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BT 1 0 0 1 0 2 Tm 12 TL /F5 10 Tf 0 0 0 rg (OKBLUE) Tj /F6 10 Tf ( = '\\x1b[94m') Tj T* ET
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BT 1 0 0 1 0 2 Tm 12 TL /F5 10 Tf 0 0 0 rg (OKCYAN) Tj /F6 10 Tf ( = '\\x1b[96m') Tj T* ET
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BT 1 0 0 1 0 2 Tm 12 TL /F4 10 Tf 0 0 0 rg (moseq2_app.util.) Tj /F5 10 Tf (index_to_dataframe) Tj /F1 10 Tf ( \() Tj (index_path) Tj (\)) Tj T* ET
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BT 1 0 0 1 0 14 Tm .634066 Tw 12 TL /F2 10 Tf 0 0 0 rg (index_data \(dict\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (Dict object containing all parsed index file contents) Tj /F1 10 Tf (\) ) Tj /F2 10 Tf (df \(pd.DataFrame\)) Tj /F1 10 Tf  T* 0 Tw (\() Tj /F6 10 Tf (Formatted dict in DataFrame form including each session\222s metadata) Tj /F1 10 Tf (\)) Tj T* ET
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BT /F1 10 Tf 12 TL ET
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BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (sorted_index \(dict\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (Sorted dict of modeled sessions) Tj /F1 10 Tf (\)) Tj T* ET
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Q
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BT /F1 10 Tf 12 TL ET
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BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (model_fit \(dict\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (Trained ARHMM results dict) Tj /F1 10 Tf (\)) Tj T* ET
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BT /F1 10 Tf 12 TL ET
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0 0 0 rg
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BT 1 0 0 1 0 14 Tm 2.586472 Tw 12 TL /F2 10 Tf 0 0 0 rg (df \(pd.DataFrame\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (Dataframe containing all of the mean syllable statistics) Tj /F1 10 Tf (\) ) Tj /F2 10 Tf (scalar_df) Tj T* 0 Tw (\(pd.DataFrame\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (Dataframe containing the frame-by-frame scalar and label data) Tj /F1 10 Tf (\)) Tj T* ET
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BT 1 0 0 1 0 2.2 Tm 13.2 TL /F3 11 Tf .12549 .262745 .360784 rg (Flip - Controller Module) Tj T* ET
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BT 1 0 0 1 0 2 Tm 12 TL /F1 10 Tf 0 0 0 rg (Bases: ) Tj /F5 10 Tf (moseq2_app.flip.widgets.FlipClassifierWidgets) Tj T* ET
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Q
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0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL (Augments the selected correct dataset with 3 rotated versions of the truth values:) Tj T* ET
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Q
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0 0 0 rg
BT /F1 10 Tf 12 TL ET
BT 1 0 0 1 0 44 Tm  T* ET
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1 0 0 1 20 30 cm
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BT 1 0 0 1 0 14 Tm 1.822205 Tw 12 TL /F1 10 Tf 0 0 0 rg (1. xflip -) Tj (> incorrect case; 2. yflip -) Tj (> correct case; 3. xyflip -) Tj (> incorrect case; and creates the X and Y) Tj T* 0 Tw (train/test sets.) Tj T* ET
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Q
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0 0 0 rg
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0 0 0 rg
BT 1 0 0 1 0 14 Tm /F1 10 Tf 12 TL .465227 Tw (The first half of X contains the incorrect cases \(1\), and the second half contains the correct cases \(0\).) Tj T* 0 Tw (Equivalently, the first half of the y variable is composed of 1s, and the latter half is composed of 0s.) Tj T* ET
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BT 1 0 0 1 0 2 Tm 12 TL /F5 10 Tf 0 0 0 rg (changed_selected_session) Tj /F2 10 Tf ( \() Tj /F1 10 Tf (event) Tj /F2 10 Tf (\)) Tj T* ET
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Q
q
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BT 1 0 0 1 0 2 Tm 12 TL /F1 10 Tf 0 0 0 rg (Callback function to load newly selected session.) Tj T* ET
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Q
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1 0 0 1 60.01575 464.4394 cm
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1 0 0 1 60.01575 449.4394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
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1 0 0 1 6 3 cm
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0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 15.23937 0 Td (Args:) Tj T* -15.23937 0 Td ET
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BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (event \(ipywidgets Event\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (self.session_select_dropdown.value is changed) Tj /F1 10 Tf (\)) Tj T* ET
Q
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q
1 0 0 1 50.01575 443.4394 cm
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q
1 0 0 1 50.01575 425.4394 cm
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BT 1 0 0 1 0 2 Tm 12 TL /F5 10 Tf 0 0 0 rg (clear_on_click) Tj /F2 10 Tf ( \() Tj /F1 10 Tf (b) Tj /F2 10 Tf (\)) Tj T* ET
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Q
q
1 0 0 1 60.01575 413.4394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F1 10 Tf 0 0 0 rg (Clears the output.) Tj T* ET
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Q
q
1 0 0 1 60.01575 407.4394 cm
Q
q
1 0 0 1 60.01575 392.4394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
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1 0 0 1 6 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 15.23937 0 Td (Args:) Tj T* -15.23937 0 Td ET
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Q
q
1 0 0 1 91.03937 3 cm
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0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL (b \(button click\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 50.01575 386.4394 cm
Q
q
1 0 0 1 50.01575 368.4394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F5 10 Tf 0 0 0 rg (curr_frame_update) Tj /F2 10 Tf ( \() Tj /F1 10 Tf (event) Tj /F2 10 Tf (\)) Tj T* ET
Q
Q
q
1 0 0 1 60.01575 356.4394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F1 10 Tf 0 0 0 rg (Updates the currently displayed frame when the slider is moved.) Tj T* ET
Q
Q
q
1 0 0 1 60.01575 350.4394 cm
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q
1 0 0 1 60.01575 335.4394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
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1 0 0 1 6 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 15.23937 0 Td (Args:) Tj T* -15.23937 0 Td ET
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Q
q
1 0 0 1 91.03937 3 cm
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BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (event \(ipywidgets Event\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (self.frame_num_slider.value is changed.) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 50.01575 329.4394 cm
Q
q
1 0 0 1 50.01575 311.4394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F5 10 Tf 0 0 0 rg (get_corrected_data) Tj /F2 10 Tf ( \(\)) Tj T* ET
Q
Q
q
1 0 0 1 60.01575 295.4394 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL (Apply the selected flip orientation ranges to the entire dataset to correct the) Tj T* ET
Q
Q
q
1 0 0 1 60.01575 280.4394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
BT 1 0 0 1 0 2 Tm  T* ET
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1 0 0 1 20 0 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F1 10 Tf 0 0 0 rg (incorrectly oriented frames.) Tj T* ET
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Q
q
Q
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q
1 0 0 1 50.01575 274.4394 cm
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q
1 0 0 1 50.01575 256.4394 cm
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BT 1 0 0 1 0 2 Tm 12 TL /F5 10 Tf 0 0 0 rg (interactive_launch_frame_selector) Tj /F2 10 Tf ( \(\)) Tj T* ET
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Q
q
1 0 0 1 60.01575 232.4394 cm
q
BT 1 0 0 1 0 14 Tm 1.537888 Tw 12 TL /F1 10 Tf 0 0 0 rg (Interactive tool that displays the frame to display with the selected data box. Users will use the start_range) Tj T* 0 Tw (button to add frame ranges to the range box list.) Tj T* ET
Q
Q
q
1 0 0 1 50.01575 226.4394 cm
Q
q
1 0 0 1 50.01575 208.4394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F5 10 Tf 0 0 0 rg (load_sessions) Tj /F2 10 Tf ( \(\)) Tj T* ET
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Q
q
1 0 0 1 60.01575 192.4394 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL (Recursively searches for completed h5 extraction files, and loads total_frames=max_frames to) Tj T* ET
Q
Q
q
1 0 0 1 60.01575 177.4394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
BT 1 0 0 1 0 2 Tm  T* ET
q
1 0 0 1 20 0 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F1 10 Tf 0 0 0 rg (include in the total dataset. Additionally applies some image filtering prior to returning the data.) Tj T* ET
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q
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q
1 0 0 1 60.01575 171.4394 cm
Q
q
1 0 0 1 60.01575 144.4394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 15 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 31.92937 0 Td (Returns:) Tj T* -31.92937 0 Td ET
Q
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q
1 0 0 1 91.03937 3 cm
q
BT 1 0 0 1 0 14 Tm 1.562671 Tw 12 TL /F2 10 Tf 0 0 0 rg (data_dict \(dict\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (dict of) Tj /F1 10 Tf (\) ) Tj /F2 10 Tf (path_dict \(dict\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (dict of session names and paths filtered for) Tj T* 0 Tw (sessions missing an h5 or mp4 files.) Tj /F1 10 Tf (\)) Tj T* ET
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q
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q
1 0 0 1 50.01575 138.4394 cm
Q
q
1 0 0 1 50.01575 120.4394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F5 10 Tf 0 0 0 rg (plot_xy_examples) Tj /F2 10 Tf ( \() Tj /F1 10 Tf (data_xflip) Tj /F2 10 Tf (, ) Tj /F1 10 Tf (data_yflip) Tj /F2 10 Tf (, ) Tj /F1 10 Tf (data_xyflip) Tj /F2 10 Tf (, ) Tj /F1 10 Tf (selected_frame) Tj (=) Tj (0) Tj /F2 10 Tf (\)) Tj T* ET
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q
1 0 0 1 60.01575 104.4394 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL (Plots 2 columns of examples for the correct and incorrect examples being used to train) Tj T* ET
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Q
q
1 0 0 1 60.01575 77.43937 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
BT 1 0 0 1 0 14 Tm  T* ET
q
1 0 0 1 20 12 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F1 10 Tf 0 0 0 rg (the flip classifier.) Tj T* ET
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q
1 0 0 1 20 0 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL (Inputted 3D array shapes are all as follows: \(nframes x nrows x ncols\)) Tj T* ET
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q
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q
1 0 0 1 60.01575 71.43937 cm
Q
q
1 0 0 1 34.01575 807.2126 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL (Welcome to moseq2-app\222s documentation!) Tj T* ET
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1 0 0 1 34.01575 22.67717 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL (2) Tj T* ET
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endstream
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1 0 0 1 0 0 cm  BT /F1 12 Tf 14.4 TL ET
q
1 0 0 1 60.01575 694.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 81 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 15.23937 0 Td (Args:) Tj T* -15.23937 0 Td ET
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q
1 0 0 1 91.03937 87 cm
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q
1 0 0 1 91.03937 87 cm
Q
q
1 0 0 1 91.03937 63 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 9 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
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q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 14 Tm 1.722248 Tw 12 TL /F2 10 Tf 0 0 0 rg (data_xflip \(3D np.ndarray\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (Single frame of the corrected dataset flipped on the) Tj T* 0 Tw (x-axis \(class 1\)) Tj /F1 10 Tf (\)) Tj T* ET
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q
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q
1 0 0 1 91.03937 57 cm
Q
q
1 0 0 1 91.03937 33 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 9 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
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q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 14 Tm 1.722248 Tw 12 TL /F2 10 Tf 0 0 0 rg (data_yflip \(3D np.ndarray\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (Single frame of the corrected dataset flipped on the) Tj T* 0 Tw (x-axis \(class 0\)) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
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q
1 0 0 1 91.03937 27 cm
Q
q
1 0 0 1 91.03937 3 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 9 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
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q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 14 Tm .46706 Tw 12 TL /F2 10 Tf 0 0 0 rg (data_xyflip \(3D np.ndarray\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (Single frame of the corrected dataset flipped on the x) Tj T* 0 Tw (and y-axis \(class 1\)) Tj /F1 10 Tf (\)) Tj T* ET
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q
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1 0 0 1 91.03937 3 cm
Q
q
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q
1 0 0 1 50.01575 688.0394 cm
Q
q
1 0 0 1 50.01575 670.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F5 10 Tf 0 0 0 rg (prepare_datasets) Tj /F2 10 Tf ( \() Tj /F1 10 Tf (test_size) Tj /F2 10 Tf (, ) Tj /F1 10 Tf (random_state) Tj (=) Tj (0) Tj /F2 10 Tf (\)) Tj T* ET
Q
Q
q
1 0 0 1 60.01575 654.0394 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL (Correct data after the appropriate flip ranges have been selected, augment and create X,y training sets,) Tj T* ET
Q
Q
q
1 0 0 1 60.01575 639.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
BT 1 0 0 1 0 2 Tm  T* ET
q
1 0 0 1 20 0 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F1 10 Tf 0 0 0 rg (and split the data to training and testing splits.) Tj T* ET
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q
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q
1 0 0 1 60.01575 633.0394 cm
Q
q
1 0 0 1 60.01575 594.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 27 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 15.23937 0 Td (Args:) Tj T* -15.23937 0 Td ET
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Q
q
1 0 0 1 91.03937 33 cm
Q
q
1 0 0 1 91.03937 33 cm
Q
q
1 0 0 1 91.03937 21 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
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q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (test_size \(int\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (Test dataset percent split size) Tj /F1 10 Tf (\)) Tj T* ET
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q
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1 0 0 1 91.03937 15 cm
Q
q
1 0 0 1 91.03937 3 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (random_state \(int\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (Seed value to randomly sort the split data) Tj /F1 10 Tf (\)) Tj T* ET
Q
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q
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1 0 0 1 91.03937 3 cm
Q
q
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q
1 0 0 1 50.01575 588.0394 cm
Q
q
1 0 0 1 50.01575 570.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F5 10 Tf 0 0 0 rg (start_stop_frame_range) Tj /F2 10 Tf ( \() Tj /F1 10 Tf (b) Tj /F2 10 Tf (\)) Tj T* ET
Q
Q
q
1 0 0 1 60.01575 554.0394 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL (Callback function that triggers the \223Add Range\224 functionality.) Tj T* ET
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q
1 0 0 1 60.01575 527.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
BT 1 0 0 1 0 14 Tm  T* ET
q
1 0 0 1 20 0 cm
q
BT 1 0 0 1 0 14 Tm .469689 Tw 12 TL /F1 10 Tf 0 0 0 rg (If user clicks the button == \221Start Range\222, then the function will start including frames in the correct flip set.) Tj T* 0 Tw (Else, it will end the included range and truncate the slider range from the start index.) Tj T* ET
Q
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q
1 0 0 1 60.01575 521.0394 cm
Q
q
1 0 0 1 60.01575 506.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 15.23937 0 Td (Args:) Tj T* -15.23937 0 Td ET
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q
1 0 0 1 91.03937 3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (b \(button click\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (User clicks on \223Start or Stop\224 Range button.) Tj /F1 10 Tf (\)) Tj T* ET
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1 0 0 1 50.01575 500.0394 cm
Q
q
1 0 0 1 50.01575 470.0394 cm
q
BT 1 0 0 1 0 14 Tm 23.35102 Tw 12 TL /F5 10 Tf 0 0 0 rg (train_and_evaluate_model) Tj /F2 10 Tf ( \() Tj /F1 10 Tf (n_estimators) Tj (=) Tj (100) Tj /F2 10 Tf (, ) Tj /F1 10 Tf (criterion) Tj (=) Tj ('gini') Tj /F2 10 Tf (, ) Tj /F1 10 Tf (n_jobs) Tj (=) Tj (4) Tj /F2 10 Tf (, ) Tj /F1 10 Tf (max_depth) Tj (=) Tj (6) Tj /F2 10 Tf (,) Tj T* 0 Tw /F1 10 Tf (min_samples_split) Tj (=) Tj (2) Tj /F2 10 Tf (, ) Tj /F1 10 Tf (min_samples_leaf) Tj (=) Tj (1) Tj /F2 10 Tf (, ) Tj /F1 10 Tf (oob_score) Tj (=) Tj (False) Tj /F2 10 Tf (, ) Tj /F1 10 Tf (random_state) Tj (=) Tj (0) Tj /F2 10 Tf (, ) Tj /F1 10 Tf (verbose) Tj (=) Tj (0) Tj /F2 10 Tf (\)) Tj T* ET
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Q
q
1 0 0 1 60.01575 454.0394 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL (Trains the flip classifier the pre-augmented dataset given some optionally adjustable) Tj T* ET
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Q
q
1 0 0 1 60.01575 439.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
BT 1 0 0 1 0 2 Tm  T* ET
q
1 0 0 1 20 0 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F1 10 Tf 0 0 0 rg (model initialization parameters.) Tj T* ET
Q
Q
q
Q
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q
1 0 0 1 60.01575 433.0394 cm
Q
q
1 0 0 1 60.01575 220.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 201 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 15.23937 0 Td (Args:) Tj T* -15.23937 0 Td ET
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q
1 0 0 1 91.03937 207 cm
Q
q
1 0 0 1 91.03937 207 cm
Q
q
1 0 0 1 91.03937 195 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (n_estimators \(int\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (The number of trees in the forest.) Tj /F1 10 Tf (\)) Tj T* ET
Q
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q
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q
1 0 0 1 91.03937 189 cm
Q
q
1 0 0 1 91.03937 177 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
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q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (criterion \(str\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (The function to measure the quality of a split. [\221gini\222, mse\222, \221mae\222]) Tj /F1 10 Tf (\)) Tj T* ET
Q
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q
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q
1 0 0 1 91.03937 171 cm
Q
q
1 0 0 1 91.03937 159 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
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q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (n_jobs \(int\)) Tj /F1 10 Tf ( \(The number of jobs to run in parallel for both ) Tj /F6 10 Tf (fit) Tj /F1 10 Tf ( and ) Tj /F6 10 Tf (predict) Tj /F1 10 Tf (.\)) Tj T* ET
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q
1 0 0 1 91.03937 153 cm
Q
q
1 0 0 1 91.03937 129 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 9 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
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q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 14 Tm -0.082714 Tw 12 TL /F2 10 Tf 0 0 0 rg (max_depth \(int\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (The maximum depth of the tree. If None, then nodes are expanded) Tj T* 0 Tw (until) Tj /F1 10 Tf (\) \226 all leaves are pure. \(This will use a lot of memory, and may take a while.\)) Tj T* ET
Q
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q
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q
1 0 0 1 91.03937 123 cm
Q
q
1 0 0 1 91.03937 99 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 9 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
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q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 14 Tm 2.454472 Tw 12 TL /F2 10 Tf 0 0 0 rg (min_samples_split \(int\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (The minimum number of samples required to split an) Tj T* 0 Tw (internal node.) Tj /F1 10 Tf (\)) Tj T* ET
Q
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q
Q
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q
1 0 0 1 91.03937 93 cm
Q
q
1 0 0 1 91.03937 69 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 9 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 14 Tm .83956 Tw 12 TL /F2 10 Tf 0 0 0 rg (min_samples_leaf \(int\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (The minimum number of samples required to be at a leaf) Tj T* 0 Tw (node.) Tj /F1 10 Tf (\)) Tj T* ET
Q
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q
Q
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q
1 0 0 1 91.03937 63 cm
Q
q
1 0 0 1 91.03937 39 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 9 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 14 Tm 2.863157 Tw 12 TL /F2 10 Tf 0 0 0 rg (oob_score \(bool\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (whether to use out-of-bag samples to estimate the R^2 on) Tj T* 0 Tw (unseen data.) Tj /F1 10 Tf (\)) Tj T* ET
Q
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q
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q
1 0 0 1 91.03937 33 cm
Q
q
1 0 0 1 91.03937 21 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (random_state \(int\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (The seed used by the random number generator.) Tj /F1 10 Tf (\)) Tj T* ET
Q
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q
Q
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q
1 0 0 1 91.03937 15 cm
Q
q
1 0 0 1 91.03937 3 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (verbose \(int\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (Controls the verbosity when fitting and predicting.) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 91.03937 3 cm
Q
q
Q
Q
q
1 0 0 1 50.01575 214.0394 cm
Q
q
1 0 0 1 50.01575 196.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F5 10 Tf 0 0 0 rg (update_state_on_selected_range) Tj /F2 10 Tf ( \(\)) Tj T* ET
Q
Q
q
1 0 0 1 60.01575 180.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (Helper function that updates the view upon a correct frame range addition \(stop > start\).) Tj T* ET
Q
Q
q
1 0 0 1 60.01575 135.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
BT 1 0 0 1 0 32 Tm  T* ET
q
1 0 0 1 20 18 cm
q
BT 1 0 0 1 0 14 Tm .556711 Tw 12 TL /F1 10 Tf 0 0 0 rg (Callback function to update the table of selected frame ranges upon button click. Function will will add the) Tj T* 0 Tw (selected ranges to the table) Tj T* ET
Q
Q
q
1 0 0 1 20 12 cm
Q
q
1 0 0 1 20 0 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
BT 1 0 0 1 0 2 Tm  T* ET
q
1 0 0 1 20 0 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL (and session dict to train the model downstream.) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 20 0 cm
Q
q
Q
Q
q
1 0 0 1 40.01575 105.8394 cm
q
.8 .8 .8 RG
.3 w
.94902 .94902 .94902 rg
n -10 0 525.2441 19.2 re B*
Q
q
BT 1 0 0 1 0 2.2 Tm 13.2 TL /F3 11 Tf .12549 .262745 .360784 rg (Flip - Widgets Module) Tj T* ET
Q
Q
q
1 0 0 1 40.01575 87.83937 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F1 10 Tf 0 0 0 rg (Widgets module containing all the interactive components of the frame selection GUI.) Tj T* ET
Q
Q
q
1 0 0 1 40.01575 81.83937 cm
Q
q
1 0 0 1 40.01575 63.83937 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F6 10 Tf 0 0 0 rg (class ) Tj /F4 10 Tf (moseq2_app.flip.widgets.) Tj /F5 10 Tf (FlipClassifierWidgets) Tj /F1 10 Tf ( \() Tj (continuous_update) Tj (\)) Tj T* ET
Q
Q
q
1 0 0 1 34.01575 807.2126 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL (Welcome to moseq2-app\222s documentation!) Tj T* ET
Q
Q
q
1 0 0 1 34.01575 22.67717 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL (3) Tj T* ET
Q
Q
 
endstream
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<<
/Length 7475
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1 0 0 1 0 0 cm  BT /F1 12 Tf 14.4 TL ET
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1 0 0 1 50.01575 775.0394 cm
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BT 1 0 0 1 0 2 Tm 12 TL /F1 10 Tf 0 0 0 rg (Bases: ) Tj /F5 10 Tf (object) Tj T* ET
Q
Q
q
1 0 0 1 40.01575 745.8394 cm
q
.8 .8 .8 RG
.3 w
.94902 .94902 .94902 rg
n -10 0 525.2441 19.2 re B*
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q
BT 1 0 0 1 0 2.2 Tm 13.2 TL /F3 11 Tf .12549 .262745 .360784 rg (Module contents) Tj T* ET
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Q
q
1 0 0 1 40.01575 715.4394 cm
q
.8 .8 .8 RG
.3 w
.94902 .94902 .94902 rg
n -10 0 525.2441 20.4 re B*
Q
q
BT 1 0 0 1 0 2.4 Tm 14.4 TL /F3 12 Tf .12549 .262745 .360784 rg (moseq2_app.roi package) Tj T* ET
Q
Q
q
1 0 0 1 40.01575 686.2394 cm
q
.8 .8 .8 RG
.3 w
.94902 .94902 .94902 rg
n -10 0 525.2441 19.2 re B*
Q
q
.12549 .262745 .360784 rg
BT 1 0 0 1 0 2.2 Tm /F3 11 Tf 13.2 TL (Submodules) Tj T* ET
Q
Q
q
1 0 0 1 40.01575 657.0394 cm
q
.8 .8 .8 RG
.3 w
.94902 .94902 .94902 rg
n -10 0 525.2441 19.2 re B*
Q
q
BT 1 0 0 1 0 2.2 Tm 13.2 TL /F3 11 Tf .12549 .262745 .360784 rg (ROI - Controller Module) Tj T* ET
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Q
q
1 0 0 1 40.01575 627.0394 cm
q
BT 1 0 0 1 0 14 Tm .201007 Tw 12 TL /F1 10 Tf 0 0 0 rg (Interactive ROI detection and extraction preview functionalities. This module utilizes the widgets from the widgets.py) Tj T* 0 Tw (file to facilitate the real-time interaction.) Tj T* ET
Q
Q
q
1 0 0 1 40.01575 621.0394 cm
Q
q
1 0 0 1 40.01575 603.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F6 10 Tf 0 0 0 rg (class ) Tj /F4 10 Tf (moseq2_app.roi.controller.) Tj /F5 10 Tf (InteractiveExtractionViewer) Tj /F1 10 Tf ( \() Tj (data_path) Tj (\)) Tj T* ET
Q
Q
q
1 0 0 1 50.01575 591.0394 cm
q
.933333 1 .8 rg
n 33.35 0 36 12 re f*
BT 1 0 0 1 0 2 Tm 12 TL /F1 10 Tf 0 0 0 rg (Bases: ) Tj /F5 10 Tf (object) Tj T* ET
Q
Q
q
1 0 0 1 50.01575 585.0394 cm
Q
q
1 0 0 1 50.01575 567.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F5 10 Tf 0 0 0 rg (clear_on_click) Tj /F2 10 Tf ( \() Tj /F1 10 Tf (b) Tj /F2 10 Tf (\)) Tj T* ET
Q
Q
q
1 0 0 1 60.01575 555.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F1 10 Tf 0 0 0 rg (Clears the cell output) Tj T* ET
Q
Q
q
1 0 0 1 60.01575 549.0394 cm
Q
q
1 0 0 1 60.01575 534.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 15.23937 0 Td (Args:) Tj T* -15.23937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL (b \(button click\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 50.01575 528.0394 cm
Q
q
1 0 0 1 50.01575 510.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F5 10 Tf 0 0 0 rg (get_extraction) Tj /F2 10 Tf ( \() Tj /F1 10 Tf (input_file) Tj /F2 10 Tf (\)) Tj T* ET
Q
Q
q
1 0 0 1 60.01575 498.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F1 10 Tf 0 0 0 rg (Returns a div containing a video object to display.) Tj T* ET
Q
Q
q
1 0 0 1 60.01575 492.0394 cm
Q
q
1 0 0 1 60.01575 477.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 15.23937 0 Td (Args:) Tj T* -15.23937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (input_file \(str\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (Path to session extraction video to view.) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 40.01575 471.0394 cm
Q
q
1 0 0 1 40.01575 441.0394 cm
q
BT 1 0 0 1 0 14 Tm 12.50852 Tw 12 TL /F6 10 Tf 0 0 0 rg (class ) Tj /F4 10 Tf (moseq2_app.roi.controller.) Tj /F5 10 Tf (InteractiveFindRoi) Tj /F1 10 Tf ( \() Tj (data_path) Tj (, config_file) Tj (, session_config) Tj (,) Tj T* 0 Tw (compute_bgs) Tj (=) Tj (True) Tj (, autodetect_depths) Tj (=) Tj (False) Tj (\)) Tj T* ET
