__init__.py 19.3 KB
Newer Older
Yannick Roehlly's avatar
Yannick Roehlly committed
1
# -*- coding: utf-8 -*-
2 3
# Copyright (C) 2012, 2013 Centre de données Astrophysiques de Marseille
# Licensed under the CeCILL-v2 licence - see Licence_CeCILL_V2-en.txt
Yannick Roehlly's avatar
Yannick Roehlly committed
4
# Authors: Yannick Roehlly, Médéric Boquien, Laure Ciesla
Yannick Roehlly's avatar
Yannick Roehlly committed
5

6
"""
Yannick Roehlly's avatar
Yannick Roehlly committed
7 8 9 10 11 12 13 14 15 16
This script is used the build pcigale internal database containing:
- The various filter transmission tables;
- The Maraston 2005 single stellar population (SSP) data;
- The Dale and Helou 2002 infra-red templates.

"""
import sys
import os
sys.path.append(os.path.join(os.path.dirname(__file__), '../'))
import glob
17
import io
18
import itertools
Yannick Roehlly's avatar
Yannick Roehlly committed
19 20
import numpy as np
from scipy import interpolate
21 22
import scipy.constants as cst
from pcigale.data import (Database, Filter, SspM2005, SspBC03, AgnFritz2006,
23
                          Dale2014, DL2007)
Yannick Roehlly's avatar
Yannick Roehlly committed
24 25


26 27 28 29 30
def read_bc03_ssp(filename):
    """Read a Bruzual and Charlot 2003 ASCII SSP file

    The ASCII SSP files of Bruzual and Charlot 2003 have se special structure.
    A vector is stored with the number of values followed by the values
Yannick Roehlly's avatar
Yannick Roehlly committed
31
    separated by a space (or a carriage return). There are the time vector, 5
32 33 34 35 36 37 38 39 40 41 42 43
    (for Chabrier IMF) or 6 lines (for Salpeter IMF) that we don't care of,
    then the wavelength vector, then the luminosity vectors, each followed by
    a 52 value table, then a bunch of other table of information that are also
    in the *colors files.

    Parameters
    ----------
    filename : string

    Returns
    -------
    time_grid: numpy 1D array of floats
Yannick Roehlly's avatar
Yannick Roehlly committed
44
              Vector of the time grid of the SSP in Myr.
45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116
    wavelength: numpy 1D array of floats
                Vector of the wavelength grid of the SSP in nm.
    spectra: numpy 2D array of floats
             Array containing the SSP spectra, first axis is the wavelength,
             second one is the time.

    """

    def file_structure_generator():
        """Generator used to identify table lines in the SSP file

        In the SSP file, the vectors are store one next to the other, but
        there are 5 informational lines after the time vector. We use this
        generator to the if we are on lines to read or not.
        """
        if "chab" in filename:
            bad_line_number = 5
        else:
            bad_line_number = 6
        yield("data")
        for i in range(bad_line_number):
            yield("bad")
        while True:
            yield("data")

    file_structure = file_structure_generator()
    # Are we in a data line or a bad one.
    what_line = file_structure.next()
    # Variable conting, in reverse order, the number of value still to
    # read for the read vector.
    counter = 0

    time_grid = []
    full_table = []
    tmp_table = []

    with open(filename) as file_:
        # We read the file line by line.
        for line in file_:
            if what_line == "data":
                # If we are in a "data" line, we analyse each number.
                for item in line.split():
                    if counter == 0:
                        # If counter is 0, then we are not reading a vector
                        # and the first number is the length of the next
                        # vector.
                        counter = int(item)
                    else:
                        # If counter > 0, we are currently reading a vector.
                        tmp_table.append(float(item))
                        counter -= 1
                        if counter == 0:
                            # We reached the end of the vector. If we have not
                            # yet store the time grid (the first table) we are
                            # currently reading it.
                            if time_grid == []:
                                time_grid = tmp_table[:]
                            # Else, we store the vector in the full table,
                            # only if its length is superior to 250 to get rid
                            # of the 52 item unknown vector and the 221 (time
                            # grid length) item vectors at the end of the
                            # file.
                            elif len(tmp_table) > 250:
                                full_table.append(tmp_table[:])

                            tmp_table = []

            # If at the end of a line, we have finished reading a vector, it's
            # time to change to the next structure context.
            if counter == 0:
                what_line = file_structure.next()

Yannick Roehlly's avatar
Yannick Roehlly committed
117
    # The time grid is in year, we want Myr.
118
    time_grid = np.array(time_grid, dtype=float)
Yannick Roehlly's avatar
Yannick Roehlly committed
119
    time_grid = time_grid * 1.e-6
120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137

