Use 'trapz' instead of 'trapezoid' consistently

#!/usr/bin/env python3

# encoding: utf-8

# Author: Akke Viitanen

# Email: akke.viitanen@helsinki.fi

# Date: <++>

"""

<+A python3 script template. Remove this line and add your description.+>

"""

import argparse

import glob

import math

import os

import random

import re

import subprocess

import sys

import time

import astropy as ap

import astropy.coordinates as c

import astropy.units as u

import fitsio

import matplotlib as mpl

import matplotlib.pyplot as plt

import numpy as np

import scipy as sp

import pyvo

tap_service = pyvo.dal.TAPService("https://datalab.noirlab.edu/tap")

query = f"""

SELECT TOP 100 * FROM lsst_sim.simdr2 WHERE

(0 <= pmode AND pmode <= 1) AND

(4 <= label AND label <= 6)

"""

print(query)

print("Getting the results")

tap_results = tap_service.search(query)

print("Converting to table")

table = tap_results.to_table()

print("Writing to file")

table.write("stars.fits")

#!/usr/bin/env python3

# encoding: utf-8

# Author: Akke Viitanen

# Email: akke.viitanen@helsinki.fi

# Date: 2024-06-14 12:21:18

"""

Get cepheid lightcurves

"""

import glob

from astropy.table import Table

import fitsio

import matplotlib.pyplot as plt

import numpy as np

def parse_filename_cepheid(filename):

    """

    Return the parameters from the filename

    """

    parts = filename.replace("/", "_").split("_")

    parts = parts[-10:]

    return {

        "z":      float(parts[0][1:]),

        "y":      float(parts[1][1:]),

        "logte":  np.log10(float(parts[3])),

        "logl":   float(parts[4]),

        "mass":   float(parts[5]),

        "pmode":  {"F": 0, "FO": 1}[parts[8]],

    }

def get_lightcurve_template_cepheid(source):

    """

    Return the closest lightcurve template according the given parameters

    """

    columns = ("z", "y", "logte", "logl", "mass")

    pmode = source["pmode"]

    dist = []

    vec1 = np.array([source[k] for k in columns])

    filenames = glob.glob(f"CEP_lsst_quasar_project/*/*_%s_lsst.csv" % (["F", "FO"][pmode]))

    for filename in filenames:

        parameters = parse_filename_cepheid(filename)

        vec2 = np.array([parameters[k] for k in columns])

        delta = vec1 - vec2

        dist.append(np.sum(delta ** 2))

    idx = np.argmin(dist)

    table = Table.read(filenames[idx])

    return table

import util

def get_lightcurve_normalized_cepheid(source, band):

    # Find the best lightcurve template

    template = get_lightcurve_template_cepheid(source)

    select = (0 <= template["phase"]) * (template["phase"] <= 1)

    template = template[select]

    # The template spells 'y' with a capital 'Y'

    b = band.replace("lsst-", "")

    key = "Y" if b == 'y' else b

    time1 = template["phase"] * template["P"]

    flux1 = util.mag_to_flux(10 ** (-0.4 * template[f"{key}_lsst"]))

    # Normalize the period to the period of the source

    period = source["period%d" % source["pmode"]]

    time2 = time1 / template["P"] * period

    # Normalize the flux to the mean flux of the source

    flux2 = flux1 / flux1.mean() * util.mag_to_flux(source[f"{b}mag"])

    return time2, flux2