コード例 #1
0
    def test_create_tables_normal(self):
        method_list = methods.builtin_method_functions()
        cosmology_list = cosmologies.builtin_cosmology_functions()

        # Create a lookup table for each method and cosmology
        for method in method_list:
            for key in cosmology_list:
                here = os.getcwd()

                cosmo = cosmologies.builtin_cosmology_functions()[key]
                filename = "_".join(["pytest_output", method, key])
                table.create(method=method, filename=filename,
                             cosmo=cosmo, output_dir=here, zmin=0,
                             zmax=20, num_samples=10000)

                # Compare new tables to existing tables for 4 dm values
                pre_calc_fn = ".".join(["_".join([method, key]), "npz"])
                new_calc_fn = "".join([filename, ".npz"])

                pre_calc = table.load(pre_calc_fn)
                new_calc = table.load(new_calc_fn, data_dir=here)

                test_dm_list = [0, 100, 1000, 2000]

                for dm in test_dm_list:
                    new_z = table.get_z_from_table(dm, new_calc)
                    pre_z = table.get_z_from_table(dm, pre_calc)
                    assert new_z == pre_z
コード例 #2
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def cosmology_comparison(filename="",
                         extension="png",
                         usetex=False,
                         passed_ax=None,
                         **kwargs):
    """
    Create a plot comparing how the estimated redshift changes as a
    function of dispersion mesure for each cosmology.

    Parameters
    ----------
    filename: string, optional
    The filename of the saved figure. Default: "cosmology_comparison"

    extension: string, optional
        The format to save the figure. e.g "png", "pdf", "eps", etc...
        Default: "png"

    Generates
    ---------
    A figure displaying how estimated redshift changes as a function of
    dispersion measure for each of the different cosmologies.
    """
    # Update rcParams for consistent plotting style
    plt.rcParams.update(set_rc_params(usetex=usetex))

    if passed_ax:
        ax = passed_ax
    else:
        fig = plt.figure(figsize=(8, 8), constrained_layout=True)
        ax = fig.add_subplot(111)

    # Remove EAGLE from cosmologies since it is the same as Planck13
    cosmology_list = cosmologies.builtin_cosmology_functions()
    cosmology_list.pop("EAGLE")

    dm_vals = np.linspace(0, 3000, 1000)

    add_axin = True
    try:
        # Add inset plot showing the part where cosmologies diverge the most.
        axin = ax.inset_axes([0.05, 0.52, 0.45, 0.45])
    except Exception:
        print("""Skipping inset axis in cosmology plot. Requires Python 3 and
              Matplotlib 3.0""")
        add_axin = False

    colours = [
        '#a6cee3', '#1f78b4', '#b2df8a', '#33a02c', '#fb9a99', '#e31a1c'
    ]
    label = [
        r"$\rm{WMAP5}$", r"$\rm{WMAP7}$", r"$\rm{WMAP9}$", r"$\rm{Planck13}$",
        r"$\rm{Planck15}$", r"$\rm{Planck18}$"
    ]

    for j, cosmo in enumerate(cosmology_list):
        z_vals = np.zeros(len(dm_vals))
        if 'method' in kwargs:
            method = kwargs['method']
        else:
            method = 'Inoue2004'

        table_name = "{}.hdf5".format(method)
        table_name = utils.get_path_to_file_from_here(table_name,
                                                      subdirs=["data"])
        for i, dm in enumerate(dm_vals):
            z_vals[i] = table.get_z_from_table(dm, table_name, cosmo)

        ax.plot(dm_vals, z_vals, colours[j], label=label[j], **kwargs)
        if add_axin:
            axin.plot(dm_vals, z_vals, colours[j], **kwargs)

    ax.set_xlabel(r"$\rm{DM\ \left[pc \ cm^{-3}\right]}$")

    if not passed_ax:
        ax.set_ylabel(r"$\rm{Redshift}$")

    ax.legend(loc='lower right', frameon=False)

    if add_axin:
        axin.set_xlim(2800, 3000)
        axin.set_ylim(3.0, 3.25)
        axin.xaxis.set_tick_params(labelsize=8)
        axin.yaxis.set_tick_params(labelsize=8)

        ax.indicate_inset_zoom(axin)

    if filename != "":
        plt.savefig(".".join([filename, extension]))

    if passed_ax:
        return ax
    else:
        return fig
コード例 #3
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def method_comparison(filename=None,
                      extension="png",
                      usetex=False,
                      passed_ax=None,
                      **kwargs):
    """
    Create a plot comparing how estimated redshift changes as a
    function of dispersion measure for each DM-z relation.