    # The first "long" vector encountered is the wavelength grid. The value
    # are in Ångström, we convert it to nano-meter.
    wavelength = np.array(full_table.pop(0), dtype=float)
    wavelength = wavelength * 0.1

    # The luminosities are in Solar luminosity (3.826.10^33 ergs.s-1) per
    # Ångström, we convert it to W/nm.
    luminosity = np.array(full_table, dtype=float)
    luminosity = luminosity * 3.826e27
    # Transposition to have the time in the second axis.
    luminosity = luminosity.transpose()

    # In the SSP, the time grid begins at 0, but not in the *colors file, so
    # we remove t=0 from the SSP.
    return time_grid[1:], wavelength, luminosity[:, 1:]


138 139
def build_filters(base):
    filters_dir = os.path.join(os.path.dirname(__file__), 'filters/')
Yannick Roehlly's avatar
Yannick Roehlly committed
140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162
    for filter_file in glob.glob(filters_dir + '*.dat'):
        with open(filter_file, 'r') as filter_file_read:
            filter_name = filter_file_read.readline().strip('# \n\t')
            filter_type = filter_file_read.readline().strip('# \n\t')
            filter_description = filter_file_read.readline().strip('# \n\t')
        filter_table = np.genfromtxt(filter_file)
        # The table is transposed to have table[0] containing the wavelength
        # and table[1] containing the transmission.
        filter_table = filter_table.transpose()
        # We convert the wavelength from Å to nm.
        filter_table[0] *= 0.1

        print("Importing %s... (%s points)" % (filter_name,
                                               filter_table.shape[1]))

        new_filter = Filter(filter_name, filter_description,
                            filter_type, filter_table)

        # We normalise the filter and compute the effective wavelength.
        new_filter.normalise()

        base.add_filter(new_filter)

163 164 165

def build_m2005(base):
    m2005_dir = os.path.join(os.path.dirname(__file__), 'maraston2005/')
Yannick Roehlly's avatar
Yannick Roehlly committed
166

Yannick Roehlly's avatar
Yannick Roehlly committed
167 168
    # Age grid (1 Myr to 13.7 Gyr with 1 Myr step)
    age_grid = np.arange(1, 13701)
Yannick Roehlly's avatar
Yannick Roehlly committed
169 170 171 172 173 174 175 176 177 178 179 180 181 182 183

    # Transpose the table to have access to each value vector on the first
    # axis
    kroupa_mass = np.genfromtxt(m2005_dir + 'stellarmass.kroupa').transpose()
    salpeter_mass = \
        np.genfromtxt(m2005_dir + '/stellarmass.salpeter').transpose()

    for spec_file in glob.glob(m2005_dir + '*.rhb'):

        print("Importing %s..." % spec_file)

        spec_table = np.genfromtxt(spec_file).transpose()
        metallicity = spec_table[1, 0]

        if 'krz' in spec_file:
184
            imf = 'krou'
Yannick Roehlly's avatar
Yannick Roehlly committed
185 186
            mass_table = np.copy(kroupa_mass)
        elif 'ssz' in spec_file:
187
            imf = 'salp'
Yannick Roehlly's avatar
Yannick Roehlly committed
188 189 190 191 192 193 194 195
            mass_table = np.copy(salpeter_mass)
        else:
            raise ValueError('Unknown IMF!!!')

        # Keep only the actual metallicity values in the mass table
        # we don't take the first column which contains metallicity
        mass_table = mass_table[1:, mass_table[0] == metallicity]

Yannick Roehlly's avatar
Yannick Roehlly committed
196 197 198 199
        # Interpolate the mass table over the new age grid. We multiply per
        # 1000 because the time in Maraston files is given in Gyr.
        mass_table = interpolate.interp1d(mass_table[0] * 1000,
                                          mass_table)(age_grid)
Yannick Roehlly's avatar
Yannick Roehlly committed
200 201 202 203 204 205 206 207 208 209 210 211 212 213

