diff --git a/.gitlab-ci.yml b/.gitlab-ci.yml
index 3e32624726c632c88d0bafc47a6e4fc7db183833..f5439dcc59ba27de4b86e8642414be90e9fa3bc3 100644
--- a/.gitlab-ci.yml
+++ b/.gitlab-ci.yml
@@ -18,8 +18,8 @@ python-2:
stage: test
image: bilbydev/test-suite-py2
before_script:
- - pip install -r requirements.txt
- - pip install -r optional_requirements.txt
+ # Install the dependencies specified in the Pipfile
+ - pipenv install --two --python=/opt/conda/bin/python2 --system --deploy
script:
- python setup.py install
# Run tests without finding coverage
@@ -30,8 +30,8 @@ python-3:
stage: test
image: bilbydev/test-suite-py3
before_script:
- - pip install -r requirements.txt
- - pip install -r optional_requirements.txt
+ # Install the dependencies specified in the Pipfile
+ - pipenv install --three --python=/opt/conda/bin/python --system --deploy
script:
- python setup.py install
@@ -44,7 +44,6 @@ python-3:
- coverage-badge -o coverage_badge.svg -f
# Make the documentation
- - pip install -r docs/requirements.txt
- cd docs
- conda install -y make
- make clean
diff --git a/CHANGELOG.md b/CHANGELOG.md
index 28a02b7d6997be81a6e09b3506493e6e5b14846f..b941c69f52bb0f2908a8310f21083015163a4a0e 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -18,6 +18,7 @@ Changes currently on master, but not under a tag.
- Adds custom titles to corner plots
- Adds plotting of the prior on 1D marginal distributions of corner plots
- Adds a method to plot time-domain GW data
+- Added pipenv as a dependency manager
- Hyperparameter estimation now enables the user to provide the single event evidences
- Add nested samples to nestle output
- Prior and child classes now implement the \_\_eq\_\_ magic method for comparisons
@@ -25,6 +26,7 @@ Changes currently on master, but not under a tag.
- Added NestedSampler and MCSampler helper classes
- Added sampler_requirements.txt file
- Add AlignedSpin gw prior
+- Add units to know prior files
### Changes
- Fix construct_cbc_derived_parameters
@@ -43,6 +45,7 @@ re-instantiate the Prior in most cases
- Users can now choose to overwrite existing result files, rather than creating
a .old file.
- Make likelihood values stored in the posterior correct for dynesty and nestle
+- pymultinest output now stored in {outdir}/pm_{label}/
### Removed
- Removes the "--detectors" command line argument (not a general CLI requirement)
diff --git a/Pipfile b/Pipfile
new file mode 100644
index 0000000000000000000000000000000000000000..258de82a4c2b72f9f7ae4017c89054e6d8dd8db6
--- /dev/null
+++ b/Pipfile
@@ -0,0 +1,33 @@
+[[source]]
+url = "https://pypi.org/simple"
+verify_ssl = true
+name = "pypi"
+
+[packages]
+future = "*"
+corner = "*"
+numpy = ">=1.9"
+matplotlib = "<3"
+scipy = ">=0.16"
+pandas = "*"
+deepdish = "*"
+mock = "*"
+astropy = "<3"
+gwpy = "*"
+theano = "*"
+lalsuite = "*"
+
+# cpnest = "*"
+dynesty = "*"
+emcee = "*"
+nestle = "*"
+ptemcee = "*"
+pymc3 = "*"
+pymultinest = "*"
+
+[requires]
+
+[dev-packages]
+
+[pipenv]
+allow_prereleases = false
diff --git a/Pipfile.lock b/Pipfile.lock
new file mode 100644
index 0000000000000000000000000000000000000000..7300f095ed679ab40898a18ef20603994527611d
--- /dev/null
+++ b/Pipfile.lock
@@ -0,0 +1,621 @@
+{
+ "_meta": {
+ "hash": {
+ "sha256": "dec6b7c15df6450bdbd7946533a3cf8c8d554a48e7ca711787eaf5bfcba6c492"
+ },
+ "pipfile-spec": 6,
+ "requires": {},
+ "sources": [
+ {
+ "name": "pypi",
+ "url": "https://pypi.org/simple",
+ "verify_ssl": true
+ }
+ ]
+ },
+ "default": {
+ "asn1crypto": {
+ "hashes": [
+ "sha256:2f1adbb7546ed199e3c90ef23ec95c5cf3585bac7d11fb7eb562a3fe89c64e87",
+ "sha256:9d5c20441baf0cb60a4ac34cc447c6c189024b6b4c6cd7877034f4965c464e49"
+ ],
+ "version": "==0.24.0"
+ },
+ "astropy": {
+ "hashes": [
+ "sha256:13cdf1ba17d2ecbafc9fcb20d82d2aa53f0fc116a815d17357f86c0180215ffc",
+ "sha256:22051a03bb268a0426a0170366e4680553028c5f9282f335c575a850e7eb85ef",
+ "sha256:32fbaf565bebbbc91b64271e1f08870cf23c63a7f852e848df932324dedc8a07",
+ "sha256:53979303beb386038ac6dd69c1d08b148d518a915c8c1f9c45179b5f752739fc",
+ "sha256:9f354bdde7fd1261b14379553dc3500956ddba56afc80c021f8592138d827a51",
+ "sha256:a8015f84c42051342a2a8ee710868e682b9775a3b7948fdc1e87124bcd6e69dc",
+ "sha256:b284f9452dc8330a0bec13713a739d5714f01de5c473a31df80f1719fe56956c",
+ "sha256:d46f4e578c2e0b69b0ae4958c426ca12cbf7849c5cadba9200aa8866ae107dfe",
+ "sha256:d918ce1da85ee8c90f3e1f40be6a6743d33bcd992fe813bfc193dac8fd7a544a"
+ ],
+ "index": "pypi",
+ "version": "==2.0.8"
+ },
+ "atomicwrites": {
+ "hashes": [
+ "sha256:0312ad34fcad8fac3704d441f7b317e50af620823353ec657a53e981f92920c0",
+ "sha256:ec9ae8adaae229e4f8446952d204a3e4b5fdd2d099f9be3aaf556120135fb3ee"
+ ],
+ "markers": "python_version != '3.1.*' and python_version != '3.2.*' and python_version >= '2.7' and python_version != '3.3.*' and python_version != '3.0.*'",
+ "version": "==1.2.1"
+ },
+ "attrs": {
+ "hashes": [
+ "sha256:10cbf6e27dbce8c30807caf056c8eb50917e0eaafe86347671b57254006c3e69",
+ "sha256:ca4be454458f9dec299268d472aaa5a11f67a4ff70093396e1ceae9c76cf4bbb"
+ ],
+ "version": "==18.2.0"
+ },
+ "cffi": {
+ "hashes": [
+ "sha256:151b7eefd035c56b2b2e1eb9963c90c6302dc15fbd8c1c0a83a163ff2c7d7743",
+ "sha256:1553d1e99f035ace1c0544050622b7bc963374a00c467edafac50ad7bd276aef",
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+ "sha256:9d1d3e63a4afdc29bd76ce6aa9d58c771cd1599fbba8cf5057e7860b203710dd",
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+ "sha256:d5d8555d9bfc3f02385c1c37e9f998e2011f0db4f90e250e5bc0c0a85a813085",
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+ "sha256:e90f17980e6ab0f3c2f3730e56d1fe9bcba1891eeea58966e89d352492cc74f4",