    Parameters
    ----------
    filename: string or None, optional
        The filename of the saved figure. Default: *None*

    extension: string, optional
        The format to save the figure. e.g "png", "pdf", "eps", etc...
        Default: "png"

    usetex: bool, optional
        Use LaTeX for for fonts.

    passed_ax: or None, optional

    Generates
    ---------
    A figure displaying how estimated redshift changes as a function of
    dispersion measure for each of the different cosmologies.
    """
    # Update rcParams for consistent plotting style
    plt.rcParams.update(set_rc_params(usetex=usetex))

    if passed_ax:
        ax = passed_ax
    else:
        fig = plt.figure(figsize=(8, 8), constrained_layout=True)
        ax = fig.add_subplot(111)

    method_list = methods.builtin_method_functions()
    method_list.pop("Batten2021")
    dm_vals = np.linspace(0, 3000, 1000)

    colours = ["#1b9e77", "#d95f02", "#7570b3"]
    label = [r"$\rm{Ioka 2003}$", r"$\rm{Inoue 2004}$", r"$\rm{Zhang 2018}$"]

    for j, method in enumerate(method_list):
        z_vals = np.zeros(len(dm_vals))
        if 'cosmology' in kwargs:
            cosmology = kwargs['cosmology']
        else:
            cosmology = 'Planck18'

        table_name = "{}.hdf5".format(method)
        table_name = utils.get_path_to_file_from_here(table_name,
                                                      subdirs=["data"])

        for i, dm in enumerate(dm_vals):
            z_vals[i] = table.get_z_from_table(dm, table_name, cosmology)

        ax.plot(dm_vals, z_vals, colours[j], label=label[j], **kwargs)

    if not passed_ax:
        ax.set_ylabel(r"$\rm{Redshift}$")

    ax.set_xlabel(r"$\rm{DM\ \left[pc \ cm^{-3}\right]}$")
    ax.legend(loc='lower right', frameon=False)

    if filename is not None:
        plt.savefig(".".join([filename, extension]))

    if passed_ax:
        return ax
    else:
        return fig
コード例 #4
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    def calc_redshift(self,
                      method='Batten2021',
                      cosmology="Planck18",
                      subtract_host=False,
                      lookup_table=None):
        """
        Calculate the redshift of the FRB from its :attr:`dm`,
        :attr:`dm_excess` or :attr:`dm_excess` - :attr:`dm_host_est`.

        Parameters
        ----------
        method : str, optional
            The dispersion meausre -redshift relation to use when
            calculating the redshift. Avaliable methods:  %(meth)s.
            Default: 'Inoue2004'

        cosmology : str, optional
            The cosmology to assume when calculating the redshift.
            Avaliable cosmologies: %(cosmo)s. Default: 'Planck18'

        subtract_host : bool, optional
            Subtract :attr:`dm_host_est` from the :attr:`dm_excess`
            before calculating the redshift. This is is used to account
            for the dispersion measure that arises from the FRB host
            galaxy. Default: False

        lookup_table : str or None, optional
            The path to the lookup table file. If ``lookup_table=None``
            a table will attempted to be loaded from the data directory
            based on the method name. Default: *None*

        Returns
        -------
        float
            The redshift of the FRB.

        Notes
        -----
        The methods_ section in the documentation has a description for
        each of the builtin methods.

        The cosmology_ section in the documentation has a list of the
        cosmological parameters for each cosmology

        .. _cosmology: https://fruitbat.readthedocs.io/en/latest/user_guide/method_and_cosmology.html#cosmology
        .. _methods: https://fruitbat.readthedocs.io/en/latest/user_guide/method_and_cosmology.html#methods

        """
        utils.check_type("subtract_host", subtract_host, bool)

        if subtract_host:
            input_dm = self.dm_excess - self.dm_host_est
            print(input_dm)
        else:
            input_dm = self.dm_excess

        # If the user provides a table use that table for estimation.
        if lookup_table is not None:
            raise NotImplementedError("Not made yet!")

        if method not in methods.available_methods():
            err_msg = ("Method '{}' is not a valid method. "
                       "Valid methods are: {}".format(
                           method, methods.available_methods()))
            raise ValueError(err_msg)

        if method in methods.methods_hydrodynamic():
            zvals, pdf, dz = self.calc_redshift_pdf(method=method)
            z_median = utils.calc_median_from_pdf(zvals, pdf)
            self.z = z_median
            self.method = method
            if method == "Batten2020":
                self.cosmology = "EAGLE"

        elif method in methods.methods_analytic():
            if cosmology in cosmologies.available_cosmologies():
                #if method in methods.builtin_method_functions().keys():
                table_name = table.get_table_path(method)
                self.z = table.get_z_from_table(input_dm, table_name,
                                                cosmology)
                self.cosmology = cosmology
                self.method = method

