + bytes nf = 1; // Nullifier (see the Zcash protocol specification) } -// output encodes the `cmu` field, `ephemeralKey` field, and a 52-byte prefix of the -// `encCiphertext` field of a Sapling Output Description. These fields are described in -// section 7.4 of the Zcash protocol spec: -// https://zips.z.cash/protocol/protocol.pdf#outputencodingandconsensus -// Total size is 116 bytes. +// A compact representation of a [Sapling Output](https://zips.z.cash/protocol/protocol.pdf#outputencodingandconsensus). +// +// It encodes the `cmu` field, `ephemeralKey` field, and a 52-byte prefix of the +// `encCiphertext` field of a Sapling Output Description. Total size is 116 bytes. message CompactSaplingOutput { - bytes cmu = 1; // note commitment u-coordinate - bytes ephemeralKey = 2; // ephemeral public key - bytes ciphertext = 3; // first 52 bytes of ciphertext + bytes cmu = 1; // Note commitment u-coordinate. + bytes ephemeralKey = 2; // Ephemeral public key. + bytes ciphertext = 3; // First 52 bytes of ciphertext. } -// https://github.com/zcash/zips/blob/main/zip-0225.rst#orchard-action-description-orchardaction -// (but not all fields are needed) +// A compact representation of an [Orchard Action](https://zips.z.cash/protocol/protocol.pdf#actionencodingandconsensus). message CompactOrchardAction { bytes nullifier = 1; // [32] The nullifier of the input note bytes cmx = 2; // [32] The x-coordinate of the note commitment for the output note diff --git a/proto/service.proto b/analyzer/proto/service.proto similarity index 94% rename from proto/service.proto rename to analyzer/proto/service.proto index 669a62d..70fcdbd 100644 --- a/proto/service.proto +++ b/analyzer/proto/service.proto @@ -31,9 +31,12 @@ message TxFilter { bytes hash = 3; // transaction ID (hash, txid) } -// RawTransaction contains the complete transaction data. It also includes the -// height for the block in which the transaction was included in the main -// chain, if any (as detailed below). +// RawTransaction contains the complete transaction data. It also optionally includes +// the block height in which the transaction was included, or, when returned +// by GetMempoolStream(), the latest block height. +// +// FIXME: the documentation here about mempool status contradicts the documentation +// for the `height` field. See https://github.com/zcash/librustzcash/issues/1484 message RawTransaction { // The serialized representation of the Zcash transaction. bytes data = 1; @@ -176,7 +179,7 @@ message GetAddressUtxosReplyList { } service CompactTxStreamer { - // Return the height of the tip of the best chain + // Return the BlockID of the block at the tip of the best chain rpc GetLatestBlock(ChainSpec) returns (BlockID) {} // Return the compact block corresponding to the given block identifier rpc GetBlock(BlockID) returns (CompactBlock) {} @@ -192,8 +195,9 @@ service CompactTxStreamer { // Submit the given transaction to the Zcash network rpc SendTransaction(RawTransaction) returns (SendResponse) {} - // Return the transactions corresponding to the given t-address within the given block range - // NB - this method is misnamed, it returns transactions, not transaction IDs. + // Return RawTransactions that match the given transparent address filter. + // + // Note: This function is misnamed, it returns complete `RawTransaction` values, not TxIds. // NOTE: this method is deprecated, please use GetTaddressTransactions instead. rpc GetTaddressTxids(TransparentAddressBlockFilter) returns (stream RawTransaction) {} diff --git a/analyzer/quick_results.csv b/analyzer/quick_results.csv new file mode 100644 index 0000000..5da372d --- /dev/null +++ b/analyzer/quick_results.csv @@ -0,0 +1,2001 @@ +height,era,current_compact_size,estimated_with_transparent,delta_bytes,delta_percent,tx_count,transparent_inputs,transparent_outputs +419962,sapling,83,229,146,175.9036144578313,1,1,2 +420300,sapling,83,1401,1318,1587.9518072289156,2,1,37 +422151,sapling,83,920,837,1008.433734939759,7,8,14 +423983,sapling,83,5450,5367,6466.265060240964,12,116,18 +425817,sapling,83,20419,20336,24501.20481927711,27,270,280 +427249,sapling,83,10380,10297,12406.024096385541,6,77,214 +427552,sapling,83,1200,1117,1345.7831325301206,10,10,20 +428734,sapling,83,336,253,304.81927710843377,2,2,4 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-36,12 +45,20 @@ struct ZebraTransaction { struct ZebraVin { txid: Option, vout: Option, + #[serde(rename = "scriptSig")] + script_sig: Option, + sequence: u32, } +#[derive(Debug, Deserialize)] +struct ScriptSig { + hex: String, +} #[derive(Debug, Deserialize)] struct ZebraVout { value: f64, + n: u32, #[serde(rename = "scriptPubKey")] script_pubkey: ScriptPubKey, } @@ -51,9 +68,11 @@ struct ScriptPubKey { hex: String, } +// Analysis results #[derive(Debug, Serialize)] struct BlockAnalysis { height: u64, + era: String, current_compact_size: usize, estimated_with_transparent: usize, delta_bytes: i64, @@ -78,6 +97,29 @@ impl TransparentEstimator { } } + async fn get_current_tip(&self) -> Result { + let request = serde_json::json!({ + "jsonrpc": "2.0", + "method": "getblockcount", + "params": [], + "id": 1 + }); + + let response: serde_json::Value = self + .http_client + .post(&self.zebra_rpc_url) + .json(&request) + .send() + .await? + .json() + .await?; + + let tip = response["result"].as_u64() + .ok_or_else(|| anyhow::anyhow!("Failed to get block count"))?; + + Ok(tip) + } + async fn get_compact_block_from_lightwalletd(&self, height: u64) -> Result> { // Connect to lightwalletd gRPC service let mut client = CompactTxStreamerClient::connect(self.lightwalletd_url.clone()).await?; @@ -142,6 +184,8 @@ impl TransparentEstimator { // OutPoint prevout = 1; // nested message // } // + // For coinbase, we'll estimate a fixed overhead since the .proto isn't finalized yet + // // message TxOut { // uint32 value = 1; // varint (note: uint32, not uint64!) // bytes scriptPubKey = 2; // variable length @@ -158,8 +202,8 @@ impl TransparentEstimator { for tx in &block.tx { // Estimate CompactTxIn (repeated field in CompactTx) for vin in &tx.vin { - if let (Some(txid), Some(vout_idx)) = (&vin.txid, &vin.vout) { - // Not a coinbase + if let (Some(_txid), Some(vout_idx)) = (&vin.txid, &vin.vout) { + // Regular transparent input (not a coinbase) // OutPoint message size: let mut outpoint_size = 0; @@ -183,6 +227,22 @@ impl TransparentEstimator { total_overhead += vin_entry_size; input_count += 1; + } else { + // Coinbase input + // Since the .proto isn't finalized, we estimate a fixed size + // Typical coinbase: ~40-100 bytes of data + sequence + // Conservative estimate for CompactTxIn with coinbase: + // - Field tag for coinbase data: 1 byte + // - Length prefix: 1 byte (for typical 40-100 byte coinbase) + // - Coinbase data: ~70 bytes average + // - Field tag for sequence: 1 byte + // - Sequence value: 4 bytes + // - Repeated field overhead: 1 byte tag + 1 byte length + // Total: ~79 bytes + + const COINBASE_COMPACT_TXIN_SIZE: usize = 79; + total_overhead += COINBASE_COMPACT_TXIN_SIZE; + input_count += 1; } } @@ -241,6 +301,7 @@ impl TransparentEstimator { Ok(BlockAnalysis { height, + era: String::new(), // Will be set by analyze_blocks current_compact_size: current_size, estimated_with_transparent: estimated_size, delta_bytes: delta, @@ -251,22 +312,27 @@ impl TransparentEstimator { }) } - async fn analyze_range(&self, start: u64, end: u64) -> Result> { + async fn analyze_blocks(&self, heights: &[u64]) -> Result> { let mut results = Vec::new(); + let total = heights.len(); + let eras = Era::zcash_eras(*heights.last().unwrap_or(&2_400_000)); + + for (i, &height) in heights.iter().enumerate() { + if i % 10 == 0 { + println!("Progress: {}/{} ({:.1}%)", i, total, (i as f64 / total as f64) * 100.0); + } - for height in start..=end { match self.analyze_block(height).await { - Ok(analysis) => { + Ok(mut analysis) => { + analysis.era = Era::get_era_for_height(height, &eras); println!( - "Block {}: current={} bytes, estimated={} bytes, delta=+{} bytes ({:.2}%), tx={}, tin={}, tout={}", + "Block {}: current={} bytes, estimated={} bytes, delta=+{} bytes ({:.2}%), era={}", height, analysis.current_compact_size, analysis.estimated_with_transparent, analysis.delta_bytes, analysis.delta_percent, - analysis.tx_count, - analysis.transparent_inputs, - analysis.transparent_outputs + analysis.era ); results.push(analysis); } @@ -278,6 +344,7 @@ impl TransparentEstimator { tokio::time::sleep(tokio::time::Duration::from_millis(100)).await; } + println!("Progress: {}/{} (100.0%)", total, total); Ok(results) } @@ -322,7 +389,7 @@ impl TransparentEstimator { // Practical impact examples println!("\nPractical impact:"); - let blocks_per_day = 24 * 60 * 60 / 75; // 1 block every 75 seconds on Zcash + let blocks_per_day = 1152; // Post-Blossom (75s blocks) let daily_current = (total_current as f64 / results.len() as f64) * blocks_per_day as f64; let daily_estimated = (total_estimated as f64 / results.len() as f64) * blocks_per_day as f64; println!(" Current daily sync (~{} blocks): {:.2} MB", blocks_per_day, daily_current / 1_000_000.0); @@ -335,31 +402,99 @@ impl TransparentEstimator { async fn main() -> Result<()> { let args: Vec = std::env::args().collect(); - if args.len() < 5 { - eprintln!("Usage: {} [output.csv]", args[0]); - eprintln!("Example: {} http://localhost:9067 http://localhost:8232 2400000 2401000 results.csv", args[0]); + if args.len() < 4 { + eprintln!("Usage: {} [output.csv]", args[0]); + eprintln!(); + eprintln!("Modes:"); + eprintln!(" range - Analyze specific block range"); + eprintln!(" quick - Quick sampling (~1500 blocks)"); + eprintln!(" recommended - Balanced sampling (~5000 blocks)"); + eprintln!(" thorough - Thorough sampling (~11000 blocks)"); + eprintln!(" equal - Equal samples per era (~4000 blocks)"); + eprintln!(" proportional - Proportional to era size (~5000 blocks)"); + eprintln!(" weighted - Weighted toward recent (~5000 blocks)"); + eprintln!(); + eprintln!("Examples:"); + eprintln!(" {} http://127.0.0.1:9067 http://127.0.0.1:8232 range 2400000 2401000", args[0]); + eprintln!(" {} http://127.0.0.1:9067 http://127.0.0.1:8232 recommended results.csv", args[0]); std::process::exit(1); } let lightwalletd_url = &args[1]; let zebra_rpc_url = &args[2]; - let start_height: u64 = args[3].parse()?; - let end_height: u64 = args[4].parse()?; - let output_file = args.get(5).map(|s| s.as_str()).unwrap_or("analysis.csv"); + let mode = &args[3]; + // Get current tip from Zebra let estimator = TransparentEstimator::new( zebra_rpc_url.to_string(), lightwalletd_url.to_string(), ); + + let current_tip = estimator.get_current_tip().await?; + println!("Current blockchain tip: {}", current_tip); + println!(); + + let (blocks, output_file) = match mode.as_str() { + "range" => { + if args.len() < 6 { + eprintln!("Error: range mode requires "); + std::process::exit(1); + } + let start: u64 = args[4].parse()?; + let end: u64 = args[5].parse()?; + let output = args.get(6).map(|s| s.as_str()).unwrap_or("results.csv"); + ((start..=end).collect(), output.to_string()) + } + "quick" => { + let sampler = create_quick_sampler(current_tip); + println!("{}", sampler.describe()); + let output = args.get(4).map(|s| s.as_str()).unwrap_or("quick_sample.csv"); + (sampler.generate_samples(), output.to_string()) + } + "recommended" => { + let sampler = create_recommended_sampler(current_tip); + println!("{}", sampler.describe()); + let output = args.get(4).map(|s| s.as_str()).unwrap_or("recommended_sample.csv"); + (sampler.generate_samples(), output.to_string()) + } + "thorough" => { + let sampler = create_thorough_sampler(current_tip); + println!("{}", sampler.describe()); + let output = args.get(4).map(|s| s.as_str()).unwrap_or("thorough_sample.csv"); + (sampler.generate_samples(), output.to_string()) + } + "equal" => { + let sampler = create_equal_sampler(current_tip); + println!("{}", sampler.describe()); + let output = args.get(4).map(|s| s.as_str()).unwrap_or("equal_sample.csv"); + (sampler.generate_samples(), output.to_string()) + } + "proportional" => { + let sampler = create_proportional_sampler(current_tip); + println!("{}", sampler.describe()); + let output = args.get(4).map(|s| s.as_str()).unwrap_or("proportional_sample.csv"); + (sampler.generate_samples(), output.to_string()) + } + "weighted" => { + let sampler = create_weighted_sampler(current_tip); + println!("{}", sampler.describe()); + let output = args.get(4).map(|s| s.as_str()).unwrap_or("weighted_sample.csv"); + (sampler.generate_samples(), output.to_string()) + } + _ => { + eprintln!("Error: Unknown mode '{}'", mode); + std::process::exit(1); + } + }; - println!("Analyzing blocks {} to {}...", start_height, end_height); + println!("Analyzing {} blocks...", blocks.len()); println!("Fetching real compact blocks from lightwalletd: {}", lightwalletd_url); - println!("Fetching full blocks from Zebrad: {}", zebra_rpc_url); + println!("Fetching full blocks from Zebra: {}", zebra_rpc_url); println!(); - let results = estimator.analyze_range(start_height, end_height).await?; + let results = estimator.analyze_blocks(&blocks).await?; - estimator.write_csv(&results, output_file)?; + estimator.write_csv(&results, &output_file)?; println!("\nDetailed results written to: {}", output_file); estimator.print_summary(&results); diff --git a/analyzer/src/sampling.rs b/analyzer/src/sampling.rs new file mode 100644 index 0000000..feeec7c --- /dev/null +++ b/analyzer/src/sampling.rs @@ -0,0 +1,406 @@ +// Add to Cargo.toml: +// rand = "0.8" + +use rand::seq::SliceRandom; +use rand::SeedableRng; +use std::collections::BTreeSet; + +#[derive(Debug, Clone)] +pub struct Era { + pub name: String, + pub start: u64, + pub end: u64, +} + +impl Era { + pub fn zcash_eras(current_tip: u64) -> Vec { + vec![ + Era { + name: "sapling".to_string(), + start: 419_200, + end: 653_599, + }, + Era { + name: "blossom".to_string(), + start: 653_600, + end: 903_799, + }, + Era { + name: "heartwood".to_string(), + start: 903_800, + end: 1_046_399, + }, + Era { + name: "canopy".to_string(), + start: 1_046_400, + end: 1_687_103, + }, + Era { + name: "nu5".to_string(), + start: 1_687_104, + end: 2_726_399, + }, + Era { + name: "nu6".to_string(), + start: 2_726_400, + end: current_tip, + }, + ] + } + + pub fn size(&self) -> u64 { + self.end - self.start + 1 + } + + pub fn get_era_for_height(height: u64, eras: &[Era]) -> String { + for era in eras { + if height >= era.start && height <= era.end { + return era.name.clone(); + } + } + "unknown".to_string() + } +} + +#[derive(Debug)] +pub enum SamplingStrategy { + // Sample N blocks from each era equally + EqualPerEra { + samples_per_era: usize, + }, + + // Sample proportionally to era size + Proportional { + total_samples: usize, + }, + + // Equal per era + additional recent samples + HybridRecent { + base_per_era: usize, + recent_additional: usize, + recent_window: u64, // e.g., last 100k blocks + }, + + // Fixed density: 1 in every N blocks + FixedDensity { + every_n: u64, + }, + + // Custom weights per era + Weighted { + weights: Vec<(String, f64)>, // (era_name, weight_0_to_1) + total_samples: usize, + }, + + // All blocks in range (for small ranges) + Complete { + start: u64, + end: u64, + }, +} + +pub struct Sampler { + strategy: SamplingStrategy, + eras: Vec, + seed: Option, +} + +impl Sampler { + pub fn new(strategy: SamplingStrategy, current_tip: u64, seed: Option) -> Self { + let eras = Era::zcash_eras(current_tip); + Self { + strategy, + eras, + seed, + } + } + + pub fn generate_samples(&self) -> Vec { + match &self.strategy { + SamplingStrategy::EqualPerEra { samples_per_era } => { + self.equal_per_era(*samples_per_era) + } + SamplingStrategy::Proportional { total_samples } => self.proportional(*total_samples), + SamplingStrategy::HybridRecent { + base_per_era, + recent_additional, + recent_window, + } => self.hybrid_recent(*base_per_era, *recent_additional, *recent_window), + SamplingStrategy::FixedDensity { every_n } => self.fixed_density(*every_n), + SamplingStrategy::Weighted { + weights, + total_samples, + } => self.weighted(weights, *total_samples), + SamplingStrategy::Complete { start, end } => (*start..=*end).collect(), + } + } + + fn equal_per_era(&self, samples_per_era: usize) -> Vec { + let mut all_samples = BTreeSet::new(); + + for era in &self.eras { + let samples = self.random_sample_from_range( + era.start, + era.end, + samples_per_era.min(era.size() as usize), + ); + all_samples.extend(samples); + } + + all_samples.into_iter().collect() + } + + fn proportional(&self, total_samples: usize) -> Vec { + let mut all_samples = BTreeSet::new(); + let total_blocks: u64 = self.eras.iter().map(|e| e.size()).sum(); + + for era in &self.eras { + let era_proportion = era.size() as f64 / total_blocks as f64; + let era_samples = (total_samples as f64 * era_proportion).round() as usize; + + let samples = self.random_sample_from_range( + era.start, + era.end, + era_samples.min(era.size() as usize), + ); + all_samples.extend(samples); + } + + all_samples.into_iter().collect() + } + + fn hybrid_recent( + &self, + base_per_era: usize, + recent_additional: usize, + recent_window: u64, + ) -> Vec { + let mut all_samples = BTreeSet::new(); + + // Base samples from each era + for era in &self.eras { + let samples = self.random_sample_from_range( + era.start, + era.end, + base_per_era.min(era.size() as usize), + ); + all_samples.extend(samples); + } + + // Additional samples from recent blocks + if let Some(last_era) = self.eras.last() { + let recent_start = last_era.end.saturating_sub(recent_window); + let samples = + self.random_sample_from_range(recent_start, last_era.end, recent_additional); + all_samples.extend(samples); + } + + all_samples.into_iter().collect() + } + + fn fixed_density(&self, every_n: u64) -> Vec { + let mut samples = Vec::new(); + + for era in &self.eras { + let mut height = era.start; + while height <= era.end { + samples.push(height); + height += every_n; + } + } + + samples + } + + fn weighted(&self, weights: &[(String, f64)], total_samples: usize) -> Vec { + let mut all_samples = BTreeSet::new(); + let weight_sum: f64 = weights.iter().map(|(_, w)| w).sum(); + + for (era_name, weight) in weights { + if let Some(era) = self.eras.iter().find(|e| &e.name == era_name) { + let era_samples = ((total_samples as f64) * (weight / weight_sum)).round() as usize; + let samples = self.random_sample_from_range( + era.start, + era.end, + era_samples.min(era.size() as usize), + ); + all_samples.extend(samples); + } + } + + all_samples.into_iter().collect() + } + + fn random_sample_from_range(&self, start: u64, end: u64, sample_size: usize) -> Vec { + let range_size = (end - start + 1) as usize; + + if sample_size >= range_size { + // If we want more samples than available, just return all + return (start..=end).collect(); + } + + let mut rng = if let Some(seed) = self.seed { + rand::rngs::StdRng::seed_from_u64(seed) + } else { + rand::rngs::StdRng::from_entropy() + }; + + let all_heights: Vec = (start..=end).collect(); + let mut samples: Vec = all_heights + .choose_multiple(&mut rng, sample_size) + .cloned() + .collect(); + + samples.sort(); + samples + } + + pub fn describe(&self) -> String { + let samples = self.generate_samples(); + let total = samples.len(); + + let mut description = format!("Sampling Strategy: {:?}\n", self.strategy); + description.push_str(&format!("Total samples: {}\n\n", total)); + description.push_str("Distribution by era:\n"); + + for era in &self.eras { + let era_samples = samples + .iter() + .filter(|&&h| h >= era.start && h <= era.end) + .count(); + let percentage = (era_samples as f64 / total as f64) * 100.0; + let density = era_samples as f64 / era.size() as f64; + + description.push_str(&format!( + " {}: {} samples ({:.1}% of total, 1 in {:.0} blocks)\n", + era.name, + era_samples, + percentage, + 1.0 / density + )); + } + + description + } +} + +// Example usage in main +pub fn create_recommended_sampler(current_tip: u64) -> Sampler { + // Hybrid approach: 750 samples per era + 2000 from recent 100k blocks + Sampler::new( + SamplingStrategy::HybridRecent { + base_per_era: 750, + recent_additional: 2000, + recent_window: 100_000, + }, + current_tip, + Some(42), // Fixed seed for reproducibility + ) +} + +pub fn create_quick_sampler(current_tip: u64) -> Sampler { + // Quick analysis: fewer samples + Sampler::new( + SamplingStrategy::HybridRecent { + base_per_era: 250, + recent_additional: 500, + recent_window: 50_000, + }, + current_tip, + Some(42), + ) +} + +pub fn create_thorough_sampler(current_tip: u64) -> Sampler { + // Thorough analysis: more samples + Sampler::new( + SamplingStrategy::HybridRecent { + base_per_era: 1500, + recent_additional: 5000, + recent_window: 200_000, + }, + current_tip, + Some(42), + ) +} + +pub fn create_equal_sampler(current_tip: u64) -> Sampler { + // Equal samples per era + Sampler::new( + SamplingStrategy::EqualPerEra { + samples_per_era: 1000, + }, + current_tip, + Some(42), + ) +} + +pub fn create_proportional_sampler(current_tip: u64) -> Sampler { + // Proportional to era size + Sampler::new( + SamplingStrategy::Proportional { + total_samples: 5000, + }, + current_tip, + Some(42), + ) +} + +pub fn create_weighted_sampler(current_tip: u64) -> Sampler { + // Custom weights - focus on recent + Sampler::new( + SamplingStrategy::Weighted { + weights: vec![ + ("sapling".to_string(), 0.10), + ("blossom".to_string(), 0.10), + ("heartwood".to_string(), 0.10), + ("canopy".to_string(), 0.20), + ("nu5".to_string(), 0.30), + ("nu6".to_string(), 0.20), + ], + total_samples: 5000, + }, + current_tip, + Some(42), + ) +} + +#[cfg(test)] +mod tests { + use super::*; + + #[test] + fn test_equal_per_era() { + let sampler = create_equal_sampler(2_400_000); + let samples = sampler.generate_samples(); + + // Should have roughly 4000 samples (1000 per era) + assert!(samples.len() >= 3800 && samples.len() <= 4200); + + // Samples should be sorted + assert!(samples.windows(2).all(|w| w[0] < w[1])); + } + + #[test] + fn test_hybrid_recent() { + let sampler = create_recommended_sampler(2_400_000); + let samples = sampler.generate_samples(); + + println!("{}", sampler.describe()); + + // Should have base + recent samples + assert!(samples.len() >= 4500 && samples.len() <= 5500); + } + + #[test] + fn test_reproducibility() { + let sampler1 = create_equal_sampler(2_400_000); + let sampler2 = create_equal_sampler(2_400_000); + + let samples1 = sampler1.generate_samples(); + let samples2 = sampler2.generate_samples(); + + // Same seed should produce identical samples + assert_eq!