Library for getting music in high quality from YouTube
Project description
installing:
pip3 install gwaves -U
importing
import gwaves as gw
geting the all data:
gw_data = gw.Gwaves_Data()
gw_data.data_gw
result:
(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:
last_gw_name = gw_data.data_gw['Name'][0]
last_gw = gw_data.get_gwave(last_gw_name)
last_gw
result:
{'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:
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:
plotting the more detector's from same signal:
the detector's used in the data:
gw_data.detectors
resut:
['L1', 'H1', 'V1']
getting the strain's
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:
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:
plotting the psd (Power Signal Density):
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:
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