Q
Q
q
1 0 0 1 50.01575 429.0394 cm
q
.933333 1 .8 rg
n 33.35 0 264 12 re f*
BT 1 0 0 1 0 2 Tm 12 TL /F1 10 Tf 0 0 0 rg (Bases: ) Tj /F5 10 Tf (moseq2_app.roi.widgets.InteractiveROIWidgets) Tj T* ET
Q
Q
q
1 0 0 1 50.01575 423.0394 cm
Q
q
1 0 0 1 50.01575 405.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F5 10 Tf 0 0 0 rg (check_all_sessions) Tj /F2 10 Tf ( \() Tj /F1 10 Tf (b) Tj /F2 10 Tf (\)) Tj T* ET
Q
Q
q
1 0 0 1 60.01575 369.0394 cm
q
BT 1 0 0 1 0 26 Tm 2.051506 Tw 12 TL /F1 10 Tf 0 0 0 rg (Callback function to run the ROI area comparison test on all the existing sessions. Saving their individual) Tj T* 0 Tw .445606 Tw (session parameter sets in the session_parameters dict in the process. Additionally updates the button styles to) Tj T* 0 Tw (reflect the outcome.) Tj T* ET
Q
Q
q
1 0 0 1 60.01575 363.0394 cm
Q
q
1 0 0 1 60.01575 348.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 15.23937 0 Td (Args:) Tj T* -15.23937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (b \(button event\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (User click) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 50.01575 342.0394 cm
Q
q
1 0 0 1 50.01575 324.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F5 10 Tf 0 0 0 rg (clear_on_click) Tj /F2 10 Tf ( \() Tj /F1 10 Tf (b) Tj /F2 10 Tf (\)) Tj T* ET
Q
Q
q
1 0 0 1 60.01575 312.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F1 10 Tf 0 0 0 rg (Clears the cell output) Tj T* ET
Q
Q
q
1 0 0 1 60.01575 306.0394 cm
Q
q
1 0 0 1 60.01575 291.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 15.23937 0 Td (Args:) Tj T* -15.23937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (b \(button click\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (User clicks Clear Button.) Tj /F1 10 Tf (\)) Tj T* ET
Q
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q
Q
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q
1 0 0 1 50.01575 285.0394 cm
Q
q
1 0 0 1 50.01575 267.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F5 10 Tf 0 0 0 rg (compute_all_bgs) Tj /F2 10 Tf ( \(\)) Tj T* ET
Q
Q
q
1 0 0 1 60.01575 255.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F1 10 Tf 0 0 0 rg (Computes all the background images before displaying the app to speed up user interaction.) Tj T* ET
Q
Q
q
1 0 0 1 50.01575 249.0394 cm
Q
q
1 0 0 1 50.01575 231.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F5 10 Tf 0 0 0 rg (extract_button_clicked) Tj /F2 10 Tf ( \() Tj /F1 10 Tf (b) Tj /F2 10 Tf (\)) Tj T* ET
Q
Q
q
1 0 0 1 60.01575 215.0394 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL (Updates the true depth autodetection parameter) Tj T* ET
Q
Q
q
1 0 0 1 60.01575 200.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
BT 1 0 0 1 0 2 Tm  T* ET
q
1 0 0 1 20 0 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F1 10 Tf 0 0 0 rg (such that the true depth is autodetected for each found session) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 60.01575 194.0394 cm
Q
q
1 0 0 1 60.01575 179.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 15.23937 0 Td (Args:) Tj T* -15.23937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (b \(ipywidgets Button\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (Button click event.) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 50.01575 173.0394 cm
Q
q
1 0 0 1 50.01575 155.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F5 10 Tf 0 0 0 rg (get_extraction) Tj /F2 10 Tf ( \() Tj /F1 10 Tf (input_file) Tj /F2 10 Tf (, ) Tj /F1 10 Tf (bground_im) Tj /F2 10 Tf (, ) Tj /F1 10 Tf (roi) Tj /F2 10 Tf (\)) Tj T* ET
Q
Q
q
1 0 0 1 60.01575 131.0394 cm
q
BT 1 0 0 1 0 14 Tm 1.89294 Tw 12 TL /F1 10 Tf 0 0 0 rg (Extracts selected frame range \(with the currently set session parameters\) and displays the extraction as a) Tj T* 0 Tw (Bokeh HTML-embedded div.) Tj T* ET
Q
Q
q
1 0 0 1 60.01575 125.0394 cm
Q
q
1 0 0 1 34.01575 807.2126 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL (Welcome to moseq2-app\222s documentation!) Tj T* ET
Q
Q
q
1 0 0 1 34.01575 22.67717 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL (4) Tj T* ET
Q
Q
 
endstream
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1 0 0 1 0 0 cm  BT /F1 12 Tf 14.4 TL ET
q
1 0 0 1 60.01575 712.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 63 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 15.23937 0 Td (Args:) Tj T* -15.23937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 69 cm
Q
q
1 0 0 1 91.03937 69 cm
Q
q
1 0 0 1 91.03937 57 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (input_file \(str\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (Path to session to extract) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 91.03937 51 cm
Q
q
1 0 0 1 91.03937 39 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (config_data \(dict\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (Extraction configuration parameters.) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 91.03937 33 cm
Q
q
1 0 0 1 91.03937 21 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (bground_im \(2D np.array\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (Computed session background.) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 91.03937 15 cm
Q
q
1 0 0 1 91.03937 3 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (roi \(2D np.array\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (Computed Region of interest array to mask bground_im with.) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 91.03937 3 cm
Q
q
Q
Q
q
1 0 0 1 50.01575 706.0394 cm
Q
q
1 0 0 1 50.01575 688.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F5 10 Tf 0 0 0 rg (get_pixels_per_metric) Tj /F2 10 Tf ( \() Tj /F1 10 Tf (pixel_width) Tj /F2 10 Tf (\)) Tj T* ET
Q
Q
q
1 0 0 1 60.01575 672.0394 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL (Helper function that computes a pixels_per_metric value, and handles) Tj T* ET
Q
Q
q
1 0 0 1 60.01575 657.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
BT 1 0 0 1 0 2 Tm  T* ET
q
1 0 0 1 20 0 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F1 10 Tf 0 0 0 rg (cases without user input.) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 60.01575 651.0394 cm
Q
q
1 0 0 1 60.01575 636.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 15.23937 0 Td (Args:) Tj T* -15.23937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (pixel_width \(int\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (width of the ROI bounding box in pixels) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 60.01575 621.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 31.92937 0 Td (Returns:) Tj T* -31.92937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL (pixels_per_inch \(float\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 60.01575 606.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 14.14937 0 Td (Return type:) Tj T* -14.14937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL (Computed ratio of real life) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 50.01575 600.0394 cm
Q
q
1 0 0 1 50.01575 582.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F5 10 Tf 0 0 0 rg (get_roi_and_depths) Tj /F2 10 Tf ( \() Tj /F1 10 Tf (bground_im) Tj /F2 10 Tf (, ) Tj /F1 10 Tf (session) Tj /F2 10 Tf (\)) Tj T* ET
Q
Q
q
1 0 0 1 60.01575 558.0394 cm
q
BT 1 0 0 1 0 14 Tm -0.058732 Tw 12 TL /F1 10 Tf 0 0 0 rg (Performs bucket centroid estimation to find the coordinates to use as the true depth value. The true depth will be) Tj T* 0 Tw (used to estimate the background depth_range, then it will update the widget values in real time.) Tj T* ET
Q
Q
q
1 0 0 1 60.01575 552.0394 cm
Q
q
1 0 0 1 60.01575 495.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 45 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 15.23937 0 Td (Args:) Tj T* -15.23937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 51 cm
Q
q
1 0 0 1 91.03937 51 cm
Q
q
1 0 0 1 91.03937 39 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (bground_im \(2D np.array\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (Computed session background) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 91.03937 33 cm
Q
q
1 0 0 1 91.03937 21 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (session \(str\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (path to currently processed session) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 91.03937 15 cm
Q
q
1 0 0 1 91.03937 3 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (config_data \(dict\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (Extraction configuration parameters) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 91.03937 3 cm
Q
q
Q
Q
q
1 0 0 1 60.01575 480.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 31.92937 0 Td (Returns:) Tj T* -31.92937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL (results \(dict\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 60.01575 465.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 14.14937 0 Td (Return type:) Tj T* -14.14937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL (dict that contains computed information. E.g. its ROI, and if it was flagged.) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 50.01575 459.0394 cm
Q
q
1 0 0 1 50.01575 441.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F5 10 Tf 0 0 0 rg (get_selected_session) Tj /F2 10 Tf ( \() Tj /F1 10 Tf (event) Tj /F2 10 Tf (\)) Tj T* ET
Q
Q
q
1 0 0 1 60.01575 425.0394 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL (Updates the selected value in checked_list, triggering the view to update with the currently) Tj T* ET
Q
Q
q
1 0 0 1 60.01575 410.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
BT 1 0 0 1 0 2 Tm  T* ET
q
1 0 0 1 20 0 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F1 10 Tf 0 0 0 rg (selected session\222s data.) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 60.01575 404.0394 cm
Q
q
1 0 0 1 60.01575 389.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 15.23937 0 Td (Args:) Tj T* -15.23937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (event \(ipywidgets event\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (Current value of checked_list has changed) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 50.01575 383.0394 cm
Q
q
1 0 0 1 50.01575 365.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F5 10 Tf 0 0 0 rg (interactive_depth_finder) Tj /F2 10 Tf ( \() Tj /F1 10 Tf (minmax_heights) Tj /F2 10 Tf (, ) Tj /F1 10 Tf (fn) Tj /F2 10 Tf (, ) Tj /F1 10 Tf (dr) Tj /F2 10 Tf (, ) Tj /F1 10 Tf (di) Tj /F2 10 Tf (\)) Tj T* ET
Q
Q
q
1 0 0 1 60.01575 329.0394 cm
q
BT 1 0 0 1 0 26 Tm 1.22294 Tw 12 TL /F1 10 Tf 0 0 0 rg (Interactive helper function that updates that views whenever the depth range or dilation iterations sliders are) Tj T* 0 Tw 1.113381 Tw (changed. At initial launch, it will auto-detect the depth estimation, then it will preserve the parameters across) Tj T* 0 Tw (session changes.) Tj T* ET
Q
Q
q
1 0 0 1 60.01575 323.0394 cm
Q
q
1 0 0 1 60.01575 230.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 81 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 15.23937 0 Td (Args:) Tj T* -15.23937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 87 cm
Q
q
1 0 0 1 91.03937 87 cm
Q
q
1 0 0 1 91.03937 75 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (session \(str or ipywidget DropDownMenu\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (path to input file) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 91.03937 69 cm
Q
q
1 0 0 1 91.03937 57 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (bground_im \(2D np.array\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (Computed session background) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 91.03937 51 cm
Q
q
1 0 0 1 91.03937 39 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (config_data \(dict\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (Extraction configuration parameters) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 91.03937 33 cm
Q
q
1 0 0 1 91.03937 21 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (dr \(tuple or ipywidget IntRangeSlider\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (Depth range to capture) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 91.03937 15 cm
Q
q
1 0 0 1 91.03937 3 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (di \(int or ipywidget IntSlider\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (Dilation iterations) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 91.03937 3 cm
Q
q
Q
Q
q
1 0 0 1 50.01575 224.0394 cm
Q
q
1 0 0 1 50.01575 206.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F5 10 Tf 0 0 0 rg (interactive_find_roi_session_selector) Tj /F2 10 Tf ( \() Tj /F1 10 Tf (session) Tj /F2 10 Tf (\)) Tj T* ET
Q
Q
q
1 0 0 1 60.01575 194.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F1 10 Tf 0 0 0 rg (First function that is called to find the current selected session\222s background and display the widget interface.) Tj T* ET
Q
Q
q
1 0 0 1 60.01575 188.0394 cm
Q
q
1 0 0 1 60.01575 149.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 27 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 15.23937 0 Td (Args:) Tj T* -15.23937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 33 cm
Q
q
1 0 0 1 91.03937 33 cm
Q
q
1 0 0 1 91.03937 21 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (session \(str or ipywidget DropDownMenu\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (path to chosen session.) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 91.03937 15 cm
Q
q
1 0 0 1 91.03937 3 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (config_data \(dict\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (ROI/Extraction configuration parameters) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 91.03937 3 cm
Q
q
Q
Q
q
1 0 0 1 50.01575 143.0394 cm
Q
q
1 0 0 1 50.01575 125.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F5 10 Tf 0 0 0 rg (mark_passing_button_clicked) Tj /F2 10 Tf ( \() Tj /F1 10 Tf (b) Tj /F2 10 Tf (\)) Tj T* ET
Q
Q
q
1 0 0 1 60.01575 101.0394 cm
q
BT 1 0 0 1 0 14 Tm 2.851506 Tw 12 TL /F1 10 Tf 0 0 0 rg (Callback function that sets the current session as Passing. The indicator will still remain Flagged if the) Tj T* 0 Tw (segmented frame or the crop-rotated frame are not appearing.) Tj T* ET
Q
Q
q
1 0 0 1 60.01575 95.03937 cm
Q
q
1 0 0 1 60.01575 80.03937 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 15.23937 0 Td (Args:) Tj T* -15.23937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (b \(ipywidgets event\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (Button click) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 50.01575 74.03937 cm
Q
q
1 0 0 1 50.01575 56.03937 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F5 10 Tf 0 0 0 rg (prepare_data_to_plot) Tj /F2 10 Tf ( \() Tj /F1 10 Tf (roi) Tj /F2 10 Tf (, ) Tj /F1 10 Tf (minmax_heights) Tj /F2 10 Tf (, ) Tj /F1 10 Tf (fn) Tj /F2 10 Tf (\)) Tj T* ET
Q
Q
q
1 0 0 1 34.01575 807.2126 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL (Welcome to moseq2-app\222s documentation!) Tj T* ET
Q
Q
q
1 0 0 1 34.01575 22.67717 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL (5) Tj T* ET
Q
Q
 
endstream
endobj
527 0 obj
<<
/Length 10924
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stream
1 0 0 1 0 0 cm  BT /F1 12 Tf 14.4 TL ET
q
1 0 0 1 60.01575 775.0394 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL (Helper function that generates the display plots with the currently selected parameters,) Tj T* ET
Q
Q
q
1 0 0 1 60.01575 748.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
BT 1 0 0 1 0 14 Tm  T* ET
q
1 0 0 1 20 0 cm
q
BT 1 0 0 1 0 14 Tm .632273 Tw 12 TL /F1 10 Tf 0 0 0 rg (and checks if the min-max height parameters are acceptable, updating the success indicator if any issues) Tj T* 0 Tw (arise.) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 60.01575 742.0394 cm
Q
q
1 0 0 1 60.01575 637.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 93 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 15.23937 0 Td (Args:) Tj T* -15.23937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 99 cm
Q
q
1 0 0 1 91.03937 99 cm
Q
q
1 0 0 1 91.03937 87 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (input_file \(str\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (Path to currently processed depth file) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 91.03937 81 cm
Q
q
1 0 0 1 91.03937 69 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (bground_im \(2D np.ndarray\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (Median depth image of the read video.) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 91.03937 63 cm
Q
q
1 0 0 1 91.03937 51 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (roi \(2D Boolean np.ndarray\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (Computed ROI representing the bucket floor) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 91.03937 45 cm
Q
q
1 0 0 1 91.03937 21 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 9 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 14 Tm 5.011636 Tw 12 TL /F2 10 Tf 0 0 0 rg (minmax_heights \(2-tuple\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (Min and max mouse heights to threshold from) Tj T* 0 Tw (background subtracted image.) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 91.03937 15 cm
Q
q
1 0 0 1 91.03937 3 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (fn \(int\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (Frame index to display.) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 91.03937 3 cm
Q
q
Q
Q
q
1 0 0 1 50.01575 631.0394 cm
Q
q
1 0 0 1 50.01575 613.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F5 10 Tf 0 0 0 rg (save_clicked) Tj /F2 10 Tf ( \() Tj /F1 10 Tf (b) Tj /F2 10 Tf (\)) Tj T* ET
Q
Q
q
1 0 0 1 60.01575 589.0394 cm
q
BT 1 0 0 1 0 14 Tm .426711 Tw 12 TL /F1 10 Tf 0 0 0 rg (Callback function to save the current session_parameters dict into the file of their choice \(given in the top-most) Tj T* 0 Tw (wrapper function\).) Tj T* ET
Q
Q
q
1 0 0 1 60.01575 583.0394 cm
Q
q
1 0 0 1 60.01575 568.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 15.23937 0 Td (Args:) Tj T* -15.23937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (b \(button event\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (User click) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 50.01575 562.0394 cm
Q
q
1 0 0 1 50.01575 544.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F5 10 Tf 0 0 0 rg (test_all_sessions) Tj /F2 10 Tf ( \() Tj /F1 10 Tf (session_dict) Tj /F2 10 Tf (\)) Tj T* ET
Q
Q
q
1 0 0 1 60.01575 532.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F1 10 Tf 0 0 0 rg (Helper function to test the current configurable UI values on all the sessions that were found.) Tj T* ET
Q
Q
q
1 0 0 1 60.01575 526.0394 cm
Q
q
1 0 0 1 60.01575 475.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 39 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 15.23937 0 Td (Args:) Tj T* -15.23937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 45 cm
Q
q
1 0 0 1 91.03937 45 cm
Q
q
1 0 0 1 91.03937 21 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 9 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 14 Tm 3.008472 Tw 12 TL /F2 10 Tf 0 0 0 rg (session_dict \(dict\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (dict of session directory names paired with their absolute) Tj T* 0 Tw (paths.) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 91.03937 15 cm
Q
q
1 0 0 1 91.03937 3 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (config_data \(dict\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (ROI/Extraction configuration parameters.) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 91.03937 3 cm
Q
q
Q
Q
q
1 0 0 1 60.01575 448.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 15 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 31.92937 0 Td (Returns:) Tj T* -31.92937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 3 cm
q
BT 1 0 0 1 0 14 Tm 1.566766 Tw 12 TL /F2 10 Tf 0 0 0 rg (all_results \(dict\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (dict of session names and values used to indicate if a session was) Tj T* 0 Tw (flagged,) Tj /F1 10 Tf (\) ) Tj /F6 10 Tf (with their computed ROI for convenience.) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 50.01575 442.0394 cm
Q
q
1 0 0 1 50.01575 424.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F5 10 Tf 0 0 0 rg (update_checked_list) Tj /F2 10 Tf ( \() Tj /F1 10 Tf (results) Tj /F2 10 Tf (\)) Tj T* ET
Q
Q
q
1 0 0 1 60.01575 412.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F1 10 Tf 0 0 0 rg (Helper function to update the session selector passing indicators when a parameter test is run.) Tj T* ET
Q
Q
q
1 0 0 1 60.01575 406.0394 cm
Q
q
1 0 0 1 60.01575 391.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 15.23937 0 Td (Args:) Tj T* -15.23937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (results \(dict\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (ROI detection results dict containing the flag and return code to display.) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 50.01575 385.0394 cm
Q
q
1 0 0 1 50.01575 367.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F5 10 Tf 0 0 0 rg (update_config_di) Tj /F2 10 Tf ( \() Tj /F1 10 Tf (event) Tj /F2 10 Tf (\)) Tj T* ET
Q
Q
q
1 0 0 1 60.01575 355.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F1 10 Tf 0 0 0 rg (Callback function to update config dict with current UI dilation iterations) Tj T* ET
Q
Q
q
1 0 0 1 60.01575 349.0394 cm
Q
q
1 0 0 1 60.01575 334.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 15.23937 0 Td (Args:) Tj T* -15.23937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (event \(ipywidget callback\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (Any user interaction.) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 50.01575 328.0394 cm
Q
q
1 0 0 1 50.01575 310.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F5 10 Tf 0 0 0 rg (update_config_dr) Tj /F2 10 Tf ( \() Tj /F1 10 Tf (event) Tj /F2 10 Tf (\)) Tj T* ET
Q
Q
q
1 0 0 1 60.01575 298.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F1 10 Tf 0 0 0 rg (Callback function to update config dict with current UI depth range values) Tj T* ET
Q
Q
q
1 0 0 1 60.01575 292.0394 cm
Q
q
1 0 0 1 60.01575 277.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 15.23937 0 Td (Args:) Tj T* -15.23937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (event \(ipywidget callback\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (Any user interaction.) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 50.01575 271.0394 cm
Q
q
1 0 0 1 50.01575 253.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F5 10 Tf 0 0 0 rg (update_config_fn) Tj /F2 10 Tf ( \() Tj /F1 10 Tf (event) Tj /F2 10 Tf (\)) Tj T* ET
Q
Q
q
1 0 0 1 60.01575 241.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F1 10 Tf 0 0 0 rg (Callback function to update config dict with current UI depth range values) Tj T* ET
Q
Q
q
1 0 0 1 60.01575 235.0394 cm
Q
q
1 0 0 1 60.01575 220.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 15.23937 0 Td (Args:) Tj T* -15.23937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (event \(ipywidget callback\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (Any user interaction.) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 50.01575 214.0394 cm
Q
q
1 0 0 1 50.01575 196.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F5 10 Tf 0 0 0 rg (update_config_fr) Tj /F2 10 Tf ( \() Tj /F1 10 Tf (event) Tj /F2 10 Tf (\)) Tj T* ET
Q
Q
q
1 0 0 1 60.01575 184.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F1 10 Tf 0 0 0 rg (Callback function to update config dict with current UI depth range values) Tj T* ET
Q
Q
q
1 0 0 1 60.01575 178.0394 cm
Q
q
1 0 0 1 60.01575 163.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 15.23937 0 Td (Args:) Tj T* -15.23937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (event \(ipywidget callback\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (Any user interaction.) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 50.01575 157.0394 cm
Q
q
1 0 0 1 50.01575 139.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F5 10 Tf 0 0 0 rg (update_minmax_config) Tj /F2 10 Tf ( \() Tj /F1 10 Tf (event) Tj /F2 10 Tf (\)) Tj T* ET
Q
Q
q
1 0 0 1 60.01575 127.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F1 10 Tf 0 0 0 rg (Callback function to update config dict with current UI min/max height range values) Tj T* ET
Q
Q
q
1 0 0 1 60.01575 121.0394 cm
Q
q
1 0 0 1 60.01575 106.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 15.23937 0 Td (Args:) Tj T* -15.23937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (event \(ipywidget callback\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (Any user interaction.) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 40.01575 76.83937 cm
q
.8 .8 .8 RG
.3 w
.94902 .94902 .94902 rg
n -10 0 525.2441 19.2 re B*
Q
q
BT 1 0 0 1 0 2.2 Tm 13.2 TL /F3 11 Tf .12549 .262745 .360784 rg (ROI - Validation Module) Tj T* ET
Q
Q
q
1 0 0 1 40.01575 58.83937 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL (The module contains extraction validation functions that test extractions\222 scalar values,) Tj T* ET
Q
Q
q
1 0 0 1 34.01575 807.2126 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL (Welcome to moseq2-app\222s documentation!) Tj T* ET
Q
Q
q
1 0 0 1 34.01575 22.67717 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL (6) Tj T* ET
Q
Q
 
endstream
endobj
528 0 obj
<<
/Length 12792
>>
stream
1 0 0 1 0 0 cm  BT /F1 12 Tf 14.4 TL ET
q
1 0 0 1 40.01575 772.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
BT 1 0 0 1 0 2 Tm  T* ET
q
1 0 0 1 20 0 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F1 10 Tf 0 0 0 rg (timestamps, and position heatmaps.) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 40.01575 766.0394 cm
Q
q
1 0 0 1 40.01575 742.0394 cm
q
BT 1 0 0 1 0 14 Tm 12 TL /F4 10 Tf 0 0 0 rg (moseq2_app.roi.validation.) Tj /F5 10 Tf (check_timestamp_error_percentage) Tj /F1 10 Tf ( \() Tj (timestamps) Tj (, fps) Tj (=) Tj (30) Tj (,) Tj T* (scaling_factor) Tj (=) Tj (1000) Tj (\)) Tj T* ET
Q
Q
q
1 0 0 1 50.01575 730.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F1 10 Tf 0 0 .501961 rg (https://www.mathworks.com/help/imaq/examples/determining-the-rate-of-acquisition.html) Tj T* ET
Q
Q
q
1 0 0 1 50.01575 718.0394 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL (Returns the proportion of dropped frames relative to the respective recorded timestamps and frames per second.) Tj T* ET
Q
Q
q
1 0 0 1 50.01575 712.0394 cm
Q
q
1 0 0 1 50.01575 643.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 57 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 15.23937 0 Td (Args:) Tj T* -15.23937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 63 cm
Q
q
1 0 0 1 91.03937 63 cm
Q
q
1 0 0 1 91.03937 51 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (timestamps \(np.array\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (Session\222s recorded timestamp array.) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 91.03937 45 cm
Q
q
1 0 0 1 91.03937 33 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (fps \(int\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (Frames per second) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 91.03937 27 cm
Q
q
1 0 0 1 91.03937 3 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 9 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 14 Tm .916793 Tw 12 TL /F2 10 Tf 0 0 0 rg (scaling_factor \(float\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (factor to divide timestamps by to convert timestamp units into) Tj T* 0 Tw (seconds) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 91.03937 3 cm
Q
q
Q
Q
q
1 0 0 1 50.01575 628.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 31.92937 0 Td (Returns:) Tj T* -31.92937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL (percentError \(float\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 50.01575 613.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 14.14937 0 Td (Return type:) Tj T* -14.14937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL (Percentage of frames that were dropped/missed during acquisition.) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 40.01575 607.0394 cm
Q
q
1 0 0 1 40.01575 583.0394 cm
q
BT 1 0 0 1 0 14 Tm 12 TL /F4 10 Tf 0 0 0 rg (moseq2_app.roi.validation.) Tj /F5 10 Tf (compute_kl_divergences) Tj /F1 10 Tf ( \() Tj (pdfs) Tj (, groups) Tj (, sessions) Tj (, sessionNames) Tj (,) Tj T* (oob) Tj (=) Tj (False) Tj (\)) Tj T* ET
Q
Q
q
1 0 0 1 50.01575 559.0394 cm
q