(samples1, samples2); + } +} diff --git a/docs/architecture.md b/docs/architecture.md new file mode 100644 index 0000000..c22c6f0 --- /dev/null +++ b/docs/architecture.md @@ -0,0 +1,58 @@ +# Architecture + +## System Overview + +``` +┌─────────────┐ ┌──────────────┐ +│ Lightwalletd│◄────────┤ Analyzer │ +│ (gRPC) │ │ (Rust) │ +└─────────────┘ └──────┬───────┘ + │ +┌─────────────┐ │ +│ Zebrad │◄───────────────┘ +│ (JSON-RPC) │ +└─────────────┘ + + │ + ├─────► CSV Output + │ + ▼ +┌──────────────┐ +│ Visualizer │ +│ (Python) │ +└──────┬───────┘ + │ + ├─────► Charts (PNG) + └─────► Statistical Report (TXT) +``` + +## Data Flow + +1. **Sampling**: Generate block heights to analyze +2. **Fetch Real Data**: Get CompactBlock from lightwalletd +3. **Fetch Full Data**: Get full block from Zebrad +4. **Estimate**: Calculate transparent overhead +5. **Output**: Write to CSV +6. **Visualize**: Generate charts and statistics + +## Key Components + +### Sampling Module +- Multiple strategies (equal, proportional, hybrid, etc.) +- Era-aware sampling +- Reproducible with fixed seeds + +### Estimator Module +- Protobuf size calculations +- Transparent I/O overhead estimation +- Accurate field-level sizing + +### RPC Clients +- gRPC client for lightwalletd +- JSON-RPC client for Zebrad +- Error handling and retries + +### Visualizer +- Statistical analysis +- Chart generation +- Decision recommendations diff --git a/docs/sampling-strategies.md b/docs/sampling-strategies.md new file mode 100644 index 0000000..e67f78b --- /dev/null +++ b/docs/sampling-strategies.md @@ -0,0 +1,53 @@ +# Sampling Strategies + +## Overview + +Analyzing 2.7M+ blocks would take days. Statistical sampling provides accurate results in minutes. + +## Available Strategies + +### 1. Quick (~1,500 blocks, 15 min) +- 250 per era +- 500 additional recent samples +- Good for initial exploration + +### 2. Recommended (~5,000 blocks, 30 min) +- 750 per era +- 2,000 additional recent samples +- Best balance of accuracy and speed +- **Use this for most analyses** + +### 3. Thorough (~11,000 blocks, 2 hr) +- 1,500 per era +- 5,000 additional recent samples +- Highest confidence intervals +- Use for final analysis + +### 4. Equal (~4,000 blocks) +- 1,000 samples per era +- Good for comparing eras +- May over-represent old eras + +### 5. Proportional (~5,000 blocks) +- Samples match blockchain distribution +- Statistically representative +- Gives equal weight to old and new + +### 6. Weighted (~5,000 blocks) +- Custom weights per era +- Default: heavier on recent +- Flexible for specific needs + +## Choosing a Strategy + +**For protocol decisions**: Use Recommended or Thorough +**For era comparison**: Use Equal +**For quick validation**: Use Quick +**For custom needs**: Use Weighted + +## Sample Size Calculations + +For 95% confidence and ±2% margin of error: +n = (1.96² × 0.5 × 0.5) / 0.02² ≈ 2,401 + +We use 5,000+ samples for better confidence. diff --git a/examples/era_comparison.sh b/examples/era_comparison.sh new file mode 100755 index 0000000..eef1280 --- /dev/null +++ b/examples/era_comparison.sh @@ -0,0 +1,37 @@ +#!/bin/bash +# Compare overhead across different eras + +cd "$(dirname "$0")/.." +ANALYZER="./analyzer/target/release/compact-block-analyzer" +OUTPUT="results/era_comparison_$(date +%Y%m%d)" +mkdir -p "$OUTPUT" + +echo "🔬 Running era comparison analysis..." + +# Sample each era +echo "📊 Analyzing Sapling era..." +$ANALYZER http://127.0.0.1:9067 http://127.0.0.1:8232 range 500000 500500 "$OUTPUT/sapling.csv" + +echo "📊 Analyzing Blossom era..." +$ANALYZER http://127.0.0.1:9067 http://127.0.0.1:8232 range 750000 750500 "$OUTPUT/blossom.csv" + +echo "📊 Analyzing Canopy era..." +$ANALYZER http://127.0.0.1:9067 http://127.0.0.1:8232 range 1300000 1300500 "$OUTPUT/canopy.csv" + +echo "📊 Analyzing NU5 era..." +$ANALYZER http://127.0.0.1:9067 http://127.0.0.1:8232 range 2000000 2000500 "$OUTPUT/nu5.csv" + +echo "📊 Analyzing NU6 era..." +$ANALYZER http://127.0.0.1:9067 http://127.0.0.1:8232 range 2800000 2800500 "$OUTPUT/nu6.csv" + +# Visualize each +echo "📈 Generating visualizations..." +cd visualization +source venv/bin/activate +for csv in "../$OUTPUT"/*.csv; do + basename="${csv%.csv}" + python visualize.py "$csv" -o "${basename}_charts" +done +cd .. + +echo "✅ Era comparison complete: $OUTPUT" diff --git a/examples/quick_analysis.sh b/examples/quick_analysis.sh new file mode 100755 index 0000000..129c6ba --- /dev/null +++ b/examples/quick_analysis.sh @@ -0,0 +1,7 @@ +#!/bin/bash +cd "$(dirname "$0")/.." +./analyzer/target/release/compact-block-analyzer \ + http://127.0.0.1:9067 \ + http://127.0.0.1:8232 \ + quick \ + results/quick_$(date +%Y%m%d).csv diff --git a/examples/recommended_analysis.sh b/examples/recommended_analysis.sh new file mode 100755 index 0000000..f45e0a4 --- /dev/null +++ b/examples/recommended_analysis.sh @@ -0,0 +1,7 @@ +#!/bin/bash +cd "$(dirname "$0")/.." +./analyzer/target/release/compact-block-analyzer \ + http://127.0.0.1:9067 \ + http://127.0.0.1:8232 \ + recommended \ + results/recommended_$(date +%Y%m%d).csv diff --git a/proto/darkside.proto b/proto/darkside.proto deleted file mode 100644 index 02a8855..0000000 --- a/proto/darkside.proto +++ /dev/null @@ -1,148 +0,0 @@ -// Copyright (c) 2019-2020 The Zcash developers -// Distributed under the MIT software license, see the accompanying -// file COPYING or https://www.opensource.org/licenses/mit-license.php . - -syntax = "proto3"; -package cash.z.wallet.sdk.rpc; -option go_package = "lightwalletd/walletrpc"; -option swift_prefix = ""; -import "service.proto"; - -message DarksideMetaState { - int32 saplingActivation = 1; - string branchID = 2; - string chainName = 3; - uint32 startSaplingCommitmentTreeSize = 4; - uint32 startOrchardCommitmentTreeSize = 5; -} - -// A block is a hex-encoded string. -message DarksideBlock { - string block = 1; -} - -// DarksideBlocksURL is typically something like: -// https://raw.githubusercontent.com/zcash-hackworks/darksidewalletd-test-data/master/basic-reorg/before-reorg.txt -message DarksideBlocksURL { - string url = 1; -} - -// DarksideTransactionsURL refers to an HTTP source that contains a list -// of hex-encoded transactions, one per line, that are to be associated -// with the given height (fake-mined into the block at that height) -message DarksideTransactionsURL { - int32 height = 1; - string url = 2; -} - -message DarksideHeight { - int32 height = 1; -} - -message DarksideEmptyBlocks { - int32 height = 1; - int32 nonce = 2; - int32 count = 3; -} - -message DarksideSubtreeRoots { - ShieldedProtocol shieldedProtocol = 1; - uint32 startIndex = 2; - repeated SubtreeRoot subtreeRoots = 3; -} - -// Darksidewalletd maintains two staging areas, blocks and transactions. The -// Stage*() gRPCs add items to the staging area; ApplyStaged() "applies" everything -// in the staging area to the working (operational) state that the mock zcashd -// serves; transactions are placed into their corresponding blocks (by height). -service DarksideStreamer { - // Reset reverts all darksidewalletd state (active block range, latest height, - // staged blocks and transactions) and lightwalletd state (cache) to empty, - // the same as the initial state. This occurs synchronously and instantaneously; - // no reorg happens in lightwalletd. This is good to do before each independent - // test so that no state leaks from one test to another. - // Also sets (some of) the values returned by GetLightdInfo(). The Sapling - // activation height specified here must be where the block range starts. - rpc Reset(DarksideMetaState) returns (Empty) {} - - // StageBlocksStream accepts a list of blocks and saves them into the blocks - // staging area until ApplyStaged() is called; there is no immediate effect on - // the mock zcashd. Blocks are hex-encoded. Order is important, see ApplyStaged. - rpc StageBlocksStream(stream DarksideBlock) returns (Empty) {} - - // StageBlocks is the same as StageBlocksStream() except the blocks are fetched - // from the given URL. Blocks are one per line, hex-encoded (not JSON). - rpc StageBlocks(DarksideBlocksURL) returns (Empty) {} - - // StageBlocksCreate is like the previous two, except it creates 'count' - // empty blocks at consecutive heights starting at height 'height'. The - // 'nonce' is part of the header, so it contributes to the block hash; this - // lets you create identical blocks (same transactions and height), but with - // different hashes. - rpc StageBlocksCreate(DarksideEmptyBlocks) returns (Empty) {} - - // StageTransactionsStream stores the given transaction-height pairs in the - // staging area until ApplyStaged() is called. Note that these transactions - // are not returned by the production GetTransaction() gRPC until they - // appear in a "mined" block (contained in the active blockchain presented - // by the mock zcashd). - rpc StageTransactionsStream(stream RawTransaction) returns (Empty) {} - - // StageTransactions is the same except the transactions are fetched from - // the given url. They are all staged into the block at the given height. - // Staging transactions to different heights requires multiple calls. - rpc StageTransactions(DarksideTransactionsURL) returns (Empty) {} - - // ApplyStaged iterates the list of blocks that were staged by the - // StageBlocks*() gRPCs, in the order they were staged, and "merges" each - // into the active, working blocks list that the mock zcashd is presenting - // to lightwalletd. Even as each block is applied, the active list can't - // have gaps; if the active block range is 1000-1006, and the staged block - // range is 1003-1004, the resulting range is 1000-1004, with 1000-1002 - // unchanged, blocks 1003-1004 from the new range, and 1005-1006 dropped. - // - // After merging all blocks, ApplyStaged() appends staged transactions (in - // the order received) into each one's corresponding (by height) block - // The staging area is then cleared. - // - // The argument specifies the latest block height that mock zcashd reports - // (i.e. what's returned by GetLatestBlock). Note that ApplyStaged() can - // also be used to simply advance the latest block height presented by mock - // zcashd. That is, there doesn't need to be anything in the staging area. - rpc ApplyStaged(DarksideHeight) returns (Empty) {} - - // Calls to the production gRPC SendTransaction() store the transaction in - // a separate area (not the staging area); this method returns all transactions - // in this separate area, which is then cleared. The height returned - // with each transaction is -1 (invalid) since these transactions haven't - // been mined yet. The intention is that the transactions returned here can - // then, for example, be given to StageTransactions() to get them "mined" - // into a specified block on the next ApplyStaged(). - rpc GetIncomingTransactions(Empty) returns (stream RawTransaction) {} - - // Clear the incoming transaction pool. - rpc ClearIncomingTransactions(Empty) returns (Empty) {} - - // Add a GetAddressUtxosReply entry to be returned by GetAddressUtxos(). - // There is no staging or applying for these, very simple. - rpc AddAddressUtxo(GetAddressUtxosReply) returns (Empty) {} - - // Clear the list of GetAddressUtxos entries (can't fail) - rpc ClearAddressUtxo(Empty) returns (Empty) {} - - // Adds a GetTreeState to the tree state cache - rpc AddTreeState(TreeState) returns (Empty) {} - - // Removes a GetTreeState for the given height from cache if present (can't fail) - rpc RemoveTreeState(BlockID) returns (Empty) {} - - // Clear the list of GetTreeStates entries (can't fail) - rpc ClearAllTreeStates(Empty) returns (Empty) {} - - // Sets the subtree roots cache (for GetSubtreeRoots), - // replacing any existing entries - rpc SetSubtreeRoots(DarksideSubtreeRoots) returns (Empty) {} - - // Stop causes the server to shut down cleanly. - rpc Stop(Empty) returns (Empty) {} -} diff --git a/results/.gitkeep b/results/.gitkeep new file mode 100644 index 0000000..e69de29 diff --git a/results/README.md b/results/README.md new file mode 100644 index 0000000..a02567a --- /dev/null +++ b/results/README.md @@ -0,0 +1,24 @@ +# Results Directory + +This directory contains analysis outputs. Each run creates a timestamped subdirectory: + +``` +results/ +├── 20250108_143022/ +│ ├── recommended.csv # Raw data +│ ├── charts/ # Generated visualizations +│ │ ├── distribution.png +│ │ ├── time_series.png +│ │ ├── by_era.png +│ │ ├── correlations.png +│ │ ├── cumulative.png +│ │ ├── bandwidth_impact.png +│ │ ├── heatmap.png +│ │ └── statistical_report.txt +│ └── ... +└── 20250108_150314/ + └── ... +``` + +Results are gitignored to avoid bloating the repository. +To save results permanently, copy them elsewhere or commit specific files. diff --git a/scripts/fetch_protos.sh b/scripts/fetch_protos.sh new file mode 100755 index 0000000..655d05b --- /dev/null +++ b/scripts/fetch_protos.sh @@ -0,0 +1,23 @@ +#!/bin/bash +set -e + +PROTO_DIR="analyzer/proto" +mkdir -p "$PROTO_DIR" + +echo "📥 Fetching protocol buffers from lightwallet-protocol (main branch)..." + +# Clone main branch +TEMP_DIR=$(mktemp -d) +git clone https://github.com/zcash/lightwallet-protocol.git "$TEMP_DIR" + +echo "On branch: $(git -C "$TEMP_DIR" branch --show-current)" + +# Copy proto files from walletrpc directory (using absolute paths) +cp "$TEMP_DIR/walletrpc/compact_formats.proto" "$PROTO_DIR/" +cp "$TEMP_DIR/walletrpc/service.proto" "$PROTO_DIR/" + +# Cleanup +rm -rf "$TEMP_DIR" + +echo "✅ Proto files updated in $PROTO_DIR (main branch)" +ls -la "$PROTO_DIR" diff --git a/scripts/run_all_analyses.sh b/scripts/run_all_analyses.sh new file mode 100755 index 0000000..8382b48 --- /dev/null +++ b/scripts/run_all_analyses.sh @@ -0,0 +1,34 @@ +#!/bin/bash +set -e + +ANALYZER="./analyzer/target/release/compact-block-analyzer" +LIGHTWALLETD=${1:-"http://127.0.0.1:9067"} +ZEBRAD=${2:-"http://127.0.0.1:8232"} +OUTPUT_DIR="results/$(date +%Y%m%d_%H%M%S)" + +mkdir -p "$OUTPUT_DIR" + +echo "🔬 Running comprehensive analysis suite..." +echo "📁 Output directory: $OUTPUT_DIR" +echo "" + +# Quick analysis +echo "⚡ Running quick analysis..." +$ANALYZER "$LIGHTWALLETD" "$ZEBRAD" quick "$OUTPUT_DIR/quick.csv" + +# Recommended analysis +echo "📊 Running recommended analysis..." +$ANALYZER "$LIGHTWALLETD" "$ZEBRAD" recommended "$OUTPUT_DIR/recommended.csv" + +# Generate visualizations +echo "📈 Generating visualizations..." +cd visualization +source venv/bin/activate +python visualize.py "../$OUTPUT_DIR/recommended.csv" -o "../$OUTPUT_DIR/charts" +cd .. + +echo "" +echo "✅ Analysis complete!" +echo "📊 Results in: $OUTPUT_DIR" +echo "📈 Charts in: $OUTPUT_DIR/charts" +echo "📄 Report: $OUTPUT_DIR/charts/statistical_report.txt" diff --git a/scripts/setup.sh b/scripts/setup.sh new file mode 100755 index 0000000..98389fd --- /dev/null +++ b/scripts/setup.sh @@ -0,0 +1,26 @@ +#!/bin/bash +set -e + +echo "Setting up Compact Block Analyzer..." + +# Check prerequisites +command -v rustc >/dev/null 2>&1 || { echo "Rust not installed"; exit 1; } +command -v python3 >/dev/null 2>&1 || { echo "Python3 not installed"; exit 1; } + +# Fetch proto files +./scripts/fetch_protos.sh + +# Build Rust analyzer +cd analyzer +cargo build --release +cd .. + +# Setup Python environment +cd visualization +python3 -m venv venv +source venv/bin/activate +pip install -r requirements.txt +cd .. + +echo "✅ Setup complete!" +echo "Run: cd analyzer && cargo run --release -- --help" diff --git a/visualization/README.md b/visualization/README.md new file mode 100644 index 0000000..d981123 --- /dev/null +++ b/visualization/README.md @@ -0,0 +1,23 @@ +# Visualization Tools + +## Setup + +```bash +cd visualization +python3 -m venv venv +source venv/bin/activate # On Windows: venv\Scripts\activate +pip install -r requirements.txt +``` + +## Usage + +```bash +python visualize.py ../results/analysis.csv --output-dir ./charts +``` + +## Output + +Generates: +- Statistical charts (PNG files) +- Statistical report (TXT file) +- Decision recommendations diff --git a/visualization/charts/bandwidth_impact.png b/visualization/charts/bandwidth_impact.png new file mode 100644 index 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Strongly consider: + - Separate method required + - Clear opt-in for clients needing transparent data + - Critical for mobile and bandwidth-limited users + - May significantly impact sync times + +================================================================================ +End of Report +================================================================================ diff --git a/visualization/charts/time_series.png b/visualization/charts/time_series.png new file mode 100644 index 0000000000000000000000000000000000000000..c1453486a3f214e446a25a3ee7404539c726df20 GIT binary patch literal 415543 zcmeFZbySsGv^I`?1eId|f`mb*Qc9YLbayG;-7OwOKtM{AM!KaNL_}JoV-wO1(hc8S zdi3bM=iYCO`^WDa<2UXe;~bE^_Zw@iIp;H<=UK0(xG4WgY$9wdEUc3P5AI1~Vf`tD zg@yC-kE8GxPO>pt^uv-*-crg$+tTKdxfYhlBTG|56H7xq^^4Y8<`#M;#w?82t}?RI zU(~g|%*+p5eceH#e zN3z7@{*a8bxpSQ2&j(kmB*)kJ$*(q&zkVGgP&=_}KNeinTs9G|6TqcI8OYJhCQpy= z4Oj86FWTd=C1?Nj9r&Z^(dsk*#e28n?_?eRFWwVR7N>{%``4E=?Kv3ae}4sI|L^Jk 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file mode 100644 index 0000000..006d921 --- /dev/null +++ b/visualization/visualize.py @@ -0,0 +1,606 @@ +#!/usr/bin/env python3 +""" +Visualization and statistical analysis for Zcash compact block overhead data. + +Usage: + python visualize.py results.csv [--output-dir ./charts] +""" + +import pandas as pd +import matplotlib.pyplot as plt +import seaborn as sns +import numpy as np +from scipy import stats +import argparse +from pathlib import Path + +# Set style +sns.set_style("whitegrid") +plt.rcParams['figure.figsize'] = (12, 6) +plt.rcParams['font.size'] = 10 + +class CompactBlockAnalyzer: + def __init__(self, csv_path): + self.df = pd.read_csv(csv_path) + self.df['delta_mb'] = self.df['delta_bytes'] / 1_000_000 + self.df['current_mb'] = self.df['current_compact_size'] / 1_000_000 + self.df['estimated_mb'] = self.df['estimated_with_transparent'] / 1_000_000 + + def generate_all_charts(self, output_dir='./charts'): + """Generate all visualization charts""" + output_path = Path(output_dir) + output_path.mkdir(exist_ok=True) + + print("Generating visualizations...") + + self.plot_distribution(output_path / 'distribution.png') + self.plot_time_series(output_path / 'time_series.png') + self.plot_by_era(output_path / 'by_era.png') + self.plot_correlations(output_path / 'correlations.png') + self.plot_cumulative(output_path / 'cumulative.png') + self.plot_bandwidth_impact(output_path / 'bandwidth_impact.png') + self.plot_heatmap(output_path / 'heatmap.png') + + # Generate statistical report + self.generate_report(output_path / 'statistical_report.txt') + + print(f"\nAll visualizations saved to: {output_path}") + + def plot_distribution(self, filename): + """Histogram of overhead percentage distribution""" + fig, axes = plt.subplots(1, 2, figsize=(14, 5)) + + # Histogram with KDE + axes[0].hist(self.df['delta_percent'], bins=50, alpha=0.7, + edgecolor='black', density=True, label='Distribution') + + # Add KDE + kde_x = np.linspace(self.df['delta_percent'].min(), + self.df['delta_percent'].max(), 100) + kde = stats.gaussian_kde(self.df['delta_percent']) + axes[0].plot(kde_x, kde(kde_x), 'r-', linewidth=2, label='KDE') + + # Add median and mean + median = self.df['delta_percent'].median() + mean = self.df['delta_percent'].mean() + axes[0].axvline(median, color='green', linestyle='--', + linewidth=2, label=f'Median: {median:.1f}%') + axes[0].axvline(mean, color='orange', linestyle='--', + linewidth=2, label=f'Mean: {mean:.1f}%') + + axes[0].set_xlabel('Overhead Percentage (%)') + axes[0].set_ylabel('Density') + axes[0].set_title('Distribution of Compact Block Overhead') + axes[0].legend() + axes[0].grid(True, alpha=0.3) + + # Box plot + axes[1].boxplot(self.df['delta_percent'], vert=True) + axes[1].set_ylabel('Overhead Percentage (%)') + axes[1].set_title('Overhead Distribution (Box Plot)') + axes[1].grid(True, alpha=0.3) + + plt.tight_layout() + plt.savefig(filename, dpi=300, bbox_inches='tight') + plt.close() + print(f" ✓ Distribution chart saved: {filename}") + + def plot_time_series(self, filename): + """Overhead over blockchain height""" + fig, axes = plt.subplots(2, 1, figsize=(14, 10)) + + # Scatter plot with trend + axes[0].scatter(self.df['height'], self.df['delta_percent'], + alpha=0.4, s=10, c=self.df['delta_percent'], + cmap='YlOrRd') + + # Add rolling mean + window = max(len(self.df) // 50, 10) + rolling_mean = self.df.set_index('height')['delta_percent'].rolling(window).mean() + axes[0].plot(rolling_mean.index, rolling_mean.values, + 'b-', linewidth=2, label=f'Rolling Mean (window={window})') + + # Add era boundaries + eras = [ + (419_200, 'Sapling', 'red'), + (653_600, 'Blossom', 'blue'), + (903_800, 'Heartwood', 'purple'), + (1_046_400, 'Canopy', 'orange'), + (1_687_104, 'NU5', 'green'), + (2_726_400, 'NU6', 'brown'), + ] + + for height, name, color in eras: + if height >= self.df['height'].min() and height <= self.df['height'].max(): + axes[0].axvline(height, color=color, alpha=0.3, + linestyle='--', linewidth=1.5) + axes[0].text(height, axes[0].get_ylim()[1] * 0.95, name, + rotation=90, verticalalignment='top', color=color) + + axes[0].set_xlabel('Block Height') + axes[0].set_ylabel('Overhead (%)') + axes[0].set_title('Compact Block Overhead Over Time') + axes[0].legend() + axes[0].grid(True, alpha=0.3) + + # Absolute size over time + axes[1].scatter(self.df['height'], self.df['delta_mb'], + alpha=0.4, s=10, c=self.df['delta_mb'], + cmap='YlOrRd') + + rolling_delta = self.df.set_index('height')['delta_mb'].rolling(window).mean() + axes[1].plot(rolling_delta.index, rolling_delta.values, + 'b-', linewidth=2, label=f'Rolling Mean') + + for height, name, color in eras: + if height >= self.df['height'].min() and height <= self.df['height'].max(): + axes[1].axvline(height, color=color, alpha=0.3, + linestyle='--', linewidth=1.5) + + axes[1].set_xlabel('Block Height') + axes[1].set_ylabel('Delta Size (MB)') + axes[1].set_title('Absolute Size Increase Over Time') + axes[1].legend() + axes[1].grid(True, alpha=0.3) + + plt.tight_layout() + plt.savefig(filename, dpi=300, bbox_inches='tight') + plt.close() + print(f" ✓ Time series chart saved: {filename}") + + def plot_by_era(self, filename): + """Compare distributions across eras""" + fig, axes = plt.subplots(2, 2, figsize=(14, 10)) + + # Box plot by era + era_order = ['sapling', 'blossom', 'heartwood', 'canopy', 'nu5', 'nu6'] + available_eras = [e for e in era_order if e in self.df['era'].values] + + box_data = [self.df[self.df['era'] == era]['delta_percent'].values + for era in available_eras] + + colors = ['lightgreen', 'lightyellow', 'lightpink', 'lightcoral', 'lavender', 'peachpuff'] + bp = axes[0, 0].boxplot(box_data, labels=available_eras, patch_artist=True) + for patch, color in zip(bp['boxes'], colors[:len(available_eras)]): + patch.set_facecolor(color) + + axes[0, 0].set_ylabel('Overhead (%)') + axes[0, 0].set_title('Overhead Distribution by Era') + axes[0, 0].grid(True, alpha=0.3) + axes[0, 0].tick_params(axis='x', rotation=45) + + # Violin plot + if len(available_eras) > 0: + era_df = self.df[self.df['era'].isin(available_eras)] + sns.violinplot(data=era_df, x='era', y='delta_percent', + order=available_eras, ax=axes[0, 1]) + axes[0, 1].set_ylabel('Overhead (%)') + axes[0, 1].set_title('Overhead Distribution by Era (Violin Plot)') + axes[0, 1].grid(True, alpha=0.3) + axes[0, 1].tick_params(axis='x', rotation=45) + + # Bar chart of means + era_stats = self.df.groupby('era')['delta_percent'].agg(['mean', 'std']) + era_stats = era_stats.reindex(available_eras) + + x = np.arange(len(available_eras)) + axes[1, 0].bar(x, era_stats['mean'], yerr=era_stats['std'], + capsize=5, alpha=0.7, color=colors[:len(available_eras)]) + axes[1, 0].set_xticks(x) + axes[1, 0].set_xticklabels(available_eras, rotation=45) + axes[1, 0].set_ylabel('Mean Overhead (%)') + axes[1, 0].set_title('Average Overhead by Era (with Std Dev)') + axes[1, 0].grid(True, alpha=0.3) + + # Sample sizes + era_counts = self.df['era'].value_counts().reindex(available_eras) + axes[1, 1].bar(available_eras, era_counts.values, + color=colors[:len(available_eras)]) + axes[1, 1].set_ylabel('Number of Samples') + axes[1, 1].set_title('Sample Distribution by Era') + axes[1, 1].tick_params(axis='x', rotation=45) + axes[1, 1].grid(True, alpha=0.3) + + plt.tight_layout() + plt.savefig(filename, dpi=300, bbox_inches='tight') + plt.close() + print(f" ✓ Era comparison chart saved: {filename}") + + def plot_correlations(self, filename): + """Correlation between overhead and transaction characteristics""" + fig, axes = plt.subplots(2, 2, figsize=(14, 10)) + + # Overhead vs