daniel-muthukrishna / astrodash Goto Github PK

When I attempt to run dash on some spectra, I get the following error message:
Traceback (most recent call last): File "check_type_with_dash.py", line 1, in <module> import dash File "/Users/uqdpark7/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/dash/__init__.py", line 3, in <module> from classify import Classify File "/Users/uqdpark7/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/dash/classify.py", line 7, in <module> from restore_model import LoadInputSpectra, BestTypesListSingleRedshift ImportError: No module named restore_model

Save the plot, list of best matches (with probabilities) and the redshift.
As requested by Brad Tucker

training three separate models trained with different age bins: 1.) less than -2 days; 2.) more than +2days; 3.) -5 to +10 days. Then, an option to allow the user to select which model to use should act like an age prior.
As requested by Mat Smith.

Hi there. I'm trying to install and followed the README but have run into the following error

Traceback (most recent call last):
  File "/usr/local/Caskroom/miniconda/base/envs/astrodash/bin/astrodash", line 8, in <module>
    sys.exit(run_gui())
  File "/usr/local/Caskroom/miniconda/base/envs/astrodash/lib/python3.8/site-packages/astrodash/__init__.py", line 39, in run_gui
    form = MainApp(inputFilename=filepath)
  File "/usr/local/Caskroom/miniconda/base/envs/astrodash/lib/python3.8/site-packages/astrodash/gui_main.py", line 24, in __init__
    self.templates()
  File "/usr/local/Caskroom/miniconda/base/envs/astrodash/lib/python3.8/site-packages/astrodash/gui_main.py", line 100, in templates
    pars = get_training_parameters()
  File "/usr/local/Caskroom/miniconda/base/envs/astrodash/lib/python3.8/site-packages/astrodash/restore_model.py", line 15, in get_training_parameters
    with open(os.path.join(scriptDirectory, data_files, "models/zeroZ/training_params.pickle"), 'rb') as f:
FileNotFoundError: [Errno 2] No such file or directory: '/usr/local/Caskroom/miniconda/base/envs/astrodash/lib/python3.8/site-packages/astrodash/models_v06/models/zeroZ/training_params.pickle'

Many thanks in advance for your help,
Dillon

• Add a wavelength scale to the horizontal axis on the lower plot
• Display rest wavelengths and observer wavelengths
• Add a quit button to the GUI

When using the option to save the plot (Export -> Plot -> Image file) the program crashes without saving the plots.
The error output :

Traceback (most recent call last):
File "/home/dustspeck/miniconda3/lib/python3.7/site-packages/pyqtgraph/exporters/Exporter.py", line 77, in fileSaveFinished
self.export(fileName=fileName, **self.fileDialog.opts)
File "/home/dustspeck/miniconda3/lib/python3.7/site-packages/pyqtgraph/exporters/ImageExporter.py", line 70, in export
bg = np.empty((self.params['width'], self.params['height'], 4), dtype=np.ubyte)

TypeError: 'float' object cannot be interpreted as an integer

When trying to export with the option 'Matplotlib Window' it also crashes.

Error output :

Traceback (most recent call last):
File "/home/dustspeck/miniconda3/lib/python3.7/site-packages/pyqtgraph/GraphicsScene/exportDialog.py", line 132, in exportClicked
self.currentExporter.export()
File "/home/dustspeck/miniconda3/lib/python3.7/site-packages/pyqtgraph/exporters/Matplotlib.py", line 109, in export
raise Exception("Matplotlib export currently only works with plot items")
Exception: Matplotlib export currently only works with plot items

When selecting the 'Entire scene' instead of 'Plot', saving in image format and SVG seems to work fine.

Hi Daniel,

Thanks for developing such a powerful software package. In issue #16 you mention a future feature to add your own SN templates to the library. Is this feature added? If yes, Is it possible to define my own class of transients?

A related question, if I would have the spectrum/SED of the host galaxy of a particular supernova, can this be used instead of the generic galaxy templates?

Cheers,

Steve

Allow control for noise, host galaxy weighting, cropping...

Hi,
I'm installing astrodash in a shared software installation. When running a simple test, I see there is a data file that is downloaded. Is there a suggested way to handle this during the installation process rather than waiting for the need of this file to trigger the download?

 python classify.py -h
Downloading data files from https://github.com/daniel-muthukrishna/astrodash/blob/master/astrodash/models_v06.zip?raw=true... 
This download contains the Tensorflow models trained using deep learning. 
The file to be downloaded is ~200MB. However, this is a one time download, and will only occur
the very first time that this version of DASH is installed.

Include pop-up tooltips that explain various tuning parameters on the interface such as "smoothing".

Asscalar was dropped in 1.23. Temporary fix is:

pip install numpy==1.22.4
pip install git+https://github.com/daniel-muthukrishna/astrodash.git

Tried out this one: https://raw.githubusercontent.com/astrocatalogs/sne-external-spectra/master/CfA_SNIbc/sn1998dt/sn1998dt-19980919.flm

Which is at a redshift of 0.0153. I had installed the latest version into a fresh Python 2.7 environment via python setup.py install.

My test.py:

import dash

classification = dash.Classify(["/path/to/sn1998dt-19980919.flm"], [0.0153])
print(classification.list_best_matches(n=1))

The error:

Invalid Input File
Traceback (most recent call last):
  File "test.py", line 4, in <module>
    print(classification.list_best_matches(n=1))
  File "/Users/james/miniconda3/envs/py27/lib/python2.7/site-packages/dash/classify.py", line 58, in list_best_matches
    bestTypes, softmaxes = self._input_spectra_info()
  File "/Users/james/miniconda3/envs/py27/lib/python2.7/site-packages/dash/classify.py", line 48, in _input_spectra_info
    inputImage, typeNamesList, nw, nBins = self._get_images(f, z, trainParams)
  File "/Users/james/miniconda3/envs/py27/lib/python2.7/site-packages/dash/classify.py", line 36, in _get_images
    loadInputSpectra = LoadInputSpectra(filename, redshift, redshift, self.smooth, trainParams)
  File "/Users/james/miniconda3/envs/py27/lib/python2.7/site-packages/dash/restore_model.py", line 43, in __init__
    self.inputImages, self.inputFilenames, self.inputRedshifts, self.typeNamesList = self.inputSpectra.redshifting()
  File "/Users/james/miniconda3/envs/py27/lib/python2.7/site-packages/dash/input_spectra.py", line 38, in redshifting
    tempwave, tempflux, tminindex, tmaxindex = readSpectra.input_spectrum(z, self.smooth)
  File "/Users/james/miniconda3/envs/py27/lib/python2.7/site-packages/dash/create_arrays.py", line 137, in input_spectrum
    wave, flux, minIndex, maxIndex = self.data.two_column_data(z, smooth)
  File "/Users/james/miniconda3/envs/py27/lib/python2.7/site-packages/dash/sn_processing.py", line 44, in two_column_data
    self.wave, self.flux = self.spectrum
TypeError: 'int' object is not iterable

Create extra dimension of bins to classify host galaxy

It would be great to pass a Nx2 (or Nx3) array into Classify rather than a filename, for use in other packages where the spectrum might already be loaded into memory.

Add mstars/mdwarfs, quasars, AGN