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Able to read pha2 files and deal with ARF and RMF not specified in file #25

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Able to read pha2 files and deal with ARF and RMF not specified in file #25

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fc680d4
Added np.sum back to RMF.apply_rmf calculation
Jul 14, 2017
4c2298d
Changed way that init file imported XSpectrum
Jul 14, 2017
9c8a26b
Removed data files from git tracking
Jul 14, 2017
7842c32
Ignore data files
Jul 14, 2017
9189243
Dealt with some units stuff using astropy.units
Jul 14, 2017
ad74bbe
Removed np.sum
Jul 14, 2017
e7fa7f9
Data no longer ignored
Jul 14, 2017
afe6293
Solved merge conflicts
Jul 28, 2017
a89c5a4
Removed some arfs and rmfs from tracking
Jul 28, 2017
9004f5d
First pass at managing arf and rmf headers
Jul 28, 2017
9184cf7
Fixed spelling in docstring [skip CI]
Jul 28, 2017
8916e6c
except, not else
Jul 28, 2017
9cf34ca
Ground work for reading a row from pha2 file
Jul 28, 2017
94da0d9
Adjust unit warning for case of arf or rmf == None
Jul 28, 2017
9aa6e08
Merge branch 'autoread_resp' of github.com:eblur/clarsach into read_pha2
Jul 28, 2017
91e653a
Can now specify arf and rmf files at init
Jul 28, 2017
cbd99b8
Merge branch 'autoread_resp' of github.com:eblur/clarsach into autore…
Jul 28, 2017
a0a371d
Merged changes from autoread_resp
Jul 28, 2017
4b6f78d
merged Spectrum.__init__ conflict
Jul 28, 2017
afb1249
arf and rmf file names resolved
Jul 28, 2017
5e94280
Added verbose flag to reduce amount of print statements
Jul 28, 2017
567e2e0
Fixed typos on case row is None
Jul 28, 2017
ef8292b
Tested that arf and rmf are set for pha2 files
Jul 31, 2017
37cd05c
Added some comments
Jul 31, 2017
2725b91
First pass at fixing arf and rmf over-ride
Aug 17, 2017
a5076aa
Fixed typo
Aug 17, 2017
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Added np.sum back to RMF.apply_rmf calculation
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eblur committed Jul 14, 2017
commit fc680d4e8a866d55c05cb0bfed5394c7b7ccaa55
4 changes: 2 additions & 2 deletions clarsach/respond.py
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Original file line number Diff line number Diff line change
Expand Up @@ -215,10 +215,10 @@ def apply_rmf(self, spec):

# add the flux to the subarray of the counts array that starts with
# counts_idx and runs over current_num_chans channels
counts[counts_idx:counts_idx + current_num_chans] += self.matrix[
counts[counts_idx:counts_idx + current_num_chans] += np.sum(self.matrix[
resp_idx:resp_idx + current_num_chans] * \
np.float(
source_bin_i)
source_bin_i))
# iterate the response index for next round
resp_idx += current_num_chans

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