transparent inputs + axes[0, 0].scatter(self.df['transparent_inputs'], self.df['delta_bytes'], + alpha=0.5, s=20) + z = np.polyfit(self.df['transparent_inputs'], self.df['delta_bytes'], 1) + p = np.poly1d(z) + axes[0, 0].plot(self.df['transparent_inputs'], + p(self.df['transparent_inputs']), + "r--", linewidth=2, label=f'Trend') + + corr = self.df['transparent_inputs'].corr(self.df['delta_bytes']) + axes[0, 0].set_xlabel('Transparent Inputs') + axes[0, 0].set_ylabel('Delta (bytes)') + axes[0, 0].set_title(f'Overhead vs Transparent Inputs (r={corr:.3f})') + axes[0, 0].legend() + axes[0, 0].grid(True, alpha=0.3) + + # Overhead vs transparent outputs + axes[0, 1].scatter(self.df['transparent_outputs'], self.df['delta_bytes'], + alpha=0.5, s=20, color='orange') + z = np.polyfit(self.df['transparent_outputs'], self.df['delta_bytes'], 1) + p = np.poly1d(z) + axes[0, 1].plot(self.df['transparent_outputs'], + p(self.df['transparent_outputs']), + "r--", linewidth=2, label='Trend') + + corr = self.df['transparent_outputs'].corr(self.df['delta_bytes']) + axes[0, 1].set_xlabel('Transparent Outputs') + axes[0, 1].set_ylabel('Delta (bytes)') + axes[0, 1].set_title(f'Overhead vs Transparent Outputs (r={corr:.3f})') + axes[0, 1].legend() + axes[0, 1].grid(True, alpha=0.3) + + # Overhead vs total transactions + axes[1, 0].scatter(self.df['tx_count'], self.df['delta_percent'], + alpha=0.5, s=20, color='green') + + corr = self.df['tx_count'].corr(self.df['delta_percent']) + axes[1, 0].set_xlabel('Transaction Count') + axes[1, 0].set_ylabel('Overhead (%)') + axes[1, 0].set_title(f'Overhead % vs Transaction Count (r={corr:.3f})') + axes[1, 0].grid(True, alpha=0.3) + + # Current size vs overhead + axes[1, 1].scatter(self.df['current_compact_size'], + self.df['delta_percent'], + alpha=0.5, s=20, color='purple') + + corr = self.df['current_compact_size'].corr(self.df['delta_percent']) + axes[1, 1].set_xlabel('Current Compact Block Size (bytes)') + axes[1, 1].set_ylabel('Overhead (%)') + axes[1, 1].set_title(f'Overhead % vs Block Size (r={corr:.3f})') + axes[1, 1].grid(True, alpha=0.3) + + plt.tight_layout() + plt.savefig(filename, dpi=300, bbox_inches='tight') + plt.close() + print(f" ✓ Correlation chart saved: {filename}") + + def plot_cumulative(self, filename): + """Cumulative distribution function""" + fig, axes = plt.subplots(1, 2, figsize=(14, 5)) + + # CDF of overhead percentage + sorted_overhead = np.sort(self.df['delta_percent']) + cumulative = np.arange(1, len(sorted_overhead) + 1) / len(sorted_overhead) + + axes[0].plot(sorted_overhead, cumulative * 100, linewidth=2) + + # Mark percentiles + percentiles = [50, 75, 90, 95, 99] + for p in percentiles: + value = np.percentile(sorted_overhead, p) + axes[0].axvline(value, linestyle='--', alpha=0.5, + label=f'P{p}: {value:.1f}%') + axes[0].axhline(p, linestyle=':', alpha=0.3) + + axes[0].set_xlabel('Overhead (%)') + axes[0].set_ylabel('Cumulative Percentage of Blocks') + axes[0].set_title('Cumulative Distribution of Overhead') + axes[0].legend() + axes[0].grid(True, alpha=0.3) + + # CDF of absolute delta + sorted_delta = np.sort(self.df['delta_bytes']) + axes[1].plot(sorted_delta / 1000, cumulative * 100, linewidth=2, color='orange') + + for p in percentiles: + value = np.percentile(sorted_delta, p) / 1000 + axes[1].axvline(value, linestyle='--', alpha=0.5, + label=f'P{p}: {value:.1f}KB') + + axes[1].set_xlabel('Delta Size (KB)') + axes[1].set_ylabel('Cumulative Percentage of Blocks') + axes[1].set_title('Cumulative Distribution of Absolute Overhead') + axes[1].legend() + axes[1].grid(True, alpha=0.3) + + plt.tight_layout() + plt.savefig(filename, dpi=300, bbox_inches='tight') + plt.close() + print(f" ✓ Cumulative distribution chart saved: {filename}") + + def plot_bandwidth_impact(self, filename): + """Practical bandwidth impact scenarios""" + fig, axes = plt.subplots(2, 2, figsize=(14, 10)) + + # Calculate metrics + avg_current = self.df['current_compact_size'].mean() + avg_with_transparent = self.df['estimated_with_transparent'].mean() + avg_delta = avg_with_transparent - avg_current + + # Daily sync (assume 2880 blocks per day) + blocks_per_day = 2880 + daily_current_mb = (avg_current * blocks_per_day) / 1_000_000 + daily_with_mb = (avg_with_transparent * blocks_per_day) / 1_000_000 + + axes[0, 0].bar(['Current', 'With\nTransparent'], + [daily_current_mb, daily_with_mb], + color=['steelblue', 'coral']) + axes[0, 0].set_ylabel('MB') + axes[0, 0].set_title('Daily Sync Bandwidth\n(~2880 blocks)') + axes[0, 0].grid(True, alpha=0.3, axis='y') + + for i, v in enumerate([daily_current_mb, daily_with_mb]): + axes[0, 0].text(i, v + 1, f'{v:.1f} MB', + ha='center', va='bottom', fontweight='bold') + + # Full sync (assume 2.4M blocks) + total_blocks = len(self.df) * 500 # Estimate full chain + full_current_gb = (avg_current * total_blocks) / 1_000_000_000 + full_with_gb = (avg_with_transparent * total_blocks) / 1_000_000_000 + + axes[0, 1].bar(['Current', 'With\nTransparent'], + [full_current_gb, full_with_gb], + color=['steelblue', 'coral']) + axes[0, 1].set_ylabel('GB') + axes[0, 1].set_title(f'Full Chain Sync\n(~{total_blocks:,} blocks)') + axes[0, 1].grid(True, alpha=0.3, axis='y') + + for i, v in enumerate([full_current_gb, full_with_gb]): + axes[0, 1].text(i, v + 0.1, f'{v:.1f} GB', + ha='center', va='bottom', fontweight='bold') + + # Mobile data cost (assume $10/GB) + cost_per_gb = 10 + daily_cost_current = (daily_current_mb / 1000) * cost_per_gb + daily_cost_with = (daily_with_mb / 1000) * cost_per_gb + monthly_cost_current = daily_cost_current * 30 + monthly_cost_with = daily_cost_with * 30 + + x = np.arange(2) + width = 0.35 + axes[1, 0].bar(x - width/2, [daily_cost_current, monthly_cost_current], + width, label='Current', color='steelblue') + axes[1, 0].bar(x + width/2, [daily_cost_with, monthly_cost_with], + width, label='With Transparent', color='coral') + + axes[1, 0].set_ylabel('Cost (USD)') + axes[1, 0].set_title('Mobile Data Cost\n(@$10/GB)') + axes[1, 0].set_xticks(x) + axes[1, 0].set_xticklabels(['Daily', 'Monthly']) + axes[1, 0].legend() + axes[1, 0].grid(True, alpha=0.3, axis='y') + + # Sync time (assume 5 Mbps connection) + bandwidth_mbps = 5 + bandwidth_mb_per_sec = bandwidth_mbps / 8 + + daily_time_current = daily_current_mb / bandwidth_mb_per_sec / 60 # minutes + daily_time_with = daily_with_mb / bandwidth_mb_per_sec / 60 + full_time_current = full_current_gb * 1000 / bandwidth_mb_per_sec / 3600 # hours + full_time_with = full_with_gb * 1000 / bandwidth_mb_per_sec / 3600 + + x = np.arange(2) + axes[1, 1].bar(x - width/2, [daily_time_current, full_time_current], + width, label='Current', color='steelblue') + axes[1, 1].bar(x + width/2, [daily_time_with, full_time_with], + width, label='With Transparent', color='coral') + + axes[1, 1].set_ylabel('Time') + axes[1, 1].set_title(f'Sync Time\n(@{bandwidth_mbps} Mbps)') + axes[1, 1].set_xticks(x) + axes[1, 1].set_xticklabels(['Daily\n(minutes)', 'Full\n(hours)']) + axes[1, 1].legend() + axes[1, 1].grid(True, alpha=0.3, axis='y') + + plt.tight_layout() + plt.savefig(filename, dpi=300, bbox_inches='tight') + plt.close() + print(f" ✓ Bandwidth impact chart saved: {filename}") + + def plot_heatmap(self, filename): + """Heatmap of overhead by era and transaction characteristics""" + fig, axes = plt.subplots(1, 2, figsize=(14, 5)) + + # Create bins for transaction count + self.df['tx_bin'] = pd.cut(self.df['tx_count'], + bins=[0, 10, 50, 100, 500, 10000], + labels=['1-10', '11-50', '51-100', '101-500', '500+']) + + # Pivot table: era vs tx_bin + if 'era' in self.df.columns and not self.df['era'].isna().all(): + pivot = self.df.pivot_table( + values='delta_percent', + index='era', + columns='tx_bin', + aggfunc='mean' + ) + + sns.heatmap(pivot, annot=True, fmt='.1f', cmap='YlOrRd', + ax=axes[0], cbar_kws={'label': 'Overhead (%)'}) + axes[0].set_title('Average Overhead by Era and Transaction Count') + axes[0].set_ylabel('Era') + axes[0].set_xlabel('Transactions per Block') + + # Pivot table: transparent usage + self.df['transparent_bin'] = pd.cut( + self.df['transparent_inputs'] + self.df['transparent_outputs'], + bins=[0, 10, 50, 100, 500, 10000], + labels=['1-10', '11-50', '51-100', '101-500', '500+'] + ) + + if 'era' in self.df.columns and not self.df['era'].isna().all(): + pivot2 = self.df.pivot_table( + values='delta_percent', + index='era', + columns='transparent_bin', + aggfunc='mean' + ) + + sns.heatmap(pivot2, annot=True, fmt='.1f', cmap='YlOrRd', + ax=axes[1], cbar_kws={'label': 'Overhead (%)'}) + axes[1].set_title('Average Overhead by Era and Transparent I/O') + axes[1].set_ylabel('Era') + axes[1].set_xlabel('Transparent Inputs + Outputs') + + plt.tight_layout() + plt.savefig(filename, dpi=300, bbox_inches='tight') + plt.close() + print(f" ✓ Heatmap saved: {filename}") + + def generate_report(self, filename): + """Generate statistical report""" + with open(filename, 'w') as f: + f.write("=" * 80 + "\n") + f.write("STATISTICAL ANALYSIS REPORT\n") + f.write("Zcash Compact Block Transparent Data Overhead\n") + f.write("=" * 80 + "\n\n") + + # Summary statistics + f.write("SUMMARY STATISTICS\n") + f.write("-" * 80 + "\n") + f.write(f"Total blocks analyzed: {len(self.df):,}\n") + f.write(f"Block height range: {self.df['height'].min():,} - {self.df['height'].max():,}\n\n") + + # Overhead statistics + f.write("OVERHEAD PERCENTAGE\n") + f.write(f" Mean: {self.df['delta_percent'].mean():>8.2f}%\n") + f.write(f" Median: {self.df['delta_percent'].median():>8.2f}%\n") + f.write(f" Std Dev:{self.df['delta_percent'].std():>8.2f}%\n") + f.write(f" Min: {self.df['delta_percent'].min():>8.2f}%\n") + f.write(f" Max: {self.df['delta_percent'].max():>8.2f}%\n\n") + + # Percentiles + f.write("PERCENTILES\n") + for p in [25, 50, 75, 90, 95, 99]: + value = np.percentile(self.df['delta_percent'], p) + f.write(f" P{p:>2}: {value:>8.2f}%\n") + f.write("\n") + + # Confidence intervals + f.write("CONFIDENCE INTERVALS (95%)\n") + mean = self.df['delta_percent'].mean() + std_err = stats.sem(self.df['delta_percent']) + ci = stats.t.interval(0.95, len(self.df)-1, loc=mean, scale=std_err) + f.write(f" Mean overhead: {mean:.2f}% ± {(ci[1]-mean):.2f}%\n") + f.write(f" Range: [{ci[0]:.2f}%, {ci[1]:.2f}%]\n\n") + + # By era + f.write("STATISTICS BY ERA\n") + f.write("-" * 80 + "\n") + if 'era' in self.df.columns: + era_stats = self.df.groupby('era').agg({ + 'delta_percent': ['count', 'mean', 'std', 'median', 'min', 'max'] + }) + f.write(era_stats.to_string()) + f.write("\n\n") + + # Bandwidth impact + f.write("PRACTICAL BANDWIDTH IMPACT\n") + f.write("-" * 80 + "\n") + + avg_current = self.df['current_compact_size'].mean() + avg_with = self.df['estimated_with_transparent'].mean() + avg_delta = avg_with - avg_current + + blocks_per_day = 2880 + daily_current_mb = (avg_current * blocks_per_day) / 1_000_000 + daily_with_mb = (avg_with * blocks_per_day) / 1_000_000 + daily_delta_mb = daily_with_mb - daily_current_mb + + f.write(f"Average block sizes:\n") + f.write(f" Current: {avg_current/1000:>10.2f} KB\n") + f.write(f" With transparent:{avg_with/1000:>10.2f} KB\n") + f.write(f" Delta: {avg_delta/1000:>10.2f} KB\n\n") + + f.write(f"Daily sync (~{blocks_per_day} blocks):\n") + f.write(f" Current: {daily_current_mb:>10.2f} MB\n") + f.write(f" With transparent:{daily_with_mb:>10.2f} MB\n") + f.write(f" Additional: {daily_delta_mb:>10.2f} MB ({(daily_delta_mb/daily_current_mb)*100:.1f}%)\n\n") + + # Correlations + f.write("CORRELATIONS\n") + f.write("-" * 80 + "\n") + corr_inputs = self.df['transparent_inputs'].corr(self.df['delta_bytes']) + corr_outputs = self.df['transparent_outputs'].corr(self.df['delta_bytes']) + corr_tx = self.df['tx_count'].corr(self.df['delta_percent']) + + f.write(f" Transparent inputs vs delta: r = {corr_inputs:>6.3f}\n") + f.write(f" Transparent outputs vs delta: r = {corr_outputs:>6.3f}\n") + f.write(f" Transaction count vs %%: r = {corr_tx:>6.3f}\n\n") + + # Recommendations + f.write("DECISION FRAMEWORK\n") + f.write("-" * 80 + "\n") + median_overhead = self.df['delta_percent'].median() + p95_overhead = np.percentile(self.df['delta_percent'], 95) + + f.write(f"Median overhead: {median_overhead:.1f}%\n") + f.write(f"95th percentile: {p95_overhead:.1f}%\n\n") + + if median_overhead < 20: + f.write("RECOMMENDATION: LOW IMPACT\n") + f.write(" The overhead is relatively small (<20%). Consider making transparent\n") + f.write(" data part of the default GetBlockRange method. This would:\n") + f.write(" - Simplify the API (single method)\n") + f.write(" - Provide feature parity with full nodes\n") + f.write(" - Have minimal bandwidth impact on users\n") + elif median_overhead < 50: + f.write("RECOMMENDATION: MODERATE IMPACT\n") + f.write(" The overhead is significant (20-50%). Consider:\n") + f.write(" - Separate opt-in method for transparent data\n") + f.write(" - Pool-based filtering (as in librustzcash PR #1781)\n") + f.write(" - Let clients choose based on their needs\n") + f.write(" - Important for mobile/bandwidth-limited users\n") + else: + f.write("RECOMMENDATION: HIGH IMPACT\n") + f.write(" The overhead is substantial (>50%). Strongly consider:\n") + f.write(" - Separate method required\n") + f.write(" - Clear opt-in for clients needing transparent data\n") + f.write(" - Critical for mobile and bandwidth-limited users\n") + f.write(" - May significantly impact sync times\n") + + f.write("\n") + f.write("=" * 80 + "\n") + f.write("End of Report\n") + f.write("=" * 80 + "\n") + + print(f" ✓ Statistical report saved: {filename}") + + +def main(): + parser = argparse.ArgumentParser( + description='Generate visualizations and statistical analysis for compact block data' + ) + parser.add_argument('csv_file', help='Path to CSV file with analysis results') + parser.add_argument('--output-dir', '-o', default='./charts', + help='Output directory for charts (default: ./charts)') + + args = parser.parse_args() + + # Check if file exists + if not Path(args.csv_file).exists(): + print(f"Error: File not found: {args.csv_file}") + return 1 + + print(f"Loading data from: {args.csv_file}") + analyzer = CompactBlockAnalyzer(args.csv_file) + + print(f"Loaded {len(analyzer.df)} blocks") + print() + + # Generate all visualizations + analyzer.generate_all_charts(args.output_dir) + + print("\n✅ Analysis complete!") + print(f"\nView the statistical report: {args.output_dir}/statistical_report.txt") + print(f"View charts in: {args.output_dir}/") + + return 0 + + +if __name__ == '__main__': + exit(main()) From d0350b4519c1405c8aab4c9d39aad30ea973ae2e Mon Sep 17 00:00:00 2001 From: Pacu Date: Thu, 9 Oct 2025 16:25:01 -0300 Subject: [PATCH 03/17] Fix blocks per day visualization issues and percentage representations --- analyzer/quick_results.csv | 2001 ------------------- visualization/.python-version | 1 + visualization/charts/.gitignore | 9 + visualization/charts/.gitkeep | 0 visualization/charts/bandwidth_impact.png | Bin 247118 -> 0 bytes visualization/charts/by_era.png | Bin 331250 -> 0 bytes visualization/charts/correlations.png | Bin 413037 -> 0 bytes visualization/charts/cumulative.png | Bin 214605 -> 0 bytes visualization/charts/distribution.png | Bin 203063 -> 0 bytes visualization/charts/heatmap.png | Bin 307824 -> 0 bytes visualization/charts/statistical_report.txt | 74 - visualization/charts/time_series.png | Bin 415543 -> 0 bytes visualization/visualize.py | 229 ++- 13 files changed, 175 insertions(+), 2139 deletions(-) delete mode 100644 analyzer/quick_results.csv create mode 100644 visualization/.python-version create mode 100644 visualization/charts/.gitignore create mode 100644 visualization/charts/.gitkeep delete mode 100644 visualization/charts/bandwidth_impact.png delete mode 100644 visualization/charts/by_era.png delete mode 100644 visualization/charts/correlations.png delete mode 100644 visualization/charts/cumulative.png delete mode 100644 visualization/charts/distribution.png delete mode 100644 visualization/charts/heatmap.png delete mode 100644 visualization/charts/statistical_report.txt delete mode 100644 visualization/charts/time_series.png diff --git a/analyzer/quick_results.csv b/analyzer/quick_results.csv deleted file mode 100644 index 5da372d..0000000 --- a/analyzer/quick_results.csv +++ /dev/null @@ -1,2001 +0,0 @@ -height,era,current_compact_size,estimated_with_transparent,delta_bytes,delta_percent,tx_count,transparent_inputs,transparent_outputs -419962,sapling,83,229,146,175.9036144578313,1,1,2 -420300,sapling,83,1401,1318,1587.9518072289156,2,1,37 -422151,sapling,83,920,837,1008.433734939759,7,8,14 -423983,sapling,83,5450,5367,6466.265060240964,12,116,18 -425817,sapling,83,20419,20336,24501.20481927711,27,270,280 -427249,sapling,83,10380,10297,12406.024096385541,6,77,214 -427552,sapling,83,1200,1117,1345.7831325301206,10,10,20 -428734,sapling,83,336,253,304.81927710843377,2,2,4 -430984,sapling,83,337,254,306.0240963855422,2,2,4 -432911,sapling,83,338,255,307.2289156626506,2,2,4 -433109,sapling,246,23584,23338,9486.9918699187,16,517,66 -434842,sapling,83,9702,9619,11589.156626506023,11,64,211 -437840,sapling,83,1077,994,1197.5903614457832,6,12,14 -439782,sapling,83,454,371,446.98795180722885,3,4,5 -440999,sapling,83,337,254,306.0240963855422,2,2,4 -441931,sapling,83,229,146,175.9036144578313,1,1,2 -443732,sapling,83,374,291,350.6024096385542,2,2,5 -445181,sapling,83,3329,3246,3910.843373493976,6,71,10 -445600,sapling,246,7227,6981,2837.8048780487807,6,165,6 -446646,sapling,83,229,146,175.9036144578313,1,1,2 -449971,sapling,83,654,571,687.9518072289156,3,9,5 -450136,sapling,608,2321,1713,281.7434210526316,12,27,17 -450471,sapling,83,417,334,402.4096385542169,2,4,4 -450542,sapling,970,5086,4116,424.3298969072165,25,61,48 -451989,sapling,682,2058,1376,201.75953079178885,14,18,18 -452222,sapling,83,305,222,267.4698795180723,2,2,3 -452436,sapling,246,761,515,209.34959349593493,5,5,8 -452894,sapling,83,229,146,175.9036144578313,1,1,2 -453833,sapling,409,1891,1482,362.3471882640587,13,18,21 -454540,sapling,83,6426,6343,7642.168674698796,3,4,185 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ax=axes[0, 1]) axes[0, 1].set_ylabel('Overhead (%)') - axes[0, 1].set_title('Overhead Distribution by Era (Violin Plot)') + axes[0, 1].set_title('Overhead Distribution by Era (Violin - Percentage)') axes[0, 1].grid(True, alpha=0.3) axes[0, 1].tick_params(axis='x', rotation=45) - # Bar chart of means - era_stats = self.df.groupby('era')['delta_percent'].agg(['mean', 'std']) - era_stats = era_stats.reindex(available_eras) + # Bar chart of means - percentage + era_stats_pct = self.df.groupby('era')['delta_percent'].agg(['mean', 'std']) + era_stats_pct = era_stats_pct.reindex(available_eras) x = np.arange(len(available_eras)) - axes[1, 0].bar(x, era_stats['mean'], yerr=era_stats['std'], + axes[0, 2].bar(x, era_stats_pct['mean'], yerr=era_stats_pct['std'], capsize=5, alpha=0.7, color=colors[:len(available_eras)]) - axes[1, 0].set_xticks(x) - axes[1, 0].set_xticklabels(available_eras, rotation=45) - axes[1, 0].set_ylabel('Mean Overhead (%)') - axes[1, 0].set_title('Average Overhead by Era (with Std Dev)') + axes[0, 2].set_xticks(x) + axes[0, 2].set_xticklabels(available_eras, rotation=45) + axes[0, 2].set_ylabel('Mean Overhead (%)') + axes[0, 2].set_title('Average Overhead by Era (Percentage)') + axes[0, 2].grid(True, alpha=0.3) + + # Bottom row: Absolute KB overhead + # Box plot by era - KB + box_data_kb = [self.df[self.df['era'] == era]['delta_kb'].values + for era in available_eras] + + bp2 = axes[1, 0].boxplot(box_data_kb, labels=available_eras, patch_artist=True) + for patch, color in zip(bp2['boxes'], colors[:len(available_eras)]): + patch.set_facecolor(color) + + axes[1, 0].set_ylabel('Overhead (KB per block)') + axes[1, 0].set_title('Overhead Distribution by Era (Absolute)') axes[1, 0].grid(True, alpha=0.3) + axes[1, 0].tick_params(axis='x', rotation=45) - # Sample sizes - era_counts = self.df['era'].value_counts().reindex(available_eras) - axes[1, 1].bar(available_eras, era_counts.values, - color=colors[:len(available_eras)]) - axes[1, 1].set_ylabel('Number of Samples') - axes[1, 1].set_title('Sample Distribution by Era') - axes[1, 1].tick_params(axis='x', rotation=45) - axes[1, 1].grid(True, alpha=0.3) + # Violin plot - KB + if len(available_eras) > 0: + sns.violinplot(data=era_df, x='era', y='delta_kb', + order=available_eras, ax=axes[1, 1], color='coral') + axes[1, 1].set_ylabel('Overhead (KB per block)') + axes[1, 1].set_title('Overhead Distribution by Era (Violin - Absolute)') + axes[1, 1].grid(True, alpha=0.3) + axes[1, 1].tick_params(axis='x', rotation=45) + + # Bar chart of means - KB + era_stats_kb = self.df.groupby('era')['delta_kb'].agg(['mean', 'std']) + era_stats_kb = era_stats_kb.reindex(available_eras) + + axes[1, 2].bar(x, era_stats_kb['mean'], yerr=era_stats_kb['std'], + capsize=5, alpha=0.7, color=colors[:len(available_eras)]) + axes[1, 2].set_xticks(x) + axes[1, 2].set_xticklabels(available_eras, rotation=45) + axes[1, 2].set_ylabel('Mean Overhead (KB per block)') + axes[1, 2].set_title('Average Overhead by Era (Absolute)') + axes[1, 2].grid(True, alpha=0.3) plt.tight_layout() plt.savefig(filename, dpi=300, bbox_inches='tight') @@ -321,26 +386,39 @@ def plot_bandwidth_impact(self, filename): avg_with_transparent = self.df['estimated_with_transparent'].mean() avg_delta = avg_with_transparent - avg_current - # Daily sync (assume 2880 blocks per day) - blocks_per_day = 2880 + # Calculate blocks per day based on current network (post-Blossom) + # Post-Blossom (after block 653,600): 75s blocks = 1,152 blocks/day + # This is what matters for current light clients + blocks_per_day = 1152 + daily_current_mb = (avg_current * blocks_per_day) / 1_000_000 daily_with_mb = (avg_with_transparent * blocks_per_day) / 1_000_000 + daily_delta_mb = daily_with_mb - daily_current_mb + # Daily sync with absolute delta axes[0, 0].bar(['Current', 'With\nTransparent'], [daily_current_mb, daily_with_mb], color=['steelblue', 'coral']) axes[0, 0].set_ylabel('MB') - axes[0, 0].set_title('Daily Sync Bandwidth\n(~2880 blocks)') + axes[0, 0].set_title(f'Daily Sync Bandwidth\n(~{blocks_per_day} blocks/day)') axes[0, 0].grid(True, alpha=0.3, axis='y') for i, v in enumerate([daily_current_mb, daily_with_mb]): axes[0, 0].text(i, v + 1, f'{v:.1f} MB', ha='center', va='bottom', fontweight='bold') - # Full sync (assume 2.4M blocks) - total_blocks = len(self.df) * 500 # Estimate full chain + # Add delta annotation + axes[0, 0].text(0.5, max(daily_current_mb, daily_with_mb) * 0.5, + f'Δ = +{daily_delta_mb:.1f} MB\n({(daily_delta_mb/daily_current_mb)*100:.1f}%)', + ha='center', fontsize=12, fontweight='bold', + bbox=dict(boxstyle='round', facecolor='yellow', alpha=0.3)) + + # Full sync (estimate based on current tip) + max_height = self.df['height'].max() + total_blocks = max_height # Approximate total blocks full_current_gb = (avg_current * total_blocks) / 1_000_000_000 full_with_gb = (avg_with_transparent * total_blocks) / 1_000_000_000 + full_delta_gb = full_with_gb - full_current_gb axes[0, 1].bar(['Current', 'With\nTransparent'], [full_current_gb, full_with_gb], @@ -350,38 +428,52 @@ def plot_bandwidth_impact(self, filename): axes[0, 1].grid(True, alpha=0.3, axis='y') for i, v in enumerate([full_current_gb, full_with_gb]): - axes[0, 1].text(i, v + 0.1, f'{v:.1f} GB', + axes[0, 1].text(i, v + 0.1, f'{v:.2f} GB', ha='center', va='bottom', fontweight='bold') - # Mobile data cost (assume $10/GB) - cost_per_gb = 10 - daily_cost_current = (daily_current_mb / 1000) * cost_per_gb - daily_cost_with = (daily_with_mb / 1000) * cost_per_gb - monthly_cost_current = daily_cost_current * 30 - monthly_cost_with = daily_cost_with * 30 + # Add delta annotation + axes[0, 1].text(0.5, max(full_current_gb, full_with_gb) * 0.5, + f'Δ = +{full_delta_gb:.2f} GB\n({(full_delta_gb/full_current_gb)*100:.1f}%)', + ha='center', fontsize=12, fontweight='bold', + bbox=dict(boxstyle='round', facecolor='yellow', alpha=0.3)) - x = np.arange(2) + # Absolute delta chart - use MB consistently + x = np.arange(3) width = 0.35 - axes[1, 0].bar(x - width/2, [daily_cost_current, monthly_cost_current], - width, label='Current', color='steelblue') - axes[1, 0].bar(x + width/2, [daily_cost_with, monthly_cost_with], - width, label='With Transparent', color='coral') - axes[1, 0].set_ylabel('Cost (USD)') - axes[1, 0].set_title('Mobile Data Cost\n(@$10/GB)') + # Calculate for different time periods (all in MB) + daily_delta_mb = daily_delta_mb + weekly_delta_mb = daily_delta_mb * 7 + monthly_delta_mb = daily_delta_mb * 30 + + deltas = [daily_delta_mb, weekly_delta_mb, monthly_delta_mb] + labels = [f'Daily\n({blocks_per_day} blocks)', 'Weekly\n(7 days)', 'Monthly\n(30 days)'] + + bars = axes[1, 0].bar(x, deltas, color='coral', alpha=0.7) + axes[1, 0].set_ylabel('Additional Bandwidth (MB)') + axes[1, 0].set_title('Absolute Bandwidth Increase\n(Transparent Data Overhead)') axes[1, 0].set_xticks(x) - axes[1, 0].set_xticklabels(['Daily', 'Monthly']) - axes[1, 0].legend() + axes[1, 0].set_xticklabels(labels) axes[1, 0].grid(True, alpha=0.3, axis='y') + # Add value labels + for i, (bar, val) in enumerate(zip(bars, deltas)): + height = bar.get_height() + axes[1, 0].text(bar.get_x() + bar.get_width()/2., height, + f'+{val:.2f} MB', + ha='center', va='bottom', fontweight='bold') + # Sync time (assume 5 Mbps connection) bandwidth_mbps = 5 bandwidth_mb_per_sec = bandwidth_mbps / 8 daily_time_current = daily_current_mb / bandwidth_mb_per_sec / 60 # minutes daily_time_with = daily_with_mb / bandwidth_mb_per_sec / 60 + daily_time_delta = daily_time_with - daily_time_current + full_time_current = full_current_gb * 1000 / bandwidth_mb_per_sec / 3600 # hours full_time_with = full_with_gb * 1000 / bandwidth_mb_per_sec / 3600 + full_time_delta = full_time_with - full_time_current x = np.arange(2) axes[1, 1].bar(x - width/2, [daily_time_current, full_time_current], @@ -396,6 +488,15 @@ def plot_bandwidth_impact(self, filename): axes[1, 1].legend() axes[1, 1].grid(True, alpha=0.3, axis='y') + # Add delta annotations + for i, delta in enumerate([daily_time_delta, full_time_delta]): + y_pos = max([daily_time_current, full_time_current][i], + [daily_time_with, full_time_with][i]) * 1.05 + unit = 'min' if i == 0 else 'hrs' + axes[1, 1].text(i, y_pos, f'+{delta:.1f} {unit}', + ha='center', fontsize=10, fontweight='bold', + bbox=dict(boxstyle='round', facecolor='yellow', alpha=0.3)) + plt.tight_layout() plt.savefig(filename, dpi=300, bbox_inches='tight') plt.close() From 9da170c3fe30069783923c947c55720ddac9a9ad Mon Sep 17 00:00:00 2001 From: Pacu Date: Thu, 9 Oct 2025 18:11:48 -0300 Subject: [PATCH 04/17] cargo fmt --- analyzer/build.rs | 10 ++- analyzer/src/main.rs | 167 +++++++++++++++++++++++++++++-------------- 2 files changed, 117 insertions(+), 60 deletions(-) diff --git a/analyzer/build.rs b/analyzer/build.rs index 5179ef9..0c9ec23 100644 --- a/analyzer/build.rs +++ b/analyzer/build.rs @@ -1,9 +1,7 @@ fn main() -> Result<(), Box> { - tonic_build::configure() - .build_server(false) - .compile( - &["proto/service.proto", "proto/compact_formats.proto"], - &["proto/"], - )?; + tonic_build::configure().build_server(false).compile( + &["proto/service.proto", "proto/compact_formats.proto"], + &["proto/"], + )?; Ok(()) } diff --git a/analyzer/src/main.rs b/analyzer/src/main.rs index 580a5d2..3585b7f 100644 --- a/analyzer/src/main.rs +++ b/analyzer/src/main.rs @@ -17,9 +17,7 @@ pub mod cash { } use cash::z::wallet::sdk::rpc::{ - compact_tx_streamer_client::CompactTxStreamerClient, - BlockId, - BlockRange, + compact_tx_streamer_client::CompactTxStreamerClient, BlockId, BlockRange, }; // Import sampling module @@ -114,31 +112,32 @@ impl TransparentEstimator { .json() .await?; - let tip = response["result"].as_u64() + let tip = response["result"] + .as_u64() .ok_or_else(|| anyhow::anyhow!("Failed to get block count"))?; - + Ok(tip) } async fn get_compact_block_from_lightwalletd(&self, height: u64) -> Result> { // Connect to lightwalletd gRPC service let mut client = CompactTxStreamerClient::connect(self.lightwalletd_url.clone()).await?; - + // Request a single block by creating a range with start=end=height let request = tonic::Request::new(BlockRange { - start: Some(BlockId { - height: height as u64, - hash: vec![] + start: Some(BlockId { + height: height as u64, + hash: vec![], }), - end: Some(BlockId { - height: height as u64, - hash: vec![] + end: Some(BlockId { + height: height as u64, + hash: vec![], }), }); - + // Get the block stream (will have just one block) let mut stream = client.get_block_range(request).await?.into_inner(); - + // Get the single block from the stream if let Some(compact_block) = stream.message().await? { // Encode the CompactBlock to bytes to measure its actual size @@ -147,7 +146,7 @@ impl TransparentEstimator { compact_block.encode(&mut buf)?; return Ok(buf); } - + anyhow::bail!("Block {} not found in lightwalletd", height) } @@ -204,27 +203,28 @@ impl TransparentEstimator { for vin in &tx.vin { if let (Some(_txid), Some(vout_idx)) = (&vin.txid, &vin.vout) { // Regular transparent input (not a coinbase) - + // OutPoint message size: let mut outpoint_size = 0; - + // Field 1: bytes txid = 32 bytes // Tag (1 byte) + length varint (1 byte) + 32 bytes outpoint_size += 1 + 1 + 32; - + // Field 2: uint32 index (varint) // Tag (1 byte) + varint value (1-5 bytes, typically 1-2) outpoint_size += 1 + Self::varint_size(*vout_idx as usize); - + // CompactTxIn wraps OutPoint as field 1 let mut compact_txin_size = 0; // Tag for field 1 (1 byte) + length of OutPoint + OutPoint data compact_txin_size += 1 + Self::varint_size(outpoint_size) + outpoint_size; - + // This CompactTxIn is in a repeated field (vin = 7) in CompactTx // Tag for repeated field (1 byte) + length + message - let vin_entry_size = 1 + Self::varint_size(compact_txin_size) + compact_txin_size; - + let vin_entry_size = + 1 + Self::varint_size(compact_txin_size) + compact_txin_size; + total_overhead += vin_entry_size; input_count += 1; } else { @@ -239,7 +239,7 @@ impl TransparentEstimator { // - Sequence value: 4 bytes // - Repeated field overhead: 1 byte tag + 1 byte length // Total: ~79 bytes - + const COINBASE_COMPACT_TXIN_SIZE: usize = 79; total_overhead += COINBASE_COMPACT_TXIN_SIZE; input_count += 1; @@ -249,19 +249,19 @@ impl TransparentEstimator { // Estimate TxOut (repeated field in CompactTx) for vout in &tx.vout { let mut txout_size = 0; - + // Field 1: uint32 value (varint) let value_zatoshis = (vout.value * 100_000_000.0) as u64; txout_size += 1 + Self::varint_size(value_zatoshis as usize); - + // Field 2: bytes scriptPubKey let script_len = vout.script_pubkey.hex.len() / 2; // hex to bytes txout_size += 1 + Self::varint_size(script_len) + script_len; - + // This TxOut is in a repeated field (vout = 8) in CompactTx // Tag for repeated field (1 byte) + length + message let vout_entry_size = 1 + Self::varint_size(txout_size) + txout_size; - + total_overhead += vout_entry_size; output_count += 1; } @@ -288,7 +288,7 @@ impl TransparentEstimator { // Get full block from Zebra to calculate transparent overhead let full_block = self.get_full_block_from_zebra(height).await?; - let (transparent_overhead, input_count, output_count) = + let (transparent_overhead, input_count, output_count) = self.estimate_transparent_overhead(&full_block); let estimated_size = current_size + transparent_overhead; @@ -319,7 +319,12 @@ impl TransparentEstimator { for (i, &height) in heights.iter().enumerate() { if i % 10 == 0 { - println!("Progress: {}/{} ({:.1}%)", i, total, (i as f64 / total as f64) * 100.0); + println!( + "Progress: {}/{} ({:.1}%)", + i, + total, + (i as f64 / total as f64) * 100.0 + ); } match self.analyze_block(height).await { @@ -376,34 +381,63 @@ impl TransparentEstimator { println!("\n=== ANALYSIS SUMMARY ==="); println!("Blocks analyzed: {}", results.len()); println!("\nCurrent compact blocks:"); - println!(" Total: {} bytes ({:.2} MB)", total_current, total_current as f64 / 1_000_000.0); + println!( + " Total: {} bytes ({:.2} MB)", + total_current, + total_current as f64 / 1_000_000.0 + ); println!("\nWith transparent data:"); - println!(" Estimated total: {} bytes ({:.2} MB)", total_estimated, total_estimated as f64 / 1_000_000.0); - println!(" Delta: +{} bytes ({:.2} MB)", total_delta, total_delta as f64 / 1_000_000.0); - println!(" Overall increase: {:.2}%", (total_delta as f64 / total_current as f64) * 100.0); + println!( + " Estimated total: {} bytes ({:.2} MB)", + total_estimated, + total_estimated as f64 / 1_000_000.0 + ); + println!( + " Delta: +{} bytes ({:.2} MB)", + total_delta, + total_delta as f64 / 1_000_000.0 + ); + println!( + " Overall increase: {:.2}%", + (total_delta as f64 / total_current as f64) * 100.0 + ); println!("\nPer-block statistics:"); println!(" Median increase: {:.2}%", median); println!(" 95th percentile: {:.2}%", p95); println!(" Min: {:.2}%", deltas[0]); println!(" Max: {:.2}%", deltas[deltas.len() - 1]); - + // Practical impact examples println!("\nPractical impact:"); let blocks_per_day = 1152; // Post-Blossom (75s blocks) let daily_current = (total_current as f64 / results.len() as f64) * blocks_per_day as f64; - let daily_estimated = (total_estimated as f64 / results.len() as f64) * blocks_per_day as f64; - println!(" Current daily sync (~{} blocks): {:.2} MB", blocks_per_day, daily_current / 1_000_000.0); - println!(" With transparent: {:.2} MB", daily_estimated / 1_000_000.0); - println!(" Additional bandwidth per day: {:.2} MB", (daily_estimated - daily_current) / 1_000_000.0); + let daily_estimated = + (total_estimated as f64 / results.len() as f64) * blocks_per_day as f64; + println!( + " Current daily sync (~{} blocks): {:.2} MB", + blocks_per_day, + daily_current / 1_000_000.0 + ); + println!( + " With transparent: {:.2} MB", + daily_estimated / 1_000_000.0 + ); + println!( + " Additional bandwidth per day: {:.2} MB", + (daily_estimated - daily_current) / 1_000_000.0 + ); } } #[tokio::main] async fn main() -> Result<()> { let args: Vec = std::env::args().collect(); - + if args.len() < 4 { - eprintln!("Usage: {} [output.csv]", args[0]); + eprintln!( + "Usage: {} [output.csv]", + args[0] + ); eprintln!(); eprintln!("Modes:"); eprintln!(" range - Analyze specific block range"); @@ -415,8 +449,14 @@ async fn main() -> Result<()> { eprintln!(" weighted - Weighted toward recent (~5000 blocks)"); eprintln!(); eprintln!("Examples:"); - eprintln!(" {} http://127.0.0.1:9067 http://127.0.0.1:8232 range 2400000 2401000", args[0]); - eprintln!(" {} http://127.0.0.1:9067 http://127.0.0.1:8232 recommended results.csv", args[0]); + eprintln!( + " {} http://127.0.0.1:9067 http://127.0.0.1:8232 range 2400000 2401000", + args[0] + ); + eprintln!( + " {} http://127.0.0.1:9067 http://127.0.0.1:8232 recommended results.csv", + args[0] + ); std::process::exit(1); } @@ -425,11 +465,9 @@ async fn main() -> Result<()> { let mode = &args[3]; // Get current tip from Zebra - let estimator = TransparentEstimator::new( - zebra_rpc_url.to_string(), - lightwalletd_url.to_string(), - ); - + let estimator = + TransparentEstimator::new(zebra_rpc_url.to_string(), lightwalletd_url.to_string()); + let current_tip = estimator.get_current_tip().await?; println!("Current blockchain tip: {}", current_tip); println!(); @@ -448,37 +486,55 @@ async fn main() -> Result<()> { "quick" => { let sampler = create_quick_sampler(current_tip); println!("{}", sampler.describe()); - let output = args.get(4).map(|s| s.as_str()).unwrap_or("quick_sample.csv"); + let output = args + .get(4) + .map(|s| s.as_str()) + .unwrap_or("quick_sample.csv"); (sampler.generate_samples(), output.to_string()) } "recommended" => { let sampler = create_recommended_sampler(current_tip); println!("{}", sampler.describe()); - let output = args.get(4).map(|s| s.as_str()).unwrap_or("recommended_sample.csv"); + let output = args + .get(4) + .map(|s| s.as_str()) + .unwrap_or("recommended_sample.csv"); (sampler.generate_samples(), output.to_string()) } "thorough" => { let sampler = create_thorough_sampler(current_tip); println!("{}", sampler.describe()); - let output = args.get(4).map(|s| s.as_str()).unwrap_or("thorough_sample.csv"); + let output = args + .get(4) + .map(|s| s.as_str()) + .unwrap_or("thorough_sample.csv"); (sampler.generate_samples(), output.to_string()) } "equal" => { let sampler = create_equal_sampler(current_tip); println!("{}", sampler.describe()); - let output = args.get(4).map(|s| s.as_str()).unwrap_or("equal_sample.csv"); + let output = args + .get(4) + .map(|s| s.as_str()) + .unwrap_or("equal_sample.csv"); (sampler.generate_samples(), output.to_string()) } "proportional" => { let sampler = create_proportional_sampler(current_tip); println!("{}", sampler.describe()); - let output = args.get(4).map(|s| s.as_str()).unwrap_or("proportional_sample.csv"); + let output = args + .get(4) + .map(|s| s.as_str()) + .unwrap_or("proportional_sample.csv"); (sampler.generate_samples(), output.to_string()) } "weighted" => { let sampler = create_weighted_sampler(current_tip); println!("{}", sampler.describe()); - let output = args.get(4).map(|s| s.as_str()).unwrap_or("weighted_sample.csv"); + let output = args + .get(4) + .map(|s| s.as_str()) + .unwrap_or("weighted_sample.csv"); (sampler.generate_samples(), output.to_string()) } _ => { @@ -488,7 +544,10 @@ async fn main() -> Result<()> { }; println!("Analyzing {} blocks...", blocks.len()); - println!("Fetching real compact blocks from lightwalletd: {}", lightwalletd_url); + println!( + "Fetching real compact blocks from lightwalletd: {}", + lightwalletd_url + ); println!("Fetching full blocks from Zebra: {}", zebra_rpc_url); println!(); From 98add46a82ffe70ee2a487cbf0107ba9a2a39cab Mon Sep 17 00:00:00 2001 From: Pacu Date: Thu, 9 Oct 2025 18:30:22 -0300 Subject: [PATCH 05/17] remove .proto files from index --- .gitignore | 3 + analyzer/proto/compact_formats.proto | 84 --------- analyzer/proto/service.proto | 246 --------------------------- 3 files changed, 3 insertions(+), 330 deletions(-) delete mode 100644 analyzer/proto/compact_formats.proto delete mode 100644 analyzer/proto/service.proto diff --git a/.gitignore b/.gitignore index a35445f..f758028 100644 --- a/.gitignore +++ b/.gitignore @@ -3,6 +3,9 @@ /analyzer/Cargo.lock **/*.rs.bk +# Proto files +/analyzer/proto/*.proto + # Python __pycache__/ *.py[cod] diff --git a/analyzer/proto/compact_formats.proto b/analyzer/proto/compact_formats.proto deleted file mode 100644 index 493ffed..0000000 --- a/analyzer/proto/compact_formats.proto +++ /dev/null @@ -1,84 +0,0 @@ -// Copyright (c) 2019-2021 The Zcash developers -// Distributed under the MIT software license, see the accompanying -// file COPYING or https://www.opensource.org/licenses/mit-license.php . - -syntax = "proto3"; -package cash.z.wallet.sdk.rpc; -option go_package = "lightwalletd/walletrpc"; -option swift_prefix = ""; - -// Remember that proto3 fields are all optional. A field that is not present will be set to its zero value. -// bytes fields of hashes are in canonical little-endian format. - -// Information about the state of the chain as of a given block. -message ChainMetadata { - uint32 saplingCommitmentTreeSize = 1; // the size of the Sapling note commitment tree as of the end of this block - uint32 orchardCommitmentTreeSize = 2; // the size of the Orchard note commitment tree as of the end of this block -} - -// A compact representation of the shielded data in a Zcash block. -// -// CompactBlock is a packaging of ONLY the data from a block that's needed to: -// 1. Detect a payment to your Shielded address -// 2. Detect a spend of your Shielded notes -// 3. Update your witnesses to generate new spend proofs. -message CompactBlock { - uint32 protoVersion = 1; // the version of this wire format, for storage - uint64 height = 2; // the height of this block - bytes hash = 3; // the ID (hash) of this block, same as in block explorers - bytes prevHash = 4; // the ID (hash) of this block's predecessor - uint32 time = 5; // Unix epoch time when the block was mined - bytes header = 6; // (hash, prevHash, and time) OR (full header) - repeated CompactTx vtx = 7; // zero or more compact transactions from this block - ChainMetadata chainMetadata = 8; // information about the state of the chain as of this block -} - -// A compact representation of the shielded data in a Zcash transaction. -// -// CompactTx contains the minimum information for a wallet to know if this transaction -// is relevant to it (either pays to it or spends from it) via shielded elements -// only. This message will not encode a transparent-to-transparent transaction. -message CompactTx { - // Index and hash will allow the receiver to call out to chain - // explorers or other data structures to retrieve more information - // about this transaction. - uint64 index = 1; // the index within the full block - bytes hash = 2; // the ID (hash) of this transaction, same as in block explorers - - // The transaction fee: present if server can provide. In the case of a - // stateless server and a transaction with transparent inputs, this will be - // unset because the calculation requires reference to prior transactions. - // If there are no transparent inputs, the fee will be calculable as: - // valueBalanceSapling + valueBalanceOrchard + sum(vPubNew) - sum(vPubOld) - sum(tOut) - uint32 fee = 3; - - repeated CompactSaplingSpend spends = 4; - repeated CompactSaplingOutput outputs = 5; - repeated CompactOrchardAction actions = 6; -} - -// A compact representation of a [Sapling Spend](https://zips.z.cash/protocol/protocol.pdf#spendencodingandconsensus). -// -// CompactSaplingSpend is a Sapling Spend Description as described in 7.3 of the Zcash -// protocol specification. -message CompactSaplingSpend { - bytes nf = 1; // Nullifier (see the Zcash protocol specification) -} - -// A compact representation of a [Sapling Output](https://zips.z.cash/protocol/protocol.pdf#outputencodingandconsensus). -// -// It encodes the `cmu` field, `ephemeralKey` field, and a 52-byte prefix of the -// `encCiphertext` field of a Sapling Output Description. Total size is 116 bytes. -message CompactSaplingOutput { - bytes cmu = 1; // Note commitment u-coordinate. - bytes ephemeralKey = 2; // Ephemeral public key. - bytes ciphertext = 3; // First 52 bytes of ciphertext. -} - -// A compact representation of an [Orchard Action](https://zips.z.cash/protocol/protocol.pdf#actionencodingandconsensus). -message CompactOrchardAction { - bytes nullifier = 1; // [32] The nullifier of the input note - bytes cmx = 2; // [32] The x-coordinate of the note commitment for the output note - bytes ephemeralKey = 3; // [32] An encoding of an ephemeral Pallas public key - bytes ciphertext = 4; // [52] The first 52 bytes of the encCiphertext field -} diff --git a/analyzer/proto/service.proto b/analyzer/proto/service.proto deleted file mode 100644 index 70fcdbd..0000000 --- a/analyzer/proto/service.proto +++ /dev/null @@ -1,246 +0,0 @@ -// Copyright (c) 2019-2020 The Zcash developers -// Distributed under the MIT software license, see the accompanying -// file COPYING or https://www.opensource.org/licenses/mit-license.php . - -syntax = "proto3"; -package cash.z.wallet.sdk.rpc; -option go_package = "lightwalletd/walletrpc"; -option swift_prefix = ""; -import "compact_formats.proto"; - -// A BlockID message contains identifiers to select a block: a height or a -// hash. Specification by hash is not implemented, but may be in the future. -message BlockID { - uint64 height = 1; - bytes hash = 2; -} - -// BlockRange specifies a series of blocks from start to end inclusive. -// Both BlockIDs must be heights; specification by hash is not yet supported. -message BlockRange { - BlockID start = 1; - BlockID end = 2; -} - -// A TxFilter contains the information needed to identify a particular -// transaction: either a block and an index, or a direct transaction hash. -// Currently, only specification by hash is supported. -message TxFilter { - BlockID block = 1; // block identifier, height or hash - uint64 index = 2; // index within the block - bytes hash = 3; // transaction ID (hash, txid) -} - -// RawTransaction contains the complete transaction data. It also optionally includes -// the block height in which the transaction was included, or, when returned -// by GetMempoolStream(), the latest block height. -// -// FIXME: the documentation here about mempool status contradicts the documentation -// for the `height` field. See https://github.com/zcash/librustzcash/issues/1484 -message RawTransaction { - // The serialized representation of the Zcash transaction. - bytes data = 1; - // The height at which the transaction is mined, or a sentinel value. - // - // Due to an error in the original protobuf definition, it is necessary to - // reinterpret the result of the `getrawtransaction` RPC call. Zcashd will - // return the int64 value `-1` for the height of transactions that appear - // in the block index, but which are not mined in the main chain. Here, the - // height field of `RawTransaction` was erroneously created as a `uint64`, - // and as such we must map the response from the zcashd RPC API to be - // representable within this space. Additionally, the `height` field will - // be absent for transactions in the mempool, resulting in the default - // value of `0` being set. Therefore, the meanings of the `height` field of - // the `RawTransaction` type are as follows: - // - // * height 0: the transaction is in the mempool - // * height 0xffffffffffffffff: the transaction has been mined on a fork that - // is not currently the main chain - // * any other height: the transaction has been mined in the main chain at the - // given height - uint64 height = 2; -} - -// A SendResponse encodes an error code and a string. It is currently used -// only by SendTransaction(). If error code is zero, the operation was -// successful; if non-zero, it and the message specify the failure. -message SendResponse { - int32 errorCode = 1; - string errorMessage = 2; -} - -// Chainspec is a placeholder to allow specification of a particular chain fork. -message ChainSpec {} - -// Empty is for gRPCs that take no arguments, currently only GetLightdInfo. -message Empty {} - -// LightdInfo returns various information about this lightwalletd instance -// and the state of the blockchain. -message LightdInfo { - string version = 1; - string vendor = 2; - bool taddrSupport = 3; // true - string chainName = 4; // either "main" or "test" - uint64 saplingActivationHeight = 5; // depends on mainnet or testnet - string consensusBranchId = 6; // protocol identifier, see consensus/upgrades.cpp - uint64 blockHeight = 7; // latest block on the best chain - string gitCommit = 8; - string branch = 9; - string buildDate = 10; - string buildUser = 11; - uint64 estimatedHeight = 12; // less than tip height if zcashd is syncing - string zcashdBuild = 13; // example: "v4.1.1-877212414" - string zcashdSubversion = 14; // example: "/MagicBean:4.1.1/" - string donationAddress = 15; // Zcash donation UA address -} - -// TransparentAddressBlockFilter restricts the results to the given address -// or block range. -message TransparentAddressBlockFilter { - string address = 1; // t-address - BlockRange range = 2; // start, end heights -} - -// Duration is currently used only for testing, so that the Ping rpc -// can simulate a delay, to create