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fixes PerformanceWarning in detect_non_wear_time_syed2021 #34

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merged 2 commits into from
Nov 11, 2024
Merged

fixes PerformanceWarning in detect_non_wear_time_syed2021 #34

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aaa97f4
fixes PerformanceWarning in detect_non_wear_time_syed2021
Trybnetic Nov 11, 2024
50f9c23
bumps version
Trybnetic Nov 11, 2024
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48 changes: 27 additions & 21 deletions paat/wear_time.py
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Original file line number Diff line number Diff line change
Expand Up @@ -245,7 +245,7 @@
return episodes.T

# create a new dataframe that will contain the grouped rows
grouped_episodes = pd.DataFrame()
grouped_episodes = []

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# get all current values from the first row
current_start = episodes.iloc[0]['start']
Expand Down Expand Up @@ -280,24 +280,28 @@
counter_label = f'{current_counter}-{next_counter}'

# save to new dataframe
grouped_episodes[counter_label] = pd.Series({'counter': counter_label,
'start_index': current_start_index,
'start': current_start,
'stop_index': current_stop_index,
'stop': current_stop,
'label': None if not training else current_label})
grouped_episodes += [pd.Series({

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'counter': counter_label,
'start_index': current_start_index,
'start': current_start,
'stop_index': current_stop_index,
'stop': current_stop,
'label': None if not training else current_label
})]
else:

# create the counter label
counter_label = current_counter if (next_counter - current_counter == 1) else f'{current_counter}-{next_counter - 1}'

# save to new dataframe
grouped_episodes[counter_label] = pd.Series({'counter': counter_label,
'start_index': current_start_index,
'start': current_start,
'stop_index': current_stop_index,
'stop': current_stop,
'label': None if not training else current_label})
grouped_episodes += [pd.Series({

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'counter': counter_label,
'start_index': current_start_index,
'start': current_start,
'stop_index': current_stop_index,
'stop': current_stop,
'label': None if not training else current_label
})]

# update tracker variables
current_start = next_start
Expand All @@ -311,14 +315,16 @@
if next_counter == episodes.iloc[-1]['counter']:

# save to new dataframe
grouped_episodes[next_counter] = pd.Series({'counter': next_counter,
'start_index': current_start_index,
'start': current_start,
'stop_index': current_stop_index,
'stop': current_stop,
'label': None if not training else current_label})

return grouped_episodes
grouped_episodes += [pd.Series({

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'counter': next_counter,
'start_index': current_start_index,
'start': current_start,
'stop_index': current_stop_index,
'stop': current_stop,
'label': None if not training else current_label
})]

return pd.concat(grouped_episodes, axis=1)

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def detect_non_wear_time_syed2021(data, sample_freq, cnn_model_file=None, std_threshold=0.004, distance_in_min=5, episode_window_sec=7, edge_true_or_false=True,
Expand Down
2 changes: 1 addition & 1 deletion pyproject.toml
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Original file line number Diff line number Diff line change
@@ -1,6 +1,6 @@
[tool.poetry]
name = "paat"
version = "1.0.0b6"
version = "1.0.0b7"
description = "A comprehensive toolbox to analyse and model raw physical activity data"

license = "MIT"
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