+ "sha256:ecbb7b01409e9b782df5ded849c178a0aa7c906cf8c5a67368047daab282b184",
+ "sha256:ed01918d545a38998bfa5902c7c00e0fee90e957ce036a4000a88e3fe2264917",
+ "sha256:edabd457cd23a02965166026fd9bfd196f4324fe6032e866d0f3bd0301cd486f",
+ "sha256:fdf1c1dc5bafc32bc5d08b054f94d659422b05aba244d6be4ddc1c72d9aa70fb"
+ ],
+ "version": "==1.11.5"
+ },
+ "corner": {
+ "hashes": [
+ "sha256:102e22797ee75d1432b6dc66aa2850f61388996ece66fd6600508742d2a7b88f"
+ ],
+ "index": "pypi",
+ "version": "==2.0.1"
+ },
+ "cryptography": {
+ "hashes": [
+ "sha256:02602e1672b62e803e08617ec286041cc453e8d43f093a5f4162095506bc0beb",
+ "sha256:10b48e848e1edb93c1d3b797c83c72b4c387ab0eb4330aaa26da8049a6cbede0",
+ "sha256:17db09db9d7c5de130023657be42689d1a5f60502a14f6f745f6f65a6b8195c0",
+ "sha256:227da3a896df1106b1a69b1e319dce218fa04395e8cc78be7e31ca94c21254bc",
+ "sha256:2cbaa03ac677db6c821dac3f4cdfd1461a32d0615847eedbb0df54bb7802e1f7",
+ "sha256:31db8febfc768e4b4bd826750a70c79c99ea423f4697d1dab764eb9f9f849519",
+ "sha256:4a510d268e55e2e067715d728e4ca6cd26a8e9f1f3d174faf88e6f2cb6b6c395",
+ "sha256:6a88d9004310a198c474d8a822ee96a6dd6c01efe66facdf17cb692512ae5bc0",
+ "sha256:76936ec70a9b72eb8c58314c38c55a0336a2b36de0c7ee8fb874a4547cadbd39",
+ "sha256:7e3b4aecc4040928efa8a7cdaf074e868af32c58ffc9bb77e7bf2c1a16783286",
+ "sha256:8168bcb08403ef144ff1fb880d416f49e2728101d02aaadfe9645883222c0aa5",
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+ "sha256:8a19e9f2fe69f6a44a5c156968d9fc8df56d09798d0c6a34ccc373bb186cee86",
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+ "sha256:dc2d3f3b1548f4d11786616cf0f4415e25b0fbecb8a1d2cd8c07568f13fdde38",
+ "sha256:e4aecdd9d5a3d06c337894c9a6e2961898d3f64fe54ca920a72234a3de0f9cb3",
+ "sha256:e79ab4485b99eacb2166f3212218dd858258f374855e1568f728462b0e6ee0d9",
+ "sha256:f995d3667301e1754c57b04e0bae6f0fa9d710697a9f8d6712e8cca02550910f"
+ ],
+ "version": "==2.3.1"
+ },
+ "cycler": {
+ "hashes": [
+ "sha256:1d8a5ae1ff6c5cf9b93e8811e581232ad8920aeec647c37316ceac982b08cb2d",
+ "sha256:cd7b2d1018258d7247a71425e9f26463dfb444d411c39569972f4ce586b0c9d8"
+ ],
+ "version": "==0.10.0"
+ },
+ "deepdish": {
+ "hashes": [
+ "sha256:2b1d3d2a32356909f2618c382a1829347990ad81b63aaecc87b35a046cd3034c",
+ "sha256:7858b674ef15ee79828de4892dadd2f58773ead527f3a62aaf1e8ce5a595a074"
+ ],
+ "index": "pypi",
+ "version": "==0.3.6"
+ },
+ "dynesty": {
+ "hashes": [
+ "sha256:82f9343a8d10de5754d16169da02721b42edb1ddca622ccfba6168746c4c838e"
+ ],
+ "index": "pypi",
+ "version": "==0.9.2"
+ },
+ "emcee": {
+ "hashes": [
+ "sha256:b83551e342b37311897906b3b8acf32979f4c5542e0a25786ada862d26241172"
+ ],
+ "index": "pypi",
+ "version": "==2.2.1"
+ },
+ "future": {
+ "hashes": [
+ "sha256:e39ced1ab767b5936646cedba8bcce582398233d6a627067d4c6a454c90cfedb"
+ ],
+ "index": "pypi",
+ "version": "==0.16.0"
+ },
+ "gwpy": {
+ "hashes": [
+ "sha256:3b6d2ba9a8844f6321c62ff3b9439f119e6447194b3d234944b5120a0856b5cc",
+ "sha256:74c5066e19e2b10dd0571ac0f0bd588b302d1f6de639a994021a580bb90d93f4"
+ ],
+ "index": "pypi",
+ "version": "==0.12.2"
+ },
+ "h5py": {
+ "hashes": [
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+ "sha256:e626c65a8587921ebc7fb8d31a49addfdd0b9a9aa96315ea484c09803337b955"
+ ],
+ "version": "==2.8.0"
+ },
+ "idna": {
+ "hashes": [
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+ "sha256:684a38a6f903c1d71d6d5fac066b58d7768af4de2b832e426ec79c30daa94a16"
+ ],
+ "version": "==2.7"
+ },
+ "joblib": {
+ "hashes": [
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+ "sha256:142e74bee7b9dfad75c7dad24c4295b9084a6788116dd149e2fc7daf0db25675"
+ ],
+ "version": "==0.12.5"
+ },
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+ "sha256:26ff56a6b5ecaf3a2a59f132681e2a80afcc76b4f902f612f518f92c2a1bf854",
+ "sha256:6488f1423b00f73b7ad5167885312bb0ce410d3312eb212393795b53c8caa580"
+ ],
+ "version": "==18.0.0"
+ },
+ "pyparsing": {
+ "hashes": [
+ "sha256:bc6c7146b91af3f567cf6daeaec360bc07d45ffec4cf5353f4d7a208ce7ca30a",
+ "sha256:d29593d8ebe7b57d6967b62494f8c72b03ac0262b1eed63826c6f788b3606401"
+ ],
+ "markers": "python_version != '3.2.*' and python_version >= '2.6' and python_version != '3.1.*' and python_version != '3.0.*'",
+ "version": "==2.2.2"
+ },
+ "pytest": {
+ "hashes": [
+ "sha256:0a72d8a9f559c006ba153e0c9b4838efd7b656cf1f993747ba7128770d6eb12c",
+ "sha256:95529588ff4e85114a0b0ad8e9cf0131ca47d46b28230e25366c5aba66b1d854"
+ ],
+ "markers": "python_version != '3.2.*' and python_version >= '2.7' and python_version != '3.3.*' and python_version != '3.1.*' and python_version != '3.0.*'",
+ "version": "==3.8.1"
+ },
+ "python-dateutil": {
+ "hashes": [
+ "sha256:1adb80e7a782c12e52ef9a8182bebeb73f1d7e24e374397af06fb4956c8dc5c0",
+ "sha256:e27001de32f627c22380a688bcc43ce83504a7bc5da472209b4c70f02829f0b8"
+ ],
+ "version": "==2.7.3"
+ },
+ "pytz": {
+ "hashes": [
+ "sha256:a061aa0a9e06881eb8b3b2b43f05b9439d6583c206d0a6c340ff72a7b6669053",
+ "sha256:ffb9ef1de172603304d9d2819af6f5ece76f2e85ec10692a524dd876e72bf277"
+ ],
+ "version": "==2018.5"
+ },
+ "scipy": {
+ "hashes": [
+ "sha256:0611ee97296265af4a21164a5323f8c1b4e8e15c582d3dfa7610825900136bb7",
+ "sha256:08237eda23fd8e4e54838258b124f1cd141379a5f281b0a234ca99b38918c07a",
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+ "sha256:d40dc7f494b06dcee0d303e51a00451b2da6119acbeaccf8369f2d29e28917ac",
+ "sha256:d8491d4784aceb1f100ddb8e31239c54e4afab8d607928a9f7ef2469ec35ae01",
+ "sha256:dfc5080c38dde3f43d8fbb9c0539a7839683475226cf83e4b24363b227dfe552",
+ "sha256:e24e22c8d98d3c704bb3410bce9b69e122a8de487ad3dbfe9985d154e5c03a40",