BT 1 0 0 1 0 14 Tm 2.701007 Tw 12 TL /F1 10 Tf 0 0 0 rg (Computes KL divergence for all sessions and returns the divergences Consider trying Jensen Shannon or) Tj T* 0 Tw (Wasserstein instead!!) Tj T* ET
Q
Q
q
1 0 0 1 50.01575 553.0394 cm
Q
q
1 0 0 1 50.01575 448.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 93 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 15.23937 0 Td (Args:) Tj T* -15.23937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 99 cm
Q
q
1 0 0 1 91.03937 99 cm
Q
q
1 0 0 1 91.03937 75 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 9 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 14 Tm 3.675472 Tw 12 TL /F2 10 Tf 0 0 0 rg (pdfs \(list\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (list of 2d probability density functions \(heatmaps\) describing mouse) Tj T* 0 Tw (position.) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 91.03937 69 cm
Q
q
1 0 0 1 91.03937 57 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (groups \(list\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (list of groups corresponding to the pdfs indices) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 91.03937 51 cm
Q
q
1 0 0 1 91.03937 39 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (sessions \(list\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (list of sessions corresponding to the pdfs indices) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 91.03937 33 cm
Q
q
1 0 0 1 91.03937 21 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (sessionNames \(list\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (list of sessionNames corresponding to the pdfs indices) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 91.03937 15 cm
Q
q
1 0 0 1 91.03937 3 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (oob \(boolean\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (Compute out-of-bag KL-divergences) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 91.03937 3 cm
Q
q
Q
Q
q
1 0 0 1 50.01575 433.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 31.92937 0 Td (Returns:) Tj T* -31.92937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL (kl_divergences \(pd.Dataframe\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 50.01575 418.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 14.14937 0 Td (Return type:) Tj T* -14.14937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL (dataframe with mouse group, session, subjectname, and kl divergence) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 40.01575 412.0394 cm
Q
q
1 0 0 1 40.01575 400.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F4 10 Tf 0 0 0 rg (moseq2_app.roi.validation.) Tj /F5 10 Tf (count_frames_with_small_areas) Tj /F1 10 Tf ( \() Tj (scalar_df) Tj (\)) Tj T* ET
Q
Q
q
1 0 0 1 50.01575 384.0394 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL (Counts the number of frames where the mouse area is smaller than 2 standard deviations of) Tj T* ET
Q
Q
q
1 0 0 1 50.01575 369.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
BT 1 0 0 1 0 2 Tm  T* ET
q
1 0 0 1 20 0 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F1 10 Tf 0 0 0 rg (all mouse areas.) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 50.01575 363.0394 cm
Q
q
1 0 0 1 50.01575 348.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 15.23937 0 Td (Args:) Tj T* -15.23937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (scalar_df \(pd.DataFrame\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (Computed Scalar DataFrame) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 50.01575 333.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 31.92937 0 Td (Returns:) Tj T* -31.92937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL (corrupt_frames \(int\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 50.01575 318.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 14.14937 0 Td (Return type:) Tj T* -14.14937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL (Number of frames where the recorded mouse area is too small) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 40.01575 312.0394 cm
Q
q
1 0 0 1 40.01575 300.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F4 10 Tf 0 0 0 rg (moseq2_app.roi.validation.) Tj /F5 10 Tf (count_missing_mouse_frames) Tj /F1 10 Tf ( \() Tj (scalar_df) Tj (\)) Tj T* ET
Q
Q
q
1 0 0 1 50.01575 288.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F1 10 Tf 0 0 0 rg (Counts the number of frames where the mouse is not found.) Tj T* ET
Q
Q
q
1 0 0 1 50.01575 282.0394 cm
Q
q
1 0 0 1 50.01575 267.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 15.23937 0 Td (Args:) Tj T* -15.23937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (scalar_df \(pd.DataFrame\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (Computed Scalar DataFrame) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 50.01575 252.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 31.92937 0 Td (Returns:) Tj T* -31.92937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL (missing_mouse_frames \(int\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 50.01575 237.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 14.14937 0 Td (Return type:) Tj T* -14.14937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL (Number of frames with recorded mouse area ~= 0) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 40.01575 231.0394 cm
Q
q
1 0 0 1 40.01575 219.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F4 10 Tf 0 0 0 rg (moseq2_app.roi.validation.) Tj /F5 10 Tf (count_nan_rows) Tj /F1 10 Tf ( \() Tj (scalar_df) Tj (\)) Tj T* ET
Q
Q
q
1 0 0 1 50.01575 207.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F1 10 Tf 0 0 0 rg (Counts the number of rows with NaN scalar values.) Tj T* ET
Q
Q
q
1 0 0 1 50.01575 201.0394 cm
Q
q
1 0 0 1 50.01575 186.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 15.23937 0 Td (Args:) Tj T* -15.23937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (scalar_df \(pd.DataFrame\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (Computed Scalar DataFrame) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 50.01575 171.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 31.92937 0 Td (Returns:) Tj T* -31.92937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL (n_missing_frames \(int\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 50.01575 156.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 14.14937 0 Td (Return type:) Tj T* -14.14937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL (Number of frames with NaN computed scalar values.) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 40.01575 150.0394 cm
Q
q
1 0 0 1 40.01575 138.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F4 10 Tf 0 0 0 rg (moseq2_app.roi.validation.) Tj /F5 10 Tf (count_stationary_frames) Tj /F1 10 Tf ( \() Tj (scalar_df) Tj (\)) Tj T* ET
Q
Q
q
1 0 0 1 50.01575 126.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F1 10 Tf 0 0 0 rg (Counts the number of frames where mouse is not moving.) Tj T* ET
Q
Q
q
1 0 0 1 50.01575 120.0394 cm
Q
q
1 0 0 1 50.01575 105.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 15.23937 0 Td (Args:) Tj T* -15.23937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (scalar_df \(pd.DataFrame\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (Computed Scalar DataFrame) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 50.01575 90.03937 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 31.92937 0 Td (Returns:) Tj T* -31.92937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL (motionless_frames \(int\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 50.01575 75.03937 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 14.14937 0 Td (Return type:) Tj T* -14.14937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL (Number of frames where the mouse is not moving) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 40.01575 69.03937 cm
Q
q
1 0 0 1 40.01575 57.03937 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F4 10 Tf 0 0 0 rg (moseq2_app.roi.validation.) Tj /F5 10 Tf (get_kl_divergence_outliers) Tj /F1 10 Tf ( \() Tj (kl_divergences) Tj (\)) Tj T* ET
Q
Q
q
1 0 0 1 34.01575 807.2126 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL (Welcome to moseq2-app\222s documentation!) Tj T* ET
Q
Q
q
1 0 0 1 34.01575 22.67717 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL (7) Tj T* ET
Q
Q
 
endstream
endobj
529 0 obj
<<
/Length 12217
>>
stream
1 0 0 1 0 0 cm  BT /F1 12 Tf 14.4 TL ET
q
1 0 0 1 50.01575 775.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F1 10 Tf 0 0 0 rg (Returns the position PDFs that are over 2 standard deviations away from the mean position divergence.) Tj T* ET
Q
Q
q
1 0 0 1 50.01575 769.0394 cm
Q
q
1 0 0 1 50.01575 742.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 15 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 15.23937 0 Td (Args:) Tj T* -15.23937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 3 cm
q
BT 1 0 0 1 0 14 Tm 5.279246 Tw 12 TL /F2 10 Tf 0 0 0 rg (kl_divergences \(pd.Dataframe\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (dataframe with group, session, subjectName, and) Tj T* 0 Tw (divergence) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 50.01575 727.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 31.92937 0 Td (Returns:) Tj T* -31.92937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL (outliers \(pd.Dataframe\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 50.01575 712.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 14.14937 0 Td (Return type:) Tj T* -14.14937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL (dataframe of outlier sessions) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 40.01575 706.0394 cm
Q
q
1 0 0 1 40.01575 694.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F4 10 Tf 0 0 0 rg (moseq2_app.roi.validation.) Tj /F5 10 Tf (get_scalar_anomaly_sessions) Tj /F1 10 Tf ( \() Tj (scalar_df) Tj (, status_dicts) Tj (\)) Tj T* ET
Q
Q
q
1 0 0 1 50.01575 682.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F1 10 Tf 0 0 0 rg (Detects outlier sessions using an EllipticEnvelope model based on a subset of their mean scalar values.) Tj T* ET
Q
Q
q
1 0 0 1 50.01575 676.0394 cm
Q
q
1 0 0 1 50.01575 625.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 39 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 15.23937 0 Td (Args:) Tj T* -15.23937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 45 cm
Q
q
1 0 0 1 91.03937 45 cm
Q
q
1 0 0 1 91.03937 33 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (scalar_df \(pd.DataFrame\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (Computed Scalar DataFrame) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 91.03937 27 cm
Q
q
1 0 0 1 91.03937 3 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 9 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 14 Tm 1.395472 Tw 12 TL /F2 10 Tf 0 0 0 rg (status_dicts \(dict\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (stacked dictionary object containing all the sessions\222 flag status) Tj T* 0 Tw (dicts.) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 91.03937 3 cm
Q
q
Q
Q
q
1 0 0 1 50.01575 610.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 31.92937 0 Td (Returns:) Tj T* -31.92937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL (status_dicts \(dict\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 50.01575 595.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 14.14937 0 Td (Return type:) Tj T* -14.14937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL (stacked dictionary object containing updated scalar_anomaly flags.) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 40.01575 589.0394 cm
Q
q
1 0 0 1 40.01575 577.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F4 10 Tf 0 0 0 rg (moseq2_app.roi.validation.) Tj /F5 10 Tf (get_scalar_df) Tj /F1 10 Tf ( \() Tj (path_dict) Tj (\)) Tj T* ET
Q
Q
q
1 0 0 1 50.01575 553.0394 cm
q
BT 1 0 0 1 0 14 Tm 1.743606 Tw 12 TL /F1 10 Tf 0 0 0 rg (Computes a scalar dataframe that contains all the extracted sessions recorded scalar values along with their) Tj T* 0 Tw (metadata.) Tj T* ET
Q
Q
q
1 0 0 1 50.01575 547.0394 cm
Q
q
1 0 0 1 50.01575 532.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 15.23937 0 Td (Args:) Tj T* -15.23937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (path_dict \(dict\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (dictionary of session folder names paired with their extraction paths) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 50.01575 517.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 31.92937 0 Td (Returns:) Tj T* -31.92937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL (scalar_df \(pd.DataFrame\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 50.01575 502.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 14.14937 0 Td (Return type:) Tj T* -14.14937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL (DataFrame containing loaded scalar info from each h5 extraction file.) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 40.01575 496.0394 cm
Q
q
1 0 0 1 40.01575 484.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F4 10 Tf 0 0 0 rg (moseq2_app.roi.validation.) Tj /F5 10 Tf (make_session_status_dicts) Tj /F1 10 Tf ( \() Tj (paths) Tj (\)) Tj T* ET
Q
Q
q
1 0 0 1 50.01575 468.0394 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL (Returns the flag status dicts for all the found completed extracted sessions. Additionally performs) Tj T* ET
Q
Q
q
1 0 0 1 50.01575 453.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
BT 1 0 0 1 0 2 Tm  T* ET
q
1 0 0 1 20 0 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F1 10 Tf 0 0 0 rg (dropped frames test on all sessions.) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 50.01575 447.0394 cm
Q
q
1 0 0 1 50.01575 432.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 15.23937 0 Td (Args:) Tj T* -15.23937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (paths \(dict\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (path dict of session names paired wit their mp4 paths.) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 50.01575 417.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 31.92937 0 Td (Returns:) Tj T* -31.92937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL (status_dicts \(dict\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 50.01575 402.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 14.14937 0 Td (Return type:) Tj T* -14.14937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL (stacked dictionary object containing all the sessions\222 flag status dicts.) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 40.01575 396.0394 cm
Q
q
1 0 0 1 40.01575 384.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F4 10 Tf 0 0 0 rg (moseq2_app.roi.validation.) Tj /F5 10 Tf (plot_heatmap) Tj /F1 10 Tf ( \() Tj (heatmap) Tj (, title) Tj (\)) Tj T* ET
Q
Q
q
1 0 0 1 50.01575 372.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F1 10 Tf 0 0 0 rg (Plots and displays outlier heatmap with the SessionName as the title.) Tj T* ET
Q
Q
q
1 0 0 1 50.01575 366.0394 cm
Q
q
1 0 0 1 50.01575 327.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 27 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 15.23937 0 Td (Args:) Tj T* -15.23937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 33 cm
Q
q
1 0 0 1 91.03937 33 cm
Q
q
1 0 0 1 91.03937 21 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (heatmap \(2d np.array\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (outlier position PDF) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 91.03937 15 cm
Q
q
1 0 0 1 91.03937 3 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (title \(str\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (plot title) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 91.03937 3 cm
Q
q
Q
Q
q
1 0 0 1 40.01575 321.0394 cm
Q
q
1 0 0 1 40.01575 309.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F4 10 Tf 0 0 0 rg (moseq2_app.roi.validation.) Tj /F5 10 Tf (print_validation_results) Tj /F1 10 Tf ( \() Tj (scalar_df) Tj (, status_dicts) Tj (\)) Tj T* ET
Q
Q
q
1 0 0 1 50.01575 293.0394 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL (Displays all the outlier sessions flag names and values. Additionally plots the flagged) Tj T* ET
Q
Q
q
1 0 0 1 50.01575 278.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
BT 1 0 0 1 0 2 Tm  T* ET
q
1 0 0 1 20 0 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F1 10 Tf 0 0 0 rg (position heatmap.) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 50.01575 272.0394 cm
Q
q
1 0 0 1 50.01575 257.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 15.23937 0 Td (Args:) Tj T* -15.23937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (anomaly_dict \(dict\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (Dict object containing specific session flags to print) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 40.01575 251.0394 cm
Q
q
1 0 0 1 40.01575 239.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F4 10 Tf 0 0 0 rg (moseq2_app.roi.validation.) Tj /F5 10 Tf (run_heatmap_kl_divergence_test) Tj /F1 10 Tf ( \() Tj (scalar_df) Tj (, status_dicts) Tj (\)) Tj T* ET
Q
Q
q
1 0 0 1 50.01575 227.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F1 10 Tf 0 0 0 rg (Finds the position PDF outlier sessions and updates the status_dicts with the respective position heatmap flag.) Tj T* ET
Q
Q
q
1 0 0 1 50.01575 221.0394 cm
Q
q
1 0 0 1 50.01575 170.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 39 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 15.23937 0 Td (Args:) Tj T* -15.23937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 45 cm
Q
q
1 0 0 1 91.03937 45 cm
Q
q
1 0 0 1 91.03937 33 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (scalar_df \(pd.DataFrame\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (Computed Scalar DataFrame) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 91.03937 27 cm
Q
q
1 0 0 1 91.03937 3 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 9 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 14 Tm 1.395472 Tw 12 TL /F2 10 Tf 0 0 0 rg (status_dicts \(dict\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (stacked dictionary object containing all the sessions\222 flag status) Tj T* 0 Tw (dicts.) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 91.03937 3 cm
Q
q
Q
Q
q
1 0 0 1 50.01575 155.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 31.92937 0 Td (Returns:) Tj T* -31.92937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL (status_dicts \(dict\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 50.01575 140.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 14.14937 0 Td (Return type:) Tj T* -14.14937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL (stacked dictionary object containing updated position_heatmap flags.) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 40.01575 134.0394 cm
Q
q
1 0 0 1 40.01575 122.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F4 10 Tf 0 0 0 rg (moseq2_app.roi.validation.) Tj /F5 10 Tf (run_validation_tests) Tj /F1 10 Tf ( \() Tj (scalar_df) Tj (, status_dicts) Tj (\)) Tj T* ET
Q
Q
q
1 0 0 1 50.01575 106.0394 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL (Main function that runs all the available extraction validation tests and updates the status_dicts) Tj T* ET
Q
Q
q
1 0 0 1 50.01575 91.03937 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
BT 1 0 0 1 0 2 Tm  T* ET
q
1 0 0 1 20 0 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F1 10 Tf 0 0 0 rg (flags accordingly.) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 50.01575 85.03937 cm
Q
q
1 0 0 1 34.01575 807.2126 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL (Welcome to moseq2-app\222s documentation!) Tj T* ET
Q
Q
q
1 0 0 1 34.01575 22.67717 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL (8) Tj T* ET
Q
Q
 
endstream
endobj
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1 0 0 1 0 0 cm  BT /F1 12 Tf 14.4 TL ET
q
1 0 0 1 50.01575 736.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 39 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 15.23937 0 Td (Args:) Tj T* -15.23937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 45 cm
Q
q
1 0 0 1 91.03937 45 cm
Q
q
1 0 0 1 91.03937 33 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (scalar_df \(pd.DataFrame\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (Computed Scalar DataFrame) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 91.03937 27 cm
Q
q
1 0 0 1 91.03937 3 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 9 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 14 Tm 1.395472 Tw 12 TL /F2 10 Tf 0 0 0 rg (status_dicts \(dict\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (stacked dictionary object containing all the sessions\222 flag status) Tj T* 0 Tw (dicts.) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 91.03937 3 cm
Q
q
Q
Q
q
1 0 0 1 50.01575 721.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 31.92937 0 Td (Returns:) Tj T* -31.92937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL (status_dicts \(dict\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 50.01575 706.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 14.14937 0 Td (Return type:) Tj T* -14.14937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL (stacked dictionary object containing all the sessions\222 updated flag status dicts.) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 40.01575 676.8394 cm
q
.8 .8 .8 RG
.3 w
.94902 .94902 .94902 rg
n -10 0 525.2441 19.2 re B*
Q
q
BT 1 0 0 1 0 2.2 Tm 13.2 TL /F3 11 Tf .12549 .262745 .360784 rg (ROI - View Module) Tj T* ET
Q
Q
q
1 0 0 1 40.01575 658.8394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F1 10 Tf 0 0 0 rg (Interactive ROI/Extraction Bokeh visualization functions.) Tj T* ET
Q
Q
q
1 0 0 1 40.01575 652.8394 cm
Q
q
1 0 0 1 40.01575 640.8394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F4 10 Tf 0 0 0 rg (moseq2_app.roi.view.) Tj /F5 10 Tf (bokeh_plot_helper) Tj /F1 10 Tf ( \() Tj (bk_fig) Tj (, image) Tj (\)) Tj T* ET
Q
Q
q
1 0 0 1 50.01575 628.8394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F1 10 Tf 0 0 0 rg (Helper function that creates the Bokeh image gylphs in the created canvases/figures.) Tj T* ET
Q
Q
q
1 0 0 1 50.01575 622.8394 cm
Q
q
1 0 0 1 50.01575 583.8394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 27 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 15.23937 0 Td (Args:) Tj T* -15.23937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 33 cm
Q
q
1 0 0 1 91.03937 33 cm
Q
q
1 0 0 1 91.03937 21 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (bk_fig \(Bokeh figure\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (figure canvas to draw image/glyph on) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 91.03937 15 cm
Q
q
1 0 0 1 91.03937 3 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (image \(2D np.array\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (image to draw.) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 91.03937 3 cm
Q
q
Q
Q
q
1 0 0 1 40.01575 577.8394 cm
Q
q
1 0 0 1 40.01575 553.8394 cm
q
BT 1 0 0 1 0 14 Tm 12 TL /F4 10 Tf 0 0 0 rg (moseq2_app.roi.view.) Tj /F5 10 Tf (plot_roi_results) Tj /F1 10 Tf ( \() Tj (sessionName) Tj (, bground_im) Tj (, roi) Tj (, overlay) Tj (, filtered_frames) Tj (,) Tj T* (depth_frames) Tj (, fn) Tj (\)) Tj T* ET
Q
Q
q
1 0 0 1 50.01575 517.8394 cm
q
BT 1 0 0 1 0 26 Tm 1.110829 Tw 12 TL /F1 10 Tf 0 0 0 rg (Main ROI plotting function that uses Bokeh to facilitate 3 interactive plots. Plots the background image, and an) Tj T* 0 Tw 1.505292 Tw (axis-connected plot of the ROI, and an independent plot of the thresholded background subracted segmented) Tj T* 0 Tw (image.) Tj T* ET
Q
Q
q
1 0 0 1 50.01575 511.8394 cm
Q
q
1 0 0 1 50.01575 382.8394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 117 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 15.23937 0 Td (Args:) Tj T* -15.23937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 123 cm
Q
q
1 0 0 1 91.03937 123 cm
Q
q
1 0 0 1 91.03937 111 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (sessionName \(str\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (Name of session currently being plotted) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 91.03937 105 cm
Q
q
1 0 0 1 91.03937 93 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (bground_im \(2D np.array\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (Computed session background) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 91.03937 87 cm
Q
q
1 0 0 1 91.03937 75 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (roi \(2D np.array\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (Computed ROI based on given depth ranges) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 91.03937 69 cm
Q
q
1 0 0 1 91.03937 57 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL (overlay \(2D np.array\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 91.03937 51 cm
Q
q
1 0 0 1 91.03937 39 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL (filtered_frames \(2D np.array\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 91.03937 33 cm
Q
q
1 0 0 1 91.03937 21 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL (depth_frames \(2D np.array\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 91.03937 15 cm
Q
q
1 0 0 1 91.03937 3 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (fn \(int or ipywidget IntSlider\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (Current frame number to display) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 91.03937 3 cm
Q
q
Q
Q
q
1 0 0 1 40.01575 376.8394 cm
Q
q
1 0 0 1 40.01575 364.8394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F4 10 Tf 0 0 0 rg (moseq2_app.roi.view.) Tj /F5 10 Tf (show_extraction) Tj /F1 10 Tf ( \() Tj (input_file) Tj (, video_file) Tj (\)) Tj T* ET
Q
Q
q
1 0 0 1 50.01575 340.8394 cm
q
BT 1 0 0 1 0 14 Tm .883675 Tw 12 TL /F1 10 Tf 0 0 0 rg (Visualization helper function to display manually triggered extraction. Function will facilitate visualization through) Tj T* 0 Tw (creating a HTML div to display in a jupyter notebook or web page.) Tj T* ET
Q
Q
q
1 0 0 1 50.01575 334.8394 cm
Q
q
1 0 0 1 50.01575 295.8394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 27 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 15.23937 0 Td (Args:) Tj T* -15.23937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 33 cm
Q
q
1 0 0 1 91.03937 33 cm
Q
q
1 0 0 1 91.03937 21 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (input_file \(str\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (session name to display.) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 91.03937 15 cm
Q
q
1 0 0 1 91.03937 3 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (video_file \(str\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (path to video to display) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 91.03937 3 cm
Q
q
Q
Q
q
1 0 0 1 40.01575 266.6394 cm
q
.8 .8 .8 RG
.3 w
.94902 .94902 .94902 rg
n -10 0 525.2441 19.2 re B*
Q
q
BT 1 0 0 1 0 2.2 Tm 13.2 TL /F3 11 Tf .12549 .262745 .360784 rg (ROI - Widgets Module) Tj T* ET
Q
Q
q
1 0 0 1 40.01575 248.6394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F1 10 Tf 0 0 0 rg (Ipywidgets used to facilitate interactive ROI detection) Tj T* ET
Q
Q
q
1 0 0 1 40.01575 242.6394 cm
Q
q
1 0 0 1 40.01575 224.6394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F6 10 Tf 0 0 0 rg (class ) Tj /F4 10 Tf (moseq2_app.roi.widgets.) Tj /F5 10 Tf (InteractiveROIWidgets) Tj T* ET
Q
Q
q
1 0 0 1 50.01575 212.6394 cm
q
.933333 1 .8 rg
n 33.35 0 36 12 re f*
BT 1 0 0 1 0 2 Tm 12 TL /F1 10 Tf 0 0 0 rg (Bases: ) Tj /F5 10 Tf (object) Tj T* ET
Q
Q
q
1 0 0 1 50.01575 188.6394 cm
q
0 0 0 rg
BT 1 0 0 1 0 14 Tm /F1 10 Tf 12 TL 1.188273 Tw (Class that contains Ipywidget widgets and layouts to facilitate interactive ROI finding functionality. This class is) Tj T* 0 Tw (extended by the controller class InteractiveFindRoi.) Tj T* ET
Q
Q
q
1 0 0 1 34.01575 807.2126 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL (Welcome to moseq2-app\222s documentation!) Tj T* ET
Q
Q
q
1 0 0 1 34.01575 22.67717 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL (9) Tj T* ET
Q
Q
 
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1 0 0 1 0 0 cm  BT /F1 12 Tf 14.4 TL ET
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1 0 0 1 40.01575 773.8394 cm
q
.8 .8 .8 RG
.3 w
.94902 .94902 .94902 rg
n -10 0 525.2441 19.2 re B*
Q
q
BT 1 0 0 1 0 2.2 Tm 13.2 TL /F3 11 Tf .12549 .262745 .360784 rg (Module contents) Tj T* ET
Q
Q
q
1 0 0 1 40.01575 743.4394 cm
q
.8 .8 .8 RG
.3 w
.94902 .94902 .94902 rg
n -10 0 525.2441 20.4 re B*
Q
q
BT 1 0 0 1 0 2.4 Tm 14.4 TL /F3 12 Tf .12549 .262745 .360784 rg (moseq2_app.gui package) Tj T* ET
Q
Q
q
1 0 0 1 40.01575 714.2394 cm
q
.8 .8 .8 RG
.3 w
.94902 .94902 .94902 rg
