From fe7287e3bd854bbee29bc991d711286ae03641f8 Mon Sep 17 00:00:00 2001 From: mikekatz04 Date: Fri, 22 Mar 2024 15:43:58 -0500 Subject: [PATCH] docs update for move --- README.md | 2 +- bbhx/likelihood.py | 4 +- docs/doctrees/README.doctree | Bin 33537 -> 33537 bytes docs/doctrees/environment.pickle | Bin 1087892 -> 1228670 bytes docs/doctrees/index.doctree | Bin 34334 -> 34334 bytes docs/doctrees/user/like.doctree | Bin 47725 -> 137075 bytes docs/html/README.html | 2 +- docs/html/_sources/README.rst.txt | 2 +- docs/html/_sources/user/like.rst.txt | 8 + docs/html/genindex.html | 113 ++++++- docs/html/index.html | 36 ++- docs/html/objects.inv | Bin 3945 -> 4390 bytes docs/html/searchindex.js | 2 +- docs/html/user/like.html | 434 +++++++++++++++++++++++++++ docs/source/README.rst | 2 +- docs/source/user/like.rst | 8 + setup.py | 4 +- 17 files changed, 592 insertions(+), 25 deletions(-) diff --git a/README.md b/README.md index 0d2bb30..4063fef 100644 --- a/README.md +++ b/README.md @@ -137,7 +137,7 @@ Please read [CONTRIBUTING.md](CONTRIBUTING.md) for details on our code of conduc We use [SemVer](http://semver.org/) for versioning. For the versions available, see the [tags on this repository](https://github.com/mikekatz04/BBHx/tags). -Current Version: 1.0.7 +Current Version: 1.0.8 ## Authors diff --git a/bbhx/likelihood.py b/bbhx/likelihood.py index 607630f..548dffa 100644 --- a/bbhx/likelihood.py +++ b/bbhx/likelihood.py @@ -253,7 +253,9 @@ class HeterodynedLikelihood: `arXiv:2109.02728 `_. We implement the method as described in `arXiv:1806.08792 `_. - This class also works with higher order harmonic modes. TODO: fill in. + This class also works with higher order harmonic modes, but it has not been tested extensivally. + It only does a direct summation over the modes rather than heterodyning per mode. So, it is less reliable, + but in practice it produces a solid posterior distribution. 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VersioningSemVer for versioning. For the versions available, see the tags on this repository.

-

Current Version: 1.0.7

+

Current Version: 1.0.8

Authors

diff --git a/docs/html/_sources/README.rst.txt b/docs/html/_sources/README.rst.txt index b5b5042..e1b43f7 100644 --- a/docs/html/_sources/README.rst.txt +++ b/docs/html/_sources/README.rst.txt @@ -191,7 +191,7 @@ We use `SemVer `__ for versioning. For the versions available, see the `tags on this repository `__. -Current Version: 1.0.7 +Current Version: 1.0.8 Authors ------- diff --git a/docs/html/_sources/user/like.rst.txt b/docs/html/_sources/user/like.rst.txt index 4e1aacb..162719f 100644 --- a/docs/html/_sources/user/like.rst.txt +++ b/docs/html/_sources/user/like.rst.txt @@ -8,3 +8,11 @@ Direct Likelihood Computation :members: :show-inheritance: :inherited-members: + +Heterodyned Likelihood Computation +************************************* + +.. autoclass:: bbhx.likelihood.HeterodynedLikelihood + :members: + :show-inheritance: + :inherited-members: diff --git a/docs/html/genindex.html b/docs/html/genindex.html index a3d2e7d..583dac7 100644 --- a/docs/html/genindex.html +++ b/docs/html/genindex.html @@ -96,6 +96,7 @@

Index

| E | F | G + | H | I | L | M @@ -193,15 +194,17 @@

C

  • c3_dm (bbhx.waveforms.phenomhm.PhenomHMAmpPhase attribute)
    • - - + -
  • like_gen (bbhx.likelihood.Likelihood attribute) +
  • length_f_het (bbhx.likelihood.HeterodynedLikelihood attribute) +
    • +
  • like_gen (bbhx.likelihood.HeterodynedLikelihood attribute)
    • @@ -392,8 +441,12 @@

    P

  • (bbhx.waveforms.phenomhm.PhenomHMAmpPhase property)
    • -
  • phase_marginalize (bbhx.likelihood.Likelihood attribute) +
  • phase_marginalize (bbhx.likelihood.HeterodynedLikelihood attribute) + +
  • phenomd_ringdown_freqs (bbhx.waveforms.phenomhm.PhenomHMAmpPhase attribute)
    • @@ -404,13 +457,27 @@