+ "sha256:e7a01e53163818d56eabddcafdc2090e9daba178aad05516b20c6591c4811020",
+ "sha256:ee677635393414930541a096fc8e61634304bb0153e4e02b75685b11eba14cae",
+ "sha256:f0521af1b722265d824d6ad055acfe9bd3341765735c44b5a4d0069e189a0f40",
+ "sha256:f25c281f12c0da726c6ed00535ca5d1622ec755c30a3f8eafef26cf43fede694"
+ ],
+ "index": "pypi",
+ "version": "==1.1.0"
+ },
+ "six": {
+ "hashes": [
+ "sha256:70e8a77beed4562e7f14fe23a786b54f6296e34344c23bc42f07b15018ff98e9",
+ "sha256:832dc0e10feb1aa2c68dcc57dbb658f1c7e65b9b61af69048abc87a2db00a0eb"
+ ],
+ "version": "==1.11.0"
+ },
+ "tables": {
+ "hashes": [
+ "sha256:07bb9e96b762874e239ad8cec2cab2c4129abf576fffcdd4e961482dc7d5a0a6",
+ "sha256:09eed21e12a1286ac2e8c5e67a75d9c7a7f262883535a31ac0b985540135d8d6",
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+ "sha256:415731ae46dfdef7fbe305399a700a54b06a82c4331ba20cc64004fb40e79069",
+ "sha256:44289caf89efac435f49fa4bd298eb48969c026dec25d3a76e7955f1281d1bdf",
+ "sha256:714f7162ffa4d470da8c9a067935520e5925384445bdb23989351b48d236345c",
+ "sha256:82d98123cf67c012d6c7cb69c6733b51eb10d17fc40547bbb71ffedae8da4f90",
+ "sha256:b625fc71f082011806a60d3b7370f75e34b141dab549ed65957aed54d1f12f63",
+ "sha256:bc1621bd84769ff3f84cfd1481f93ed0c537db4b3355576270bdbb79bb390b1f",
+ "sha256:bdc5c073712af2a43babd139c4855fc99496bb2c3f3f5d1b4770a985e6f9ce29",
+ "sha256:bed4f423dd33600907f1c3b88f994920f2b879b12bf83d4372f861ef4085e085",
+ "sha256:c3ac22e3391f67a381d9a3018fd7e0a1ccfcc88b5f61b0d051fe5eba8196388f",
+ "sha256:da98c8abfeefefad40110b994d5d06ac28d89b00d085530d377376b201566ebf",
+ "sha256:e2e4e40d010a6aa0464e5e281d4aa15f64acd99fd881c0e1e4c1c567b7167dba",
+ "sha256:e3bd7084dbf80ef347ad5d33645584e0fe7f8353cf2c33d8922a4c00034fa015",
+ "sha256:e8f9b20b9623c900e7007b89a9d3e315280b666ac70b38b0c191345f7d4d8585",
+ "sha256:f786d310cf954eaf52340680dfbc5c1190afc276093f5c454fab605a11488306",
+ "sha256:f97c8b5ebec23894fc56af25c6e73bc86b463cbccb1f9b9887def24cd7811e2c"
+ ],
+ "version": "==3.4.4"
+ },
+ "theano": {
+ "hashes": [
+ "sha256:637f3b34d40ef5e0d54dd4c40618475aaa085c26d2491e925c98e2ad4bc2115a"
+ ],
+ "index": "pypi",
+ "version": "==1.0.3"
+ },
+ "tqdm": {
+ "hashes": [
+ "sha256:18f1818ce951aeb9ea162ae1098b43f583f7d057b34d706f66939353d1208889",
+ "sha256:df02c0650160986bac0218bb07952245fc6960d23654648b5d5526ad5a4128c9"
+ ],
+ "markers": "python_version != '3.1.*' and python_version >= '2.6' and python_version != '3.0.*'",
+ "version": "==4.26.0"
+ }
+ },
+ "develop": {}
+}
diff --git a/examples/injection_examples/basic_tutorial.py b/examples/injection_examples/basic_tutorial.py
index 2c18ef1c33fba11302dd09a6a892196a2e8861dd..b86058a3a64b223c6bf1f7acae187803b5b703b3 100644
--- a/examples/injection_examples/basic_tutorial.py
+++ b/examples/injection_examples/basic_tutorial.py
@@ -60,8 +60,9 @@ ifos.inject_signal(waveform_generator=waveform_generator,
# that will be included in the sampler. If we do nothing, then the default priors get used.
priors = tupak.gw.prior.BBHPriorSet()
priors['geocent_time'] = tupak.core.prior.Uniform(
- minimum=injection_parameters['geocent_time'] - 1, maximum=injection_parameters['geocent_time'] + 1,
- name='geocent_time', latex_label='$t_c$')
+ minimum=injection_parameters['geocent_time'] - 1,
+ maximum=injection_parameters['geocent_time'] + 1,
+ name='geocent_time', latex_label='$t_c$', unit='$s$')
for key in ['a_1', 'a_2', 'tilt_1', 'tilt_2', 'phi_12', 'phi_jl', 'psi', 'ra', 'dec', 'geocent_time', 'phase']:
priors[key] = injection_parameters[key]
diff --git a/examples/injection_examples/change_sampled_parameters.py b/examples/injection_examples/change_sampled_parameters.py
index 106ace05c782ec8dc485e46c288527722e8731f8..a25bd15381f9241522b7ecadea03e266a2c0ec23 100644
--- a/examples/injection_examples/change_sampled_parameters.py
+++ b/examples/injection_examples/change_sampled_parameters.py
@@ -50,7 +50,8 @@ priors.pop('mass_1')
priors.pop('mass_2')
priors.pop('luminosity_distance')
priors['chirp_mass'] = tupak.prior.Uniform(
- name='chirp_mass', latex_label='$m_c$', minimum=13, maximum=45)
+ name='chirp_mass', latex_label='$m_c$', minimum=13, maximum=45,
+ unit='$M_{\\odot}$')
priors['symmetric_mass_ratio'] = tupak.prior.Uniform(
name='symmetric_mass_ratio', latex_label='q', minimum=0.1, maximum=0.25)
priors['redshift'] = tupak.prior.Uniform(
diff --git a/examples/injection_examples/create_your_own_time_domain_source_model.py b/examples/injection_examples/create_your_own_time_domain_source_model.py
index b1f814c6e9cf3bc7fe6f2c5146cdf2f10fed49d8..7fdbaa06fa88fbb7c7ed3f1afbf8ba315ea6fa83 100644
--- a/examples/injection_examples/create_your_own_time_domain_source_model.py
+++ b/examples/injection_examples/create_your_own_time_domain_source_model.py
@@ -47,8 +47,9 @@ ifos.inject_signal(waveform_generator=waveform,
# create the priors
prior = injection_parameters.copy()
prior['amplitude'] = tupak.core.prior.Uniform(1e-23, 1e-21, r'$h_0$')
-prior['damping_time'] = tupak.core.prior.Uniform(0, 1, r'damping time')
-prior['frequency'] = tupak.core.prior.Uniform(0, 200, r'frequency')
+prior['damping_time'] = tupak.core.prior.Uniform(
+ 0, 1, r'damping time', unit='$s$')
+prior['frequency'] = tupak.core.prior.Uniform(0, 200, r'frequency', unit='Hz')
prior['phase'] = tupak.core.prior.Uniform(-np.pi / 2, np.pi / 2, r'$\phi$')
# define likelihood
diff --git a/examples/injection_examples/eccentric_inspiral.py b/examples/injection_examples/eccentric_inspiral.py
index f4077b640c2d3446f7c32699e58e4bdfda3f3215..fc8500e5d36b5218a6cf6f800bc8af2e4da43fb5 100644
