diff --git a/notebooks/1-dataset-inscriptions-zksync.ipynb b/notebooks/1-dataset-inscriptions-zksync.ipynb new file mode 100755 index 0000000..716642b --- /dev/null +++ b/notebooks/1-dataset-inscriptions-zksync.ipynb @@ -0,0 +1,705 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Project Inscriptions -- Data set construction\n", + "\n", + "**Johnnatan Messias**, April 2024\n" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "import os\n", + "import pandas as pd\n", + "import polars as pl\n", + "import web3" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "import sys\n", + "code_dir = os.path.realpath(os.path.join(os.getcwd(), \"..\", \"src\"))\n", + "\n", + "sys.path.append(code_dir)" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "from utils import Utils\n", + "utils = Utils(\n", + " zkSync_data_dir='/Users/johnnatan/matterlabs/zkSync-node-crawler/data/parquet_files/')" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [], + "source": [ + "# Existing dataset dir\n", + "data_dir = '../data/'\n", + "\n", + "# Existing plots dir\n", + "plots_dir = data_dir+'/plots/'\n", + "os.makedirs(data_dir, exist_ok=True)\n", + "os.makedirs(plots_dir, exist_ok=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "'data:,{\"p\":\"zrc-20\",\"op\":\"mint\",\"tick\":\"sync\",\"amt\":\"4\"}'" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "web3.Web3.to_text(\n", + " '0x646174613a2c7b2270223a227a72632d3230222c226f70223a226d696e74222c227469636b223a2273796e63222c22616d74223a2234227d')" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [], + "source": [ + "inscriptions_tag = '0x646174613a'" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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contractAddresscodeFormatcontractNamecompilerZksolcVersioncompilerSolcVersionoptimizationUsedoptimizerModeconstructorArgumentsisSystemcompilerZkvyperVersioncompilerVyperVersion
00x5500052b962685a86217fc37107425ef32c1ff20solidity-single-fileContracts/Greeter.sol:GreeterOneFourv1.3.130.8.17TrueNaN0x00000000000000000000000000000000000000000000...FalseNaNNaN
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" + ], + "text/plain": [ + " contractAddress codeFormat \\\n", + "0 0x5500052b962685a86217fc37107425ef32c1ff20 solidity-single-file \n", + "\n", + " contractName compilerZksolcVersion \\\n", + "0 Contracts/Greeter.sol:GreeterOneFour v1.3.13 \n", + "\n", + " compilerSolcVersion optimizationUsed optimizerMode \\\n", + "0 0.8.17 True NaN \n", + "\n", + " constructorArguments isSystem \\\n", + "0 0x00000000000000000000000000000000000000000000... False \n", + "\n", + " compilerZkvyperVersion compilerVyperVersion \n", + "0 NaN NaN " + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "verified_contracts_df = pd.read_csv(data_dir+'verified-contracts.csv')\n", + "verified_contracts_map = verified_contracts_df.set_index('contractAddress')[\n", + " 'contractName'].to_dict()\n", + "verified_contracts_df.head(1)" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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namesymboldecimalsl2Addressl1Address
0EtherETH180x000000000000000000000000000000000000800a0x0000000000000000000000000000000000000000
1ChainLink TokenLINK180x082fade8b84b18c441d506e1d3a43a387cc59d200x514910771af9ca656af840dff83e8264ecf986ca
2Wrapped BTCWBTC80xbbeb516fb02a01611cbbe0453fe3c580d72810110x2260fac5e5542a773aa44fbcfedf7c193bc2c599
3Matic TokenMATIC180x770e221ec6f3e8a2e2e168399bb3aa56a63e397d0x7d1afa7b718fb893db30a3abc0cfc608aacfebb0
4UniswapUNI180x1c6f53185061d7cc387e481c350ad00c2c876f3e0x1f9840a85d5af5bf1d1762f925bdaddc4201f984
\n", + "
" + ], + "text/plain": [ + " name symbol decimals \\\n", + "0 Ether ETH 18 \n", + "1 ChainLink Token LINK 18 \n", + "2 Wrapped BTC WBTC 8 \n", + "3 Matic Token MATIC 18 \n", + "4 Uniswap UNI 18 \n", + "\n", + " l2Address \\\n", + "0 0x000000000000000000000000000000000000800a \n", + "1 0x082fade8b84b18c441d506e1d3a43a387cc59d20 \n", + "2 0xbbeb516fb02a01611cbbe0453fe3c580d7281011 \n", + "3 0x770e221ec6f3e8a2e2e168399bb3aa56a63e397d \n", + "4 0x1c6f53185061d7cc387e481c350ad00c2c876f3e \n", + "\n", + " l1Address \n", + "0 0x0000000000000000000000000000000000000000 \n", + "1 0x514910771af9ca656af840dff83e8264ecf986ca \n", + "2 0x2260fac5e5542a773aa44fbcfedf7c193bc2c599 \n", + "3 0x7d1afa7b718fb893db30a3abc0cfc608aacfebb0 \n", + "4 0x1f9840a85d5af5bf1d1762f925bdaddc4201f984 " + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "contracts_df = pd.read_csv(data_dir+'contracts.csv')\n", + "contracts_map = contracts_df.set_index('l2Address').to_dict(orient='index')\n", + "contracts_df.head()" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [], + "source": [ + "address_to_name_dict = dict(\n", + " map(lambda x: (x[0], x[1]['name']), contracts_map.items()))" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "There are 328694216 transactions and 29800000 blocks in our dataset.\n", + "Blocks range from 1 (2023-02-14 14:22:22) to 29799999 (2024-03-25 02:21:27)\n" + ] + } + ], + "source": [ + "n_transactions = utils.get_num_transactions()\n", + "n_blocks = utils.get_num_blocks()\n", + "block_info = utils.get_min_max_blocks()\n", + "print(\n", + " f\"There are {n_transactions} transactions and {n_blocks} blocks in our dataset.\")\n", + "print(\n", + " f\"Blocks range from {block_info['min_number'][0]} ({block_info['min_timestamp'][0]}) to {block_info['max_number'][0]} ({block_info['max_timestamp'][0]})\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Data gathering\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Filter transactions of interest\n" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(17054466, 6)" + ] + }, + "execution_count": 11, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Gathering transactions that contains inscriptions\n", + "txs_df = utils.get_txs(inscriptions_tag)\n", + "txs_df.shape" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(17054466, 6)" + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "txs_df.shape" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(470864,)" + ] + }, + "execution_count": 13, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Gathering unique issuers' wallet addresses from transactions\n", + "wallet_addresses = txs_df['issuer'].unique()\n", + "wallet_addresses.shape" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(62698179, 5)" + ] + }, + "execution_count": 14, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Gathering receipts for the issuers\n", + "receipts_df = utils.get_receipts(wallet_addresses)\n", + "receipts_df.shape" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [], + "source": [ + "# Merging the transactions and receipts dataframes\n", + "inscriptions_df = txs_df.join(receipts_df, on='tx_hash', how='left').sort(\n", + " pl.col(['block_number']))" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "There are 17060492 inscriptions in our dataset.\n" + ] + } + ], + "source": [ + "inscriptions_df = inscriptions_df.with_columns(pl.col('tx_input_data').map_elements(\n", + " Utils.decode_input_data).alias('decoded_input_data'))\n", + "print(\"There are {} inscriptions in our dataset.\".format(\n", + " inscriptions_df.shape[0]))" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "shape: (5, 11)
block_numbertx_hashtx_input_dataissuerreceivertimestampgas_usedgas_effective_pricefeestx_statusdecoded_input_data
i64strstrstrstrdatetime[μs]i64i64f64i64str
6332862"0x2359c19cc715…"0x646174613a2c…"0x86f04d8f599a…"0x86f04d8f599a…2023-06-18 02:04:062155302500000000.0000541"data:,dashboar…
6351363"0x9fb936db1466…"0x646174613a69…"0x39ebe965aff2…"0x488bd13f16a2…2023-06-18 07:13:342211812500000000.0000551"data:image/png…
6351394"0x364528a9e973…"0x646174613a69…"0x39ebe965aff2…"0x488bd13f16a2…2023-06-18 07:14:051486882500000000.0000371"data:image/png…
6351410"0x0d746c0320ff…"0x646174613a69…"0x39ebe965aff2…"0x488bd13f16a2…2023-06-18 07:14:212209872500000000.0000551"data:image/png…
6351431"0xcd99fb93cee9…"0x646174613a69…"0x39ebe965aff2…"0x488bd13f16a2…2023-06-18 07:14:421476042500000000.0000371"data:image/png…
" + ], + "text/plain": [ + "shape: (5, 11)\n", + "┌───────────┬───────────┬───────────┬───────────┬───┬───────────┬──────────┬───────────┬───────────┐\n", + "│ block_num ┆ tx_hash ┆ tx_input_ ┆ issuer ┆ … ┆ gas_effec ┆ fees ┆ tx_status ┆ decoded_i │\n", + "│ ber ┆ --- ┆ data ┆ --- ┆ ┆ tive_pric ┆ --- ┆ --- ┆ nput_data │\n", + "│ --- ┆ str ┆ --- ┆ str ┆ ┆ e ┆ f64 ┆ i64 ┆ --- │\n", + "│ i64 ┆ ┆ str ┆ ┆ ┆ --- ┆ ┆ ┆ str │\n", + "│ ┆ ┆ ┆ ┆ ┆ i64 ┆ ┆ ┆ │\n", + "╞═══════════╪═══════════╪═══════════╪═══════════╪═══╪═══════════╪══════════╪═══════════╪═══════════╡\n", + "│ 6332862 ┆ 0x2359c19 ┆ 0x6461746 ┆ 0x86f04d8 ┆ … ┆ 250000000 ┆ 0.000054 ┆ 1 ┆ data:,das │\n", + "│ ┆ cc71569da ┆ 13a2c6461 ┆ f599a5b56 ┆ ┆ ┆ ┆ ┆ hboard │\n", + "│ ┆ f700191b8 ┆ 7368626f6 ┆ ddcd91a96 ┆ ┆ ┆ ┆ ┆ │\n", + "│ ┆ 94cf4… ┆ 17264 ┆ 89a66… ┆ ┆ ┆ ┆ ┆ │\n", + "│ 6351363 ┆ 0x9fb936d ┆ 0x6461746 ┆ 0x39ebe96 ┆ … ┆ 250000000 ┆ 0.000055 ┆ 1 ┆ data:imag │\n", + "│ ┆ b146658f1 ┆ 13a696d61 ┆ 5aff2f380 ┆ ┆ ┆ ┆ ┆ e/png;bas │\n", + "│ ┆ d43a79373 ┆ 67652f706 ┆ 3305db701 ┆ ┆ ┆ ┆ ┆ e64,iVBOR │\n", + "│ ┆ 4269d… ┆ e673b… ┆ c8ebc… ┆ ┆ ┆ ┆ ┆ w0KGg… │\n", + "│ 6351394 ┆ 0x364528a ┆ 0x6461746 ┆ 0x39ebe96 ┆ … ┆ 250000000 ┆ 0.000037 ┆ 1 ┆ data:imag │\n", + "│ ┆ 9e973bbc6 ┆ 13a696d61 ┆ 5aff2f380 ┆ ┆ ┆ ┆ ┆ e/png;bas │\n", + "│ ┆ 9cabc3250 ┆ 67652f706 ┆ 3305db701 ┆ ┆ ┆ ┆ ┆ e64,iVBOR │\n", + "│ ┆ f99f3… ┆ e673b… ┆ c8ebc… ┆ ┆ ┆ ┆ ┆ w0KGg… │\n", + "│ 6351410 ┆ 0x0d746c0 ┆ 0x6461746 ┆ 0x39ebe96 ┆ … ┆ 250000000 ┆ 0.000055 ┆ 1 ┆ data:imag │\n", + "│ ┆ 320ff460b ┆ 13a696d61 ┆ 5aff2f380 ┆ ┆ ┆ ┆ ┆ e/png;bas │\n", + "│ ┆ 817e974c8 ┆ 67652f706 ┆ 3305db701 ┆ ┆ ┆ ┆ ┆ e64,iVBOR │\n", + "│ ┆ b3f1d… ┆ e673b… ┆ c8ebc… ┆ ┆ ┆ ┆ ┆ w0KGg… │\n", + "│ 6351431 ┆ 0xcd99fb9 ┆ 0x6461746 ┆ 0x39ebe96 ┆ … ┆ 250000000 ┆ 0.000037 ┆ 1 ┆ data:imag │\n", + "│ ┆ 3cee9376e ┆ 13a696d61 ┆ 5aff2f380 ┆ ┆ ┆ ┆ ┆ e/png;bas │\n", + "│ ┆ 985142223 ┆ 67652f706 ┆ 3305db701 ┆ ┆ ┆ ┆ ┆ e64,iVBOR │\n", + "│ ┆ d52f8… ┆ e673b… ┆ c8ebc… ┆ ┆ ┆ ┆ ┆ w0KGg… │\n", + "└───────────┴───────────┴───────────┴───────────┴───┴───────────┴──────────┴───────────┴───────────┘" + ] + }, + "execution_count": 17, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "inscriptions_df.head()" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(17060492, 11)\n" + ] + } + ], + "source": [ + "# Persisting inscriptions dataframe to a file\n", + "print(inscriptions_df.shape)\n", + "inscriptions_df.write_parquet(data_dir+'inscriptions_df.parquet')" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(289466141, 5)\n" + ] + }, + { + "data": { + "text/html": [ + "
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block_numbertx_hashis_self_transferis_inscriptiontimestamp
i64strboolbooldatetime[μs]
10000000"0x60b1dd4432b7…falsefalse2023-07-31 06:11:24
10000000"0x50225618b693…falsefalse2023-07-31 06:11:24
10000000"0xc9eca17d5877…falsefalse2023-07-31 06:11:24
10000000"0x56d6d32deef0…falsefalse2023-07-31 06:11:24
10000000"0x6dd263ae54dd…falsefalse2023-07-31 06:11:24
" + ], + "text/plain": [ + "shape: (5, 5)\n", + "┌──────────────┬─────────────────────────┬──────────────────┬────────────────┬─────────────────────┐\n", + "│ block_number ┆ tx_hash ┆ is_self_transfer ┆ is_inscription ┆ timestamp │\n", + "│ --- ┆ --- ┆ --- ┆ --- ┆ --- │\n", + "│ i64 ┆ str ┆ bool ┆ bool ┆ datetime[μs] │\n", + "╞══════════════╪═════════════════════════╪══════════════════╪════════════════╪═════════════════════╡\n", + "│ 10000000 ┆ 0x60b1dd4432b73c862c0ef ┆ false ┆ false ┆ 2023-07-31 06:11:24 │\n", + "│ ┆ 3fef4a09a… ┆ ┆ ┆ │\n", + "│ 10000000 ┆ 0x50225618b693a6c86aceb ┆ false ┆ false ┆ 2023-07-31 06:11:24 │\n", + "│ ┆ 4e3249fee… ┆ ┆ ┆ │\n", + "│ 10000000 ┆ 0xc9eca17d58773cbc98de7 ┆ false ┆ false ┆ 2023-07-31 06:11:24 │\n", + "│ ┆ 25fbf4998… ┆ ┆ ┆ │\n", + "│ 10000000 ┆ 0x56d6d32deef05581f90d7 ┆ false ┆ false ┆ 2023-07-31 06:11:24 │\n", + "│ ┆ 3c0db83e5… ┆ ┆ ┆ │\n", + "│ 10000000 ┆ 0x6dd263ae54dd10735f3d3 ┆ false ┆ false ┆ 2023-07-31 06:11:24 │\n", + "│ ┆ e63018b85… ┆ ┆ ┆ │\n", + "└──────────────┴─────────────────────────┴──────────────────┴────────────────┴─────────────────────┘" + ] + }, + "execution_count": 19, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "min_block, max_block = inscriptions_df['block_number'].min(\n", + "), inscriptions_df['block_number'].max()\n", + "q_1 = (pl.scan_parquet(utils.data_path['transactions'])\n", + " .filter(pl.col('blockNumber').is_between(min_block, max_block))\n", + " .select([\n", + " pl.col('blockNumber').alias('block_number'),\n", + " pl.col('hash').alias('tx_hash'),\n", + " pl.col('from').eq(pl.col('to')).alias('is_self_transfer'),\n", + " pl.col('hash').is_in(\n", + " inscriptions_df['tx_hash'].unique()).alias('is_inscription')\n", + " ])\n", + " # ).with_columns(\n", + " # pl.col('tx_hash').is_in(\n", + " # inscriptions_df['tx_hash'].unique()).alias('is_inscription')\n", + " )\n", + "q_2 = (pl.scan_parquet(utils.data_path['blocks'])\n", + " .filter(pl.col('number').is_between(min_block, max_block))\n", + " .select(pl.col('number').alias('block_number'), pl.from_epoch(pl.col('timestamp')))\n", + " )\n", + "q = q_1.join(q_2, left_on='block_number', right_on='block_number', how='left')\n", + "all_txs_df = q.collect(streaming=True)\n", + "\n", + "print(all_txs_df.shape)\n", + "all_txs_df.head()" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "There are 289466141 unique transactions in our dataset.\n", + "There are 23070883 unique blocks in our dataset.\n", + "The average number of txs per block is 12.55 txs.\n", + "The minimum and max number of txs per block are: 6332862 and 29799866.\n", + "The minimum timestamp is 2023-06-18 02:04:06 and the maximum timestamp is 2024-03-25 02:19:14.\n" + ] + } + ], + "source": [ + "print(\"There are {} unique transactions in our dataset.\".format(\n", + " all_txs_df['tx_hash'].n_unique()))\n", + "print(\"There are {} unique blocks in our dataset.\".format(\n", + " all_txs_df['block_number'].n_unique()))\n", + "print(\"The average number of txs per block is {} txs.\".format(round(\n", + " all_txs_df['tx_hash'].n_unique()/all_txs_df['block_number'].n_unique(), 2)))\n", + "\n", + "print(\"The minimum and max number of txs per block are: {} and {}.\".format(\n", + " all_txs_df['block_number'].min(), all_txs_df['block_number'].max()))\n", + "\n", + "print(\"The minimum timestamp is {} and the maximum timestamp is {}.\".format(\n", + " all_txs_df['timestamp'].min(), all_txs_df['timestamp'].max()))" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "There are 289466141 unique transactions in our dataset.\n", + "There are 23070883 unique blocks in our dataset.\n", + "The average number of txs per block is 12.55 txs.\n", + "The minimum and max number of txs per block are: 6332862 and 29799866.\n", + "The minimum timestamp is 2023-06-18 02:04:06 and the maximum timestamp is 2024-03-25 02:19:14.\n" + ] + } + ], + "source": [ + "print(\"There are {} unique transactions in our dataset.\".format(\n", + " all_txs_df['tx_hash'].n_unique()))\n", + "print(\"There are {} unique blocks in our dataset.\".format(\n", + " all_txs_df['block_number'].n_unique()))\n", + "print(\"The average number of txs per block is {} txs.\".format(round(\n", + " all_txs_df['tx_hash'].n_unique()/all_txs_df['block_number'].n_unique(), 2)))\n", + "\n", + "print(\"The minimum and max number of txs per block are: {} and {}.