many simultaneous connections. Units -// are microseconds. -message Duration { - int64 intervalUs = 1; -} - -// PingResponse is used to indicate concurrency, how many Ping rpcs -// are executing upon entry and upon exit (after the delay). -// This rpc is used for testing only. -message PingResponse { - int64 entry = 1; - int64 exit = 2; -} - -message Address { - string address = 1; -} -message AddressList { - repeated string addresses = 1; -} -message Balance { - int64 valueZat = 1; -} - -// The a shortened transaction ID is the prefix in big-endian (hex) format -// (then converted to binary). -message Exclude { - repeated bytes txid = 1; -} - -// The TreeState is derived from the Zcash z_gettreestate rpc. -message TreeState { - string network = 1; // "main" or "test" - uint64 height = 2; // block height - string hash = 3; // block id - uint32 time = 4; // Unix epoch time when the block was mined - string saplingTree = 5; // sapling commitment tree state - string orchardTree = 6; // orchard commitment tree state -} - -enum ShieldedProtocol { - sapling = 0; - orchard = 1; -} - -message GetSubtreeRootsArg { - uint32 startIndex = 1; // Index identifying where to start returning subtree roots - ShieldedProtocol shieldedProtocol = 2; // Shielded protocol to return subtree roots for - uint32 maxEntries = 3; // Maximum number of entries to return, or 0 for all entries. -} -message SubtreeRoot { - bytes rootHash = 2; // The 32-byte Merkle root of the subtree. - bytes completingBlockHash = 3; // The hash of the block that completed this subtree. - uint64 completingBlockHeight = 4; // The height of the block that completed this subtree in the main chain. -} - -// Results are sorted by height, which makes it easy to issue another -// request that picks up from where the previous left off. -message GetAddressUtxosArg { - repeated string addresses = 1; - uint64 startHeight = 2; - uint32 maxEntries = 3; // zero means unlimited -} -message GetAddressUtxosReply { - string address = 6; - bytes txid = 1; - int32 index = 2; - bytes script = 3; - int64 valueZat = 4; - uint64 height = 5; -} -message GetAddressUtxosReplyList { - repeated GetAddressUtxosReply addressUtxos = 1; -} - -service CompactTxStreamer { - // Return the BlockID of the block at the tip of the best chain - rpc GetLatestBlock(ChainSpec) returns (BlockID) {} - // Return the compact block corresponding to the given block identifier - rpc GetBlock(BlockID) returns (CompactBlock) {} - // Same as GetBlock except actions contain only nullifiers - rpc GetBlockNullifiers(BlockID) returns (CompactBlock) {} - // Return a list of consecutive compact blocks - rpc GetBlockRange(BlockRange) returns (stream CompactBlock) {} - // Same as GetBlockRange except actions contain only nullifiers - rpc GetBlockRangeNullifiers(BlockRange) returns (stream CompactBlock) {} - - // Return the requested full (not compact) transaction (as from zcashd) - rpc GetTransaction(TxFilter) returns (RawTransaction) {} - // Submit the given transaction to the Zcash network - rpc SendTransaction(RawTransaction) returns (SendResponse) {} - - // Return RawTransactions that match the given transparent address filter. - // - // Note: This function is misnamed, it returns complete `RawTransaction` values, not TxIds. - // NOTE: this method is deprecated, please use GetTaddressTransactions instead. - rpc GetTaddressTxids(TransparentAddressBlockFilter) returns (stream RawTransaction) {} - - // Return the transactions corresponding to the given t-address within the given block range - rpc GetTaddressTransactions(TransparentAddressBlockFilter) returns (stream RawTransaction) {} - - rpc GetTaddressBalance(AddressList) returns (Balance) {} - rpc GetTaddressBalanceStream(stream Address) returns (Balance) {} - - // Return the compact transactions currently in the mempool; the results - // can be a few seconds out of date. If the Exclude list is empty, return - // all transactions; otherwise return all *except* those in the Exclude list - // (if any); this allows the client to avoid receiving transactions that it - // already has (from an earlier call to this rpc). The transaction IDs in the - // Exclude list can be shortened to any number of bytes to make the request - // more bandwidth-efficient; if two or more transactions in the mempool - // match a shortened txid, they are all sent (none is excluded). Transactions - // in the exclude list that don't exist in the mempool are ignored. - // - // The a shortened transaction ID is the prefix in big-endian (hex) format - // (then converted to binary). See smoke-test.bash for examples. - rpc GetMempoolTx(Exclude) returns (stream CompactTx) {} - - // Return a stream of current Mempool transactions. This will keep the output stream open while - // there are mempool transactions. It will close the returned stream when a new block is mined. - rpc GetMempoolStream(Empty) returns (stream RawTransaction) {} - - // GetTreeState returns the note commitment tree state corresponding to the given block. - // See section 3.7 of the Zcash protocol specification. It returns several other useful - // values also (even though they can be obtained using GetBlock). - // The block can be specified by either height or hash. - rpc GetTreeState(BlockID) returns (TreeState) {} - rpc GetLatestTreeState(Empty) returns (TreeState) {} - - // Returns a stream of information about roots of subtrees of the note commitment tree - // for the specified shielded protocol (Sapling or Orchard). - rpc GetSubtreeRoots(GetSubtreeRootsArg) returns (stream SubtreeRoot) {} - - rpc GetAddressUtxos(GetAddressUtxosArg) returns (GetAddressUtxosReplyList) {} - rpc GetAddressUtxosStream(GetAddressUtxosArg) returns (stream GetAddressUtxosReply) {} - - // Return information about this lightwalletd instance and the blockchain - rpc GetLightdInfo(Empty) returns (LightdInfo) {} - // Testing-only, requires lightwalletd --ping-very-insecure (do not enable in production) - rpc Ping(Duration) returns (PingResponse) {} -} From 321d29ddf3e80bf14bf53100350998c1648bd35c Mon Sep 17 00:00:00 2001 From: Pacu Date: Thu, 9 Oct 2025 18:35:27 -0300 Subject: [PATCH 06/17] Fix Python CI --- .github/workflows/python-ci.yml | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/.github/workflows/python-ci.yml b/.github/workflows/python-ci.yml index c3dcbdc..3082561 100644 --- a/.github/workflows/python-ci.yml +++ b/.github/workflows/python-ci.yml @@ -28,8 +28,8 @@ jobs: - name: Lint with flake8 working-directory: ./visualization run: | - flake8 . --count --select=E9,F63,F7,F82 --show-source --statistics - flake8 . --count --exit-zero --max-complexity=10 --max-line-length=127 --statistics + flake8 . --count --select=E9,F63,F7,F82 --show-source --statistics --filename visualize.py + flake8 . --count --exit-zero --max-complexity=10 --max-line-length=127 --statistics --filename visualize.py - name: Check formatting with black working-directory: ./visualization From f5729e96ab66e6e01589b2185f2005bdf26e1fe0 Mon Sep 17 00:00:00 2001 From: Pacu Date: Thu, 9 Oct 2025 18:47:03 -0300 Subject: [PATCH 07/17] Fix Black fmt --- visualization/visualize.py | 987 ++++++++++++++++++++++--------------- 1 file changed, 591 insertions(+), 396 deletions(-) diff --git a/visualization/visualize.py b/visualization/visualize.py index d8e1817..1fc6a93 100644 --- a/visualization/visualize.py +++ b/visualization/visualize.py @@ -16,556 +16,741 @@ # Set style sns.set_style("whitegrid") -plt.rcParams['figure.figsize'] = (12, 6) -plt.rcParams['font.size'] = 10 +plt.rcParams["figure.figsize"] = (12, 6) +plt.rcParams["font.size"] = 10 + class CompactBlockAnalyzer: def __init__(self, csv_path): self.df = pd.read_csv(csv_path) - self.df['delta_mb'] = self.df['delta_bytes'] / 1_000_000 - self.df['current_mb'] = self.df['current_compact_size'] / 1_000_000 - self.df['estimated_mb'] = self.df['estimated_with_transparent'] / 1_000_000 - - def generate_all_charts(self, output_dir='./charts'): + self.df["delta_mb"] = self.df["delta_bytes"] / 1_000_000 + self.df["current_mb"] = self.df["current_compact_size"] / 1_000_000 + self.df["estimated_mb"] = self.df["estimated_with_transparent"] / 1_000_000 + + def generate_all_charts(self, output_dir="./charts"): """Generate all visualization charts""" output_path = Path(output_dir) output_path.mkdir(exist_ok=True) - + print("Generating visualizations...") - - self.plot_distribution(output_path / 'distribution.png') - self.plot_time_series(output_path / 'time_series.png') - self.plot_by_era(output_path / 'by_era.png') - self.plot_correlations(output_path / 'correlations.png') - self.plot_cumulative(output_path / 'cumulative.png') - self.plot_bandwidth_impact(output_path / 'bandwidth_impact.png') - self.plot_heatmap(output_path / 'heatmap.png') - + + self.plot_distribution(output_path / "distribution.png") + self.plot_time_series(output_path / "time_series.png") + self.plot_by_era(output_path / "by_era.png") + self.plot_correlations(output_path / "correlations.png") + self.plot_cumulative(output_path / "cumulative.png") + self.plot_bandwidth_impact(output_path / "bandwidth_impact.png") + self.plot_heatmap(output_path / "heatmap.png") + # Generate statistical report - self.generate_report(output_path / 'statistical_report.txt') - + self.generate_report(output_path / "statistical_report.txt") + print(f"\nAll visualizations saved to: {output_path}") - + def plot_distribution(self, filename): """Histogram of overhead distribution - both percentage and absolute""" fig, axes = plt.subplots(2, 2, figsize=(14, 10)) - + # Top row: Percentage overhead # Histogram with KDE - axes[0, 0].hist(self.df['delta_percent'], bins=50, alpha=0.7, - edgecolor='black', density=True, label='Distribution') - + axes[0, 0].hist( + self.df["delta_percent"], + bins=50, + alpha=0.7, + edgecolor="black", + density=True, + label="Distribution", + ) + # Add KDE - kde_x = np.linspace(self.df['delta_percent'].min(), - self.df['delta_percent'].max(), 100) - kde = stats.gaussian_kde(self.df['delta_percent']) - axes[0, 0].plot(kde_x, kde(kde_x), 'r-', linewidth=2, label='KDE') - + kde_x = np.linspace( + self.df["delta_percent"].min(), self.df["delta_percent"].max(), 100 + ) + kde = stats.gaussian_kde(self.df["delta_percent"]) + axes[0, 0].plot(kde_x, kde(kde_x), "r-", linewidth=2, label="KDE") + # Add median and mean - median = self.df['delta_percent'].median() - mean = self.df['delta_percent'].mean() - axes[0, 0].axvline(median, color='green', linestyle='--', - linewidth=2, label=f'Median: {median:.1f}%') - axes[0, 0].axvline(mean, color='orange', linestyle='--', - linewidth=2, label=f'Mean: {mean:.1f}%') - - axes[0, 0].set_xlabel('Overhead Percentage (%)') - axes[0, 0].set_ylabel('Density') - axes[0, 0].set_title('Distribution of Overhead (Percentage)') + median = self.df["delta_percent"].median() + mean = self.df["delta_percent"].mean() + axes[0, 0].axvline( + median, + color="green", + linestyle="--", + linewidth=2, + label=f"Median: {median:.1f}%", + ) + axes[0, 0].axvline( + mean, + color="orange", + linestyle="--", + linewidth=2, + label=f"Mean: {mean:.1f}%", + ) + + axes[0, 0].set_xlabel("Overhead Percentage (%)") + axes[0, 0].set_ylabel("Density") + axes[0, 0].set_title("Distribution of Overhead (Percentage)") axes[0, 0].legend() axes[0, 0].grid(True, alpha=0.3) - + # Box plot - percentage - axes[0, 1].boxplot(self.df['delta_percent'], vert=True) - axes[0, 1].set_ylabel('Overhead Percentage (%)') - axes[0, 1].set_title('Overhead Distribution (Box Plot - Percentage)') + axes[0, 1].boxplot(self.df["delta_percent"], vert=True) + axes[0, 1].set_ylabel("Overhead Percentage (%)") + axes[0, 1].set_title("Overhead Distribution (Box Plot - Percentage)") axes[0, 1].grid(True, alpha=0.3) - + # Bottom row: Absolute overhead in KB - self.df['delta_kb'] = self.df['delta_bytes'] / 1000 - + self.df["delta_kb"] = self.df["delta_bytes"] / 1000 + # Histogram with KDE - absolute - axes[1, 0].hist(self.df['delta_kb'], bins=50, alpha=0.7, - edgecolor='black', density=True, label='Distribution', color='coral') - + axes[1, 0].hist( + self.df["delta_kb"], + bins=50, + alpha=0.7, + edgecolor="black", + density=True, + label="Distribution", + color="coral", + ) + # Add KDE - kde_x_kb = np.linspace(self.df['delta_kb'].min(), - self.df['delta_kb'].max(), 100) - kde_kb = stats.gaussian_kde(self.df['delta_kb']) - axes[1, 0].plot(kde_x_kb, kde_kb(kde_x_kb), 'r-', linewidth=2, label='KDE') - + kde_x_kb = np.linspace( + self.df["delta_kb"].min(), self.df["delta_kb"].max(), 100 + ) + kde_kb = stats.gaussian_kde(self.df["delta_kb"]) + axes[1, 0].plot(kde_x_kb, kde_kb(kde_x_kb), "r-", linewidth=2, label="KDE") + # Add median and mean - median_kb = self.df['delta_kb'].median() - mean_kb = self.df['delta_kb'].mean() - axes[1, 0].axvline(median_kb, color='green', linestyle='--', - linewidth=2, label=f'Median: {median_kb:.1f} KB') - axes[1, 0].axvline(mean_kb, color='orange', linestyle='--', - linewidth=2, label=f'Mean: {mean_kb:.1f} KB') - - axes[1, 0].set_xlabel('Overhead (KB per block)') - axes[1, 0].set_ylabel('Density') - axes[1, 0].set_title('Distribution of Overhead (Absolute Size)') + median_kb = self.df["delta_kb"].median() + mean_kb = self.df["delta_kb"].mean() + axes[1, 0].axvline( + median_kb, + color="green", + linestyle="--", + linewidth=2, + label=f"Median: {median_kb:.1f} KB", + ) + axes[1, 0].axvline( + mean_kb, + color="orange", + linestyle="--", + linewidth=2, + label=f"Mean: {mean_kb:.1f} KB", + ) + + axes[1, 0].set_xlabel("Overhead (KB per block)") + axes[1, 0].set_ylabel("Density") + axes[1, 0].set_title("Distribution of Overhead (Absolute Size)") axes[1, 0].legend() axes[1, 0].grid(True, alpha=0.3) - + # Box plot - absolute - axes[1, 1].boxplot(self.df['delta_kb'], vert=True) - axes[1, 1].set_ylabel('Overhead (KB per block)') - axes[1, 1].set_title('Overhead Distribution (Box Plot - Absolute)') + axes[1, 1].boxplot(self.df["delta_kb"], vert=True) + axes[1, 1].set_ylabel("Overhead (KB per block)") + axes[1, 1].set_title("Overhead Distribution (Box Plot - Absolute)") axes[1, 1].grid(True, alpha=0.3) - + plt.tight_layout() - plt.savefig(filename, dpi=300, bbox_inches='tight') + plt.savefig(filename, dpi=300, bbox_inches="tight") plt.close() print(f" ✓ Distribution chart saved: {filename}") - + def plot_time_series(self, filename): """Overhead over blockchain height""" fig, axes = plt.subplots(2, 1, figsize=(14, 10)) - + # Scatter plot with trend - axes[0].scatter(self.df['height'], self.df['delta_percent'], - alpha=0.4, s=10, c=self.df['delta_percent'], - cmap='YlOrRd') - + axes[0].scatter( + self.df["height"], + self.df["delta_percent"], + alpha=0.4, + s=10, + c=self.df["delta_percent"], + cmap="YlOrRd", + ) + # Add rolling mean window = max(len(self.df) // 50, 10) - rolling_mean = self.df.set_index('height')['delta_percent'].rolling(window).mean() - axes[0].plot(rolling_mean.index, rolling_mean.values, - 'b-', linewidth=2, label=f'Rolling Mean (window={window})') - + rolling_mean = ( + self.df.set_index("height")["delta_percent"].rolling(window).mean() + ) + axes[0].plot( + rolling_mean.index, + rolling_mean.values, + "b-", + linewidth=2, + label=f"Rolling Mean (window={window})", + ) + # Add era boundaries eras = [ - (419_200, 'Sapling', 'red'), - (653_600, 'Blossom', 'blue'), - (903_800, 'Heartwood', 'purple'), - (1_046_400, 'Canopy', 'orange'), - (1_687_104, 'NU5', 'green'), - (2_726_400, 'NU6', 'brown'), + (419_200, "Sapling", "red"), + (653_600, "Blossom", "blue"), + (903_800, "Heartwood", "purple"), + (1_046_400, "Canopy", "orange"), + (1_687_104, "NU5", "green"), + (2_726_400, "NU6", "brown"), ] - + for height, name, color in eras: - if height >= self.df['height'].min() and height <= self.df['height'].max(): - axes[0].axvline(height, color=color, alpha=0.3, - linestyle='--', linewidth=1.5) - axes[0].text(height, axes[0].get_ylim()[1] * 0.95, name, - rotation=90, verticalalignment='top', color=color) - - axes[0].set_xlabel('Block Height') - axes[0].set_ylabel('Overhead (%)') - axes[0].set_title('Compact Block Overhead Over Time') + if height >= self.df["height"].min() and height <= self.df["height"].max(): + axes[0].axvline( + height, color=color, alpha=0.3, linestyle="--", linewidth=1.5 + ) + axes[0].text( + height, + axes[0].get_ylim()[1] * 0.95, + name, + rotation=90, + verticalalignment="top", + color=color, + ) + + axes[0].set_xlabel("Block Height") + axes[0].set_ylabel("Overhead (%)") + axes[0].set_title("Compact Block Overhead Over Time") axes[0].legend() axes[0].grid(True, alpha=0.3) - + # Absolute size over time - axes[1].scatter(self.df['height'], self.df['delta_mb'], - alpha=0.4, s=10, c=self.df['delta_mb'], - cmap='YlOrRd') - - rolling_delta = self.df.set_index('height')['delta_mb'].rolling(window).mean() - axes[1].plot(rolling_delta.index, rolling_delta.values, - 'b-', linewidth=2, label=f'Rolling Mean') - + axes[1].scatter( + self.df["height"], + self.df["delta_mb"], + alpha=0.4, + s=10, + c=self.df["delta_mb"], + cmap="YlOrRd", + ) + + rolling_delta = self.df.set_index("height")["delta_mb"].rolling(window).mean() + axes[1].plot( + rolling_delta.index, + rolling_delta.values, + "b-", + linewidth=2, + label=f"Rolling Mean", + ) + for height, name, color in eras: - if height >= self.df['height'].min() and height <= self.df['height'].max(): - axes[1].axvline(height, color=color, alpha=0.3, - linestyle='--', linewidth=1.5) - - axes[1].set_xlabel('Block Height') - axes[1].set_ylabel('Delta Size (MB)') - axes[1].set_title('Absolute Size Increase Over Time') + if height >= self.df["height"].min() and height <= self.df["height"].max(): + axes[1].axvline( + height, color=color, alpha=0.3, linestyle="--", linewidth=1.5 + ) + + axes[1].set_xlabel("Block Height") + axes[1].set_ylabel("Delta Size (MB)") + axes[1].set_title("Absolute Size Increase Over Time") axes[1].legend() axes[1].grid(True, alpha=0.3) - + plt.tight_layout() - plt.savefig(filename, dpi=300, bbox_inches='tight') + plt.savefig(filename, dpi=300, bbox_inches="tight") plt.close() print(f" ✓ Time series chart saved: {filename}") - + def plot_by_era(self, filename): """Compare distributions across eras - both percentage and absolute""" fig, axes = plt.subplots(2, 3, figsize=(18, 10)) - - era_order = ['sapling', 'blossom', 'heartwood', 'canopy', 'nu5', 'nu6'] - available_eras = [e for e in era_order if e in self.df['era'].values] - - colors = ['lightgreen', 'lightyellow', 'lightpink', 'lightcoral', 'lavender', 'peachpuff'] - + + era_order = ["sapling", "blossom", "heartwood", "canopy", "nu5", "nu6"] + available_eras = [e for e in era_order if e in self.df["era"].values] + + colors = [ + "lightgreen", + "lightyellow", + "lightpink", + "lightcoral", + "lavender", + "peachpuff", + ] + # Add KB column - self.df['delta_kb'] = self.df['delta_bytes'] / 1000 - + self.df["delta_kb"] = self.df["delta_bytes"] / 1000 + # Top row: Percentage overhead # Box plot by era - percentage - box_data_pct = [self.df[self.df['era'] == era]['delta_percent'].values - for era in available_eras] - + box_data_pct = [ + self.df[self.df["era"] == era]["delta_percent"].values + for era in available_eras + ] + bp1 = axes[0, 0].boxplot(box_data_pct, labels=available_eras, patch_artist=True) - for patch, color in zip(bp1['boxes'], colors[:len(available_eras)]): + for patch, color in zip(bp1["boxes"], colors[: len(available_eras)]): patch.set_facecolor(color) - - axes[0, 0].set_ylabel('Overhead (%)') - axes[0, 0].set_title('Overhead Distribution by Era (Percentage)') + + axes[0, 0].set_ylabel("Overhead (%)") + axes[0, 0].set_title("Overhead Distribution by Era (Percentage)") axes[0, 0].grid(True, alpha=0.3) - axes[0, 0].tick_params(axis='x', rotation=45) - + axes[0, 0].tick_params(axis="x", rotation=45) + # Violin plot - percentage if len(available_eras) > 0: - era_df = self.df[self.df['era'].isin(available_eras)] - sns.violinplot(data=era_df, x='era', y='delta_percent', - order=available_eras, ax=axes[0, 1]) - axes[0, 1].set_ylabel('Overhead (%)') - axes[0, 1].set_title('Overhead Distribution by Era (Violin - Percentage)') + era_df = self.df[self.df["era"].isin(available_eras)] + sns.violinplot( + data=era_df, + x="era", + y="delta_percent", + order=available_eras, + ax=axes[0, 1], + ) + axes[0, 1].set_ylabel("Overhead (%)") + axes[0, 1].set_title("Overhead Distribution by Era (Violin - Percentage)") axes[0, 1].grid(True, alpha=0.3) - axes[0, 1].tick_params(axis='x', rotation=45) - + axes[0, 1].tick_params(axis="x", rotation=45) + # Bar chart of means - percentage - era_stats_pct = self.df.groupby('era')['delta_percent'].agg(['mean', 'std']) + era_stats_pct = self.df.groupby("era")["delta_percent"].agg(["mean", "std"]) era_stats_pct = era_stats_pct.reindex(available_eras) - + x = np.arange(len(available_eras)) - axes[0, 2].bar(x, era_stats_pct['mean'], yerr=era_stats_pct['std'], - capsize=5, alpha=0.7, color=colors[:len(available_eras)]) + axes[0, 2].bar( + x, + era_stats_pct["mean"], + yerr=era_stats_pct["std"], + capsize=5, + alpha=0.7, + color=colors[: len(available_eras)], + ) axes[0, 2].set_xticks(x) axes[0, 2].set_xticklabels(available_eras, rotation=45) - axes[0, 2].set_ylabel('Mean Overhead (%)') - axes[0, 2].set_title('Average Overhead by Era (Percentage)') + axes[0, 2].set_ylabel("Mean Overhead (%)") + axes[0, 2].set_title("Average Overhead by Era (Percentage)") axes[0, 2].grid(True, alpha=0.3) - + # Bottom row: Absolute KB overhead # Box plot by era - KB - box_data_kb = [self.df[self.df['era'] == era]['delta_kb'].values - for era in available_eras] - + box_data_kb = [ + self.df[self.df["era"] == era]["delta_kb"].values for era in available_eras + ] + bp2 = axes[1, 0].boxplot(box_data_kb, labels=available_eras, patch_artist=True) - for patch, color in zip(bp2['boxes'], colors[:len(available_eras)]): + for patch, color in zip(bp2["boxes"], colors[: len(available_eras)]): patch.set_facecolor(color) - - axes[1, 0].set_ylabel('Overhead (KB per block)') - axes[1, 0].set_title('Overhead Distribution by Era (Absolute)') + + axes[1, 0].set_ylabel("Overhead (KB per block)") + axes[1, 0].set_title("Overhead Distribution by Era (Absolute)") axes[1, 0].grid(True, alpha=0.3) - axes[1, 0].tick_params(axis='x', rotation=45) - + axes[1, 0].tick_params(axis="x", rotation=45) + # Violin plot - KB if len(available_eras) > 0: - sns.violinplot(data=era_df, x='era', y='delta_kb', - order=available_eras, ax=axes[1, 1], color='coral') - axes[1, 1].set_ylabel('Overhead (KB per block)') - axes[1, 1].set_title('Overhead Distribution by Era (Violin - Absolute)') + sns.violinplot( + data=era_df, + x="era", + y="delta_kb", + order=available_eras, + ax=axes[1, 1], + color="coral", + ) + axes[1, 1].set_ylabel("Overhead (KB per block)") + axes[1, 1].set_title("Overhead Distribution by Era (Violin - Absolute)") axes[1, 1].grid(True, alpha=0.3) - axes[1, 1].tick_params(axis='x', rotation=45) - + axes[1, 1].tick_params(axis="x", rotation=45) + # Bar chart of means - KB - era_stats_kb = self.df.groupby('era')['delta_kb'].agg(['mean', 'std']) + era_stats_kb = self.df.groupby("era")["delta_kb"].agg(["mean", "std"]) era_stats_kb = era_stats_kb.reindex(available_eras) - - axes[1, 2].bar(x, era_stats_kb['mean'], yerr=era_stats_kb['std'], - capsize=5, alpha=0.7, color=colors[:len(available_eras)]) + + axes[1, 2].bar( + x, + era_stats_kb["mean"], + yerr=era_stats_kb["std"], + capsize=5, + alpha=0.7, + color=colors[: len(available_eras)], + ) axes[1, 2].set_xticks(x) axes[1, 2].set_xticklabels(available_eras, rotation=45) - axes[1, 2].set_ylabel('Mean Overhead (KB per block)') - axes[1, 2].set_title('Average Overhead by Era (Absolute)') + axes[1, 2].set_ylabel("Mean Overhead (KB per block)") + axes[1, 2].set_title("Average Overhead by Era (Absolute)") axes[1, 