    P

  • pointer_adjust() (in module bbhx.utils.utility)
    • -
  • psd (bbhx.likelihood.Likelihood attribute) +
  • psd (bbhx.likelihood.HeterodynedLikelihood attribute) + +

    • R

    + - @@ -429,6 +498,10 @@

    R

    S

    -
    +
    • SSB_to_LISA() (in module bbhx.utils.transform)
      • @@ -444,9 +517,11 @@

      T

    • template_channels (bbhx.waveformbuild.TemplateInterpFD property)
      • -
    • template_gen (bbhx.likelihood.Likelihood attribute) +
    • template_gen (bbhx.likelihood.HeterodynedLikelihood attribute)
      • @@ -476,9 +551,11 @@

      T

      U

      • x_shaped (bbhx.utils.interpolate.CubicSplineInterpolant property)
        • -
      • xp (bbhx.likelihood.Likelihood attribute) +
      • xp (bbhx.likelihood.HeterodynedLikelihood attribute)
      • Utility Functions
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"Available Waveform Models": [[8, "available-waveform-models"]], "PhenomHM (PhenomD)": [[8, "phenomhm-phenomd"]], "Constants": [[3, "constants"], [7, "constants"]], "Likelihood Methods": [[4, "likelihood-methods"]], "Direct Likelihood Computation": [[4, "direct-likelihood-computation"]], "Heterodyned Likelihood Computation": [[4, "heterodyned-likelihood-computation"]], "Utility Functions": [[7, "utility-functions"]], "Interpolation Utilities": [[7, "interpolation-utilities"]], "Useful Transformation Functions": [[7, "useful-transformation-functions"]], "Citation Module": [[7, "module-bbhx.utils.citations"]], "Cython GPU/CPU Agnostic Tools": [[7, "module-bbhx.utils.utility"]], "GPU-Accelerated Black Hole Binary Waveforms (bbhx)": [[0, "gpu-accelerated-black-hole-binary-waveforms-bbhx"], [2, "gpu-accelerated-black-hole-binary-waveforms-bbhx"]], "Designed for LISA data analysis of Massive Black Hole Binaries.": [[0, "designed-for-lisa-data-analysis-of-massive-black-hole-binaries"], [2, 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        • +
      • Heterodyned Likelihood Computation +
    • Utility Functions
      • @@ -334,6 +368,406 @@

      Direct Likelihood Computation +

      Heterodyned Likelihood Computation

      +
      +
      +class bbhx.likelihood.HeterodynedLikelihood(template_gen, data_freqs, data_channels, reference_template_params, length_f_het, template_gen_kwargs={}, reference_gen_kwargs={}, sens_mat=None, use_gpu=False)
      +

      Bases: object

      +

      Compute the Heterodyned log-Likelihood

      +

      Heterdyning involves separating the fast and slow evolutions when comparing +signals. This involves comparing a reference template to the data stream and determining +various quantities at the full frequency resolution of the data stream. Then, during +online computation, the log-Likelihood is determined by computing a new waveform +on a sparse frequency grid and comparing it to the reference waveform on the same +sparse grid. The practical aspect is the computation of a smaller number of frequency +points which lowers the required memory and increases the speed of the computation. +More information on the general method can be found in +arXiv:2109.02728. We implement the method +as described in arXiv:1806.08792.

      +

      This class also works with higher order harmonic modes, but it has not been tested extensivally. +It only does a direct summation over the modes rather than heterodyning per mode. So, it is less reliable, +but in practice it produces a solid posterior distribution.

      +

      This class has GPU capabilities.

      +
      +
      Parameters:
      +
        +

      • template_gen (obj) – Waveform generation class that returns a tuple of +(list of template arrays, start indices, lengths). See +bbhx.waveform.BBHWaveformFD for more information on this +return type.

        • +

      • data_freqs (double xp.ndarray) – Frequencies for the data stream. data_freqs +should be a numpy (cupy) array if running on the CPU (GPU).

        • +

      • data_channels (complex128 xp.ndarray) – Data stream. 2D array of shape: (3, len(data_freqs)). +It is assumed there are 3 channels. data_channels +should be a numpy (cupy) array if running on the CPU (GPU).

        • +

      • reference_template_params (np.ndarray) – Parameters for the reference template for +template_gen.

