[yt-svn] commit/yt: ngoldbaum: Merged in chummels/yt (pull request #1870)
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Fri Nov 20 08:31:18 PST 2015
1 new commit in yt:
https://bitbucket.org/yt_analysis/yt/commits/3f1fc1c90019/
Changeset: 3f1fc1c90019
Branch: yt
User: ngoldbaum
Date: 2015-11-20 16:29:31+00:00
Summary: Merged in chummels/yt (pull request #1870)
Changing AbsorptionSpectrum attribute lambda_bins to be lambda_field for consistency.
Affected #: 1 file
diff -r f0e05114dfdc9a068d78373311336b5f6fa14578 -r 3f1fc1c900195d9d35e7f9b13f1c603b67337a3d yt/analysis_modules/absorption_spectrum/absorption_spectrum.py
--- a/yt/analysis_modules/absorption_spectrum/absorption_spectrum.py
+++ b/yt/analysis_modules/absorption_spectrum/absorption_spectrum.py
@@ -51,13 +51,14 @@
def __init__(self, lambda_min, lambda_max, n_lambda):
self.n_lambda = n_lambda
+ # lambda, flux, and tau are wavelength, flux, and optical depth
+ self.lambda_field = YTArray(np.linspace(lambda_min, lambda_max,
+ n_lambda), "angstrom")
self.tau_field = None
self.flux_field = None
- self.spectrum_line_list = None
- self.lambda_bins = YTArray(np.linspace(lambda_min, lambda_max, n_lambda),
- "angstrom")
self.bin_width = YTQuantity((lambda_max - lambda_min) /
float(n_lambda - 1), "angstrom")
+ self.spectrum_line_list = None
self.line_list = []
self.continuum_list = []
@@ -186,7 +187,7 @@
input_ds = input_file
field_data = input_ds.all_data()
- self.tau_field = np.zeros(self.lambda_bins.size)
+ self.tau_field = np.zeros(self.lambda_field.size)
self.spectrum_line_list = []
if njobs == "auto":
@@ -211,7 +212,7 @@
self._write_spectrum_line_list(line_list_file)
del field_data
- return (self.lambda_bins, self.flux_field)
+ return (self.lambda_field, self.flux_field)
def _add_continua_to_spectrum(self, field_data, use_peculiar_velocity):
"""
@@ -228,11 +229,11 @@
else:
delta_lambda = continuum['wavelength'] * field_data['redshift']
this_wavelength = delta_lambda + continuum['wavelength']
- right_index = np.digitize(this_wavelength, self.lambda_bins).clip(0, self.n_lambda)
+ right_index = np.digitize(this_wavelength, self.lambda_field).clip(0, self.n_lambda)
left_index = np.digitize((this_wavelength *
np.power((min_tau * continuum['normalization'] /
column_density), (1. / continuum['index']))),
- self.lambda_bins).clip(0, self.n_lambda)
+ self.lambda_field).clip(0, self.n_lambda)
valid_continuua = np.where(((column_density /
continuum['normalization']) > min_tau) &
@@ -241,7 +242,7 @@
(continuum['label'], continuum['wavelength']),
valid_continuua.size)
for i, lixel in enumerate(valid_continuua):
- line_tau = np.power((self.lambda_bins[left_index[lixel]:right_index[lixel]] /
+ line_tau = np.power((self.lambda_field[left_index[lixel]:right_index[lixel]] /
this_wavelength[lixel]), continuum['index']) * \
column_density[lixel] / continuum['normalization']
self.tau_field[left_index[lixel]:right_index[lixel]] += line_tau
@@ -272,8 +273,8 @@
delta_lambda = line['wavelength'] * field_data['redshift']
# lambda_obs is central wavelength of line after redshift
lambda_obs = line['wavelength'] + delta_lambda
- # bin index in lambda_bins of central wavelength of line after z
- center_index = np.digitize(lambda_obs, self.lambda_bins)
+ # bin index in lambda_field of central wavelength of line after z
+ center_index = np.digitize(lambda_obs, self.lambda_field)
# thermal broadening b parameter
thermal_b = np.sqrt((2 * boltzmann_constant_cgs *
@@ -355,7 +356,7 @@
my_n_vbins *= 2
# identify the extrema of the vbin_window so as to speed
- # up searching over the entire lambda_bins array
+ # up searching over the entire lambda_field array
bins_from_center = np.ceil((my_vbin_window_width/2.) / \
self.bin_width.d) + 1
left_index = (center_index[i] - bins_from_center).clip(0, self.n_lambda)
@@ -368,7 +369,7 @@
# this has the effect of assuring np.digitize will place
# the vbins in the closest bin center.
binned = np.digitize(vbins,
- self.lambda_bins[left_index:right_index] \
+ self.lambda_field[left_index:right_index] \
+ (0.5 * self.bin_width))
# numerically integrate the virtual bins to calculate a
@@ -431,8 +432,8 @@
mylog.info("Writing spectrum to ascii file: %s." % filename)
f = open(filename, 'w')
f.write("# wavelength[A] tau flux\n")
- for i in range(self.lambda_bins.size):
- f.write("%e %e %e\n" % (self.lambda_bins[i],
+ for i in range(self.lambda_field.size):
+ f.write("%e %e %e\n" % (self.lambda_field[i],
self.tau_field[i], self.flux_field[i]))
f.close()
@@ -442,7 +443,8 @@
Write spectrum to a fits file.
"""
mylog.info("Writing spectrum to fits file: %s." % filename)
- col1 = pyfits.Column(name='wavelength', format='E', array=self.lambda_bins)
+ col1 = pyfits.Column(name='wavelength', format='E', \
+ array=self.lambda_field)
col2 = pyfits.Column(name='flux', format='E', array=self.flux_field)
cols = pyfits.ColDefs([col1, col2])
tbhdu = pyfits.BinTableHDU.from_columns(cols)
@@ -456,7 +458,7 @@
"""
mylog.info("Writing spectrum to hdf5 file: %s." % filename)
output = h5py.File(filename, 'w')
- output.create_dataset('wavelength', data=self.lambda_bins)
+ output.create_dataset('wavelength', data=self.lambda_field)
output.create_dataset('tau', data=self.tau_field)
output.create_dataset('flux', data=self.flux_field)
output.close()
Repository URL: https://bitbucket.org/yt_analysis/yt/
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