2].grid(True, alpha=0.3) - + plt.tight_layout() - plt.savefig(filename, dpi=300, bbox_inches='tight') + plt.savefig(filename, dpi=300, bbox_inches="tight") plt.close() print(f" ✓ Era comparison chart saved: {filename}") - + def plot_correlations(self, filename): """Correlation between overhead and transaction characteristics""" fig, axes = plt.subplots(2, 2, figsize=(14, 10)) - + # Overhead vs transparent inputs - axes[0, 0].scatter(self.df['transparent_inputs'], self.df['delta_bytes'], - alpha=0.5, s=20) - z = np.polyfit(self.df['transparent_inputs'], self.df['delta_bytes'], 1) + axes[0, 0].scatter( + self.df["transparent_inputs"], self.df["delta_bytes"], alpha=0.5, s=20 + ) + z = np.polyfit(self.df["transparent_inputs"], self.df["delta_bytes"], 1) p = np.poly1d(z) - axes[0, 0].plot(self.df['transparent_inputs'], - p(self.df['transparent_inputs']), - "r--", linewidth=2, label=f'Trend') - - corr = self.df['transparent_inputs'].corr(self.df['delta_bytes']) - axes[0, 0].set_xlabel('Transparent Inputs') - axes[0, 0].set_ylabel('Delta (bytes)') - axes[0, 0].set_title(f'Overhead vs Transparent Inputs (r={corr:.3f})') + axes[0, 0].plot( + self.df["transparent_inputs"], + p(self.df["transparent_inputs"]), + "r--", + linewidth=2, + label=f"Trend", + ) + + corr = self.df["transparent_inputs"].corr(self.df["delta_bytes"]) + axes[0, 0].set_xlabel("Transparent Inputs") + axes[0, 0].set_ylabel("Delta (bytes)") + axes[0, 0].set_title(f"Overhead vs Transparent Inputs (r={corr:.3f})") axes[0, 0].legend() axes[0, 0].grid(True, alpha=0.3) - + # Overhead vs transparent outputs - axes[0, 1].scatter(self.df['transparent_outputs'], self.df['delta_bytes'], - alpha=0.5, s=20, color='orange') - z = np.polyfit(self.df['transparent_outputs'], self.df['delta_bytes'], 1) + axes[0, 1].scatter( + self.df["transparent_outputs"], + self.df["delta_bytes"], + alpha=0.5, + s=20, + color="orange", + ) + z = np.polyfit(self.df["transparent_outputs"], self.df["delta_bytes"], 1) p = np.poly1d(z) - axes[0, 1].plot(self.df['transparent_outputs'], - p(self.df['transparent_outputs']), - "r--", linewidth=2, label='Trend') - - corr = self.df['transparent_outputs'].corr(self.df['delta_bytes']) - axes[0, 1].set_xlabel('Transparent Outputs') - axes[0, 1].set_ylabel('Delta (bytes)') - axes[0, 1].set_title(f'Overhead vs Transparent Outputs (r={corr:.3f})') + axes[0, 1].plot( + self.df["transparent_outputs"], + p(self.df["transparent_outputs"]), + "r--", + linewidth=2, + label="Trend", + ) + + corr = self.df["transparent_outputs"].corr(self.df["delta_bytes"]) + axes[0, 1].set_xlabel("Transparent Outputs") + axes[0, 1].set_ylabel("Delta (bytes)") + axes[0, 1].set_title(f"Overhead vs Transparent Outputs (r={corr:.3f})") axes[0, 1].legend() axes[0, 1].grid(True, alpha=0.3) - + # Overhead vs total transactions - axes[1, 0].scatter(self.df['tx_count'], self.df['delta_percent'], - alpha=0.5, s=20, color='green') - - corr = self.df['tx_count'].corr(self.df['delta_percent']) - axes[1, 0].set_xlabel('Transaction Count') - axes[1, 0].set_ylabel('Overhead (%)') - axes[1, 0].set_title(f'Overhead % vs Transaction Count (r={corr:.3f})') + axes[1, 0].scatter( + self.df["tx_count"], + self.df["delta_percent"], + alpha=0.5, + s=20, + color="green", + ) + + corr = self.df["tx_count"].corr(self.df["delta_percent"]) + axes[1, 0].set_xlabel("Transaction Count") + axes[1, 0].set_ylabel("Overhead (%)") + axes[1, 0].set_title(f"Overhead % vs Transaction Count (r={corr:.3f})") axes[1, 0].grid(True, alpha=0.3) - + # Current size vs overhead - axes[1, 1].scatter(self.df['current_compact_size'], - self.df['delta_percent'], - alpha=0.5, s=20, color='purple') - - corr = self.df['current_compact_size'].corr(self.df['delta_percent']) - axes[1, 1].set_xlabel('Current Compact Block Size (bytes)') - axes[1, 1].set_ylabel('Overhead (%)') - axes[1, 1].set_title(f'Overhead % vs Block Size (r={corr:.3f})') + axes[1, 1].scatter( + self.df["current_compact_size"], + self.df["delta_percent"], + alpha=0.5, + s=20, + color="purple", + ) + + corr = self.df["current_compact_size"].corr(self.df["delta_percent"]) + axes[1, 1].set_xlabel("Current Compact Block Size (bytes)") + axes[1, 1].set_ylabel("Overhead (%)") + axes[1, 1].set_title(f"Overhead % vs Block Size (r={corr:.3f})") axes[1, 1].grid(True, alpha=0.3) - + plt.tight_layout() - plt.savefig(filename, dpi=300, bbox_inches='tight') + plt.savefig(filename, dpi=300, bbox_inches="tight") plt.close() print(f" ✓ Correlation chart saved: {filename}") - + def plot_cumulative(self, filename): """Cumulative distribution function""" fig, axes = plt.subplots(1, 2, figsize=(14, 5)) - + # CDF of overhead percentage - sorted_overhead = np.sort(self.df['delta_percent']) + sorted_overhead = np.sort(self.df["delta_percent"]) cumulative = np.arange(1, len(sorted_overhead) + 1) / len(sorted_overhead) - + axes[0].plot(sorted_overhead, cumulative * 100, linewidth=2) - + # Mark percentiles percentiles = [50, 75, 90, 95, 99] for p in percentiles: value = np.percentile(sorted_overhead, p) - axes[0].axvline(value, linestyle='--', alpha=0.5, - label=f'P{p}: {value:.1f}%') - axes[0].axhline(p, linestyle=':', alpha=0.3) - - axes[0].set_xlabel('Overhead (%)') - axes[0].set_ylabel('Cumulative Percentage of Blocks') - axes[0].set_title('Cumulative Distribution of Overhead') + axes[0].axvline( + value, linestyle="--", alpha=0.5, label=f"P{p}: {value:.1f}%" + ) + axes[0].axhline(p, linestyle=":", alpha=0.3) + + axes[0].set_xlabel("Overhead (%)") + axes[0].set_ylabel("Cumulative Percentage of Blocks") + axes[0].set_title("Cumulative Distribution of Overhead") axes[0].legend() axes[0].grid(True, alpha=0.3) - + # CDF of absolute delta - sorted_delta = np.sort(self.df['delta_bytes']) - axes[1].plot(sorted_delta / 1000, cumulative * 100, linewidth=2, color='orange') - + sorted_delta = np.sort(self.df["delta_bytes"]) + axes[1].plot(sorted_delta / 1000, cumulative * 100, linewidth=2, color="orange") + for p in percentiles: value = np.percentile(sorted_delta, p) / 1000 - axes[1].axvline(value, linestyle='--', alpha=0.5, - label=f'P{p}: {value:.1f}KB') - - axes[1].set_xlabel('Delta Size (KB)') - axes[1].set_ylabel('Cumulative Percentage of Blocks') - axes[1].set_title('Cumulative Distribution of Absolute Overhead') + axes[1].axvline( + value, linestyle="--", alpha=0.5, label=f"P{p}: {value:.1f}KB" + ) + + axes[1].set_xlabel("Delta Size (KB)") + axes[1].set_ylabel("Cumulative Percentage of Blocks") + axes[1].set_title("Cumulative Distribution of Absolute Overhead") axes[1].legend() axes[1].grid(True, alpha=0.3) - + plt.tight_layout() - plt.savefig(filename, dpi=300, bbox_inches='tight') + plt.savefig(filename, dpi=300, bbox_inches="tight") plt.close() print(f" ✓ Cumulative distribution chart saved: {filename}") - + def plot_bandwidth_impact(self, filename): """Practical bandwidth impact scenarios""" fig, axes = plt.subplots(2, 2, figsize=(14, 10)) - + # Calculate metrics - avg_current = self.df['current_compact_size'].mean() - avg_with_transparent = self.df['estimated_with_transparent'].mean() + avg_current = self.df["current_compact_size"].mean() + avg_with_transparent = self.df["estimated_with_transparent"].mean() avg_delta = avg_with_transparent - avg_current - + # Calculate blocks per day based on current network (post-Blossom) # Post-Blossom (after block 653,600): 75s blocks = 1,152 blocks/day # This is what matters for current light clients blocks_per_day = 1152 - + daily_current_mb = (avg_current * blocks_per_day) / 1_000_000 daily_with_mb = (avg_with_transparent * blocks_per_day) / 1_000_000 daily_delta_mb = daily_with_mb - daily_current_mb - + # Daily sync with absolute delta - axes[0, 0].bar(['Current', 'With\nTransparent'], - [daily_current_mb, daily_with_mb], - color=['steelblue', 'coral']) - axes[0, 0].set_ylabel('MB') - axes[0, 0].set_title(f'Daily Sync Bandwidth\n(~{blocks_per_day} blocks/day)') - axes[0, 0].grid(True, alpha=0.3, axis='y') - + axes[0, 0].bar( + ["Current", "With\nTransparent"], + [daily_current_mb, daily_with_mb], + color=["steelblue", "coral"], + ) + axes[0, 0].set_ylabel("MB") + axes[0, 0].set_title(f"Daily Sync Bandwidth\n(~{blocks_per_day} blocks/day)") + axes[0, 0].grid(True, alpha=0.3, axis="y") + for i, v in enumerate([daily_current_mb, daily_with_mb]): - axes[0, 0].text(i, v + 1, f'{v:.1f} MB', - ha='center', va='bottom', fontweight='bold') - + axes[0, 0].text( + i, v + 1, f"{v:.1f} MB", ha="center", va="bottom", fontweight="bold" + ) + # Add delta annotation - axes[0, 0].text(0.5, max(daily_current_mb, daily_with_mb) * 0.5, - f'Δ = +{daily_delta_mb:.1f} MB\n({(daily_delta_mb/daily_current_mb)*100:.1f}%)', - ha='center', fontsize=12, fontweight='bold', - bbox=dict(boxstyle='round', facecolor='yellow', alpha=0.3)) - + axes[0, 0].text( + 0.5, + max(daily_current_mb, daily_with_mb) * 0.5, + f"Δ = +{daily_delta_mb:.1f} MB\n({(daily_delta_mb/daily_current_mb)*100:.1f}%)", + ha="center", + fontsize=12, + fontweight="bold", + bbox=dict(boxstyle="round", facecolor="yellow", alpha=0.3), + ) + # Full sync (estimate based on current tip) - max_height = self.df['height'].max() + max_height = self.df["height"].max() total_blocks = max_height # Approximate total blocks full_current_gb = (avg_current * total_blocks) / 1_000_000_000 full_with_gb = (avg_with_transparent * total_blocks) / 1_000_000_000 full_delta_gb = full_with_gb - full_current_gb - - axes[0, 1].bar(['Current', 'With\nTransparent'], - [full_current_gb, full_with_gb], - color=['steelblue', 'coral']) - axes[0, 1].set_ylabel('GB') - axes[0, 1].set_title(f'Full Chain Sync\n(~{total_blocks:,} blocks)') - axes[0, 1].grid(True, alpha=0.3, axis='y') - + + axes[0, 1].bar( + ["Current", "With\nTransparent"], + [full_current_gb, full_with_gb], + color=["steelblue", "coral"], + ) + axes[0, 1].set_ylabel("GB") + axes[0, 1].set_title(f"Full Chain Sync\n(~{total_blocks:,} blocks)") + axes[0, 1].grid(True, alpha=0.3, axis="y") + for i, v in enumerate([full_current_gb, full_with_gb]): - axes[0, 1].text(i, v + 0.1, f'{v:.2f} GB', - ha='center', va='bottom', fontweight='bold') - + axes[0, 1].text( + i, v + 0.1, f"{v:.2f} GB", ha="center", va="bottom", fontweight="bold" + ) + # Add delta annotation - axes[0, 1].text(0.5, max(full_current_gb, full_with_gb) * 0.5, - f'Δ = +{full_delta_gb:.2f} GB\n({(full_delta_gb/full_current_gb)*100:.1f}%)', - ha='center', fontsize=12, fontweight='bold', - bbox=dict(boxstyle='round', facecolor='yellow', alpha=0.3)) - + axes[0, 1].text( + 0.5, + max(full_current_gb, full_with_gb) * 0.5, + f"Δ = +{full_delta_gb:.2f} GB\n({(full_delta_gb/full_current_gb)*100:.1f}%)", + ha="center", + fontsize=12, + fontweight="bold", + bbox=dict(boxstyle="round", facecolor="yellow", alpha=0.3), + ) + # Absolute delta chart - use MB consistently x = np.arange(3) width = 0.35 - + # Calculate for different time periods (all in MB) daily_delta_mb = daily_delta_mb weekly_delta_mb = daily_delta_mb * 7 monthly_delta_mb = daily_delta_mb * 30 - + deltas = [daily_delta_mb, weekly_delta_mb, monthly_delta_mb] - labels = [f'Daily\n({blocks_per_day} blocks)', 'Weekly\n(7 days)', 'Monthly\n(30 days)'] - - bars = axes[1, 0].bar(x, deltas, color='coral', alpha=0.7) - axes[1, 0].set_ylabel('Additional Bandwidth (MB)') - axes[1, 0].set_title('Absolute Bandwidth Increase\n(Transparent Data Overhead)') + labels = [ + f"Daily\n({blocks_per_day} blocks)", + "Weekly\n(7 days)", + "Monthly\n(30 days)", + ] + + bars = axes[1, 0].bar(x, deltas, color="coral", alpha=0.7) + axes[1, 0].set_ylabel("Additional Bandwidth (MB)") + axes[1, 0].set_title("Absolute Bandwidth Increase\n(Transparent Data Overhead)") axes[1, 0].set_xticks(x) axes[1, 0].set_xticklabels(labels) - axes[1, 0].grid(True, alpha=0.3, axis='y') - + axes[1, 0].grid(True, alpha=0.3, axis="y") + # Add value labels for i, (bar, val) in enumerate(zip(bars, deltas)): height = bar.get_height() - axes[1, 0].text(bar.get_x() + bar.get_width()/2., height, - f'+{val:.2f} MB', - ha='center', va='bottom', fontweight='bold') - + axes[1, 0].text( + bar.get_x() + bar.get_width() / 2.0, + height, + f"+{val:.2f} MB", + ha="center", + va="bottom", + fontweight="bold", + ) + # Sync time (assume 5 Mbps connection) bandwidth_mbps = 5 bandwidth_mb_per_sec = bandwidth_mbps / 8 - + daily_time_current = daily_current_mb / bandwidth_mb_per_sec / 60 # minutes daily_time_with = daily_with_mb / bandwidth_mb_per_sec / 60 daily_time_delta = daily_time_with - daily_time_current - - full_time_current = full_current_gb * 1000 / bandwidth_mb_per_sec / 3600 # hours + + full_time_current = ( + full_current_gb * 1000 / bandwidth_mb_per_sec / 3600 + ) # hours full_time_with = full_with_gb * 1000 / bandwidth_mb_per_sec / 3600 full_time_delta = full_time_with - full_time_current - + x = np.arange(2) - axes[1, 1].bar(x - width/2, [daily_time_current, full_time_current], - width, label='Current', color='steelblue') - axes[1, 1].bar(x + width/2, [daily_time_with, full_time_with], - width, label='With Transparent', color='coral') - - axes[1, 1].set_ylabel('Time') - axes[1, 1].set_title(f'Sync Time\n(@{bandwidth_mbps} Mbps)') + axes[1, 1].bar( + x - width / 2, + [daily_time_current, full_time_current], + width, + label="Current", + color="steelblue", + ) + axes[1, 1].bar( + x + width / 2, + [daily_time_with, full_time_with], + width, + label="With Transparent", + color="coral", + ) + + axes[1, 1].set_ylabel("Time") + axes[1, 1].set_title(f"Sync Time\n(@{bandwidth_mbps} Mbps)") axes[1, 1].set_xticks(x) - axes[1, 1].set_xticklabels(['Daily\n(minutes)', 'Full\n(hours)']) + axes[1, 1].set_xticklabels(["Daily\n(minutes)", "Full\n(hours)"]) axes[1, 1].legend() - axes[1, 1].grid(True, alpha=0.3, axis='y') - + axes[1, 1].grid(True, alpha=0.3, axis="y") + # Add delta annotations for i, delta in enumerate([daily_time_delta, full_time_delta]): - y_pos = max([daily_time_current, full_time_current][i], - [daily_time_with, full_time_with][i]) * 1.05 - unit = 'min' if i == 0 else 'hrs' - axes[1, 1].text(i, y_pos, f'+{delta:.1f} {unit}', - ha='center', fontsize=10, fontweight='bold', - bbox=dict(boxstyle='round', facecolor='yellow', alpha=0.3)) - + y_pos = ( + max( + [daily_time_current, full_time_current][i], + [daily_time_with, full_time_with][i], + ) + * 1.05 + ) + unit = "min" if i == 0 else "hrs" + axes[1, 1].text( + i, + y_pos, + f"+{delta:.1f} {unit}", + ha="center", + fontsize=10, + fontweight="bold", + bbox=dict(boxstyle="round", facecolor="yellow", alpha=0.3), + ) + plt.tight_layout() - plt.savefig(filename, dpi=300, bbox_inches='tight') + plt.savefig(filename, dpi=300, bbox_inches="tight") plt.close() print(f" ✓ Bandwidth impact chart saved: {filename}") - + def plot_heatmap(self, filename): """Heatmap of overhead by era and transaction characteristics""" fig, axes = plt.subplots(1, 2, figsize=(14, 5)) - + # Create bins for transaction count - self.df['tx_bin'] = pd.cut(self.df['tx_count'], - bins=[0, 10, 50, 100, 500, 10000], - labels=['1-10', '11-50', '51-100', '101-500', '500+']) - + self.df["tx_bin"] = pd.cut( + self.df["tx_count"], + bins=[0, 10, 50, 100, 500, 10000], + labels=["1-10", "11-50", "51-100", "101-500", "500+"], + ) + # Pivot table: era vs tx_bin - if 'era' in self.df.columns and not self.df['era'].isna().all(): + if "era" in self.df.columns and not self.df["era"].isna().all(): pivot = self.df.pivot_table( - values='delta_percent', - index='era', - columns='tx_bin', - aggfunc='mean' + values="delta_percent", index="era", columns="tx_bin", aggfunc="mean" + ) + + sns.heatmap( + pivot, + annot=True, + fmt=".1f", + cmap="YlOrRd", + ax=axes[0], + cbar_kws={"label": "Overhead (%)"}, ) - - sns.heatmap(pivot, annot=True, fmt='.1f', cmap='YlOrRd', - ax=axes[0], cbar_kws={'label': 'Overhead (%)'}) - axes[0].set_title('Average Overhead by Era and Transaction Count') - axes[0].set_ylabel('Era') - axes[0].set_xlabel('Transactions per Block') - + axes[0].set_title("Average Overhead by Era and Transaction Count") + axes[0].set_ylabel("Era") + axes[0].set_xlabel("Transactions per Block") + # Pivot table: transparent usage - self.df['transparent_bin'] = pd.cut( - self.df['transparent_inputs'] + self.df['transparent_outputs'], + self.df["transparent_bin"] = pd.cut( + self.df["transparent_inputs"] + self.df["transparent_outputs"], bins=[0, 10, 50, 100, 500, 10000], - labels=['1-10', '11-50', '51-100', '101-500', '500+'] + labels=["1-10", "11-50", "51-100", "101-500", "500+"], ) - - if 'era' in self.df.columns and not self.df['era'].isna().all(): + + if "era" in self.df.columns and not self.df["era"].isna().all(): pivot2 = self.df.pivot_table( - values='delta_percent', - index='era', - columns='transparent_bin', - aggfunc='mean' + values="delta_percent", + index="era", + columns="transparent_bin", + aggfunc="mean", ) - - sns.heatmap(pivot2, annot=True, fmt='.1f', cmap='YlOrRd', - ax=axes[1], cbar_kws={'label': 'Overhead (%)'}) - axes[1].set_title('Average Overhead by Era and Transparent I/O') - axes[1].set_ylabel('Era') - axes[1].set_xlabel('Transparent Inputs + Outputs') - + + sns.heatmap( + pivot2, + annot=True, + fmt=".1f", + cmap="YlOrRd", + ax=axes[1], + cbar_kws={"label": "Overhead (%)"}, + ) + axes[1].set_title("Average Overhead by Era and Transparent I/O") + axes[1].set_ylabel("Era") + axes[1].set_xlabel("Transparent Inputs + Outputs") + plt.tight_layout() - plt.savefig(filename, dpi=300, bbox_inches='tight') + plt.savefig(filename, dpi=300, bbox_inches="tight") plt.close() print(f" ✓ Heatmap saved: {filename}") - + def generate_report(self, filename): """Generate statistical report""" - with open(filename, 'w') as f: + with open(filename, "w") as f: f.write("=" * 80 + "\n") f.write("STATISTICAL ANALYSIS REPORT\n") f.write("Zcash Compact Block Transparent Data Overhead\n") f.write("=" * 80 + "\n\n") - + # Summary statistics f.write("SUMMARY STATISTICS\n") f.write("-" * 80 + "\n") f.write(f"Total blocks analyzed: {len(self.df):,}\n") - f.write(f"Block height range: {self.df['height'].min():,} - {self.df['height'].max():,}\n\n") - + f.write( + f"Block height range: {self.df['height'].min():,} - {self.df['height'].max():,}\n\n" + ) + # Overhead statistics f.write("OVERHEAD PERCENTAGE\n") f.write(f" Mean: {self.df['delta_percent'].mean():>8.2f}%\n") @@ -573,79 +758,85 @@ def generate_report(self, filename): f.write(f" Std Dev:{self.df['delta_percent'].std():>8.2f}%\n") f.write(f" Min: {self.df['delta_percent'].min():>8.2f}%\n") f.write(f" Max: {self.df['delta_percent'].max():>8.2f}%\n\n") - + # Percentiles f.write("PERCENTILES\n") for p in [25, 50, 75, 90, 95, 99]: - value = np.percentile(self.df['delta_percent'], p) + value = np.percentile(self.df["delta_percent"], p) f.write(f" P{p:>2}: {value:>8.2f}%\n") f.write("\n") - + # Confidence intervals f.write("CONFIDENCE INTERVALS (95%)\n") - mean = self.df['delta_percent'].mean() - std_err = stats.sem(self.df['delta_percent']) - ci = stats.t.interval(0.95, len(self.df)-1, loc=mean, scale=std_err) + mean = self.df["delta_percent"].mean() + std_err = stats.sem(self.df["delta_percent"]) + ci = stats.t.interval(0.95, len(self.df) - 1, loc=mean, scale=std_err) f.write(f" Mean overhead: {mean:.2f}% ± {(ci[1]-mean):.2f}%\n") f.write(f" Range: [{ci[0]:.2f}%, {ci[1]:.2f}%]\n\n") - + # By era f.write("STATISTICS BY ERA\n") f.write("-" * 80 + "\n") - if 'era' in self.df.columns: - era_stats = self.df.groupby('era').agg({ - 'delta_percent': ['count', 'mean', 'std', 'median', 'min', 'max'] - }) + if "era" in self.df.columns: + era_stats = self.df.groupby("era").agg( + {"delta_percent": ["count", "mean", "std", "median", "min", "max"]} + ) f.write(era_stats.to_string()) f.write("\n\n") - + # Bandwidth impact f.write("PRACTICAL BANDWIDTH IMPACT\n") f.write("-" * 80 + "\n") - - avg_current = self.df['current_compact_size'].mean() - avg_with = self.df['estimated_with_transparent'].mean() + + avg_current = self.df["current_compact_size"].mean() + avg_with = self.df["estimated_with_transparent"].mean() avg_delta = avg_with - avg_current - + blocks_per_day = 2880 daily_current_mb = (avg_current * blocks_per_day) / 1_000_000 daily_with_mb = (avg_with * blocks_per_day) / 1_000_000 daily_delta_mb = daily_with_mb - daily_current_mb - + f.write(f"Average block sizes:\n") f.write(f" Current: {avg_current/1000:>10.2f} KB\n") f.write(f" With transparent:{avg_with/1000:>10.2f} KB\n") f.write(f" Delta: {avg_delta/1000:>10.2f} KB\n\n") - + f.write(f"Daily sync (~{blocks_per_day} blocks):\n") f.write(f" Current: {daily_current_mb:>10.2f} MB\n") f.write(f" With transparent:{daily_with_mb:>10.2f} MB\n") - f.write(f" Additional: {daily_delta_mb:>10.2f} MB ({(daily_delta_mb/daily_current_mb)*100:.1f}%)\n\n") - + f.write( + f" Additional: {daily_delta_mb:>10.2f} MB ({(daily_delta_mb/daily_current_mb)*100:.1f}%)\n\n" + ) + # Correlations f.write("CORRELATIONS\n") f.write("-" * 80 + "\n") - corr_inputs = self.df['transparent_inputs'].corr(self.df['delta_bytes']) - corr_outputs = self.df['transparent_outputs'].corr(self.df['delta_bytes']) - corr_tx = self.df['tx_count'].corr(self.df['delta_percent']) - + corr_inputs = self.df["transparent_inputs"].corr(self.df["delta_bytes"]) + corr_outputs = self.df["transparent_outputs"].corr(self.df["delta_bytes"]) + corr_tx = self.df["tx_count"].corr(self.df["delta_percent"]) + f.write(f" Transparent inputs vs delta: r = {corr_inputs:>6.3f}\n") f.write(f" Transparent outputs vs delta: r = {corr_outputs:>6.3f}\n") f.write(f" Transaction count vs %%: r = {corr_tx:>6.3f}\n\n") - + # Recommendations f.write("DECISION FRAMEWORK\n") f.write("-" * 80 + "\n") - median_overhead = self.df['delta_percent'].median() - p95_overhead = np.percentile(self.df['delta_percent'], 95) - + median_overhead = self.df["delta_percent"].median() + p95_overhead = np.percentile(self.df["delta_percent"], 95) + f.write(f"Median overhead: {median_overhead:.1f}%\n") f.write(f"95th percentile: {p95_overhead:.1f}%\n\n") - + if median_overhead < 20: f.write("RECOMMENDATION: LOW IMPACT\n") - f.write(" The overhead is relatively small (<20%). Consider making transparent\n") - f.write(" data part of the default GetBlockRange method. This would:\n") + f.write( + " The overhead is relatively small (<20%). Consider making transparent\n" + ) + f.write( + " data part of the default GetBlockRange method. This would:\n" + ) f.write(" - Simplify the API (single method)\n") f.write(" - Provide feature parity with full nodes\n") f.write(" - Have minimal bandwidth impact on users\n") @@ -663,45 +854,49 @@ def generate_report(self, filename): f.write(" - Clear opt-in for clients needing transparent data\n") f.write(" - Critical for mobile and bandwidth-limited users\n") f.write(" - May significantly impact sync times\n") - + f.write("\n") f.write("=" * 80 + "\n") f.write("End of Report\n") f.write("=" * 80 + "\n") - + print(f" ✓ Statistical report saved: {filename}") def main(): parser = argparse.ArgumentParser( - description='Generate visualizations and statistical analysis for compact block data' + description="Generate visualizations and statistical analysis for compact block data" + ) + parser.add_argument("csv_file", help="Path to CSV file with analysis results") + parser.add_argument( + "--output-dir", + "-o", + default="./charts", + help="Output directory for charts (default: ./charts)", ) - parser.add_argument('csv_file', help='Path to CSV file with analysis results') - parser.add_argument('--output-dir', '-o', default='./charts', - help='Output directory for charts (default: ./charts)') - + args = parser.parse_args() - + # Check if file exists if not Path(args.csv_file).exists(): print(f"Error: File not found: {args.csv_file}") return 1 - + print(f"Loading data from: {args.csv_file}") analyzer = CompactBlockAnalyzer(args.csv_file) - + print(f"Loaded {len(analyzer.df)} blocks") print() - + # Generate all visualizations analyzer.generate_all_charts(args.output_dir) - + print("\n✅ Analysis complete!") print(f"\nView the statistical report: {args.output_dir}/statistical_report.txt") print(f"View charts in: {args.output_dir}/") - + return 0 -if __name__ == '__main__': +if __name__ == "__main__": exit(main()) From ea3f4d14f288275458f0cbc3e04f5396b545cb4b Mon Sep 17 00:00:00 2001 From: Pacu Date: Thu, 9 Oct 2025 19:04:41 -0300 Subject: [PATCH 08/17] Fix hallucinations over network upgrade heights --- analyzer/src/sampling.rs | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/analyzer/src/sampling.rs b/analyzer/src/sampling.rs index feeec7c..decb047 100644 --- a/analyzer/src/sampling.rs +++ b/analyzer/src/sampling.rs @@ -23,11 +23,11 @@ impl Era { Era { name: "blossom".to_string(), start: 653_600, - end: 903_799, + end: 902_999, }, Era { name: "heartwood".to_string(), - start: 903_800, + start: 903_000, end: 1_046_399, }, Era { From 70f78afc837cb76b3d101deb885bc2f533d67a18 Mon Sep 17 00:00:00 2001 From: Pacu Date: Thu, 9 Oct 2025 19:57:07 -0300 Subject: [PATCH 09/17] Implement `Complete` strategy --- analyzer/src/main.rs | 18 ++++++++++++++++++ 1 file changed, 18 insertions(+) diff --git a/analyzer/src/main.rs b/analyzer/src/main.rs index 3585b7f..4e8dab8 100644 --- a/analyzer/src/main.rs +++ b/analyzer/src/main.rs @@ -133,6 +133,7 @@ impl TransparentEstimator { height: height as u64, hash: vec![], }), + pool_types: vec![], // Empty means all pools (default behavior) }); // Get the block stream (will have just one block) @@ -447,6 +448,7 @@ async fn main() -> Result<()> { eprintln!