Emissivity compiling and loading.

hoki/constants.py

@@ -40,6 +40,8 @@
               "imf135_100", "imf135_300", "imf135all_100", "imf170_100",
               "imf170_300"]
 
+# wavelengths at which spectra are given [angstrom]
+BPASS_WAVELENGTHS = np.arange(1, 100001)
 
 # Create a deprecation warning when using dummy_dict
 dummy_dict = {'timestep': 0, 'age': 1, 'log(R1)': 2, 'log(T1)': 3, 'log(L1)': 4, 'M1': 5, 'He_core1': 6, 'CO_core1': 7,

hoki/csp/tests/test_spectra.py

@@ -13,7 +13,6 @@
 from hoki.csp.spectra import CSPSpectra
 from hoki.load import model_output
 from hoki.constants import BPASS_NUM_METALLICITIES
-import itertools
 data_path = pkg_resources.resource_filename('hoki', 'data')
 
 # Load Test spectra. Not an actual spectra.

hoki/data_compilers.py

@@ -1,14 +1,14 @@
 """
-Author: Max Briel & Heloise Stevance
+Author: Heloise Stevance, Max Briel, & Martin Glatzle
 
 Objects and pipelines that compile BPASS data files into more convenient, more pythonic data types
 """
-
+import abc
 import numpy as np
-
 from hoki.constants import (DEFAULT_BPASS_VERSION, MODELS_PATH,
                             OUTPUTS_PATH, dummy_dicts,
-                            BPASS_IMFS, BPASS_METALLICITIES)
+                            BPASS_IMFS, BPASS_METALLICITIES,
+                            BPASS_WAVELENGTHS, BPASS_TIME_BINS)
 import hoki.load
 import pandas as pd
 import re
@@ -17,6 +17,120 @@
 from hoki.utils.exceptions import HokiFatalError, HokiUserWarning, HokiFormatError, HokiKeyError
 from hoki.utils.hoki_object import HokiObject
 
+class _CompilerBase(abc.ABC):
+    def __init__(self, input_folder, output_folder, imf, binary=True,
+                 verbose=False):
+        if verbose:
+            _print_welcome()
+
+        # Check population type
+        star = "bin" if binary else "sin"
+
+        # check IMF key
+        if imf not in BPASS_IMFS:
+            raise HokiKeyError(
+                f"{imf} is not a BPASS IMF. Please select a correct IMF.")
+
+        # Setup the numpy output
+        output = np.empty(self._shape(), dtype=np.float64)
+
+        # loop over all the metallicities and load all the spectra
+        for num, metallicity in enumerate(BPASS_METALLICITIES):
+            print_progress_bar(num, 12)
+            # Check if file exists
+            assert isfile(f"{input_folder}/spectra-{star}-{imf}.{metallicity}.dat"),\
+                   "HOKI ERROR: This file does not exist, or its path is incorrect."
+            output[num] = self._load_single(
+                f"{input_folder}/{self._input_name()}-{star}-{imf}.{metallicity}.dat"
+            )
+
+        np.save(f"{output_folder}/{self._output_name()}-{star}-{imf}", output)
+        # pickle the datafile
+        self.output = output
+        print(
+            f"Compiled data stored in {output_folder} as '{self._output_name()}-{star}-{imf}.npy'")
+        if verbose:
+            _print_exit_message()
+        return
+
+    @abc.abstractmethod
+    def _input_name(self):
+        return
+
+    @abc.abstractmethod
+    def _output_name(self):
+        return
+
+    @abc.abstractmethod
+    def _shape(self):
+        return
+
+    @abc.abstractmethod
+    def _load_single(self, path):
+        return
+
+class SpectraCompiler(_CompilerBase):
+    """
+    Pipeline to load the BPASS spectra txt files and save them as a 3D
+    `numpy.ndarray` binary file.
+
+    Attributes
+    output : `numpy.ndarray` (N_Z, N_age, N_lam) [(metallicity, log_age, wavelength)]
+    ----------
+        A 3D numpy array containing all the BPASS spectra for a specific imf
+        and binary or single star population.
+        Usage: spectra[1][2][1000]
+                (gives L_\\odot for Z=0.0001 and log_age=6.2 at 999 Angstrom)
+    """
+
+    def _input_name(self):
+        return "spectra"
+
+    def _output_name(self):
+        return "all_spectra"
+
+    def _shape(self):
+        return (
+            len(BPASS_METALLICITIES),
+            len(BPASS_TIME_BINS),
+            len(BPASS_WAVELENGTHS)
+        )
+
+    def _load_single(self, path):
+        return np.loadtxt(path).T[1:, :]
+
+
+class EmissivityCompiler(_CompilerBase):
+    """
+    Pipeline to load the BPASS ionizing txt files and save them as a 3D
+    `numpy.ndarray` binary file.
+
+    Attributes
+    ----------
+    output : `numpy.ndarray` (N_Z, N_age, 4) [(metallicity, log_age, band)]
+        A 3D numpy array containing all the BPASS emissivities (Nion [1/s],
+        L_Halpha [ergs/s], L_FUV [ergs/s/A], L_NUV [ergs/s/A]) for a specific
+        imf and binary or single star population.
+        Usage: spectra[1][2][0]
+                (gives Nion for Z=0.0001 and log_age=6.2)
+    """
+    def _input_name(self):
+        return "ionizing"
+
+    def _output_name(self):
+        return "all_ionizing"
+
+    def _shape(self):
+        return (
+            len(BPASS_METALLICITIES),
+            len(BPASS_TIME_BINS),
+            4
+        )
+
+    def _load_single(self, path):
+        return np.loadtxt(path)[:, 1:]
+
+
 class ModelDataCompiler(HokiObject):
     """
     Given a list of metalicities, a list of valid BPASS model attributes (in the dummy array), chosen types of model
@@ -202,81 +316,6 @@ def _select_input_files(z_list, directory=OUTPUTS_PATH,
 