        • +

      • template_gen_kwargs (dict, optional) – Keywords arguments for generating the +template with template_gen. It will automatically add/change direct +and compress keyword arguments to True. The keyword argument +squeeze is automatically set to True for the initial setup and then +automatically set to False for online computations. If you so choose (not +recomended), you can change these kwargs for online running using the +**waveform_kwargs setup in the self.get_ll method. However, +if you include in this adjustment direct, compress, or squeeze +will still automatically be overwritten. +(Default: {})

        • +

      • reference_gen_kwargs (dict, optional) – Keywords arguments for generating the +reference template with template_gen. It will automatically add/change +fill, compress, and squeeze keyword arguments to True. +These waveforms can be produced without interpolation with direct = True. +If length keyword argument is given and direct=False, the +waveform will be interpolated. If length and direct are not given, +it will interpolate the signal with length=8096. +(Default: {})

        • +

      • sens_mat (SensitivityMatrix, optional) – SensitivityMatrix object representing the AET channels. +If None, defaults to class:AET1SensitivityMatrix. (default: None)

        • +

      • use_gpu (bool, optional) – If True, use GPU.

        • +
      +
      +
      +
      +
      +reference_d_d
      +

      \(\langle d|d\rangle\) inner product value.

      +
      +
      Type:
      +

      double

      +
      +
      +
      + +
      +
      +reference_h_h
      +

      \(\langle h|h\rangle\) inner product value +for the reference template.

      +
      +
      Type:
      +

      double

      +
      +
      +
      + +
      +
      +reference_d_h
      +

      \(\langle d|h\rangle\) inner product value +for the reference template.

      +
      +
      Type:
      +

      double

      +
      +
      +
      + +
      +
      +reference_ll
      +

      log-Likelihood value for the reference template.

      +
      +
      Type:
      +

      double

      +
      +
      +
      + +
      +
      +hdyn_d_h
      +

      Heterodyned \(\langle d|h\rangle\) +inner product values for the test templates.

      +
      +
      Type:
      +

      complex128 xp.ndarray

      +
      +
      +
      + +
      +
      +hdyn_h_h
      +

      Heterodyned \(\langle d|h\rangle\) +inner product values for the test templates.

      +
      +
      Type:
      +

      complex128 xp.ndarray

      +
      +
      +
      + +
      +
      +h0_sparse
      +

      Array with sparse waveform for reference parameters.

      +
      +
      Type:
      +

      xp.ndarray

      +
      +
      +
      + +
      +
      +h_sparse
      +

      Array with sparse waveform for test parameters.

      +
      +
      Type:
      +

      xp.ndarray

      +
      +
      +
      + +
      +
      +d
      +

      Data stream. 1D flattened array +of shape: (3, len(data_freqs)).

      +
      +
      Type:
      +

      complex128 xp.ndarray

      +
      +
      +
      + +
      +
      +data_stream_length
      +

      Length of data.

      +
      +
      Type:
      +

      int

      +
      +
      +
      + +
      +
      +data_constants
      +

      Flattened array container holding all heterodyning +constants needed: A0, A1, B0, B1.

      +
      +
      Type:
      +

      xp.ndarray

      +
      +
      +
      + +
      +
      +f_dense
      +

      Frequencies for the data stream (1D).

      +
      +
      Type:
      +

      xp.ndarray

      +
      +
      +
      + +
      +
      +freqs
      +

      Frequencies for sparse arrays.

      +
      +
      Type:
      +

      xp.ndarray

      +
      +
      +
      + +
      +
      +f_m
      +

      Frequency of mid-point in each sparse bin.

      +
      +
      Type:
      +

      xp.ndarray

      +
      +
      +
      + +
      +
      +length_f_het
      +

      Length of sparse array.

      +
      +
      Type:
      +

      int

      +
      +
      +
      + +
      +
      +like_gen
      +

      C/CUDA implementation of likelihood compuation.

      +
      +
      Type:
      +

      obj

      +
      +
      +
      + +
      +
      +psd
      +

      \(\sqrt{\frac{\Delta f}{S_n(f)}}\). +1D flattened array of shape: (3, len(data_freqs)).

      +
      +
      Type:
      +

      double xp.ndarray

      +
      +
      +
      + +
      +
      +template_gen
      +

      Waveform generation class that returns a tuple of +(list of template arrays, start indices, lengths). See +bbhx.waveform.BBHWaveformFD for more information on this +return type.

      +
      +
      Type:
      +

      obj

      +
      +
      +
      + +
      +
      +return_extracted_snr
      +

      Return the snr in addition to the Likeilihood.