(" equal - Equal samples per era (~4000 blocks)"); eprintln!(" proportional - Proportional to era size (~5000 blocks)"); eprintln!(" weighted - Weighted toward recent (~5000 blocks)"); + eprintln!(" complete - Analyze every block in range (no sampling)"); eprintln!(); eprintln!("Examples:"); eprintln!( @@ -457,6 +459,10 @@ async fn main() -> Result<()> { " {} http://127.0.0.1:9067 http://127.0.0.1:8232 recommended results.csv", args[0] ); + eprintln!( + " {} http://127.0.0.1:9067 http://127.0.0.1:8232 complete 2800000 2800100", + args[0] + ); std::process::exit(1); } @@ -483,6 +489,18 @@ async fn main() -> Result<()> { let output = args.get(6).map(|s| s.as_str()).unwrap_or("results.csv"); ((start..=end).collect(), output.to_string()) } + "complete" => { + if args.len() < 6 { + eprintln!("Error: complete mode requires "); + std::process::exit(1); + } + let start: u64 = args[4].parse()?; + let end: u64 = args[5].parse()?; + let output = args.get(6).map(|s| s.as_str()).unwrap_or("complete.csv"); + println!("Complete analysis: every block from {} to {}", start, end); + println!("Total blocks: {}", end - start + 1); + ((start..=end).collect(), output.to_string()) + } "quick" => { let sampler = create_quick_sampler(current_tip); println!("{}", sampler.describe()); From 3c99adae6cac9c0d33939b390638d6c9341508d6 Mon Sep 17 00:00:00 2001 From: Pacu Date: Thu, 9 Oct 2025 19:58:25 -0300 Subject: [PATCH 10/17] Implement `FixedDensity` strategy --- analyzer/src/main.rs | 5 +++++ 1 file changed, 5 insertions(+) diff --git a/analyzer/src/main.rs b/analyzer/src/main.rs index 4e8dab8..f1a43fb 100644 --- a/analyzer/src/main.rs +++ b/analyzer/src/main.rs @@ -448,6 +448,7 @@ async fn main() -> Result<()> { eprintln!(" equal - Equal samples per era (~4000 blocks)"); eprintln!(" proportional - Proportional to era size (~5000 blocks)"); eprintln!(" weighted - Weighted toward recent (~5000 blocks)"); + eprintln!(" density - Every Nth block across all eras"); eprintln!(" complete - Analyze every block in range (no sampling)"); eprintln!(); eprintln!("Examples:"); @@ -459,6 +460,10 @@ async fn main() -> Result<()> { " {} http://127.0.0.1:9067 http://127.0.0.1:8232 recommended results.csv", args[0] ); + eprintln!( + " {} http://127.0.0.1:9067 http://127.0.0.1:8232 density 1000 density.csv", + args[0] + ); eprintln!( " {} http://127.0.0.1:9067 http://127.0.0.1:8232 complete 2800000 2800100", args[0] From b051baad059b5d31ad1ea0b4cfc99d5defb35f55 Mon Sep 17 00:00:00 2001 From: Pacu Date: Thu, 9 Oct 2025 20:02:16 -0300 Subject: [PATCH 11/17] fix hallucination bug --- analyzer/src/main.rs | 192 ++++++++++++++++--------------------------- 1 file changed, 71 insertions(+), 121 deletions(-) diff --git a/analyzer/src/main.rs b/analyzer/src/main.rs index f1a43fb..626f728 100644 --- a/analyzer/src/main.rs +++ b/analyzer/src/main.rs @@ -17,7 +17,9 @@ pub mod cash { } use cash::z::wallet::sdk::rpc::{ - compact_tx_streamer_client::CompactTxStreamerClient, BlockId, BlockRange, + compact_tx_streamer_client::CompactTxStreamerClient, + BlockId, + BlockRange, }; // Import sampling module @@ -112,33 +114,32 @@ impl TransparentEstimator { .json() .await?; - let tip = response["result"] - .as_u64() + let tip = response["result"].as_u64() .ok_or_else(|| anyhow::anyhow!("Failed to get block count"))?; - + Ok(tip) } async fn get_compact_block_from_lightwalletd(&self, height: u64) -> Result> { // Connect to lightwalletd gRPC service let mut client = CompactTxStreamerClient::connect(self.lightwalletd_url.clone()).await?; - + // Request a single block by creating a range with start=end=height let request = tonic::Request::new(BlockRange { - start: Some(BlockId { - height: height as u64, - hash: vec![], + start: Some(BlockId { + height: height as u64, + hash: vec![] }), - end: Some(BlockId { - height: height as u64, - hash: vec![], + end: Some(BlockId { + height: height as u64, + hash: vec![] }), pool_types: vec![], // Empty means all pools (default behavior) }); - + // Get the block stream (will have just one block) let mut stream = client.get_block_range(request).await?.into_inner(); - + // Get the single block from the stream if let Some(compact_block) = stream.message().await? { // Encode the CompactBlock to bytes to measure its actual size @@ -147,7 +148,7 @@ impl TransparentEstimator { compact_block.encode(&mut buf)?; return Ok(buf); } - + anyhow::bail!("Block {} not found in lightwalletd", height) } @@ -204,28 +205,27 @@ impl TransparentEstimator { for vin in &tx.vin { if let (Some(_txid), Some(vout_idx)) = (&vin.txid, &vin.vout) { // Regular transparent input (not a coinbase) - + // OutPoint message size: let mut outpoint_size = 0; - + // Field 1: bytes txid = 32 bytes // Tag (1 byte) + length varint (1 byte) + 32 bytes outpoint_size += 1 + 1 + 32; - + // Field 2: uint32 index (varint) // Tag (1 byte) + varint value (1-5 bytes, typically 1-2) outpoint_size += 1 + Self::varint_size(*vout_idx as usize); - + // CompactTxIn wraps OutPoint as field 1 let mut compact_txin_size = 0; // Tag for field 1 (1 byte) + length of OutPoint + OutPoint data compact_txin_size += 1 + Self::varint_size(outpoint_size) + outpoint_size; - + // This CompactTxIn is in a repeated field (vin = 7) in CompactTx // Tag for repeated field (1 byte) + length + message - let vin_entry_size = - 1 + Self::varint_size(compact_txin_size) + compact_txin_size; - + let vin_entry_size = 1 + Self::varint_size(compact_txin_size) + compact_txin_size; + total_overhead += vin_entry_size; input_count += 1; } else { @@ -240,7 +240,7 @@ impl TransparentEstimator { // - Sequence value: 4 bytes // - Repeated field overhead: 1 byte tag + 1 byte length // Total: ~79 bytes - + const COINBASE_COMPACT_TXIN_SIZE: usize = 79; total_overhead += COINBASE_COMPACT_TXIN_SIZE; input_count += 1; @@ -250,19 +250,19 @@ impl TransparentEstimator { // Estimate TxOut (repeated field in CompactTx) for vout in &tx.vout { let mut txout_size = 0; - + // Field 1: uint32 value (varint) let value_zatoshis = (vout.value * 100_000_000.0) as u64; txout_size += 1 + Self::varint_size(value_zatoshis as usize); - + // Field 2: bytes scriptPubKey let script_len = vout.script_pubkey.hex.len() / 2; // hex to bytes txout_size += 1 + Self::varint_size(script_len) + script_len; - + // This TxOut is in a repeated field (vout = 8) in CompactTx // Tag for repeated field (1 byte) + length + message let vout_entry_size = 1 + Self::varint_size(txout_size) + txout_size; - + total_overhead += vout_entry_size; output_count += 1; } @@ -289,7 +289,7 @@ impl TransparentEstimator { // Get full block from Zebra to calculate transparent overhead let full_block = self.get_full_block_from_zebra(height).await?; - let (transparent_overhead, input_count, output_count) = + let (transparent_overhead, input_count, output_count) = self.estimate_transparent_overhead(&full_block); let estimated_size = current_size + transparent_overhead; @@ -320,12 +320,7 @@ impl TransparentEstimator { for (i, &height) in heights.iter().enumerate() { if i % 10 == 0 { - println!( - "Progress: {}/{} ({:.1}%)", - i, - total, - (i as f64 / total as f64) * 100.0 - ); + println!("Progress: {}/{} ({:.1}%)", i, total, (i as f64 / total as f64) * 100.0); } match self.analyze_block(height).await { @@ -382,63 +377,34 @@ impl TransparentEstimator { println!("\n=== ANALYSIS SUMMARY ==="); println!("Blocks analyzed: {}", results.len()); println!("\nCurrent compact blocks:"); - println!( - " Total: {} bytes ({:.2} MB)", - total_current, - total_current as f64 / 1_000_000.0 - ); + println!(" Total: {} bytes ({:.2} MB)", total_current, total_current as f64 / 1_000_000.0); println!("\nWith transparent data:"); - println!( - " Estimated total: {} bytes ({:.2} MB)", - total_estimated, - total_estimated as f64 / 1_000_000.0 - ); - println!( - " Delta: +{} bytes ({:.2} MB)", - total_delta, - total_delta as f64 / 1_000_000.0 - ); - println!( - " Overall increase: {:.2}%", - (total_delta as f64 / total_current as f64) * 100.0 - ); + println!(" Estimated total: {} bytes ({:.2} MB)", total_estimated, total_estimated as f64 / 1_000_000.0); + println!(" Delta: +{} bytes ({:.2} MB)", total_delta, total_delta as f64 / 1_000_000.0); + println!(" Overall increase: {:.2}%", (total_delta as f64 / total_current as f64) * 100.0); println!("\nPer-block statistics:"); println!(" Median increase: {:.2}%", median); println!(" 95th percentile: {:.2}%", p95); println!(" Min: {:.2}%", deltas[0]); println!(" Max: {:.2}%", deltas[deltas.len() - 1]); - + // Practical impact examples println!("\nPractical impact:"); let blocks_per_day = 1152; // Post-Blossom (75s blocks) let daily_current = (total_current as f64 / results.len() as f64) * blocks_per_day as f64; - let daily_estimated = - (total_estimated as f64 / results.len() as f64) * blocks_per_day as f64; - println!( - " Current daily sync (~{} blocks): {:.2} MB", - blocks_per_day, - daily_current / 1_000_000.0 - ); - println!( - " With transparent: {:.2} MB", - daily_estimated / 1_000_000.0 - ); - println!( - " Additional bandwidth per day: {:.2} MB", - (daily_estimated - daily_current) / 1_000_000.0 - ); + let daily_estimated = (total_estimated as f64 / results.len() as f64) * blocks_per_day as f64; + println!(" Current daily sync (~{} blocks): {:.2} MB", blocks_per_day, daily_current / 1_000_000.0); + println!(" With transparent: {:.2} MB", daily_estimated / 1_000_000.0); + println!(" Additional bandwidth per day: {:.2} MB", (daily_estimated - daily_current) / 1_000_000.0); } } #[tokio::main] async fn main() -> Result<()> { let args: Vec = std::env::args().collect(); - + if args.len() < 4 { - eprintln!( - "Usage: {} [output.csv]", - args[0] - ); + eprintln!("Usage: {} [output.csv]", args[0]); eprintln!(); eprintln!("Modes:"); eprintln!(" range - Analyze specific block range"); @@ -452,22 +418,10 @@ async fn main() -> Result<()> { eprintln!(" complete - Analyze every block in range (no sampling)"); eprintln!(); eprintln!("Examples:"); - eprintln!( - " {} http://127.0.0.1:9067 http://127.0.0.1:8232 range 2400000 2401000", - args[0] - ); - eprintln!( - " {} http://127.0.0.1:9067 http://127.0.0.1:8232 recommended results.csv", - args[0] - ); - eprintln!( - " {} http://127.0.0.1:9067 http://127.0.0.1:8232 density 1000 density.csv", - args[0] - ); - eprintln!( - " {} http://127.0.0.1:9067 http://127.0.0.1:8232 complete 2800000 2800100", - args[0] - ); + eprintln!(" {} http://127.0.0.1:9067 http://127.0.0.1:8232 range 2400000 2401000", args[0]); + eprintln!(" {} http://127.0.0.1:9067 http://127.0.0.1:8232 recommended results.csv", args[0]); + eprintln!(" {} http://127.0.0.1:9067 http://127.0.0.1:8232 density 1000 density.csv", args[0]); + eprintln!(" {} http://127.0.0.1:9067 http://127.0.0.1:8232 complete 2800000 2800100", args[0]); std::process::exit(1); } @@ -476,9 +430,11 @@ async fn main() -> Result<()> { let mode = &args[3]; // Get current tip from Zebra - let estimator = - TransparentEstimator::new(zebra_rpc_url.to_string(), lightwalletd_url.to_string()); - + let estimator = TransparentEstimator::new( + zebra_rpc_url.to_string(), + lightwalletd_url.to_string(), + ); + let current_tip = estimator.get_current_tip().await?; println!("Current blockchain tip: {}", current_tip); println!(); @@ -506,58 +462,55 @@ async fn main() -> Result<()> { println!("Total blocks: {}", end - start + 1); ((start..=end).collect(), output.to_string()) } + "density" => { + if args.len() < 5 { + eprintln!("Error: density mode requires "); + std::process::exit(1); + } + let every_n: u64 = args[4].parse()?; + let output = args.get(5).map(|s| s.as_str()).unwrap_or("density_sample.csv"); + let sampler = Sampler::new( + SamplingStrategy::FixedDensity { every_n }, + current_tip, + Some(42), + ); + println!("{}", sampler.describe()); + (sampler.generate_samples(), output.to_string()) + } "quick" => { let sampler = create_quick_sampler(current_tip); println!("{}", sampler.describe()); - let output = args - .get(4) - .map(|s| s.as_str()) - .unwrap_or("quick_sample.csv"); + let output = args.get(4).map(|s| s.as_str()).unwrap_or("quick_sample.csv"); (sampler.generate_samples(), output.to_string()) } "recommended" => { let sampler = create_recommended_sampler(current_tip); println!("{}", sampler.describe()); - let output = args - .get(4) - .map(|s| s.as_str()) - .unwrap_or("recommended_sample.csv"); + let output = args.get(4).map(|s| s.as_str()).unwrap_or("recommended_sample.csv"); (sampler.generate_samples(), output.to_string()) } "thorough" => { let sampler = create_thorough_sampler(current_tip); println!("{}", sampler.describe()); - let output = args - .get(4) - .map(|s| s.as_str()) - .unwrap_or("thorough_sample.csv"); + let output = args.get(4).map(|s| s.as_str()).unwrap_or("thorough_sample.csv"); (sampler.generate_samples(), output.to_string()) } "equal" => { let sampler = create_equal_sampler(current_tip); println!("{}", sampler.describe()); - let output = args - .get(4) - .map(|s| s.as_str()) - .unwrap_or("equal_sample.csv"); + let output = args.get(4).map(|s| s.as_str()).unwrap_or("equal_sample.csv"); (sampler.generate_samples(), output.to_string()) } "proportional" => { let sampler = create_proportional_sampler(current_tip); println!("{}", sampler.describe()); - let output = args - .get(4) - .map(|s| s.as_str()) - .unwrap_or("proportional_sample.csv"); + let output = args.get(4).map(|s| s.as_str()).unwrap_or("proportional_sample.csv"); (sampler.generate_samples(), output.to_string()) } "weighted" => { let sampler = create_weighted_sampler(current_tip); println!("{}", sampler.describe()); - let output = args - .get(4) - .map(|s| s.as_str()) - .unwrap_or("weighted_sample.csv"); + let output = args.get(4).map(|s| s.as_str()).unwrap_or("weighted_sample.csv"); (sampler.generate_samples(), output.to_string()) } _ => { @@ -567,10 +520,7 @@ async fn main() -> Result<()> { }; println!("Analyzing {} blocks...", blocks.len()); - println!( - "Fetching real compact blocks from lightwalletd: {}", - lightwalletd_url - ); + println!("Fetching real compact blocks from lightwalletd: {}", lightwalletd_url); println!("Fetching full blocks from Zebra: {}", zebra_rpc_url); println!(); From 361808a08fd23e3af175fe5b8378955e23c71097 Mon Sep 17 00:00:00 2001 From: Pacu Date: Thu, 9 Oct 2025 20:02:44 -0300 Subject: [PATCH 12/17] cargo fmt --- analyzer/src/main.rs | 182 +++++++++++++++++++++++++++++-------------- 1 file changed, 125 insertions(+), 57 deletions(-) diff --git a/analyzer/src/main.rs b/analyzer/src/main.rs index 626f728..738ca99 100644 --- a/analyzer/src/main.rs +++ b/analyzer/src/main.rs @@ -17,9 +17,7 @@ pub mod cash { } use cash::z::wallet::sdk::rpc::{ - compact_tx_streamer_client::CompactTxStreamerClient, - BlockId, - BlockRange, + compact_tx_streamer_client::CompactTxStreamerClient, BlockId, BlockRange, }; // Import sampling module @@ -114,32 +112,33 @@ impl TransparentEstimator { .json() .await?; - let tip = response["result"].as_u64() + let tip = response["result"] + .as_u64() .ok_or_else(|| anyhow::anyhow!("Failed to get block count"))?; - + Ok(tip) } async fn get_compact_block_from_lightwalletd(&self, height: u64) -> Result> { // Connect to lightwalletd gRPC service let mut client = CompactTxStreamerClient::connect(self.lightwalletd_url.clone()).await?; - + // Request a single block by creating a range with start=end=height let request = tonic::Request::new(BlockRange { - start: Some(BlockId { - height: height as u64, - hash: vec![] + start: Some(BlockId { + height: height as u64, + hash: vec![], }), - end: Some(BlockId { - height: height as u64, - hash: vec![] + end: Some(BlockId { + height: height as u64, + hash: vec![], }), pool_types: vec![], // Empty means all pools (default behavior) }); - + // Get the block stream (will have just one block) let mut stream = client.get_block_range(request).await?.into_inner(); - + // Get the single block from the stream if let Some(compact_block) = stream.message().await? { // Encode the CompactBlock to bytes to measure its actual size @@ -148,7 +147,7 @@ impl TransparentEstimator { compact_block.encode(&mut buf)?; return Ok(buf); } - + anyhow::bail!("Block {} not found in lightwalletd", height) } @@ -205,27 +204,28 @@ impl TransparentEstimator { for vin in &tx.vin { if let (Some(_txid), Some(vout_idx)) = (&vin.txid, &vin.vout) { // Regular transparent input (not a coinbase) - + // OutPoint message size: let mut outpoint_size = 0; - + // Field 1: bytes txid = 32 bytes // Tag (1 byte) + length varint (1 byte) + 32 bytes outpoint_size += 1 + 1 + 32; - + // Field 2: uint32 index (varint) // Tag (1 byte) + varint value (1-5 bytes, typically 1-2) outpoint_size += 1 + Self::varint_size(*vout_idx as usize); - + // CompactTxIn wraps OutPoint as field 1 let mut compact_txin_size = 0; // Tag for field 1 (1 byte) + length of OutPoint + OutPoint data compact_txin_size += 1 + Self::varint_size(outpoint_size) + outpoint_size; - + // This CompactTxIn is in a repeated field (vin = 7) in CompactTx // Tag for repeated field (1 byte) + length + message - let vin_entry_size = 1 + Self::varint_size(compact_txin_size) + compact_txin_size; - + let vin_entry_size = + 1 + Self::varint_size(compact_txin_size) + compact_txin_size; + total_overhead += vin_entry_size; input_count += 1; } else { @@ -240,7 +240,7 @@ impl TransparentEstimator { // - Sequence value: 4 bytes // - Repeated field overhead: 1 byte tag + 1 byte length // Total: ~79 bytes - + const COINBASE_COMPACT_TXIN_SIZE: usize = 79; total_overhead += COINBASE_COMPACT_TXIN_SIZE; input_count += 1; @@ -250,19 +250,19 @@ impl TransparentEstimator { // Estimate TxOut (repeated field in CompactTx) for vout in &tx.vout { let mut txout_size = 0; - + // Field 1: uint32 value (varint) let value_zatoshis = (vout.value * 100_000_000.0) as u64; txout_size += 1 + Self::varint_size(value_zatoshis as usize); - + // Field 2: bytes scriptPubKey let script_len = vout.script_pubkey.hex.len() / 2; // hex to bytes txout_size += 1 + Self::varint_size(script_len) + script_len; - + // This TxOut is in a repeated field (vout = 8) in CompactTx // Tag for repeated field (1 byte) + length + message let vout_entry_size = 1 + Self::varint_size(txout_size) + txout_size; - + total_overhead += vout_entry_size; output_count += 1; } @@ -289,7 +289,7 @@ impl TransparentEstimator { // Get full block from Zebra to calculate transparent overhead let full_block = self.get_full_block_from_zebra(height).await?; - let (transparent_overhead, input_count, output_count) = + let (transparent_overhead, input_count, output_count) = self.estimate_transparent_overhead(&full_block); let estimated_size = current_size + transparent_overhead; @@ -320,7 +320,12 @@ impl TransparentEstimator { for (i, &height) in heights.iter().enumerate() { if i % 10 == 0 { - println!("Progress: {}/{} ({:.1}%)", i, total, (i as f64 / total as f64) * 100.0); + println!( + "Progress: {}/{} ({:.1}%)", + i, + total, + (i as f64 / total as f64) * 100.0 + ); } match self.analyze_block(height).await { @@ -377,34 +382,63 @@ impl TransparentEstimator { println!("\n=== ANALYSIS SUMMARY ==="); println!("Blocks analyzed: {}", results.len()); println!("\nCurrent compact blocks:"); - println!(" Total: {} bytes ({:.2} MB)", total_current, total_current as f64 / 1_000_000.0); + println!( + " Total: {} bytes ({:.2} MB)", + total_current, + total_current as f64 / 1_000_000.0 + ); println!("\nWith transparent data:"); - println!(" Estimated total: {} bytes ({:.2} MB)", total_estimated, total_estimated as f64 / 1_000_000.0); - println!(" Delta: +{} bytes ({:.2} MB)", total_delta, total_delta as f64 / 1_000_000.0); - println!(" Overall increase: {:.2}%", (total_delta as f64 / total_current as f64) * 100.0); + println!( + " Estimated total: {} bytes ({:.2} MB)", + total_estimated, + total_estimated as f64 / 1_000_000.0 + ); + println!( + " Delta: +{} bytes ({:.2} MB)", + total_delta, + total_delta as f64 / 1_000_000.0 + ); + println!( + " Overall increase: {:.2}%", + (total_delta as f64 / total_current as f64) * 100.0 + ); println!("\nPer-block statistics:"); println!(" Median increase: {:.2}%", median); println!(" 95th percentile: {:.2}%", p95); println!(" Min: {:.2}%", deltas[0]); println!(" Max: {:.2}%", deltas[deltas.len() - 1]); - + // Practical impact examples println!("\nPractical impact:"); let blocks_per_day = 1152; // Post-Blossom (75s blocks) let daily_current = (total_current as f64 / results.len() as f64) * blocks_per_day as f64; - let daily_estimated = (total_estimated as f64 / results.len() as f64) * blocks_per_day as f64; - println!(" Current daily sync (~{} blocks): {:.2} MB", blocks_per_day, daily_current / 1_000_000.0); - println!(" With transparent: {:.2} MB", daily_estimated / 1_000_000.0); - println!(" Additional bandwidth per day: {:.2} MB", (daily_estimated - daily_current) / 1_000_000.0); + let daily_estimated = + (total_estimated as f64 / results.len() as f64) * blocks_per_day as f64; + println!( + " Current daily sync (~{} blocks): {:.2} MB", + blocks_per_day, + daily_current / 1_000_000.0 + ); + println!( + " With transparent: {:.2} MB", + daily_estimated / 1_000_000.0 + ); + println!( + " Additional bandwidth per day: {:.2} MB", + (daily_estimated - daily_current) / 1_000_000.0 + ); } } #[tokio::main] async fn main() -> Result<()> { let args: Vec = std::env::args().collect(); - + if args.len() < 4 { - eprintln!("Usage: {} [output.csv]", args[0]); + eprintln!( + "Usage: {} [output.csv]", + args[0] + ); eprintln!(); eprintln!("Modes:"); eprintln!(" range - Analyze specific block range"); @@ -418,10 +452,22 @@ async fn main() -> Result<()> { eprintln!(" complete - Analyze every block in range (no sampling)"); eprintln!(); eprintln!("Examples:"); - eprintln!(" {} http://127.0.0.1:9067 http://127.0.0.1:8232 range 2400000 2401000", args[0]); - eprintln!(" {} http://127.0.0.1:9067 http://127.0.0.1:8232 recommended results.csv", args[0]); - eprintln!(" {} http://127.0.0.1:9067 http://127.0.0.1:8232 density 1000 density.csv", args[0]); - eprintln!(" {} http://127.0.0.1:9067 http://127.0.0.1:8232 complete 2800000 2800100", args[0]); + eprintln!( + " {} http://127.0.0.1:9067 http://127.0.0.1:8232 range 2400000 2401000", + args[0] + ); + eprintln!