--- a/examples/injection_examples/eccentric_inspiral.py
+++ b/examples/injection_examples/eccentric_inspiral.py
@@ -60,16 +60,23 @@ ifos.inject_signal(waveform_generator=waveform_generator,
# Now we set up the priors on each of the binary parameters.
priors = dict()
-priors["mass_1"] = tupak.core.prior.Uniform(name='mass_1', minimum=5, maximum=60)
-priors["mass_2"] = tupak.core.prior.Uniform(name='mass_2', minimum=5, maximum=60)
-priors["eccentricity"] = tupak.core.prior.PowerLaw(name='eccentricity', latex_label='$e$', alpha=-1, minimum=1e-4, maximum=0.4)
-priors["luminosity_distance"] = tupak.gw.prior.UniformComovingVolume(name='luminosity_distance', minimum=1e2, maximum=2e3)
-priors["dec"] = tupak.core.prior.Cosine(name='dec')
-priors["ra"] = tupak.core.prior.Uniform(name='ra', minimum=0, maximum=2 * np.pi)
-priors["iota"] = tupak.core.prior.Sine(name='iota')
-priors["psi"] = tupak.core.prior.Uniform(name='psi', minimum=0, maximum=np.pi)
-priors["phase"] = tupak.core.prior.Uniform(name='phase', minimum=0, maximum=2 * np.pi)
-priors["geocent_time"] = tupak.core.prior.Uniform(1180002600.9, 1180002601.1, name='geocent_time')
+priors["mass_1"] = tupak.core.prior.Uniform(
+ name='mass_1', minimum=5, maximum=60, unit='$M_{\\odot}$')
+priors["mass_2"] = tupak.core.prior.Uniform(
+ name='mass_2', minimum=5, maximum=60, unit='$M_{\\odot}$')
+priors["eccentricity"] = tupak.core.prior.PowerLaw(
+ name='eccentricity', latex_label='$e$', alpha=-1, minimum=1e-4, maximum=0.4)
+priors["luminosity_distance"] = tupak.gw.prior.UniformComovingVolume(
+ name='luminosity_distance', minimum=1e2, maximum=2e3)
+priors["dec"] = tupak.core.prior.Cosine(name='dec')
+priors["ra"] = tupak.core.prior.Uniform(
+ name='ra', minimum=0, maximum=2 * np.pi)
+priors["iota"] = tupak.core.prior.Sine(name='iota')
+priors["psi"] = tupak.core.prior.Uniform(name='psi', minimum=0, maximum=np.pi)
+priors["phase"] = tupak.core.prior.Uniform(
+ name='phase', minimum=0, maximum=2 * np.pi)
+priors["geocent_time"] = tupak.core.prior.Uniform(
+ 1180002600.9, 1180002601.1, name='geocent_time', unit='s')
# Initialising the likelihood function.
likelihood = tupak.gw.likelihood.GravitationalWaveTransient(interferometers=ifos,
diff --git a/examples/injection_examples/how_to_specify_the_prior.py b/examples/injection_examples/how_to_specify_the_prior.py
index 51b7877dde665ece58094500d25e9504e81c94d7..3489d4aa3c3e4233c4d2c13759106c1a01eead1d 100644
--- a/examples/injection_examples/how_to_specify_the_prior.py
+++ b/examples/injection_examples/how_to_specify_the_prior.py
@@ -40,25 +40,29 @@ ifos.inject_signal(waveform_generator=waveform_generator,
# This loads in a predefined set of priors for BBHs.
priors = tupak.gw.prior.BBHPriorSet()
# These parameters will not be sampled
-for key in ['tilt_1', 'tilt_2', 'phi_12', 'phi_jl', 'phase', 'iota', 'ra', 'dec', 'geocent_time', 'psi']:
+for key in ['tilt_1', 'tilt_2', 'phi_12', 'phi_jl', 'phase', 'iota', 'ra',
+ 'dec', 'geocent_time', 'psi']:
priors[key] = injection_parameters[key]
# We can make uniform distributions.
-priors['mass_2'] = tupak.core.prior.Uniform(name='mass_2', minimum=20, maximum=40)
+priors['mass_2'] = tupak.core.prior.Uniform(
+ name='mass_2', minimum=20, maximum=40, unit='$M_{\\odot}$')
# We can make a power-law distribution, p(x) ~ x^{alpha}
# Note: alpha=0 is a uniform distribution, alpha=-1 is uniform-in-log
-priors['a_1'] = tupak.core.prior.PowerLaw(name='a_1', alpha=-1, minimum=1e-2, maximum=1)
+priors['a_1'] = tupak.core.prior.PowerLaw(
+ name='a_1', alpha=-1, minimum=1e-2, maximum=1)
# We can define a prior from an array as follows.
# Note: this doesn't have to be properly normalised.
a_2 = np.linspace(0, 1, 1001)
p_a_2 = a_2 ** 4
-priors['a_2'] = tupak.core.prior.Interped(name='a_2', xx=a_2, yy=p_a_2, minimum=0, maximum=0.5)
+priors['a_2'] = tupak.core.prior.Interped(
+ name='a_2', xx=a_2, yy=p_a_2, minimum=0, maximum=0.5)
# Additionally, we have Gaussian, TruncatedGaussian, Sine and Cosine.
# It's also possible to load an interpolate a prior from a file.
# Finally, if you don't specify any necessary parameters it will be filled in from the default when the sampler starts.
# Enjoy.
# Initialise GravitationalWaveTransient
-likelihood = tupak.GravitationalWaveTransient(interferometers=ifos, waveform_generator=waveform_generator)
+likelihood = tupak.gw.GravitationalWaveTransient(interferometers=ifos, waveform_generator=waveform_generator)
# Run sampler
result = tupak.run_sampler(likelihood=likelihood, priors=priors, sampler='dynesty',
diff --git a/examples/injection_examples/sine_gaussian_example.py b/examples/injection_examples/sine_gaussian_example.py
index aba4081847b49c4f7388df6ccf348c4558c8c5d7..7974332df265f62b3e10c37c1dba7a2176f19a10 100644
--- a/examples/injection_examples/sine_gaussian_example.py
+++ b/examples/injection_examples/sine_gaussian_example.py
@@ -53,7 +53,7 @@ for key in ['psi', 'ra', 'dec', 'geocent_time']:
#priors['Q'] = tupak.prior.create_default_prior(name='Q')
#priors['frequency'] = tupak.prior.create_default_prior(name='frequency')
priors['Q'] = tupak.core.prior.Uniform(2, 50, 'Q')
-priors['frequency'] = tupak.core.prior.Uniform(30, 1000, 'frequency')
+priors['frequency'] = tupak.core.prior.Uniform(30, 1000, 'frequency', unit='Hz')
priors['hrss'] = tupak.core.prior.Uniform(1e-23, 1e-21, 'hrss')
# Initialise the likelihood by passing in the interferometer data (IFOs) and the waveoform generator
diff --git a/examples/supernova_example/supernova_example.py b/examples/supernova_example/supernova_example.py
index 2365bd55ef652f47819214acf7635615e5ab82b2..18cfd389cff034ebff31cba9e14bc3de0c11793e 100644
--- a/examples/supernova_example/supernova_example.py
+++ b/examples/supernova_example/supernova_example.py
@@ -68,7 +68,7 @@ priors = dict()
for key in ['psi', 'geocent_time']:
priors[key] = injection_parameters[key]
priors['luminosity_distance'] = tupak.core.prior.Uniform(
- 2, 20, 'luminosity_distance')
+ 2, 20, 'luminosity_distance', unit='$kpc$')
priors['pc_coeff1'] = tupak.core.prior.Uniform(-1, 1, 'pc_coeff1')
priors['pc_coeff2'] = tupak.core.prior.Uniform(-1, 1, 'pc_coeff2')
priors['pc_coeff3'] = tupak.core.prior.Uniform(-1, 1, 'pc_coeff3')
@@ -80,7 +80,7 @@ priors['dec'] = tupak.core.prior.Sine(name='dec')
priors['geocent_time'] = tupak.core.prior.Uniform(
injection_parameters['geocent_time'] - 1,
injection_parameters['geocent_time'] + 1,
- 'geocent_time')
+ 'geocent_time', unit='$s$')
# Initialise the likelihood by passing in the interferometer data (IFOs) and
# the waveoform generator
diff --git a/test/prior_files/binary_black_holes.prior b/test/prior_files/binary_black_holes.prior
index 7dfc784a2107c1b0eb5a837743a054fef3fc7c37..eb47cdaf08f722c97c9552a8fe4b880f26b71a00 100644