n -10 0 525.2441 19.2 re B*
Q
q
.12549 .262745 .360784 rg
BT 1 0 0 1 0 2.2 Tm /F3 11 Tf 13.2 TL (Submodules) Tj T* ET
Q
Q
q
1 0 0 1 40.01575 685.0394 cm
q
.8 .8 .8 RG
.3 w
.94902 .94902 .94902 rg
n -10 0 525.2441 19.2 re B*
Q
q
BT 1 0 0 1 0 2.2 Tm 13.2 TL /F3 11 Tf .12549 .262745 .360784 rg (GUI - Progress Module) Tj T* ET
Q
Q
q
1 0 0 1 40.01575 667.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F1 10 Tf 0 0 0 rg (This module handles all jupyter notebook progress related functionalities.) Tj T* ET
Q
Q
q
1 0 0 1 40.01575 661.0394 cm
Q
q
1 0 0 1 40.01575 625.0394 cm
q
BT 1 0 0 1 0 26 Tm 12 TL /F4 10 Tf 0 0 0 rg (moseq2_app.gui.progress.) Tj /F5 10 Tf (check_progress) Tj /F1 10 Tf  T* (\() Tj (progress_filepath) Tj (=) Tj ('/Users/aymanzeine/Desktop/moseq/moseq2-app/docs/progress.yaml') Tj (, exts) Tj (=) Tj (['dat', 'mkv', 'avi',) Tj T* ('tar.gz']) Tj (\)) Tj T* ET
Q
Q
q
1 0 0 1 50.01575 601.0394 cm
q
BT 1 0 0 1 0 14 Tm .526339 Tw 12 TL /F1 10 Tf 0 0 0 rg (Checks whether progress file exists and prompts user input on whether to overwrite, load old, or generate a new) Tj T* 0 Tw (one.) Tj T* ET
Q
Q
q
1 0 0 1 50.01575 595.0394 cm
Q
q
1 0 0 1 50.01575 556.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 27 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 15.23937 0 Td (Args:) Tj T* -15.23937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 33 cm
Q
q
1 0 0 1 91.03937 33 cm
Q
q
1 0 0 1 91.03937 21 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (base_dir \(str\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (path to directory to create/find progress file) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 91.03937 15 cm
Q
q
1 0 0 1 91.03937 3 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (progress_filepath \(str\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (path to progress filename) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 91.03937 3 cm
Q
q
Q
Q
q
1 0 0 1 50.01575 541.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 31.92937 0 Td (Returns:) Tj T* -31.92937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 15 cm
Q
q
Q
Q
q
1 0 0 1 50.01575 526.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 14.14937 0 Td (Return type:) Tj T* -14.14937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL (All restored variables or None.) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 40.01575 520.0394 cm
Q
q
1 0 0 1 40.01575 508.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F4 10 Tf 0 0 0 rg (moseq2_app.gui.progress.) Tj /F5 10 Tf (count_total_found_items) Tj /F1 10 Tf ( \() Tj (i_dict) Tj (\)) Tj T* ET
Q
Q
q
1 0 0 1 50.01575 496.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F1 10 Tf 0 0 0 rg (Counts the total number of found progress items) Tj T* ET
Q
Q
q
1 0 0 1 50.01575 490.0394 cm
Q
q
1 0 0 1 50.01575 475.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 15.23937 0 Td (Args:) Tj T* -15.23937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (i_dict \(dict\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (Dict containing paths to respective pipelines items.) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 50.01575 460.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 31.92937 0 Td (Returns:) Tj T* -31.92937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL (num_files \(int\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 50.01575 445.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 14.14937 0 Td (Return type:) Tj T* -14.14937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL (Number of found previously computed paths.) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 40.01575 439.0394 cm
Q
q
1 0 0 1 40.01575 427.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F4 10 Tf 0 0 0 rg (moseq2_app.gui.progress.) Tj /F5 10 Tf (find_progress) Tj /F1 10 Tf ( \() Tj (base_progress) Tj (\)) Tj T* ET
Q
Q
q
1 0 0 1 50.01575 411.0394 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL (Searches for paths to all existing MosSeq2-Notebook dependencies) Tj T* ET
Q
Q
q
1 0 0 1 50.01575 396.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
BT 1 0 0 1 0 2 Tm  T* ET
q
1 0 0 1 20 0 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F1 10 Tf 0 0 0 rg (and updates the progress paths dictionary.) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 50.01575 390.0394 cm
Q
q
1 0 0 1 50.01575 375.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 15.23937 0 Td (Args:) Tj T* -15.23937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (base_progress \(dict\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (base dictionary of progress variables) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 50.01575 360.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 31.92937 0 Td (Returns:) Tj T* -31.92937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL (base_progress \(dict\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 50.01575 345.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 14.14937 0 Td (Return type:) Tj T* -14.14937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL (updated dictionary of progress variables) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 40.01575 339.0394 cm
Q
q
1 0 0 1 40.01575 327.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F4 10 Tf 0 0 0 rg (moseq2_app.gui.progress.) Tj /F5 10 Tf (generate_intital_progressfile) Tj /F1 10 Tf ( \() Tj (filename) Tj (=) Tj ('progress.yaml') Tj (\)) Tj T* ET
Q
Q
q
1 0 0 1 50.01575 311.0394 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL (Generates a progress YAML file with the scanned parameter paths.) Tj T* ET
Q
Q
q
1 0 0 1 50.01575 284.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
BT 1 0 0 1 0 14 Tm  T* ET
q
1 0 0 1 20 0 cm
q
BT 1 0 0 1 0 14 Tm .029243 Tw 12 TL /F1 10 Tf 0 0 0 rg (It will either load a previous progress file if the progress log and pickle file or will scan the given base directory) Tj T* 0 Tw (to find all relative paths) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 50.01575 278.0394 cm
Q
q
1 0 0 1 50.01575 263.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 15.23937 0 Td (Args:) Tj T* -15.23937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (filename \(str\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (path to file to write progress YAML to) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 50.01575 248.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 31.92937 0 Td (Returns:) Tj T* -31.92937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL (base_progress_vars \(dict\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 50.01575 233.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 14.14937 0 Td (Return type:) Tj T* -14.14937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL (Loaded/Found progress variables) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 40.01575 227.0394 cm
Q
q
1 0 0 1 40.01575 215.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F4 10 Tf 0 0 0 rg (moseq2_app.gui.progress.) Tj /F5 10 Tf (generate_missing_metadata) Tj /F1 10 Tf ( \() Tj (sess_dir) Tj (, sess_name) Tj (\)) Tj T* ET
Q
Q
q
1 0 0 1 50.01575 203.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F1 10 Tf 0 0 0 rg (Generates default metadata.json file for session that does not already include one.) Tj T* ET
Q
Q
q
1 0 0 1 50.01575 197.0394 cm
Q
q
1 0 0 1 50.01575 158.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 27 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 15.23937 0 Td (Args:) Tj T* -15.23937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 33 cm
Q
q
1 0 0 1 91.03937 33 cm
Q
q
1 0 0 1 91.03937 21 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (sess_dir \(str\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (Path to directory to create metadata.json file in.) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 91.03937 15 cm
Q
q
1 0 0 1 91.03937 3 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (sess_name \(str\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (Name of the directory to set the metadata SessionName.) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 91.03937 3 cm
Q
q
Q
Q
q
1 0 0 1 40.01575 152.0394 cm
Q
q
1 0 0 1 40.01575 140.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F4 10 Tf 0 0 0 rg (moseq2_app.gui.progress.) Tj /F5 10 Tf (get_extraction_progress) Tj /F1 10 Tf ( \() Tj (base_dir) Tj (, exts) Tj (=) Tj (['dat', 'mkv', 'avi']) Tj (\)) Tj T* ET
Q
Q
q
1 0 0 1 50.01575 124.0394 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL (Counts the number of fully extracted sessions, and prints the session directory names) Tj T* ET
Q
Q
q
1 0 0 1 50.01575 109.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
BT 1 0 0 1 0 2 Tm  T* ET
q
1 0 0 1 20 0 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F1 10 Tf 0 0 0 rg (of the incomplete or missing extractions.) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 50.01575 103.0394 cm
Q
q
1 0 0 1 50.01575 88.03937 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 15.23937 0 Td (Args:) Tj T* -15.23937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (base_dir \(str\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (Path to parent directory containing all sessions) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 50.01575 61.03937 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 15 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 31.92937 0 Td (Returns:) Tj T* -31.92937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 3 cm
q
BT 1 0 0 1 0 14 Tm .675394 Tw 12 TL /F2 10 Tf 0 0 0 rg (path_dict \(dict\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (Dict with paths to all found sessions) Tj /F1 10 Tf (\) ) Tj /F2 10 Tf (num_extracted \(int\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (Total number) Tj T* 0 Tw (of completed extractions) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 40.01575 55.03937 cm
Q
q
1 0 0 1 34.01575 807.2126 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL (Welcome to moseq2-app\222s documentation!) Tj T* ET
Q
Q
q
1 0 0 1 34.01575 22.67717 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL (10) Tj T* ET
Q
Q
 
endstream
endobj
532 0 obj
<<
/Length 13540
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stream
1 0 0 1 0 0 cm  BT /F1 12 Tf 14.4 TL ET
q
1 0 0 1 40.01575 775.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F4 10 Tf 0 0 0 rg (moseq2_app.gui.progress.) Tj /F5 10 Tf (get_pca_progress) Tj /F1 10 Tf ( \() Tj (progress_vars) Tj (, pca_progress) Tj (\)) Tj T* ET
Q
Q
q
1 0 0 1 50.01575 763.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F1 10 Tf 0 0 0 rg (Updates the PCA progress dict variables and prints the names of the missing keys.) Tj T* ET
Q
Q
q
1 0 0 1 50.01575 757.0394 cm
Q
q
1 0 0 1 50.01575 718.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 27 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 15.23937 0 Td (Args:) Tj T* -15.23937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 33 cm
Q
q
1 0 0 1 91.03937 33 cm
Q
q
1 0 0 1 91.03937 21 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (progress_vars \(dict\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (Notebook progress dict including the relevant PCA paths) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 91.03937 15 cm
Q
q
1 0 0 1 91.03937 3 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (pca_progress \(dict\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (PCA progress boolean dict used to display progress bar) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 91.03937 3 cm
Q
q
Q
Q
q
1 0 0 1 50.01575 703.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 31.92937 0 Td (Returns:) Tj T* -31.92937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL (pca_progress \(dict\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 50.01575 688.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 14.14937 0 Td (Return type:) Tj T* -14.14937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL (Updated PCA progress boolean dict.) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 40.01575 682.0394 cm
Q
q
1 0 0 1 40.01575 670.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F4 10 Tf 0 0 0 rg (moseq2_app.gui.progress.) Tj /F5 10 Tf (get_session_paths) Tj /F1 10 Tf ( \() Tj (data_dir) Tj (, extracted) Tj (=) Tj (False) Tj (, exts) Tj (=) Tj (['dat', 'mkv', 'avi']) Tj (\)) Tj T* ET
Q
Q
q
1 0 0 1 50.01575 658.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F1 10 Tf 0 0 0 rg (Find all depth recording sessions and their paths \(with given extensions\) to work on given base directory.) Tj T* ET
Q
Q
q
1 0 0 1 50.01575 642.0394 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL (Function also generates metadata.json files for un-extracted directories that) Tj T* ET
Q
Q
q
1 0 0 1 50.01575 627.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
BT 1 0 0 1 0 2 Tm  T* ET
q
1 0 0 1 20 0 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL (are missing them.) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 50.01575 621.0394 cm
Q
q
1 0 0 1 50.01575 582.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 27 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 15.23937 0 Td (Args:) Tj T* -15.23937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 33 cm
Q
q
1 0 0 1 91.03937 33 cm
Q
q
1 0 0 1 91.03937 21 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (data_dir \(str\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (path to directory containing all session folders.) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 91.03937 15 cm
Q
q
1 0 0 1 91.03937 3 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (exts \(list\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (list of depth file extensions to search for.) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 91.03937 3 cm
Q
q
Q
Q
q
1 0 0 1 50.01575 567.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 31.92937 0 Td (Returns:) Tj T* -31.92937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL (path_dict \(dict\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 50.01575 552.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 14.14937 0 Td (Return type:) Tj T* -14.14937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL (session directory name keys pair with their respective absolute paths.) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 40.01575 546.0394 cm
Q
q
1 0 0 1 40.01575 534.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F4 10 Tf 0 0 0 rg (moseq2_app.gui.progress.) Tj /F5 10 Tf (load_progress) Tj /F1 10 Tf ( \() Tj (progress_file) Tj (\)) Tj T* ET
Q
Q
q
1 0 0 1 50.01575 522.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F1 10 Tf 0 0 0 rg (Loads progress file variables) Tj T* ET
Q
Q
q
1 0 0 1 50.01575 516.0394 cm
Q
q
1 0 0 1 50.01575 501.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 15.23937 0 Td (Args:) Tj T* -15.23937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (progress_file \(str\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (path to progress file.) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 50.01575 486.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 31.92937 0 Td (Returns:) Tj T* -31.92937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL (progress_vars \(dict\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 50.01575 471.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 14.14937 0 Td (Return type:) Tj T* -14.14937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL (dictionary of loaded progress variables) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 40.01575 465.0394 cm
Q
q
1 0 0 1 40.01575 453.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F4 10 Tf 0 0 0 rg (moseq2_app.gui.progress.) Tj /F5 10 Tf (print_progress) Tj /F1 10 Tf ( \() Tj (base_dir) Tj (, progress_vars) Tj (, exts) Tj (=) Tj (['dat', 'mkv', 'avi']) Tj (\)) Tj T* ET
Q
Q
q
1 0 0 1 50.01575 441.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F1 10 Tf 0 0 0 rg (Searches for all the paths included in the progress file and displays 4 progress bars, one for each pipeline step.) Tj T* ET
Q
Q
q
1 0 0 1 50.01575 429.0394 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL (Displays tqdm progress bars checking a users jupyter notebook progress.) Tj T* ET
Q
Q
q
1 0 0 1 50.01575 423.0394 cm
Q
q
1 0 0 1 50.01575 384.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 27 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 15.23937 0 Td (Args:) Tj T* -15.23937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 33 cm
Q
q
1 0 0 1 91.03937 33 cm
Q
q
1 0 0 1 91.03937 21 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (base_dir \(str\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (Path to parent directory containing all sessions) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 91.03937 15 cm
Q
q
1 0 0 1 91.03937 3 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (progress_vars \(dict\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (notebook progress dict) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 91.03937 3 cm
Q
q
Q
Q
q
1 0 0 1 40.01575 378.0394 cm
Q
q
1 0 0 1 40.01575 354.0394 cm
q
BT 1 0 0 1 0 14 Tm 12 TL /F4 10 Tf 0 0 0 rg (moseq2_app.gui.progress.) Tj /F5 10 Tf (restore_progress_vars) Tj /F1 10 Tf  T* (\() Tj (progress_file) Tj (=) Tj ('/Users/aymanzeine/Desktop/moseq/moseq2-app/docs/progress.yaml') Tj (, init) Tj (=) Tj (False) Tj (, overwrite) Tj (=) Tj (False) Tj (\)) Tj T* ET
Q
Q
q
1 0 0 1 50.01575 342.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F1 10 Tf 0 0 0 rg (Restore all saved progress variables to Jupyter Notebook.) Tj T* ET
Q
Q
q
1 0 0 1 50.01575 336.0394 cm
Q
q
1 0 0 1 50.01575 321.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 15.23937 0 Td (Args:) Tj T* -15.23937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (progress_file \(str\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (path to progress file) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 50.01575 306.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 31.92937 0 Td (Returns:) Tj T* -31.92937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL (vars \(dict\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 50.01575 291.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 14.14937 0 Td (Return type:) Tj T* -14.14937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL (All progress file variables) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 40.01575 285.0394 cm
Q
q
1 0 0 1 40.01575 273.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F4 10 Tf 0 0 0 rg (moseq2_app.gui.progress.) Tj /F5 10 Tf (show_progress_bar) Tj /F1 10 Tf ( \() Tj (nfound) Tj (, total) Tj (, desc) Tj (\)) Tj T* ET
Q
Q
q
1 0 0 1 50.01575 261.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F1 10 Tf 0 0 0 rg (Helper function to print progress bars for each MoSeq-step progress dict) Tj T* ET
Q
Q
q
1 0 0 1 50.01575 255.0394 cm
Q
q
1 0 0 1 50.01575 180.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 63 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 15.23937 0 Td (Args:) Tj T* -15.23937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 69 cm
Q
q
1 0 0 1 91.03937 69 cm
Q
q
1 0 0 1 91.03937 57 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (i_dict \(dict\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (Progress dict.) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 91.03937 51 cm
Q
q
1 0 0 1 91.03937 39 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (nfound \(int\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (Total number of found progress items) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 91.03937 33 cm
Q
q
1 0 0 1 91.03937 21 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (total \(int\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (Total number of progress items) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 91.03937 15 cm
Q
q
1 0 0 1 91.03937 3 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (desc \(str\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (Progress description text to display.) Tj /F1 10 Tf (\)) Tj T* ET
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1 0 0 1 91.03937 3 cm
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1 0 0 1 40.01575 174.0394 cm
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BT 1 0 0 1 0 2 Tm 12 TL /F4 10 Tf 0 0 0 rg (moseq2_app.gui.progress.) Tj /F5 10 Tf (update_pickle_log) Tj /F1 10 Tf ( \() Tj (log_dict) Tj (\)) Tj T* ET
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q
1 0 0 1 40.01575 144.0394 cm
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BT 1 0 0 1 0 2 Tm 12 TL /F4 10 Tf 0 0 0 rg (moseq2_app.gui.progress.) Tj /F5 10 Tf (update_progress) Tj /F1 10 Tf ( \() Tj (progress_file) Tj (, varK) Tj (, varV) Tj (\)) Tj T* ET
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1 0 0 1 50.01575 132.0394 cm
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BT 1 0 0 1 0 2 Tm 12 TL /F1 10 Tf 0 0 0 rg (Updates progress file with new notebook variable) Tj T* ET
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BT /F1 10 Tf 12 TL ET
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1 0 0 1 6 45 cm
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0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 15.23937 0 Td (Args:) Tj T* -15.23937 0 Td ET
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1 0 0 1 91.03937 51 cm
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1 0 0 1 91.03937 51 cm
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1 0 0 1 91.03937 39 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
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1 0 0 1 6 -3 cm
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0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
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Q
q
1 0 0 1 23 -3 cm
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BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (progress_file \(str\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (path to progress file) Tj /F1 10 Tf (\)) Tj T* ET
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1 0 0 1 91.03937 33 cm
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1 0 0 1 91.03937 21 cm
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BT /F1 10 Tf 12 TL ET
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1 0 0 1 6 -3 cm
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0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
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1 0 0 1 23 -3 cm
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BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (varK \(str\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (key in progress file to update) Tj /F1 10 Tf (\)) Tj T* ET
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1 0 0 1 91.03937 15 cm
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1 0 0 1 91.03937 3 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
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1 0 0 1 6 -3 cm
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0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
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1 0 0 1 23 -3 cm
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BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (varV \(str\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (updated value to write) Tj /F1 10 Tf (\)) Tj T* ET
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0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL (Welcome to moseq2-app\222s documentation!) Tj T* ET
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BT /F1 10 Tf 12 TL ET
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0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 31.92937 0 Td (Returns:) Tj T* -31.92937 0 Td ET
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1 0 0 1 91.03937 3 cm
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0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL (progress \(dict\)) Tj T* ET
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BT /F1 10 Tf 12 TL ET
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1 0 0 1 6 3 cm
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0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 14.14937 0 Td (Return type:) Tj T* -14.14937 0 Td ET
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0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL (Loaded path dict from the progress yaml file.) Tj T* ET
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BT 1 0 0 1 0 14 Tm .55694 Tw 12 TL /F1 10 Tf 0 0 0 rg (This module contains the widget components that comprise the group setting table functionality. These widgets will) Tj T* 0 Tw (work in tandem with the qgrid functionality to facilitate the real time updates.) Tj T* ET
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1 0 0 1 40.01575 691.8394 cm
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1 0 0 1 40.01575 673.8394 cm
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BT 1 0 0 1 0 2 Tm 12 TL /F6 10 Tf 0 0 0 rg (class ) Tj /F4 10 Tf (moseq2_app.gui.widgets.) Tj /F5 10 Tf (GroupSettingWidgets) Tj T* ET
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BT 1 0 0 1 0 2 Tm 12 TL /F1 10 Tf 0 0 0 rg (Bases: ) Tj /F5 10 Tf (object) Tj T* ET
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BT 1 0 0 1 0 2.2 Tm 13.2 TL /F3 11 Tf .12549 .262745 .360784 rg (GUI - Wrappers Module) Tj T* ET
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1 0 0 1 40.01575 602.6394 cm
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BT 1 0 0 1 0 14 Tm 2.264578 Tw 12 TL /F1 10 Tf 0 0 0 rg (Wrapper functions for all the functionality included in moseq2-app. These functions are executed directly from) Tj T* 0 Tw (main.py.) Tj T* ET
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1 0 0 1 40.01575 596.6394 cm
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1 0 0 1 40.01575 572.6394 cm
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BT 1 0 0 1 0 14 Tm 12 TL /F4 10 Tf 0 0 0 rg (moseq2_app.gui.wrappers.) Tj /F5 10 Tf (get_frame_flips_wrapper) Tj /F1 10 Tf ( \() Tj (input_dir) Tj (, output_file) Tj (, max_frames) Tj (=) Tj (1000000.0) Tj (,) Tj T* (tail_filter_iters) Tj (=) Tj (1) Tj (, space_filter_size) Tj (=) Tj (3) Tj (, continuous_slider_update) Tj (=) Tj (True) Tj (\)) Tj T* ET
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Q
q
1 0 0 1 50.01575 560.6394 cm
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BT 1 0 0 1 0 2 Tm 12 TL /F1 10 Tf 0 0 0 rg (Wrapper function that facilitates the interactive) Tj T* ET
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1 0 0 1 50.01575 554.6394 cm
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q
1 0 0 1 50.01575 461.6394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
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1 0 0 1 6 81 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 15.23937 0 Td (Args:) Tj T* -15.23937 0 Td ET
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1 0 0 1 91.03937 87 cm
Q
q
1 0 0 1 91.03937 87 cm
Q
q
1 0 0 1 91.03937 75 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (input_dir \(str\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (Input directory containing extracted session folders.) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 91.03937 69 cm
Q
q
1 0 0 1 91.03937 57 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (output_file \(str\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (Path to save flip classifier in.) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 91.03937 51 cm
Q
q
1 0 0 1 91.03937 39 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (max_frames \(int\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (Maximum number of frames to load from the extracted data.) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 91.03937 33 cm
Q
q
1 0 0 1 91.03937 21 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (tail_filter_iters \(int\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (Number of tail filtering iterations) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
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q
1 0 0 1 91.03937 15 cm
Q
q
1 0 0 1 91.03937 3 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (prefilter_kernel_size \(int\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (Size of the median spatial filter.) Tj /F1 10 Tf (\)) Tj T* ET
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Q
q
Q
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q
1 0 0 1 91.03937 3 cm
Q
q
Q
Q
q
1 0 0 1 50.01575 434.6394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 15 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 31.92937 0 Td (Returns:) Tj T* -31.92937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 3 cm