     return input_file_list
 
-class SpectraCompiler():
-    """
-    Pipeline to load the BPASS spectra txt files and save them as a 3D
-    `numpy.ndarray` binary file.
-
-    Attributes
-    ----------
-    spectra : `numpy.ndarray` (13, 51, 100000) [(metallicity, log_age, wavelength)]
-        A 3D numpy array containing all the BPASS spectra for a specific imf
-        and binary or single star population.
-        Usage: spectra[1][2][1000]
-                (gives L_\\odot for Z=0.0001 and log_age=6.2 at 999 Angstrom)
-    """
-
-    def __init__(self, spectra_folder, output_folder, imf, binary=True, verbose=False):
-        """
-        Input
-        -----
-        spectra_folder : `str`
-            Path to the folder containing the spectra of the given imf.
-
-        output_folder : `str`
-            Path to the folder, where to output the pickled pandas.DataFrame
-
-        imf : `str`
-            BPASS IMF Identifiers
-            The accepted IMF identifiers are:
-            - `"imf_chab100"`
-            - `"imf_chab300"`
-            - `"imf100_100"`
-            - `"imf100_300"`
-            - `"imf135_100"`
-            - `"imf135_300"`
-            - `"imfall_300"`
-            - `"imf170_100"`
-            - `"imf170_300"`
-
-        binary : `bool`
-            If `True`, loads the binary files. Otherwise, just loads single stars.
-            Default=True
-
-        verbose : `bool`
-            If `True` prints out extra information for the user.
-            Default=False
-        """
-        if verbose:
-            _print_welcome()
-
-        # Check population type
-        star = "bin" if binary else "sin"
-
-        # check IMF key
-        if imf not in BPASS_IMFS:
-            raise HokiKeyError(
-                f"{imf} is not a BPASS IMF. Please select a correct IMF.")
-
-        # Setup the numpy output
-        spectra = np.empty((13, 51, 100000), dtype=np.float64)
-
-        # loop over all the metallicities and load all the spectra
-        for num, metallicity in enumerate(BPASS_METALLICITIES):
-            print_progress_bar(num, 12)
-            assert isfile(f"{spectra_folder}/spectra-{star}-{imf}.{metallicity}.dat"),\
-                   "HOKI ERROR: This file does not exist, or its path is incorrect."
-            spectra[num] = np.loadtxt(f"{spectra_folder}/spectra-{star}-{imf}.{metallicity}.dat").T[1:, :]
-
-        # pickle the datafile
-        np.save(f"{output_folder}/all_spectra-{star}-{imf}", spectra)
-        self.spectra = spectra
-        print(
-            f"Spectra file stored in {output_folder} as 'all_spectra-{star}-{imf}.npy'")
-        if verbose:
-            _print_exit_message()
-
-
 