\".format(\n", + " all_txs_df['block_number'].min(), all_txs_df['block_number'].max()))\n", + "\n", + "print(\"The minimum timestamp is {} and the maximum timestamp is {}.\".format(\n", + " all_txs_df['timestamp'].min(), all_txs_df['timestamp'].max()))" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "metadata": {}, + "outputs": [], + "source": [ + "all_txs_df.write_parquet(data_dir+'inscriptions_all_txs_df.parquet')" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "base", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.11.7" + }, + "orig_nbformat": 4 + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/notebooks/2-inscriptions-eda-zksync.ipynb b/notebooks/2-inscriptions-eda-zksync.ipynb new file mode 100755 index 0000000..b22a16e --- /dev/null +++ b/notebooks/2-inscriptions-eda-zksync.ipynb @@ -0,0 +1,1329 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Project Inscriptions -- Exploratory Data Analysis\n", + "\n", + "**Johnnatan Messias**, April 2024\n" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "import os\n", + "from tqdm.notebook import tqdm\n", + "import polars as pl\n", + "import json\n", + "import plotly.graph_objects as go" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "import sys\n", + "code_dir = os.path.realpath(os.path.join(os.getcwd(), \"..\", \"src\"))\n", + "\n", + "sys.path.append(code_dir)" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "from plot_utils import get_plotly_layout\n", + "from plot_utils import colors\n", + "width, height = 800, 450" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [], + "source": [ + "# Existing dataset dir\n", + "data_dir = '../data/'\n", + "\n", + "# Existing plots dir\n", + "plots_dir = data_dir+'/plots/'\n", + "os.makedirs(data_dir, exist_ok=True)\n", + "os.makedirs(plots_dir, exist_ok=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [], + "source": [ + "inscriptions_tag = '0x646174613a'" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Exploratory Data Analysis\n" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [], + "source": [ + "def parse_input_data(data):\n", + " response = dict()\n", + " if data is None:\n", + " response = None\n", + " else:\n", + " if data.startswith('data:,{'):\n", + " response['type'] = 'json'\n", + " response['data'] = ','.join(data.split(',')[1:])\n", + " elif data.startswith('data:image/png;'):\n", + " response['type'] = 'image/png'\n", + " response['data'] = ','.join(data.split(',')[1:])\n", + " elif data.startswith('data:application/json,'):\n", + " response['type'] = 'application/json'\n", + " response['data'] = ','.join(data.split(',')[1:])\n", + " elif data.startswith('data:application/json,'):\n", + " response['type'] = 'application/json'\n", + " response['data'] = ','.join(data.split(',')[1:])\n", + " else:\n", + " response['type'] = 'unknown'\n", + " response['data'] = data\n", + " return response" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "There are 17060492 inscriptions in our dataset.\n" + ] + }, + { + "data": { + "text/html": [ + "
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" + ], + "text/plain": [ + "shape: (5, 17)\n", + "┌──────────────┬─────────────┬─────────────┬─────────────┬───┬──────┬─────────┬──────┬─────────────┐\n", + "│ block_number ┆ tx_hash ┆ tx_input_da ┆ issuer ┆ … ┆ tick ┆ amt ┆ tx ┆ price │\n", + "│ --- ┆ --- ┆ ta ┆ --- ┆ ┆ --- ┆ --- ┆ --- ┆ --- │\n", + "│ i64 ┆ str ┆ --- ┆ str ┆ ┆ str ┆ str ┆ str ┆ str │\n", + "│ ┆ ┆ str ┆ ┆ ┆ ┆ ┆ ┆ │\n", + "╞══════════════╪═════════════╪═════════════╪═════════════╪═══╪══════╪═════════╪══════╪═════════════╡\n", + "│ 22219206 ┆ 0xccca8ddf6 ┆ 0x646174613 ┆ 0xcd5446c94 ┆ … ┆ bgnt ┆ 5 ┆ null ┆ 10000000000 │\n", + "│ ┆ 83dd96195d7 ┆ a2c7b227022 ┆ 6f45eba0121 ┆ ┆ ┆ ┆ ┆ 000 │\n", + "│ ┆ 633a851f8a… ┆ 3a22657261… ┆ 65a1eace31… ┆ ┆ ┆ ┆ ┆ │\n", + "│ 22233218 ┆ 0x57d7eb724 ┆ 0x646174613 ┆ 0xf4f837133 ┆ … ┆ bgnt ┆ 5 ┆ null ┆ 10000000000 │\n", + "│ ┆ a78a290bd06 ┆ a2c7b227022 ┆ a7b5a907813 ┆ ┆ ┆ ┆ ┆ 000 │\n", + "│ ┆ ee832d5364… ┆ 3a22657261… ┆ 6b42fd10ed… ┆ ┆ ┆ ┆ ┆ │\n", + "│ 22568611 ┆ 0x3c7659c2d ┆ 0x646174613 ┆ 0x9c4ee801d ┆ … ┆ pook ┆ 170000 ┆ null ┆ 19700000000 │\n", + "│ ┆ 3bd78a5be31 ┆ a2c7b227022 ┆ c5d51520461 ┆ ┆ ┆ ┆ ┆ 0000 │\n", + "│ ┆ e1b5a85964… ┆ 3a22787273… ┆ c1f217707f… ┆ ┆ ┆ ┆ ┆ │\n", + "│ 22581154 ┆ 0x5b3270339 ┆ 0x646174613 ┆ 0xfe85c6f21 ┆ … ┆ pook ┆ 1000000 ┆ null ┆ 20000000000 │\n", + "│ ┆ 52b196d38e6 ┆ a2c7b227022 ┆ 17e6caef6d3 ┆ ┆ ┆ ┆ ┆ 0000 │\n", + "│ ┆ 8135dfdd42… ┆ 3a22787273… ┆ 21be5128ee… ┆ ┆ ┆ ┆ ┆ │\n", + "│ 22581168 ┆ 0x43662e5a3 ┆ 0x646174613 ┆ 0x7fab58d90 ┆ … ┆ pook ┆ 65000 ┆ null ┆ 20000000000 │\n", + "│ ┆ 6e84f78fe44 ┆ a2c7b227022 ┆ ab7635e2d58 ┆ ┆ ┆ ┆ ┆ 000000 │\n", + "│ ┆ 8a1e1790e7… ┆ 3a22787273… ┆ 224e988e64… ┆ ┆ ┆ ┆ ┆ │\n", + "└──────────────┴─────────────┴─────────────┴─────────────┴───┴──────┴─────────┴──────┴─────────────┘" + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "inscriptions_parsed.filter(pl.col('price').is_not_null()).head()" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "['mffdfdfdint',\n", + " 'mint23523',\n", + " None,\n", + " 'min6j6t',\n", + " 'min',\n", + " 'mint',\n", + " 'doge',\n", + " 'mwefefint',\n", + " '0x646174613a2c7b2270223a227a72632d3230222c226f70223a226d696e74222c227469636b223a2273796e63222c22616d74223a2234227mint',\n", + " 'min6556756t',\n", + " 'mintsdaf',\n", + " 'mzvdfint',\n", + " 'transfer',\n", + " 'cancel',\n", + " 'list',\n", + " '34345mint',\n", + " '薄荷',\n", + " 'minuykyhgt',\n", + " '55253245345mint',\n", + " 'mivsfant',\n", + " 'adfsmint',\n", + " 'mwertint',\n", + " 'm45645in54645654t',\n", + " 'йуцаmint',\n", + " 'mintasdf',\n", + " 'mi647567nt',\n", + " 'm egrteint',\n", + " 'm23fc ewint',\n", + " 'm dtrint',\n", + " 'sdfgmint',\n", + " 'mi',\n", + " 'mi b ert ertbnt',\n", + " 'miafdsnt',\n", + " 'buy',\n", + " 'min453t',\n", + " 'min6556t',\n", + " 'dep',\n", + " 'mintdsfkldsjfnç',\n", + " 'mintzzzx',\n", + " 'claim',\n", + " 'zcvmint',\n", + " 'minr33r3r3rt',\n", + " 'mdsgfint',\n", + " 'mi456456546nt',\n", + " 'min2435t',\n", + " 'burn',\n", + " 'minZxct',\n", + " 'asdf samint',\n", + " 'mцуксint',\n", + " 'min56565666',\n", + " 'wefmint',\n", + " 'mdgfxbbvcxbvcxint',\n", + " 'minвапиt',\n", + " '2223mint',\n", + " 'mdsfaadsfint',\n", + " 'min54645654t',\n", + " ' mint',\n", + " 'deploy',\n", + " 'sell',\n", + " 'mindsfgt',\n", + " 'mdsvfint',\n", + " 'mwdwddwint',\n", + " 'miZxcbnt',\n", + " 'mцуйаint',\n", + " 'min656u6t',\n", + " 'ferwrfwergwergwerwerttwermint',\n", + " 'mint3345345',\n", + " 'dwdwdwdwdw',\n", + " 'cross',\n", + " 'msmzy327327int',\n", + " 'minxcvt']" + ] + }, + "execution_count": 14, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "inscriptions_parsed['op'].unique().to_list()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### What are the top deployed inscriptions on zkSync?\n" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "shape: (10, 2)
opcount
stru32
"mint"11150631
"claim"5651954
null39451
"deploy"14990
"list"3246
"transfer"1314
"buy"1206
"cancel"719
"sell"103
" mint"17
" + ], + "text/plain": [ + "shape: (10, 2)\n", + "┌──────────┬──────────┐\n", + "│ op ┆ count │\n", + "│ --- ┆ --- │\n", + "│ str ┆ u32 │\n", + "╞══════════╪══════════╡\n", + "│ mint ┆ 11150631 │\n", + "│ claim ┆ 5651954 │\n", + "│ null ┆ 39451 │\n", + "│ deploy ┆ 14990 │\n", + "│ list ┆ 3246 │\n", + "│ transfer ┆ 1314 │\n", + "│ buy ┆ 1206 │\n", + "│ cancel ┆ 719 │\n", + "│ sell ┆ 103 │\n", + "│ mint ┆ 17 │\n", + "└──────────┴──────────┘" + ] + }, + "execution_count": 13, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "inscriptions_parsed['op'].value_counts().sort('count', descending=True).head(10)" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "p\n", + "zrc-20 9193856\n", + "layer2-20 5672385\n", + "era-20 1601931\n", + "brc-20 254986\n", + "Others 89873\n", + "zks-20 50698\n", + "Name: count, dtype: int64\n" + ] + }, + { + "data": { + 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" + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "data = inscriptions_parsed[['p']].to_pandas().copy()\n", + "top_protocols = data['p'].value_counts().iloc[:5].index\n", + "data.loc[~data['p'].isin(top_protocols), 'p'] = 'Others'\n", + "\n", + "print(data['p'].value_counts(normalize=False))\n", + "data = data['p'].value_counts(normalize=True)*100\n", + "\n", + "fig = go.Figure(layout=get_plotly_layout(width=width, height=height))\n", + "\n", + "fig.add_trace(go.Bar(x=data.index, y=data.values,\n", + " marker_color=colors['blue'], textposition='auto', text=data.values.round(2), name='Protocols'))\n", + "fig.update_layout(yaxis_title=\"Percentage\",\n", + " xaxis_title=\"Protocol\", yaxis_ticksuffix=\"%\")\n", + "\n", + "fig.update_traces(\n", + " texttemplate='%{text:,.4}', textfont_size=18)\n", + "fig.update_yaxes(range=[0, 100])\n", + "\n", + "fig.write_image(plots_dir+\"top-15-protocols-zksync.pdf\")\n", + "\n", + "fig.show('png')" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "op\n", + "mint 11150631\n", + "claim 5651954\n", + "Others 41594\n", + "deploy 14990\n", + "list 3246\n", + "transfer 1314\n", + "Name: count, dtype: int64\n" + ] + }, + { + "data": { + "image/png": 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" + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "data = inscriptions_parsed[['op']].to_pandas().copy()\n", + "top_protocols = data['op'].value_counts().iloc[:5].index\n", + "data.loc[~data['op'].isin(top_protocols), 'op'] = 'Others'\n", + "\n", + "print(data['op'].value_counts(normalize=False))\n", + "data = data['op'].value_counts(normalize=True)*100\n", + "\n", + "fig = go.Figure(layout=get_plotly_layout(width=width, height=height))\n", + "\n", + "fig.add_trace(go.Bar(x=data.index, y=data.values,\n", + " marker_color=colors['blue'], textposition='auto', text=data.values.round(2), name='Operation'))\n", + "fig.update_layout(yaxis_title=\"Percentage\",\n", + " xaxis_title=\"Operation\", yaxis_ticksuffix=\"%\")\n", + "\n", + "fig.update_traces(\n", + " texttemplate='%{text:,.4}', textfont_size=18)\n", + "fig.update_yaxes(range=[0, 100])\n", + "\n", + "fig.write_image(plots_dir+\"top-15-operation-zksync.pdf\")\n", + "\n", + "fig.show('png')" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "tick\n", + "sync 7009236\n", + "$L2 5672713\n", + "bgnt 1604378\n", + "zkzk 1220449\n", + "Others 728245\n", + "zksi 628708\n", + "Name: count, dtype: int64\n" + ] + }, + { + "data": { + "image/png": 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" + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "data = inscriptions_parsed[['tick']].to_pandas().copy()\n", + "top_protocols = data['tick'].value_counts().iloc[:5].index\n", + "data.loc[~data['tick'].isin(top_protocols), 'tick'] = 'Others'\n", + "\n", + "print(data['tick'].value_counts(normalize=False))\n", + "data = data['tick'].value_counts(normalize=True)*100\n", + "\n", + "fig = go.Figure(layout=get_plotly_layout(width=width, height=height))\n", + "\n", + "fig.add_trace(go.Bar(x=data.index, y=data.values,\n", + " marker_color=colors['blue'], textposition='auto', text=data.values.round(2), name='Protocols'))\n", + "fig.update_layout(yaxis_title=\"Percentage\",\n", + " xaxis_title=\"Tick\", yaxis_ticksuffix=\"%\")\n", + "\n", + "fig.update_traces(\n", + " texttemplate='%{text:,.4}', textfont_size=18)\n", + "fig.update_yaxes(range=[0, 100])\n", + "\n", + "fig.write_image(plots_dir+\"top-15-tick-zksync.pdf\")\n", + "\n", + "fig.show('png')" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "shape: (2_897, 17)
block_numbertx_hashtx_input_dataissuerreceivertimestampgas_usedgas_effective_pricefeestx_statusdecoded_input_datapoptickamttxprice
i64strstrstrstrdatetime[μs]i64i64f64i64strstrstrstrstrstrstr
22219206"0xccca8ddf683d…"0x646174613a2c…"0xcd5446c946f4…"0xcd5446c946f4…2023-12-23 11:49:372045941500000000.0000311"{"p":"era-20",…"era-20""list""bgnt""5"null"10000000000000…
22233218"0x57d7eb724a78…"0x646174613a2c…"0xf4f837133a7b…"0xf4f837133a7b…2023-12-23 15:55:162713861500000000.0000411"{"p":"era-20",…"era-20""list""bgnt""5"null"10000000000000…
22890920"0x05388d7a8e00…"0x646174613a2c…"0x055c851d9d3a…"0x055c851d9d3a…2023-12-31 18:38:321960511500000000.0000291"{"p":"era-20",…"era-20""list""bgnt""5"null"0.000000000000…
22890935"0xda4cbf4cd4e5…"0x646174613a2c…"0x055c851d9d3a…"0x055c851d9d3a…2023-12-31 18:38:471761551500000000.0000261"{"p":"era-20",…"era-20""list""bgnt""5"null"0.000000000000…
22891682"0x44c898f21ea3…"0x646174613a2c…"0x055c851d9d3a…"0x055c851d9d3a…2023-12-31 18:51:401921441500000000.0000291"{"p":"era-20",…"era-20""list""bgnt""500"null"0.000000000000…
……………………………………………
29763651"0x61e80eb1b621…"0x646174613a2c…"0x0edbc4d0adf2…"0x0edbc4d0adf2…2024-03-24 15:41:54171608250000000.0000041"{"p":"era-20",…"era-20""list""bgnt""6"null"16000000000000…
29763654"0xa03980b586d0…"0x646174613a2c…"0xc497876f1d41…"0x0edbc4d0adf2…2024-03-24 15:41:57160729250000000.0000041"{"p":"era-20",…"era-20""list""bgnt""6"null"16000000000000…
29772646"0xa9a5dbda6b86…"0x646174613a2c…"0x66d5e667c691…"0x66d5e667c691…2024-03-24 18:22:26179575250000000.0000041"{"p":"era-20",…"era-20""list""bgnt""1070"null"6000000000000"