--- a/test/prior_files/binary_black_holes.prior
+++ b/test/prior_files/binary_black_holes.prior
@@ -2,10 +2,10 @@
# Note that you may wish to use more specific mass and distance parameters.
# These commands are all known to tupak.gw.prior.
# Lines beginning "#" are ignored.
-mass_1 = Uniform(name='mass_1', minimum=5, maximum=100)
-mass_2 = Uniform(name='mass_2', minimum=5, maximum=100)
-# chirp_mass = Uniform(name='chirp_mass', minimum=25, maximum=100)
-# total_mass = Uniform(name='total_mass', minimum=10, maximum=200)
+mass_1 = Uniform(name='mass_1', minimum=5, maximum=100, unit='$M_{\\odot}$')
+mass_2 = Uniform(name='mass_2', minimum=5, maximum=100, unit='$M_{\\odot}$')
+# chirp_mass = Uniform(name='chirp_mass', minimum=25, maximum=100, unit='$M_{\\odot}$')
+# total_mass = Uniform(name='total_mass', minimum=10, maximum=200, unit='$M_{\\odot}$')
# mass_ratio = Uniform(name='mass_ratio', minimum=0.125, maximum=1)
# symmetric_mass_ratio = Uniform(name='symmetric_mass_ratio', minimum=8 / 81, maximum=0.25)
a_1 = Uniform(name='a_1', minimum=0, maximum=0.8)
@@ -16,7 +16,7 @@ tilt_2 = Sine(name='tilt_2')
# cos_tilt_2 = Uniform(name='cos_tilt_2', minimum=-1, maximum=1)
phi_12 = Uniform(name='phi_12', minimum=0, maximum=2 * np.pi)
phi_jl = Uniform(name='phi_jl', minimum=0, maximum=2 * np.pi)
-luminosity_distance = tupak.gw.prior.UniformComovingVolume(name='luminosity_distance', minimum=1e2, maximum=5e3)
+luminosity_distance = tupak.gw.prior.UniformComovingVolume(name='luminosity_distance', minimum=1e2, maximum=5e3, unit='Mpc')
dec = Cosine(name='dec')
ra = Uniform(name='ra', minimum=0, maximum=2 * np.pi)
iota = Sine(name='iota')
diff --git a/test/prior_test.py b/test/prior_test.py
index 89047308738512b59799c994f90fb48ea3137309..c147d723efb477b5064378b960cfeacfdf3c8032 100644
--- a/test/prior_test.py
+++ b/test/prior_test.py
@@ -347,22 +347,30 @@ class TestPriorSet(unittest.TestCase):
# shutil.rmtree(outdir_path)
def test_read_from_file(self):
- expected = dict(mass_1=tupak.core.prior.Uniform(name='mass_1', minimum=5, maximum=100),
- mass_2=tupak.core.prior.Uniform(name='mass_2', minimum=5, maximum=100),
- a_1=tupak.core.prior.Uniform(name='a_1', minimum=0, maximum=0.8),
- a_2=tupak.core.prior.Uniform(name='a_2', minimum=0, maximum=0.8),
- tilt_1=tupak.core.prior.Sine(name='tilt_1'),
- tilt_2=tupak.core.prior.Sine(name='tilt_2'),
- phi_12=tupak.core.prior.Uniform(name='phi_12', minimum=0, maximum=2 * np.pi),
- phi_jl=tupak.core.prior.Uniform(name='phi_jl', minimum=0, maximum=2 * np.pi),
- luminosity_distance=tupak.gw.prior.UniformComovingVolume(name='luminosity_distance',
- minimum=1e2, maximum=5e3),
- dec=tupak.core.prior.Cosine(name='dec'),
- ra=tupak.core.prior.Uniform(name='ra', minimum=0, maximum=2 * np.pi),
- iota=tupak.core.prior.Sine(name='iota'),
- psi=tupak.core.prior.Uniform(name='psi', minimum=0, maximum=np.pi),
- phase=tupak.core.prior.Uniform(name='phase', minimum=0, maximum=2 * np.pi)
- )
+ expected = dict(
+ mass_1=tupak.core.prior.Uniform(
+ name='mass_1', minimum=5, maximum=100, unit='$M_{\\odot}$'),
+ mass_2=tupak.core.prior.Uniform(
+ name='mass_2', minimum=5, maximum=100, unit='$M_{\\odot}$'),
+ a_1=tupak.core.prior.Uniform(name='a_1', minimum=0, maximum=0.8),
+ a_2=tupak.core.prior.Uniform(name='a_2', minimum=0, maximum=0.8),
+ tilt_1=tupak.core.prior.Sine(name='tilt_1'),
+ tilt_2=tupak.core.prior.Sine(name='tilt_2'),
+ phi_12=tupak.core.prior.Uniform(
+ name='phi_12', minimum=0, maximum=2 * np.pi),
+ phi_jl=tupak.core.prior.Uniform(
+ name='phi_jl', minimum=0, maximum=2 * np.pi),
+ luminosity_distance=tupak.gw.prior.UniformComovingVolume(
+ name='luminosity_distance', minimum=1e2,
+ maximum=5e3, unit='Mpc'),
+ dec=tupak.core.prior.Cosine(name='dec'),
+ ra=tupak.core.prior.Uniform(
+ name='ra', minimum=0, maximum=2 * np.pi),
+ iota=tupak.core.prior.Sine(name='iota'),
+ psi=tupak.core.prior.Uniform(name='psi', minimum=0, maximum=np.pi),
+ phase=tupak.core.prior.Uniform(
+ name='phase', minimum=0, maximum=2 * np.pi)
+ )
self.assertDictEqual(expected, self.prior_set_from_file)
def test_convert_floats_to_delta_functions(self):
@@ -380,22 +388,30 @@ class TestPriorSet(unittest.TestCase):
def test_prior_set_from_dict_but_using_a_string(self):
prior_set = tupak.core.prior.PriorSet(dictionary=self.default_prior_file)
- expected = dict(mass_1=tupak.core.prior.Uniform(name='mass_1', minimum=5, maximum=100),
- mass_2=tupak.core.prior.Uniform(name='mass_2', minimum=5, maximum=100),
- a_1=tupak.core.prior.Uniform(name='a_1', minimum=0, maximum=0.8),
- a_2=tupak.core.prior.Uniform(name='a_2', minimum=0, maximum=0.8),
- tilt_1=tupak.core.prior.Sine(name='tilt_1'),
- tilt_2=tupak.core.prior.Sine(name='tilt_2'),
- phi_12=tupak.core.prior.Uniform(name='phi_12', minimum=0, maximum=2 * np.pi),
- phi_jl=tupak.core.prior.Uniform(name='phi_jl', minimum=0, maximum=2 * np.pi),
- luminosity_distance=tupak.gw.prior.UniformComovingVolume(name='luminosity_distance',
- minimum=1e2, maximum=5e3),
- dec=tupak.core.prior.Cosine(name='dec'),
- ra=tupak.core.prior.Uniform(name='ra', minimum=0, maximum=2 * np.pi),
- iota=tupak.core.prior.Sine(name='iota'),
- psi=tupak.core.prior.Uniform(name='psi', minimum=0, maximum=np.pi),
- phase=tupak.core.prior.Uniform(name='phase', minimum=0, maximum=2 * np.pi)
- )
+ expected = dict(
+ mass_1=tupak.core.prior.Uniform(
+ name='mass_1', minimum=5, maximum=100, unit='$M_{\\odot}$'),
+ mass_2=tupak.core.prior.Uniform(
+ name='mass_2', minimum=5, maximum=100, unit='$M_{\\odot}$'),
+ a_1=tupak.core.prior.Uniform(name='a_1', minimum=0, maximum=0.8),
+ a_2=tupak.core.prior.Uniform(name='a_2', minimum=0, maximum=0.8),
+ tilt_1=tupak.core.prior.Sine(name='tilt_1'),
+ tilt_2=tupak.core.prior.Sine(name='tilt_2'),
+ phi_12=tupak.core.prior.Uniform(
+ name='phi_12', minimum=0, maximum=2 * np.pi),
+ phi_jl=tupak.core.prior.Uniform(
+ name='phi_jl', minimum=0, maximum=2 * np.pi),
+ luminosity_distance=tupak.gw.prior.UniformComovingVolume(
+ name='luminosity_distance', minimum=1e2,
+ maximum=5e3, unit='Mpc'),
+ dec=tupak.core.prior.Cosine(name='dec'),
+ ra=tupak.core.prior.Uniform(
+ name='ra', minimum=0, maximum=2 * np.pi),
+ iota=tupak.core.prior.Sine(name='iota'),
+ psi=tupak.core.prior.Uniform(name='psi', minimum=0, maximum=np.pi),
+ phase=tupak.core.prior.Uniform(
+ name='phase', minimum=0, maximum=2 * np.pi)
+ )
self.assertDictEqual(expected, prior_set)
def test_dict_argument_is_not_string_or_dict(self):
diff --git a/test/sampler_test.py b/test/sampler_test.py
index 53ec81b109cee30759484bc40624ffd635bab5d9..035d5324dabae6d2f457d4b8144c40409cab9763 100644
--- a/test/sampler_test.py
+++ b/test/sampler_test.py
@@ -360,7 +360,7 @@ class TestPymultinest(unittest.TestCase):
def test_default_kwargs(self):
expected = dict(importance_nested_sampling=False, resume=True,
verbose=True, sampling_efficiency='parameter',
- outputfiles_basename='outdir/pymultinest_label/',
+ outputfiles_basename='outdir/pm_label/',
n_live_points=500, n_params=None,
n_clustering_params=None, wrapped_params=None,
multimodal=True, const_efficiency_mode=False,
@@ -374,7 +374,7 @@ class TestPymultinest(unittest.TestCase):
def test_translate_kwargs(self):
expected = dict(importance_nested_sampling=False, resume=True,
verbose=True, sampling_efficiency='parameter',
- outputfiles_basename='outdir/pymultinest_label/',
+ outputfiles_basename='outdir/pm_label/',
n_live_points=123, n_params=None,
n_clustering_params=None, wrapped_params=None,
multimodal=True, const_efficiency_mode=False,
diff --git a/tupak/__init__.py b/tupak/__init__.py
index 8e0fd6a27cdee23f3676bd0da0930d5cd9f96d66..2dca9e6f1f44e7829c10c3e7842a622bb2d7e1d7 100644
--- a/tupak/__init__.py
+++ b/tupak/__init__.py
@@ -16,12 +16,10 @@ https://monash.docs.ligo.org/tupak/installation.html.