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BT 1 0 0 1 0 14 Tm 3.472472 Tw 12 TL /F2 10 Tf 0 0 0 rg (flip_finder \(FlipRangeTool\)) Tj /F1 10 Tf ( \226 hold the labeled accepted frame ranges and selected) Tj T* 0 Tw (paths/info.) Tj T* ET
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Q
q
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q
1 0 0 1 50.01575 419.6394 cm
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BT /F1 10 Tf 12 TL ET
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1 0 0 1 6 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 14.14937 0 Td (Return type:) Tj T* -14.14937 0 Td ET
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q
1 0 0 1 91.03937 3 cm
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0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL (Flip Classifier Training object that will be used throughout the notebook to) Tj T* ET
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q
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q
1 0 0 1 40.01575 377.6394 cm
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BT 1 0 0 1 0 26 Tm 12 TL /F4 10 Tf 0 0 0 rg (moseq2_app.gui.wrappers.) Tj /F5 10 Tf (interactive_crowd_movie_comparison_preview_wrapper) Tj /F1 10 Tf  T* (\() Tj (config_filepath) Tj (, index_path) Tj (, model_path) Tj (, syll_info_path) Tj (, output_dir) Tj (, df_path) Tj (=) Tj (None) Tj (, get_pdfs) Tj (=) Tj (True) Tj (,) Tj T* (load_parquet) Tj (=) Tj (False) Tj (\)) Tj T* ET
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Q
q
1 0 0 1 50.01575 353.6394 cm
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BT 1 0 0 1 0 14 Tm .081721 Tw 12 TL /F1 10 Tf 0 0 0 rg (Wrapper function that launches an interactive crowd movie comparison application. Uses ipywidgets and Bokeh to) Tj T* 0 Tw (facilitate real time user interaction.) Tj T* ET
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Q
q
1 0 0 1 50.01575 347.6394 cm
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q
1 0 0 1 50.01575 188.6394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
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1 0 0 1 6 147 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 15.23937 0 Td (Args:) Tj T* -15.23937 0 Td ET
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Q
q
1 0 0 1 91.03937 153 cm
Q
q
1 0 0 1 91.03937 153 cm
Q
q
1 0 0 1 91.03937 129 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 9 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 14 Tm 5.873858 Tw 12 TL /F2 10 Tf 0 0 0 rg (config_filepath \(str\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (path to config file containing crowd movie generation) Tj T* 0 Tw (parameters) Tj /F1 10 Tf (\)) Tj T* ET
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Q
q
Q
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1 0 0 1 91.03937 123 cm
Q
q
1 0 0 1 91.03937 111 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (index_path \(str\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (path to index file with paths to all the extracted sessions) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
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1 0 0 1 91.03937 105 cm
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q
1 0 0 1 91.03937 93 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
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BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (model_path \(str\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (path to trained model containing syllable labels.) Tj /F1 10 Tf (\)) Tj T* ET
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Q
q
Q
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1 0 0 1 91.03937 87 cm
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q
1 0 0 1 91.03937 75 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
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1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
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Q
q
1 0 0 1 23 -3 cm
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BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (syll_info_path \(str\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (path to syllable information file containing syllable labels) Tj /F1 10 Tf (\)) Tj T* ET
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Q
q
Q
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q
1 0 0 1 91.03937 69 cm
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q
1 0 0 1 91.03937 57 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
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1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
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BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (output_dir \(str\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (path to directory to store crowd movies) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 91.03937 51 cm
Q
q
1 0 0 1 91.03937 39 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (df_path \(str\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (optional path to pre-existing syllable information to plot) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 91.03937 33 cm
Q
q
1 0 0 1 91.03937 21 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (get_pdfs \(bool\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (indicates whether to compute and display position heatmaps) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 91.03937 15 cm
Q
q
1 0 0 1 91.03937 3 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (load_parquet \(bool\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (Indicates to load previously saved syllable data.) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 91.03937 3 cm
Q
q
Q
Q
q
1 0 0 1 40.01575 182.6394 cm
Q
q
1 0 0 1 40.01575 170.6394 cm
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BT 1 0 0 1 0 2 Tm 12 TL /F4 10 Tf 0 0 0 rg (moseq2_app.gui.wrappers.) Tj /F5 10 Tf (interactive_extraction_preview_wrapper) Tj /F1 10 Tf ( \() Tj (input_dir) Tj (\)) Tj T* ET
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Q
q
1 0 0 1 50.01575 146.6394 cm
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BT 1 0 0 1 0 14 Tm 3.084918 Tw 12 TL /F1 10 Tf 0 0 0 rg (Interactive extraction previewing tool. Upon extracted session selection, function automatically displays the) Tj T* 0 Tw (extraction mp4 video file.) Tj T* ET
Q
Q
q
1 0 0 1 50.01575 140.6394 cm
Q
q
1 0 0 1 50.01575 125.6394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 15.23937 0 Td (Args:) Tj T* -15.23937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 3 cm
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BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (input_dir \(str\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (path to base directory containing extraction directories) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 40.01575 119.6394 cm
Q
q
1 0 0 1 40.01575 107.6394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F4 10 Tf 0 0 0 rg (moseq2_app.gui.wrappers.) Tj /F5 10 Tf (interactive_group_setting_wrapper) Tj /F1 10 Tf ( \() Tj (index_filepath) Tj (\)) Tj T* ET
Q
Q
q
1 0 0 1 50.01575 95.63937 cm
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BT 1 0 0 1 0 2 Tm 12 TL /F1 10 Tf 0 0 0 rg (Wrapper function that handles the interactive group display and value updating.) Tj T* ET
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Q
q
1 0 0 1 50.01575 89.63937 cm
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q
1 0 0 1 50.01575 74.63937 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
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1 0 0 1 6 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 15.23937 0 Td (Args:) Tj T* -15.23937 0 Td ET
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Q
q
1 0 0 1 91.03937 3 cm
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BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (index_filepath \(str\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (Path to index file.) Tj /F1 10 Tf (\)) Tj T* ET
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1 0 0 1 40.01575 68.63937 cm
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1 0 0 1 34.01575 807.2126 cm
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0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL (Welcome to moseq2-app\222s documentation!) Tj T* ET
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1 0 0 1 34.01575 22.67717 cm
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0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL (12) Tj T* ET
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BT 1 0 0 1 0 14 Tm 12 TL /F4 10 Tf 0 0 0 rg (moseq2_app.gui.wrappers.) Tj /F5 10 Tf (interactive_plot_transition_graph_wrapper) Tj /F1 10 Tf ( \() Tj (model_path) Tj (, index_path) Tj (,) Tj T* (info_path) Tj (, df_path) Tj (=) Tj (None) Tj (, max_syllables) Tj (=) Tj (None) Tj (, plot_vertically) Tj (=) Tj (False) Tj (, load_parquet) Tj (=) Tj (False) Tj (\)) Tj T* ET
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BT 1 0 0 1 0 2 Tm 12 TL /F1 10 Tf 0 0 0 rg (Wrapper function that works as a background process that prepares the data for the interactive graphing function.) Tj T* ET
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q
1 0 0 1 50.01575 634.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 99 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 15.23937 0 Td (Args:) Tj T* -15.23937 0 Td ET
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1 0 0 1 91.03937 105 cm
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1 0 0 1 91.03937 105 cm
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1 0 0 1 91.03937 93 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
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1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (model_path \(str\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (Path to trained model.) Tj /F1 10 Tf (\)) Tj T* ET
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1 0 0 1 91.03937 87 cm
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1 0 0 1 91.03937 75 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
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1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
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1 0 0 1 23 -3 cm
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BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (index_path \(str\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (Path to index file containined trained data metadata.) Tj /F1 10 Tf (\)) Tj T* ET
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1 0 0 1 91.03937 69 cm
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1 0 0 1 91.03937 57 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
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1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
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1 0 0 1 23 -3 cm
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BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (info_path \(str\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (Path to user-labeled syllable information file.) Tj /F1 10 Tf (\)) Tj T* ET
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1 0 0 1 91.03937 51 cm
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1 0 0 1 91.03937 39 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
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1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
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1 0 0 1 23 -3 cm
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BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (df_path \(str\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (Path to pre-saved syllable information.) Tj /F1 10 Tf (\)) Tj T* ET
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1 0 0 1 91.03937 33 cm
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1 0 0 1 91.03937 21 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
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1 0 0 1 23 -3 cm
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BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (max_syllables \(int or None\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (Limit maximum number of displayed syllables.) Tj /F1 10 Tf (\)) Tj T* ET
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1 0 0 1 91.03937 15 cm
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1 0 0 1 91.03937 3 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
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1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
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1 0 0 1 23 -3 cm
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BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (load_parquet \(bool\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (Indicates to load previously saved data.) Tj /F1 10 Tf (\)) Tj T* ET
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1 0 0 1 91.03937 3 cm
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1 0 0 1 40.01575 628.0394 cm
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1 0 0 1 40.01575 604.0394 cm
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BT 1 0 0 1 0 14 Tm 12 TL /F4 10 Tf 0 0 0 rg (moseq2_app.gui.wrappers.) Tj /F5 10 Tf (interactive_roi_wrapper) Tj /F1 10 Tf ( \() Tj (data_path) Tj (, config_file) Tj (, session_config) Tj (=) Tj (None) Tj (,) Tj T* (compute_bgs) Tj (=) Tj (True) Tj (, autodetect_depths) Tj (=) Tj (False) Tj (\)) Tj T* ET
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1 0 0 1 50.01575 580.0394 cm
q
BT 1 0 0 1 0 14 Tm 2.817606 Tw 12 TL /F1 10 Tf 0 0 0 rg (Interactive ROI detection wrapper function. Users can use run this wrapper to find the required extraction) Tj T* 0 Tw (parameters, as well as preview examples of the extraction with the found parameters.) Tj T* ET
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1 0 0 1 50.01575 574.0394 cm
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1 0 0 1 50.01575 517.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
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1 0 0 1 6 45 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 15.23937 0 Td (Args:) Tj T* -15.23937 0 Td ET
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1 0 0 1 91.03937 51 cm
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1 0 0 1 91.03937 51 cm
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1 0 0 1 91.03937 39 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
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1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
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1 0 0 1 23 -3 cm
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BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (data_path \(str\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (Path to base directory containing session folders.) Tj /F1 10 Tf (\)) Tj T* ET
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1 0 0 1 91.03937 33 cm
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1 0 0 1 91.03937 21 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
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1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
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1 0 0 1 23 -3 cm
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BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (config_data \(dict\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (ROI and Extraction configuration parameters) Tj /F1 10 Tf (\)) Tj T* ET
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1 0 0 1 91.03937 15 cm
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1 0 0 1 91.03937 3 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
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1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
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1 0 0 1 23 -3 cm
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BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (session_parameters \(str\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (Path to file containing individual session parameter sets.) Tj /F1 10 Tf (\)) Tj T* ET
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1 0 0 1 91.03937 3 cm
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1 0 0 1 40.01575 511.0394 cm
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1 0 0 1 40.01575 487.0394 cm
q
BT 1 0 0 1 0 14 Tm 12 TL /F4 10 Tf 0 0 0 rg (moseq2_app.gui.wrappers.) Tj /F5 10 Tf (interactive_syllable_labeler_wrapper) Tj /F1 10 Tf ( \() Tj (model_path) Tj (, config_file) Tj (,) Tj T* (index_file) Tj (, crowd_movie_dir) Tj (, output_file) Tj (, max_syllables) Tj (=) Tj (None) Tj (, n_explained) Tj (=) Tj (99) Tj (\)) Tj T* ET
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1 0 0 1 50.01575 475.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F1 10 Tf 0 0 0 rg (Wrapper function to launch a syllable crowd movie preview and interactive labeling application.) Tj T* ET
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1 0 0 1 50.01575 469.0394 cm
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1 0 0 1 50.01575 394.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
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1 0 0 1 6 63 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 15.23937 0 Td (Args:) Tj T* -15.23937 0 Td ET
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1 0 0 1 91.03937 69 cm
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1 0 0 1 91.03937 69 cm
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1 0 0 1 91.03937 57 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
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1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
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1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (model_path \(str\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (Path to trained model.) Tj /F1 10 Tf (\)) Tj T* ET
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1 0 0 1 91.03937 51 cm
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1 0 0 1 91.03937 39 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
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1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
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1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (crowd_movie_dir \(str\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (Path to crowd movie directory) Tj /F1 10 Tf (\)) Tj T* ET
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1 0 0 1 91.03937 33 cm
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1 0 0 1 91.03937 21 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
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1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
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1 0 0 1 23 -3 cm
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BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (output_file \(str\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (Path to syllable label information file) Tj /F1 10 Tf (\)) Tj T* ET
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1 0 0 1 91.03937 15 cm
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1 0 0 1 91.03937 3 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
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1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
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1 0 0 1 23 -3 cm
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BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (max_syllables \(int\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (Maximum number of syllables to preview and label.) Tj /F1 10 Tf (\)) Tj T* ET
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1 0 0 1 91.03937 3 cm
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1 0 0 1 40.01575 388.0394 cm
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1 0 0 1 40.01575 364.0394 cm
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BT 1 0 0 1 0 14 Tm 12 TL /F4 10 Tf 0 0 0 rg (moseq2_app.gui.wrappers.) Tj /F5 10 Tf (interactive_syllable_stat_wrapper) Tj /F1 10 Tf ( \() Tj (index_path) Tj (, model_path) Tj (, info_path) Tj (,) Tj T* (df_path) Tj (=) Tj (None) Tj (, max_syllables) Tj (=) Tj (None) Tj (, load_parquet) Tj (=) Tj (False) Tj (\)) Tj T* ET
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1 0 0 1 50.01575 328.0394 cm
q
BT 1 0 0 1 0 26 Tm 1.983381 Tw 12 TL /F1 10 Tf 0 0 0 rg (Wrapper function to launch the interactive syllable statistics API. Users will be able to view different syllable) Tj T* 0 Tw .166123 Tw (statistics, sort them according to their metric of choice, and dynamically group the data to view individual sessions) Tj T* 0 Tw (or group averages.) Tj T* ET
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1 0 0 1 50.01575 322.0394 cm
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1 0 0 1 50.01575 229.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
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1 0 0 1 6 81 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 15.23937 0 Td (Args:) Tj T* -15.23937 0 Td ET
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1 0 0 1 91.03937 87 cm
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1 0 0 1 91.03937 87 cm
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1 0 0 1 91.03937 75 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
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1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (index_path \(str\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (Path to index file.) Tj /F1 10 Tf (\)) Tj T* ET
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1 0 0 1 91.03937 69 cm
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1 0 0 1 91.03937 57 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
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1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (model_path \(str\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (Path to trained model file.) Tj /F1 10 Tf (\)) Tj T* ET
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1 0 0 1 91.03937 51 cm
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1 0 0 1 91.03937 39 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
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1 0 0 1 23 -3 cm
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BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (info_path \(str\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (Path to syllable information file.) Tj /F1 10 Tf (\)) Tj T* ET
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1 0 0 1 91.03937 33 cm
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1 0 0 1 91.03937 21 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
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1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
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1 0 0 1 23 -3 cm
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BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (max_syllables \(int\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (Maximum number of syllables to plot.) Tj /F1 10 Tf (\)) Tj T* ET
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1 0 0 1 91.03937 15 cm
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1 0 0 1 91.03937 3 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
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1 0 0 1 23 -3 cm
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BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (load_parquet \(bool\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (Indicates to load previously loaded data) Tj /F1 10 Tf (\)) Tj T* ET
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1 0 0 1 91.03937 3 cm
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1 0 0 1 40.01575 223.0394 cm
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1 0 0 1 40.01575 211.0394 cm
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BT 1 0 0 1 0 2 Tm 12 TL /F4 10 Tf 0 0 0 rg (moseq2_app.gui.wrappers.) Tj /F5 10 Tf (validate_extractions_wrapper) Tj /F1 10 Tf ( \() Tj (input_dir) Tj (\)) Tj T* ET
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1 0 0 1 50.01575 195.0394 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL (Wrapper function to test the measured scalar values to determine whether some sessions should be) Tj T* ET
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1 0 0 1 50.01575 180.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
BT 1 0 0 1 0 2 Tm  T* ET
q
1 0 0 1 20 0 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F1 10 Tf 0 0 0 rg (flagged and diagnosed before aggregating the sessions.) Tj T* ET
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1 0 0 1 50.01575 174.0394 cm
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1 0 0 1 50.01575 159.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 15.23937 0 Td (Args:) Tj T* -15.23937 0 Td ET
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1 0 0 1 91.03937 3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (input_dir \(str\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (path to parent directory containing all the extracted session folders) Tj /F1 10 Tf (\)) Tj T* ET
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1 0 0 1 34.01575 807.2126 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL (Welcome to moseq2-app\222s documentation!) Tj T* ET
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1 0 0 1 34.01575 22.67717 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL (13) Tj T* ET
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1 0 0 1 0 0 cm  BT /F1 12 Tf 14.4 TL ET
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1 0 0 1 40.01575 773.8394 cm
q
.8 .8 .8 RG
.3 w
.94902 .94902 .94902 rg
n -10 0 525.2441 19.2 re B*
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q
BT 1 0 0 1 0 2.2 Tm 13.2 TL /F3 11 Tf .12549 .262745 .360784 rg (Module contents) Tj T* ET
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1 0 0 1 40.01575 743.4394 cm
q
.8 .8 .8 RG
.3 w
.94902 .94902 .94902 rg
n -10 0 525.2441 20.4 re B*
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BT 1 0 0 1 0 2.4 Tm 14.4 TL /F3 12 Tf .12549 .262745 .360784 rg (moseq2_app.stat package) Tj T* ET
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1 0 0 1 40.01575 714.2394 cm
q
.8 .8 .8 RG
.3 w
.94902 .94902 .94902 rg
n -10 0 525.2441 19.2 re B*
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.12549 .262745 .360784 rg
BT 1 0 0 1 0 2.2 Tm /F3 11 Tf 13.2 TL (Submodules) Tj T* ET
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1 0 0 1 40.01575 685.0394 cm
q
.8 .8 .8 RG
.3 w
.94902 .94902 .94902 rg
n -10 0 525.2441 19.2 re B*
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BT 1 0 0 1 0 2.2 Tm 13.2 TL /F3 11 Tf .12549 .262745 .360784 rg (Stats - Controller Module) Tj T* ET
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1 0 0 1 40.01575 655.0394 cm
q
BT 1 0 0 1 0 14 Tm 2.506175 Tw 12 TL /F1 10 Tf 0 0 0 rg (Main interactive model syllable statistics results application functionality. This module facilitates the interactive) Tj T* 0 Tw (functionality for the statistics plotting, and) Tj T* ET
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1 0 0 1 40.01575 649.0394 cm
Q
q
1 0 0 1 40.01575 637.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
BT 1 0 0 1 0 2 Tm  T* ET
q
1 0 0 1 20 0 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL (transition graph features.) Tj T* ET
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1 0 0 1 40.01575 637.0394 cm
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1 0 0 1 40.01575 631.0394 cm
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1 0 0 1 40.01575 601.0394 cm
q
BT 1 0 0 1 0 14 Tm 7.286024 Tw 12 TL /F6 10 Tf 0 0 0 rg (class ) Tj /F4 10 Tf (moseq2_app.stat.controller.) Tj /F5 10 Tf (InteractiveSyllableStats) Tj /F1 10 Tf ( \() Tj (index_path) Tj (, model_path) Tj (, df_path) Tj (,) Tj T* 0 Tw (info_path) Tj (, max_sylls) Tj (, load_parquet) Tj (\)) Tj T* ET
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1 0 0 1 50.01575 589.0394 cm
q
.933333 1 .8 rg
n 33.35 0 258 12 re f*
BT 1 0 0 1 0 2 Tm 12 TL /F1 10 Tf 0 0 0 rg (Bases: ) Tj /F5 10 Tf (moseq2_app.stat.widgets.SyllableStatWidgets) Tj T* ET
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1 0 0 1 50.01575 573.0394 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL (Interactive Syllable Statistics grapher class that holds the context for the current) Tj T* ET