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EmdUqIUCsEkR5NwlggHSTtrNtYYB0lq9btUOAuEXa+XbQvzrP2K0W0L9CgLgVa2m3AwGSNjoU9IAABkgPoDvUJAZIh8C6XC0EiMvAHWwO/auDcF2uGv0rBIjLIWe+uUwQIHy0YHFxMRUWFpoHhBKiCJSUlBAf+5mfny/KLhhjnkBRUREVFBRQVlaW+cIoIYYA+lcxrrBsCPpXywjFVID+FQJETDBWZwgEiHgXwcAYAhgggxMOGCCD4UsIkGD4kZ8C/WtwfIn+FQJEfDRDgIh3EQyEAAlkDGCADIZbIUCC4UcIkOD4kZ8E/SsEiPiIzgQBgjXK4sPQsIFYo2wYlfiMWKMs3kWGDET/agiTLzKhf/WFmwwZif4VAsRQoHiZCQLES/po2ywBDJBmicnNjwFSrm/MWAYBYoaW7LzoX2X7x4x16F8hQMzEiyd5IUA8wY5G0ySAATJNcAKLYYAU6JQ0TIIASQOa0CLoX4U6Jg2z0L9CgKQRNu4WyQQB4i5RtAYCIAACIAACIAACICCFAC4ilOKJGDsgQAQ6BSaBAAiAAAiAAAiAAAjYQgACxBaM9lYCAWIvT9QGAiAAAiAAAiAAAiAghwAEiBxfRC3JBAHCF9eVl5dTXl6eQA/AJDME+MhPTtnZ2WaKIa9AAmVlZZSbm0uapgm0DiYZJYD+1Sgp+fnQv8r3kVEL0b/Gk4IAMRo5LuaDAHERNpqyTAADpGWEYirAACnGFZYMgQCxhE9UYfSvotxhyRj0rxAglgLIjcIQIG5QRht2EcAAaRdJ7+vBAOm9D+ywAALEDooy6kD/KsMPdliB/hUCxI44crSOTBAgjgJE5SAAAiAAAiAAAiAAAmIJYAmWQNewAJk2bVrUst69e0dfV1RURF9nZWXhfSICh0gYgAM4oH+IxAA4gAP6Q/SH6Ae87QdS/byGAElFyIPPWYDcdttt0Zbvueee6Gu+YEpPOTk5eJ+IwCESBuAADugfIjEADuCA/hD9IfoBb/uBVD+fIUBSEfLg80xYgoWbej0ILIeaxE29DoH1oFrc1OsBdAeaRP/qAFSPqkT/6hF4B5pF/xoPFQLEgSCzWiUEiFWCKO8mAQyQbtJ2ti0MkM7ydat2CBC3SDvfDvpX5xm71QL6VwgQt2It7XYgQNJGh4IeEMAA6QF0h5rEAOkQWJerhQBxGbiDzaF/dRCuy1Wjf4UAcTnkzDeXCQKEjxYsLi6mwsJC84BQQhSBkpIS4mM/8/PzRdkFY8wTKCoqooKCgrgDDczXghJeE0D/6rUH7Gsf/at9LL2uCf0rBIjXMZiyfQiQlIiQQRABDJCCnGHRFAyQFgEKKQ4BIsQRNpiB/tUGiEKqQP8KASIkFKs3AwJEvItgYAwBDJDBCQcMkMHwJQRIMPzIT4H+NTi+RP8KASI+mjNBgGCNsvgwNGwg1igbRiU+I9Yoi3eRIQPRvxrC5ItM6F994SZDRqJ/hQAxFCheZoIA8ZI+2jZLAAOkWWJy82OAlOsbM5ZBgJihJTsv+lfZ/jFjHfpXCBAz8eJJXggQT7Cj0TQJYIBME5zAYhggBTolDZMgQNKAJrQI+lehjknDLPSvGSRA+GSeAwcOEK+7q1u3LjVt2rTGkOF1s3v27KFGjRpRbm5utXm///574k7hpJNOSpqPg2zt2rXUrl07atGihekwzQQBYhoKCoAACIAACIAACIAACASCQGAvIty0aRONHTuWtm3bFnVUy5Yt6fLLL6fbb7+dQqFQ9H0WFKNGjaIPP/ww+l6nTp3oscceo+bNm0ff27t3Lw0dOpQ+++yz6HuPPvoo9e3bNy4Yxo0bRy+//DKtXr2aTj75ZNOBAgFiGhkKgAAIgAAIgAAIgAAI+IRAIAXIoUOHqEuXLur0iGuuuYa6du1Ku3btoldffVX9nwVC//79lYtKS0vp/PPPp/379xOLDn69ceNGWrNmjZo1WbVqFTVs2FDlvf/++1UdXL5Jkyb0yCOP0I4dO2jdunXRPN9++y1dcMEFdO2119LEiRPTCgMIkLSwoRAIgAAIgAAIgAAIgIAPCARSgHz00Ud04403KkGxaNGiqBtWrFihZjAuvfRSevLJJ9X7+ntt2rRR4iIvL48qKipo8ODBakZkzJgxNHDgQJW3Q4cOSngsX75c/XvJkiU0YsQImjx5Ml1xxRXqvQcffJBeeeWVtGc/uI5MECC8PI7XKde01M0H3x+YSES8dJFTdnY2ePicQFlZmfpOaprm8yfJbPO5fy0vL1fjGZK/CaB/9bf/Yq1H/xrvy0AKEJ69uOWWW5QI4WVYevrHP/5BV155pZoReeGFF9Tbd911lxIU06dPp169ekXzfvzxx2qWhEXH4sWL6eDBg9SxY0fq3r07zZkzR+XjmZLrr7+ehg8fTkOGDKHdu3fThRdeSP369aMJEyak/a0xK0C+LK6grT9UpN2eVwV5kPTbD51aIaKzGmRTg7yjS/i84ielXQyQUjxh3Q4MkNYZSqgBAkSCF+yxAf2rPRwl1IL+NQMECC+nOvvss9WTPvPMM3TRRRepjegsFHhzuC4Y+PM+ffrQ1q1baf369dSgQYMoHf7St27dWi3D4j0fxcXFdMYZZ1DPnj1p1qxZKh/vM2GxMWzYMLrjjjuU2FmwYAG9++67aoN6usmsANm47wiN/PRQus2hnAkCJ9YJ0aMd61CT2hAgOjYMkCYCSHhWDJDCHWTQPAgQg6B8kA39qw+cZNBE9K8ZIED4Ed955x267bbb1NPyUiwWC5wuueQSmjZtWnTpDwsVFiy8WT12Yzrn1T9jgZKTk6OWRrVq1YreeOMNVdfSpUuVmHn88cfpzDPPVLMfPCPywAMP0OzZs2nlypVKuHTu3Jnuu+8+aty4saEwhQAxhMmTTBAgnmBHoyAAAiAAAiAAAgEiEMglWOwf3oDO+zeWLVsWdVf9+vXVcqrYk6n4x74+y1HVr7xX5OuvvyZejlVQUKBOynrttdfUsi3emD5z5kx1bC/PnvCeEp79eO+999QekGeffVadoMXChNvk12+//TZlZWXFNcNipWrifSu8VExPo0ePjr6urKyMex7+B2ZA3PtGsgCZ0C6Pjs8Lx+1fYRGrp1ghm8xfnI/XZ+spdh8M6olQAZ8IB8RPhAO+F/heoF+NxADGiwgH/j2nJ4wXssaL4447ztCPskAKEJ7m4qNxeVbjnHPOoTvvvJM2bNgQ3XjO+z94Hwgn3uPBYmX79u0JwHi/B5+atWXLFqpduzYlO4aXhUfbtm3V3pAbbrhBLcM67bTTiI/85ZkSFhxTpkxR+0b4aN6zzjorrh3eMF818d6V559/Pvp2bBmeWtdTrVq11EsIEEOxbksmFiCTTq9NTWprcTNmfJqanmL3tSTzV9UflrEDK+pJ7EjBJ8JE/74jfo5ukMf3KxIb6DfQb2DcicQAxgvvxwujh18EUoDwLAXPVvByqyeeeCI666BvLO/WrVv0B74+y7F582aqU6dO3I/U6sQJ3xvCR/3yxYa8NEvf+/H++++rf7O4iT2Glze586xJsjtDkv0qxhIsW7SCI5VgCVYiVtzU60ioeVIpbur1BLvtjeImdNuRelYh+lfP0NveMPrXeKSBFCCTJk2iefPm0XPPPafu9YhNvImc7+7gE7FYpQ0aNEgdt/vSSy+p2RI98dIrFic8k6Efu5ssGnmGhGc/+MQsvh/km2++oR49etCAAQPUkbyceFM6n5I1fvx4NUuSKkGApCLk3ecQIBAg3kWf8y1jgHSesRstQIC4QdmdNiBA3OHsRivoXzNAgPByJ172xHd58D0deuIlVOedd576p76xnPdn8B4LFhs8W6JPY+oiRj/hqrrg5D0cvGfjgw8+oBNOOIEOHz5M7du3jzuud+HChWo/Cm9MZ3GSKkGApCLk3ecQIBAg3kWf8y1jgHSesRstQIC4QdmdNiBA3OHsRivoXzNAgHz55ZfUu3dv9aRXXXWVuhWdZybeeusttak89hhevt+DRQnvA2ERwnl5ORYv4+LEd4pUd3pVstkOLnPTTTep4355aRZfcMgnYPGsi76ZPVWgQ4CkIuTd5xAgiez5u8Nr8fPz871zDFq2hQAfV84HblQ9LMOWylGJawT46FY+gbGwsNC1NtGQMwTQvzrD1Yta0b9mgADhR+TTqObPn6+WV8UmXhrF+0NiT5LYuXOnuseDN63rie/x4Ps+eEN5dUmf/eA2+IZ0PbHI4dkXXp6lp6oXHdYU/BIFSLi8lOjHfaSVHSI6pj6F8+tXe4mg2hj6372kHSmjcP2mpGWZuyE7XHGEtAP/VojC9U8gLRR/cpgXHYfeJgQIBIiX8ed02xggnSbsTv0QIO5wdqMVCBA3KLvTBvrXDBEg+mMeOHCAWGAcc8wxaokUn2ZVXeKjHnlWgzeX8zG7qRIv3+Kj4JItq+IBgNvlE7maNWumjvo1miQJkHD5YQotn0Xal+vizc+rS5U9biZqd+HR9/mI4Hf+RNpnK0kLHz0uuPLE1hS+YgRpdY+tEQGLnNAH80nbtDwuX/jUs6my152k5UZ8py2bQdrWNTXWVXnCL4hufMQocsP5IEAgQAwHiw8zYoD0odOSmAwBEgw/8lNAgATHl+hfM0yA+DF0JQkQWjKFQtvWV4uxcsAkoqatIsJg6dREofJzyXCtfArfOY/PyKveJW/PptDmVUk/DzdqTuGbp6ZsRy8cbnoahQdMtN39ECCJSLFG2fYw86xCrFH2DL2tDWMPiK04Pa0M/aun+G1tHP0rBIitAeVEZZIEiPb4NWo2I6yFKNz3Pgo3bEahvy0i7fN31aNXnnUF0YU3Eh3+kUJP3hTFET6vX2SZ1qrnSKv4KZL3qpFEp8bfgxIVDCXFlPX0LUfLd76MwsefQtqKOUfL3/go0QmnkvbxUgpvS7w/RfvPN6T9FLmPI9zjZgqf0ct290CAQIDYHlSCKsQAKcgZFkyBALEAT1hRCBBhDrFgDvpXCBAL4eNOUTEChJdETe8f+UHf/HQK9xsbAbD/Owo9e2dEVJzWhajPH4k+WU6hd56L5P3l+RTudVck7z8+oNCbT0bytuhMdPXRW93jaO78nEILx0XKn9aFwlwnp8/fpdBbMyPlO/6a6OLfV+sE7ZlbSfvhP0osVf7hz6Tlxd/rYof3IEASKWKAtCOyZNSBAVKGH6xaAQFilaCc8uhf5fjCqiXoX+MJBvIeEKtB4nV5MQKEl1XNvYO0A3siAuDKERQ+sQ2F/jqdtJ1bIu/9+lai03uSxns/PnlLvVdxzRjSTukQwRgrYgqaUHjw08nxxgqVX/UnOveqSL6S/1Lo6UGRtv5fB6JrxyQtH96xhbIWjVefhdt0o3DvYY64EQLEEayoFARAAARAAARAIIMIQIAIdLYkAUK7vyBt4fjoMqhYXDxTUfmbe9RpWNrrj5O2fUNEgAyZRdpxx0ezhmYMJCorIeKN68NeTE5811YKvRIRF7zMKzzwMaLsHKKD+yk0MzLrwSdqhX8fmU2pmpSNuij67eNEjVs44lkIEEewolIQAAEQAAEQAIEMIgABItDZogQIn2z1+qMU+t9P4kiFs3Iim7z1H/ovjaLQd1+pPJV3/Zmo9tE7IbSnf0dayYHIPpJ7FyclHi4tUXtI9NOzuH7iI3j/szOaP3Yjelwl/91LoTm3R0RKQWMKD44s2XIiQYA4QRV1ggAIgAAIgAAIZBIBCBCB3hYlQBaOo9DOzyM/7uscS+EWnSn08wZ0JTauH090clvSFk8g7V+fRgTI7XOJjjl6AZb2xG9JKz1ISrQMX1g98Zh9JMkycdvhZHtIVs6l0KcrIm1fPJio4yWOeRUCJBEtH/nJKTvb3H0vjjkJFadNgI8N5zuSeFYTyb8E+C6m8vJyysvL8+9DwHJFAP1rcAIB/Wu8LyFABMa2FAESPniAsmb+LiI+6jelypunkJadS7RjM4UWPRR5Xz8e9+1nKLT5nYgIiFkCFa6spNCUfpGTtOXvw24AACAASURBVI49nsK3zqqZ+K6tpG1ZTeGiXUTHNiKtsClp6yK30oc7XEzhS4bElVf3lMwYePSkrmEvEeXWcsyrECAQII4Fl4CKMUAKcIINJkCA2ABRSBUQIEIcYYMZ6F8hQGwII2erkCJAaOvfKLRsekRUdLmaqNv10QfXplyn9oWEc2pR+J6Xida/TqEPX44IBT6Ct+u1kbyxeztO+iWFb4gIF6NJHeP788WEvN+EWneNK6ptfIO01fMiNrbrTnTZHUarTisfBAgESFqB45NCGCB94qgUZkKABMOP/BQQIMHxJfpXCBDx0SxGgHy3nUIv3RcRFfUaqqNxeY8F30IeeudPkfcbnEThQTOIfvgPhZ65NfIe7/W44o9EdY4ljU/M+nFfRCBcfidR2wtIzYrwhvPvd1C423VEZ/aO+KSkmLRXxlCY/33CqRHxorfDQodnN2IuMuRBljeo8/4SThU3TyOtUTNH/QsB4iheVA4CIAACIAACIJABBLAES6CTWYA0b948atmqVUdvBy8tjVy0x6lWrchSo437jtDITw/Z/iThIz+p+z74bo3qUtyei9cmJWxWj5bLq0sVdz5PWla2Eh6heZF7PmI3jWuvjCVt1z+TNlX569uITr8o7rPw159Q1l8mRerhk7NumWY7g6oVsgB5uG0ONcoNR/lznmR+wftHl8KBTySSwAEc9H4b8YD+IXYcRzwgHoIWD6l+kEGApCLkwediZkD4h/1/95LG+zt+3oiu41AbynlJ1tl9ooTCFUfUzeWxm9SVODj+FKq8ejRp+QURscB3gzw9SN1aru/r4LKhd1+ILreKtsMzH7ysii88rJJiBUvlZUOJ2l3ouLcwA+I4YjQAAiAAAiAAAiAQcAIQIAIdLEmARIVAaUlkJqS0hML1GpBWr2HccqhYjCwmqGgXaT+VUbhRM9JyaydQ5uVTWmlJ3HG9Spxw2R+KIsu26jchyq8vykMQIInuwE29okLUkjG4qdcSPjGFcRO6GFdYNgT9q2WEYipA/xrvCggQMaF51BCJAkQgJk9MggCBAPEk8FxqFAOkS6AdbgYCxGHALlYPAeIibIebQv8KAeJwiFmvHgLEOkOnaoAAgQBxKrYk1IsBUoIXrNsAAWKdoZQaIECkeMK6HehfIUCsR5HDNUCAOAzYQvUQIInwSkpKiJfU5efnWyCLohIIFBUVUUFBAWVlZUkwBzakSYCPbi0uLqbCwqMXwqZZFYp5TAD9q8cOsLF59K8QIDaGkzNVQYA4w9WOWiFAIEDsiCOpdWCAlOoZc3ZBgJjjJTk3BIhk75izDf0rBIi5iPEgNwSIB9ANNgkBAgFiMFR8mQ0DpC/dlmA0BEgw/MhPAQESHF+if4UAER/NECByXQQBkugbrFGWG69mLcMaZbPEZObHHhCZfknHKvSv6VCTWQb9KwSIzMiMsQoCRK6LIEAgQORGp3XLMEBaZyihBggQCV6wxwYIEHs4SqgF/SsEiIQ4rNEGCBC5LoIAgQCRG53WLcMAaZ2hhBogQCR4wR4bIEDs4SihFvSvECAS4hACRLwXkhsIAeJTx8FsEAABEAABEAABMQRwEaEYVxw1BDMgAp3ys0kQIHJ9A8tAAARAAARAAAT8QQACRKCfIEAEOgUCRK5TYBkIgAAIgAAIgICvCECACHQXBIhAp0CAVOsUPvKTU3Z2tlzHwTJDBMrKyig3N5c0TTOUH5lkEuCLQcvLyykvL0+mgbDKMAH0r4ZRic+I/jXeRRAgAkMWAkSgUyBAIEDkhqVtlmGAtA2lpxVBgHiK39bGIUBsxelpZehfIUA8DUAjjUOAGKHkTR7sAUnkjgHSm1h0olUMkE5Qdb9OCBD3mTvVIvpXp8i6Xy/6VwgQ96POZIssQF544YVoqa5du0ZfV1ZWRl+HQiH1euO+IzTy00MmW0H2dAiwAJl0em1qUlsjnT/Xk8wveD8Sn+AADhwD+L5EvgvgAA4YLzAuZEI/kOo3FpZgpSLkwecsQK677rpoyw8//HD0Na/r1ROv1YYAcddBLEAmtMuj4/PCaq28npL5hT/D+xFC4AAO+L5EYgAcwAH9IfrDTOgHUv06gwBJRciDz7EEywPoBpvEEiyDoJANBEAABEAABEAABKohAAEiMDQgQAQ65WeTIEASfYObeuXGq1nLcFOvWWIy8+MmdJl+Sccq9K/pUJNZBv1rvF8gQATGKQSIQKdAgFTrFAyQcuPVrGUYIM0Sk5kfAkSmX9KxCv1rOtRklkH/CgEiMzJjrIIAkesizIBgBkRudFq3DAOkdYYSaoAAkeAFe2yAALGHo4Ra0L9CgEiIwxptgACR6yIIkETflJSUEB/7mZ+fL9dxsMwQgaKiIiooKKCsrCxD+ZFJJgE+urW4uJgKCwtlGgirDBNA/2oYlfiM6F8hQMQHKQSIXBdBgECAyI1O65ZhgLTOUEINECASvGCPDRAg9nCUUAv6VwgQCXGIGRDxXkhuIAQIBIhPQ9eQ2RggDWESnwkCRLyLDBsIAWIYlfiM6F8hQMQHKWZA5LoIAiTRN1ijLDdezVqGNcpmicnMjz0gMv2SjlXoX9OhJrMM+lcIEJmRGWMVBIhcF0GAQIDIjU7rlmGAtM5QQg0QIBK8YI8NECD2cJRQC/pXCBAJcVijDRAgcl0EAQIBIjc6rVuGAdI6Qwk1QIBI8II9NkCA2MNRQi3oXyFAJMQhBIh4LyQ3EALEp46D2SAAAiAAAiAAAmII4CJCMa44aghmQAQ65WeTIEDk+gaWgQAIgAAIgAAI+IMABIhAP0GACHQKBIhcp8AyEAABEAABEAABXxGAABHoLggQgU6BAKnWKXzkJ6fs7Gy5joNlhgiUlZVRbm4uaZpmKD8yySTAF4OWl5dTXl6eTANhlWEC6F8NoxKfEf1rvIsgQASGLASIQKdAgECAyA1L2yzDAGkbSk8rggDxFL+tjUOA2IrT08rQv9okQHbu3ElvvfUW7d69m/bs2UMdOnSgO++8U9XOX5g333yT+vTp46mz/do4BIhcz2EPSKJvMEDKjVezlmGANEtMZn4IEJl+Sccq9K/pUJNZBv2rDQJk9uzZNHXq1LiaevbsSbNmzVLvvfDCCzRx4kQaPXo03XzzzTIjQbBVLECGDBkStXD48OHR13y8op5ycnLUy437jtDITw8JfqLgmMYCZGL7PDo+j0jnz0+XzC94PxKf4AAOHAP4vkS+C+AADhgvMC5kQj+Q6pef6SVYmzZton79+ql6O3XqROeffz5Nnz6dYgXIyy+/TOPGjVN5Nm/eTHXq1EllBz6PIcACZMaMGdF3Lr/88ujrioqK6OusrCwIEJcjhwXIpNNrUeNaGun82YRkfsH7kfgEB3DgGMD3JfJdAAdwwHiBcSET+oFUP89MCxCe+eAZEP6rvP5Xev7BHCtAuNGhQ4fSihUraNGiRUqoIBkngCVYxlm5nRNLsNwmjvZAAARAAARAAASCRsC0ALn99ttp1apVSlyccsopikcyAfKnP/2JHn30UXr44YfpuuuuCxo3R58HAsRRvJYqhwBJxIebei2FlKjCuKlXlDvSNgY3oaeNTlxB9K/iXJK2Qehf49GZFiDjx4+n+fPnq2VXvXr1qlaA8B4Q3gsyZcoUbEY3Ga4QICaBuZgdAgQCxMVwc70pDJCuI3ekQQgQR7B6UikEiCfYHWkU/atFAbJgwQIaO3asWlbFAqN27doJMyBfffUV6fsW3nnnHWrWrJkjzgxqpRAgcj0LAQIBIjc6rVuGAdI6Qwk1QIBI8II9NkCA2MNRQi3oXy0KkP3799Oll15K/P/69eur17zpvHnz5vSb3/yGtm/fTsuXL1etdOvWjZ5//nkJfveVDRAgct0FAZLom5KSEuJjP/Pz8+U6DpYZIlBUVEQFBQVxG6UNFUQmUQT46Nbi4mIqLCwUZReMMU8A/at5ZlJLoH+1KEC4+GeffaY2oLMIqS517dqVpk2bpkQKkjkCECDmeLmZGwIEAsTNeHO7LQyQbhN3pj0IEGe4elErBIgX1J1pE/2rDQKEqzh8+DC9//77Soz8+9//Jr5gpWHDhtS0aVM666yzqHPnzs54MANqhQCR62QIEAgQudFp3TIMkNYZSqgBAkSCF+yxAQLEHo4SakH/apMAkeDMoNoAASLXsxAgib7BGmW58WrWMqxRNktMZn7sAZHpl3SsQv+aDjWZZdC/QoDIjMwYqyBA5LoIAgQCRG50WrcMA6R1hhJqgACR4AV7bIAAsYejhFrQv1oUIF9++SWtXLnSsC95QyNvUD/77LMpNzfXcDk7M/IXeM+ePdSkSZMaN8rytDXna9SoUY22fv/998R1nnTSSUnzcZCtXbuW2rVrRy1atDD9KBAgppG5VgACBALEtWDzoCEMkB5Ad6BJCBAHoHpUJQSIR+AdaBb9q0UBsnTpUnULutnEIoRvUE/nB7nZtvT8X3zxBY0YMYK2bdsWreKMM85QlyO2bNky+h4LilGjRtGHH34YfY+PGX7ssceUeNLT3r171Q3vvO9FT3zZYt++feNMHDdunDoZbPXq1XTyySebNh8CxDQy1wpAgLiGGg2BAAiAAAiAAAgElIDpiwj/+c9/Uv/+/Yk3RvFdH7zpPDYdOnRIXVTI6eabb1YnZfFdIJyfZ0H0z5zm+Y9//IOuvPJK1Uy/fv2odevWShCsWbOGZsyYEb2npLS0lM4//3xlJ4sOfr1x40aVr27duurWd95cz+n++++nV199lVhg8GzKI488Qjt27KB169ZF83z77bd0wQUX0LXXXkt8GWM6CQIkHWrulIEAcYczWgEBEAABEAABEAguAdMChGcV+L6PDh060MKFC5OeFz958mSaO3cujR49OipC9LtD3n33XbV0yenEszQ8W3PvvffS73//e9UcL7F644036Iorrog2v2LFCjWr0aZNGyUu8vLyqKKiggYPHqxmRMaMGUMDBw5U+fmZWXjo95wsWbJEzbDw8+p1Pvjgg/TKK6+kPfvB7UCAOB0d6dcPAZI+O5QEARAAARAAARAAASZgWoA89dRT9OSTT6o7Pnr37p2U4sGDB6ljx45q+RLPIHCaOnWqWoLFS5P4mF4nE89m8GwLz2B89NFHVKtWrWqbu+uuu5SgmD59OvXq1Sua7+OPP1YzPSw6Fi9eTPozde/enebMmaPy8UzJ9ddfr5ak8b0ou3fvpgsvvFDNuEyYMCHtR4QASRud4wUhQBIRs7DnlJ2d7Th/NOAsAT5OnffqaZrmbEOo3VECfDFoeXm5+oMakr8JoH/1t/9irUf/Gu9L0wJE/8GeSkjwD/Vdu3bRpk2b6JhjjqF58+bRpEmT6Omnn6ZLLrnE0YjasGEDDRgwQC2zYmHBG8tZlPDMS7169eLa7tOnD23dupXWr19PDRo0iH7GX3petsUihvd88K2yvH+kZ8+eNGvWLJWPn43FxrBhw+iOO+6gsWPH0oIFC8jqLA8EiKPhYalyCBAIEEsBJLwwBkjhDjJoHgSIQVA+yAYB4gMnGTQR/atFAaLPZPASJV5+lCzt27ePzjnnHPURzxIce+yxar/E888/r5ZtOX1Job5Rnjeas/CIvbGdZyx4aZg+K8IzJfw5b1QPhUJxj6N/xgIlJydHLY1q1aqVWsbFSW/n8ccfpzPPPFPNfnD9DzzwgJrt4dPCWLjw8953333UuHFjQ2EKAWIIkyeZIEAgQDwJPJcaxQDpEmiHm4EAcRiwi9VDgLgI2+Gm0L9aFCC8OfuWW25RtfD/eQaAT3ri5Re8AZ0FB4sU/tHeo0cP9UO8srJSzUZ8/fXX9N5779GJJ57oqJufffZZYlHAqWvXrkoAbN++Pbp3g2dx7rzzTvU5/9jXZzmqGsX7VthmXo7FxwnzSVmvvfYacXnemD5z5kw1u8KzJ7wsjWc/+Pl4DwjbwEvQWJjwEi5+/fbbbyfsmeHN6lXTp59+Sqeffnr07WeeeSb6mgcWPfFxwUrk7TtCIz895ChTVB4hwALk4bY51Cg3HLe0j09S01Ps8pVk/uJ8fPiBnmKXCKKeCBXwiXBA/EQ44HuB7wX61UgMYLyIcNB//2C8OLpcVsp4oR/clOp3o+klWFwhn+70wgsv1Fg3/6jnH9z8V39dtPC9GK+//noqmyx/ri/3ihUaXOnf//53uuGGG6I28Xu8x4NP6GKBUjXpy8i2bNlCtWvXpmTH8LLwaNu2LXFerpuXYZ122mnqmF+eKcnKyqIpU6aofSPJlq3Fzs7o7fPMC4saPdWvXz8pE33GBgLEcsgYrqC6GRAW2alS1Rm2ZPlRT80UwQd8qiOA71fNsQE+4FMdAfSr6Fft7FeN9DXcXloChE+J4uVFPAMQe8eG/gC8OZ2XaPEPcU68GY43evMeC56RcDrxD/+7775bnW71hz/8IdocT2XyPg4WHHxML2/Q02c5Nm/eTHXq1IkzrTpxwn+N49kePoKYl2bpez/ef/999W9+xthjePnZWQwluzMkGQsswXI6QtKvH0uw0meHkiAAAiAAAiAAAiCQtgCJRXf48GE1M8A/6llgFBYWen4ajr4JXV8CptvLt8Pykii2lY8T5mVjgwYNUsftvvTSS9F9K5yfl16xOOGZDP3Y3WQhwxvtefaDT8zi+0G++eYbtfSMN8HzkbyceFM6n5I1fvx4NUuSKkGApCLk3ecQIInscVOvd/Fod8u4qdduot7Uh5vQveHuRKvoX52g6k2d6F/juac1A+KN64y3yjMufNQvC40PPviATjjhBFVYP1o3diM578/gTeksNp544ono8ZN8Yhcv5dJPuKqudd5wvmjRomg7LMjat2+vRIl+XC9vvOf7RHg/DIuTVAkCJBUh7z6HAIEA8S76nG8ZA6TzjN1oAQLEDcrutAEB4g5nN1pB/2qjAOF1g/zlqCnxCVheJL7tnJeI8dG7vFF+586dajM4p9g7TPh+j/POO0+JFRYhXbp0IV6OxZvNOfH+lepOr0o228FlbrrpJlq7dq1amsUXHPIJWHxjur6ZPRUPCJBUhLz7HAIEAsS76HO+ZQyQzjN2owUIEDcou9MGBIg7nN1oBf2rDQKE77/gY3X5foxUqaYf8KnKWvmc96nw5u/nnnsurhqeibjxxhvjLtpiccL3eMTuZ2Hhwvd96PtYktmiz37wEi6+IV1PvHyL98Dw8iw9Vb3osKZngwCx4nlny0KAJPJl8c6nb+Tn5zsLH7U7TqCoqEid+MeHZyD5lwDvd+Qj4HlJNJK/CaB/9bf/Yq1H/2pRgPAGbDMbyb0SIPpj8nIsFhi8OVzfNF5dOPOJVDyrwfmMHCPGMyp8QlWyZVU8AHC7fO5zs2bN1FG/RhMEiFFS7ueDAIEAcT/q3GsRA6R7rJ1sCQLESbru1g0B4i5vJ1tD/2pRgPzpT39SpznxPgpeysT3YPBGbr6UkO8F4b+E8slTq1atovnz5xMfKYtkjgAEiDlebuaGAIEAcTPe3G4LA6TbxJ1pDwLEGa5e1AoB4gV1Z9pE/2pRgPBJT3yfxYQJE9Teiq+++kpdMsjigy/q43TgwAF1K/gxxxyjLubj06aQjBOAADHOyu2cECCJxLFG2e0odK49rFF2jq2bNWMPiJu0nW0L/auzfN2sHf2rRQHC91nwsbR/+ctf1GlP+/btU8fX/upXvyKeHdGTforUkiVL6Je//KWbPvZ9WxAgcl0IAQIBIjc6rVuGAdI6Qwk1QIBI8II9NkCA2MNRQi3oXy0KkMmTJ9PcuXOJbwDnU6M4devWTZ2GxSc/6Xsd9Mv59JkSCc73iw0QIHI9BQECASI3Oq1bhgHSOkMJNUCASPCCPTZAgNjDUUIt6F8tChD9lnGe9eATpvg2cb5Hgzdk83t8+hOfvsEnRPHaRX6fbxRHMk4AAsQ4K7dzQoC4TRztgQAIgAAIgAAIBI2A6YsI+RSs3r17E58YxXtB+MI/Po73mmuuSWDTqVMndUkfkjkCECDmeLmZGwLETdpoCwRAAARAAARAIIgETAsQhvDll1/Sn//8Z3UXiJ54sznf9M13hHDiZVk8C3LKKacEkZujzwQB4iheS5VDgFjCh8IgAAIgAAIgAAIgQGkJkJq48b0XfIkVTr5KP7ogQNJn53RJCJBEwnzkJyd8552OPufr5/47Nzc37qJW51tFC3YT4OPw+Q4sXiKN5G8C6F/97b9Y69G/xvvSdgESWz0v0+LbkXlAQzJOAALEOCu3c0KAQIC4HXNutocB0k3azrUFAeIcW7drhgBxm7hz7aF/tShA/vnPf9Kbb75Jl112GbVt27ZaT/FyrKlTp2ITehqxzAKEN/vriS991BMPLHrSNE293LjvCI389FAaLaGIWQIsQB7pUJua1A7F/ZU4mV+47kx4v6KiQmHkGZBMeF79exdE/+oDZOz3IsjPW1O/6mf/6gIk9o9/8GPE237joAsQXlniR/v9/D2yu3/gWUkeJzkG/RaH6fgx1e8r0zMgS5cupeHDh6vb0Pv27Vtt/XwL+vjx42nKlCnUp0+fVHbg8xgCLEB69OgRfYfFnJ74B4Ke9Ol1CBD3wocFyIR2udQoNxy3vCGZX9gqvB/xDTiAQ+xyIMQD4gHxEIkBcACHoPaHqX6ZOSZAhg0bpmZKcA9IKhckfo4lWOaZuVUCS7DcIo12QAAEQAAEQAAEgkrAkADh5UD6kqDdu3fTtm3bqGXLltSsWbMELgcPHqTt27erY3o5rVu3jho2bBhUfo48FwSII1htqRQCxBaMqAQEQAAEQAAEQCCDCRgSIE899ZS6+dxs+sMf/kBDhw41Wyzj80OAyA0BCJBE3+CmXrnxatYy3NRrlpjM/LgJXaZf0rEK/Ws61GSWQf8a7xdDAoRnPL766itVcsOGDepyQb548Nxzz03wMm+sKSgooBYtWlDjxo1lRoFwqyBA5DoIAgQCRG50WrcMA6R1hhJqgACR4AV7bIAAsYejhFrQv6YhQGKLLFu2jO655x5sLncwmiFAHIRrsWoIEAgQiyEkujgGSNHuMWwcBIhhVOIzQoCId5FhA9G/WhQghkkjY9oEIEDSRud4QQiQRMQlJSXq+F2+8wfJ3wSKiorUDLZ+5Ke/nyZzreejW4uLi6mwsDBzIQTkydG/BsSRRIT+1WYBwj88Ys/+rxoqoVAoONHj0pNAgLgEOo1mIEAgQNIIG98UwQDpG1fVaCgESDD8yE8BARIcX6J/tUGArFy5kubNm0dffPGF+nLUlP72t7/R8ccfH5wIcuFJIEBcgJxmExAgECBpho4vimGA9IWbUhoJAZISkW8yQID4xlUpDUX/alGA7Ny5ky666KKUoPUMa9aswWZ0w7QiGSFATAJzMTsESCJsrFF2MQAdbgprlB0G7FL12APiEmgXmkH/6gJkl5pA/2pRgDz00EP00ksvUatWrWjcuHF04oknUk5OTty18rFN8Hri2CvnXfKzr5uBAJHrPggQCBC50WndMgyQ1hlKqAECRIIX7LEBAsQejhJqQf9qUYAMHz6cli5dShMnTqRrr71Wgk8DZwMEiFyXQoBAgMiNTuuWYYC0zlBCDRAgErxgjw0QIPZwlFAL+leLAmTJkiU0YsQIGjBgAD344IMSfBo4GyBA5LoUAkSub2AZCIAACIAACICAPwgYuogw9lH27dtHPXr0UG/xZvRGjRr540l9ZCUEiFxnQYDI9Q0sAwEQAAEQAAEQ8AcB0wJEFx533HEHdevWjZ577jnCUbv2OhsCxF6edtYGAWInTdQFAiAAAiAAAiCQiQRMC5Dly5fTqFGjosfv1q1bt0ZumCUxH1YQIOaZuVUCAiSRNB/5ySk7O9stN6AdhwiUlZVRbm4uDg5xiK9b1fLdXOXl5ZSXl+dWk2jHIQLoXx0C60G16F/joZsWILwBnTeiG004htcoqaP5IEDMM3OrBAQIBIhbseZFOxggvaBuf5sQIPYz9apGCBCvyNvfLvpXiwLk4MGD9P333xv2TLNmzSgrK8twfmSM3APywAMPRFH89re/jb7WOyN+Q/+L88Z9R2jkp4eAzgUCLEAmts+jxrW0uL/4J/MLm5MJ7+vYOR4z4XljZ3qC9rz6AFlRURH9NgX5efWHDJofdQESO/bCjxFv+40Dx2ZlZWV0qbvf7M+UcdCIX7h/1b+TRvL7vV9K9ZPM9AxIqgrxuXUCLEDuv//+aEU33XQTBIh1rLbUAAESwej3jhH2w4+Z8AMAcY44R5z7U3gGYZxN9aPLkgDhs8Z5NoTPNq5Xrx6dcsop0fb4M76gEMk8ASzBMs/MrRJYguUWabQDAiAAAiAAAiAQVAJpCZDvvvuOnn76aVq8eHGUS8+ePWnWrFnq319//TXddtttNH/+fDr++OODys6x54IAcQyt5YohQCwjRAUgAAIgAAIgAAIZTsC0AOE9IL/5zW9o165dcehiBcjo0aOVOGnZsiW99dZbOFHFZJBBgJgE5mJ2CJBE2Lip18UAdLgp3NTrMGCXqsdN6C6BdqEZ9K8uQHapCfSv8aBNC5CFCxfSmDFjqFWrVsRCo2PHjtS+fXuKFSB79+6lq6++mvbs2UOrV6+mk08+2SX3BqMZCBC5foQAgQCRG53WLcMAaZ2hhBogQCR4wR4bIEDs4SihFvSvFgXIvffeS//zP/9DLEQ6d+6sauMfzLEChN+bOnUqzZ49m5566in69a9/LcH3vrEBAkSuqyBAIEDkRqd1yzBAWmcooQYIEAlesMcGCBB7OEqoBf2rRQEybNgwevPNN4nvA2nTpk21AuSZZ56hadOm0bhx46h///4SfO8bGyBA5LoKAiTRNyUlJcTHfubn58t1HCwzRKCoqIgKCgpwdLohWnIz8elXxcXFVFhYKNdIWGaIAPpXQ5h8kQn9q0UBwpvPn3jiCRo8eDCNGDEiqQDhM+RvuOEG2rRpE/35z3+mLl26+CI4pBgJASLFE4l2QIBAgMiNXn7oaAAAIABJREFUTuuWYYC0zlBCDRAgErxgjw0QIPZwlFAL+leLAmT9+vU0cOBAVcuDDz6oll6dd9556v8zZsyg//u//6Nnn31WzZBw2rx5M9WpU0eC731jAwSIXFdBgECAyI1O65ZhgLTOUEINECASvGCPDRAg9nCUUAv6V4sChIuPHTuWFixYkNKf06dPp169eqXMhwzxBCBA5EYEBEiib7BGWW68mrUMa5TNEpOZH3tAZPolHavQv6ZDTWYZ9K82CBDu3PiY3Xnz5tGOHTsSPN21a1e66667qFOnTjKjQLhVECByHQQBAgEiNzqtW4YB0jpDCTVAgEjwgj02QIDYw1FCLehfbRAgsVX897//VcftcofHG94aNWpE2dnZEnztWxsgQOS6DgIEAkRudFq3DAOkdYYSaoAAkeAFe2yAALGHo4Ra0L/aLECqcypvRM/KypLgc9/ZAAEi12UQIHJ9A8tAAARAAARAAAT8QcD0RYT8WHzR4MSJE9Uxu8lmO7744gt1QhafgIVjAM0HAgSIeWZulYAAcYs02gEBEAABEAABEAgqAdMC5IcfflBH7G7bto0mT55MV1xxRQIb3v+xfPlydU+IfhpWUAE68VwQIE5QtadOCBB7OKIWEAABEAABEACBzCVgWoDwDehjxoyhdu3aqU3oxx57bAK9b7/9lq666irav38/rVmzhho3bpy5hNN4cgiQNKC5VAQCJBE0H/nJCXu/XApCB5spKyuj3Nxc0jTNwVZQtdME+GLQ8vJyysvLc7op1O8wAfSvDgN2sXr0r/GwTQuQ8ePH0/z582nWrFnq7o/q0iOPPELPP/88zZw5ky6++GIXXez/piBA5PoQAgQCRG50WrcMA6R1hhJqgACR4AV7bIAAsYejhFrQv1oUIPfccw8tW7ZMHcPboUOHan3KlxKy+Bg3bhz1799fgu99YwMLkO7du0ftnTNnTvQ1B7Ce9L9ubdx3hEZ+esg3z+dnQ1mATGiXS41yw3F/XUzmF37OTHhfP2yCZ0Ay4Xlj/6octOfVB0j+63nVfiZT4jkI/tUFSGxfG4Tn0p8naN+7mp6LBQj/p89Kwo8RWn7kUFpamlF+TPVbz/QMyOzZs2nq1Kl05513qrs+kiX+svTt25e2bt2qNqJ36dIllR34PIYACxDeQ6Onli1bRl/zwKInvUOCAHEvfFiAPNKhNjWpHYpbppLML2wV3o/4BhzAIXZZF+IB8YB4iMQAOIBDUPvDVL/MTAuQTZs2Ub9+/VS9gwcPpiuvvJKaNWtGOTk5VFxcTN988w099thjtGHDBqpbty599NFHVKtWrVR24PMqAmT79u2GmUCAGEZlOSOWYFlGiApAAARAAARAAAQynIBpAcK8pkyZQrHLgqpjmGqfSIazr/bxsQdEbmRAgMj1DSwDARAAARAAARDwB4G0BEhlZSWtWLFC7fHg43irJt6/wMuzfvnLX/qDgjArIUCEOSTGHAiQRN/gpl658WrWMtzUa5aYzPy4CV2mX9KxCv1rOtRklkH/Gu8X0wKEOzbebKqvWzx8+DDt3LmT+P2GDRtSgwYNcBynxdiHALEI0MHiECAQIA6Gl+dVY4D03AW2GAABYgtGEZVAgIhwgy1GoH+1KED4CF5egnXbbbfRkCFDbHEKKoknAAEiNyIgQCBA5EandcswQFpnKKEGCBAJXrDHBggQezhKqAX9q0UB8txzz6lN5ldffTXxXR9I9hOAALGfqV01QoAkkiwpKVGnXOXn59uFGfV4RKCoqIgKCgpIP1rZIzPQrEUCfBIlHwpTWFhosSYU95oA+levPWBf++hfLQqQr7/+mi699FI66aSTaPXq1bgx177YjNYEAeIAVJuqhACBALEplERWgwFSpFtMGwUBYhqZ2AIQIGJdY9ow9K8WBQgX5w3mfE/F8OHDsQzLdAimLgABkpqRVzkgQCBAvIo9N9rFAOkGZefbgABxnrFbLUCAuEXa+XbQv1oUILzh/N1336VJkyapmliE8JR9dal3795Uu3Zt5z0boBYgQOQ6EwIk0TdYoyw3Xs1ahjXKZonJzI89IDL9ko5V6F/ToSazDPpXiwJk6dKlSnQYTWvWrKHGjRsbze5pPv6r0Z49e6hRo0aUm5tbrS3ff/89cafAy9CS5eMgW7t2LbVr145atGhh+pkgQEwjc60ABAgEiGvB5kFDGCA9gO5AkxAgDkD1qEoIEI/AO9As+leLAuSTTz6hBQsWGHbNmDFj6NhjjzWc34mM3BkPGDCA+Bb3xYsXU4cOHeKaYUExatQo+vDDD6Pvd+rUSW22b968efS9vXv30tChQ+mzzz6Lvvfoo49S37594+obN24cvfzyy2qPzMknn2z6kSBATCNzrQAECASIa8HmQUMYID2A7kCTECAOQPWoSggQj8A70Cz6V4sCxAGfOF7l5MmTae7cuaqdRYsWEYsLPZWWltL5559P+/fvV+/z640bNxLP3NStW5dWrVql7jfhdP/999Orr75KLDCaNGmiTgHbsWMHrVu3Lprn22+/pQsuuICuvfZamjhxYlrPBgGSFjZXCkGAuIIZjYAACIAACIAACASYgOmLCP3G4r333qPBgwdHza4qQPhGd57VaNOmjRIXeXl5VFFRocrwjAjP4AwcOFCV55kTFh68AZ/TkiVLaMSIEcQC54orrlDvPfjgg/TKK6+kPfvBdUCAyI0yCBC5voFlIAACIAACIAAC/iCQtgDh/RK8FIn/4s/TSrzU6OKLL44+9b/+9S865ZRTPKXw3Xff0WWXXUZ8igQfHczCoaoA0U/0mj59OvXq1Stq78cff0z9+/dXooOXbR08eJA6duxI3bt3pzlz5qh8PFNy/fXXR08D2717N1144YXUr18/mjBhQtrPDgGSNjrHC0KAOI4YDYAACIAACIAACAScQFoChDdY88zArl27onh69uxJs2bNUv/+4IMP6He/+52aCTjzzDM9QVheXq4EBIukp556ilgQscioKkD69OlDW7dupfXr11ODBg2itrLAat26tVqGxXXwpU5nnHEGxT4n7ylhsTFs2DC64447aOzYsWp/DJ8SxhvU000QIOmSc74cBEgiY/6ucMrOznbeAWjBUQJlZWXqYA1N0xxtB5U7S4AvBuUxkGf0kfxNAP2rv/0Xaz3613hfmhYg33zzDfXo0SNayznnnEMfffRR3A9zPqJ33rx56sc7zxJ48cOEN5Dzre233HKL2mDO4iiZADn77LPV/o9t27ZRKBSKo6N/xgIlJydHLY1q1aoVvfHGGyqffiLY448/roQWz37wjMgDDzxAs2fPppUrVyrh0rlzZ7rvvvuSngbG50JXTeeee646RUtPscIoNq9u78Z9R2jkp4eC8y0V/CTVCZDKysqUVleNr2QF/FiPbnNN33M/PldQ/VXTc+kDJP+ATZUykY/ORHo8s/94I3rsKY3wV80RLZUPCxD+g0BWVlbCA0iPw2TEpXKuKTrs4sz9K4+TNf2BJwh8jDwD8zYtQHgzN+954Ps9Hn74YSUy+Id57MwA/+Xluuuuo88//5yWLVtGp512WqqxzNbP+fSpW2+9VW0qnz9/vhIP1QkQtl2f5ahqBC/b4pvfeTkW33XCQua1115TFzHyxvSZM2eqY3t59uTJJ59Usx+854Rnfp599ll1ghYLE17Cxa/ffvvthE6EOVVNfNIYL/fSE7ejp9gfBnxcMCcIEFvDp8bKWIA83DaHGuWGqVatWtG8fJKanmI7l2T+4nx8+IGe/F5P/fr11aNwxxqk59K/X0HzV03PpQsQXlabqfEcFL9XFZFBeS6Oy0zoV3V/sQBhMamPK34fLxCHkZ41yL8T9IObUv0yMy1A9D0TPAvAswGcqgoQfo9nAKZOnUo8O3DllVemssO2z3kfBu/l4Knnv/71r3T88ceruqsTILzHg/eIbN++PcEG3u/By8y2bNmiLlNMdgwvC4+2bduqvSE33HCDWobFgqtly5ZqpoT/ajFlyhS1b4SP5j3rrLNSPiuWYKVE5FkGLMHyDD0aBgEQAAEQAAEQCAgB0wJk5MiR9Prrr9OLL75IvFSoOgEyY8YMNUPAR9HykbRupdtvv10dncuzF926dYs2+84776i9Gb///e+VcOK9H5z0WY7NmzdTnTp14sysTpzwX7sPHTpETZs2VbMr+t6P999/X/27a9euccfw8uZ3Fm7J7gxJxgUCxK1oMd8OBIh5ZigBAiAAAiAAAiAAArEETAuQ559/Xt1/wT/g+S/7yQQIX5zDp0/x8iQWK3wjuFuJLxzcsGFDjc3FLrkaNGiQOm73pZdeIt7PoideesXihGcy9GN3k1XKMyQ8+8Eb3vl+EH2PDNvBR/JyYuEzZMgQGj9+vJolSZUgQFIR8u5zCBDv2KNlEAABEAABEACBYBAwLUD0H+b8+Jdccgldfvnl6q/7vN/innvuUXsmXnjhBXVBH58ExRux3dyE/tVXX6kjc6sm3rvBezFYJLAgat++vcrC740ePVqJjSeeeCK6Lk/fSK+fcFWdu3nDOZ+sxSd/nXDCCXT48GFVd+xxvQsXLlSnhvGytNgN/NXVCQEi98sFAZLoG9zUKzdezVqGm3rNEpOZHzehy/RLOlahf02Hmswy6F/j/WJagHBx/sHNP7xrSjzLwJux+YI/Cam6PSAsVs4777zoXSFdunQhXo7FgoUT34jeuHHjpI+QbLaDM950003qFCtemsXPzydgsSDTN7On4gEBkoqQd59DgECAeBd9zreMAdJ5xm60AAHiBmV32oAAcYezG62gf7VBgHAVX375pRIif//734k3fvNGbv6hzqc98R4IXpJ0zDHHuOFTQ23om+Kr3gPChXfu3Knu8eCjePXEszcsWmo6wUuf/eAlXHxDup54FohvUo+9J6XqRYc1GQ0BYsilnmSCAIEA8STwXGoUA6RLoB1uBgLEYcAuVg8B4iJsh5tC/2qTAHHYT55Uz/eB8KwGby43cowYL9/iI0iTLavio/NY2PCxls2aNVNH/RpNECBGSbmfDwIkkTn/8YGPxczPz3ffIWjRVgJ8LxEfOZ7szgFbG0JljhLg8YfvoCosLHS0HVTuPAH0r84zdqsF9K82CBDu2PgM43r16rnlt4xqBwJErrshQCBA5EandcswQFpnKKEGCBAJXrDHBggQezhKqAX9a5oChJcT8elX69atU8utOPFf9X/1q1/RvffeSyeeeKIE/wbCBggQuW6EAIEAkRud1i3DAGmdoYQaIEAkeMEeGyBA7OEooRb0r2kIEF6axKc66cIjmSNr2qwtwfF+sgECRK63IEASfYM1ynLj1axlWKNslpjM/NgDItMv6ViF/jUdajLLoH9NQ4BMnjyZ5s6dq0reeeed1LlzZyovL6d//OMfxDeBc7r++uvpoYcekul1n1kFASLXYRAgECByo9O6ZRggrTOUUAMEiAQv2GMDBIg9HCXUgv41DQFyzTXX0GeffUbDhw9XF+rFJv0eDT41ii/cQ7JOAALEOkOnaoAAgQBxKrYk1IsBUoIXrNsAAWKdoZQaIECkeMK6Hehf0xAgZ599NvEyLL4RnG8Gj028If2MM85Qb33xxReuXjpoPRxk1gABItMvbBUEiFzfwDIQAAEQAAEQAAF/EDB0ESH/IOa0ceNGOvbYY+OejI/f/MUvfqHeM3rRnj/QeGclBIh37FO1DAGSihA+BwEQAAEQAAEQAIGaCZgSILwMK9l9FrpA2bBhg7oXA8kaAQgQa/ycLA0B4iRd1A0CIAACIAACIJAJBEwJkFGjRlFeXl4Cl3Hjxqn3eI9I1cvIrrrqKqpdu3YmsLTtGSFAbENpe0UQIIlI+chPTtnZ2bbzRoXuEuCLU3Nzc9U9T0j+JcArE/igmGTjtX+fKjMtR/8aHL+jf433pSkBkk4Y4Hhe89RYgEybNi1asHfv3tHXFRUV0df6bcUb9x2hkZ8eMt8QSpgmwAJk0um1qHEtLe626GR+4coz4X3+saMLkEx43thbwoP2vPoAWVlZmdDPZEo8B8G/ugCJ/aNAEJ5LD8qgfe9qei4WIOzPUCikssGPEVp+5MD9q/6d9KP9Zr93qX5gGRIgfMRu7ICUqtLYz5955hksyzIDjIhYgNx2223RUvfcc0/0NZ9uoqecnBz1EgLEJGAL2VmATGyfR8fnEen8ubpkfsmU9/W/lnPHmskcghAPugDR/+rKMRyE59K/8pkSn7oA0X+0wo+J46Zf+mf+LvIPP92X+D5Gvs1+5FBaWqr8yGOmH+0323+m+qllSICkqgSf20sAS7Ds5WlnbViCZSdN1AUCIAACIAACIJCJBCBABHodAkSgU342CQJErm9gGQiAAAiAAAiAgD8IQIAI9BMEiECnQIDIdQosAwEQAAEQAAEQ8BUBCBCB7oIAEegUCJBqnYKbeuXGq1nLcFOvWWIy8+MmdJl+Sccq9K/pUJNZBv1rvF8gQATGKQSIQKdAgECAyA1L2yzDAGkbSk8rggDxFL+tjUOA2IrT08rQv0KAeBqARhqHADFCyZs82AOSyB0DpDex6ESrGCCdoOp+nRAg7jN3qkX0r06Rdb9e9K8QIO5HnckWIUBMAnMxOwRIIuySkhJ1Tn3VS0hddAuasolAUVERFRQUxJ2xb1PVqMZFAnx0a3FxMRUWFrrYKppyggD6VyeoelMn+lcIEG8iz0SrECAmYLmcFQIEAsTlkHO1OQyQruJ2rDEIEMfQul4xBIjryB1rEP0rBIhjwWVXxRAgdpG0vx4IEAgQ+6NKTo0YIOX4woolECBW6MkqCwEiyx9WrEH/CgFiJX5cKQsB4grmtBqBAEnEhjXKaYWSyEJYoyzSLaaNwh4Q08jEFkD/KtY1pg1D/woBYjpo3C4AAeI2cePtQYBAgBiPFv/lxADpP58lsxgCJBh+5KeAAAmOL9G/QoCIj2YIELkuggCBAJEbndYtwwBpnaGEGiBAJHjBHhsgQOzhKKEW9K8QIBLisEYbIEDkuggCRK5vYBkIgAAIgAAIgIA/COAiQoF+ggAR6JSfTYIAkesbWAYCIAACIAACIOAPAhAgAv0EASLQKRAgcp0Cy0AABEAABEAABHxFAAJEoLsgQAQ6BQKkWqfwkZ+csrOz5ToOlhkiUFZWRrm5uaRpmqH8yCSTAF8MWl5eTnl5eTINhFWGCaB/NYxKfEb0r/EuggARGLIsQK655pqoZZMmTYq+5kFFT/xDgdPGfUdo5KeHBD5J8EziJVgT2uXR8Xlh9UNNT8n8wp9lwvuhUCgqQDLheYPsd32A5E3MVfuZTInnIPhXFyCxQjIIz5WJ/S0LkIqKiugfBeDHSBT4kUNpaanyI//nR/vNju+pfgFCgKQi5MHnLEBefPHFaMvnnntu9HVlZWX0tf7DDwLEPSexAJl0em1qUlsjnT+3nswvmfK+/uw8A5LJHIIQD7oA4R+wegrCc+nPkinxqQuQnJwc+NHn/TMLEPZnVlaW8iW+j5GQ9iMH7l/176Qf7Tfbf6b6ZQYBkoqQB59jCZYH0A02iU3oBkEhGwiAAAiAAAiAAAhUQwACRGBoQIAIdMrPJkGAyPUNLAMBEAABEAABEPAHAQgQgX6CABHoFAgQuU6BZSAAAiAAAiAAAr4iAAEi0F0QIAKdAgFSrVNwU6/ceDVrGW7qNUtMZn7chC7TL+lYhf41HWoyy6B/jfcLBIjAOIUAEegUCBAIELlhaZtlGCBtQ+lpRRAgnuK3tXEIEFtxeloZ+lcIEE8D0EjjECBGKHmTB3tAErljgPQmFp1oFQOkE1TdrxMCxH3mTrWI/tUpsu7Xi/4VAsT9qDPZIgSISWAuZocASYRdUlKijonMz8930RNoygkCRUVFVFBQED3y04k2UKfzBPjo1uLiYiosLHS+MbTgKAH0r47idbVy9K8QIK4GXDqNQYCkQ82dMhAgECDuRJo3rWCA9Ia73a1CgNhN1Lv6IEC8Y293y+hfIUDsjinb64MAsR2pbRVCgECA2BZMAivCACnQKWmYBAGSBjShRSBAhDomDbPQv0KApBE27haBAHGXt5nWIEASaWGNspkIkp0Xa5Rl+8eoddgDYpSU/HzoX+X7yKiF6F8hQIzGimf5IEA8Q5+yYQgQCJCUQeLjDBggfey8GNMhQILhR34KCJDg+BL9KwSI+GiGAJHrIggQCBC50WndMgyQ1hlKqAECRIIX7LEBAsQejhJqQf8KASIhDmu0AQJErosgQOT6BpaBAAiAAAiAAAj4gwAuIhToJwgQgU752SQIELm+gWUgAAIgAAIgAAL+IAABItBPECACnQIBItcpsAwEQAAEQAAEQMBXBCBABLoLAkSgUyBAqnUKH/nJKTs7W67jYJkhAmVlZZSbm0uaphnKj0wyCfDFoOXl5ZSXlyfTQFhlmAD6V8OoxGdE/xrvIggQgSHLAqR58+ZRy1atWhV9XVpaGn1dq1Yt9XrjviM08tNDAp8keCbxEqyH2+ZQo9ww6fz5KZP5JVPe14UH/z+TOQQhHvQBkv+vpyA8l/4smRKfugDh/8OP/u6fWYDoIoR9ie9jJKLBQT6HVL8AIUBSEfLgc8yAeADdYJPYA5IICn+hMxg8PsiGv9D5wEkGTMQMiAFIPsmC/tUnjjJgJvrXeEgQIAaCxu0sECBuEzfeHgSIcVbICQIgAAIgAAIgAALJCECACIwLCBCBTvnZJAgQub6BZSAAAiAAAiAAAv4gAAEi0E8QIAKdAgEi1ymwDARAAARAAARAwFcEIEAEugsCRKBTIECqdQpu6pUbr2Ytw029ZonJzI+b0GX6JR2r0L+mQ01mGfSv8X6BABEYpxAgAp0CAQIBIjcsbbMMA6RtKD2tCALEU/y2Ng4BYitOTytD/woB4mkAGmkcAsQIJW/yYA9IIncMkN7EohOtYoB0gqr7dUKAuM/cqRbRvzpF1v160b9CgLgfdSZbhAAxCczF7BAgibBLSkqIj/3Mz8930RNoygkCRUVFVFBQQFlZWU5UjzpdIsBHtxYXF1NhYaFLLaIZpwigf3WKrPv1on+FAHE/6ky2CAFiEpiL2SFAIEBcDDfXm8IA6TpyRxqEAHEEqyeVQoB4gt2RRtG/QoA4Elh2VgoBYidNe+uCAIEAsTeiZNWGAVKWP9K1BgIkXXLyykGAyPNJuhahf80wAVJeXk7ffPONWh7SsGHDGpcWcKe9Z88eatSoEeXm5lYbY99//z3xusyTTjopaT5e57d27Vpq164dtWjRwnSsQoCYRuZaAQiQRNRYo+xa+DneENYoO47YlQawB8QVzK40gv7VFcyuNIL+NUMEyM6dO+nuu++mzz//PPrEjRs3pgcffJAuuuiiOAosKEaNGkUffvhh9P1OnTrRY489Rs2bN4++t3fvXho6dCh99tln0fceffRR6tu3b1x948aNo5dffplWr15NJ598sunAhgAxjcy1AhAgECCuBZsHDWGA9AC6A01CgDgA1aMqIUA8Au9As+hfM0CA7Nq1i66++mrav38/de3alc466yx67733osLhnXfeoWbNmikSpaWldP7556u8LDr49caNG2nNmjVUt25dWrVqlZo54XT//ffTq6++SiwwmjRpQo888gjt2LGD1q1bF83z7bff0gUXXEDXXnstTZw4Ma0QhgBJC5srhSBAIEBcCTSPGsEA6RF4m5uFALEZqIfVQYB4CN/mptG/ZoAA4WVUQ4YMIf4hP2XKlOgT33jjjfTRRx/R+PHj6YYbblDvr1ixQs1qtGnTRomLvLw8qqiooMGDB6sZkTFjxtDAgQNV3g4dOijhsXz5cvXvJUuW0IgRI2jy5Ml0xRVXqPd4huWVV15Je/aD64AAsflbb2N1ECA2wkRVIAACIAACIAACGUkgsBcR8swGHw1au3btqGPnz5+vxAeLk+HDh6v377rrLiUopk+fTr169Yrm/fjjj6l///5KdCxevJgOHjxIHTt2pO7du9OcOXNUPp4puf7661VdXOfu3bvpwgsvpH79+tGECRPSDigIkLTROV4QAsRxxGgABEAABEAABEAg4AQCK0CS+W3q1Kk0e/ZsGjt2LPFsCKc+ffrQ1q1baf369dSgQYNoMd6Q3rp1a7UMi/d88JnqZ5xxBvXs2ZNmzZql8m3atEmJjWHDhtEdd9yh6l2wYAG9++67aoN6ugkCJF1yzpeDAHGeMVoAARAAARAAARAINoGMESAsIC6++GK112PZsmV02mmnKc+effbZ6r1t27ZRKBSK87b+GQuUnJwctTSqVatW9MYbb6h8S5cuVbMfjz/+OJ155plq9oNnRB544AEldFauXKmES+fOnem+++4j3gRfNfH+karpt7/9LT333HPRt88555zoa57V0VOtWrXUy437jtDITw8FO1KFPB0LkEmn16YmtbW4eOEZNz1pmlajv/jDysrKaJ7YuPNjPdnZ2epZ+P9Bei79+xU0f9X0XGVlZepkP/5/psZzUPzO+0D07yb7MijPxc+SbBwM6veU/xjKSR8n/D5eZHIc8koa/TsZ5N8JvJXBSMoIAcI/ilgosPDgGY/YfSEsKvRZjqrALr30Uvr666+Jl2Px7cB8UtZrr72mlm3xxvSZM2eqY3t59uTJJ59Usx+82Z33gDz77LPqBC0WJryEi1+//fbbCccA856RqonL8yZ6PY0cOTL6OvYHXv369SFAjES5jXlYgExol0fH54XjjmBmEaun2AEimb84Hx8PrafYI5/9WE+9evWiAiRIz6V/v4Lmr5qeSxcgBw4cyNh4DoLf+Qd67I90dmYQnksPykzoV3V/sQDh//Rxxe/jRSbH4b59+0gXHkH+nXDccccZ+tWVEQJk0qRJNG/ePLXRnH/cs+DQE+/x4It+tm/fngCM93vwiVpbtmxRe0mSHcPLwqNt27ZqbwhvbOdlWDy70rJlSzVTkpWVpQQP7xvho3n5RK5UCUtkb6ZFAAAgAElEQVSwUhHy7nMswUpkr/+FLvavrd55CC1bIaALkNi/zlmpD2W9IcDig/8YYPQvkd5YiVaNEED/aoSSP/Kgf433U6AFCHfC/ON/7ty5ShC8+OKL0eNydQz6LMfmzZupTp06cXSqEyd8b8ihQ4eoadOmammWvvfj/fffV//mo39jj+HlTe48a5LszpBkXxsIELmdCQSIXN/AMhAAARAAARAAAX8QCKwA4b8aPPTQQ2pZFN9IznsqYqf+dPcMGjRIHbf70ksvUexeC156xeKEhYt+7G4yl/IMCc9+8IlZfD8I37reo0cPGjBggDqSlxNvSudTsmKP/60pPCBA5H55IEDk+gaWgQAIgAAIgAAI+INAIAXI4cOH6Y9//KO6RPBXv/qV2p8Ru+wq1jW8P2P06NFKbDzxxBPR9Xn6si39hKvq3MkbzhctWkQffPABnXDCCcRtt2/fPu643oULF6r7RHhjOouTVAkCJBUh7z6HAPGOPVoGARAAARAAARAIBoFAChDee3H33XcrD/EP/thNW/wer1WfNm2a+pxPJTjvvPPUPhAWIV26dCFejsWbzTnxjejJTq/iz5LNdvD7N910E61du1YtzeJ9J3wCFt+Yrm9mTxU6ECCpCHn3OQRIIntejsip6hJG77yEltMlgJt60yUnqxxuQpflDyvW4CZ0K/RklUX/Gu+PwAuQ6sIvdtP5zp071T0efBSvnvgeD77vQz+uN1k9+uwHL+HiG9L1xMu3+CZ1Xp6lp6oXHdb0tYAAkdVpxFrjtABZ8H9l9Pf9FXIBBMiyswqz6Lrmxo4LDNBj1/goGCCD4WkIkGD4kZ8CAiQ4vkT/mgECJN1w5SNQeVaDN5fzMbupEi/f4n0lyZZV8R4UFjZ86kGzZs2qXQKWrA0IkFTkvfvcaQEybethevO7n7x7wAxquXfTHBrWunYGPXHqR8UAmZqRH3JAgPjBS8ZshAAxxskPudC/QoCIj1MIELkuggCR6xuzlkGAJBIrKipSdx7x8eFI/iXAfwDjS3ALCwv9+xCwXBHg5eF8omd+fj6I+JwA+lcIEPEhDAEi10UQIHJ9Y9YyCBAIELMx45f8ECB+8VRqOyFAUjPySw4IEAgQ8bEKASLXRRAgcn1j1jIIEAgQszHjl/wQIH7xVGo7IUBSM/JLDggQCBDxsQoBItdFECByfWPWMgiQRGJYo2w2imTmxx4QmX5JxyrsAUmHmswy6F8hQGRGZoxVECByXQQBItc3Zi2DAIEAMRszfskPAeIXT6W2EwIkNSO/5IAAgQARH6sQIHJdBAEi1zdmLYMAgQAxGzN+yQ8B4hdPpbYTAiQ1I7/kgACBABEfqxAgcl0EASLXN2YtgwAxSwz5QQAEQAAEQMAeAoG8iNAeNN7VAgHiHftULWeaAAlXVpD24z6ikmIK1z6GqF4D0rKyU2E6+nllJYUP/Ju0yiMULjiBtOycGsuGSw+Stv87otzaRPWbEoVCxtsymRMCxCQwZAcBEAABEAABmwhAgNgE0s5qIEDspGlvXYESIH+dRqEv1lK46WkUHjAxEdSaBaRtWEpaxdGLEcNaiKjzZVTZ/SbSNK16uPt2k/b646Tt/zYuT+WJrSl85b2k1akXX3bnFtL+OoO0Q8Xx+U+/iMKX3FpzW2m6GAIkTXAoBgIgAAIgAAIWCUCAWAToRHEWIEOGDIlWPXz48OhrXturp5ycyF+TN+47QiM/PeSEKaizCgEWIBPb59HxeUQ6f86SzC/pvO/aTej/u4lCr0VER7jJqRQe+Gj8k37yFoXe+VO1/q/sdgNRl77JP/9uO2nzR5MWrkz6ebhRcwrfPPXoZ199RKH/mZw8b/PTKdxvrCNxyAJk6Kk5lJ19dEbHLj/6tZ6ysjLKzc0lPsa1aj+TTjz7lYP+7H61ny+uKy8vp1DMDKIT/ZVf+fjJv/xdrKioiPoSfox4z48cSktLlR/5j3d+tN/s9z3VwA0BkoqQB5+zAJkxY0a05csvvzz6mjsiPem3FUOAuOckFiCTTq9FjWtpcbdFJ/MLW2X2facFiLZ6HtHOz0n7z84otGQCRHthBGl7/6Xy8GxHuPV5pG3/mEIr50ZES1UREeuC8lKi1x+l0M7PKVyvIYVPv4jov3sp9Pm7R+P47vmk8TIrItLm3kHagT2Rett1p/CpZ5G2cwvRprcpfPscovz6jjiYBcidv8h1xI9m/S4lvy5AKiuPisfYW9Gl2KkHBOyJkKjKQRcgseIafoyw8hsHFiDsT11M+s3+dMbBoH6vuX/Vv5OZ4MdUAzcESCpCHnyOJVgeQDfYpN+XYGmPX5MwM5FUgPwsCsJZORQevjBKR5tynVqSFa6VT+E//Llaajxgah//lcKn9yCtVv7PQmMoaQf+HRE1Q58nqnss0fc7KDTvj8lFzeGDRLUjZZ1IWIKVSFUXIDUur3PCGajTVgK6AMnLy7O1XlTmPgF9NjJWTLpvBVq0gwD613iKECB2RJXNdUCA2AzUxur8LkBo5bNEZSWKSGjrmsgP/yRLsLRVz5G2aXlELJxzJYXPvZq09X+h0EevR977xTlEV44wRDZcWUna7i8otCCylCpc0ITCg5+OlF3/OoU+fPnndq4ianASEc+GHNuQws1PJ+0YZ2Y/uEEIEEPuQyYQAAEQAAEQsJ0ABIjtSK1XCAFinaFTNfhegMSACT0W2cORTICEf9xPoQVjokujYnmGCxpT5YBHEjeSJ4GuLZtB9MXa6KwLz5xU9vkjac3bR3KvnEuhT1ckdRdveA+zyDn1LEfcCQHiCFZUCgIgAAIgAAIpCUCApETkfgYIEPeZG20xUwSI4vHJcgq981wCmsqLhxB1vNgQMm3+/aR9+2U0b+U5V1H43Kui+z/otUkU+t9Pqq2Ll4BV3jXvaH5DrRrLBAFijBNygQAIgAAIgIDdBCBA7CZqQ30QIDZAdKiKjBEgG5ZS6P0XFUU1E9HhYtK2rI4eyVvZ5RqibtelpvzJctJ2byXasYW00oOR+hqcROFBkUMWYgVKZc/fU7h9d6J931LoL49E7h/hDbZ9R5PWsnPqtkzmgABJBIabek0GkdDsuAldqGPSMAs3oacBTWgR9K/xjoEAERioECACnfKzSZkiQLSnf0dayQElPipvfYa0eg2ISv5L2jO3RkVIxR8XprxYMNaTcSdr3TabqF5Dop/vIuF8lbdMI2rYLFLk479S6L3IJvdwj5spfEYv24MCAgQCxPagElIhBIgQR9hgBgSIDRCFVAEBAgEiJBSrNwMCRK6LMkGAhA/9QFlP3aycUNm4BdFvH486RFv0EGk7Nqt/V/zuSdIKm1bvrN1fEJ3Y+ujny2dRaMvqSL29hhH9shvRh69QaP1fIu9dNpSo3YWR/H97lUJrF0Xev2QIUQdjS77MRA4ECASImXjxU14IED95q2ZbIUCC40sIEAgQ8dEMASLXRRkhQPjM+cnXRjeOV149msIntSHavU1dXsgXDKqZkbvmEeXWodArY9RxumFeknVmb6LDB0n76zQlVCpP60LU+jy1rEpb++rRJVwsaljcxBzDS3l1I2JD00hbMSe6ZKvypslEx59ie1BAgCQiLSoqooKCgri7EmwHjwodJ8BHtxYXF1NhYaHjbaEBZwmUlJSoe0Dy8507ktzZJ0DtOgH0rxAg4r8NECByXZQJAkTRXzYjekxvMm9E94DE3uNR0JjCg2cSxdyynqysOkVr0BOkZUVuINcWTyDtX58mdXr4pF9S+IaHHAkICBAIEEcCS0ClECACnGCTCRAgNoEUUA0ECASIgDCs2QQIELkuCqIAqTzhF0Q3PhIP/chPRKuejS6Ziv2wkm8rv/j3pGXnUri8lEJPDyLtp1K1UT3MMxic/ncTaSvnkvbDf+LqDZ/SkSovuTWyp+TnFD7yk8obe1M6fxRu040qLxpEWu1jHAkICBAIEEcCS0ClECACnGCTCRAgNoEUUA0ECASIgDCEABHvhGoMDJIAMeIDJQ7+u0dtQA/XLSA6rpESHrFJ3XpeWpL81vLyUrXMivJqU/jYRjUepxuuOEJUtIs0ChMVnECUW8uIiWnngQBJRIc1ymmHk6iC2AMiyh2WjMEeEEv4RBVG/woBIiogkxmDGRC5Lso0ASLXE9YtgwCBALEeRTJrgACR6Zd0rIIASYeazDIQIBAgMiMzxioIELkuggCR6xuzlkGAQICYjRm/5IcA8YunUtsJAZKakV9yQIBAgIiPVQgQuS6CAJHrG7OWQYCYJYb8IAACIAACIGAPAVxEaA9HW2uBALEVp62VQYDYitPTyiBAPMWPxkEABEAABDKYAASIQOdDgAh0ys8mQYDI9Y1ZyyBAzBJDfhAAARAAARCwhwAEiD0cba2FBUiHDh2idS5evDj6urS0NPq6Vq3IKUEb9x2hkZ8estUGVJacAAuQh9vmUKPcMOn8OWcyv6Tz/tSth+it744AvwsEejXNpttPyaK8vLwav1/p+NGueHC7nrKyMsrNzSX+v56ciHO3n0t/lkxpl0+mKy8vVxfYwY/29c9exA8fqcz/wY/+9iP77/Dhw6RpmnJlJvSrqYZxCJBUhDz4nAXIhg0boi3Xr1+/RisgQNxzEmZA3GPtdEuYAUkkrAsQfZB02geo3xkCugCJFdfOtIRanSagi4/s7MjFrUj+JcB/FMjJyYmKEP8+iT2WQ4DYw9HWWrAEy1actlYGAWIrTk8rgwCBAPE0AB1sHALEQbguVw0B4jJwB5vDH3ji4UKAOBhs6VYNAZIuOefLQYA4z9itFiBA3CKNdkAABEAABEAAAkR8DECAyHURBIhc35i1DALELDHkBwEQAAEQAAF7CGAGxB6OttYCAWIrTlsrgwCxFaenlUGAeIofjYMACIAACGQwAQgQgc6HABHolJ9NggCR6xuzlkGAJBLDTb1mo0hmftyELtMv6ViFm9DToSazDPrXeL9AgAiMUwgQgU6BAJHrlDQtgwCBAEkzdMQXgwAR7yLDBkKAGEYlPiMECASI+CCFAJHrIsyAyPWNWcsgQCBAzMaMX/JDgPjFU6nthABJzcgvOSBAIEDExyoEiFwXQYDI9Y1ZyyBA/n97ZwFtVdG+8aFUFBVUQlQEO7EAETAAuxUTbOxuBBNRLERBxQDFJsTuxAKxUKy/CgYoYKCoHxIq8l+/+b73rLn7nq577jnPuxaLc8+ZPfG8e8+eZ96Y6ojNmTPHNWnSxNWrVy9TOFW+hBAgdevvv//uVl555RLqlbqSDQJ//vmnP1CyUaNG2Vyua0oIAc2vIiAldDvG74oISOmqSASkdHWTac9EQERAMr1nakt5EZDaoqnU/RQBSY1RbSkhAiICUvL3qghI6apIBKR0dZNpz0RAREAyvWdqS3kRkNqiqdT9FAFJjVFtKSECIgJS8veqCEjpqkgEpHR1k2nPRECqIyYf5UzvotIsrxiQ0tRLNr1SDEg2qJXmNZpfRUBK884MeiUCUroqEgEpXd1k2rNyJiDz589333//vWvatKmP6UhX7AXJ9bNmzXIrrbSSW2WVVVzdunXjVvHXX3+5GTNmuOWWW861aNHC1alTJ92mVC4NBLLVowhIGuDWkiIiILVEUWl0UwREBCSN26Rmi4iA1Cz+yVoXASld3WTas3IkIFOnTnXnnnuu++yzz2JwQCIuv/xyt8suu6SE6KabbnL333+/+/XXX2Nl11hjDXfxxRe7rl27xr574403fJ3ffvttlTpPP/10d/LJJyuIPSXSyQvkqseQgDz//PPu1FNP9STxww8/rNLwlVde6e6+++6kndlpp53csGHDchyRLs+WTGZDQObNm+dmzpzpmjVrltEGhLSUGgESAsyePdstXLjQtWrVytWvXz/1Rf8rkQ0BwW2L+Xj11Vd3yy67bNpt1YaCOgekBLUkAlKCSvlfl0RASlc3mfas3AgIloju3bsnhOHGG290e+yxR8LfBw0a5G6//faEvz/33HNu7bXXdo899pg777zzEpaDAJ1wwgmZqkPl/4dArnoMgcSKdeSRR8aIIsQmlP79+3vCmUwgrjfffLP0kyUCuZLJsNlkZJKF8fDhw919993nfvjhh9hlbEBcccUVDiIpyR6BxYsXu1tuucXdddddjrgck912280NGDDArbjiihlVzjX33nuv3xiKPl+QVZ5N9B22tdFGGznmadaI5SAiICWoRRGQElSKCEjpKiXLnpUbARk6dKjDgoG0a9fOHX/88e7ll192Y8aM8d9tueWWsc/xIGPxcu211/qfDjzwQLfZZpv5xcwXX3zhv+vXr587+uij/e7fcccd57/n5bvttts6LCLPPvusL7f11lunXNRmqbKKuCxXPQISunjyySfdxIkTqyxgogRk7Nix7tVXX62G68cffxxbxF599dWuR48eFYF9vgdZTDJ54YUXOvSZSJgHmAMk2SGQjKy3bt3asUGTbvryd955x/Xq1ct3hE2j2267LdYprFeHHHJIbN6N11uez2WWWSa7gZTQVSIgJaQM6woE5Kmnnor1bP311499ZpfDxPyt3/vlH9fng/klOJLy6xIWkKs2b+hWbVi3ir97PL0w+ky/H/zZAvf0rL/LD7gSHBEE5IwNlimIHjPVez7KQwRs55OFJ/Ef7Nrts88+sZcZhAS3AZNou+PHj/exHz179vRFJk2a5I444gj/+aijjvIkBGFX7plnnnEHHXSQ/3vBggWubdu2/jO7dI8//rj/nI9xVVo9+dAjVijTQfjoGQFJpRcIB4sc3La4lxo2bFjtvVNpeslmvJmSyXh6SUYmw/Lvvvuu33Tg2Tz22GP9cz569OiYO+aZZ57p3SOj64dsxpXq/qHOMB6stpfnTB02dUxwSWV+veyyy2Luqrgydu7cOem8h6XjvffecxMmTIjVBQG59dZbq+iFunCPxHrFpg/EZsSIEbG2sFp26NDBX1PKOKd67YuApEKoBn6HgISuFCE7XrRoUaxHSy+9tP8sAlI8JUFArth0KddsqSXO8Kf1eHrJ5vvrP5vvnpn1T/EGVMEt7blafXfK2vXdUkstFUMhX3osdj0Eg2+88cZ+HLyYcBOw+5OX2+DBg/1vfM8C1yTaT/4GD+pDIBnnn3++/3zppZd6y4iJ1c81Dz/8sP8dIQ7ktNNO85+LjUOicdWW7/OlR9zkIBDICy+8ECOmRkCS6WXKlCmx3VlIJzvr0uN/76BMcQjJ5FtvveUTOrApsPfee7svv/zS1/nKK6844qwS1X/OOee4J554otpMjS6j/Zk+fbr7+uuvXadOnXx5SAkLWARdQkyjz28248oUh9pefty4ca5v374eOvC0jRjIIfMdwtw4cODApPfJ5ptvXsUiSWHWekOGDKmmF6zKHCSK2ytyxx13OAgtgjvtjjvu6D8XYh2SL31Vu2kjX4iApEKoBn6XC1YNgJ5mk4oBSROoWlCsnFywsHwYscB6gbuACdbUs846y/95ww03uD333DOhdoyAsKvGYnj//fePWU8eeughxws0FH63hS7fb7fddv4l3Lx581pwB5ReF/OlR3ac0R+LkxNPPNG74iFRF6x4CJx99tnefQt5+umn3XrrrVd6QNWCHoVksmPHjt6d0STcFOB7fk8kjzzyiLdikImOBa9ZOVPp8rfffvPxAuaCmerZrwWQ1lgXcW21xf+oUaNi1hAC0TfddFPfLywk/JZM0AHWYmTkyJH+/6gLVrzrv/vuO59IwpKLvPbaa65ly5Y1hke+GhYByReSeaxHBCSPYOa5KhGQPANag9WVEwH5v//7P7+riuCGEQaJs8NqQeG4DJjvcTzoQwJClitbNBHrYS/g8LpoMCTWWrJlJUrbW4PqrhVN50uP2RKQkAClihmqFYDWYCfzRSY5VBIh21I6ZBILCC5YLFpNcMMklieTjE01CF3JNX3JJZfEyAWWCVKOm3Tr1s1jjRWLuTaZhPOrzZ3JCAgbAcTlhUkF2FwyF9mSAyrDDomAZAhYMYqLgBQD5ezaEAHJDrdSvKqcCEgY7ErMBj7KJgRHmkvUdddd5/bdd9+U6sDET8YXhJct8QT4I0eFnUFevuzIWeperC2hr3nKxlQghkC+9UjF6SxarQO4glhGHtz29tprL2knSwTyRSbD5tPR5eeff15Fbzy/ZLcjNkuSHQLMZy+++KK/ePLkyW755ZePVYRFmYQc8dJcJ2stHQJCrEdozd5hhx18RrNysTCLgGR3Pxb0KhGQgsKbU+UiIDnBV1IXlxMBIfDU3KOi1orwJRaNAYmnkNDdgF09rk9l7setYJtttvH+zWSEsZd1SSm8FnQmn3q04aazaKVsqEMWUyQgKIdMOzWl9poik5w1cc8993h3u3BH/sEHH3Tt27evKThqdbt9+vRxuMIhFstjAyK9MechsUHz9ttvpz3OdAgI5/aQihfSwz8TvucZre0iAlKCGhQBKUGl/K9LIiClq5tMe1ZOBISxW4AjLyaCTxs0aOAhwf3KFiLJfPoJjmV3zc6FWGeddfwhdfF22/Bv/+abb1yYoS+MByHTS6Z58TPVX7mWz1WPUVzSJSAkErjgggv85VE3vnLFupDjqkkyaeMiocABBxzg/zzssMNiiSIKOe5yrPv666+Ppcolps7mvX///denNjZdEyeXrqRDQMK67rzzTu9Gh+AOy0ZTbRcRkBLUoAhICSpFBKR0lZJlz8qNgISnWpORhWwt7NZx4BUCoSCrFQHmuExBNjhZlziPFVZYwWfICVO3cn2TJk2qoAuZYbePsgSfkw2Gl/H7778fixHJ1BUhS/WV7WW56hFgwpPQ0yEgxIzgbmVnvmDBwpIlyQ2BfJDJ8CT0VLr85ZdfvO4tRoFr7ewPnn87qye3UVXe1ViPLMsf7q2Wmpw5kI0XJFGcXIhWeBJ6KgIybdo0H1diWa6Ys4ntQcJMXLVZGyIgJag9EZASVIoISOkqJcuelRsBIfiUU3UTCRlxCEZFQrJh+evjpYiM1oVfO9lb7MDCeG1BUsJ0n1mqp2Ivy1WP2RCQ8GA0zjLgnpDkjkA+yGS6BIQFKimz2QA444wzXOPGjX02M9tUwFVo2LBhuQ+qAmv48ccfXZcuXfzIwRc3VTZnSFFtmanAFoyxipCaF+sTejALFNemQ0CwRDPHXnPNNT6zIUlDcI/EfdYyDhIUf/jhh9d6TYiAlKAKRUBKUCkiIKWrlCx7Vm4EBBh4GfLSw0phwgsTa0eYfveBBx7wh2jxGz7GuFlxgrkFkieCFAJCJh2uZ5Eabad3797upJNOUradLO9JuywXPWZDQFgw2e44QejJiGyOQ6uoy/NBJtMhIFiwcJuLd6q9AY5+sYJIskMAa28iFyssFZy3w9wY6jyaSS4dAkIZrCph5quwx7SFJbsc4rNEQLK7Fwt6lQhIQeHNqXLFgOQEX0ldXI4ExACeO3eu41AyiAXuGOFpuVYGsoHrVZiac86cOX5nj5N30xFOCKYdAjBpy+JO0rlWZVIjkK0eSd2KbjjITFKzCORKJokvgGA0atQoaUYz4rKuuuoqvzgNNxJYsJKWuxxiBmpSkzxTnOPBgYChkJkKa4VlCSTVLocEQiBOOeUUxwn0JuH8ai5Y8SxTXIurV5RQskkEESqXjGYiIMGdxA2G4ps1a1bldOToTf/TTz85diV4sMNTlK0cDHbChAn+gBo7xTKTB0cEJBO0iltWBKS4eBeytXImINnilikBybYdXVdYBERACotvNrVnSyZDApJuu7Nnz3bEg7CW4fR1ncuTLnKpy/FssekC0WjTpo1r2LBhtYsgjPPmzauSrpdCmc6vuGOR7IM2V1111bJL7CEC4pyDUPTt29e9/vrrsRsJ0xmsNgzEww+Q0yhJgWZCVoIePXpUuQFxbcBFgdNnW7VqlfqOjpQQAckYsqJdIAJSNKgL3pAISHWIM31BFlxJaiArBERAsoKtJC/KhoCU5EDUqYwJSLlDVvEEZOHChW777bf3JktIB59JIclpl/hHkw2kadOm/j4g4Gjs2LHedxo2irkTH+iJEyfGysycOdNhkjvooIMcAWjZiAhINqgV5xoRkOLgXIxWRECqoxz6KBdDB2qjMAiEWbAK04JqLRYCYQxIsdpUO4VBQPNrVVwrnoAQgIlVA586yAUpzzB7EdCFRSRMuUaWGIiHBes99thj3rcyPF2YVG2kbMvW+oF6REAK8/Dno1YRkHygWBp1iICIgJTGnZj/XoiA5B/TmqpRBKSmkM9/uyIgIiBVELDsHwQXhVliLC0hpIPMB/jzbbHFFq5bt27u9ttv93VgKTn00EN9yklST37//feua9eu7uCDD/ZZZ7IVEZBskSv8dSIghce4WC2IgIiAFOteK3Y7IiDFRrxw7YmAFA7bYtcsAiICUgUB8uKTpYIDuwjWMsGHdsMNN/RuWMR8kFGkXbt2Ps+z5dKePHmyJxtkOSDbAbmZR40a5U8dJkA9W6kEArLk5xmu7hOD3ZLeN2YLU41cJwJSHfY6E8Y6t2SJW9Ll4BrRSbaNioBUR+6YY47xLqbZxK5lqwddl38EcA1mE2zEiBH5r1w1FhUBDgolqNkOvytq42osrwhofhUBqYKA5b7nBNhopgj7DYJCekmIAaf+PvXUU74ODvjB+sGhXO3bt/fWDywiF110kbvtttt8XmiIy1ZbbeUuuOCC2Omkqe5oEZBUCNXc7yIgIiA1d/cVvmW9IAuPcTFaEAEpBsrFaUMEpDg4F6MVza8iIFUQYLFvVo7oDUje7GnTpjncsciNT6ascePG+VMuCUy/5ZZbfNperCdDhw711o/x48f7GJDhw4f7DFoQE1y4+Pzcc89Vy6/P5BKVyy+/3FtTTFKdePnxb4vdyK8WFeP5yVsbC3+Y7maMGuTWO+umvNVZjIqaLlPHHb3W0q5Fw7oFaW7UN4vcu78uLkjdhar0x5dGO+eWuOY7HlqoJgpSb4eV6wpFAgAAACAASURBVLlDWi9dkLp/+etf98lv/7oFi5cUpP5CVTqyzwlu7zMudCu3zDx7X6H6lE69G6xQz7VerjDP5I8L/nVz/65depw141s3cvBV7sIb/+suXFukfh3nmi9T1y3foE5Bujx93hL395Lapcunx9zvlrglbs+Da9fJ1+iydaPCPJN//L3EzVm0xNWy6dX1P+1Yd3yfS9yqq9eu+XW5+s61LMCap+KD0InxIM3d1KlTq014xHt899137qOPPvK5nuOl4YV4bLLJJj42pGfPnp44bLDBBv7EUSwlHOg1aNAgHzdCat4OHTpUaefee++t1u6AAQNc48aNY9//9ttvBZmMVakQEAJCoNIQ6Nixo5s0aVKlDVvjFQJCQAgUBYF46+l4DVc8ATErx5QpU9yyyy5bBaNE5IRzQ+bPn+9WW20175plsR+cWsnfnTt3rpKGl6xZWE3inRlSlLuhBBuRi0AJKiXLLslFIEvgSvAyuQiUoFKy6JLm1yxAK9FLNL+WqGKy6Jbm16qgVTwB6d27t0+3y0POzpgJrleQEywZlnY33v2GhQTrR69evXzw5owZM1z37t3dYYcd5kjJixCUTpas/v37eyuJxPnzUxQkWR53gl6Q5aFHRqEXZHnoUvNreeiRUWh+LR9dan4VAamCAPEZ/fr182RjyJAhrk6d//qeDhw40I0cOTKW4SrRI0DA+ZgxY9xrr73mWrZs6RYsWODatm1bJV3v6NGj/XkiBKZDTiQiIOV0D+gFWT7a1AuyPHQpAlIeehQBKR89aoOnui4r3gLC+R5dunTxcSCQkE6dOjncsQg2RzgRvUWLFnGfgnjWDgoeddRRbsKECd41iwMOyYDFC8GC2cvrkcpuNHpBZodbKV4lAlKKWsmuTyIg2eFWaldpfi01jWTfH82v2WNXaldqfpUFpNo9OX36dH+OB6l4TTjHg/M+CChPZf3AhYsT0k1w3+IkddyzTKIHHZbag1Hs/ugFWWzEC9eeXpCFw7bYNesFWWzEC9Oe5tfC4FoTtWp+rQnUC9Om5lcRkIR31q+//upjOAguJ81uKsF9a6WVVorrVsVBhhCbRYsWuTXXXNOn+pUIASEgBISAEBACQkAICIFKR6DiXbAq/QbQ+IWAEBACQkAICAEhIASEQDEREAEpJtpqSwgIASEgBISAEBACQkAIVDgCIiAVfgNo+EJACAgBISAEhIAQEAJCoJgIiIAUE221JQSEgBAQAkJACAgBISAEKhwBEZAKvwE0fCEgBISAEBACQkAICAEhUEwERECKibbaEgJCQAgIASEgBISAEBACFY6ACEiF3wAavhAQAkJACAgBISAEhIAQKCYCIiDFRFttZYzATz/95P744w9/0GOqs1Tmzp3rFi9e7FZZZZWM26nUC04//XQ/9KFDhxYcgn///dcfzlmnTh3XokULt9RSSyVsc8mSJe7HH390jRo18v8kVRHgfCGwXHHFFdM6syi8euLEiW7QoEHu3HPPdZ06dRK0FYyAnsnapfz//Oc/bvbs2f4dxxlkyUTvw8Lo9vfff3c//PCDW3fddV3dunUL0kilrHtEQApy+6jSXBG4+eabHSfAcjikyT777OMuueQSt8IKK1SpfuzYse7666+PlYWonHDCCf5foSaIXMdXKtfvtNNOvisvvvhiwbq0YMEC16dPH/fss89WaePMM890p5xySpXv/vrrL3f11Ve7Rx55xP3555/+tzXWWMNdfPHFrmvXrgXrY22p+KuvvnIXXHCB+/DDD2Nd5n4/6aST3LHHHuvq1asX+/6pp55y7777rjv//POrkHf0APGEdO622261ZejqZx4R0DOZRzDjVPXzzz/HyP2rr77qDzc2YXPlkEMOcZMnT3Z33XWX23bbbVN2Zvz48W7AgAF+08Fkyy23dFdccYVfCIei92FKOHMqcPjhh7tJkya5Bx980LVv3z6nuqIXV9q6RwQkr7ePKssHAjfccIMbNmyYXzQdeOCB3qphC9KDDjrIXXnllbFmmAQuvfRS//dRRx3ld9UfeOABv3g98cQT3TnnnJOPLpVtHYUmIOzUszBmwl5nnXX8gnfatGkxMsJOPMTShIUxC2QsJOienaaHHnrI/3znnXe67bbbrmx1kWpgX3/9tdtll118sc6dO/t/LHRYcHC/H3rooe7yyy+PVcNzwfMB9iuvvHLsexGQVEiX9+96Jouj31tvvdUNHjzYz2/McyZsDJx11lmuW7du7vbbb0/Zmddee83PoQh1tWrVys+JzI2tW7d2Tz/9dMyarPdhSjhzLvDYY4+5119/3fXt2zdj63Oyxitx3SMCkvPtqAqSIYCJP1MrBATisssuc0zU66+/vq+endyePXt6UhLu/tqCNtzNff/99/0OE2XfeeedpK4+la69TAlIpvrEooH1gt0+Jm5zo4NgMuGiP3P/wuzMohp56aWX3Jprruk/85LmBd69e3d32223VazKrrrqKr9jyiLk2muvjT1XH3/8sdt///09Lm+//XbMNSMTApKOXtMpk++5oBKUXWxc9UwW565auHChY36FKDz66KNuk002cViedthhB2+tf/nllz2ZSCW8z3r37u0uvPBCvymDzJ8/32222Wb+MwRkvfXW85/1PkyFZvq/Y6lCcBnOVLJ5pitx3SMCkumdVQHlv/jiC79zE09Y2OMKw6R4xx13uOOPP95PhuzIsEOL21STJk38ApKFI2SB3Wx8zXHDSeW3am3iv0o9JlhBttpqK7/T+8EHH/i4gKlTp7rdd9/du+i88sorVbp72GGH+cVYuibuclQri3YwisrSSy8dW/RHCQiLk/79+7s5c+Y4XKQ23HBDN2PGDO8WRewAgi7BN5P4gag+P//8c7fXXnu5TTfd1Fu3kFGjRnkXu+hOfviyNd2Xo76SjSm8/6MuHVzXr18//wxC3Hv16uXOPvtsN2HCBL/Q6dixo1t22WU9gd9+++29hclcsOrXr+8thpSF7ENy0InJ33//7W655Ra/yPn222/9s3bwwQdXcfdCb/SJe+T555/3Gwf4qN944415uXfKUde//PKLx/qNN97wOtpoo43cGWec4XfFTcyyiy7vvfdeP6fut99+3tLL/TB8+HD3+OOPe4siuuNZPvXUU6u44SXDTs9k4e8sSAaW+K233trdf//9/lniuUDX6CpdieqK67ie523EiBH+udb7MF0045ez5433HtYrni2shZA+1i7MlfaeYr5jE4gYPGJCcHNl84z1Ce8z5sp27dr5d6mRw3R6V2nrHhGQdO6KCivz2WefxdyabOhmdeCh4yVoixgWK+zAIuxus0BksYKJmb933HFHN3PmTPfee+/5lySLpIYNG2aM6Lx589wWW2zhr/vyyy/9rgR+sRCgI444wu+yhwI5uu6667yPLAumShQmv08++SQ2dHbi+AcJhJwhUQJy0UUXuTFjxnhczzvvPMcCFJLHhMrOHdfy0mOiZeHJJJuNsPA65phjfPtYQxD0hd7wgzVXI6ubslzDfYcrV6UJhHCbbbbxC1VejFGxhc7RRx/tyQh4YXVCT1yDayIxUTyP9uzivoFeeU6bNm3qP/OMQiBMWPw++eSTXu/4qlvbBLBTH8J9xuIKn3TaRNiJJS6rEPdObdc9ixr0wLMI3uyCWwwWzx442rOJi53phu+MYELUef4ghPihgzv6i5L3TLDSM5kJWumXtbmLBS7PChty6HuZZZZJv5I4JbF68u7lmeQZ1/swJzj9u4hnCP3wbPKegdwjWN6xwIfzHZs2zZo1c6Hlnt95J7LG4XlibmVzNN2N1+gIyn3dIwKS2z1bEVdDSHD74GUJu2cxY4sYAGA3h11XCw7nQSZYjkmWRQ4ycuRI/yLdc889s8KM6wcOHOgXpixQkYcfftgH5IaLIascdx8W0PECnbPqQBlcZPEVN910k9t1111jixw+oCvDGMsE1hNc5yB7e+yxRxU/ZiZldoAgfskyWSWDjMUrEzMvZawpCLtIuCqEizCrA3/bcePG+d36Dh06lIE2MhuCWYxCwhbW8Omnn7p99923iktbKhcsrmdBS1wVu3sWGGtWJos5YXHDs0YZXohdunTxTVOOjQAjILxs2dXHQtqgQQNHwHwh7p3MkCu90jZvGVmkh2zwsNMauiTagog5lOcRFx7wZkMHSwkLJOrCuoXl8pprrvGbQ5TLRvRMZoNa6mt4Dmy+pTSbLLkm1JgyZYo74IAD/MKWeASs2nofptZFshL2vLEBwEYrLsBGynk2WGcgNt9FCQibAWymbbDBBr6cWbvirU/S7Wm5r3tEQNK9Eyq0HLt1LGxYdIYxGUZAWBiyw2Py/fff+8k10U5tNjAaAeLasA+YnnnpEnjLzl8oL7zwgs+wFL7ks2m7XK6xwEfIReheZxYQLB8EOrJ7c/fdd/sXGoJ7CO4DWLpw+QiDmbPFZvTo0d5iFd0JxM+Zl+kzzzxTLbMLiQfoV7gTlW37tfE63N+OPPJITxbCJAw2lunTp/tdddytcINEUhEQCL35lFPeMGYndfXVV/cxO5B4dAXZNIHUY+W0eBN7IbMAatu2baxcIe6d2qi7aJ+NTNvONb/jM87Ch3Tjli2OZ5MU5Fi3wlTUXMeixqyU+cBEz2Q+UExcB/pCb5DGaDbATFvmnujRo4ffrQ+fYb0PM0WyanmeN+J22BhjAwXBVZI5lXkSrJFEBISNNHPjohzuVGyW4TnAuzNTqYR1jwhIpndFhZVn541YDhYivPBMEmXSsQDw6MMYwsYLlWwdUcGtwAKP7Td2YTE140pC0HJoQbGYAVxOIBqh2IIbP1ksNJUsnKeB5QhSgftU48aNY3DYro998dZbb1U7R8UsJ5Rh53XnnXf2rjXmSsdOj7neWD1M4PECxmkfnbBbjkUjdKeydrCyhXEI1GkuJ5AQC1SvJJ1aoHm4Qx6O3ywkYaB+KgISTcNrLnAWHIv+cKNKJOYOF30hh+VT3TuVpEMbKzEc7J7GkzDJRqIEEaaXZGmU9UyWzp1l86+lFY+6rhJjxzMUFVyHmWtDIR6Odx3zbdTdTu/D3HQe73mD7BF7yhqEzU4kXQJC2c033zy2qaB1T3X9iIDkds+W9dVMckyCPERMbhaExaATERBerLxgSX9L8F08wV883oRrmULsGsgHkyw7qaGrjv2O29DJJ5/s/xFzEopllIh3XVkrLTI4Mnlg2cCyYMGKYZEoATnttNN8gHIoZG655557vImfXTcEtxDuCYKNLRgyims0AJ4gWs6rYJFFcgDzdbfr2GHC5BwvcYAtZIlHMBN3JekRn2RiMCyYNTp2iCNWipD450pALC0k9bZp06Ya3GwGQGaTEZBU904l6dDGym4qLlfhbqn9xiaBWaUSERCCmCEYWC1YHMUTPZOlc2fZ3AVxYH5j0+WJJ56I7bLb5kG0x9GNNdwfmT9Jq40lGzeh8J2s92FuOo/3vHHwI++pfBAQrXtEQHK7QyvoanZaWGAQy8Gu9VprrVVl9IkICK5a7NKScSceyaCSf/75x/+LCi9fS3mHTztxJewakV0Hk3NUzG8atyEWw6FY8Cw+mTaxVJD6YkPljAjSNyZy3TECAn4cdIXZN1mcBRnSLPsOmUEgNwSqk5UnFPRoblx8D7m0A/GYiOP5qVMvL1Ve2BAhE+om4xZENHqmRaXoFIxxa0RI6ED2lVDMUmk64TcjILhvEX9lkujZjVpA7EyBVD7ryQhI2Md4906l6C8cpy1IsRZHD1UNyyUiIOYuBREhxiae6JksjTvLAsPNDcdcscLnlE0iXJ2jArkwgsHcRxwC7zw2BYndCskH1+p9mJvO801A2HzBJZWzqzjDSuue6vqRBSS3e7ZsryauAl/yRBaERIsYS5lKQBa71XbuAz7qSNTFKh6AZkXht2SLHx5o3HGYnMOd8VmzZvm0hEilpm1l7JBHXKaItUBfoR+54R5OukYeCWx87rnnYmmQ2aEjUw/BroiV40RYXKNSiZ3jQT8gH4nuAQt65t7BX3r55Zf3VZvlJNHuf6r2y+V3c0OLWvyIu2KzALKOpYs4AsTODQljDfg+XQJiVpWoqweZ1diQsPshGQHJ9d4pF92F4yAJBO5TUZdSzjpiM8U2YRIREDsTCfIBCTHBYk3Kz3jPeRRHPZOFv7N4Hgk+x3pp5xrhjmVJHDhgsGXLlik7wvON9QTrM5YtCGy8syn0PkwJZdICuRKQ6PNoSQHSdQOvxHWPCEhu92xZXm07KQyOXevwIMGNN97YB2UlO03ZdlIpR6YOArsIfIYokFWChWgyYdHM4pmFMIvOqBAUb/nybdecsgTDE3vAIpfrKz0A3YK62YGJntmBdYk0kNFJF9IJ+eR73DxY7FAWMzSudQiplNFjNIg5nk5nz54dO73c/GGj5dgVtAO5rM/s9uOKQhCgZT0jNzuB1pUqYTYd7n+eDfAhloZnK0oUzIJBBjv+YZEiKDJdAkJg9N577+2wXPAs8TzjVoe1hYx4EJt69eoldMHiENBc7p1y1XO4CMXNBkKOfzjWynDOSkRA2DHHIkxcELvhuOahlyFDhngrGckDkh2epmeyOHcW1lzeT1GLrgWLJ8poF+2dbTzwPd4FUeGdbCmx9T7MXre5EhBa5l2LexzzMp4byJtvvumaN2+esmOVuO4RAUl5W1ReAQvgjjdye0FaMHG8MxswPRKwhSuPCZYQsuwkchkI27IHMRHyoW8sL2N286LBsrgGEYcSNVNXkjaT4cjikIMeo5Mui06yLeHqxA46BNJ2Sw07CCQLU9zcWIAmE4tdSFYmDDpn15AsQWGmGO4dznPJNoVzOekc6xObAnb2jo0NXZAkItQHB2Th6sHiFiFuBz/xRM+uuXGRBQYrFEKALM+RnQPEd9F0k7jucVBevAQGudw75aS36FjY7URnEEcTCB7zqbnXJSIglMfKi15wxzNBv7icrrvuunoma/jmsUMBmSvJyBiefUXKZCwjbJKlc1BuSEDiDYt5nucM0fswe8XHe97sHI4wC1Z0vrNzQCD/xIygV4T3Fs9jugf2VuK6RwQk+/tVV6ZAgMUkZmNcaWyHu1CgYX6mLf7HPSTb8ykK1b/aXi9xGN98840ndHa2SyHHBIllx597hwVvaIUrZLu1pW6eLdwaWazixpFsx5vdOHa9eQaTxRwkGzsHIeIKQlscvpWJFPveyaRvNVkWXCASkJC11147LdepaH/RLQsedJvtYWfpYqBnMl2kar6c3ofF04EREBKAEG9p6xCSDRR6A7S261kEpHj3qVoSAkJACAgBISAEhIAQKBMEQgISL7NdmQyzIMMQASkIrKpUCAgBISAEhIAQEAJCoJwREAHJXrsiINljpyuFgBAQAkJACAgBISAEKhQBXBPHjBnjz6cijkuSPgIiIOljpZJCQAgIASEgBISAEBACQkAI5IiACEiOAOpyISAEhIAQEAJCQAgIASEgBNJHQAQkfaxUUggIASEgBISAEBACQkAICIEcERAByRFAXS4EhIAQEAJCQAgIASEgBIRA+giIgKSPlUoKASEgBISAEBACQkAICAEhkCMCIiA5AqjLhYAQEAJCQAgIASEgBISAEEgfARGQ9LFSSSEgBISAEBACQkAICAEhIARyREAEJEcAdbkQEAJCQAgIASEgBISAEBAC6SMgApI+ViopBISAEBACQkAICAEhIASEQI4IiIDkCKAuFwJCQAgIASEgBISAEBACQiB9BERA0sdKJYWAEBACQkAICAEhIASEgBDIEQERkBwB1OVCQAgIASEgBISAEBACQkAIpI+ACEj6WKmkEBACQkAICAEhIASEgBAQAjkiIAKSI4C6XAgIASEgBISAEBACQkAICIH0ERABSR8rlRQCQkAICIESQOCjjz5y//zzj9t0001dgwYNitKjb7/91v3666+udevWbqWVVipKmzTy9ddfu99++821adPGNWnSpGjt5qOhOXPmuBkzZriVV17ZrbnmmvmoUnUIASFQJgiIgJSJIjUMISAEaicCv//+u1uwYEGVzi+11FJuhRVWcPXr16+dgypwr9ddd13fwquvvupWW221Arf23+pPP/109+yzz7qrr77a9ejRoyht0siJJ57oXn75ZTdo0CC3zz77FK3dfDT0wAMPuMsuu8ztt99+7tprr81HlapDCAiBMkFABKRMFKlhCAEhUDsROPfcc93jjz8et/OdO3d2J5xwgttmm20KOjh294cNG+ZatmzpzjzzzIK2lY/KRUDygWLh6xABKTzGakEI1FYEREBqq+bUbyEgBMoCgZCALLfccn5Mf/75Z5WxjRgxwm2//fYFG+/777/vDjnkELfOOuv4Xf5SFxGQUtfQf/snAlI79KReCoGaQEAEpCZQV5tCQAgIgf8hYATk+OOPd+edd57/duHChe7tt992559/vo87aNGihXvjjTcKhpkISGpo5YKVGqNoCRGQzDHTFUKgUhAQAakUTWucQkAIlCQC8QiIdRRrBAtfBEJC8DPB17fffrv/DvesuXPnuldeecW9++67bocddnB77rmn/+0///mP34H+7LPP3PTp030QMEHbvXr1cssuu2wMC8oQ1P3II484LDDHHnus/w1ryK677hort3jxYl/mvffec1OnTvWBxRtssIE76KCD3BprrBEX29dff92NHz/e94G6t9hiC9etWze38cYbVytPsPXDDz/sPv/8cz8m6t56663d3nvv7erUqVOlfCILCGTt3nvvdR9//LGvY7PNNnNbbbWV23nnnR1xNenI33//7UaPHu3x/P77792GG27o9t9/f3fPPfckjAH56aef/DWMc/bs2W7ttdf2bnPEitStWzfWLDqk3vbt27vll1/ePfXUUw7yR7wP/TzyyCNdw4YNq3QzWQxIOpj99ddf7o477vB1Hnjgga558+ZV6v/333/979xXBxxwgCe7SLpjsspefPFFr+tPP/3U32vdu3f392D//v0VA5LOjacyQqDCEBABqTCFa7hCQAiUFgLJCAjEYccdd/QdJk5ko402cvPnz/cLa2To0KExgsLfkJXTTjvNffHFF55I/PDDD9UGSxYnXLosKxGE4LvvvqtWbrfddvP1IywkTz75ZDdp0qRq5SAWQ4YMqeYiNnDgQDdy5Mi4YN95551uu+22i/0WEq3oBfTvxhtvrLIwj0dACOSHgEFCokJbN998c7XFfbQcrm/gl8zaFA1C//DDD91RRx1VzW2OuukPi3sjUDfccIOPtYFIxusnBBGiAzkxSURAMsGM4HXI0VlnneX1GAo6Pfzwwz1BfOuttzxGmYyJuq6//np32223JXywFIReWnOOeiMESgEBEZBS0IL6IASEQMUikIyAfPLJJ373GHnyySe9VSAkIHzPwnGXXXZxa621ll/wrr/++u7QQw/1lgo+X3HFFZ5sTJs2zfXp08eTjZ122skvhJEpU6a4yZMnOwgDu99kW0KwcGAFQW666SZPRmjrmmuu8Tv4v/zyiy+L9YUFNRmpbPeehewRRxzhr6XNPfbYw82bN8/dfffdbuzYsY7gesgJC3NSzNJvFv977bWXO/XUU92KK67o3nzzTQc2yCWXXOIXySbxCMjw4cN9piX6TL8Y8wcffBCrA9LFAj+ZQBauu+46X4S6GCdpZG+99dYY+QoJyJIlS9y+++7rF/fbbrut6927t7dkYNU45ZRT/JhYmGMNQIyA8HnLLbf05dEpFijIgeFlVij+jkdAMsVs1KhRHkP0+9prr1WxyuDm9+ijj7qjjz7a9evXz2U6JsgKlhUEixyfyexGnffff7//XgSkYqc3DVwIJERABEQ3hxAQAkKgBhFIRkBwJxowYIDvHYtUFvghAcEiApEIU9FCJg4++GB/DTv55lLD37hO7b777v635557zrsKIcliQIhHsYU7JATLiAnuSl26dPG7+VdeeaV3x0KOOeYY3zZE6PLLL4+Vx90HN6SOHTvGrAK4k0EYsMy88MILVdytbOEMwWGn3iwJ8QjIYYcd5utmEc1i2gQrUKNGjfy/ZIKrUocOHTxpCMfCNSzKIQuMKSQguFP17NnTEzN+Cy0XLPjpP+5bkDbECAiEEatOmGYZcka7jJVxmMQjIJliBiFo166dr/LBBx/0xArBsgURQnAHg7BmOiYI4/PPP+/J4+DBg6tADPnCOiICUoMTjJoWAiWKgAhIiSpG3RICQqAyEDACQmwG7j/44rMwZEGLVQJhwX7ffff5zyEBwcqBtSCUhx56yC/CsTKwqI2KuePgksRCGElGQIgzsHL490djKbAUYH3A4nHxxRf7+jbffHO/kCe+hEV9MrHx8z876KGEC2esKqussor/OR4B6du3rxs3bpwnMldddZVfWIfxF6nuJlIRYxlCjOyF18QLQh8zZoy76KKLfKwKC+1QcJGCUPCbWQKMgOAGZRYPu4bYEXNLw3JjhCkeAckGM7sGC4XdV3avoC8+I5mOifFBQBkjn0NREHqqu06/C4HKRUAEpHJ1r5ELASFQAggkOweE7rG7zsLa3KFCAoL7VBhQTnniMSAXUeuDDdV2rC+88EIfu4AkIyATJkzw5Qg0x90qKiw8CTTGzYgdb2Ix2rZt64vh7sPZIskEaw1WGxbnFkAfljey8dhjj8WC1+MRENygwoP6sPxgrSEA3Xb/k/XD3MYSZRyLR0CwCOGelkxC3JIREIgnAe8IFgVc6pB4BCQbzCzWgzpxm+K+gozwGRJprn6ZjGnRokVuk0028f2MdyikCEgJTDDqghAoUQREQEpUMeqWEBAClYFAPALCIpidfHbxWfw3adIkBkYqAmLB3+bTH0Xx7LPP9vEk55xzjl/cpiIgZDdixx73HNx0okJMB2TGLC7EhmCxQVj0EkuSTCAJxKcQZ2EB92F5s6aQZYr4CiRRFiyC9rFERM8ygZjgOpXsZHkW/ZCzROOMy+Hw9wAABkVJREFUR0CwcGBlghwSAxJPGL9ZdpIRENy81ltvPV8F/TfCGY+AZIMZ7m+cJYNLGi5vEAfLchYS2UzGNGfOnNghme+8806V+5RxiIBUxhymUQqBbBAQAckGNV0jBISAEMgTAsliQOI1kYqAkGGKxTaLbgsoD+ux+IwwliGZBYTFKelZ2TFntzwqFrhtfv4sdFnEI6HVIhFcxx13nN89hzhZMLOVJfUvQdrISy+9FMvcleogQgLeiaOAaD399NP+erAILSTR/ljsTDQGw8rFIyAW+J5ujEMyAkJgucVmEIfRuHFj33Q8ApINZtRlMRm4SpESmb8J7idexSSTMYVWG4gqpDkUEZA8TRKqRgiUIQIiIGWoVA1JCAiB2oNAvgmIpWfFisLCvl69ejEwcI/ifAriM0j32qlTJ/9bssU350Fg3YiSAKvUFsPEr9iZJcRSEFORatFPHbhv4cYVBmtb3UZ++JuzPZZZZhn/UyoCEmqfIH6C+SFexIkkEs786Nq1q/8ZV7Po2SbxCAgWIWI54gXQx2snGQExC0yU6MUjINlgRn/COBPrn6V3tr8zHROWH7OqRAmeCEjtmYfUUyFQbAREQIqNuNoTAkJACAQI5JuAhClaL7vsMn/woIml042mzQ3PG7H4gFBJltaXTEfEC5grU5huN1zIWhwB7UCI+B8hBfAZZ5zhd91ZrBIkHtZB6laLKSD7FqlsOcwwTBuciIBMnDjRn29CULjFT1DWLD7hSfPxbkBcoMgQhjsYFh9ckegf35M5CiyR0HL0888/x0hc9HwQ0gwTtE8a4qZNm/prjYDgXsVns+4QxI2eaDvqOhePgGSDmY3ZCCN/k92MwyVDyXRM5rKF1QucOFQRwSULUsrY0rUQaWIQAkKgchAQAakcXWukQkAIlCAC+SYgDNFcbfiM9aJNmzb+rAosHQg76KSPNSEFLTvZLBbZzScWY+bMmX6RjAXFUrNSnsUzLjxYRnC7QcJDC/mb7FXEG2BpYUef7E4s5rHI8B11kHXJMj0R50Kwu9WF+xGLbKwoiJ2BYv2NWkBwBaIO3K5oj8MLyQ5GvzmUEaH+Zs2aJb0DaIcYGYQUx6Qp5rrw0MAo0cDKYyfTE/vC2DjNnQxlyKWXXupIEYyE54DwNzha0Dtt0HcI26qrrhrrZ6KDCDPFzCo0Swt/x3N74/tMxhSSV8bCmCBekCkTEZASnHjUJSFQwwiIgNSwAtS8EBAClY2AERACle3gvWSIhFmm4qWL5drorn1YHwftcXheVOKdrA1JIAgcCXe0w2uxMBDQHk3Pi7WD8RjpsWsgRASKh8HpjInUuZybEQpuUJyXYVm17DcjIFhHbLGOxQTrB5aYULC+YL0Izy9Jhq9l9QrLYJX46quvvDUmzBhFGeJUsHbYWR92HWSC8Rv54HsjIJA9LFW4lZkwVoiMjc2+JwEARC+aJSxTzKw+iIFhEab7DcebyZi4DrLF4YmQSxPGiIWHmJJ47nWV/dRr9EJACIiA6B4QAkJACJQpAhwUyA41vv8cVtiqVaukmaBYFGMxgMBwknjz5s2rnKVBgPmsWbN8nVgpcHWy088TQcjOPov3Bg0a+AWpxXHEK88ClnNH/vjjD183O+p2+GC6KmLMtIcrEf3HohMlR6nqItAfKwZWG1yLUo2R+rAicWo6WIMdhCLa9zAG5Mwzz/QuaWCJXviX6VhpN1PMLH4ECxifk0k6Y7LrsUJBbubOnev1HGZuS4W3fhcCQqDyEBABqTyda8RCQAgIASFQAwgkC0IvRncgVcTxIOFZI8VoW20IASEgBEIEREB0PwgBISAEhIAQKAICNUFACM4fNmyYj38hxgXBLYzYFIkQEAJCoKYQEAGpKeTVrhAQAkJACFQUAjVBQOxgSoAmHobsY8TsLL300hWFvQYrBIRAaSEgAlJa+lBvhIAQEAJCoEwR4LwM/hHbwr9iCLEZnHFC0DoB7slOgy9Gf9SGEBACQgAEREB0HwgBISAEhIAQEAJCQAgIASFQNAREQIoGtRoSAkJACAgBISAEhIAQEAJCQARE94AQEAJCQAgIASEgBISAEBACRUNABKRoUKshISAEhIAQEAJCQAgIASEgBERAdA8IASEgBISAEBACQkAICAEhUDQE/h+8Weo7kYEdqwAAAABJRU5ErkJggg==" + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "data = inscriptions_parsed.filter(pl.col('op').eq('deploy')).to_pandas().copy()\n", + "top_protocols = data['p'].value_counts().iloc[:5].index\n", + "data.loc[~data['p'].isin(top_protocols), 'p'] = 'Others'\n", + "\n", + "print(data['p'].value_counts(normalize=False))\n", + "data = data['p'].value_counts(normalize=True)*100\n", + "\n", + "\n", + "fig = go.Figure(layout=get_plotly_layout(width=width, height=height))\n", + "\n", + "fig.add_trace(go.Bar(x=data.index, y=data.values,\n", + " marker_color=colors['blue'], textposition='auto', text=data.values.round(2), name='Protocols'))\n", + "fig.update_layout(yaxis_title=\"Percentage\",\n", + " xaxis_title=\"Protocols deployed\", yaxis_ticksuffix=\"%\")\n", + "\n", + "fig.update_traces(\n", + " texttemplate='%{text:,.4}', textfont_size=18)\n", + "fig.update_yaxes(range=[0, 100])\n", + "\n", + "fig.write_image(plots_dir+\"top-15-deployed-protocols-zksync.pdf\")\n", + "\n", + "fig.show('png')" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "tick\n", + "sync 11057\n", + "zks 2415\n", + "Others 604\n", + "izks 319\n", + "zkzk 313\n", + "zkss 282\n", + "Name: count, dtype: int64\n" + ] + }, + { + "data": { + "image/png": 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" + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "data = inscriptions_parsed.filter(pl.col('op').eq('deploy')).to_pandas().copy()\n", + "top_protocols = data['tick'].value_counts().iloc[:5].index\n", + "data.loc[~data['tick'].isin(top_protocols), 'tick'] = 'Others'\n", + "\n", + "print(data['tick'].value_counts(normalize=False))\n", + "data = data['tick'].value_counts(normalize=True)*100\n", + "\n", + "\n", + "fig = go.Figure(layout=get_plotly_layout(width=width, height=height))\n", + "\n", + "fig.add_trace(go.Bar(x=data.index, y=data.values,\n", + " marker_color=colors['blue'], textposition='auto', text=data.values.round(2), name='Ticks'))\n", + "fig.update_layout(yaxis_title=\"Percentage\",\n", + " xaxis_title=\"Ticks deployed\", yaxis_ticksuffix=\"%\")\n", + "\n", + "fig.update_traces(\n", + " texttemplate='%{text:,.4}', textfont_size=18)\n", + "fig.update_yaxes(range=[0, 100])\n", + "\n", + "fig.write_image(plots_dir+\"ticks-zksync.pdf\")\n", + "\n", + "fig.show('png')" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "There are 289466141 txs in our dataset.\n" + ] + }, + { + "data": { + "text/html": [ + "
\n", + "shape: (5, 5)
block_numbertx_hashis_self_transferis_inscriptiontimestamp
i64strboolbooldatetime[μs]
10000000"0x60b1dd4432b7…falsefalse2023-07-31 06:11:24
10000000"0x50225618b693…falsefalse2023-07-31 06:11:24
10000000"0xc9eca17d5877…falsefalse2023-07-31 06:11:24
10000000"0x56d6d32deef0…falsefalse2023-07-31 06:11:24
10000000"0x6dd263ae54dd…falsefalse2023-07-31 06:11:24
" + ], + "text/plain": [ + "shape: (5, 5)\n", + "┌──────────────┬─────────────────────────┬──────────────────┬────────────────┬─────────────────────┐\n", + "│ block_number ┆ tx_hash ┆ is_self_transfer ┆ is_inscription ┆ timestamp │\n", + "│ --- ┆ --- ┆ --- ┆ --- ┆ --- │\n", + "│ i64 ┆ str ┆ bool ┆ bool ┆ datetime[μs] │\n", + "╞══════════════╪═════════════════════════╪══════════════════╪════════════════╪═════════════════════╡\n", + "│ 10000000 ┆ 0x60b1dd4432b73c862c0ef ┆ false ┆ false ┆ 2023-07-31 06:11:24 │\n", + "│ ┆ 3fef4a09a… ┆ ┆ ┆ │\n", + "│ 10000000 ┆ 0x50225618b693a6c86aceb ┆ false ┆ false ┆ 2023-07-31 06:11:24 │\n", + "│ ┆ 4e3249fee… ┆ ┆ ┆ │\n", + "│ 10000000 ┆ 0xc9eca17d58773cbc98de7 ┆ false ┆ false ┆ 2023-07-31 06:11:24 │\n", + "│ ┆ 25fbf4998… ┆ ┆ ┆ │\n", + "│ 10000000 ┆ 0x56d6d32deef05581f90d7 ┆ false ┆ false ┆ 2023-07-31 06:11:24 │\n", + "│ ┆ 3c0db83e5… ┆ ┆ ┆ │\n", + "│ 10000000 ┆ 0x6dd263ae54dd10735f3d3 ┆ false ┆ false ┆ 2023-07-31 06:11:24 │\n", + "│ ┆ e63018b85… ┆ ┆ ┆ │\n", + "└──────────────┴─────────────────────────┴──────────────────┴────────────────┴─────────────────────┘" + ] + }, + "execution_count": 21, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Loading all txs inscriptions dataframe from a file\n", + "all_txs_df = pl.scan_parquet(\n", + " data_dir+'inscriptions_all_txs_df.parquet').collect(streaming=True)\n", + "print(\"There are {} txs in our dataset.\".format(\n", + " all_txs_df.shape[0]))\n", + "all_txs_df.head()" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "There are 289466141 unique transactions in our dataset.\n", + "There are 23070883 unique blocks in our dataset.\n", + "The average number of txs per block is 12.55 txs.\n", + "The minimum and max number of txs per block are: 6332862 and 29799866.\n", + "The minimum timestamp is 2023-06-18 02:04:06 and the maximum timestamp is 2024-03-25 02:19:14.\n" + ] + } + ], + "source": [ + "print(\"There are {} unique transactions in our dataset.\".format(\n", + " all_txs_df['tx_hash'].n_unique()))\n", + "print(\"There are {} unique blocks in our dataset.\".format(\n", + " all_txs_df['block_number'].n_unique()))\n", + "print(\"The average number of txs per block is {} txs.\".format(round(\n", + " all_txs_df['tx_hash'].n_unique()/all_txs_df['block_number'].n_unique(), 2)))\n", + "\n", + "print(\"The minimum and max number of txs per block are: {} and {}.\".format(\n", + " all_txs_df['block_number'].min(), all_txs_df['block_number'].max()))\n", + "\n", + "print(\"The minimum timestamp is {} and the maximum timestamp is {}.\".format(\n", + " all_txs_df['timestamp'].min(), all_txs_df['timestamp'].max()))" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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" + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Number of inscriptions in comparison to the total number of transactions per day on zkSync Era\n", + "\n", + "all_txs_per_day = (all_txs_df[['block_number', 'timestamp']]\n", + " .sort('timestamp').group_by_dynamic(\"timestamp\", every=\"1d\")\n", + " .agg(pl.len()))\n", + "\n", + "inscriptions_txs_per_day = (all_txs_df.filter(pl.col('is_inscription').eq(True))[['block_number', 'timestamp']]\n", + " .sort('timestamp')\n", + " .group_by_dynamic(\"timestamp\", every=\"1d\")\n", + " .agg(pl.len()))\n", + "\n", + "\n", + "fig = go.Figure(layout=get_plotly_layout(width=width, height=height))\n", + "fig.add_trace(go.Scatter(\n", + " x=all_txs_per_day['timestamp'], y=all_txs_per_day['len'], line=dict(color=colors['blue'], width=3, dash='solid'), mode='lines', name='Transactions'))\n", + "fig.add_trace(go.Scatter(\n", + " x=inscriptions_txs_per_day['timestamp'], y=inscriptions_txs_per_day['len'], line=dict(color=colors['red'], width=3, dash='solid'), mode='lines', name='Inscripted transactions'))\n", + "# fig.add_trace(go.Scatter(\n", + "# x=self_txs_per_day['timestamp'], y=self_txs_per_day['len'], line=dict(color=colors['green'], width=3, dash='solid'), mode='lines', name='Self-transfer transactions'))\n", + "\n", + "fig.update_layout(yaxis_title=\"Number of transactions\",\n", + " xaxis_title=\"Date\", legend=dict(xanchor='center',\n", + " x=0.5, y=1.02, orientation='h'))\n", + "\n", + "fig.write_image(plots_dir+'fraction-of-inscriptions-zksync.pdf')\n", + "fig.show('png')" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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" + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Distribution of the percentage of inscriptions in comparison to the total number of transactions per week on zkSync\n", + "\n", + "all_txs_per_day = (all_txs_df[['block_number', 'timestamp']]\n", + " .sort('timestamp').group_by_dynamic(\"timestamp\", every=\"6h\")\n", + " .agg(pl.len()))\n", + "\n", + "inscriptions_txs_per_day = (all_txs_df.filter(pl.col('is_inscription').eq(True))[['block_number', 'timestamp']]\n", + " .sort('timestamp')\n", + " .group_by_dynamic(\"timestamp\", every=\"6h\")\n", + " .agg(pl.len()))\n", + "\n", + "data = inscriptions_txs_per_day.join(all_txs_per_day, on='timestamp', how='left', suffix='_all_txs').with_columns(\n", + " pl.col('len').truediv(pl.col('len_all_txs')).alias('fraction'))\n", + "\n", + "\n", + "fig = go.Figure(layout=get_plotly_layout(width=width, height=height))\n", + "fig.add_trace(go.Scatter(\n", + " x=data['timestamp'], y=data['fraction']*100, line=dict(color=colors['blue'], width=3, dash='solid'), mode='lines', name='Transactions'))\n", + "\n", + "fig.update_xaxes(range=['2023-11-09', '2024-03-24'])\n", + "\n", + "fig.update_yaxes(range=[0, 100])\n", + "\n", + "fig.update_layout(yaxis_title=\"Percentage\",\n", + " xaxis_title=\"Date\", yaxis_ticksuffix=\"%\", legend=dict(xanchor='center',\n", + " x=0.5, y=1.02, orientation='h'))\n", + "\n", + "fig.write_image(plots_dir+'fraction-of-inscriptions-zksync.pdf')\n", + "fig.show('png')" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "base", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.11.7" + }, + "orig_nbformat": 4 + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/requirements.txt b/requirements.txt new file mode 100644 index 0000000..4447770 --- /dev/null +++ b/requirements.txt @@ -0,0 +1,7 @@ +matplotlib==3.7.2 +numpy==1.26.4 +pandas==2.2.1 +polars==0.20.18 +tqdm==4.65.0 +plotly==5.19.0 +web3==6.9.0 diff --git a/src/plot_utils.py b/src/plot_utils.py new file mode 100644 index 0000000..e0492c3 --- /dev/null +++ b/src/plot_utils.py @@ -0,0 +1,35 @@ + + +import matplotlib +import plotly.graph_objects as go +matplotlib.rcParams['pdf.fonttype'] = 42 +matplotlib.rcParams['ps.fonttype'] = 42 + +colors = {'red': '#ee443a', 'blue': '#42bbf1', 'dark_blue': '#1a4fec', + 'green': '#50be61', 'grey': '#b7b7b7', 'orange': '#f28222', 'purple': '#6e18ee', 'brown': '#a65628', 'pink': '#ef4793', + 'yellow': '#f8c94c', 'black': '#000000', 'white': '#ffffff', 'light_blue': '#a6cee3', 'light_green': '#b2df8a', + 'light_grey': '#999999', 'light_orange': '#fdbf6f', 'light_purple': '#cab2d6', 'light_brown': '#ffff99', 'light_pink': '#1f78b4', + 'light_yellow': '#fb9a99', 'light_black': '#e31a1c', 'light_white': '#33a02c', 'gold': '#ff7f00', 'silver': '#b2df8a'} +styles = ['-', '--', ':', '-.'] +percentiles = [.01, .05, .1, .2, .25, .50, .75, .8, .9, .95, .99] +linestyles = ['dotted', 'dotted', 'solid', 'dashdot', 'dashed', 'solid'] + + +def get_plotly_layout(height, width): + layout = go.Layout( + template='simple_white', + font=dict(size=18, family='Clear Sans'), + margin=go.layout.Margin( + l=10, # left margin + r=10, # right margin + b=10, # bottom margin + t=10 # top margin + ), + width=width, + height=height, + xaxis=dict(minor_ticks="inside", showgrid=True, + griddash='dash', minor_griddash="dot"), + yaxis=dict(minor_ticks="inside", showgrid=True, + griddash='dash', minor_griddash="dot") + ) + return layout diff --git a/src/utils.py b/src/utils.py new file mode 100644 index 0000000..3e3a52f --- /dev/null +++ b/src/utils.py @@ -0,0 +1,779 @@ +import web3 +import polars as pl +from tqdm import tqdm + + +class Utils: + + def __init__(self, zkSync_data_dir, data_dir='../data/'): + # Existing dataset + self.data_dir = data_dir + self.data_path = self.create_data_path(zkSync_data_dir) + + def get_data_path(self): + return self.data_path + + def create_data_path(self, path_dir): + data_path = dict() + data_path['blocks'] = path_dir+'blocks_*.parquet.gz' + data_path['transactions'] = path_dir+'transactions_*.parquet.gz' + data_path['tx_receipts'] = path_dir+'tx_receipts_*.parquet.gz' + data_path['logs'] = path_dir+'logs_*.parquet.gz' + return data_path + + @staticmethod + def check_sig(sig, topic_0): + return