"""
-from __future__ import print_function, division, absolute_import
+from __future__ import absolute_import
-import tupak.core
-import tupak.gw
-import tupak.hyper
+from . import core, gw, hyper
-from tupak.core import utils, likelihood, prior, result, sampler
-from tupak.core.sampler import run_sampler
-from tupak.core.likelihood import Likelihood
+from .core import utils, likelihood, prior, result, sampler
+from .core.sampler import run_sampler
+from .core.likelihood import Likelihood
diff --git a/tupak/core/__init__.py b/tupak/core/__init__.py
index 94d3b3b2ffc7020e9f38eba6f7f4d031078bb56a..daa0c453de731ff0581c863b58b599d7b37e9d26 100644
--- a/tupak/core/__init__.py
+++ b/tupak/core/__init__.py
@@ -1,6 +1,2 @@
from __future__ import absolute_import
-import tupak.core.likelihood
-import tupak.core.prior
-import tupak.core.result
-import tupak.core.sampler
-import tupak.core.utils
\ No newline at end of file
+from . import likelihood, prior, result, sampler, utils
diff --git a/tupak/core/likelihood.py b/tupak/core/likelihood.py
index f743ecb3262b9e0bcb8b155deea277dcb687f3f5..0b184cefa9c4c96cdd392ef16107fb5d0e5dce0f 100644
--- a/tupak/core/likelihood.py
+++ b/tupak/core/likelihood.py
@@ -1,9 +1,9 @@
from __future__ import division, print_function
+import copy
import numpy as np
from scipy.special import gammaln
-from tupak.core.utils import infer_parameters_from_function
-import copy
+from .utils import infer_parameters_from_function
class Likelihood(object):
diff --git a/tupak/core/prior.py b/tupak/core/prior.py
index 3cc6f12f6b85150e52a358444c91477893b25ca7..68fa8ba9102b8d7538c56487c57da63b65cf57a7 100644
--- a/tupak/core/prior.py
+++ b/tupak/core/prior.py
@@ -9,8 +9,8 @@ import os
from collections import OrderedDict
from future.utils import iteritems
-from tupak.core.utils import logger
-from tupak.core import utils
+from .utils import logger
+from . import utils
import tupak # noqa
import inspect
diff --git a/tupak/core/result.py b/tupak/core/result.py
index 018c9a120299b3abd4c3af51bc1a7d34fa2bd77e..2617aff8a5121a3d87175c9eb74e8c66d5fe088e 100644
--- a/tupak/core/result.py
+++ b/tupak/core/result.py
@@ -8,9 +8,9 @@ import matplotlib
import matplotlib.pyplot as plt
from collections import OrderedDict
-from tupak.core import utils
-from tupak.core.utils import logger
-from tupak.core.prior import PriorSet, DeltaFunction
+from . import utils
+from .utils import logger
+from .prior import PriorSet, DeltaFunction
def result_file_name(outdir, label):
diff --git a/tupak/core/sampler/pymultinest.py b/tupak/core/sampler/pymultinest.py
index 4ea5b0f2929e8868130e81f98e10746adc9d9d1d..025368318c4a78b316809b1d22c03348b876cb85 100644
--- a/tupak/core/sampler/pymultinest.py
+++ b/tupak/core/sampler/pymultinest.py
@@ -2,6 +2,7 @@ from __future__ import absolute_import
from ..utils import check_directory_exists_and_if_not_mkdir
from .base_sampler import NestedSampler
+from tupak.core.utils import logger
class Pymultinest(NestedSampler):
@@ -48,12 +49,26 @@ class Pymultinest(NestedSampler):
kwargs['n_live_points'] = kwargs.pop(equiv)
def _verify_kwargs_against_default_kwargs(self):
+ """
+ Test the length of the directory where multinest will write the output.
+
+ This is an issue with MultiNest that we can't solve here.
+ https://github.com/JohannesBuchner/PyMultiNest/issues/115
+ """
if not self.kwargs['outputfiles_basename']:
- self.kwargs['outputfiles_basename'] = self.outdir + '/pymultinest_{}/'.format(self.label)
+ self.kwargs['outputfiles_basename'] =\
+ '{}/pm_{}/'.format(self.outdir, self.label)
if self.kwargs['outputfiles_basename'].endswith('/') is False:
self.kwargs['outputfiles_basename'] = '{}/'.format(
self.kwargs['outputfiles_basename'])
- check_directory_exists_and_if_not_mkdir(self.kwargs['outputfiles_basename'])
+ if len(self.kwargs['outputfiles_basename']) > (100 - 22):
+ logger.warning(
+ 'The length of {} exceeds 78 characters. '
+ ' Post-processing will fail because the file names will be cut'
+ ' off. Please choose a shorter "outdir" or "label".'
