<div align='center'>
<h1>gwaves</h1>
<p>A python lib for works with gravitational waves data</p>
<img alt="CodeFactor Grade" src="https://img.shields.io/codefactor/grade/github/reinanbr/gwaves?logo=codefactor"><img alt="Code Climate maintainability" src="https://img.shields.io/codeclimate/maintainability-percentage/reinanbr/dreams"><img alt="GitHub Pipenv locked Python version" src="https://img.shields.io/github/pipenv/locked/python-version/reinanbr/gwaves">
<br/>
<a href='https://pypi.org/project/dreams/'><img src='https://img.shields.io/pypi/v/gwaves'></a><img alt="PyPI - License" src="https://img.shields.io/pypi/l/gwaves?color=b"><a href="https://doi.org/10.5281/zenodo.7966690"><img src="https://zenodo.org/badge/DOI/10.5281/zenodo.7966690.svg" alt="DOI"></a>
<hr>
</div>
## installing:
```sh
pip3 install gwaves -U
```
## importing
```py
import gwaves as gw
```
## geting the all data:
```py
gw_data = gw.Gwaves_Data()
gw_data.data_gw
```
result:
```sh
(base)
Unnamed: 0 Name Version Release ... Pastro Final Mass (M☉) Date Link
0 0 GW200322_091133 v1 GWTC-3-confident ... 0.077572 0.08 53.0 53 +38 -26 2020-03-22T09:12:10.300 https://www.gw-openscience.org/eventapi/html/G...
1 1 GW200316_215756 v1 GWTC-3-confident ... 0.99 ≥ 0.99 20.2 20.2 +7.4 -1.9 2020-03-16T21:58:33.100 https://www.gw-openscience.org/eventapi/html/G...
2 2 GW200311_115853 v1 GWTC-3-confident ... 0.99 ≥ 0.99 59.0 59.0 +4.8 -3.9 2020-03-11T11:59:30.300 https://www.gw-openscience.org/eventapi/html/G...
3 3 GW200308_173609 v1 GWTC-3-confident ... 0.8566 0.86 47.4 47.4 +11.1 -7.7 2020-03-08T17:36:46.700 https://www.gw-openscience.org/eventapi/html/G...
4 4 GW200306_093714 v1 GWTC-3-confident ... 0.24004 0.24 41.7 41.7 +12.3 -6.9 2020-03-06T09:37:51.100 https://www.gw-openscience.org/eventapi/html/G...
.. ... ... ... ... ... ... ... ... ...
88 88 GW170608 v3 GWTC-1-confident ... 1.0 1.00 17.8 17.8 +3.4 -0.7 2017-06-08T02:01:53.500 https://www.gw-openscience.org/eventapi/html/G...
89 89 GW170104 v2 GWTC-1-confident ... 1.0 1.00 48.9 48.9 +5.1 -4.0 2017-01-04T10:12:35.600 https://www.gw-openscience.org/eventapi/html/G...
90 90 GW151226 v2 GWTC-1-confident ... 1.0 1.00 20.5 20.5 +6.4 -1.5 2015-12-26T03:39:29.600 https://www.gw-openscience.org/eventapi/html/G...
91 91 GW151012 v3 GWTC-1-confident ... 1.0 1.00 35.6 35.6 +10.8 -3.8 2015-10-12T09:55:19.400 https://www.gw-openscience.org/eventapi/html/G...
92 92 GW150914 v3 GWTC-1-confident ... 1.0 1.00 63.1 63.1 +3.4 -3.0 2015-09-14T09:51:21.400 https://www.gw-openscience.org/eventapi/html/G...
