2024-08-30 17:12:40.941245 new snippets

seeker/report.txt

@@ -1,3 +1,29 @@
+--------------------------------------------------------------------------------
+ 2024-08-30 17:12:40.941245
+--------------------------------------------------------------------------------
+  On branch main
+Your branch is up to date with 'origin/main'.
+
+Changes not staged for commit:
+  (use "git add/rm <file>..." to update what will be committed)
+  (use "git restore <file>..." to discard changes in working directory)
+	deleted:    snippet/recept_analysis.py
+
+Untracked files:
+  (use "git add <file>..." to include in what will be committed)
+	snippet/bench.py
+	snippet/collect_data_openai_sample_imports.py
+	snippet/csv2star.py
+	snippet/disable.bash
+	snippet/docker_iptables
+	snippet/forty.java
+	snippet/mat_demo_v1.py
+	snippet/radar_chart_example.py
+	snippet/test.py
+	snippet/tts_backup.py
+
+no changes added to commit (use "git add" and/or "git commit -a")
+
 --------------------------------------------------------------------------------
  2024-08-29 17:11:54.148933
 --------------------------------------------------------------------------------

seeker/snippet/bench.py

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+#date: 2024-08-30T16:36:13Z
+#url: https://api.github.com/gists/6832dd94f8bb34a1a6a5a20de6af6132
+#owner: https://api.github.com/users/samwho
+
+import random
+import string
+import time
+from typing import Tuple
+
+import psycopg2
+from psycopg2.extensions import cursor
+from rich.console import Console
+from rich.table import Table
+
+LARGE_STRING = "a" * 64 * 1024
+
+
+def random_string(length: int = 10) -> str:
+    return "".join(random.choices(string.ascii_lowercase, k=length))
+
+
+def create_tables(cur: cursor) -> None:
+    cur.execute("""CREATE TABLE IF NOT EXISTS int_table
+                   (id INTEGER PRIMARY KEY, value TEXT)""")
+    cur.execute("""CREATE TABLE IF NOT EXISTS string_table
+                   (id TEXT PRIMARY KEY, value TEXT)""")
+
+
+def truncate_table(cur: cursor, table_name: str) -> None:
+    cur.execute(f"TRUNCATE TABLE {table_name}")
+    cur.connection.commit()
+
+
+def insert_data(
+    cur: cursor, table_name: str, data: list[Tuple[int | str, str]]
+) -> float:
+    total = 0
+    truncate_table(cur, table_name)
+    for record in data:
+        start_time = time.perf_counter()
+        cur.execute(f"INSERT INTO {table_name} (id, value) VALUES (%s, %s)", record)
+        cur.connection.commit()
+        end_time = time.perf_counter()
+        total += end_time - start_time
+    return total
+
+
+def read_data(cur: cursor, table_name: str, ids: list[int | str]) -> float:
+    total = 0
+    for id in ids:
+        start_time = time.perf_counter()
+        cur.execute(f"SELECT * FROM {table_name} WHERE id = %s", (id,))
+        cur.fetchone()
+        end_time = time.perf_counter()
+        total += end_time - start_time
+    return total
+
+
+def benchmark(num_records: int = 10000, num_reads: int = 1000) -> dict[str, float]:
+    # PostgreSQL connection parameters
+    conn_params = {
+        "dbname": "postgres",
+        "user": "postgres",
+        "password": "**********"
+        "host": "localhost",
+        "port": "5432",
+    }
+
+    conn = psycopg2.connect(**conn_params)
+    cur = conn.cursor()
+
+    # Ensure tables don't exist
+    cur.execute("DROP TABLE IF EXISTS int_table")
+    cur.execute("DROP TABLE IF EXISTS string_table")
+    conn.commit()
+
+    create_tables(cur)
+    conn.commit()
+
+    ints = list(range(num_records))
+    random_ints = ints
+    random.shuffle(random_ints)
+
+    # Prepare data
+    int_seq_data = [(i, LARGE_STRING) for i in ints]
+    int_random_data = [(i, LARGE_STRING) for i in random_ints]
+    str_seq_data = [(f"{i:010d}", LARGE_STRING) for i in ints]
+    str_random_data = [(random_string(), LARGE_STRING) for i in ints]
+
+    # Benchmark insertions
+    int_seq_insert = insert_data(cur, "int_table", int_seq_data)
+    int_random_insert = insert_data(cur, "int_table", int_random_data)
+    str_seq_insert = insert_data(cur, "string_table", str_seq_data)
+    str_random_insert = insert_data(cur, "string_table", str_random_data)
+
+    # Prepare read data
+    int_seq_ids = [i for i, _ in int_seq_data[:num_reads]]
+    int_random_ids = [i for i, _ in int_random_data[:num_reads]]
+    str_seq_ids = [i for i, _ in str_seq_data[:num_reads]]
+    str_random_ids = [i for i, _ in str_random_data[:num_reads]]
+
+    # Benchmark reads
+    int_seq_read = read_data(cur, "int_table", int_seq_ids)
+    int_random_read = read_data(cur, "int_table", int_random_ids)
+    str_seq_read = read_data(cur, "string_table", str_seq_ids)
+    str_random_read = read_data(cur, "string_table", str_random_ids)
+
+    cur.close()
+    conn.close()
+
+    return {
+        ("int", "sequential", "insert"): int_seq_insert,
+        ("int", "random", "insert"): int_random_insert,
+        ("str", "sequential", "insert"): str_seq_insert,
+        ("str", "random", "insert"): str_random_insert,
+        ("int", "sequential", "read"): int_seq_read,
+        ("int", "random", "read"): int_random_read,
+        ("str", "sequential", "read"): str_seq_read,
+        ("str", "random", "read"): str_random_read,
+    }
+
+
+if __name__ == "__main__":
+    n = 10000
+    results = benchmark(num_records=n, num_reads=n)
+
+    table = Table()
+
+    table.add_column("Type", style="cyan", no_wrap=True)
+    table.add_column("Mode", style="cyan", no_wrap=True)
+    table.add_column("Operation", style="cyan", no_wrap=True)
+    table.add_column("Time (seconds)", style="magenta")
+
+    for (type, mode, op), time in results.items():
+        table.add_row(type, mode, op, f"{time:.3f}")
+
+    console = Console()
+    console.print(table)
+table)

