# Import the relevant PTS classes and modules
from pts.core.tools import filesystem as fs
from pts.do.commandline import Command
from pts.evolve.core import reference
from pts.evolve.optimize.optimizer import show_best
from pts.evolve.core.crossovers import G1DListCrossoverOX
from pts.evolve.core.mutators import G1DListMutatorSwap
from pts.core.basics.animation import Animation
from pts.core.basics.range import RealRange
from pts.core.test.implementation import TestImplementation
from pts.core.basics.log import log
# -----------------------------------------------------------------
this_path = fs.absolute_path(inspect.stack()[0][1])
this_dir_path = fs.directory_of(this_path)
# -----------------------------------------------------------------
description = "finding the maximum of the function defined by Charbonneau (1995)"
# -----------------------------------------------------------------
# Define properties
#nparameters = 20
nparameters = 2
nindividuals = 80
parameter_range = RealRange(0., 1.)
#best_raw_score = float('inf')
best_raw_score = 100
#round_decimal = None
import inspect import numpy as np from matplotlib import pyplot as plt # Import the relevant PTS classes and modules from pts.core.tools import filesystem as fs from pts.do.commandline import Command from pts.core.basics.range import RealRange from pts.evolve.core import reference from pts.evolve.optimize.optimizer import show_best from pts.core.test.implementation import TestImplementation # ----------------------------------------------------------------- this_path = fs.absolute_path(inspect.stack()[0][1]) this_dir_path = fs.directory_of(this_path) # ----------------------------------------------------------------- description = "optimizing the Rastrigin function, a deceptive function" # ----------------------------------------------------------------- # Define properties #nparameters = 20 nparameters = 2 nindividuals = 80 parameter_range = RealRange(-5.2, 5.30) best_raw_score = 0.0 round_decimal = None #ngenerations = 800
lum_neutral = lum.to("W", density=True, wavelength=fltr_wavelength)
lum_solar = lum.to("Lsun", density=True, wavelength=fltr_wavelength)
# Neutral and solar
log.info("Luminosity in spectral solar units: " + tostr(lum_spectral_solar) + " Lsun_" + fltr.band)
log.info("Luminosity in neutral units: " + tostr(lum_neutral))
log.info("Luminosity in solar units: " + tostr(lum_solar))
# -----------------------------------------------------------------
# Calculate from file with sampled luminosituies
if config.sampled:
# Determine the path to this directory
this_filepath = fs.absolute_or_in_cwd(inspect.getfile(inspect.currentframe()))
directory_path = fs.directory_of(this_filepath)
# Determine the filepath
filepath = fs.join(directory_path, "MappingsTemplate.dat")
# Get wavelength grid, calculate luminosities in W
wg = WavelengthGrid.from_text_file(filepath, "m")
deltas = wg.deltas(asarray=True, unit="m")
lums = np.loadtxt(filepath, skiprows=0, unpack=True, usecols=(1))
lums *= sfr_scalar # CORRECT FOR SFR
# Construct the SED
spectrallums = lums / deltas
sampled_sed = SED.from_arrays(wg.wavelengths(asarray=True, unit="m"), spectrallums, "m", "W/m")
print("FROM SAMPLED LUMINOSITIES:")
from pts.core.data.sed import SED, ObservedSED
from pts.core.plot.sed import SEDPlotter
# -----------------------------------------------------------------
# Set the log level
level = "DEBUG"
# Initialize the logger
log = logging.setup_log(level=level)
log.start("Starting compare_sed ...")
# -----------------------------------------------------------------
fit_path = fs.absolute_path("../../../../../")
modeling_path = fs.directory_of(fit_path)
galaxy_name = fs.name(modeling_path)
# -----------------------------------------------------------------
# Create the plotter
plotter = SEDPlotter()
# Add the SEDs
filename = galaxy_name + "_earth_sed.dat"
sed = SED.from_skirt(filename)
# Load the reference SED
reference_sed_path = fs.join(modeling_path, "sed.dat")
reference_sed = ObservedSED.from_file(reference_sed_path)
# Cache
# Create directory for the image
# Get the path
path = paths[name]
# Get filename
filename = fs.strip_extension(fs.name(path))
#print(filename)
# Determine origin from filename
#origin = instrument_to_origin(filename.split("_")[1])
# Other way
origin = fs.name(fs.directory_of(path))
# CHeck
#if origin != origin_alt: raise ValueError(origin + " != " + origin_alt)
# Create remote directory
remote_image_directory = fs.join(remote_data_path, origin)
if not remote.is_directory(remote_image_directory):
remote.create_directory(remote_image_directory)
# Check whether the file exists
if not fs.is_file(path):
# Check whether already cached to the remote
remote_image_path = fs.join(remote_image_directory, fs.name(path))
from pts.core.data.sed import SED, ObservedSED
from pts.core.plot.sed import SEDPlotter
# -----------------------------------------------------------------
# Set the log level
level = "DEBUG"
# Initialize the logger
log = logging.setup_log(level=level)
log.start("Starting compare_sed ...")
# -----------------------------------------------------------------
fit_path = fs.absolute_path("../../../../../")
modeling_path = fs.directory_of(fit_path)
galaxy_name = fs.name(modeling_path)
# -----------------------------------------------------------------
# Create the plotter
plotter = SEDPlotter()
# Add the SEDs
filename = galaxy_name + "_earth_sed.dat"
sed = SED.from_skirt(filename)
# Load the reference SED
reference_sed_path = fs.join(modeling_path, "sed.dat")
reference_sed = ObservedSED.from_file(reference_sed_path)
# Create configuration
definition = ConfigurationDefinition(write_config=False)
#definition.add_required("filename", "file_path", "table file")
definition.add_required("columns", "string_list", "names of columns")
definition.add_optional("method", "string", "table reading method", "lines")
config = parse_arguments("remove_columns", definition)
# -----------------------------------------------------------------
# Find table files
filepaths = fs.files_in_cwd(extension="dat", recursive=True)
for filepath in filepaths:
#print(filepath)
directory_name = fs.name(fs.directory_of(filepath))
filename = fs.name(filepath)
# Get column names
column_names = fs.get_column_names(filepath)
if not sequences.contains_any(column_names, config.columns): continue
print(directory_name, filename, column_names)
# -----------------------------------------------------------------
# Load the table
table = SmartTable.from_file(filepath, method=config.method)
# -----------------------------------------------------------------