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1 0 0 1 50.01575 558.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
BT 1 0 0 1 0 2 Tm  T* ET
q
1 0 0 1 20 0 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL (inputted session.) Tj T* ET
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1 0 0 1 50.01575 552.0394 cm
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1 0 0 1 50.01575 534.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F5 10 Tf 0 0 0 rg (clear_on_click) Tj /F2 10 Tf ( \() Tj /F1 10 Tf (b) Tj /F2 10 Tf (\)) Tj T* ET
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1 0 0 1 60.01575 522.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F1 10 Tf 0 0 0 rg (Clears the cell output) Tj T* ET
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1 0 0 1 60.01575 516.0394 cm
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1 0 0 1 60.01575 501.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 15.23937 0 Td (Args:) Tj T* -15.23937 0 Td ET
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1 0 0 1 91.03937 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL (b \(button click\)) Tj T* ET
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1 0 0 1 50.01575 495.0394 cm
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1 0 0 1 50.01575 477.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F5 10 Tf 0 0 0 rg (compute_dendrogram) Tj /F2 10 Tf ( \(\)) Tj T* ET
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1 0 0 1 60.01575 453.0394 cm
q
BT 1 0 0 1 0 14 Tm .599546 Tw 12 TL /F1 10 Tf 0 0 0 rg (Computes the pairwise distances between the included model AR-states, and generates the graph information) Tj T* 0 Tw (to be plotted after the stats.) Tj T* ET
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1 0 0 1 50.01575 447.0394 cm
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1 0 0 1 50.01575 429.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F5 10 Tf 0 0 0 rg (interactive_stat_helper) Tj /F2 10 Tf ( \(\)) Tj T* ET
Q
Q
q
1 0 0 1 60.01575 413.0394 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL (Computes and saves the all the relevant syllable information to be displayed.) Tj T* ET
Q
Q
q
1 0 0 1 60.01575 398.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
BT 1 0 0 1 0 2 Tm  T* ET
q
1 0 0 1 20 0 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F1 10 Tf 0 0 0 rg (Loads the syllable information dict and merges it with the syllable statistics DataFrame.) Tj T* ET
Q
Q
q
Q
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q
1 0 0 1 50.01575 392.0394 cm
Q
q
1 0 0 1 50.01575 374.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F5 10 Tf 0 0 0 rg (interactive_syll_stats_grapher) Tj /F2 10 Tf ( \() Tj /F1 10 Tf (stat) Tj /F2 10 Tf (, ) Tj /F1 10 Tf (sort) Tj /F2 10 Tf (, ) Tj /F1 10 Tf (groupby) Tj /F2 10 Tf (, ) Tj /F1 10 Tf (errorbar) Tj /F2 10 Tf (, ) Tj /F1 10 Tf (sessions) Tj /F2 10 Tf (, ) Tj /F1 10 Tf (ctrl_group) Tj /F2 10 Tf (, ) Tj /F1 10 Tf (exp_group) Tj /F2 10 Tf (\)) Tj T* ET
Q
Q
q
1 0 0 1 60.01575 358.0394 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL (Helper function that is responsible for handling ipywidgets interactions and updating the currently) Tj T* ET
Q
Q
q
1 0 0 1 60.01575 343.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
BT 1 0 0 1 0 2 Tm  T* ET
q
1 0 0 1 20 0 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F1 10 Tf 0 0 0 rg (displayed Bokeh plot.) Tj T* ET
Q
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q
Q
Q
q
1 0 0 1 60.01575 337.0394 cm
Q
q
1 0 0 1 60.01575 136.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 189 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 15.23937 0 Td (Args:) Tj T* -15.23937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 195 cm
Q
q
1 0 0 1 91.03937 195 cm
Q
q
1 0 0 1 91.03937 183 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (stat \(str or ipywidgets.DropDown\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (Statistic to plot: [\221usage\222, \221distance to center\222]) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 91.03937 177 cm
Q
q
1 0 0 1 91.03937 153 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 9 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 14 Tm 1.956472 Tw 12 TL /F2 10 Tf 0 0 0 rg (sort \(str or ipywidgets.DropDown\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (Statistic to sort syllables by \(in descending) Tj T* 0 Tw (order\).) Tj /F1 10 Tf (\) \226 [\221usage\222, \221distance to center\222, \221similarity\222, \221difference\222].) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 91.03937 147 cm
Q
q
1 0 0 1 91.03937 123 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 9 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 14 Tm 1.788472 Tw 12 TL /F2 10 Tf 0 0 0 rg (groupby \(str or ipywidgets.DropDown\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (Data to plot; either group averages, or) Tj T* 0 Tw (individual session data.) Tj /F1 10 Tf (\)) Tj T* ET
Q
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q
Q
Q
q
1 0 0 1 91.03937 117 cm
Q
q
1 0 0 1 91.03937 93 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 9 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 14 Tm 2.291472 Tw 12 TL /F2 10 Tf 0 0 0 rg (errorbar \(str or ipywidgets.DropDown\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (Error bar to display. [\221CI 95%\222 ,\222SEM\222,) Tj T* 0 Tw (\221STD\222]) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 91.03937 87 cm
Q
q
1 0 0 1 91.03937 63 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 9 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 14 Tm .395472 Tw 12 TL /F2 10 Tf 0 0 0 rg (sessions \(list or ipywidgets.MultiSelect\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (List of selected sessions to display data) Tj T* 0 Tw (from.) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 91.03937 57 cm
Q
q
1 0 0 1 91.03937 33 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 9 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 14 Tm 2.852747 Tw 12 TL /F2 10 Tf 0 0 0 rg (ctrl_group \(str or ipywidgets.DropDown\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (Name of control group to compute) Tj T* 0 Tw (group difference sorting with.) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 91.03937 27 cm
Q
q
1 0 0 1 91.03937 3 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 9 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 14 Tm -0.049475 Tw 12 TL /F2 10 Tf 0 0 0 rg (exp_group \(str or ipywidgets.DropDown\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (Name of comparative group to compute) Tj T* 0 Tw (group difference sorting with.) Tj /F1 10 Tf (\)) Tj T* ET
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q
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q
1 0 0 1 91.03937 3 cm
Q
q
Q
Q
q
1 0 0 1 50.01575 130.0394 cm
Q
q
1 0 0 1 50.01575 112.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F5 10 Tf 0 0 0 rg (on_grouping_update) Tj /F2 10 Tf ( \() Tj /F1 10 Tf (event) Tj /F2 10 Tf (\)) Tj T* ET
Q
Q
q
1 0 0 1 60.01575 88.03937 cm
q
BT 1 0 0 1 0 14 Tm -0.077565 Tw 12 TL /F1 10 Tf 0 0 0 rg (Updates the MultipleSelect widget upon selecting groupby == SubjectName or SessionName. Hides it if groupby) Tj T* 0 Tw (== group.) Tj T* ET
Q
Q
q
1 0 0 1 60.01575 82.03937 cm
Q
q
1 0 0 1 60.01575 67.03937 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 15.23937 0 Td (Args:) Tj T* -15.23937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL (event \(user clicks new grouping\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 40.01575 61.03937 cm
Q
q
1 0 0 1 34.01575 807.2126 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL (Welcome to moseq2-app\222s documentation!) Tj T* ET
Q
Q
q
1 0 0 1 34.01575 22.67717 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL (14) Tj T* ET
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endstream
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1 0 0 1 0 0 cm  BT /F1 12 Tf 14.4 TL ET
q
1 0 0 1 40.01575 763.0394 cm
q
BT 1 0 0 1 0 14 Tm 2.341024 Tw 12 TL /F6 10 Tf 0 0 0 rg (class ) Tj /F4 10 Tf (moseq2_app.stat.controller.) Tj /F5 10 Tf (InteractiveTransitionGraph) Tj /F1 10 Tf ( \() Tj (model_path) Tj (, index_path) Tj (, info_path) Tj (,) Tj T* 0 Tw (df_path) Tj (, max_sylls) Tj (, plot_vertically) Tj (, load_parquet) Tj (\)) Tj T* ET
Q
Q
q
1 0 0 1 50.01575 751.0394 cm
q
.933333 1 .8 rg
n 33.35 0 276 12 re f*
BT 1 0 0 1 0 2 Tm 12 TL /F1 10 Tf 0 0 0 rg (Bases: ) Tj /F5 10 Tf (moseq2_app.stat.widgets.TransitionGraphWidgets) Tj T* ET
Q
Q
q
1 0 0 1 50.01575 739.0394 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL (Interactive transition graph class used to facilitate interactive graph generation and thresholding functionality.) Tj T* ET
Q
Q
q
1 0 0 1 50.01575 733.0394 cm
Q
q
1 0 0 1 50.01575 715.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F5 10 Tf 0 0 0 rg (clear_on_click) Tj /F2 10 Tf ( \() Tj /F1 10 Tf (b) Tj /F2 10 Tf (\)) Tj T* ET
Q
Q
q
1 0 0 1 60.01575 703.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F1 10 Tf 0 0 0 rg (Clears the cell output) Tj T* ET
Q
Q
q
1 0 0 1 60.01575 697.0394 cm
Q
q
1 0 0 1 60.01575 682.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 15.23937 0 Td (Args:) Tj T* -15.23937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL (b \(button click\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 50.01575 676.0394 cm
Q
q
1 0 0 1 50.01575 658.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F5 10 Tf 0 0 0 rg (compute_entropies) Tj /F2 10 Tf ( \() Tj /F1 10 Tf (labels) Tj /F2 10 Tf (, ) Tj /F1 10 Tf (label_group) Tj /F2 10 Tf (\)) Tj T* ET
Q
Q
q
1 0 0 1 60.01575 646.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F1 10 Tf 0 0 0 rg (Compute individual syllable entropy and transition entropy rates for all sessions with in a label_group.) Tj T* ET
Q
Q
q
1 0 0 1 60.01575 640.0394 cm
Q
q
1 0 0 1 60.01575 601.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 27 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 15.23937 0 Td (Args:) Tj T* -15.23937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 33 cm
Q
q
1 0 0 1 91.03937 33 cm
Q
q
1 0 0 1 91.03937 21 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (labels \(2d list\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (list of session syllable labels over time.) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 91.03937 15 cm
Q
q
1 0 0 1 91.03937 3 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (label_group \(list\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (list of groups computing entropies for.) Tj /F1 10 Tf (\)) Tj T* ET
Q
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q
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1 0 0 1 91.03937 3 cm
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q
Q
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q
1 0 0 1 50.01575 595.0394 cm
Q
q
1 0 0 1 50.01575 577.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F5 10 Tf 0 0 0 rg (compute_entropy_differences) Tj /F2 10 Tf ( \(\)) Tj T* ET
Q
Q
q
1 0 0 1 60.01575 561.0394 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL (Computes cross group entropy/entropy-rate differences) Tj T* ET
Q
Q
q
1 0 0 1 60.01575 546.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
BT 1 0 0 1 0 2 Tm  T* ET
q
1 0 0 1 20 0 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F1 10 Tf 0 0 0 rg (and casts them to OrderedDict objects) Tj T* ET
Q
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q
Q
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q
1 0 0 1 50.01575 540.0394 cm
Q
q
1 0 0 1 50.01575 522.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F5 10 Tf 0 0 0 rg (initialize_transition_data) Tj /F2 10 Tf ( \(\)) Tj T* ET
Q
Q
q
1 0 0 1 60.01575 506.0394 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL (Performs all necessary pre-processing to compute the transition graph data and) Tj T* ET
Q
Q
q
1 0 0 1 60.01575 491.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
BT 1 0 0 1 0 2 Tm  T* ET
q
1 0 0 1 20 0 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F1 10 Tf 0 0 0 rg (syllable metadata to display via HoverTool.) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 60.01575 475.0394 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL (Stores the syll_info dict, groups to explore, maximum number of syllables, and) Tj T* ET
Q
Q
q
1 0 0 1 60.01575 460.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
BT 1 0 0 1 0 2 Tm  T* ET
q
1 0 0 1 20 0 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL (the respective transition graphs and syllable scalars associated.) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 50.01575 454.0394 cm
Q
q
1 0 0 1 50.01575 424.0394 cm
q
BT 1 0 0 1 0 14 Tm 11.55852 Tw 12 TL /F5 10 Tf 0 0 0 rg (interactive_transition_graph_helper) Tj /F2 10 Tf ( \() Tj /F1 10 Tf (layout) Tj /F2 10 Tf (, ) Tj /F1 10 Tf (scalar_color) Tj /F2 10 Tf (, ) Tj /F1 10 Tf (edge_threshold) Tj /F2 10 Tf (, ) Tj /F1 10 Tf (usage_threshold) Tj /F2 10 Tf (,) Tj T* 0 Tw /F1 10 Tf (speed_threshold) Tj /F2 10 Tf (\)) Tj T* ET
Q
Q
q
1 0 0 1 60.01575 400.0394 cm
q
BT 1 0 0 1 0 14 Tm 1.191007 Tw 12 TL /F1 10 Tf 0 0 0 rg (Helper function that generates all the transition graphs given the currently selected thresholding values, then) Tj T* 0 Tw (displays them in a Jupyter notebook or web page.) Tj T* ET
Q
Q
q
1 0 0 1 60.01575 394.0394 cm
Q
q
1 0 0 1 60.01575 301.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 81 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 15.23937 0 Td (Args:) Tj T* -15.23937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 87 cm
Q
q
1 0 0 1 91.03937 87 cm
Q
q
1 0 0 1 91.03937 63 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 9 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 14 Tm 3.358945 Tw 12 TL /F2 10 Tf 0 0 0 rg (edge_threshold \(tuple or ipywidgets.FloatRangeSlider\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (Transition probability) Tj T* 0 Tw (range to include in graphs.) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 91.03937 57 cm
Q
q
1 0 0 1 91.03937 33 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 9 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 14 Tm 1.684121 Tw 12 TL /F2 10 Tf 0 0 0 rg (usage_threshold \(tuple or ipywidgets.FloatRangeSlider\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (Syllable usage range) Tj T* 0 Tw (to include in graphs.) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 91.03937 27 cm
Q
q
1 0 0 1 91.03937 3 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 9 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 14 Tm 1.684121 Tw 12 TL /F2 10 Tf 0 0 0 rg (speed_threshold \(tuple or ipywidgets.FloatRangeSlider\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (Syllable speed range) Tj T* 0 Tw (to include in graphs.) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 91.03937 3 cm
Q
q
Q
Q
q
1 0 0 1 50.01575 295.0394 cm
Q
q
1 0 0 1 50.01575 277.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F5 10 Tf 0 0 0 rg (on_set_scalar) Tj /F2 10 Tf ( \() Tj /F1 10 Tf (event) Tj /F2 10 Tf (\)) Tj T* ET
Q
Q
q
1 0 0 1 60.01575 253.0394 cm
q
BT 1 0 0 1 0 14 Tm -0.096818 Tw 12 TL /F1 10 Tf 0 0 0 rg (Updates the scalar threshold slider filter criteria according to the current node coloring. Changes the name of the) Tj T* 0 Tw (slider as well.) Tj T* ET
Q
Q
q
1 0 0 1 60.01575 247.0394 cm
Q
q
1 0 0 1 60.01575 232.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 15.23937 0 Td (Args:) Tj T* -15.23937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (event \(dropdown event\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (User changes selected dropdown value) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 50.01575 226.0394 cm
Q
q
1 0 0 1 50.01575 208.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F5 10 Tf 0 0 0 rg (set_range_widget_values) Tj /F2 10 Tf ( \(\)) Tj T* ET
Q
Q
q
1 0 0 1 60.01575 192.0394 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL (After the dataset is initialized, the threshold range sliders\222 values will be set) Tj T* ET
Q
Q
q
1 0 0 1 60.01575 177.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
BT 1 0 0 1 0 2 Tm  T* ET
q
1 0 0 1 20 0 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F1 10 Tf 0 0 0 rg (according to the standard deviations of the dataset.) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 40.01575 147.8394 cm
q
.8 .8 .8 RG
.3 w
.94902 .94902 .94902 rg
n -10 0 525.2441 19.2 re B*
Q
q
BT 1 0 0 1 0 2.2 Tm 13.2 TL /F3 11 Tf .12549 .262745 .360784 rg (Stats - View Module) Tj T* ET
Q
Q
q
1 0 0 1 40.01575 129.8394 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL (View module to facilitate graphing of interactive statistics tools: the Dendrogram, statistics plot,) Tj T* ET
Q
Q
q
1 0 0 1 40.01575 114.8394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
BT 1 0 0 1 0 2 Tm  T* ET
q
1 0 0 1 20 0 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F1 10 Tf 0 0 0 rg (and transition graph grid. Module primarily uses Bokeh to facilitate the interactive graphing functionality.) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 40.01575 108.8394 cm
Q
q
1 0 0 1 40.01575 84.83937 cm
q
BT 1 0 0 1 0 14 Tm 12 TL /F4 10 Tf 0 0 0 rg (moseq2_app.stat.view.) Tj /F5 10 Tf (bokeh_plotting) Tj /F1 10 Tf ( \() Tj (df) Tj (, stat) Tj (, sorting) Tj (, mean_df) Tj (=) Tj (None) Tj (, groupby) Tj (=) Tj ('group') Tj (, errorbar) Tj (=) Tj ('SEM') Tj (,) Tj T* (syllable_families) Tj (=) Tj (None) Tj (, sort_name) Tj (=) Tj ('usage') Tj (\)) Tj T* ET
Q
Q
q
1 0 0 1 50.01575 60.83937 cm
q
BT 1 0 0 1 0 14 Tm .039606 Tw 12 TL /F1 10 Tf 0 0 0 rg (Generates a Bokeh plot with interactive tools such as the HoverTool, which displays additional syllable information) Tj T* 0 Tw (and the associated crowd movie.) Tj T* ET
Q
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1 0 0 1 50.01575 54.85039 cm
Q
q
1 0 0 1 34.01575 807.2126 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL (Welcome to moseq2-app\222s documentation!) Tj T* ET
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Q
q
1 0 0 1 34.01575 22.67717 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL (15) Tj T* ET
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endstream
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<<
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stream
1 0 0 1 0 0 cm  BT /F1 12 Tf 14.4 TL ET
q
1 0 0 1 50.01575 646.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 129 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 15.23937 0 Td (Args:) Tj T* -15.23937 0 Td ET
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q
1 0 0 1 91.03937 135 cm
Q
q
1 0 0 1 91.03937 135 cm
Q
q
1 0 0 1 91.03937 123 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
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q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (df \(pd.DataFrame\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (Mean syllable statistic DataFrame.) Tj /F1 10 Tf (\)) Tj T* ET
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1 0 0 1 91.03937 117 cm
Q
q
1 0 0 1 91.03937 105 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
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q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (stat \(str\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (Statistic to plot) Tj /F1 10 Tf (\)) Tj T* ET
Q
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q
1 0 0 1 91.03937 99 cm
Q
q
1 0 0 1 91.03937 87 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (sorting \(list\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (List of the current/selected syllable ordering) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
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q
1 0 0 1 91.03937 81 cm
Q
q
1 0 0 1 91.03937 57 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 9 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 14 Tm .04248 Tw 12 TL /F2 10 Tf 0 0 0 rg (groupby \(str\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (Value to group data by. Either by unique group name, session name, or) Tj T* 0 Tw (subject name.) Tj /F1 10 Tf (\)) Tj T* ET
Q
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q
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q
1 0 0 1 91.03937 51 cm
Q
q
1 0 0 1 91.03937 39 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
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q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (errorbar \(str\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (Error bar type to display) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 91.03937 33 cm
Q
q
1 0 0 1 91.03937 21 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (syllable_families \(dict\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (dict containing cladogram figure) Tj /F1 10 Tf (\)) Tj T* ET
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q
Q
Q
q
1 0 0 1 91.03937 15 cm
Q
q
1 0 0 1 91.03937 3 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
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q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (sort_name \(str\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (Syllable sorting name displayed in title.) Tj /F1 10 Tf (\)) Tj T* ET
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1 0 0 1 91.03937 3 cm
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q
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Q
q
1 0 0 1 50.01575 631.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 31.92937 0 Td (Returns:) Tj T* -31.92937 0 Td ET
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Q
q
1 0 0 1 91.03937 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL (p \(bokeh figure\)) Tj T* ET
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q
Q
Q
q
1 0 0 1 50.01575 616.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 14.14937 0 Td (Return type:) Tj T* -14.14937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL (Displayed stat plot with optional color pickers.) Tj T* ET
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q
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q
1 0 0 1 40.01575 610.0394 cm
Q
q
1 0 0 1 40.01575 598.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F4 10 Tf 0 0 0 rg (moseq2_app.stat.view.) Tj /F5 10 Tf (clamp) Tj /F1 10 Tf ( \() Tj (val) Tj (, minimum) Tj (=) Tj (0) Tj (, maximum) Tj (=) Tj (255) Tj (\)) Tj T* ET
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Q
q
1 0 0 1 50.01575 586.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F1 10 Tf 0 0 0 rg (Caps the given R/G/B value to set min and max values) Tj T* ET
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Q
q
1 0 0 1 50.01575 574.0394 cm
q
0 0 .501961 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL (https://thadeusb.com/weblog/2010/10/10/python_scale_hex_color/) Tj T* ET
Q
Q
q
1 0 0 1 50.01575 568.0394 cm
Q
q
1 0 0 1 50.01575 511.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 45 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 15.23937 0 Td (Args:) Tj T* -15.23937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 51 cm
Q
q
1 0 0 1 91.03937 51 cm
Q
q
1 0 0 1 91.03937 39 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
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Q
q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (val \(float\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (value for given color tuple member) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 91.03937 33 cm
Q
q
1 0 0 1 91.03937 21 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (minimum \(int\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (min thresholding value) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 91.03937 15 cm
Q
q
1 0 0 1 91.03937 3 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (maximum \(int\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (max thresholding value) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 91.03937 3 cm
Q
q
Q
Q
q
1 0 0 1 50.01575 496.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 31.92937 0 Td (Returns:) Tj T* -31.92937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL (val \(int\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 50.01575 481.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 14.14937 0 Td (Return type:) Tj T* -14.14937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL (thresholded color tuple member) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 40.01575 475.0394 cm
Q
q
1 0 0 1 40.01575 463.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F4 10 Tf 0 0 0 rg (moseq2_app.stat.view.) Tj /F5 10 Tf (colorscale) Tj /F1 10 Tf ( \() Tj (hexstr) Tj (, scalefactor) Tj (\)) Tj T* ET
Q
Q
q
1 0 0 1 50.01575 451.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F1 10 Tf 0 0 0 rg (Scales a hex string by ) Tj /F4 10 Tf (scalefactor) Tj /F1 10 Tf (. Returns scaled hex string.) Tj T* ET
Q
Q
q
1 0 0 1 50.01575 439.0394 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL (To darken the color, use a float value between 0 and 1. To brighten the color, use a float value greater than 1.) Tj T* ET
Q
Q
q
1 0 0 1 50.01575 360.2394 cm
q
q
q
1 0 0 1 4.4 .4 cm
q
.666667 .8 .6 RG
.3 w
.933333 1 .8 rg
n -4 0 504.4441 78 re B*
Q
q
BT 1 0 0 1 0 62 Tm 12 TL /F4 10 Tf 0 0 0 rg (>) Tj (>) Tj (>) Tj ( colorscale\("#DF3C3C", .5\)) Tj T* (#6F1E1E) Tj T* (>) Tj (>) Tj (>) Tj ( colorscale\("#52D24F", 1.6\)) Tj T* (#83FF7E) Tj T* (>) Tj (>) Tj (>) Tj ( colorscale\("#4F75D2", 1\)) Tj T* (#4F75D2) Tj T* ET
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q
1 0 0 1 40.01575 346.2394 cm
Q
q
1 0 0 1 40.01575 334.2394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F4 10 Tf 0 0 0 rg (moseq2_app.stat.view.) Tj /F5 10 Tf (draw_stats) Tj /F1 10 Tf ( \() Tj (fig) Tj (, df) Tj (, groups) Tj (, colors) Tj (, sorting) Tj (, groupby) Tj (, stat) Tj (, errorbar) Tj (, line_dash) Tj (=) Tj ('solid') Tj (\)) Tj T* ET
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Q
q
1 0 0 1 50.01575 310.2394 cm
q
BT 1 0 0 1 0 14 Tm .554006 Tw 12 TL /F1 10 Tf 0 0 0 rg (Helper function to bokeh_plotting that iterates through the given DataFrame and plots the data grouped by some) Tj T* 0 Tw (user defined column \(\221group\222, \221SessionName\222, \221SubjectName\222\), with the errorbars of their choice.) Tj T* ET
Q
Q
q
1 0 0 1 50.01575 304.2394 cm
Q
q
1 0 0 1 50.01575 157.2394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 135 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 15.23937 0 Td (Args:) Tj T* -15.23937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 141 cm
Q
q
1 0 0 1 91.03937 141 cm
Q
q
1 0 0 1 91.03937 129 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (fig \(bokeh figure\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (Figure to draw line plot glyphs on) Tj /F1 10 Tf (\)) Tj T* ET
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q
Q
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q
1 0 0 1 91.03937 123 cm
Q
q
1 0 0 1 91.03937 111 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
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q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (df \(pd.DataFrame\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (DataFrame containing all relevant data to plot) Tj /F1 10 Tf (\)) Tj T* ET
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1 0 0 1 91.03937 105 cm
Q
q
1 0 0 1 91.03937 93 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (groups \(list of str\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (List of group names to iterate by) Tj /F1 10 Tf (\)) Tj T* ET
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q
Q
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q
1 0 0 1 91.03937 87 cm
Q
q
1 0 0 1 91.03937 75 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (colors \(list of str\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (List of group-corresponding colors to iterate by) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 91.03937 69 cm
Q
q
1 0 0 1 91.03937 57 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (sorting \(list of int\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (Pre-selected syllable index order) Tj /F1 10 Tf (\)) Tj T* ET
Q
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q
Q
Q
q
1 0 0 1 91.03937 51 cm
Q
q
1 0 0 1 91.03937 39 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (groupby \(str\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (string that indicates which DataFrame column is being grouped.) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 91.03937 33 cm
Q
q
1 0 0 1 91.03937 21 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (stat \(str\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (String that indicates the statistic that is being plotted.) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 91.03937 15 cm
Q
q