seeker/snippet/collect_data_openai_sample_imports.py

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+#date: 2024-08-30T17:12:04Z
+#url: https://api.github.com/gists/22d5da6fb48207927a0dc4b8ec62df0d
+#owner: https://api.github.com/users/zsasko
+
+import json
+from typing import AsyncGenerator, NoReturn
+
+import uvicorn
+from dotenv import load_dotenv
+from fastapi import FastAPI, WebSocket
+from fastapi.responses import HTMLResponse
+from openai import AsyncOpenAI
+
+load_dotenv()
+
+model = "gpt-3.5-turbo"
+conversation_history = []
+
+app = FastAPI()
+client = AsyncOpenAI()
+
+with open("index.html") as f:
+    html = f.read()

seeker/snippet/csv2star.py

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+#date: 2024-08-30T16:56:05Z
+#url: https://api.github.com/gists/7781ef8063e0102d7121d799efcb700f
+#owner: https://api.github.com/users/shahpnmlab
+
+import os
+import glob
+import pandas as pd
+import starfile
+
+# Function to read CSV files
+def read_csv_files(directory):
+    all_data = []
+    for filename in glob.glob(os.path.join(directory, '*.csv')):
+        df = pd.read_csv(filename, header=None, names=['X', 'Y', 'Z'])
+        tomogram_name = os.path.basename(filename).split('_')[1]
+        df['MicrographName'] = f'TS_{tomogram_name}'
+        all_data.append(df)
+    return pd.concat(all_data, ignore_index=True)
+
+# Read all CSV files
+data = read_csv_files('particle_lists')
+
+# Create the particles data block
+particles_data = pd.DataFrame({
+    'rlnMicrographName': data['MicrographName'],
+    'rlnCoordinateX': data['X'],
+    'rlnCoordinateY': data['Y'],
+    'rlnCoordinateZ': data['Z'],
+    'rlnOriginXAngst': [0] * len(data),
+    'rlnOriginYAngst': [0] * len(data),
+    'rlnOriginZAngst': [0] * len(data)
+})
+
+# Create the optics data block
+optics_data = pd.DataFrame({
+    'rlnOpticsGroup': [1,""],
+    'rlnOpticsGroupName': ['opticsGroup1',""],
+    'rlnSphericalAberration': [2.700000,""],
+    'rlnVoltage': [300.000000,""],
+    'rlnImagePixelSize': [13.48,""],
+    'rlnImageSize': [64,""],
+    'rlnImageDimensionality': [3,""],
+    'rlnPickingImagePixelSize': [13.48,""]
+})
+
+# Create the STAR file structure
+star_data = {
+    'optics': optics_data,
+    'particles': particles_data
+}
+
+# Write the STAR file
+starfile.write(star_data, 'particles.star', overwrite=True)
+
+print("particles.star file has been created successfully.")

seeker/snippet/disable.bash

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+#date: 2024-08-30T17:10:15Z
+#url: https://api.github.com/gists/f1825a7e2c54c2c6e46095f95c697285
+#owner: https://api.github.com/users/genzj
+
+#!/bin/bash
+
+# ref:
+#   https://askubuntu.com/a/1167767
+#   https://manpages.ubuntu.com/manpages/bionic/man5/NetworkManager.conf.5.html#connectivity%20section
+
+sudo cp --backup=t /etc/NetworkManager/NetworkManager.conf /etc/NetworkManager/NetworkManager.conf.backup
+echo -e "\n[connectivity]\nuri=\n" | sudo tee -a /etc/NetworkManager/NetworkManager.conf
+sudo systemctl restart NetworkManager.service