web3.Web3.keccak(text=sig).hex() == topic_0 + + @staticmethod + def parse_addresses(address): + if isinstance(address, str): + return '0x' + address[-40:].lower() + return address + + @staticmethod + def parse_amount(amount): + if isinstance(amount, str): + return int(amount, 16) + return amount + + @staticmethod + def decode_input_data(input_data): + try: + response = web3.Web3.to_text(input_data) + except: + response = None + return response + + def get_txs(self, inscriptions_tag): + txs = (pl.scan_parquet(self.data_path['transactions']) + # .filter(pl.col('from').eq(pl.col('to')) & pl.col('input').str.starts_with(inscriptions_tag)) + .filter(pl.col('input').str.starts_with(inscriptions_tag)) + .select([ + pl.col('blockNumber').alias('block_number'), + pl.col('hash').alias('tx_hash'), + pl.col('input').alias('tx_input_data'), + pl.col('from').str.to_lowercase().alias('issuer'), + pl.col('to').str.to_lowercase().alias('receiver'), + ]) + ) + blocks = ( + pl.scan_parquet(self.data_path['blocks']) + .select(pl.col('number').alias('block_number'), pl.from_epoch(pl.col('timestamp'))) + ) + q = txs.join(blocks, left_on='block_number', + right_on='block_number', how='left') + + return q.collect(streaming=True) + + def get_receipts(self, wallet_addresses): + q = (pl.scan_parquet(self.data_path['tx_receipts']) + # .filter(pl.col('from').eq(pl.col('to'))) + # .filter(pl.col('from').str.to_lowercase().is_in(wallet_addresses) | pl.col('to').str.to_lowercase().is_in(wallet_addresses)) + .filter(pl.col('from').str.to_lowercase().is_in(wallet_addresses)) + .select([ + pl.col('transactionHash').alias('tx_hash'), + pl.col('gasUsed').alias('gas_used'), + pl.col('effectiveGasPrice').alias('gas_effective_price'), + pl.col('gasUsed').mul( + pl.col('effectiveGasPrice')).truediv(1e18).alias('fees'), + pl.col('status').alias('tx_status'), + ]) + ) + return q.collect(streaming=True) + + def get_txs(self, inscriptions_tag): + txs = (pl.scan_parquet(self.data_path['transactions']) + # .filter(pl.col('from').eq(pl.col('to')) & pl.col('input').str.starts_with(inscriptions_tag)) + .filter(pl.col('input').str.starts_with(inscriptions_tag)) + .select([ + pl.col('blockNumber').alias('block_number'), + pl.col('hash').alias('tx_hash'), + pl.col('input').alias('tx_input_data'), + pl.col('from').str.to_lowercase().alias('issuer'), + pl.col('to').str.to_lowercase().alias('receiver'), + ]) + ) + blocks = ( + pl.scan_parquet(self.data_path['blocks']) + .select(pl.col('number').alias('block_number'), pl.from_epoch(pl.col('timestamp'))) + ) + q = txs.join(blocks, left_on='block_number', + right_on='block_number', how='left') + + return q.collect(streaming=True) + + def get_receipts(self, wallet_addresses): + q = (pl.scan_parquet(self.data_path['tx_receipts']) + # .filter(pl.col('from').eq(pl.col('to'))) + # .filter(pl.col('from').str.to_lowercase().is_in(wallet_addresses) | pl.col('to').str.to_lowercase().is_in(wallet_addresses)) + .filter(pl.col('from').str.to_lowercase().is_in(wallet_addresses)) + .select([ + pl.col('transactionHash').alias('tx_hash'), + pl.col('gasUsed').alias('gas_used'), + pl.col('effectiveGasPrice').alias('gas_effective_price'), + pl.col('gasUsed').mul( + pl.col('effectiveGasPrice')).truediv(1e18).alias('fees'), + pl.col('status').alias('tx_status'), + ]) + ) + return q.collect(streaming=True) + + def get_event_name(self, signature): + # https://www.4byte.directory/event-signatures/ + if signature in self.events_dict: + return self.events_dict[signature]['name'] + return 'Unknown' + + def get_event_signature(self, signature): + if signature in self.events_dict: + return self.events_dict[signature]['signature'] + return 'Unknown' + + def get_min_max_blocks(self): + # get the min and max block number + q = ( + pl.scan_parquet(self.data_path['blocks']) + .filter(pl.col('number') > 0) + .select([pl.col('number').min().alias('min_number'), + pl.col('number').max().alias('max_number'), + pl.from_epoch(pl.col('timestamp').min() + ).alias('min_timestamp'), + pl.from_epoch(pl.col('timestamp').max()).alias('max_timestamp')]) + ) + return q.collect(streaming=True) + + def get_num_transactions(self): + q = ( + pl.scan_parquet(self.data_path['transactions']) + .select(pl.len()) + ) + return q.collect(streaming=True).rows()[0][0] + + def get_num_blocks(self): + q = ( + pl.scan_parquet(self.data_path['blocks']) + .select(pl.col('hash').n_unique()) + ) + return q.collect(streaming=True).rows()[0][0] + + def get_events_from_contract_address(self, contract_address): + q = ( + pl.scan_parquet(self.data_path['logs']) + .filter(pl.col('address').str.to_lowercase() == contract_address.lower()) + .select(pl.col('topics_0').unique().alias('topics_0')) + ) + return q.collect(streaming=True) + + def get_topics_0_count(self, contract_address): + q = ( + pl.scan_parquet(self.data_path['logs']) + .filter(pl.col('address').str.to_lowercase() == contract_address) + .group_by(pl.col('topics_0')) + .agg(pl.len()) + .sort(pl.col('len'), descending=True) + ) + return q.collect(streaming=True) + + def get_count_unique_transactions_per_contract(self, contract_address): + response = dict() + response['from'] = ( + pl.scan_parquet(self.data_path['transactions']) + .filter(pl.col('from').str.to_lowercase() == contract_address) + .select(pl.col('hash').n_unique()) + ).collect(streaming=True)['hash'][0] + response['to'] = ( + pl.scan_parquet(self.data_path['transactions']) + .filter(pl.col('to').str.to_lowercase() == contract_address) + .select(pl.col('hash').n_unique()) + ).collect(streaming=True)['hash'][0] + + response['from_to'] = ( + pl.scan_parquet(self.data_path['transactions']) + .filter((pl.col('from').str.to_lowercase() == contract_address) | (pl.col('to').str.to_lowercase() == contract_address)) + .select(pl.col('hash').n_unique()) + ).collect(streaming=True)['hash'][0] + return response + + def get_unique_transactions_calling_contract(self, contract_address): + q = ( + pl.scan_parquet(self.data_path['logs']) + .filter(pl.col('address').str.to_lowercase() == contract_address) + .select(pl.col('transactionHash').unique()) + ) + return q.collect(streaming=True) + + def get_contract_events(self, contract_address): + q = ( + pl.scan_parquet(self.data_path['logs']) + .filter(pl.col('address').str.to_lowercase() == contract_address) + .select(pl.col( + ['blockNumber', 'transactionHash', 'transactionIndex', 'logIndex', + 'topics_0', 'topics_1', 'topics_2', 'topics_3', + 'data'] + )) + .sort(pl.col(['blockNumber', 'transactionIndex', 'logIndex'])) + ) + return q.collect(streaming=True) + + def get_contract_transfer_events_bkp(self, contract_address): + q = ( + pl.scan_parquet(self.data_path['logs']) + .filter( + (pl.col('address').str.to_lowercase() == contract_address) + & + (pl.col('topics_0').eq("0xddf252ad1be2c89b69c2b068fc378daa952ba7f163c4a11628f55a4df523b3ef"))) + .select([ + pl.col('blockNumber'), + pl.col('transactionHash'), + pl.col('transactionIndex'), + pl.col('logIndex'), + pl.format("0x{}", pl.col( + 'topics_1').str.slice(-40)).alias('sender'), + pl.format("0x{}", pl.col('topics_2').str.slice(-40) + ).alias('receiver'), + pl.col('data').str.replace('0x', '0x0').alias('amount') + ]) + ) + return q.collect(streaming=True) + + def get_contract_transfer_events(self, contract_address): + txs = ( + pl.scan_parquet(self.data_path['logs']) + .filter( + (pl.col('address').str.to_lowercase() == contract_address) + & + (pl.col('topics_0').eq("0xddf252ad1be2c89b69c2b068fc378daa952ba7f163c4a11628f55a4df523b3ef"))) + .select([ + pl.col('blockNumber'), + pl.col('transactionHash'), + pl.col('transactionIndex'), + pl.col('logIndex'), + pl.format("0x{}", pl.col( + 'topics_1').str.slice(-40)).alias('sender'), + pl.format("0x{}", pl.col('topics_2').str.slice(-40) + ).alias('receiver'), + pl.col('data').str.replace('0x', '0x0').alias('amount') + ]) + ) + blocks = ( + pl.scan_parquet(self.data_path['blocks']) + .select(pl.col('number'), pl.from_epoch(pl.col('timestamp'))) + ) + q = txs.join(blocks, left_on='blockNumber', right_on='number', how='left').sort( + pl.col(['blockNumber', 'transactionIndex', 'logIndex'])) + return q.collect(streaming=True) + + def get_events_from_transactions(self, transactions): + q = ( + pl.scan_parquet(self.data_path['logs']) + .filter(pl.col('transactionHash').is_in(transactions['transactionHash'])) + .select(pl.col( + ['blockNumber', 'transactionHash', 'transactionIndex', + 'logIndex', 'topics_0', 'topics_1', 'topics_2', 'topics_3', + 'data'] + )) + .sort(pl.col(['blockNumber', 'transactionIndex', 'logIndex'])) + ) + return q.collect(streaming=True) + + def get_contract_calls(self, contract_address): + contract_address = contract_address.lower() + q = ( + pl.scan_parquet(self.data_path['logs']) + .filter( + (pl.col('topics_1').map_elements(Utils.parse_addresses) == contract_address) | ( + pl.col('topics_2').map_elements(Utils.parse_addresses) == contract_address)) + .select(pl.col( + ['blockNumber', 'transactionHash', 'transactionIndex', + 'logIndex', 'address', + 'topics_0', 'topics_1', 'topics_2', 'topics_3', + 'data'] + )) + .sort(pl.col(['blockNumber', 'transactionIndex', 'logIndex'])) + ) + return q.collect(streaming=True) + + def get_fees_spent(self, user_address): + txs = ( + pl.scan_parquet(self.data_path['tx_receipts']) + .filter(pl.col('from').str.to_lowercase() == user_address) + .select(pl.col('blockNumber'), pl.col('gasUsed'), + pl.col('effectiveGasPrice'), + pl.col('gasUsed').mul(pl.col('effectiveGasPrice')).alias('fees')) + ).collect(streaming=True) + min_block = txs['blockNumber'].min() + max_block = txs['blockNumber'].max() + blocks = ( + pl.scan_parquet(self.data_path['blocks']) + .filter((pl.col('number') >= min_block) & (pl.col('number') <= max_block)) + .select(pl.col('number'), pl.from_epoch(pl.col('timestamp'))) + ).collect(streaming=True) + return txs.join(blocks, left_on='blockNumber', right_on='number', how='left') + + def get_fees_spent_by_contract(self, contract_address): + txs = ( + pl.scan_parquet(self.data_path['tx_receipts']) + .filter(pl.col('from').str.to_lowercase() == contract_address) + .select(pl.col('blockNumber'), pl.col('gasUsed'), + pl.col('effectiveGasPrice'), + pl.col('gasUsed').mul(pl.col('effectiveGasPrice')).alias('fees')) + ).collect(streaming=True) + min_block = txs['blockNumber'].min() + max_block = txs['blockNumber'].max() + blocks = ( + pl.scan_parquet(self.data_path['blocks']) + .filter((pl.col('number') >= min_block) & (pl.col('number') <= max_block)) + .select(pl.col('number'), pl.from_epoch(pl.col('timestamp'))) + ).collect(streaming=True) + return txs.join(blocks, left_on='blockNumber', right_on='number', how='left') + + def compute_account_balances(self, transfer_df): + # Loading account balances history for specific addresses + balances_history_dict = dict() + for row in tqdm(transfer_df.iter_rows(named=True), desc='Loading balances', total=transfer_df.shape[0]): + if row['sender'] not in balances_history_dict: + balances_history_dict[row['sender']] = { + 'current': 0, 'history': [], 'n_sender': 0, 'n_receiver': 0} + if row['receiver'] not in balances_history_dict: + balances_history_dict[row['receiver']] = { + 'current': 0, 'history': [], 'n_sender': 0, 'n_receiver': 0} + + balance = row['amount']/1e18 + + balances_history_dict[row['sender']]['history'].append( + {'block_number': row['blockNumber'], 'timestamp': row['timestamp'], + 'balance': balances_history_dict[row['sender']]['current']-balance}) + balances_history_dict[row['receiver']]['history'].append( + {'block_number': row['blockNumber'], 'timestamp': row['timestamp'], + 'balance': balances_history_dict[row['receiver']]['current']+balance}) + + balances_history_dict[row['sender']]['n_sender'] += 1 + balances_history_dict[row['receiver']]['n_receiver'] += 1 + + balances_history_dict[row['sender']]['current'] -= balance + balances_history_dict[row['receiver']]['current'] += balance + + print("There are in total {} addresses".format( + len(balances_history_dict))) + return balances_history_dict + + def count_occurrences(self, file, column): + q = ( + pl.scan_parquet(self.data_path[file]) + .group_by(pl.col(column).str.to_lowercase()) + .agg(pl.len()) + .sort(pl.col('len'), descending=True) + ) + return q.collect(streaming=True) + + def get_total_txs_per_address(self): + q = ( + pl.scan_parquet(self.data_path['transactions']) + .group_by('from') + .agg(pl.len('from').alias('n_txs')) + .select([pl.col('from').str.to_lowercase().alias('address'), pl.col('n_txs')]) + .sort('n_txs', descending=True) + ) + return q.collect(streaming=True) + + def get_total_transactions_per_day(self): + q_1 = (pl.scan_parquet(self.data_path['transactions']) + # .filter(pl.col('blockNumber').is_between(min_block, max_block)) + .select('blockNumber') + ) + q_2 = (pl.scan_parquet(self.data_path['blocks']) + # .filter(pl.col('number').is_between(min_block, max_block)) + .select(pl.col('number'), pl.from_epoch(pl.col('timestamp'))) + ) + q = q_1.join(q_2, left_on='blockNumber', right_on='number', how='left') + q = (q + .group_by(pl.col('timestamp').cast(pl.Date).alias('date')) + .agg(pl.len()) + .sort(pl.col('date')) + ) + return q.collect(streaming=True) + + # def get_transactions_per_day_per_contract(contract_address): + # q_1 = (pl.scan_parquet(data_path['transactions']) + # .filter(pl.col('to').str.to_lowercase() == contract_address) + # .select('blockNumber') + # ) + # q_2 = (pl.scan_parquet(data_path['blocks']) + # .select(pl.col('number'), pl.from_epoch(pl.col('timestamp'))) + # ) + # q = q_1.join(q_2, left_on='blockNumber', right_on='number', how='left') + # q = (q + # .group_by(pl.col('timestamp').cast(pl.Date).alias('date')) + # .agg(pl.len()) + # .sort(pl.col('date')) + # ) + # return q.collect(streaming=True) + + def get_transactions_per_day_per_contract(self, contract_addresses): + q_1 = (pl.scan_parquet(self.data_path['transactions']) + .filter(pl.col('to').str.to_lowercase().is_in(contract_addresses)) + .select(pl.col('blockNumber'), pl.col('to').alias('contractAddress').str.to_lowercase()) + ) + q_2 = (pl.scan_parquet(self.data_path['blocks']) + .select(pl.col('number'), pl.col('timestamp')) + ) + q = q_1.join(q_2, left_on='blockNumber', right_on='number', how='left') + q = (q + .group_by([pl.col('contractAddress'), pl.from_epoch(pl.col('timestamp')).cast(pl.Date).alias('date')]) + .agg(pl.len()) + .sort(pl.col('date')) + ) + return q.collect(streaming=True) + + +def construct_events_dict(self): + self.events_dict = dict() + self.events_dict['0xddf252ad1be2c89b69c2b068fc378daa952ba7f163c4a11628f55a4df523b3ef'] = { + 'name': 'Transfer', 'signature': 'Transfer(address,address,uint256)'} + self.events_dict['0x7f26b83ff96e1f2b6a682f133852f6798a09c465da95921460cefb3847402498'] = { + 'name': 'Initialized', 'signature': 'Initialized(uint8)'} + self.events_dict['0x9b5b9a05e4726d8bb959f1440e05c6b8109443f2083bc4e386237d7654526553'] = { + 'name': 'BridgeBurn', 'signature': 'BridgeBurn(address,uint256)'} + self.events_dict['0x8c5be1e5ebec7d5bd14f71427d1e84f3dd0314c0f7b2291e5b200ac8c7c3b925'] = { + 'name': 'Approval', 'signature': 'Approval(address,address,uint256)'} + self.events_dict['0x1cf3b03a6cf19fa2baba4df148e9dcabedea7f8a5c07840e207e5c089be95d3e'] = { + 'name': 'BeaconUpgraded', 'signature': 'BeaconUpgraded(address)'} + self.events_dict['0x397b33b307fc137878ebfc75b295289ec0ee25a31bb5bf034f33256fe8ea2aa6'] = { + 