[93 rows x 19 columns]
```
## getting the last gravitational wave detected:
```py
last_gw_name = gw_data.data_gw['Name'][0]
last_gw = gw_data.get_gwave(last_gw_name)
last_gw
```
result:
```sh
{'strain': array([-1.20377769e-18, -1.23316083e-18, -1.19155622e-18, ...,
-7.84331557e-19, -7.46261544e-19, -7.87365720e-19]),
'freq': 16000,
'name': 'GW200322_091133',
'date': '2020-03-22T09:12:10.300',
'size': 4030830,
'detector': 'L1'}
```
## plotting:
```py
import matplotlib.pyplot as plt
plt.style.use('seaborn')
strain = last_gw['strain']
ax, fig = plt.subplots(figsize=(20,12))
plt.title(last_gw_name)
plt.plot(strain)
```
result:
<br/>
<img src='https://raw.githubusercontent.com/reinanbr/gwaves/main/img/plot_1.png'>
<br/>
### plotting the more detector's from same signal:
the detector's used in the data:
```py
gw_data.detectors
```
resut:
```sh
['L1', 'H1', 'V1']
```
getting the strain's
```py
strain_L1 = strain
strain_H1 = gw_data.get_gwave(last_gw_name,detector='H1')['strain']
strain_V1 = gw_data.get_gwave(last_gw_name,detector='V1')['strain']
```
plotting:
```py
ax,fig = plt.subplots(figsize=(32,14))
t = np.linspace(0,32,len(strain_L1))
plt.plot(t,strain_L1,label='L1',c='blue')
plt.plot(t,strain_V1,label='V1',c='green')
plt.plot(t,strain_H1,label='H1',c='red')
plt.legend()
```
result:
<br/>
<img src='https://raw.githubusercontent.com/reinanbr/gwaves/main/img/plot2.png'>
<br/>
### plotting the psd (Power Signal Density):
```py
ax,fig = plt.subplots(figsize=(32,14))
gw_data.plot_psd_from_gwname(last_gw_name,detector="L1")
gw_data.plot_psd_from_gwname(last_gw_name,detector="V1")
gw_data.plot_psd_from_gwname(last_gw_name,detector="H1")
```
result:
<br/>
<img src='https://raw.githubusercontent.com/reinanbr/gwaves/main/img/plot3.png'>
Raw data
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"description": "<div align='center'>\n <h1>gwaves</h1>\n<p>A python lib for works with gravitational waves data</p>\n<img alt=\"CodeFactor Grade\" src=\"https://img.shields.io/codefactor/grade/github/reinanbr/gwaves?logo=codefactor\"><img alt=\"Code Climate maintainability\" src=\"https://img.shields.io/codeclimate/maintainability-percentage/reinanbr/dreams\"><img alt=\"GitHub Pipenv locked Python version\" src=\"https://img.shields.io/github/pipenv/locked/python-version/reinanbr/gwaves\">\n<br/>\n<a href='https://pypi.org/project/dreams/'><img src='https://img.shields.io/pypi/v/gwaves'></a><img alt=\"PyPI - License\" src=\"https://img.shields.io/pypi/l/gwaves?color=b\"><a href=\"https://doi.org/10.5281/zenodo.7966690\"><img src=\"https://zenodo.org/badge/DOI/10.5281/zenodo.7966690.svg\" alt=\"DOI\"></a>\n\n<hr>\n\n\n\n</div>\n\n## installing:\n\n```sh\npip3 install gwaves -U\n```\n\n## importing\n```py\nimport gwaves as gw\n```\n## geting the all data:\n```py\ngw_data = gw.Gwaves_Data()\n\ngw_data.data_gw\n\n```\nresult:\n```sh\n (base) \n Unnamed: 0 Name Version Release ... Pastro Final Mass (M\u2609) Date Link\n0 0 GW200322_091133 v1 GWTC-3-confident ... 0.077572 0.08 53.0 53 +38 -26 2020-03-22T09:12:10.300 https://www.gw-openscience.org/eventapi/html/G...\n1 1 GW200316_215756 v1 GWTC-3-confident ... 0.99 \u2265 0.99 20.2 20.2 +7.4 -1.9 2020-03-16T21:58:33.100 https://www.gw-openscience.org/eventapi/html/G...