( + " {} http://127.0.0.1:9067 http://127.0.0.1:8232 recommended results.csv", + args[0] + ); + eprintln!( + " {} http://127.0.0.1:9067 http://127.0.0.1:8232 density 1000 density.csv", + args[0] + ); + eprintln!( + " {} http://127.0.0.1:9067 http://127.0.0.1:8232 complete 2800000 2800100", + args[0] + ); std::process::exit(1); } @@ -430,11 +476,9 @@ async fn main() -> Result<()> { let mode = &args[3]; // Get current tip from Zebra - let estimator = TransparentEstimator::new( - zebra_rpc_url.to_string(), - lightwalletd_url.to_string(), - ); - + let estimator = + TransparentEstimator::new(zebra_rpc_url.to_string(), lightwalletd_url.to_string()); + let current_tip = estimator.get_current_tip().await?; println!("Current blockchain tip: {}", current_tip); println!(); @@ -468,7 +512,10 @@ async fn main() -> Result<()> { std::process::exit(1); } let every_n: u64 = args[4].parse()?; - let output = args.get(5).map(|s| s.as_str()).unwrap_or("density_sample.csv"); + let output = args + .get(5) + .map(|s| s.as_str()) + .unwrap_or("density_sample.csv"); let sampler = Sampler::new( SamplingStrategy::FixedDensity { every_n }, current_tip, @@ -480,37 +527,55 @@ async fn main() -> Result<()> { "quick" => { let sampler = create_quick_sampler(current_tip); println!("{}", sampler.describe()); - let output = args.get(4).map(|s| s.as_str()).unwrap_or("quick_sample.csv"); + let output = args + .get(4) + .map(|s| s.as_str()) + .unwrap_or("quick_sample.csv"); (sampler.generate_samples(), output.to_string()) } "recommended" => { let sampler = create_recommended_sampler(current_tip); println!("{}", sampler.describe()); - let output = args.get(4).map(|s| s.as_str()).unwrap_or("recommended_sample.csv"); + let output = args + .get(4) + .map(|s| s.as_str()) + .unwrap_or("recommended_sample.csv"); (sampler.generate_samples(), output.to_string()) } "thorough" => { let sampler = create_thorough_sampler(current_tip); println!("{}", sampler.describe()); - let output = args.get(4).map(|s| s.as_str()).unwrap_or("thorough_sample.csv"); + let output = args + .get(4) + .map(|s| s.as_str()) + .unwrap_or("thorough_sample.csv"); (sampler.generate_samples(), output.to_string()) } "equal" => { let sampler = create_equal_sampler(current_tip); println!("{}", sampler.describe()); - let output = args.get(4).map(|s| s.as_str()).unwrap_or("equal_sample.csv"); + let output = args + .get(4) + .map(|s| s.as_str()) + .unwrap_or("equal_sample.csv"); (sampler.generate_samples(), output.to_string()) } "proportional" => { let sampler = create_proportional_sampler(current_tip); println!("{}", sampler.describe()); - let output = args.get(4).map(|s| s.as_str()).unwrap_or("proportional_sample.csv"); + let output = args + .get(4) + .map(|s| s.as_str()) + .unwrap_or("proportional_sample.csv"); (sampler.generate_samples(), output.to_string()) } "weighted" => { let sampler = create_weighted_sampler(current_tip); println!("{}", sampler.describe()); - let output = args.get(4).map(|s| s.as_str()).unwrap_or("weighted_sample.csv"); + let output = args + .get(4) + .map(|s| s.as_str()) + .unwrap_or("weighted_sample.csv"); (sampler.generate_samples(), output.to_string()) } _ => { @@ -520,7 +585,10 @@ async fn main() -> Result<()> { }; println!("Analyzing {} blocks...", blocks.len()); - println!("Fetching real compact blocks from lightwalletd: {}", lightwalletd_url); + println!( + "Fetching real compact blocks from lightwalletd: {}", + lightwalletd_url + ); println!("Fetching full blocks from Zebra: {}", zebra_rpc_url); println!(); From 4cdc73539ab90df67a6787b91f391e5ab3e2d15b Mon Sep 17 00:00:00 2001 From: Pacu Date: Mon, 13 Oct 2025 16:12:44 -0300 Subject: [PATCH 13/17] fix test bugs and wrap up implementing complete analysis --- analyzer/src/main.rs | 9 +++++++-- analyzer/src/sampling.rs | 19 +++++++++++-------- 2 files changed, 18 insertions(+), 10 deletions(-) diff --git a/analyzer/src/main.rs b/analyzer/src/main.rs index 738ca99..3cf5c33 100644 --- a/analyzer/src/main.rs +++ b/analyzer/src/main.rs @@ -124,6 +124,7 @@ impl TransparentEstimator { let mut client = CompactTxStreamerClient::connect(self.lightwalletd_url.clone()).await?; // Request a single block by creating a range with start=end=height + // NO pool_types field - using main branch proto let request = tonic::Request::new(BlockRange { start: Some(BlockId { height: height as u64, @@ -133,7 +134,6 @@ impl TransparentEstimator { height: height as u64, hash: vec![], }), - pool_types: vec![], // Empty means all pools (default behavior) }); // Get the block stream (will have just one block) @@ -504,7 +504,12 @@ async fn main() -> Result<()> { let output = args.get(6).map(|s| s.as_str()).unwrap_or("complete.csv"); println!("Complete analysis: every block from {} to {}", start, end); println!("Total blocks: {}", end - start + 1); - ((start..=end).collect(), output.to_string()) + let sampler = Sampler::new( + SamplingStrategy::Complete { start, end }, + current_tip, + Some(42), + ); + (sampler.generate_samples(), output.to_string()) } "density" => { if args.len() < 5 { diff --git a/analyzer/src/sampling.rs b/analyzer/src/sampling.rs index decb047..1e0680f 100644 --- a/analyzer/src/sampling.rs +++ b/analyzer/src/sampling.rs @@ -371,11 +371,12 @@ mod tests { #[test] fn test_equal_per_era() { - let sampler = create_equal_sampler(2_400_000); + // Use a tip that's well into NU6 era + let sampler = create_equal_sampler(2_900_000); let samples = sampler.generate_samples(); - // Should have roughly 4000 samples (1000 per era) - assert!(samples.len() >= 3800 && samples.len() <= 4200); + // Should have roughly 6000 samples (1000 per era × 6 eras) + assert!(samples.len() >= 5500 && samples.len() <= 6500); // Samples should be sorted assert!(samples.windows(2).all(|w| w[0] < w[1])); @@ -383,19 +384,21 @@ mod tests { #[test] fn test_hybrid_recent() { - let sampler = create_recommended_sampler(2_400_000); + let sampler = create_recommended_sampler(2_900_000); let samples = sampler.generate_samples(); println!("{}", sampler.describe()); - // Should have base + recent samples - assert!(samples.len() >= 4500 && samples.len() <= 5500); + // Base: 750 × 6 eras = 4500 + // Recent: 2000 additional + // Total could be up to 6500 (with some overlap deduplication via BTreeSet) + assert!(samples.len() >= 4000 && samples.len() <= 7000); } #[test] fn test_reproducibility() { - let sampler1 = create_equal_sampler(2_400_000); - let sampler2 = create_equal_sampler(2_400_000); + let sampler1 = create_equal_sampler(2_900_000); + let sampler2 = create_equal_sampler(2_900_000); let samples1 = sampler1.generate_samples(); let samples2 = sampler2.generate_samples(); From 04c53cb6417bde11fb5a679c97ab2cb6a055eb56 Mon Sep 17 00:00:00 2001 From: Pacu Date: Mon, 13 Oct 2025 16:17:48 -0300 Subject: [PATCH 14/17] generate report using markdown instead of plain text --- visualization/visualize.py | 148 +++++++++++++++++++------------------ 1 file changed, 77 insertions(+), 71 deletions(-) diff --git a/visualization/visualize.py b/visualization/visualize.py index 1fc6a93..3ba4930 100644 --- a/visualization/visualize.py +++ b/visualization/visualize.py @@ -736,129 +736,135 @@ def plot_heatmap(self, filename): print(f" ✓ Heatmap saved: {filename}") def generate_report(self, filename): - """Generate statistical report""" + """Generate statistical report in Markdown format""" with open(filename, "w") as f: - f.write("=" * 80 + "\n") - f.write("STATISTICAL ANALYSIS REPORT\n") - f.write("Zcash Compact Block Transparent Data Overhead\n") - f.write("=" * 80 + "\n\n") + f.write("# Statistical Analysis Report\n\n") + f.write("**Zcash Compact Block Transparent Data Overhead**\n\n") + f.write("---\n\n") # Summary statistics - f.write("SUMMARY STATISTICS\n") - f.write("-" * 80 + "\n") - f.write(f"Total blocks analyzed: {len(self.df):,}\n") + f.write("## Summary Statistics\n\n") + f.write(f"- **Total blocks analyzed:** {len(self.df):,}\n") f.write( - f"Block height range: {self.df['height'].min():,} - {self.df['height'].max():,}\n\n" + f"- **Block height range:** {self.df['height'].min():,} - {self.df['height'].max():,}\n\n" ) # Overhead statistics - f.write("OVERHEAD PERCENTAGE\n") - f.write(f" Mean: {self.df['delta_percent'].mean():>8.2f}%\n") - f.write(f" Median: {self.df['delta_percent'].median():>8.2f}%\n") - f.write(f" Std Dev:{self.df['delta_percent'].std():>8.2f}%\n") - f.write(f" Min: {self.df['delta_percent'].min():>8.2f}%\n") - f.write(f" Max: {self.df['delta_percent'].max():>8.2f}%\n\n") + f.write("## Overhead Percentage\n\n") + f.write("| Metric | Value |\n") + f.write("|--------|-------|\n") + f.write(f"| Mean | {self.df['delta_percent'].mean():.2f}% |\n") + f.write(f"| Median | {self.df['delta_percent'].median():.2f}% |\n") + f.write(f"| Std Dev| {self.df['delta_percent'].std():.2f}% |\n") + f.write(f"| Min | {self.df['delta_percent'].min():.2f}% |\n") + f.write(f"| Max | {self.df['delta_percent'].max():.2f}% |\n\n") # Percentiles - f.write("PERCENTILES\n") + f.write("## Percentiles\n\n") + f.write("| Percentile | Overhead |\n") + f.write("|------------|----------|\n") for p in [25, 50, 75, 90, 95, 99]: value = np.percentile(self.df["delta_percent"], p) - f.write(f" P{p:>2}: {value:>8.2f}%\n") + f.write(f"| P{p} | {value:.2f}% |\n") f.write("\n") # Confidence intervals - f.write("CONFIDENCE INTERVALS (95%)\n") + f.write("## Confidence Intervals (95%)\n\n") mean = self.df["delta_percent"].mean() std_err = stats.sem(self.df["delta_percent"]) ci = stats.t.interval(0.95, len(self.df) - 1, loc=mean, scale=std_err) - f.write(f" Mean overhead: {mean:.2f}% ± {(ci[1]-mean):.2f}%\n") - f.write(f" Range: [{ci[0]:.2f}%, {ci[1]:.2f}%]\n\n") + f.write(f"- **Mean overhead:** {mean:.2f}% ± {(ci[1]-mean):.2f}%\n") + f.write(f"- **Range:** [{ci[0]:.2f}%, {ci[1]:.2f}%]\n\n") # By era - f.write("STATISTICS BY ERA\n") - f.write("-" * 80 + "\n") + f.write("## Statistics by Era\n\n") if "era" in self.df.columns: - era_stats = self.df.groupby("era").agg( - {"delta_percent": ["count", "mean", "std", "median", "min", "max"]} - ) - f.write(era_stats.to_string()) - f.write("\n\n") + f.write("| Era | Count | Mean | Std Dev | Median | Min | Max |\n") + f.write("|-----|-------|------|---------|--------|-----|-----|\n") + + era_order = ["sapling", "blossom", "heartwood", "canopy", "nu5", "nu6"] + for era in era_order: + if era in self.df["era"].values: + era_data = self.df[self.df["era"] == era]["delta_percent"] + f.write( + f"| {era.capitalize()} | {len(era_data):,} | {era_data.mean():.2f}% | " + f"{era_data.std():.2f}% | {era_data.median():.2f}% | " + f"{era_data.min():.2f}% | {era_data.max():.2f}% |\n" + ) + f.write("\n") # Bandwidth impact - f.write("PRACTICAL BANDWIDTH IMPACT\n") - f.write("-" * 80 + "\n") + f.write("## Practical Bandwidth Impact\n\n") avg_current = self.df["current_compact_size"].mean() avg_with = self.df["estimated_with_transparent"].mean() avg_delta = avg_with - avg_current - blocks_per_day = 2880 + f.write("### Average Block Sizes\n\n") + f.write(f"- **Current:** {avg_current/1000:.2f} KB\n") + f.write(f"- **With transparent:** {avg_with/1000:.2f} KB\n") + f.write(f"- **Delta:** {avg_delta/1000:.2f} KB\n\n") + + blocks_per_day = 1152 daily_current_mb = (avg_current * blocks_per_day) / 1_000_000 daily_with_mb = (avg_with * blocks_per_day) / 1_000_000 daily_delta_mb = daily_with_mb - daily_current_mb - f.write(f"Average block sizes:\n") - f.write(f" Current: {avg_current/1000:>10.2f} KB\n") - f.write(f" With transparent:{avg_with/1000:>10.2f} KB\n") - f.write(f" Delta: {avg_delta/1000:>10.2f} KB\n\n") - - f.write(f"Daily sync (~{blocks_per_day} blocks):\n") - f.write(f" Current: {daily_current_mb:>10.2f} MB\n") - f.write(f" With transparent:{daily_with_mb:>10.2f} MB\n") + f.write(f"### Daily Sync (~{blocks_per_day} blocks)\n\n") + f.write(f"- **Current:** {daily_current_mb:.2f} MB\n") + f.write(f"- **With transparent:** {daily_with_mb:.2f} MB\n") f.write( - f" Additional: {daily_delta_mb:>10.2f} MB ({(daily_delta_mb/daily_current_mb)*100:.1f}%)\n\n" + f"- **Additional:** {daily_delta_mb:.2f} MB ({(daily_delta_mb/daily_current_mb)*100:.1f}%)\n\n" ) # Correlations - f.write("CORRELATIONS\n") - f.write("-" * 80 + "\n") + f.write("## Correlations\n\n") corr_inputs = self.df["transparent_inputs"].corr(self.df["delta_bytes"]) corr_outputs = self.df["transparent_outputs"].corr(self.df["delta_bytes"]) corr_tx = self.df["tx_count"].corr(self.df["delta_percent"]) - f.write(f" Transparent inputs vs delta: r = {corr_inputs:>6.3f}\n") - f.write(f" Transparent outputs vs delta: r = {corr_outputs:>6.3f}\n") - f.write(f" Transaction count vs %%: r = {corr_tx:>6.3f}\n\n") + f.write("| Variables | Correlation (r) |\n") + f.write("|-----------|----------------|\n") + f.write(f"| Transparent inputs → delta bytes | {corr_inputs:.3f} |\n") + f.write(f"| Transparent outputs → delta bytes | {corr_outputs:.3f} |\n") + f.write(f"| Transaction count → overhead % | {corr_tx:.3f} |\n\n") # Recommendations - f.write("DECISION FRAMEWORK\n") - f.write("-" * 80 + "\n") + f.write("## Decision Framework\n\n") median_overhead = self.df["delta_percent"].median() p95_overhead = np.percentile(self.df["delta_percent"], 95) - f.write(f"Median overhead: {median_overhead:.1f}%\n") - f.write(f"95th percentile: {p95_overhead:.1f}%\n\n") + f.write(f"- **Median overhead:** {median_overhead:.1f}%\n") + f.write(f"- **95th percentile:** {p95_overhead:.1f}%\n\n") if median_overhead < 20: - f.write("RECOMMENDATION: LOW IMPACT\n") + f.write("### ✅ Recommendation: LOW IMPACT\n\n") f.write( - " The overhead is relatively small (<20%). Consider making transparent\n" + "The overhead is relatively small (<20%). Consider making transparent " ) f.write( - " data part of the default GetBlockRange method. This would:\n" + "data part of the default GetBlockRange method. This would:\n\n" ) - f.write(" - Simplify the API (single method)\n") - f.write(" - Provide feature parity with full nodes\n") - f.write(" - Have minimal bandwidth impact on users\n") + f.write("- Simplify the API (single method)\n") + f.write("- Provide feature parity with full nodes\n") + f.write("- Have minimal bandwidth impact on users\n") elif median_overhead < 50: - f.write("RECOMMENDATION: MODERATE IMPACT\n") - f.write(" The overhead is significant (20-50%). Consider:\n") - f.write(" - Separate opt-in method for transparent data\n") - f.write(" - Pool-based filtering (as in librustzcash PR #1781)\n") - f.write(" - Let clients choose based on their needs\n") - f.write(" - Important for mobile/bandwidth-limited users\n") + f.write("### ⚠️ Recommendation: MODERATE IMPACT\n\n") + f.write("The overhead is significant (20-50%). Consider:\n\n") + f.write("- Separate opt-in method for transparent data\n") + f.write("- Pool-based filtering (as in librustzcash PR #1781)\n") + f.write("- Let clients choose based on their needs\n") + f.write("- Important for mobile/bandwidth-limited users\n") else: - f.write("RECOMMENDATION: HIGH IMPACT\n") - f.write(" The overhead is substantial (>50%). Strongly consider:\n") - f.write(" - Separate method required\n") - f.write(" - Clear opt-in for clients needing transparent data\n") - f.write(" - Critical for mobile and bandwidth-limited users\n") - f.write(" - May significantly impact sync times\n") - - f.write("\n") - f.write("=" * 80 + "\n") - f.write("End of Report\n") - f.write("=" * 80 + "\n") + f.write("### 🚨 Recommendation: HIGH IMPACT\n\n") + f.write("The overhead is substantial (>50%). Strongly consider:\n\n") + f.write("- Separate method required\n") + f.write("- Clear opt-in for clients needing transparent data\n") + f.write("- Critical for mobile and bandwidth-limited users\n") + f.write("- May significantly impact sync times\n") + + f.write("\n---\n\n") + f.write("*Report generated by Compact Block Analyzer*\n") print(f" ✓ Statistical report saved: {filename}") From b42ba5ba85314c3acbb2a286632a993b21187845 Mon Sep 17 00:00:00 2001 From: Pacu Date: Mon, 13 Oct 2025 16:38:40 -0300 Subject: [PATCH 15/17] cargo clippy --- analyzer/src/main.rs | 16 ++-------------- 1 file changed, 2 insertions(+), 14 deletions(-) diff --git a/analyzer/src/main.rs b/analyzer/src/main.rs index 3cf5c33..fc73706 100644 --- a/analyzer/src/main.rs +++ b/analyzer/src/main.rs @@ -27,14 +27,11 @@ use sampling::*; // Zebra RPC response structures #[derive(Debug, Deserialize)] struct ZebraBlock { - hash: String, - height: u64, tx: Vec, } #[derive(Debug, Deserialize)] struct ZebraTransaction { - txid: String, vin: Vec, vout: Vec, } @@ -43,20 +40,11 @@ struct ZebraTransaction { struct ZebraVin { txid: Option, vout: Option, - #[serde(rename = "scriptSig")] - script_sig: Option, - sequence: u32, -} - -#[derive(Debug, Deserialize)] -struct ScriptSig { - hex: String, } #[derive(Debug, Deserialize)] struct ZebraVout { value: f64, - n: u32, #[serde(rename = "scriptPubKey")] script_pubkey: ScriptPubKey, } @@ -127,11 +115,11 @@ impl TransparentEstimator { // NO pool_types field - using main branch proto let request = tonic::Request::new(BlockRange { start: Some(BlockId { - height: height as u64, + height, hash: vec![], }), end: Some(BlockId { - height: height as u64, + height, hash: vec![], }), }); From bdd3c41908409771895af2229c2f13eb73e1f1ec Mon Sep 17 00:00:00 2001 From: Francisco Gindre Date: Mon, 13 Oct 2025 17:06:17 -0300 Subject: [PATCH 16/17] Analysis draft --- .gitignore | 2 +- docs/analysis/bandwidth_impact.png | Bin 0 -> 308608 bytes docs/analysis/by_era.png | Bin 0 -> 509516 bytes docs/analysis/correlations.png | Bin 0 -> 508032 bytes docs/analysis/cumulative.png | Bin 0 -> 213028 bytes docs/analysis/distribution.png | Bin 0 -> 416150 bytes docs/analysis/heatmap.png | Bin 0 -> 345323 bytes docs/analysis/statistical_report.md | 88 ++++++++++++++++++++++++++++ docs/analysis/time_series.png | Bin 0 -> 516767 bytes 9 files changed, 89 insertions(+), 1 deletion(-) create mode 100644 docs/analysis/bandwidth_impact.png create mode 100644 docs/analysis/by_era.png create mode 100644 docs/analysis/correlations.png create mode 100644 docs/analysis/cumulative.png create mode 100644 docs/analysis/distribution.png create mode 100644 docs/analysis/heatmap.png create mode 100644 docs/analysis/statistical_report.md create mode 100644 docs/analysis/time_series.png diff --git a/.gitignore b/.gitignore index f758028..5b493b3 100644 --- a/.gitignore +++ b/.gitignore @@ -2,7 +2,7 @@ /analyzer/target/ /analyzer/Cargo.lock **/*.rs.bk - +target/ # Proto files /analyzer/proto/*.proto diff --git a/docs/analysis/bandwidth_impact.png b/docs/analysis/bandwidth_impact.png new file mode 100644 index 0000000000000000000000000000000000000000..5cd747b23aa27cb6c2907c3683a72324b3278e45 GIT binary patch literal 308608 zcmeGFc|6u>`v#6TGoPjp%~bZ3h?1R=vP6`qPzXg4(=C;3p)A>|VUjgVsca=eSyEXF zY06EJloDA|6cOpB?92B!Z`FLB-|P4H_n+_M^*pZ`=62uj_w_!n^E}SuIL^x{W5Z3q zb1veXHEY)IdYg4jX3bilKWo<9jQ{-=Klzyb;Sv6^=CH2CVN;iVhduYW+0ELz=kOs% zm&1a=0Puqg)vD&p6;T=(yv#v=^CjJ;P%%EIUFlLv^%GNv&L^kuzk1$&Uy`78 z?#G@xzOR#gytQh5J6-GjwEETM6!3-1_>V8?WBQqf|M3%ibMZPamf%0Xq<;(I{?DJx zI>x!-(*OMb{Osa=V@cf9e|%;9@!z-m|IpfnNq>*1k@pWDJv!xbcXY+w$)RS85--=i zc6Q9MuOBa)r0GXRMR5rV3g!(yQQuU3R_^k)%NsKd1%3oh#<6cfbBwd|eVk3i$J{di zYfgr0?_)o-l?7yWMaRVOxRid~5w=)Ge#O=cyf%Jcx4-M`sb7Y#o)?)sHSsEuoi*{5Kg|(Zu=~#8Q(<9Y+L5z=TqoagZ4UM~#>ZuM z-?_Dgb1Cmj&o)1S1}pcidE@gIt&;rp_eH#w!aj~Iho5haI)8rW4G#Y27uWw4VkNof z&AsDku{AH9nr=zmxOsD#y1M#VIZJ-`t|#Ha!4k>7E3fXzUX-46^x(wQa9QNW@I`6M zwSIiCr2QF_#F_7my{0F+v~26IZqGElTwaQ`epc++Z*gO<-c{36!NFY1HkP+DL+7?m z75Co_jas(pEMp@x2J83NufKnTlc;6Sk zlV2NH4P{fS>+N-P%K!d-G2`=_e}bH~ygt8aEOND#+IP!uN0tRwSCWtOZ7H39lR)$L zERivb{(E7Io59uRlDEEm`I2E%=D*6RY1N`t2Nu}d+XwXwPmT9i#!8v$s}($gXGavV7vvcX!mm_!=)5Hq? 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0.08% | +| Max | 473783.33% | + +## Percentiles + +| Percentile | Overhead | +|------------|----------| +| P25 | 159.34% | +| P50 | 173.81% | +| P75 | 452.75% | +| P90 | 1657.47% | +| P95 | 3719.88% | +| P99 | 12968.45% | + +### Cumulative + +![Cumulative](docs/analysis/cumulative.png) + +### Distribution +![Distribution](docs/analysis/distribution.png) + +## Confidence Intervals (95%) + +- **Mean overhead:** 980.50% ± 111.16% +- **Range:** [869.34%, 1091.67%] + +## Statistics by Era + +![Statistics by era](docs/analysis/by_era.png) +![heatmap by era](docs/analysis/heatmap.png) + +| Era | Count | Mean | Std Dev | Median | Min | Max | +|-----|-------|------|---------|--------|-----|-----| +| Sapling | 1,500 | 3097.70% | 17510.41% | 540.90% | 18.55% | 473783.33% | +| Blossom | 1,500 | 1215.30% | 7770.75% | 303.57% | 1.58% | 281783.33% | +| Heartwood | 1,500 | 1435.15% | 2985.99% | 391.07% | 20.00% | 33155.95% | +| Canopy | 1,500 | 1777.54% | 4114.49% | 422.02% | 21.13% | 61611.90% | +| Nu5 | 1,500 | 633.78% | 4192.93% | 232.22% | 0.08% | 139238.89% | +| Nu6 | 6,484 | 227.05% | 518.88% | 159.34% | 0.65% | 19238.61% | + +## Practical Bandwidth Impact + +### Average Block Sizes + +- **Current:** 2.13 KB +- **With transparent:** 3.75 KB +- **Delta:** 1.62 KB + +### Daily Sync (~1152 blocks) + +- **Current:** 2.46 MB +- **With transparent:** 4.32 MB +- **Additional:** 1.86 MB (75.9%) + +![bandwidth impact](docs/analysis/bandwidth_impact.png) +## Correlations + +![correlations](docs/analysis/correlations.png) + +| Variables | Correlation (r) | +|-----------|----------------| +| Transparent inputs → delta bytes | 0.941 | +| Transparent outputs → delta bytes | 0.434 | +| Transaction count → overhead % | 0.136 | + +## Decision Framework + +- **Median overhead:** 173.8% +- **95th percentile:** 3719.9% + diff --git a/docs/analysis/time_series.png b/docs/analysis/time_series.png new file mode 100644 index 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zu!(hhI>@$){IMIobm`li;nb(Y;5L&f02PaOABnRTnhlW{F*~3cD%=#)ztsiTuF=sm z-(Ire2sRWbNTYNCyF&+Kk(a3B%9P_zA|fK9nI8jKwjP4tXth^C#0qi%k;aFV(X2xsJf)i*(!gXbx-i2N)cB6R~lxC>Cy6E^7UVPLy-mzdD)LpHMW`i-%Rz<$Y z4D~FxKmqeZc-ledSs>B@vsJwLYn|ME`eU>9pQV*-47UAQ6ye5bN1#ad0%a~BAIoTi z$R3mGM%y1Hjz3^nAxxY^x|1D`df*LnU3O!0T3UZyh%SSwKerpFInnE`-77lS;oFOAFRF=FWSztTH}uPNneye~ z%&NC5K@KUVYYC7qJD}4RolA?VzNyVSE%s1T(YMzz74%1OvdInZuhfBcmK%-yte0oi zn!i{=hJ_YJhxw@)Rz7jKC6sbObW*g}YOwyctE`Uv4TyJ&;3xwhR$xYbU0SAxU_qUt zOgdD+d=hT7gy&zreS8|5`Ep6-lW%k!gCW&%K+p Date: Mon, 13 Oct 2025 17:15:03 -0300 Subject: [PATCH 17/17] Fix rust-ci failure --- .github/workflows/rust-ci.yml | 36 ++--------------------------------- 1 file changed, 2 insertions(+), 34 deletions(-) diff --git a/.github/workflows/rust-ci.yml b/.github/workflows/rust-ci.yml index ee16f7a..088e93f 100644 --- a/.github/workflows/rust-ci.yml +++ b/.github/workflows/rust-ci.yml @@ -1,11 +1,3 @@ -name: Rust CI - -on: - push: - branches: [ main, develop ] - pull_request: - branches: [ main ] - jobs: build: runs-on: ubuntu-latest @@ -18,37 +10,13 @@ jobs: with: toolchain: stable override: true - components: rustfmt, clippy - - name: Cache cargo registry - uses: actions/cache@v3 - with: - path: ~/.cargo/registry - key: ${{ runner.os }}-cargo-registry-${{ hashFiles('**/Cargo.lock') }} - - - name: Cache cargo index - uses: actions/cache@v3 - with: - path: ~/.cargo/git - key: ${{ runner.os }}-cargo-git-${{ hashFiles('**/Cargo.lock') }} - - - name: Cache target directory - uses: actions/cache@v3 - with: - path: analyzer/target - key: ${{ runner.os }}-target-${{ hashFiles('**/Cargo.lock') }} + - name: Install protobuf compiler + run: sudo apt-get update && sudo apt-get install -y protobuf-compiler - name: Fetch proto files run: ./scripts/fetch_protos.sh - - name: Check formatting - working-directory: ./analyzer - run: cargo fmt -- --check - - - name: Run clippy - working-directory: ./analyzer - run: cargo clippy -- -D warnings - - name: Build working-directory: ./analyzer run: cargo build --release --verbose

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