        # Remove the age column from the mass table
        mass_table = np.delete(mass_table, 0, 0)

        # Remove the metallicity column from the spec table
        spec_table = np.delete(spec_table, 1, 0)

        # Convert the wavelength from Å to nm
        spec_table[1] = spec_table[1] * 0.1

        # For all ages, the lambda grid is the same.
        lambda_grid = np.unique(spec_table[1])

        # Creation of the age vs lambda flux table
214
        tmp_list = []
Yannick Roehlly's avatar
Yannick Roehlly committed
215 216 217 218
        for wavelength in lambda_grid:
            [age_grid_orig, lambda_grid_orig, flux_orig] = \
                spec_table[:, spec_table[1, :] == wavelength]
            flux_orig = flux_orig * 10 * 1.e-7  # From erg/s^-1/Å to W/nm
Yannick Roehlly's avatar
Yannick Roehlly committed
219
            age_grid_orig = age_grid_orig * 1000  # Gyr to Myr
Yannick Roehlly's avatar
Yannick Roehlly committed
220 221 222
            flux_regrid = interpolate.interp1d(age_grid_orig,
                                               flux_orig)(age_grid)

223 224 225 226 227 228 229 230
            tmp_list.append(flux_regrid)
        flux_age = np.array(tmp_list)

        # Use Z value for metallicity, not log([Z/H])
        metallicity = {-1.35: 0.001,
                       -0.33: 0.01,
                       0.0: 0.02,
                       0.35: 0.04}[metallicity]
Yannick Roehlly's avatar
Yannick Roehlly committed
231 232 233 234 235

        base.add_ssp_m2005(SspM2005(imf, metallicity, age_grid,
                                    lambda_grid, mass_table, flux_age))


236 237
def build_bc2003(base):
    bc03_dir = os.path.join(os.path.dirname(__file__), 'bc03//')
238

Yannick Roehlly's avatar
Yannick Roehlly committed
239 240
    # Time grid (1 Myr to 20 Gyr with 1 Myr step)
    time_grid = np.arange(1, 20000)
241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263

    # Metallicities associated to each key
    metallicity = {
        "m22": 0.0001,
        "m32": 0.0004,
        "m42": 0.004,
        "m52": 0.008,
        "m62": 0.02,
        "m72": 0.05
    }

    for key, imf in itertools.product(metallicity, ["salp", "chab"]):
        base_filename = bc03_dir + "bc2003_lr_" + key + "_" + imf + "_ssp"
        ssp_filename = base_filename + ".ised_ASCII"
        color3_filename = base_filename + ".3color"
        color4_filename = base_filename + ".4color"

        print("Importing %s..." % base_filename)

        # Read the desired information from the color files
        color_table = []
        color3_table = np.genfromtxt(color3_filename).transpose()
        color4_table = np.genfromtxt(color4_filename).transpose()
264 265 266 267 268 269 270
        color_table.append(color4_table[6])        # Mstar
        color_table.append(color4_table[7])        # Mgas
        color_table.append(10 ** color3_table[5])  # NLy
        color_table.append(color3_table[1])        # B4000
        color_table.append(color3_table[2])        # B4_VN
        color_table.append(color3_table[3])        # B4_SDSS
        color_table.append(color3_table[4])        # B(912)
271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289

        color_table = np.array(color_table)

        ssp_time, ssp_wave, ssp_lumin = read_bc03_ssp(ssp_filename)

        # Regrid the SSP data to the evenly spaced time grid.
        color_table = interpolate.interp1d(ssp_time, color_table)(time_grid)
        ssp_lumin = interpolate.interp1d(ssp_time,
                                         ssp_lumin)(time_grid)

        base.add_ssp_bc03(SspBC03(
            imf,
            metallicity[key],
            time_grid,
            ssp_wave,
            color_table,
            ssp_lumin
        ))

290 291 292

def build_dh2002(base):
    dh2002_dir = os.path.join(os.path.dirname(__file__), 'dh2002/')
Yannick Roehlly's avatar
Yannick Roehlly committed
293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309

    # Getting the alpha grid for the templates
    dhcal = np.genfromtxt(dh2002_dir + 'dhcal.dat')
    alpha_grid = dhcal[:, 1]

    # Getting the lambda grid for the templates (we checked that all share the
    # same grid).
    first_template = np.genfromtxt(dh2002_dir + 'irdh01.spec', skip_header=1)
    lambda_grid = first_template[:, 0] * 0.1  # Convert Å to nm

    templates = []

    for i in range(len(alpha_grid)):
        filename = dh2002_dir + 'irdh' + ("%02d" % (i + 1)) + '.spec'
        print("Importing %s..." % filename)
        table = np.genfromtxt(filename, skip_header=1)[:, 1]  # Luminosity
                                                              # column
310
        # The table give the luminosity density in Lsun/Å normalised to 1 Lsun
Yannick Roehlly's avatar
Yannick Roehlly committed
311 312 313 314 315 316 317 318 319 320 321
        # over the full spectrum. As we converted the wavelengths to nm, we
        # must multiply the density per 10 to keep the normalisation.
        table = table * 10
        templates.append(table)

    templates = np.array(templates)

    data = (alpha_grid, lambda_grid, templates)

    base.add_dh2002_infrared_templates(data)