'name': 'BridgeMint', 'signature': 'BridgeMint(address,uint256)'} + self.events_dict['0xe6b2ac4004ee4493db8844da5db69722d2128345671818c3c41928655a83fb2c'] = { + 'name': 'Unknown', 'signature': 'Unknown'} + self.events_dict['0x66753cd2356569ee081232e3be8909b950e0a76c1f8460c3a5e3c2be32b11bed'] = { + 'name': 'SafeMultiSigTransaction', 'signature': 'SafeMultiSigTransaction(address,uint256,bytes,uint8,uint256,uint256,uint256,address,address,bytes,bytes)' + } + self.events_dict['0x25bc54a32c894b07fd47ed3cc4296ec7d97a974e5ebd17c9f5163afddaf107fa'] = { + 'name': 'PairCreated', 'signature': 'PairCreated(address,address,bool,address,uint256,uint256)' + } + self.events_dict['0x0d3648bd0f6ba80134a33ba9275ac585d9d315f0ad8355cddefde31afa28d0e9'] = { + 'name': 'PairCreated', 'signature': 'PairCreated(address,address,address,uint256)' + } + self.events_dict['0x9c5d829b9b23efc461f9aeef91979ec04bb903feb3bee4f26d22114abfc7335b'] = { + 'name': 'PoolCreated', 'signature': 'PoolCreated(address,address,address)' + } + self.events_dict['0xe5b6779c4a18cbf7e4bce3a6c308b215c678f316648b832318a03841664fc2e9'] = { + 'name': 'Add', 'signature': 'Add(uint256,address,uint256)' + } + self.events_dict['0x90890809c654f11d6e72a28fa60149770a0d11ec6c92319d6ceb2bb0a4ea1a15'] = { + 'name': 'Deposit', 'signature': 'Deposit(address,uint256,uint256)' + } + self.events_dict['0x99d2b755eb38920131acb332adf086ea38d15009f223c21f3aa978d6ab234786'] = { + 'name': 'TokenListed', 'signature': 'TokenListed(address,address)' + } + self.events_dict['0x76af224a143865a50b41496e1a73622698692c565c1214bc862f18e22d829c5e'] = { + 'name': 'Swapped', 'signature': 'Swapped(address,address,address,address,uint256,uint256,uint256,uint256,uint256,address)' + + } + self.events_dict['0x0fda88444c12e1f4744fdef52d79861522a79baa20a440385e449e39f0de5cd5'] = { + 'name': 'PoolAmountUpdated', 'signature': 'PoolAmountUpdated(address,uint256,uint256,uint256,uint256)' + } + self.events_dict['0x4daa66261ce0fd318a8b8e5a12526b9e43f3f411a9cb6488e3959d6d12313787'] = { + 'name': 'CaptureSwapFee', 'signature': 'CaptureSwapFee(address,uint256,uint256)' + } + self.events_dict['0x5b99554095b82fa9d0725a9ff1f1db8bc3e4d461e7d61911c752c349a47b987f'] = { + 'name': 'Executed', 'signature': 'Executed(address,uint256,uint256,address,uint256,uint256,uint256,uint256,(uint8,(uint256,address),(uint256,address),address,address,bytes),address)' + + } + self.events_dict['0x4bc8151c051441255339d01fbaeb38cf109cbfd75e9a5c62fb8f1dfb37fe6fd6'] = { + 'name': 'Unknown', 'signature': 'Unknown' + + } + self.events_dict['0x76e3540b214147a4d1733ed21adbc36bc76fe68060033ed6a6dc81a8d3e699a4'] = { + 'name': 'AddLiquidity', 'signature': 'AddLiquidity(address,uint256,uint256,address)' + } + self.events_dict['0x7055e3d08e2c20429c6b162f3e3bee3f426d59896e66084c3580dc353e54129d'] = { + 'name': 'TransitSwapped', 'signature': 'TransitSwapped(address,address,address,address,bool,uint256,uint256,uint256,uint256,uint256,string,uint256)' + } + self.events_dict['0x3d58404efba0e9fa8c42b15fd0c0aee3cc2ac3a59477f4e392bff292d4977879'] = { + 'name': 'RemoveLiquidity', 'signature': 'RemoveLiquidity(address,uint256,uint256,address)' + + } + self.events_dict['0xdec2bacdd2f05b59de34da9b523dff8be42e5e38e818c82fdb0bae774387a724'] = { + 'name': 'DelegateVotesChanged', 'signature': 'DelegateVotesChanged(address,uint256,uint256)' + + } + self.events_dict['0xb5cb27a38d4490736679c8feb25b220de6e56af98bbc4d61378dffde8e46101c'] = { + 'name': 'Unknown', 'signature': 'Unknown' + + } + + self.events_dict['0x9aa05b3d70a9e3e2f004f039648839560576334fb45c81f91b6db03ad9e2efc9'] = { + 'name': 'ClaimRewards', 'signature': 'ClaimRewards(address,address,uint256)' + + } + + self.events_dict['0x3134e8a2e6d97e929a7e54011ea5485d7d196dd5f0ba4d4ef95803e8e3fc257f'] = { + 'name': 'DelegateChanged', 'signature': 'DelegateChanged(address,address,address)' + + } + + self.events_dict['0xf70d5c697de7ea828df48e5c4573cb2194c659f1901f70110c52b066dcf50826'] = { + 'name': 'NotifyReward', 'signature': 'NotifyReward(address,address,uint256)' + + } + + self.events_dict['0x0d7d75e01ab95780d3cd1c8ec0dd6c2ce19e3a20427eec8bf53283b6fb8e95f0'] = { + 'name': 'FlashLoan', 'signature': 'FlashLoan(address,address,uint256,uint256)' + + } + + self.events_dict['0x783cca1c0412dd0d695e784568c96da2e9c22ff989357a2e8b1d9b2b4e6b7118'] = { + 'name': 'PoolCreated', 'signature': 'PoolCreated(address,address,uint24,int24,address)' + + } + self.events_dict['0xd78ad95fa46c994b6551d0da85fc275fe613ce37657fb8d5e3d130840159d822'] = { + 'name': 'Swap', 'signature': 'Swap(address,uint256,uint256,uint256,uint256,address)' + + } + + self.events_dict['0xcf2aa50876cdfbb541206f89af0ee78d44a2abf8d328e37fa4917f982149848a'] = { + 'name': 'Sync', 'signature': 'Sync(uint256,uint256)' + + } + + self.events_dict['0x0f6798a560793a54c3bcfe86a93cde1e73087d944c0ea20544137d4121396885'] = { + 'name': 'Mint', 'signature': 'Mint(address,uint256)' + + } + self.events_dict['0x1c411e9a96e071241c2f21f7726b17ae89e3cab4c78be50e062b03a9fffbbad1'] = { + 'name': 'Sync', 'signature': 'Sync(uint112,uint112)' + + } + + self.events_dict['0xe7779a36a28ae0e49bcbd9fcf57286fb607699c0c339c202e92495640505613e'] = { + 'name': 'Swap', 'signature': 'Swap(address,address,uint24,bool,uint256,uint256)' + + } + + self.events_dict['0x3b841dc9ab51e3104bda4f61b41e4271192d22cd19da5ee6e292dc8e2744f713'] = { + 'name': 'Swap', 'signature': 'Swap(address,address,bool,bool,uint256,uint256,int32)' + + } + + self.events_dict['0xf26bfd49b39c52efaf04ee7f21ca2fdc73c680fada92ab7a8f1ea37b350bcf8c'] = { + 'name': 'Message', 'signature': 'Message(string,address,string)' + + } + + self.events_dict['0x4c209b5fc8ad50758f13e2e1088ba56a560dff690a1c6fef26394f4c03821c4f'] = { + 'name': 'Mint', 'signature': 'Mint(address,uint256,uint256)' + + } + + self.events_dict['0x2caecd17d02f56fa897705dcc740da2d237c373f70686f4e0d9bd3bf0400ea7a'] = { + 'name': 'DistributedSupplierComp', 'signature': 'DistributedSupplierComp(address,address,uint256,uint256)' + + } + + self.events_dict['0xce0457fe73731f824cc272376169235128c118b49d344817417c6d108d155e82'] = { + 'name': 'NewOwner', 'signature': 'NewOwner(bytes32,bytes32,address)' + + } + + self.events_dict['0xa8137fff86647d8a402117b9c5dbda627f721d3773338fb9678c83e54ed39080'] = { + 'name': 'Mint', 'signature': 'Mint(address,uint256,uint256,uint256,address)' + + } + + self.events_dict['0xc3d58168c5ae7397731d063d5bbf3d657854427343f4c083240f7aacaa2d0f62'] = { + 'name': 'TransferSingle', 'signature': 'TransferSingle(address,address,address,uint256,uint256)' + + } + + self.events_dict['0xe5b754fb1abb7f01b499791d0b820ae3b6af3424ac1c59768edb53f4ec31a929'] = { + 'name': 'Redeem', 'signature': 'Redeem(address,uint256,uint256)' + + } + + self.events_dict['0xfa76a4010d9533e3e964f2930a65fb6042a12fa6ff5b08281837a10b0be7321e'] = { + 'name': 'TokensClaimed', 'signature': 'TokensClaimed(uint256,address,address,uint256,uint256)' + + } + + self.events_dict['0xbc7cd75a20ee27fd9adebab32041f755214dbc6bffa90cc0225b39da2e5c2d3b'] = { + 'name': 'Upgraded', 'signature': 'Upgraded(address)' + } + + self.events_dict['0x1271330ebae535a48b1e51c35100aab270c68fe44a98e2c04ce905979a28ffbf'] = { + 'name': 'ProtocolFeeDynamicChange', 'signature': 'ProtocolFeeDynamicChange(uint256)' + } + + self.events_dict['0x11d0eb59e2eba9f45cb018cb9a3009b3646d176071d40521ad22cdbc1c8170bc'] = { + 'name': 'ProtocolFeeToChange', 'signature': 'ProtocolFeeToChange(address)' + } + + self.events_dict['0x7e644d79422f17c01e4894b5f4f588d331ebfa28653d42ae832dc59e38c9798f'] = { + 'name': 'AdminChanged', 'signature': 'AdminChanged(address,address)' + } + + self.events_dict['0xc21caeb4e8f73861400d4c0870ad3e468ddb4e45225da3832ce1da5561f1f61e'] = { + 'name': 'Unknown', 'signature': 'Unknown' + } + + self.events_dict['0x865ca08d59f5cb456e85cd2f7ef63664ea4f73327414e9d8152c4158b0e94645'] = { + 'name': 'Claim', 'signature': 'Claim(address,address,uint256,uint256)' + } + + self.events_dict['0xebf2df875b555f5edaef342e52b6a9498cccaec4813df8eb0f3842acc6d08281'] = { + 'name': 'Fees', 'signature': 'Fees(address,uint256,uint256,uint256,uint256)' + } + + self.events_dict['0xdccd412f0b1252819cb1fd330b93224ca42612892bb3f4f789976e6d81936496'] = { + 'name': 'Burn', 'signature': 'Burn(address,uint256,uint256,address)' + } + + self.events_dict['0x91e72fa36e0202be93e86c97a3d3d3497cf0a06cf859b14b616a304367835a8e'] = { + 'name': 'ChangeFee', 'signature': 'ChangeFee(uint256,uint256)' + } + self.events_dict['0x6eef835a3905d9ada7e0cc03c9912f07fac2fe4c8f1b503a0b31a93b55c5ca18'] = { + 'name': 'PriceRequested', 'signature': 'PriceRequested(uint256,bytes32,uint256,uint8,uint256,uint256)' + } + + self.events_dict['0x3e544118c04e3bb18b669475695cd270ba0e41fb13177483f01c14222de62a86'] = { + 'name': 'MarketOrderInitiated', 'signature': 'MarketOrderInitiated(uint256,address,uint256,bool)' + } + + self.events_dict['0x2dc8e290002f06fc0085bbca9dfb8b415cf4d1178950c72ff9ee8f4d8878ee66'] = { + 'name': 'Refunded', 'signature': 'Refunded(address,uint256,uint256)' + } + + self.events_dict['0x606834f57405380c4fb88d1f4850326ad3885f014bab3b568dfbf7a041eef738'] = { + 'name': 'Received', 'signature': 'Received(uint256,address,bytes)' + } + + self.events_dict['0x31c5374dcc95d137f3c21741a151157300dc87c02ffd59e4a177713557a916b1'] = { + 'name': 'ImplementationUpdated', 'signature': 'ImplementationUpdated(address,string,address)' + } + + self.events_dict['0xfd2dd1404be8946179e2efaadd5b7b78920403c755422016c708b3c84d5fd8e3'] = { + 'name': 'Unknown', 'signature': 'Unknown' + } + + self.events_dict['0x2a2899ae8177fb54d81544d727d24141bf8fd23e78e721fe56cda337d397044b'] = { + 'name': 'Unknown', 'signature': 'Unknown' + } + self.events_dict['0xbaec78ca3218aba6fc32d82b79acdd1a47663d7b8da46e0c00947206d08f2071'] = { + 'name': 'Swap', 'signature': 'Swap(address,address,bytes32[],int128[])' + } + + self.events_dict['0x19b47279256b2a23a1665c810c8d55a1758940ee09377d4f8d26497a3577dc83'] = { + 'name': 'Swap', 'signature': 'Swap(address,address,int256,int256,uint160,uint128,int24,uint128,uint128)' + } + + self.events_dict['0x4dec04e750ca11537cabcd8a9eab06494de08da3735bc8871cd41250e190bc04'] = { + 'name': 'AccrueInterest', 'signature': 'AccrueInterest(uint256,uint256,uint256,uint256)' + } + + self.events_dict['0xa3e4886b89c6d25cb1409eb38693c679fbc0122c8f524f71c8b7c0ea4fde21a5'] = { + 'name': 'GetTicket', 'signature': 'GetTicket(address,uint256)' + } + + self.events_dict['0xd175a80c109434bb89948928ab2475a6647c94244cb70002197896423c883363'] = { + 'name': 'Burn', 'signature': 'Burn(address,uint256,uint256,uint256,address)' + } + + self.events_dict['0x290afdae231a3fc0bbae8b1af63698b0a1d79b21ad17df0342dfb952fe74f8e5'] = { + 'name': 'ContractDeployed', 'signature': 'ContractDeployed(address,bytes32,address)' + } + + self.events_dict['0x14be1c122ee505f1d86e447cb0ae7bf79456d3f660501d9d24f901e3bbc8e65c'] = { + 'name': 'MintSoul', 'signature': 'MintSoul(address,uint256,uint256)' + } + self.events_dict['0xe9bded5f24a4168e4f3bf44e00298c993b22376aad8c58c7dda9718a54cbea82'] = { + 'name': 'Packet', 'signature': 'Packet(bytes)' + } + + self.events_dict['0xdf21c415b78ed2552cc9971249e32a053abce6087a0ae0fbf3f78db5174a3493'] = { + 'name': 'AssignJob', 'signature': 'AssignJob(uint256)' + } + + self.events_dict['0xb0c632f55f1e1b3b2c3d82f41ee4716bb4c00f0f5d84cdafc141581bb8757a4f'] = { + 'name': 'RelayerParams', 'signature': 'RelayerParams(bytes,uint16)' + } + + self.events_dict['0x4e41ee13e03cd5e0446487b524fdc48af6acf26c074dacdbdfb6b574b42c8146'] = { + 'name': 'AssignJob', 'signature': 'AssignJob(uint16,uint16,uint256,address,uint256)' + } + + self.events_dict['0x9c248aa1a265aa616f707b979d57f4529bb63a4fc34dc7fc61fdddc18410f74e'] = { + 'name': 'ERC721SellOrderFilled', 'signature': 'ERC721SellOrderFilled(bytes32,address,address,uint256,address,uint256,(address,uint256)[],address,uint256)' + } + self.events_dict['0x52977ea98a2220a03ee9ba5cb003ada08d394ea10155483c95dc2dc77a7eb24b'] = { + 'name': 'NotifyReward', 'signature': 'NotifyReward(address,address,uint256,uint256)' + } + + self.events_dict['0x3ab23ab0d51cccc0c3085aec51f99228625aa1a922b3a8ca89a26b0f2027a1a5'] = { + 'name': 'MarketEntered', 'signature': 'MarketEntered(address,address)' + } + + self.events_dict['0x3a36e47291f4201faf137fab081d92295bce2d53be2c6ca68ba82c7faa9ce241'] = { + 'name': 'L1MessageSent', 'signature': 'L1MessageSent(address,bytes32,bytes)' + } + + self.events_dict['0x17307eab39ab6107e8899845ad3d59bd9653f200f220920489ca2b5937696c31'] = { + 'name': 'ApprovalForAll', 'signature': 'ApprovalForAll(address,address,bool)' + } + + self.events_dict['0x0e8e403c2d36126272b08c75823e988381d9dc47f2f0a9a080d95f891d95c469'] = { + 'name': 'WooSwap', 'signature': 'WooSwap(address,address,uint256,uint256,address,address,address,uint256,uint256)' + } + + self.events_dict['0x2717ead6b9200dd235aad468c9809ea400fe33ac69b5bfaa6d3e90fc922b6398'] = { + 'name': 'Withdrawal', 'signature': 'Withdrawal(address,address,uint256)' + } + + self.events_dict['0x3303facd24627943a92e9dc87cfbb34b15c49b726eec3ad3487c16be9ab8efe8'] = { + 'name': 'Accrued', 'signature': 'Accrued(address,address,address,uint256,uint256,uint256)' + } + + self.events_dict['0x112c256902bf554b6ed882d2936687aaeb4225e8cd5b51303c90ca6cf43a8602'] = { + 'name': 'Fees', 'signature': 'Fees(address,uint256,uint256)' + } + + self.events_dict['0x27c98e911efdd224f4002f6cd831c3ad0d2759ee176f9ee8466d95826af22a1c'] = { + 'name': 'WooRouterSwap', 'signature': 'WooRouterSwap(uint8,address,address,uint256,uint256,address,address,address)' + } + + self.events_dict['0x69ca02dd4edd7bf0a4abb9ed3b7af3f14778db5d61921c7dc7cd545266326de2'] = { + 'name': 'Transfer', 'signature': 'Transfer(address,uint256)' + } + + self.events_dict['0x055a181b27c0ef897e8c559755721e45a372d5ac946a2ae3905b8a4364e8745b'] = { + 'name': 'EventClaim', 'signature': 'EventClaim(uint256,uint256,uint256,address,address)' + } + + self.events_dict['0xddac40937f35385a34f721af292e5a83fc5b840f722bff57c2fc71adba708c48'] = { + 'name': 'Exchange', 'signature': 'Exchange(address,uint256,address)' + } + + self.events_dict['0x1fc3ecc087d8d2d15e23d0032af5a47059c3892d003d8e139fdcb6bb327c99a6'] = { + 'name': 'DistributedBorrowerComp', 'signature': 'DistributedBorrowerComp(address,address,uint256,uint256)' + } + + self.events_dict['0xb3d987963d01b2f68493b4bdb130988f157ea43070d4ad840fee0466ed9370d9'] = { + 'name': 'NameRegistered', 'signature': 'NameRegistered(uint256,address,uint256)' + } + + self.events_dict['0xca6abbe9d7f11422cb6ca7629fbf6fe9efb1c621f71ce8f02b9f2a230097404f'] = { + 'name': 'NameRegistered', 'signature': 'NameRegistered(string,bytes32,address,uint256,uint256)' + } + + self.events_dict['0x2f00e3cdd69a77be7ed215ec7b2a36784dd158f921fca79ac29deffa353fe6ee'] = { + 'name': 'Mint', 'signature': 'Mint(address,address,uint256,uint256)' + } + + self.events_dict['0x1eeaa4acf3c225a4033105c2647625dbb298dec93b14e16253c4231e26c02b1d'] = { + 'name': 'Swapped', 'signature': 'Swapped(address,address,address,uint256,uint256,address)' + } + + self.events_dict['0x47cee97cb7acd717b3c0aa1435d004cd5b3c8c57d70dbceb4e4458bbd60e39d4'] = { + 'name': 'Claim', 'signature': 'Claim(address,uint256)' + } + + self.events_dict['0x3f693fff038bb8a046aa76d9516190ac7444f7d69cf952c4cbdc086fdef2d6fc'] = { + 'name': 'Redeem', 'signature': 'Redeem(address,address,uint256,uint256)' + }