      +
      +
      Type:
      +

      bool

      +
      +
      +
      + +
      +
      +phase_marginalize
      +

      If True, compute the phase-marginalized +log-Likelihood (and snr if return_extracted_snr==True).

      +
      +
      Type:
      +

      bool

      +
      +
      +
      + +
      +
      +use_gpu
      +

      If True, using GPU.

      +
      +
      Type:
      +

      bool

      +
      +
      +
      + +
      +
      +xp
      +

      Either numpy or cupy.

      +
      +
      Type:
      +

      obj

      +
      +
      +
      + +
      +
      +property sens_mat
      +

      Sensitivity Matrix

      +
      + +
      +
      +property like_gen
      +

      C function on GPU/CPU

      +
      + +
      +
      +property xp
      +

      Numpy or Cupy

      +
      + +
      +
      +property citation
      +

      Citations for this class

      +
      + +
      +
      +init_heterodyne_info(reference_template_params, template_gen_kwargs={}, reference_gen_kwargs={})
      +

      Prepare all information for Heterdyning

      +
      +
      Parameters:
      +
        +

      • reference_template_params (np.ndarray) – Parameters for the reference template for +template_gen.

        • +

      • template_gen_kwargs (dict, optional) – Keywords arguments for generating the +template with template_gen. It will automatically add/change direct +and compress keyword arguments to True. The keyword argument +squeeze is automatically set to True for the initial setup and then +automatically set to False for online computations. If you so choose (not +recomended), you can change these kwargs for online running using the +**waveform_kwargs setup in the self.get_ll method. However, +if you include in this adjustment direct, compress, or squeeze +will still automatically be overwritten. +(Default: {})

        • +

      • reference_gen_kwargs (dict, optional) – Keywords arguments for generating the +reference template with template_gen. It will automatically add/change +fill, compress, and squeeze keyword arguments to True. +These waveforms can be produced without interpolation with direct = True. +If length keyword argument is given and direct=False, the +waveform will be interpolated. If length and direct are not given, +it will interpolate the signal with length=8096. +(Default: {})

        • +
      +
      +
      +
      + +
      +
      +get_ll(params, return_extracted_snr=False, phase_marginalize=False, **waveform_kwargs)
      +

      Compute the log-Likelihood

      +
      +
      params (double np.ndarray): Parameters for evaluating log-Likelihood.

      params.shape=(num_params,) if 1D or +params.shape=(num_params, num_bin_all) if 2D for more than +one binary.

      +
      +
      return_extracted_snr (bool, optional): If True, return

      \(\langle d|h\rangle\ / \sqrt{\langle h|h\rangle}\) as a second entry +of the return array. This produces a return array of +xp.array([log likelihood, snr]).T. If False, just return +the log-Likelihood array.

      +
      +
      phase_marginalize (bool, optional): If True, compute the phase-marginalized

      log-Likelihood (and snr if return_extracted_snr==True).

      +
      +
      **waveform_kwargs (dict, optional): Keyword arguments for waveform

      generator. Some may be overwritten. See the main class docstring.

      +
      +
      +
      +
      Returns:
      +

      log-Likelihoods or np.array([log-Likelihoods, snr]).T

      +
      +
      Return type:
      +

      np.ndarray

      +
      +
      +
      + +
      + diff --git a/docs/source/README.rst b/docs/source/README.rst index b5b5042..e1b43f7 100644 --- a/docs/source/README.rst +++ b/docs/source/README.rst @@ -191,7 +191,7 @@ We use `SemVer `__ for versioning. For the versions available, see the `tags on this repository `__. -Current Version: 1.0.7 +Current Version: 1.0.8 Authors ------- diff --git a/docs/source/user/like.rst b/docs/source/user/like.rst index 4e1aacb..162719f 100644 --- a/docs/source/user/like.rst +++ b/docs/source/user/like.rst @@ -8,3 +8,11 @@ Direct Likelihood Computation :members: :show-inheritance: :inherited-members: + +Heterodyned Likelihood Computation +************************************* + +.. autoclass:: bbhx.likelihood.HeterodynedLikelihood + :members: + :show-inheritance: + :inherited-members: diff --git a/setup.py b/setup.py index a444c9a..6489346 100644 --- a/setup.py +++ b/setup.py @@ -343,6 +343,6 @@ def build_extensions(self): cmdclass={"build_ext": custom_build_ext}, # Since the package has c code, the egg cannot be zipped zip_safe=False, - version="1.0.7", - python_requires=">=3.6", + version="1.0.8", + python_requires=">=3.12", )