 def _print_welcome():
     print('*************************************************')
@@ -285,11 +324,10 @@ def _print_welcome():
     print("\n\nThis may take a while ;)\nGo get yourself a cup of tea, sit back and relax\nI'm working for you boo!")
 
     print(
-      "\nNOTE: The progress bar doesn't move smoothly - it might accelerate or slow down - it's perfectly normal :D")
+        "\nNOTE: The progress bar doesn't move smoothly - it might accelerate or slow down - it's perfectly normal :D")
 
 
 def _print_exit_message():
-
     print('\n\n\n*************************************************')
     print('*******     JOB DONE! HAPPY SCIENCING!     ******')
     print('*************************************************')

hoki/load.py

@@ -571,10 +571,82 @@ def spectra_all_z(data_path, imf, binary=True):
         spec = hoki.data_compilers.SpectraCompiler(
             data_path, data_path, imf, binary=binary
         )
-        spectra = spec.spectra
+        spectra = spec.output
     return spectra
 
 
+def emissivities_all_z(data_path, imf, binary=True):
+    """
+    Load all BPASS emissivities from files.
+
+    Notes
+    -----
+    The first time this function is run on a folder it will generate an npy
+    file containing all the BPASS emissivities for faster loading in the
+    future. It stores the file in the same folder with the name:
+    `all_ionizing-[bin/sin]-[imf].npy`.
+
+    The emissivities are just read from file and not normalised.
+
+
+    Input
+    -----
+    data_path : `str`
+        The path to the folder containing the BPASS files.
+
+    binary : `bool`
+        Use the binary files or just the single stars. Default=True
+
+    imf : `str`
+        BPASS Identifier of the IMF to be used.
+        The accepted IMF identifiers are:
+        - `"imf_chab100"`
+        - `"imf_chab300"`
+        - `"imf100_100"`
+        - `"imf100_300"`
+        - `"imf135_100"`
+        - `"imf135_300"`
+        - `"imfall_300"`
+        - `"imf170_100"`
+        - `"imf170_300"`
+
+    Returns
+    -------
+    emissivities : `numpy.ndarray` (N_Z, N_age, 4) [(metallicity, log_age, band)]
+        A 3D numpy array containing all the BPASS emissivities (Nion [1/s],
+        L_Halpha [ergs/s], L_FUV [ergs/s/A], L_NUV [ergs/s/A]) for a specific
+        imf and binary or single star population.
+        Usage: spectra[1][2][0]
+                (gives Nion for Z=0.0001 and log_age=6.2)
+    """
+    # Check population type
+    star = "bin" if binary else "sin"
+
+    # check IMF key
+    if imf not in BPASS_IMFS:
+        raise HokiKeyError(
+            f"{imf} is not a BPASS IMF. Please select a correct IMF.")
+
+    # check if data_path is a string
+    if not isinstance(data_path, str):
+         raise HokiTypeError("The folder location is expected to be a string.")
+
+    # Check if compiled spectra are already present in data folder
+    if os.path.isfile(f"{data_path}/all_ionizing-{star}-{imf}.npy"):
+        print("Load precompiled file.")
+        emissivities = np.load(f"{data_path}/all_ionizing-{star}-{imf}.npy")
+        print("Done Loading.")
+
+    # Compile the spectra for faster reading next time otherwise
+    else:
+        print("Compiled file not found. Data will be compiled.")
+        res = hoki.data_compilers.EmissivityCompiler(
+            data_path, data_path, imf, binary=binary
+        )
+        emissivities = res.output
+    return emissivities
+
+
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