1 0 0 1 91.03937 3 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (errorbar \(str\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (String that indicates the type of error bars to be plotted.) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 91.03937 3 cm
Q
q
Q
Q
q
1 0 0 1 50.01575 142.2394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 31.92937 0 Td (Returns:) Tj T* -31.92937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL (pickers \(list of ColorPickers\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 50.01575 127.2394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 14.14937 0 Td (Return type:) Tj T* -14.14937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL (List of interactive color picker widgets to update the graph colors) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 40.01575 121.2394 cm
Q
q
1 0 0 1 40.01575 109.2394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F4 10 Tf 0 0 0 rg (moseq2_app.stat.view.) Tj /F5 10 Tf (format_graphs) Tj /F1 10 Tf ( \() Tj (graphs) Tj (, group) Tj (\)) Tj T* ET
Q
Q
q
1 0 0 1 50.01575 85.23937 cm
q
BT 1 0 0 1 0 14 Tm .040273 Tw 12 TL /F1 10 Tf 0 0 0 rg (Formats multiple transition graphs to be stacked in vertical column-order with graph positions corresponding to the) Tj T* 0 Tw (difference graphs.) Tj T* ET
Q
Q
q
1 0 0 1 50.01575 73.23937 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL (For example for 3 groups output would look like this: [ a b-a c-a ] [ b c-b ] [ c ]) Tj T* ET
Q
Q
q
1 0 0 1 50.01575 67.23937 cm
Q
q
1 0 0 1 34.01575 807.2126 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL (Welcome to moseq2-app\222s documentation!) Tj T* ET
Q
Q
q
1 0 0 1 34.01575 22.67717 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL (16) Tj T* ET
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Q
 
endstream
endobj
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<<
/Length 12995
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stream
1 0 0 1 0 0 cm  BT /F1 12 Tf 14.4 TL ET
q
1 0 0 1 50.01575 748.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 27 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 15.23937 0 Td (Args:) Tj T* -15.23937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 33 cm
Q
q
1 0 0 1 91.03937 33 cm
Q
q
1 0 0 1 91.03937 21 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (graphs \(list\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (list of generated Bokeh figures.) Tj /F1 10 Tf (\)) Tj T* ET
Q
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q
1 0 0 1 91.03937 15 cm
Q
q
1 0 0 1 91.03937 3 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (group \(list\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (list of unique groups) Tj /F1 10 Tf (\)) Tj T* ET
Q
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1 0 0 1 91.03937 3 cm
Q
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Q
Q
q
1 0 0 1 50.01575 733.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 31.92937 0 Td (Returns:) Tj T* -31.92937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL (formatted_plots \(2D list\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 50.01575 718.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 14.14937 0 Td (Return type:) Tj T* -14.14937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL (list of lists corresponding to rows of figures being plotted.) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 40.01575 712.0394 cm
Q
q
1 0 0 1 40.01575 700.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F4 10 Tf 0 0 0 rg (moseq2_app.stat.view.) Tj /F5 10 Tf (format_plot) Tj /F1 10 Tf ( \() Tj (plot) Tj (\)) Tj T* ET
Q
Q
q
1 0 0 1 50.01575 688.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F1 10 Tf 0 0 0 rg (Turns off all major and minor x,y ticks on the transition plot graphs) Tj T* ET
Q
Q
q
1 0 0 1 50.01575 682.0394 cm
Q
q
1 0 0 1 50.01575 667.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 15.23937 0 Td (Args:) Tj T* -15.23937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (plot \(bokeh Plot\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (Current graph being generated) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 40.01575 661.0394 cm
Q
q
1 0 0 1 40.01575 637.0394 cm
q
BT 1 0 0 1 0 14 Tm 12 TL /F4 10 Tf 0 0 0 rg (moseq2_app.stat.view.) Tj /F5 10 Tf (get_ci_vect_vectorized) Tj /F1 10 Tf ( \() Tj /F4 10 Tf (x) Tj /F1 10 Tf (, ) Tj /F4 10 Tf (n_boots=10000) Tj /F1 10 Tf (, ) Tj /F4 10 Tf (n_samp=None) Tj /F1 10 Tf (,) Tj T* /F4 10 Tf (function=) Tj (<) Tj (function nanmean) Tj (>) Tj /F1 10 Tf (, ) Tj /F4 10 Tf (pct=5) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
1 0 0 1 40.01575 631.0394 cm
Q
q
1 0 0 1 40.01575 619.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F4 10 Tf 0 0 0 rg (moseq2_app.stat.view.) Tj /F5 10 Tf (get_difference_legend_items) Tj /F1 10 Tf ( \() Tj (plot) Tj (, edge_width) Tj (, group_name) Tj (\)) Tj T* ET
Q
Q
q
1 0 0 1 50.01575 603.0394 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL (Creates the difference graph legend items with the min and max transition probabilities) Tj T* ET
Q
Q
q
1 0 0 1 50.01575 588.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
BT 1 0 0 1 0 2 Tm  T* ET
q
1 0 0 1 20 0 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F1 10 Tf 0 0 0 rg (for both the up and down-regulated transition probabilities.) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 50.01575 582.0394 cm
Q
q
1 0 0 1 50.01575 525.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 45 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 15.23937 0 Td (Args:) Tj T* -15.23937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 51 cm
Q
q
1 0 0 1 91.03937 51 cm
Q
q
1 0 0 1 91.03937 39 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (plot \(bokeh.figure\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (Bokeh plot to add legend to.) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 91.03937 33 cm
Q
q
1 0 0 1 91.03937 21 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (edge_width \(dict\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (Dictionary of edge widths) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 91.03937 15 cm
Q
q
1 0 0 1 91.03937 3 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (group_name \(str\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (Difference graph title.) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 91.03937 3 cm
Q
q
Q
Q
q
1 0 0 1 50.01575 510.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 31.92937 0 Td (Returns:) Tj T* -31.92937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL (diff_items \(list\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 50.01575 495.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 14.14937 0 Td (Return type:) Tj T* -14.14937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL (List of LegendItem objects to display) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 40.01575 489.0394 cm
Q
q
1 0 0 1 40.01575 477.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F4 10 Tf 0 0 0 rg (moseq2_app.stat.view.) Tj /F5 10 Tf (get_minmax_tp) Tj /F1 10 Tf ( \() Tj (edge_width) Tj (, diff) Tj (=) Tj (False) Tj (\)) Tj T* ET
Q
Q
q
1 0 0 1 50.01575 453.0394 cm
q
BT 1 0 0 1 0 14 Tm .57377 Tw 12 TL /F1 10 Tf 0 0 0 rg (Computes the min and max transition probabilities given the rescaled edge-widths. If diff = True, the function will) Tj T* 0 Tw (return 4 variables: min/max for down and up-regulated syllables,) Tj T* ET
Q
Q
q
1 0 0 1 50.01575 447.0394 cm
Q
q
1 0 0 1 50.01575 396.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 39 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 15.23937 0 Td (Args:) Tj T* -15.23937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 45 cm
Q
q
1 0 0 1 91.03937 45 cm
Q
q
1 0 0 1 91.03937 33 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (edge_width \(dict\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (dict of syllables paired with drawn edge widths) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 91.03937 27 cm
Q
q
1 0 0 1 91.03937 3 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 9 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 14 Tm 3.694975 Tw 12 TL /F2 10 Tf 0 0 0 rg (diff \(bool\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (indicates whether to compute min/max transition probs. for up and) Tj T* 0 Tw (down-regulated syllables.) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 91.03937 3 cm
Q
q
Q
Q
q
1 0 0 1 50.01575 345.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 39 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 31.92937 0 Td (Returns:) Tj T* -31.92937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 3 cm
q
BT 1 0 0 1 0 38 Tm 1.507472 Tw 12 TL /F2 10 Tf 0 0 0 rg (min_tp \(float\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (min transition probability \(min_down_tp if diff=True\)) Tj /F1 10 Tf (\) ) Tj /F2 10 Tf (max_tp \(float\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (max) Tj T* 0 Tw 1.48456 Tw (transition probability \(max_down_tp if diff=True\)) Tj /F1 10 Tf (\) \226 if diff == True ) Tj /F2 10 Tf (min_up_tp \(float\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (min) Tj T* 0 Tw .837192 Tw (transition probability in up-regulated syllable) Tj /F1 10 Tf (\) ) Tj /F2 10 Tf (max_up_tp \(float\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (max transition probability) Tj T* 0 Tw (in up-regulated syllable) Tj /F1 10 Tf (\)) Tj T* ET
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q
Q
Q
q
1 0 0 1 40.01575 339.0394 cm
Q
q
1 0 0 1 40.01575 327.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F4 10 Tf 0 0 0 rg (moseq2_app.stat.view.) Tj /F5 10 Tf (get_neighbors) Tj /F1 10 Tf ( \() Tj (graph) Tj (, node_indices) Tj (, group_name) Tj (\)) Tj T* ET
Q
Q
q
1 0 0 1 50.01575 311.0394 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL (Computes the incoming and outgoing syllable entropies, entropy rates, previous nodes and) Tj T* ET
Q
Q
q
1 0 0 1 50.01575 296.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
BT 1 0 0 1 0 2 Tm  T* ET
q
1 0 0 1 20 0 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F1 10 Tf 0 0 0 rg (neighboring nodes for all the nodes included in node_indices.) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 50.01575 290.0394 cm
Q
q
1 0 0 1 50.01575 233.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 45 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 15.23937 0 Td (Args:) Tj T* -15.23937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 51 cm
Q
q
1 0 0 1 91.03937 51 cm
Q
q
1 0 0 1 91.03937 39 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (graph \(networkx DiGraph\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (Generated DiGraph to convert to Bokeh glyph and plot.) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 91.03937 33 cm
Q
q
1 0 0 1 91.03937 21 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (node_indices \(list\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (List of node indices included in the given graph) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 91.03937 15 cm
Q
q
1 0 0 1 91.03937 3 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (group_name \(str\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (Graph\222s group name.) Tj /F1 10 Tf (\)) Tj T* ET
Q
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q
Q
Q
q
1 0 0 1 91.03937 3 cm
Q
q
Q
Q
q
1 0 0 1 50.01575 182.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 39 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 31.92937 0 Td (Returns:) Tj T* -31.92937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 3 cm
q
BT 1 0 0 1 0 38 Tm 1.172671 Tw 12 TL /F2 10 Tf 0 0 0 rg (prev_states \(list\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (List of previous nodes for each node index in the graph.) Tj /F1 10 Tf (\) ) Tj /F2 10 Tf (next_states) Tj T* 0 Tw .226793 Tw (\(list\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (List of successor nodes/syllables for each node in the graph) Tj /F1 10 Tf (\) ) Tj /F2 10 Tf (neighbor_edge_colors) Tj T* 0 Tw .016982 Tw (\(list\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (List of colors determining whether an edge is incoming or outgoing from each node.) Tj /F1 10 Tf (\) \226) Tj T* 0 Tw (Where orange = incoming, and purple = outgoing) Tj T* ET
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q
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q
1 0 0 1 40.01575 176.0394 cm
Q
q
1 0 0 1 40.01575 164.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F4 10 Tf 0 0 0 rg (moseq2_app.stat.view.) Tj /F5 10 Tf (graph_dendrogram) Tj /F1 10 Tf ( \() Tj (obj) Tj (, syll_info) Tj (\)) Tj T* ET
Q
Q
q
1 0 0 1 50.01575 140.0394 cm
q
BT 1 0 0 1 0 14 Tm 1.483675 Tw 12 TL /F1 10 Tf 0 0 0 rg (Graphs the distance sorted dendrogram representing syllable neighborhoods. Distance sorting is computed by) Tj T* 0 Tw (processing the respective syllable AR matrices.) Tj T* ET
Q
Q
q
1 0 0 1 50.01575 134.0394 cm
Q
q
1 0 0 1 50.01575 71.03937 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 51 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 15.23937 0 Td (Args:) Tj T* -15.23937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 57 cm
Q
q
1 0 0 1 91.03937 57 cm
Q
q
1 0 0 1 91.03937 33 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 9 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 14 Tm 2.091841 Tw 12 TL /F2 10 Tf 0 0 0 rg (obj \(InteractiveSyllableStats object\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (Syllable Stats object containing syllable stat) Tj T* 0 Tw (information.) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 91.03937 27 cm
Q
q
1 0 0 1 91.03937 3 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 9 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 14 Tm .283727 Tw 12 TL /F2 10 Tf 0 0 0 rg (syll_info \(dict\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (dict object containing syllable numbers paired with dicts of their labels) Tj T* 0 Tw (and descriptions.) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
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q
1 0 0 1 91.03937 3 cm
Q
q
Q
Q
q
1 0 0 1 40.01575 65.03937 cm
Q
q
1 0 0 1 34.01575 807.2126 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL (Welcome to moseq2-app\222s documentation!) Tj T* ET
Q
Q
q
1 0 0 1 34.01575 22.67717 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL (17) Tj T* ET
Q
Q
 
endstream
endobj
539 0 obj
<<
/Length 9047
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stream
1 0 0 1 0 0 cm  BT /F1 12 Tf 14.4 TL ET
q
1 0 0 1 40.01575 751.0394 cm
q
BT 1 0 0 1 0 26 Tm 12 TL /F4 10 Tf 0 0 0 rg (moseq2_app.stat.view.) Tj /F5 10 Tf (plot_interactive_transition_graph) Tj /F1 10 Tf ( \() Tj (graphs) Tj (, pos) Tj (, group) Tj (, group_names) Tj (,) Tj T* (usages) Tj (, syll_info) Tj (, incoming_transition_entropy) Tj (, outgoing_transition_entropy) Tj (, scalars) Tj (, scalar_color) Tj (=) Tj ('default') Tj (,) Tj T* (plot_vertically) Tj (=) Tj (False) Tj (, legend_loc) Tj (=) Tj ('above') Tj (\)) Tj T* ET
Q
Q
q
1 0 0 1 50.01575 727.0394 cm
q
BT 1 0 0 1 0 14 Tm .068381 Tw 12 TL /F1 10 Tf 0 0 0 rg (Converts the computed networkx transition graphs to Bokeh glyph objects that can be interacted with and updated) Tj T* 0 Tw (throughout run-time.) Tj T* ET
Q
Q
q
1 0 0 1 50.01575 721.0394 cm
Q
q
1 0 0 1 50.01575 580.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 129 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 15.23937 0 Td (Args:) Tj T* -15.23937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 135 cm
Q
q
1 0 0 1 91.03937 135 cm
Q
q
1 0 0 1 91.03937 123 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (graphs \(list of nx.DiGraphs\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (list of created networkx graphs.) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 91.03937 117 cm
Q
q
1 0 0 1 91.03937 105 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (pos \(nx.Layout\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (shared node position coordinates layout object.) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 91.03937 99 cm
Q
q
1 0 0 1 91.03937 87 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (group \(list\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (list of unique group names.) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 91.03937 81 cm
Q
q
1 0 0 1 91.03937 57 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 9 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 14 Tm .81456 Tw 12 TL /F2 10 Tf 0 0 0 rg (group_names \(list\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (list of names for all the generated transition graphs + difference) Tj T* 0 Tw (graphs) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 91.03937 51 cm
Q
q
1 0 0 1 91.03937 39 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (usages \(list of OrdreredDicts\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (list of OrderedDicts containing syllable usages.) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 91.03937 33 cm
Q
q
1 0 0 1 91.03937 21 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (syll_info \(dict\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (dict of syllable label information to display with HoverTool) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
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q
1 0 0 1 91.03937 15 cm
Q
q
1 0 0 1 91.03937 3 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (scalars \(dict\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (dict of syllable scalar information to display with HoverTool) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 91.03937 3 cm
Q
q
Q
Q
q
1 0 0 1 40.01575 574.0394 cm
Q
q
1 0 0 1 40.01575 562.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F4 10 Tf 0 0 0 rg (moseq2_app.stat.view.) Tj /F5 10 Tf (set_fill_color) Tj /F1 10 Tf ( \() Tj (scalar_color) Tj (, data_dict) Tj (\)) Tj T* ET
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Q
q
1 0 0 1 50.01575 538.0394 cm
q
BT 1 0 0 1 0 14 Tm .109705 Tw 12 TL /F1 10 Tf 0 0 0 rg (Sets the node fill coloring based on the selected scalar value. Uses the inputted data_dict to get the key and array) Tj T* 0 Tw (for the requested scalar.) Tj T* ET
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Q
q
1 0 0 1 50.01575 532.0394 cm
Q
q
1 0 0 1 50.01575 481.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 39 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 15.23937 0 Td (Args:) Tj T* -15.23937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 45 cm
Q
q
1 0 0 1 91.03937 45 cm
Q
q
1 0 0 1 91.03937 33 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (scalar_color \(str\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (name of scalar to color nodes by.) Tj /F1 10 Tf (\)) Tj T* ET
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q
Q
Q
q
1 0 0 1 91.03937 27 cm
Q
q
1 0 0 1 91.03937 3 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 9 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
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q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 14 Tm 2.127702 Tw 12 TL /F2 10 Tf 0 0 0 rg (data_dict \(dict\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (dict containing dicts of scalar_df keys and their corresponding) Tj /F1 10 Tf (\) \226) Tj T* 0 Tw (values to create the linear color map from.) Tj T* ET
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1 0 0 1 91.03937 3 cm
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q
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q
1 0 0 1 50.01575 454.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 15 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 31.92937 0 Td (Returns:) Tj T* -31.92937 0 Td ET
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Q
q
1 0 0 1 91.03937 3 cm
q
BT 1 0 0 1 0 14 Tm .170315 Tw 12 TL /F2 10 Tf 0 0 0 rg (fill_color \(str or list\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (list of colors per node, or single color \(white\)) Tj /F1 10 Tf (\) ) Tj /F2 10 Tf (empty \(bool\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (indicator) Tj T* 0 Tw (for whether to display a color bar.) Tj /F1 10 Tf (\)) Tj T* ET
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q
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1 0 0 1 40.01575 424.8394 cm
q
.8 .8 .8 RG
.3 w
.94902 .94902 .94902 rg
n -10 0 525.2441 19.2 re B*
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q
BT 1 0 0 1 0 2.2 Tm 13.2 TL /F3 11 Tf .12549 .262745 .360784 rg (Stats - Widgets Module) Tj T* ET
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q
1 0 0 1 40.01575 406.8394 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL (Widgets module containing classes with components for each of the interactive syllable) Tj T* ET
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q
1 0 0 1 40.01575 391.8394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
BT 1 0 0 1 0 2 Tm  T* ET
q
1 0 0 1 20 0 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F1 10 Tf 0 0 0 rg (statistics tools: Syllable Stats plot, and Transition Graph plot.) Tj T* ET
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1 0 0 1 40.01575 385.8394 cm
Q
q
1 0 0 1 40.01575 367.8394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F6 10 Tf 0 0 0 rg (class ) Tj /F4 10 Tf (moseq2_app.stat.widgets.) Tj /F5 10 Tf (SyllableStatWidgets) Tj T* ET
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1 0 0 1 50.01575 355.8394 cm
q
.933333 1 .8 rg
n 33.35 0 36 12 re f*
BT 1 0 0 1 0 2 Tm 12 TL /F1 10 Tf 0 0 0 rg (Bases: ) Tj /F5 10 Tf (object) Tj T* ET
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q
1 0 0 1 40.01575 349.8394 cm
Q
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1 0 0 1 40.01575 331.8394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F6 10 Tf 0 0 0 rg (class ) Tj /F4 10 Tf (moseq2_app.stat.widgets.) Tj /F5 10 Tf (TransitionGraphWidgets) Tj T* ET
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1 0 0 1 50.01575 319.8394 cm
q
.933333 1 .8 rg
n 33.35 0 36 12 re f*
BT 1 0 0 1 0 2 Tm 12 TL /F1 10 Tf 0 0 0 rg (Bases: ) Tj /F5 10 Tf (object) Tj T* ET
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Q
q
1 0 0 1 50.01575 291.8394 cm
q
0 0 0 rg
BT 1 0 0 1 0 14 Tm /F2 10 Tf 12 TL (edge_thresholder = widgets.FloatRangeSlider\(value=[0.0025, 1], min=0, max=1, step=0.001, style=style,) Tj T* (readout_format=\222.4f\222,) Tj T* ET
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q
1 0 0 1 50.01575 276.8394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
BT 1 0 0 1 0 2 Tm  T* ET
q
1 0 0 1 20 0 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL (description=\222Edges weights to display\222, continuous_update=False\)) Tj T* ET
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q
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q
1 0 0 1 50.01575 248.8394 cm
q
0 0 0 rg
BT 1 0 0 1 0 14 Tm /F2 10 Tf 12 TL (usage_thresholder = widgets.FloatRangeSlider\(value=[0, 1], min=0, max=1, step=0.001, style=style,) Tj T* (readout_format=\222.4f\222,) Tj T* ET
Q
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q
1 0 0 1 50.01575 233.8394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
BT 1 0 0 1 0 2 Tm  T* ET
q
1 0 0 1 20 0 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL (description=\222Usage nodes to display\222, continuous_update=False\)) Tj T* ET
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q
Q
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q
1 0 0 1 50.01575 205.8394 cm
q
0 0 0 rg
BT 1 0 0 1 0 14 Tm /F2 10 Tf 12 TL (speed_thresholder = widgets.FloatRangeSlider\(value=[-25, 200], min=-50, max=200, step=1, style=style,) Tj T* (readout_format=\222.1f\222,) Tj T* ET
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1 0 0 1 50.01575 190.8394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
BT 1 0 0 1 0 2 Tm  T* ET
q
1 0 0 1 20 0 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL (description=\222Threshold nodes by speed\222, continuous_update=False\)) Tj T* ET
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1 0 0 1 34.01575 807.2126 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL (Welcome to moseq2-app\222s documentation!) Tj T* ET
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Q
q
1 0 0 1 34.01575 22.67717 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL (18) Tj T* ET
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1 0 0 1 0 0 cm  BT /F1 12 Tf 14.4 TL ET
q
1 0 0 1 40.01575 773.8394 cm
q
.8 .8 .8 RG
.3 w
.94902 .94902 .94902 rg
n -10 0 525.2441 19.2 re B*
Q
q
BT 1 0 0 1 0 2.2 Tm 13.2 TL /F3 11 Tf .12549 .262745 .360784 rg (Module contents) Tj T* ET
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Q
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1 0 0 1 40.01575 743.4394 cm
q
.8 .8 .8 RG
.3 w
.94902 .94902 .94902 rg
n -10 0 525.2441 20.4 re B*
Q
q
BT 1 0 0 1 0 2.4 Tm 14.4 TL /F3 12 Tf .12549 .262745 .360784 rg (moseq2_app.viz package) Tj T* ET
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q
1 0 0 1 40.01575 714.2394 cm
q
.8 .8 .8 RG
.3 w
.94902 .94902 .94902 rg
n -10 0 525.2441 19.2 re B*
Q
q
.12549 .262745 .360784 rg
BT 1 0 0 1 0 2.2 Tm /F3 11 Tf 13.2 TL (Submodules) Tj T* ET
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1 0 0 1 40.01575 685.0394 cm
q
.8 .8 .8 RG
.3 w
.94902 .94902 .94902 rg
n -10 0 525.2441 19.2 re B*
Q
q
BT 1 0 0 1 0 2.2 Tm 13.2 TL /F3 11 Tf .12549 .262745 .360784 rg (Viz - Controller Module) Tj T* ET
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q
1 0 0 1 40.01575 667.0394 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL (Main syllable crowd movie viewing, comparing, and labeling functionality.) Tj T* ET
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Q
q
1 0 0 1 40.01575 652.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
BT 1 0 0 1 0 2 Tm  T* ET
q
1 0 0 1 20 0 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F1 10 Tf 0 0 0 rg (Included tools are the Syllable labeler, and the crowd movie/position pdf comparison tool.) Tj T* ET
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1 0 0 1 40.01575 646.0394 cm
Q
q
1 0 0 1 40.01575 616.0394 cm
q
BT 1 0 0 1 0 14 Tm .376819 Tw 12 TL /F6 10 Tf 0 0 0 rg (class ) Tj /F4 10 Tf (moseq2_app.viz.controller.) Tj /F5 10 Tf (CrowdMovieComparison) Tj /F1 10 Tf ( \() Tj (config_data) Tj (, index_path) Tj (, df_path) Tj (, model_path) Tj (,) Tj T* 0 Tw (syll_info) Tj (, output_dir) Tj (, get_pdfs) Tj (, load_parquet) Tj (\)) Tj T* ET
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1 0 0 1 50.01575 604.0394 cm
q
.933333 1 .8 rg
n 33.35 0 282 12 re f*
BT 1 0 0 1 0 2 Tm 12 TL /F1 10 Tf 0 0 0 rg (Bases: ) Tj /F5 10 Tf (moseq2_app.viz.widgets.CrowdMovieCompareWidgets) Tj T* ET
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q
1 0 0 1 50.01575 592.0394 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL (Crowd Movie Comparison application class. Contains all the user inputted parameters within its context.) Tj T* ET
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1 0 0 1 50.01575 586.0394 cm
Q
q
1 0 0 1 50.01575 568.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F5 10 Tf 0 0 0 rg (clear_on_click) Tj /F2 10 Tf ( \() Tj /F1 10 Tf (b) Tj /F2 10 Tf (\)) Tj T* ET
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q
1 0 0 1 60.01575 556.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F1 10 Tf 0 0 0 rg (Clears the cell output) Tj T* ET
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q
1 0 0 1 60.01575 550.0394 cm
Q
q
1 0 0 1 60.01575 535.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 15.23937 0 Td (Args:) Tj T* -15.23937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL (b) Tj T* ET
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q
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q
1 0 0 1 50.01575 529.0394 cm
Q
q
1 0 0 1 50.01575 511.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F5 10 Tf 0 0 0 rg (crowd_movie_preview) Tj /F2 10 Tf ( \() Tj /F1 10 Tf (syllable) Tj /F2 10 Tf (, ) Tj /F1 10 Tf (groupby) Tj /F2 10 Tf (, ) Tj /F1 10 Tf (nexamples) Tj /F2 10 Tf (\)) Tj T* ET
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Q
q
1 0 0 1 60.01575 487.0394 cm
q
BT 1 0 0 1 0 14 Tm 2.097238 Tw 12 TL /F1 10 Tf 0 0 0 rg (Helper function that triggers the crowd_movie_wrapper function and creates the HTML divs containing the) Tj T* 0 Tw (generated crowd movies. Function is triggered whenever any of the widget function inputs are changed.) Tj T* ET
Q
Q
q
1 0 0 1 60.01575 481.0394 cm
Q
q
1 0 0 1 60.01575 430.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 39 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 15.23937 0 Td (Args:) Tj T* -15.23937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 45 cm
Q
q
1 0 0 1 91.03937 45 cm
Q
q
1 0 0 1 91.03937 33 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (syllable \(int or ipywidgets.DropDownMenu\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (Currently displayed syllable.) Tj /F1 10 Tf (\)) Tj T* ET
