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Asimov fixes (#14)
* Add SNR-based injection functionality and corresponding tests - Implemented functions to calculate network SNR for a given luminosity distance and to find the distance that produces a target network SNR. - Updated the `make_injection` function to support injections based on target SNR. - Enhanced documentation in quickstart and software injections guides to include SNR-based injection examples. - Added unit tests for SNR calculations and injection creation. - Modified noise models to conditionally use PyTorch if available. * Update asimov interface to enable pretty printing
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minke/asimov.py

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from asimov.utils import set_directory
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from asimov import config
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import configparser
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import pprint
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class Asimov(asimov.pipeline.Pipeline):
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minke/distribution.py

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from scipy import random
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from numpy import random
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import numpy
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def sky_params(net, time, ra, dec, psi, incl=numpy.pi):

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