Last Update: 2024.10.27

1. SQL (Recommended)

Let’s say LAAKE DataBase (DB) is saved in db_path and we want to read light curve for source named objname. For example,

db_path = '/Users/kamp/Desktop/KAMP/LAAKE/output/N59_2016.db'
objname = 'J...'

Check available tables from DB

import sqlite3

conn = sqlite3.connect(db_path)
cursor = conn.cursor()

cursor.execute("SELECT name FROM sqlite_master WHERE type='table';")
tables_list = [i[0] for i in cursor.fetchall()]

cursor.close()
conn.close()

print(tables_list)

Select the table you wish to navigate (tb_name) and the source name (objname). Then run the following SQL query to read light curve (lc)

import pandas as pd

tb_name = tables_list[0]
sql_prompt = f"SELECT * FROM {tb_name} WHERE Jname = '{objname}'"

conn = sqlite3.connect(db_path)
lc = pd.read_sql(sql_prompt, conn)
conn.close()

2. CSV

Developer’s Note: Reading light curve directly from CSV will be depreciated in later version, due to intense pressure on RAM.

Let’s say LAAKE CSV file is saved in csv_path and we want to read light curve for source named objname. For example,

csv_path = '/Users/kamp/Desktop/KAMP/LAAKE/output/N59_2016_CTIO_B.csv'
objname = 'J...'

Use pandas.Dataframe.read_csv or dask.dataframe.read_csv to read entire CSV file

# Using pandas
import pandas as pd
df = pd.read_csv(csv_path, sep=' ')

# Using dask (for parallel computation)
import dask.dataframe as dd
ddf = dd.read_csv(csv_path, sep=' ')
df = ddf.compute()