+ .format(self.__kwargs['outputfiles_basename']))
+ check_directory_exists_and_if_not_mkdir(
+ self.kwargs['outputfiles_basename'])
NestedSampler._verify_kwargs_against_default_kwargs(self)
def run_sampler(self):
diff --git a/tupak/gw/__init__.py b/tupak/gw/__init__.py
index 47063bf1e2790e5ef41ad096f9723905994e9cd9..3273cbd3e8358d2d91a3a44249c6dac3d00db287 100644
--- a/tupak/gw/__init__.py
+++ b/tupak/gw/__init__.py
@@ -1,13 +1,5 @@
-from __future__ import absolute_import
-import tupak.gw.conversion
-import tupak.gw.detector
-import tupak.gw.likelihood
-import tupak.gw.prior
-import tupak.gw.source
-import tupak.gw.utils
-import tupak.gw.waveform_generator
-from . import calibration
+from . import (calibration, conversion, detector, likelihood, prior, source,
+ utils, waveform_generator)
-
-from tupak.gw.waveform_generator import WaveformGenerator
-from tupak.gw.likelihood import GravitationalWaveTransient
+from .waveform_generator import WaveformGenerator
+from .likelihood import GravitationalWaveTransient
diff --git a/tupak/gw/conversion.py b/tupak/gw/conversion.py
index 5f78db028e631ec5d6e0daf2ac8ffb221a48c9aa..8c24eb8f3bc4a9db0e21850c785c7e8fd2af0e12 100644
--- a/tupak/gw/conversion.py
+++ b/tupak/gw/conversion.py
@@ -1,9 +1,9 @@
from __future__ import division
-import tupak
import numpy as np
import pandas as pd
-from tupak.core.utils import logger
+from ..core.utils import logger, solar_mass
+from ..core.prior import DeltaFunction
try:
from astropy.cosmology import z_at_value, Planck15
@@ -535,7 +535,7 @@ def fill_from_fixed_priors(sample, priors):
output_sample = sample.copy()
if priors is not None:
for name in priors:
- if isinstance(priors[name], tupak.core.prior.DeltaFunction):
+ if isinstance(priors[name], DeltaFunction):
output_sample[name] = priors[name].peak
return output_sample
@@ -610,8 +610,8 @@ def generate_component_spins(sample):
output_sample['tilt_1'], output_sample['tilt_2'],
output_sample['phi_12'], output_sample['a_1'],
output_sample['a_2'],
- output_sample['mass_1'] * tupak.core.utils.solar_mass,
- output_sample['mass_2'] * tupak.core.utils.solar_mass,
+ output_sample['mass_1'] * solar_mass,
+ output_sample['mass_2'] * solar_mass,
output_sample['reference_frequency'], output_sample['phase'])
output_sample['phi_1'] =\
@@ -637,8 +637,8 @@ def generate_component_spins(sample):
output_sample['tilt_1'][ii], output_sample['tilt_2'][ii],
output_sample['phi_12'][ii], output_sample['a_1'][ii],
output_sample['a_2'][ii],
- output_sample['mass_1'][ii] * tupak.core.utils.solar_mass,
- output_sample['mass_2'][ii] * tupak.core.utils.solar_mass,
+ output_sample['mass_1'][ii] * solar_mass,
+ output_sample['mass_2'][ii] * solar_mass,
output_sample['reference_frequency'][ii],
output_sample['phase'][ii])
diff --git a/tupak/gw/detector.py b/tupak/gw/detector.py
index 924e8a8782149439c956381d431edd0114ac80dd..1755ab484d4c1f17c5278f050dc471ca71650a68 100644
--- a/tupak/gw/detector.py
+++ b/tupak/gw/detector.py
@@ -7,9 +7,9 @@ import numpy as np
from scipy.signal.windows import tukey
from scipy.interpolate import interp1d
-from tupak.gw import utils as gwutils
-from tupak.core import utils
-from tupak.core.utils import logger
+from . import utils as gwutils
+from ..core import utils
+from ..core.utils import logger
from .calibration import Recalibrate
try:
diff --git a/tupak/gw/likelihood.py b/tupak/gw/likelihood.py
index 3d7a77197c89cde2caa64042dd663ab7567ddb1d..8965678ce40ace58af4c0722ae4c184fc6a04d29 100644
--- a/tupak/gw/likelihood.py
+++ b/tupak/gw/likelihood.py
@@ -8,11 +8,14 @@ except ImportError:
from scipy.misc import logsumexp
from scipy.special import i0e
-import tupak
-from tupak.core import likelihood as likelihood
-from tupak.core.utils import logger
-from tupak.gw.prior import BBHPriorSet
-from tupak.core.prior import Uniform
+from ..core import likelihood
+from ..core.utils import logger
+from ..core.prior import Prior, Uniform
+from .detector import InterferometerList
+from .prior import BBHPriorSet
+from .source import lal_binary_black_hole
+from .utils import noise_weighted_inner_product
+from .waveform_generator import WaveformGenerator
class GravitationalWaveTransient(likelihood.Likelihood):
@@ -57,7 +60,7 @@ class GravitationalWaveTransient(likelihood.Likelihood):
self.waveform_generator = waveform_generator
likelihood.Likelihood.__init__(self, dict())
- self.interferometers = tupak.gw.detector.InterferometerList(interferometers)
+ self.interferometers = InterferometerList(interferometers)
self.time_marginalization = time_marginalization
self.distance_marginalization = distance_marginalization
self.phase_marginalization = phase_marginalization
@@ -111,7 +114,7 @@ class GravitationalWaveTransient(likelihood.Likelihood):
def _check_prior_is_set(self, key):
if key not in self.prior or not isinstance(
- self.prior[key], tupak.core.prior.Prior):
+ self.prior[key], Prior):
logger.warning(
'Prior not provided for {}, using the BBH default.'.format(key))
if key == 'geocent_time':
@@ -138,7 +141,7 @@ class GravitationalWaveTransient(likelihood.Likelihood):
def noise_log_likelihood(self):
log_l = 0
for interferometer in self.interferometers:
- log_l -= tupak.gw.utils.noise_weighted_inner_product(
+ log_l -= noise_weighted_inner_product(
interferometer.frequency_domain_strain,
interferometer.frequency_domain_strain,
interferometer.power_spectral_density_array,
@@ -381,8 +384,10 @@ def get_binary_black_hole_likelihood(interferometers):
tupak.GravitationalWaveTransient: The likelihood to pass to `run_sampler`
"""
- waveform_generator = tupak.gw.waveform_generator.WaveformGenerator(
- duration=interferometers.duration, sampling_frequency=interferometers.sampling_frequency,
- frequency_domain_source_model=tupak.gw.source.lal_binary_black_hole,
- waveform_arguments={'waveform_approximant': 'IMRPhenomPv2', 'reference_frequency': 50})
- return tupak.gw.likelihood.GravitationalWaveTransient(interferometers, waveform_generator)
+ waveform_generator = WaveformGenerator(
+ duration=interferometers.duration,
+ sampling_frequency=interferometers.sampling_frequency,
+ frequency_domain_source_model=lal_binary_black_hole,
+ waveform_arguments={'waveform_approximant': 'IMRPhenomPv2',
+ 'reference_frequency': 50})
+ return GravitationalWaveTransient(interferometers, waveform_generator)
diff --git a/tupak/gw/prior.py b/tupak/gw/prior.py
index d45f2a7eedc314242aa0618ecdabc60a416a0309..0907e49b6addf30dc77abb8008fa5f105a88bbad 100644
--- a/tupak/gw/prior.py
+++ b/tupak/gw/prior.py
@@ -1,14 +1,15 @@
import os
+import numpy as np
+from scipy.interpolate import UnivariateSpline
from ..core.prior import (PriorSet, Uniform, FromFile, Prior, DeltaFunction,
Gaussian, Interped)
from ..core.utils import logger
-import numpy as np
-from scipy.interpolate import UnivariateSpline
class UniformComovingVolume(FromFile):
- def __init__(self, minimum=None, maximum=None, name='luminosity distance', latex_label='$d_L$'):
+ def __init__(self, minimum=None, maximum=None,
+ name='luminosity distance', latex_label='$d_L$', unit='Mpc'):
"""
Parameters
@@ -24,7 +25,7 @@ class UniformComovingVolume(FromFile):
"""
file_name = os.path.join(os.path.dirname(__file__), 'prior_files', 'comoving.txt')
FromFile.__init__(self, file_name=file_name, minimum=minimum, maximum=maximum, name=name,
- latex_label=latex_label, unit='Mpc')
+ latex_label=latex_label, unit=unit)
class AlignedSpin(Interped):
diff --git a/tupak/gw/prior_files/GW150914.prior b/tupak/gw/prior_files/GW150914.prior
index 8c372425f351e4df9012377101e9b41d8e1da85a..022d9c9ee1541e3fd9baec4b812c8d38f59a1d54 100644
