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Added html link in notebook
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raphaelvallat committed Aug 14, 2019
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6 changes: 3 additions & 3 deletions notebooks/10_bandpower.ipynb
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" N3 => 3\n",
" R => 4\n",
" \n",
"However, you can also apply a custom mapping using the `mapping_dict=` argument of the `hypno_str_to_int function`."
"However, you can also apply a custom mapping using the `mapping_dict=` argument of the [hypno_str_to_int](https://htmlpreview.github.io/?https://raw.githubusercontent.com/raphaelvallat/yasa/master/html/hypno.html#yasa.hypno.hypno_str_to_int) function."
]
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{
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"source": [
"The last step is to upsample our hypnogram to the sampling frequency of the data. This step is *absolutely critical* and all YASA's function require that the data and hypnogram have the same sampling frequency and shape -- which makes life so much easier to mask and select specific sleep stages.\n",
"\n",
"Fortunately, YASA also provides a convenient function (`hypno_upsample_to_data`) to automatically upsample and fit the hypnogram to a given sampling frequency and data length.\n",
"Fortunately, YASA also provides a convenient function ([hypno_upsample_to_data](https://htmlpreview.github.io/?https://raw.githubusercontent.com/raphaelvallat/yasa/master/html/hypno.html#yasa.hypno.hypno_upsample_to_data)) to automatically upsample and fit the hypnogram to a given sampling frequency and data length.\n",
"This function requires the hypnogram and its sampling frequency, as well as the data and its sampling frequency. In our case, the sampling frequency of our hypnogram is 1 / 30 since there is one point per every 30 seconds of data. The sampling frequency of the data is 100 Hz.\n",
"\n",
"Note that if the upsampled hypnogram is shorter or longer than the length of data, a warning will be displayed and the hypnogram will be automatically padded or cropped to exactly match the length of data."
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"\n",
"Now that we have the PSD for each channel, we need to calculate the average power in specified bands. The power in a frequency band is defined by the area under the curve of the non-log-transformed PSD. For more details, please refer to https://raphaelvallat.com/bandpower.html.\n",
"\n",
"Here again, YASA provides a convenient function (`bandpower_from_psd`) to extract the average bandpower in specified bands from a pre-computed PSD."
"Here again, YASA provides a convenient function ([bandpower_from_psd](https://htmlpreview.github.io/?https://raw.githubusercontent.com/raphaelvallat/yasa/master/html/spectral.html#yasa.spectral.bandpower_from_psd)) to extract the average bandpower in specified bands from a pre-computed PSD."
]
},
{
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