322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363
def build_dale2014(base):

    dh2002_dir = os.path.join(os.path.dirname(__file__), 'dh2002/')
    dale2014_dir = os.path.join(os.path.dirname(__file__), 'dale2014/')

    # Getting the alpha grid for the templates
    d14cal = np.genfromtxt(dh2002_dir + 'dhcal.dat')
    alpha_grid = d14cal[:, 1]

    # Getting the lambda grid for the templates and convert from microns to nm.
    first_template = np.genfromtxt(dale2014_dir + 'spectra.0.00AGN.dat')
    wave = first_template[:, 0] * 1E3

    # Getting the stellar emission and interpolate it at the same wavelength grid
    stell_emission_file = np.genfromtxt(dale2014_dir + 'stellar_SED_age13Gyr_tau10Gyr.spec')
    # A -> to nm
    wave_stell = stell_emission_file[:,0] * 0.1
    # W/A -> W/nm
    stell_emission = stell_emission_file[:,1] * 10
    stell_emission_interp = np.interp(wave,wave_stell,stell_emission)

    # The models are in nuFnu and contain stellar emission.
    # We convert this to W/nm and remove the stellar emission.

    # Emission from dust heated by SB
    fraction = 0.0
    filename = dale2014_dir + "spectra.0.00AGN.dat"
    print("Importing {}...".format(filename))
    datafile = open(filename)
    data = "".join(datafile.readlines())
    datafile.close()

    for al in range(1,len(alpha_grid),1):
        lumin_with_stell = np.genfromtxt(io.BytesIO(data.encode()), usecols=(al))
        lumin_with_stell = pow(10,lumin_with_stell) / wave
        constant = lumin_with_stell[7] / stell_emission_interp[7]
        lumin = lumin_with_stell - stell_emission_interp * constant
        lumin[lumin<0] = 0
        lumin[wave<2E3] = 0
        norm = np.trapz(lumin, x = wave)
        lumin = lumin/norm

364
        base.add_dale2014(Dale2014(fraction, alpha_grid[al-1], wave, lumin))
365 366 367 368 369 370 371 372 373 374 375 376 377 378 379 380

    # Emission from dust heated by AGN - Quasar template
    fraction = 1.0
    filename = dale2014_dir + "spectra.1.00AGN.dat"
    print("Importing {}...".format(filename))
    datafile = open(filename)
    data = "".join(datafile.readlines())
    datafile.close()

    for al in range(1,len(alpha_grid),1):
        lumin_quasar = np.genfromtxt(io.BytesIO(data.encode()), usecols=(al))
        lumin_quasar = pow(10,lumin_quasar) / wave
        lumin_quasar[lumin_quasar<0] = 0
        norm = np.trapz(lumin_quasar, x = wave)
        lumin_quasar = lumin_quasar/norm

381
        base.add_dale2014(Dale2014(fraction, alpha_grid[al-1], wave, lumin_quasar))
382

383

384 385 386 387 388 389 390 391 392 393 394 395 396 397 398 399 400 401 402 403 404 405 406 407 408 409 410 411 412 413 414 415 416 417 418 419 420 421 422 423 424 425 426 427 428 429 430 431 432 433 434 435 436 437 438 439 440 441 442 443 444 445 446 447 448 449 450 451 452 453 454 455
def build_dl2007(base):
    dl2007_dir = os.path.join(os.path.dirname(__file__), 'dl2007/')

    qpah = {
        "00": 0.47,
        "10": 1.12,
        "20": 1.77,
        "30": 2.50,
        "40": 3.19,
        "50": 3.90,
        "60": 4.58
    }

    umaximum = ["1e3", "1e4", "1e5", "1e6"]
    uminimum = ["0.10", "0.15", "0.20", "0.30", "0.40", "0.50", "0.70",
                "0.80", "1.00", "1.20", "1.50", "2.00", "2.50", "3.00",
                "4.00", "5.00", "7.00", "8.00", "10.0", "12.0", "15.0",
                "20.0", "25.0"]

    # Here we obtain the wavelength beforehand to avoid reading it each time.
    datafile = open(dl2007_dir + "U{}/U{}_{}_MW3.1_{}.txt".format(umaximum[0],
                                                                  umaximum[0],
                                                                  umaximum[0],
                                                                  "00"))
    data = "".join(datafile.readlines()[-1001:])
    datafile.close()

    wave = np.genfromtxt(io.BytesIO(data.encode()), usecols=(0))
    # For some reason wavelengths are decreasing in the model files
    wave = wave[::-1]
    # We convert wavelengths from μm to nm
    wave *= 1000.