Q
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q
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q
1 0 0 1 91.03937 27 cm
Q
q
1 0 0 1 91.03937 3 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 9 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 14 Tm 2.344472 Tw 12 TL /F2 10 Tf 0 0 0 rg (nexamples \(int or ipywidgets.IntSlider\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (Number of mice to display per crowd) Tj T* 0 Tw (movie.) Tj /F1 10 Tf (\)) Tj T* ET
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q
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q
1 0 0 1 91.03937 3 cm
Q
q
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q
1 0 0 1 50.01575 424.0394 cm
Q
q
1 0 0 1 50.01575 406.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F5 10 Tf 0 0 0 rg (generate_crowd_movie_divs) Tj /F2 10 Tf ( \(\)) Tj T* ET
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Q
q
1 0 0 1 60.01575 390.0394 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL (Generates HTML divs containing crowd movies and syllable metadata tables) Tj T* ET
Q
Q
q
1 0 0 1 60.01575 375.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
BT 1 0 0 1 0 2 Tm  T* ET
q
1 0 0 1 20 0 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F1 10 Tf 0 0 0 rg (from the given syllable dict file.) Tj T* ET
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Q
q
Q
Q
q
1 0 0 1 60.01575 369.0394 cm
Q
q
1 0 0 1 60.01575 342.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 15 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 31.92937 0 Td (Returns:) Tj T* -31.92937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 3 cm
q
BT 1 0 0 1 0 14 Tm .987702 Tw 12 TL /F2 10 Tf 0 0 0 rg (divs \(list of Bokeh.models.Div\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (Divs of HTML videos and metadata tables.) Tj /F1 10 Tf (\) ) Tj /F2 10 Tf (bk_plots) Tj T* 0 Tw (\(list\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (list of corresponding position heatmap figures.) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 50.01575 336.0394 cm
Q
q
1 0 0 1 50.01575 318.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F5 10 Tf 0 0 0 rg (get_mean_group_dict) Tj /F2 10 Tf ( \() Tj /F1 10 Tf (group_df) Tj /F2 10 Tf (\)) Tj T* ET
Q
Q
q
1 0 0 1 60.01575 306.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F1 10 Tf 0 0 0 rg (Creates a dict object to convert to a displayed table containing syllable scalars.) Tj T* ET
Q
Q
q
1 0 0 1 60.01575 300.0394 cm
Q
q
1 0 0 1 60.01575 273.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 15 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 15.23937 0 Td (Args:) Tj T* -15.23937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 3 cm
q
BT 1 0 0 1 0 14 Tm 2.19608 Tw 12 TL /F2 10 Tf 0 0 0 rg (group_df \(pd.DataFrame\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (DataFrame containing mean syllable scalar data for each) Tj T* 0 Tw (session and their groups) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 50.01575 267.0394 cm
Q
q
1 0 0 1 50.01575 249.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F5 10 Tf 0 0 0 rg (get_pdf_plot) Tj /F2 10 Tf ( \() Tj /F1 10 Tf (group_syllable_pdf) Tj /F2 10 Tf (, ) Tj /F1 10 Tf (group_name) Tj /F2 10 Tf (\)) Tj T* ET
Q
Q
q
1 0 0 1 60.01575 237.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F1 10 Tf 0 0 0 rg (Helper function that creates a bokeh plot with the given PDF heatmap and figure title.) Tj T* ET
Q
Q
q
1 0 0 1 60.01575 231.0394 cm
Q
q
1 0 0 1 60.01575 192.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 27 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 15.23937 0 Td (Args:) Tj T* -15.23937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 33 cm
Q
q
1 0 0 1 91.03937 33 cm
Q
q
1 0 0 1 91.03937 21 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (group_syllable_pdf \(2D np.ndarray\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (Mean syllable position PDF heatmap.) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 91.03937 15 cm
Q
q
1 0 0 1 91.03937 3 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 -3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL 10.5 0 Td (\177) Tj T* -10.5 0 Td ET
Q
Q
q
1 0 0 1 23 -3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (group_name \(str\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (Name of group for generated syllable pdf) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
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q
1 0 0 1 91.03937 3 cm
Q
q
Q
Q
q
1 0 0 1 60.01575 177.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 31.92937 0 Td (Returns:) Tj T* -31.92937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL (pdf_fig \(bokeh.figure\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 60.01575 162.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 14.14937 0 Td (Return type:) Tj T* -14.14937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL (Create bokeh figure.) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 50.01575 156.0394 cm
Q
q
1 0 0 1 50.01575 138.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F5 10 Tf 0 0 0 rg (get_selected_session_syllable_info) Tj /F2 10 Tf ( \() Tj /F1 10 Tf (sel_sessions) Tj /F2 10 Tf (\)) Tj T* ET
Q
Q
q
1 0 0 1 60.01575 126.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F1 10 Tf 0 0 0 rg (Prepares dict of session-based syllable information to display.) Tj T* ET
Q
Q
q
1 0 0 1 60.01575 120.0394 cm
Q
q
1 0 0 1 60.01575 105.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 15.23937 0 Td (Args:) Tj T* -15.23937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (sel_sessions \(list\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (list of selected session names.) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 50.01575 99.03937 cm
Q
q
1 0 0 1 50.01575 81.03937 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F5 10 Tf 0 0 0 rg (get_session_mean_syllable_info_df) Tj /F2 10 Tf ( \(\)) Tj T* ET
Q
Q
q
1 0 0 1 60.01575 69.03937 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F1 10 Tf 0 0 0 rg (Populates session-based syllable information dict with usage and scalar information.) Tj T* ET
Q
Q
q
1 0 0 1 50.01575 63.03937 cm
Q
q
1 0 0 1 34.01575 807.2126 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL (Welcome to moseq2-app\222s documentation!) Tj T* ET
Q
Q
q
1 0 0 1 34.01575 22.67717 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL (19) Tj T* ET
Q
Q
 
endstream
endobj
541 0 obj
<<
/Length 9611
>>
stream
1 0 0 1 0 0 cm  BT /F1 12 Tf 14.4 TL ET
q
1 0 0 1 50.01575 775.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F5 10 Tf 0 0 0 rg (on_click_trigger_button) Tj /F2 10 Tf ( \() Tj /F1 10 Tf (b) Tj /F2 10 Tf (\)) Tj T* ET
Q
Q
q
1 0 0 1 60.01575 763.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F1 10 Tf 0 0 0 rg (Generates crowd movies and displays them when the user clicks the trigger button) Tj T* ET
Q
Q
q
1 0 0 1 60.01575 757.0394 cm
Q
q
1 0 0 1 60.01575 742.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 15.23937 0 Td (Args:) Tj T* -15.23937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (b \(ipywidgets.Button click event\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (User clicks \223Generate Movies\224 button) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 50.01575 736.0394 cm
Q
q
1 0 0 1 50.01575 718.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F5 10 Tf 0 0 0 rg (select_session) Tj /F2 10 Tf ( \() Tj /F1 10 Tf (event) Tj /F2 10 Tf (\)) Tj T* ET
Q
Q
q
1 0 0 1 60.01575 702.0394 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL (Callback function to save the list of selected sessions to config_data,) Tj T* ET
Q
Q
q
1 0 0 1 60.01575 675.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
BT 1 0 0 1 0 14 Tm  T* ET
q
1 0 0 1 20 0 cm
q
BT 1 0 0 1 0 14 Tm .082435 Tw 12 TL /F1 10 Tf 0 0 0 rg (and get session syllable info to pass to crowd_movie_wrapper and create the accompanying syllable scalar) Tj T* 0 Tw (metadata table.) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 60.01575 669.0394 cm
Q
q
1 0 0 1 60.01575 654.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 15.23937 0 Td (Args:) Tj T* -15.23937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (event \(event\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (User clicks on multiple sessions in the SelectMultiple widget) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 50.01575 648.0394 cm
Q
q
1 0 0 1 50.01575 630.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F5 10 Tf 0 0 0 rg (set_default_cm_parameters) Tj /F2 10 Tf ( \(\)) Tj T* ET
Q
Q
q
1 0 0 1 50.01575 624.0394 cm
Q
q
1 0 0 1 50.01575 606.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F5 10 Tf 0 0 0 rg (show_session_select) Tj /F2 10 Tf ( \() Tj /F1 10 Tf (change) Tj /F2 10 Tf (\)) Tj T* ET
Q
Q
q
1 0 0 1 60.01575 582.0394 cm
q
BT 1 0 0 1 0 14 Tm 2.997238 Tw 12 TL /F1 10 Tf 0 0 0 rg (Callback function to change current view to show session selector when user switches DropDownMenu) Tj T* 0 Tw (selection to \221SessionName\222, and hides it if the user selects \221groups\222.) Tj T* ET
Q
Q
q
1 0 0 1 60.01575 576.0394 cm
Q
q
1 0 0 1 60.01575 561.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 15.23937 0 Td (Args:) Tj T* -15.23937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (change \(event\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (User switches their DropDownMenu selection) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 40.01575 555.0394 cm
Q
q
1 0 0 1 40.01575 525.0394 cm
q
BT 1 0 0 1 0 14 Tm 7.832819 Tw 12 TL /F6 10 Tf 0 0 0 rg (class ) Tj /F4 10 Tf (moseq2_app.viz.controller.) Tj /F5 10 Tf (SyllableLabeler) Tj /F1 10 Tf ( \() Tj (model_fit) Tj (, model_path) Tj (, index_file) Tj (, max_sylls) Tj (,) Tj T* 0 Tw (save_path) Tj (\)) Tj T* ET
Q
Q
q
1 0 0 1 50.01575 513.0394 cm
q
.933333 1 .8 rg
n 33.35 0 270 12 re f*
BT 1 0 0 1 0 2 Tm 12 TL /F1 10 Tf 0 0 0 rg (Bases: ) Tj /F5 10 Tf (moseq2_app.viz.widgets.SyllableLabelerWidgets) Tj T* ET
Q
Q
q
1 0 0 1 50.01575 497.0394 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL (Class that contains functionality for previewing syllable crowd movies and) Tj T* ET
Q
Q
q
1 0 0 1 50.01575 482.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
BT 1 0 0 1 0 2 Tm  T* ET
q
1 0 0 1 20 0 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL (user interactions with buttons and menus.) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 50.01575 476.0394 cm
Q
q
1 0 0 1 50.01575 458.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F5 10 Tf 0 0 0 rg (clear_on_click) Tj /F2 10 Tf ( \() Tj /F1 10 Tf (b) Tj /F2 10 Tf (\)) Tj T* ET
Q
Q
q
1 0 0 1 60.01575 446.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F1 10 Tf 0 0 0 rg (Clears the cell output) Tj T* ET
Q
Q
q
1 0 0 1 60.01575 440.0394 cm
Q
q
1 0 0 1 60.01575 425.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 15.23937 0 Td (Args:) Tj T* -15.23937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL (b \(button click\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 50.01575 419.0394 cm
Q
q
1 0 0 1 50.01575 401.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F5 10 Tf 0 0 0 rg (get_crowd_movie_paths) Tj /F2 10 Tf ( \() Tj /F1 10 Tf (index_path) Tj /F2 10 Tf (, ) Tj /F1 10 Tf (model_path) Tj /F2 10 Tf (, ) Tj /F1 10 Tf (config_data) Tj /F2 10 Tf (, ) Tj /F1 10 Tf (crowd_movie_dir) Tj /F2 10 Tf (\)) Tj T* ET
Q
Q
q
1 0 0 1 60.01575 389.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F1 10 Tf 0 0 0 rg (Populates the syllable information dict with the respective crowd movie paths.) Tj T* ET
Q
Q
q
1 0 0 1 60.01575 383.0394 cm
Q
q
1 0 0 1 60.01575 368.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 15.23937 0 Td (Args:) Tj T* -15.23937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (crowd_movie_dir \(str\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (Path to directory containing all the generated crowd movies) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 50.01575 362.0394 cm
Q
q
1 0 0 1 50.01575 344.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F5 10 Tf 0 0 0 rg (get_mean_group_dict) Tj /F2 10 Tf ( \() Tj /F1 10 Tf (group_df) Tj /F2 10 Tf (\)) Tj T* ET
Q
Q
q
1 0 0 1 60.01575 332.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F1 10 Tf 0 0 0 rg (Creates a dict object to convert to a displayed table containing syllable scalars.) Tj T* ET
Q
Q
q
1 0 0 1 60.01575 326.0394 cm
Q
q
1 0 0 1 60.01575 299.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 15 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 15.23937 0 Td (Args:) Tj T* -15.23937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 3 cm
q
BT 1 0 0 1 0 14 Tm 2.19608 Tw 12 TL /F2 10 Tf 0 0 0 rg (group_df \(pd.DataFrame\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (DataFrame containing mean syllable scalar data for each) Tj T* 0 Tw (session and their groups) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 50.01575 293.0394 cm
Q
q
1 0 0 1 50.01575 275.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F5 10 Tf 0 0 0 rg (get_mean_syllable_info) Tj /F2 10 Tf ( \(\)) Tj T* ET
Q
Q
q
1 0 0 1 60.01575 263.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F1 10 Tf 0 0 0 rg (Populates syllable information dict with usage and scalar information.) Tj T* ET
Q
Q
q
1 0 0 1 50.01575 257.0394 cm
Q
q
1 0 0 1 50.01575 239.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F5 10 Tf 0 0 0 rg (interactive_syllable_labeler) Tj /F2 10 Tf ( \() Tj /F1 10 Tf (syllables) Tj /F2 10 Tf (\)) Tj T* ET
Q
Q
q
1 0 0 1 60.01575 215.0394 cm
q
BT 1 0 0 1 0 14 Tm .722006 Tw 12 TL /F1 10 Tf 0 0 0 rg (Helper function that facilitates the interactive view. Function will create a Bokeh Div object that will display the) Tj T* 0 Tw (current video path.) Tj T* ET
Q
Q
q
1 0 0 1 60.01575 209.0394 cm
Q
q
1 0 0 1 60.01575 194.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 15.23937 0 Td (Args:) Tj T* -15.23937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (syllables \(int or ipywidgets.DropDownMenu\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (Current syllable to label) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 50.01575 188.0394 cm
Q
q
1 0 0 1 50.01575 170.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F5 10 Tf 0 0 0 rg (on_next) Tj /F2 10 Tf ( \() Tj /F1 10 Tf (event) Tj /F2 10 Tf (\)) Tj T* ET
Q
Q
q
1 0 0 1 60.01575 158.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F1 10 Tf 0 0 0 rg (Callback function to trigger an view update when the user clicks the \223Next\224 button.) Tj T* ET
Q
Q
q
1 0 0 1 60.01575 152.0394 cm
Q
q
1 0 0 1 60.01575 137.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 15.23937 0 Td (Args:) Tj T* -15.23937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (event \(ipywidgets.ButtonClick\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (User clicks next button.) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 50.01575 131.0394 cm
Q
q
1 0 0 1 50.01575 113.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F5 10 Tf 0 0 0 rg (on_prev) Tj /F2 10 Tf ( \() Tj /F1 10 Tf (event) Tj /F2 10 Tf (\)) Tj T* ET
Q
Q
q
1 0 0 1 60.01575 101.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F1 10 Tf 0 0 0 rg (Callback function to trigger an view update when the user clicks the \223Previous\224 button.) Tj T* ET
Q
Q
q
1 0 0 1 60.01575 95.03937 cm
Q
q
1 0 0 1 60.01575 80.03937 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 15.23937 0 Td (Args:) Tj T* -15.23937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (event \(ipywidgets.ButtonClick\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (User clicks \221previous\222 button.) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 50.01575 74.03937 cm
Q
q
1 0 0 1 50.01575 56.03937 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F5 10 Tf 0 0 0 rg (on_set) Tj /F2 10 Tf ( \() Tj /F1 10 Tf (event) Tj /F2 10 Tf (\)) Tj T* ET
Q
Q
q
1 0 0 1 34.01575 807.2126 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL (Welcome to moseq2-app\222s documentation!) Tj T* ET
Q
Q
q
1 0 0 1 34.01575 22.67717 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL (20) Tj T* ET
Q
Q
 
endstream
endobj
542 0 obj
<<
/Length 7104
>>
stream
1 0 0 1 0 0 cm  BT /F1 12 Tf 14.4 TL ET
q
1 0 0 1 60.01575 775.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F1 10 Tf 0 0 0 rg (Callback function to save the dict to syllable information file.) Tj T* ET
Q
Q
q
1 0 0 1 60.01575 769.0394 cm
Q
q
1 0 0 1 60.01575 754.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 15.23937 0 Td (Args:) Tj T* -15.23937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (event \(ipywidgets.ButtonClick\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (User clicks the \221Save\222 button.) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 50.01575 748.0394 cm
Q
q
1 0 0 1 50.01575 730.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F5 10 Tf 0 0 0 rg (set_default_cm_parameters) Tj /F2 10 Tf ( \() Tj /F1 10 Tf (config_data) Tj /F2 10 Tf (\)) Tj T* ET
Q
Q
q
1 0 0 1 60.01575 718.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F1 10 Tf 0 0 0 rg (Sets default crowd movie generation parameters that may be manually updated.) Tj T* ET
Q
Q
q
1 0 0 1 60.01575 712.0394 cm
Q
q
1 0 0 1 60.01575 697.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 15.23937 0 Td (Args:) Tj T* -15.23937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (config_data \(dict\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (Dict of main moseq configuration parameters.) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 60.01575 682.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 31.92937 0 Td (Returns:) Tj T* -31.92937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (config_data \(dict\)) Tj /F1 10 Tf ( \226 with default crowd movie generation parameters.) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 60.01575 667.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 14.14937 0 Td (Return type:) Tj T* -14.14937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL (Updated dict of main moseq configuration parameters) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 50.01575 661.0394 cm
Q
q
1 0 0 1 50.01575 643.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F5 10 Tf 0 0 0 rg (set_group_info_widgets) Tj /F2 10 Tf ( \() Tj /F1 10 Tf (group_info) Tj /F2 10 Tf (\)) Tj T* ET
Q
Q
q
1 0 0 1 60.01575 619.0394 cm
q
BT 1 0 0 1 0 14 Tm .39377 Tw 12 TL /F1 10 Tf 0 0 0 rg (Display function that reads the syllable information into a pandas DataFrame, converts it to an HTML table and) Tj T* 0 Tw (displays it in a Bokeh Div facilitated via the Output\(\) widget.) Tj T* ET
Q
Q
q
1 0 0 1 60.01575 613.0394 cm
Q
q
1 0 0 1 60.01575 598.0394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 15.23937 0 Td (Args:) Tj T* -15.23937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 3 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F2 10 Tf 0 0 0 rg (group_info \(dict\)) Tj /F1 10 Tf ( \() Tj /F6 10 Tf (Dictionary of grouped current syllable information) Tj /F1 10 Tf (\)) Tj T* ET
Q
Q
q
Q
Q
q
1 0 0 1 50.01575 592.0394 cm
Q
q
1 0 0 1 50.01575 574.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F5 10 Tf 0 0 0 rg (write_syll_info) Tj /F2 10 Tf ( \(\)) Tj T* ET
Q
Q
q
1 0 0 1 60.01575 562.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F1 10 Tf 0 0 0 rg (Writes current syllable info data to a YAML file.) Tj T* ET
Q
Q
q
1 0 0 1 40.01575 532.8394 cm
q
.8 .8 .8 RG
.3 w
.94902 .94902 .94902 rg
n -10 0 525.2441 19.2 re B*
Q
q
BT 1 0 0 1 0 2.2 Tm 13.2 TL /F3 11 Tf .12549 .262745 .360784 rg (Viz - View Module) Tj T* ET
Q
Q
q
1 0 0 1 40.01575 514.8394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F1 10 Tf 0 0 0 rg (Helper function that displays a grid of crowd movies and plotted bokeh figures of position heatmaps.) Tj T* ET
Q
Q
q
1 0 0 1 40.01575 508.8394 cm
Q
q
1 0 0 1 40.01575 496.8394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F4 10 Tf 0 0 0 rg (moseq2_app.viz.view.) Tj /F5 10 Tf (display_crowd_movies) Tj /F1 10 Tf ( \() Tj (widget_box) Tj (, curr_name) Tj (, desc) Tj (, divs) Tj (, bk_figs) Tj (\)) Tj T* ET
Q
Q
q
1 0 0 1 50.01575 472.8394 cm
q
BT 1 0 0 1 0 14 Tm .245256 Tw 12 TL /F1 10 Tf 0 0 0 rg (Crowd movie comparison helper function that displays the widgets and embedded HTML divs to a running jupyter) Tj T* 0 Tw (notebook cell or HTML webpage.) Tj T* ET
Q
Q
q
1 0 0 1 50.01575 466.8394 cm
Q
q
1 0 0 1 50.01575 451.8394 cm
0 0 0 rg
BT /F1 10 Tf 12 TL ET
q
1 0 0 1 6 3 cm
q
0 0 0 rg
BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL 15.23937 0 Td (Args:) Tj T* -15.23937 0 Td ET
Q
Q
q
1 0 0 1 91.03937 3 cm
q
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BT 1 0 0 1 0 2 Tm /F2 10 Tf 12 TL (Widgets module containing classes with components for each of the interactive syllable) Tj T* ET
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BT /F1 10 Tf 12 TL ET
BT 1 0 0 1 0 2 Tm  T* ET
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BT 1 0 0 1 0 2.2 Tm 13.2 TL /F3 11 Tf .12549 .262745 .360784 rg (Module contents) Tj T* ET
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BT 1 0 0 1 0 4 Tm 24 TL /F2 20 Tf .12549 .262745 .360784 rg (Index) Tj T* ET
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0 0 0 rg
BT /F1 10 Tf 12 TL ET
BT 1 0 0 1 0 2 Tm  T* ET
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1 0 0 1 40.01575 239.8394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F1 10 Tf 0 0 .501961 rg (colorscale\(\) \(in module moseq2_app.stat.view\)) Tj  T* ET
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q
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q
BT 1 0 0 1 0 26 Tm 12 TL /F1 10 Tf 0 0 .501961 rg (compute_dendrogram\(\)) Tj T* (\(moseq2_app.stat.controller.InteractiveSyllableStats) Tj T* (method\)) Tj  T* ET
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q
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q
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BT 1 0 0 1 0 2 Tm 12 TL /F1 10 Tf 0 0 .501961 rg (get_minmax_tp\(\) \(in module moseq2_app.stat.view\)) Tj  T* ET
Q
Q
q
1 0 0 1 40.01575 415.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F1 10 Tf 0 0 .501961 rg (get_neighbors\(\) \(in module moseq2_app.stat.view\)) Tj  T* ET
Q
Q
q
1 0 0 1 40.01575 385.0394 cm
q
BT 1 0 0 1 0 14 Tm 55.0948 Tw 12 TL /F1 10 Tf 0 0 .501961 rg (get_pca_progress\(\) \(in module) Tj T* 0 Tw (moseq2_app.gui.progress\)) Tj  T* ET
Q
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q
1 0 0 1 40.01575 343.0394 cm
q
BT 1 0 0 1 0 26 Tm 12 TL /F1 10 Tf 0 0 .501961 rg (get_pdf_plot\(\)) Tj T* (\(moseq2_app.viz.controller.CrowdMovieComparison) Tj T* (method\)) Tj  T* ET
Q
Q
q
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q
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Q
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q
1 0 0 1 40.01575 283.0394 cm
q
BT 1 0 0 1 0 14 Tm 12 TL /F1 10 Tf 0 0 .501961 rg (get_roi_and_depths\(\)) Tj T* (\(moseq2_app.roi.controller.InteractiveFindRoi method\)) Tj  T* ET
Q
Q
q
1 0 0 1 40.01575 253.0394 cm
q
BT 1 0 0 1 0 14 Tm 28.1448 Tw 12 TL /F1 10 Tf 0 0 .501961 rg (get_scalar_anomaly_sessions\(\) \(in module) Tj T* 0 Tw (moseq2_app.roi.validation\)) Tj  T* ET
Q
Q
q
1 0 0 1 40.01575 235.0394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F1 10 Tf 0 0 .501961 rg (get_scalar_df\(\) \(in module moseq2_app.roi.validation\)) Tj  T* ET
Q
Q
q
1 0 0 1 40.01575 205.0394 cm
q
BT 1 0 0 1 0 14 Tm 12 TL /F1 10 Tf 0 0 .501961 rg (get_selected_session\(\)) Tj T* (\(moseq2_app.roi.controller.InteractiveFindRoi method\)) Tj  T* ET
Q
Q
q
1 0 0 1 40.01575 163.0394 cm
q
BT 1 0 0 1 0 26 Tm 12 TL /F1 10 Tf 0 0 .501961 rg (get_selected_session_syllable_info\(\)) Tj T* (\(moseq2_app.viz.controller.CrowdMovieComparison) Tj T* (method\)) Tj  T* ET
Q
Q
q
1 0 0 1 40.01575 121.0394 cm
q
BT 1 0 0 1 0 26 Tm 12 TL /F1 10 Tf 0 0 .501961 rg (get_session_mean_syllable_info_df\(\)) Tj T* (\(moseq2_app.viz.controller.CrowdMovieComparison) Tj T* (method\)) Tj  T* ET
Q
Q
q
1 0 0 1 40.01575 91.03937 cm
q
BT 1 0 0 1 0 14 Tm 53.4248 Tw 12 TL /F1 10 Tf 0 0 .501961 rg (get_session_paths\(\) \(in module) Tj T* 0 Tw (moseq2_app.gui.progress\)) Tj  T* ET
Q
Q
q
1 0 0 1 40.01575 61.03937 cm
q
BT 1 0 0 1 0 14 Tm 52.5948 Tw 12 TL /F1 10 Tf 0 0 .501961 rg (graph_dendrogram\(\) \(in module) Tj T* 0 Tw (moseq2_app.stat.view\)) Tj  T* ET
Q
Q
q
1 0 0 1 308.9102 775.0394 cm
q
BT 1 0 0 1 0 14 Tm 55.9298 Tw 12 TL /F1 10 Tf 0 0 .501961 rg (GroupSettingWidgets \(class in) Tj T* 0 Tw (moseq2_app.gui.widgets\)) Tj  T* ET
Q
Q
q
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q
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Q
q
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Q
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q
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q
BT 1 0 0 1 0 2 Tm 12 TL /F1 10 Tf 0 0 .501961 rg (HEADER \(moseq2_app.util.bcolors attribute\)) Tj  T* ET
Q
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q
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BT 1 0 0 1 0 2.4 Tm /F3 12 Tf 14.4 TL (I) Tj T* ET
Q
Q
q
1 0 0 1 308.9102 678.2394 cm
q
BT 1 0 0 1 0 2 Tm 12 TL /F1 10 Tf 0 0 .501961 rg (index_to_dataframe\(\) \(in module moseq2_app.util\)) Tj  T* ET
Q
Q
q
1 0 0 1 308.9102 636.2394 cm
q
BT 1 0 0 1 0 26 Tm 12 TL /F1 10 Tf 0 0 .501961 rg (initialize_transition_data\(\)) Tj T* (\(moseq2_app.stat.controller.InteractiveTransitionGraph) Tj T* (method\)) Tj  T* ET
Q
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q
1 0 0 1 308.9102 606.2394 cm
q
BT 1 0 0 1 0 14 Tm 12 TL /F1 10 Tf 0 0 .501961 rg (interactive_crowd_movie_comparison_preview_wrappe) Tj T* (r\(\) \(in module moseq2_app.gui.wrappers\)) Tj  T* ET
Q
Q
q
1 0 0 1 308.9102 576.2394 cm
q
BT 1 0 0 1 0 14 Tm 12 TL /F1 10 Tf 0 0 .501961 rg (interactive_depth_finder\(\)) Tj T* (\(moseq2_app.roi.controller.InteractiveFindRoi method\)) Tj  T* ET
Q
Q
q
1 0 0 1 308.9102 546.2394 cm
q
BT 1 0 0 1 0 14 Tm 7.029803 Tw 12 TL /F1 10 Tf 0 0 .501961 rg (interactive_extraction_preview_wrapper\(\) \(in module) Tj T* 0 Tw (moseq2_app.gui.wrappers\)) Tj  T* ET
Q
Q
q
1 0 0 1 308.9102 516.2394 cm
q
BT 1 0 0 1 0 14 Tm 12 TL /F1 10 Tf 0 0 .501961 rg (interactive_find_roi_session_selector\(\)) Tj T* (\(moseq2_app.roi.controller.InteractiveFindRoi method\)) Tj  T* ET
Q
Q
q
1 0 0 1 308.9102 486.2394 cm
q
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Q
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q
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q
BT 1 0 0 1 0 14 Tm 12 TL /F1 10 Tf 0 0 .501961 rg (interactive_launch_frame_selector\(\)) Tj T* (\(moseq2_app.flip.controller.FlipRangeTool method\)) Tj  T* ET
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q
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Q
Q
q
1 0 0 1 308.9102 396.2394 cm
q
BT 1 0 0 1 0 14 Tm 43.1548 Tw 12 TL /F1 10 Tf 0 0 .501961 rg (interactive_roi_wrapper\(\) \(in module) Tj T* 0 Tw (moseq2_app.gui.wrappers\)) Tj  T* ET
Q
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q
1 0 0 1 308.9102 354.2394 cm
q
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Q
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q
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q
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Q
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q
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q
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Q
Q
q
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q
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Q
Q
q
1 0 0 1 308.9102 222.2394 cm
q
BT 1 0 0 1 0 14 Tm 21.1998 Tw 12 TL /F1 10 Tf 0 0 .501961 rg (interactive_syllable_stat_wrapper\(\) \(in module) Tj T* 0 Tw (moseq2_app.gui.wrappers\)) Tj  T* ET
Q
Q
q
1 0 0 1 308.9102 180.2394 cm
q
BT 1 0 0 1 0 26 Tm 12 TL /F1 10 Tf 0 0 .501961 rg (interactive_transition_graph_helper\(\)) Tj T* (\(moseq2_app.stat.controller.InteractiveTransitionGraph) Tj T* (method\)) Tj  T* ET
Q
Q
q
1 0 0 1 308.9102 150.2394 cm
q
BT 1 0 0 1 0 14 Tm 42.8748 Tw 12 TL /F1 10 Tf 0 0 .501961 rg (InteractiveExtractionViewer \(class in) Tj T* 0 Tw (moseq2_app.roi.controller\)) Tj  T* ET
Q
Q
q
1 0 0 1 308.9102 132.2394 cm
q
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Q
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q
1 0 0 1 308.9102 102.2394 cm
q
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Q
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1 0 0 1 40.01575 636.2394 cm
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q
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q
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BT 1 0 0 1 0 2 Tm 12 TL /F1 10 Tf 0 0 .501961 rg (moseq2_app.stat.widgets) Tj  T* ET
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