            else:
                err_msg = ("Cosmology '{}' is not a valid cosmology. Valid "
                           "cosmologies are: {}".format(
                               cosmology, cosmologies.available_cosmologies()))
                raise ValueError(err_msg)

        else:
            table_name = utils.get_path_to_file_from_here(
                "{}.hdf5".format(method), subdirs=["data"])
            self.z = table.get_z_from_table(input_dm, table_name)
            self.cosmology = cosmology
            self.method = method

        return self.z
コード例 #5
0
    def calc_redshift(self,
                      method='Inoue2004',
                      cosmology="Planck18",
                      subtract_host=False,
                      lookup_table=None):
        """
        Calculate the redshift of the FRB from its :attr:`dm`,
        :attr:`dm_excess` or :attr:`dm_excess` - :attr:`dm_host_est`.

        Parameters
        ----------
        method : str, optional
            The dispersion meausre -redshift relation to use when 
            calculating the redshift. Avaliable methods:  %(meth)s. 
            Default: 'Inoue2004'

        cosmology : str, optional
            The cosmology to assume when calculating the redshift. 
            Avaliable cosmologies: %(cosmo)s. Default: 'Planck18'

        subtract_host : bool, optional
            Subtract :attr:`dm_host_est` from the :attr:`dm_excess`
            before calculating the redshift. This is is used to account
            for the dispersion measure that arises from the FRB host
            galaxy. Default: False

        lookup_table : str or None, optional
            The path to the lookup table file. If ``lookup_table=None``
            a table will attempted to be loaded from the data directory 
            based on the method name. Default: *None*       

        Returns
        -------
        float
            The redshift of the FRB.

        Notes
        -----
        The methods_ section in the documentation has a description for
        each of the builtin methods.

        The cosmology_ section in the documentation has a list of the
        cosmological parameters for each cosmology

        .. _cosmology: https://fruitbat.readthedocs.io/en/latest/user_guide/method_and_cosmology.html#cosmology
        .. _methods: https://fruitbat.readthedocs.io/en/latest/user_guide/method_and_cosmology.html#methods
        """
        if not isinstance(subtract_host, bool):
            raise ValueError("subtract_host must be of type bool.")

        if subtract_host:
            input_dm = self.dm_excess - self.dm_host_est
        else:
            input_dm = self.dm_excess

        if method not in methods.available_methods():
            err_msg = ("Method '{}' is not a valid method. "
                       "Valid methods are: {}".format(
                           method, methods.available_methods()))
            raise ValueError(err_msg)

        if cosmology not in cosmologies.available_cosmologies():
            err_msg = ("Cosmology '{}' is not a valid cosmology. Valid "
                       "cosmologies are: {}".format(
                           cosmology, cosmologies.available_cosmologies()))
            raise ValueError(err_msg)

        # If the user provides a table use that table for estimation.
        if lookup_table is not None:
            lookup_table = table.load(lookup_table)

        else:
            if method in methods.builtin_method_functions().keys():
                table_name = "".join(["_".join([method, cosmology]), ".npz"])
            else:
                table_name = "".join(["custom_", method, ".npz"])

            lookup_table = table.load(table_name)

        self.z = table.get_z_from_table(input_dm, lookup_table)
        lookup_table.close()

        self.cosmology = cosmology
        self.method = method
        return self.z
コード例 #6
0
ファイル: old_dmz_plot.py プロジェクト: abatten/admire
method_list = methods.available_methods()

colours = ["#66c2a5", "#e7298a", "#8da0cb"]
label = [r"$\rm{Ioka\ 2003}$", r"$\rm{Inoue\ 2004}$", r"$\rm{Zhang\ 2018}$"]
lstyle = ["-", "--", "-."]

for j, method in enumerate(method_list):
    z_vals = np.zeros(len(dm_vals))
    cosmology = 'Planck18'

    table_name = "".join(["_".join([method, cosmology]), ".npz"])
    lookup_table = table.load(table_name)

    for i, dm in enumerate(dm_vals):
        z_vals[i] = table.get_z_from_table(dm, lookup_table)
    ax.plot(z_vals,
            np.log10(dm_vals),
            colours[j],
            linestyle=lstyle[j],
            label=label[j],
            linewidth=2)

#divider = make_axes_locatable(ax)
#cax = divider.append_axes("right", size="5%", pad=0.05)
legend = plt.legend(frameon=False, fontsize=20)
plt.setp(legend.get_texts(), color='w')

#plt.colorbar(im, cax=cax)

plt.savefig("postimage_magma_lines_colorbar.png", dpi=800)