    # The models are in Jy cm² sr¯¹ H¯¹. We convert this to W/nm.
    conv = 4. * np.pi * 1e-30 / cst.m_p * cst.c / (wave * wave) * 1e9

    for model in sorted(qpah.keys()):
        for umin in uminimum:
            filename = dl2007_dir + "U{}/U{}_{}_MW3.1_{}.txt".format(umin,
                                                                     umin,
                                                                     umin,
                                                                     model)
            print("Importing {}...".format(filename))
            datafile = open(filename)
            data = "".join(datafile.readlines()[-1001:])
            datafile.close()
            lumin = np.genfromtxt(io.BytesIO(data.encode()), usecols=(2))
            # For some reason fluxes are decreasing in the model files
            lumin = lumin[::-1]
            # Conversion from Jy cm² sr¯¹ H¯¹ to W/nm
            lumin *= conv

            base.add_dl2007(DL2007(qpah[model], umin, umin, wave, lumin))
            for umax in umaximum:
                filename = dl2007_dir + "U{}/U{}_{}_MW3.1_{}.txt".format(umin,
                                                                         umin,
                                                                         umax,
                                                                         model)
                print("Importing {}...".format(filename))
                datafile = open(filename)
                data = "".join(datafile.readlines()[-1001:])
                datafile.close()
                lumin = np.genfromtxt(io.BytesIO(data.encode()), usecols=(2))
                # For some reason fluxes are decreasing in the model files
                lumin = lumin[::-1]

                # Conversion from Jy cm² sr¯¹ H¯¹ to W/nm
                lumin *= conv

                base.add_dl2007(DL2007(qpah[model], umin, umax, wave, lumin))


456 457
def build_fritz2006(base):
    fritz2006_dir = os.path.join(os.path.dirname(__file__), 'fritz2006/')
458 459 460 461 462 463 464 465 466 467 468 469 470 471 472 473 474 475 476 477 478 479 480 481 482 483 484

    model_list = np.genfromtxt(fritz2006_dir + "fritz.dat")

    for model_line in model_list:

        (model_nb, agn_type, r_ratio, tau,
         beta, gamma, theta, psy) = model_line

        # Convert some floats to int
        model_nb = int(model_nb)
        agn_type = int(agn_type)

        wave, lumin = np.genfromtxt("{}AGN_fritz{}.spec".format(fritz2006_dir,
                                                                model_nb),
                                    skip_header=1).transpose()

        # Convert the wavelength from Å to nm
        wave = wave * 0.1

        # Convert the luminosity from erg/s^-1/Å to W/nm
        lumin = lumin * 10 * 1.e-7

        agn = AgnFritz2006(model_nb, agn_type, r_ratio, tau, beta, gamma,
                           theta, psy, wave, lumin)

        base.add_fritz2006_agn(agn)

485 486 487 488 489 490 491 492 493 494 495 496 497 498 499 500 501 502 503 504 505 506 507 508 509 510

def build_base():
    base = Database(writable=True)
    base.upgrade_base()

    print('#' * 78)
    print("1- Importing filters...\n")
    build_filters(base)
    print("\nDONE\n")
    print('#' * 78)

    print("2- Importing Maraston 2005 SSP\n")
    build_m2005(base)
    print("\nDONE\n")
    print('#' * 78)

    print("3- Importing Bruzual and Charlot 2003 SSP\n")
    build_bc2003(base)
    print("\nDONE\n")
    print('#' * 78)

    print("4- Importing Dale and Helou (2002) templates\n")
    build_dh2002(base)
    print("\nDONE\n")
    print('#' * 78)

511 512 513 514 515 516
    print("5- Importing Draine and Li (2007) templates\n")
    build_dl2007(base)
    print("\nDONE\n")
    print('#' * 78)

    print("6- Importing Fritz et al. (2006) models\n")
517
    build_fritz2006(base)
Yannick Roehlly's avatar
Yannick Roehlly committed
518 519 520
    print("\nDONE\n")
    print('#' * 78)

521 522 523 524 525
    print("7- Importing Dale et al (2014) templates\n")
    build_dale2014(base)
    print("\nDONE\n")
    print('#' * 78)

526 527
    base.session.close_all()

Yannick Roehlly's avatar
Yannick Roehlly committed
528 529 530

if __name__ == '__main__':
    build_base()