\n2 2 GW200311_115853 v1 GWTC-3-confident ... 0.99 \u2265 0.99 59.0 59.0 +4.8 -3.9 2020-03-11T11:59:30.300 https://www.gw-openscience.org/eventapi/html/G...\n3 3 GW200308_173609 v1 GWTC-3-confident ... 0.8566 0.86 47.4 47.4 +11.1 -7.7 2020-03-08T17:36:46.700 https://www.gw-openscience.org/eventapi/html/G...\n4 4 GW200306_093714 v1 GWTC-3-confident ... 0.24004 0.24 41.7 41.7 +12.3 -6.9 2020-03-06T09:37:51.100 https://www.gw-openscience.org/eventapi/html/G...\n.. ... ... ... ... ... ... ... ... ...\n88 88 GW170608 v3 GWTC-1-confident ... 1.0 1.00 17.8 17.8 +3.4 -0.7 2017-06-08T02:01:53.500 https://www.gw-openscience.org/eventapi/html/G...\n89 89 GW170104 v2 GWTC-1-confident ... 1.0 1.00 48.9 48.9 +5.1 -4.0 2017-01-04T10:12:35.600 https://www.gw-openscience.org/eventapi/html/G...\n90 90 GW151226 v2 GWTC-1-confident ... 1.0 1.00 20.5 20.5 +6.4 -1.5 2015-12-26T03:39:29.600 https://www.gw-openscience.org/eventapi/html/G...\n91 91 GW151012 v3 GWTC-1-confident ... 1.0 1.00 35.6 35.6 +10.8 -3.8 2015-10-12T09:55:19.400 https://www.gw-openscience.org/eventapi/html/G...\n92 92 GW150914 v3 GWTC-1-confident ... 1.0 1.00 63.1 63.1 +3.4 -3.0 2015-09-14T09:51:21.400 https://www.gw-openscience.org/eventapi/html/G...\n\n[93 rows x 19 columns]\n```\n\n## getting the last gravitational wave detected:\n```py\nlast_gw_name = gw_data.data_gw['Name'][0]\nlast_gw = gw_data.get_gwave(last_gw_name)\n\nlast_gw\n```\nresult:\n```sh\n{'strain': array([-1.20377769e-18, -1.23316083e-18, -1.19155622e-18, ...,\n -7.84331557e-19, -7.46261544e-19, -7.87365720e-19]),\n 'freq': 16000,\n 'name': 'GW200322_091133',\n 'date': '2020-03-22T09:12:10.300',\n 'size': 4030830,\n 'detector': 'L1'}\n```\n## plotting:\n```py\nimport matplotlib.pyplot as plt\nplt.style.use('seaborn')\n\nstrain = last_gw['strain']\n\nax, fig = plt.subplots(figsize=(20,12))\n\nplt.title(last_gw_name)\nplt.plot(strain)\n```\nresult:\n<br/>\n\n<img src='https://raw.githubusercontent.com/reinanbr/gwaves/main/img/plot_1.png'>\n<br/>\n\n### plotting the more detector's from same signal:\nthe detector's used in the data:\n```py\ngw_data.detectors\n```\nresut:\n```sh\n['L1', 'H1', 'V1']\n```\ngetting the strain's\n```py\nstrain_L1 = strain\n\nstrain_H1 = gw_data.get_gwave(last_gw_name,detector='H1')['strain']\n\nstrain_V1 = gw_data.get_gwave(last_gw_name,detector='V1')['strain']\n```\nplotting:\n```py\nax,fig = plt.subplots(figsize=(32,14))\n\nt = np.linspace(0,32,len(strain_L1))\n\nplt.plot(t,strain_L1,label='L1',c='blue')\n\nplt.plot(t,strain_V1,label='V1',c='green')\n\nplt.plot(t,strain_H1,label='H1',c='red')\n\nplt.legend()\n```\nresult:\n<br/>\n\n<img src='https://raw.githubusercontent.com/reinanbr/gwaves/main/img/plot2.png'>\n\n<br/>\n\n\n### plotting the psd (Power Signal Density):\n\n```py\nax,fig = plt.subplots(figsize=(32,14))\n\ngw_data.plot_psd_from_gwname(last_gw_name,detector=\"L1\")\n\ngw_data.plot_psd_from_gwname(last_gw_name,detector=\"V1\")\n\ngw_data.plot_psd_from_gwname(last_gw_name,detector=\"H1\")\n```\n\nresult:\n<br/>\n<img src='https://raw.githubusercontent.com/reinanbr/gwaves/main/img/plot3.png'>\n",
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