--- a/tupak/gw/prior_files/GW150914.prior
+++ b/tupak/gw/prior_files/GW150914.prior
@@ -1,19 +1,19 @@
# These are the default priors for analysing GW150914.
-mass_1 = Uniform(name='mass_1', minimum=30, maximum=50)
-mass_2 = Uniform(name='mass_2', minimum=20, maximum=40)
+mass_1 = Uniform(name='mass_1', minimum=30, maximum=50, unit='$M_{\\odot}$')
+mass_2 = Uniform(name='mass_2', minimum=20, maximum=40, unit='$M_{\\odot}$')
a_1 = Uniform(name='a_1', minimum=0, maximum=0.8)
a_2 = Uniform(name='a_2', minimum=0, maximum=0.8)
tilt_1 = Sine(name='tilt_1')
tilt_2 = Sine(name='tilt_2')
phi_12 = Uniform(name='phi_12', minimum=0, maximum=2 * np.pi)
phi_jl = Uniform(name='phi_jl', minimum=0, maximum=2 * np.pi)
-luminosity_distance = tupak.gw.prior.UniformComovingVolume(name='luminosity_distance', minimum=1e2, maximum=1e3)
+luminosity_distance = tupak.gw.prior.UniformComovingVolume(name='luminosity_distance', minimum=1e2, maximum=1e3, unit='Mpc')
dec = Cosine(name='dec')
ra = Uniform(name='ra', minimum=0, maximum=2 * np.pi)
iota = Sine(name='iota')
psi = Uniform(name='psi', minimum=0, maximum=np.pi)
phase = Uniform(name='phase', minimum=0, maximum=2 * np.pi)
-geocent_time = Uniform(1126259462.322, 1126259462.522, name='geocent_time')
+geocent_time = Uniform(1126259462.322, 1126259462.522, name='geocent_time', unit='$s$')
# These are the calibration parameters as described in
# https://journals.aps.org/prx/abstract/10.1103/PhysRevX.6.041015
# recalib_H1_frequency_0 = 20
diff --git a/tupak/gw/prior_files/binary_black_holes.prior b/tupak/gw/prior_files/binary_black_holes.prior
index 7dfc784a2107c1b0eb5a837743a054fef3fc7c37..eb47cdaf08f722c97c9552a8fe4b880f26b71a00 100644
--- a/tupak/gw/prior_files/binary_black_holes.prior
+++ b/tupak/gw/prior_files/binary_black_holes.prior
@@ -2,10 +2,10 @@
# Note that you may wish to use more specific mass and distance parameters.
# These commands are all known to tupak.gw.prior.
# Lines beginning "#" are ignored.
-mass_1 = Uniform(name='mass_1', minimum=5, maximum=100)
-mass_2 = Uniform(name='mass_2', minimum=5, maximum=100)
-# chirp_mass = Uniform(name='chirp_mass', minimum=25, maximum=100)
-# total_mass = Uniform(name='total_mass', minimum=10, maximum=200)
+mass_1 = Uniform(name='mass_1', minimum=5, maximum=100, unit='$M_{\\odot}$')
+mass_2 = Uniform(name='mass_2', minimum=5, maximum=100, unit='$M_{\\odot}$')
+# chirp_mass = Uniform(name='chirp_mass', minimum=25, maximum=100, unit='$M_{\\odot}$')
+# total_mass = Uniform(name='total_mass', minimum=10, maximum=200, unit='$M_{\\odot}$')
# mass_ratio = Uniform(name='mass_ratio', minimum=0.125, maximum=1)
# symmetric_mass_ratio = Uniform(name='symmetric_mass_ratio', minimum=8 / 81, maximum=0.25)
a_1 = Uniform(name='a_1', minimum=0, maximum=0.8)
@@ -16,7 +16,7 @@ tilt_2 = Sine(name='tilt_2')
# cos_tilt_2 = Uniform(name='cos_tilt_2', minimum=-1, maximum=1)
phi_12 = Uniform(name='phi_12', minimum=0, maximum=2 * np.pi)
phi_jl = Uniform(name='phi_jl', minimum=0, maximum=2 * np.pi)
-luminosity_distance = tupak.gw.prior.UniformComovingVolume(name='luminosity_distance', minimum=1e2, maximum=5e3)
+luminosity_distance = tupak.gw.prior.UniformComovingVolume(name='luminosity_distance', minimum=1e2, maximum=5e3, unit='Mpc')
dec = Cosine(name='dec')
ra = Uniform(name='ra', minimum=0, maximum=2 * np.pi)
iota = Sine(name='iota')
diff --git a/tupak/gw/prior_files/binary_neutron_stars.prior b/tupak/gw/prior_files/binary_neutron_stars.prior
index f7b427c3c324c00ea8246d5150e6df9362f709c9..605498a7a4eb3066d5716fb4aa3a38c6fe9afd6b 100644
--- a/tupak/gw/prior_files/binary_neutron_stars.prior
+++ b/tupak/gw/prior_files/binary_neutron_stars.prior
@@ -2,15 +2,15 @@
# Note that you may wish to use more specific mass and distance parameters.
# These commands are all known to tupak.gw.prior.
# Lines beginning "#" are ignored.
-mass_1 = Uniform(name='mass_1', minimum=1, maximum=2)
-mass_2 = Uniform(name='mass_2', minimum=1, maximum=2)
-# chirp_mass = Uniform(name='chirp_mass', minimum=0.87, maximum=1.74)
-# total_mass = Uniform(name='total_mass', minimum=2, maximum=4)
+mass_1 = Uniform(name='mass_1', minimum=1, maximum=2, unit='$M_{\\odot}$')
+mass_2 = Uniform(name='mass_2', minimum=1, maximum=2, unit='$M_{\\odot}$')
+# chirp_mass = Uniform(name='chirp_mass', minimum=0.87, maximum=1.74, unit='$M_{\\odot}$')
+# total_mass = Uniform(name='total_mass', minimum=2, maximum=4, unit='$M_{\\odot}$')
# mass_ratio = Uniform(name='mass_ratio', minimum=0.5, maximum=1)
# symmetric_mass_ratio = Uniform(name='symmetric_mass_ratio', minimum=0.22, maximum=0.25)
a_1 = Uniform(name='a_1', minimum= -0.05, maximum= 0.05)
a_2 = Uniform(name='a_2', minimum= -0.05, maximum= 0.05)
-luminosity_distance = tupak.gw.prior.UniformComovingVolume(name='luminosity_distance', minimum=10, maximum=500)
+luminosity_distance = tupak.gw.prior.UniformComovingVolume(name='luminosity_distance', minimum=10, maximum=500, unit='Mpc')
dec = Cosine(name='dec')
ra = Uniform(name='ra', minimum=0, maximum=2 * np.pi)
iota = Sine(name='iota')
diff --git a/tupak/gw/source.py b/tupak/gw/source.py
index 85641ab26d61b7fc8963e5dda18c4045bc4279de..6ea32a002b47d9db62b0e1faf2ed77ca0af6662b 100644
--- a/tupak/gw/source.py
+++ b/tupak/gw/source.py
@@ -2,8 +2,8 @@ from __future__ import division, print_function
import numpy as np
-from tupak.core.utils import logger
-from tupak.core import utils
+from ..core import utils
+from ..core.utils import logger
try:
import lalsimulation as lalsim
diff --git a/tupak/gw/utils.py b/tupak/gw/utils.py
index 60fb7d150270bb7130f6f93d8605e3d632aca32c..6bc9d061fcf6f03c5542bff3bca45e04fd8844a1 100644
--- a/tupak/gw/utils.py
+++ b/tupak/gw/utils.py
@@ -3,7 +3,8 @@ import os
import numpy as np
-from ..core.utils import (gps_time_to_gmst, ra_dec_to_theta_phi, speed_of_light, logger)
+from ..core.utils import (gps_time_to_gmst, ra_dec_to_theta_phi,
+ speed_of_light, logger)
try:
from gwpy.timeseries import TimeSeries
diff --git a/tupak/gw/waveform_generator.py b/tupak/gw/waveform_generator.py
index 0134ffbb5f0c7ae6caeffbb830a4308ff5086c50..b9f00c76aaa0ccdb12cc385f1f1be4a7192cb5b4 100644
--- a/tupak/gw/waveform_generator.py
+++ b/tupak/gw/waveform_generator.py
@@ -1,5 +1,5 @@
-from tupak.core import utils
import numpy as np
+from ..core import utils
class WaveformGenerator(object):
diff --git a/tupak/hyper/__init__.py b/tupak/hyper/__init__.py
index 45ec4869a0c81d87d975e9171cf5da6a52c08926..b25e08c4f8e1e6f317063eb26e5d3512011f6e65 100644
--- a/tupak/hyper/__init__.py
+++ b/tupak/hyper/__init__.py
@@ -1,3 +1 @@
-from __future__ import absolute_import
-import tupak.hyper.likelihood
-import tupak.hyper.model
+from . import likelihood, model