The following output files are produced by Tierpsy Tracker during the analysis steps. The basename prefix in each of the files refers to the original video name without the extension. For example, if the video file is named as myfile.avi, the files will look like myfile.hdf5, myfile_subsample.avi myfile_skeletons.hdf5, myfile_features.hdf5, myfile_intensities.hdf5.
Contains the compressed hdf5 video data.
Shape (tot_images, im_high, im_width)
Compressed array with the masked images.
Additionally, this dataset will store as attributes the following information:
expected_fps: expected frames per second given by the user. If there is a valid video timestamp thefpswill be calculated from it and this field will be ignored.- time_units = this value is set to
secondsif there is a validexpected_fpsortimestamp, otherwise it will be set toframes. - microns_per_pixel : user given micrometers per pixels conversion.
- xy_units : set to
micronsif a validmicrons_per_pixelwas given otherwise it will be set topixels. - is_light_background : user given flag. It must be
1if the background is lighter than the objects tracker, and0if the background is darker.
Shape (tot_images/save_full_interval, im_high, im_width)
Frame without mask saved every save_full_interval frames. By default the interval is adjusted to be saved every 5 min. This field can be useful to identify changes in the background that are lost in /mask e.g. food depletion or contrast lost due to water condensation.
Shape (tot_images,)
Mean intensity of a given frame. It is useful in optogenetic experiments to identify when the light is turned on.
Timestamp extracted from the video if the is_extract_metadata flag set to true. If this fields exists and are valid (there are not nan values and they increase monotonically), they will be used to calculate the fps used in subsequent parts of the analysis. The extraction of the timestamp can be a slow process since it uses ffprobe to read the whole video. If you believe that your video does not have a significative number of dropped frames and you know the frame rate, or simply realise that ffprobe cannot extract the timestamp correctly, I recommend to set is_extract_metadata to false.
Low time and spatial resolution avi video generated using the data in /mask.
Contains the results of the tracking and skeletonization steps.
Table where the first results of TRAJ_CREATE and TRAJ_JOIN. Do not use this table in further analysis, use instead /trajectories_data.
worm_index_blob: trajectory index given by the program. Since there can be several short spurious tracks identified this number can be very large and does not reflect the number of final trajectories.worm_index_joined: index after joining trajectories separated by a small time gap and filtering short spurious tracks, and invalid row will be assigned -1.threshold: threshold used for the image binarization.frame_number: video frame number.coord_x,coord_y,box_length,box_width,angle: center coordinates, length, width and orientation of the minimum rotated rectangle.area: blob area.bounding_box_xmin,bounding_box_xmax,bounding_box_ymin,bounding_box_ymax: bounding rectangle coordinates.
Table containing the data of the trajectories used in the analysis and displayed by the Tierpsy Tracker Viewer. Each row should have a unique pair of worm_index_joined and frame_number keys corresponding to each of the particles identified in each video frame. Additionally, this dataset will store the same attributes described in /mask:
frame_number: video frame number.worm_index_joined: same as in/plate_worms.plate_worm_id: row number in/plate_worms.skeleton_id: row in this table. It is useful to recover data after slicing using pandas.coord_x,coord_y: centroid coordinates after smoothing /plate_worms. It is used to find the ROI to calculate the skeletons. If you want to calculate the centroid features use the corresponding field in /blob_features.threshold: value used to binarize the ROI.has_skeleton:trueis the skeletonization was succesful.is_good_skel:trueif the skeleton passed the filter step. Only rows with this flag astruewill be used to calculate the skeleton features.- skel_outliers_flag: internal used to identify why a skeleton was rejected in the filter step.
roi_size: size in pixels of the region of interest. Should be constant for a given trajectory.area: expected blob area. Useful to filter spurious particles after the ROI binarization.timestamp_raw: timestamp number. Useful to find droped frames.timestamp_time: real time timestamp value.int_map_id: corresponding row in thebasename_intensities.hdf5.
coord_x,coord_y,box_length,box_width,box_orientation. features calculated using minAreaRect.area: area.perimeter: perimeter.quirkiness: defined assqrt(1 - box_width^2 / box_length^2).compactness: defined as4 * pi * area / (perimeter^2).solidity:area / convex hull areawhere the convex hull is calculated as here.intensity_mean,intensity_std: mean and standard deviation inside the thresholded region.hu0,hu1,hu2,hu3,hu4,hu5,hu6: Hu moments.
Shape (tot_valid_skel, n_segments, x-y coordinate)
Normalized coordinates (same number of points) for the skeletons and the contour in each side of the worm. The head should correspond to the first index and the tail to the last.
Shape (tot_valid_skel, n_segments)
Contour width along the skeleton.
Shape (tot_valid_skel)
Contour width of the midbody. Used to calculate the intensity maps in INT_PROFILE.
Shape (tot_valid_skel)
Contours and skeleton length in pixels before normalization and smoothing. This value is likely to be larger than the length caculated in FEAT_CREATE due to the noiser contours and probably should be deprecated.
Shape (tot_valid_skel)
Area in pixels of the binary image used to calculate the skeletons. Probably should be deprecated.
Internal. Table with the skeleton switched in INT_SKE_ORIENT.
Same as in basename.hdf5.
Shape (tot_points, x-y coordinate)
Optional see (FOOD_CNT).
Same as /trajectories_data but only containing rows where has_skeleton is true.
Shape (tot_valid_skel, n_length, n_width)
Intensity maps of the straigten worms described in INT_PROFILE. Each index in the first dimension correspond to the same row in /trajectories_data_valid. Note that the data type is float16. Cast this data to float32 or float64 before doing any operation to avoid overflows.
Shape (tot_valid_skel, n_length)
Averaged intensity along the skeleton. Calculated in INT_PROFILE and used by INT_SKE_ORIENT. The data is organized as in /straighten_worm_intensity.
basename_features.hdf5 (OpenWorm Analysis Toolbox)
This file contains the results of FEAT_CREATE. For a more detailed information of the features see the supplementary information of Yemini et al.
Contour and skeleton coordinates after smoothing. Each index in the first dimension correspond to a row in /features_timeseries.
Table containing the features that can be represented as timeseries. Each row corresponds to a single (worm_index, timestamp) pair. Additionally, this dataset will store the same attributes described in /mask
worm_index: trajectory index. Same asworm_index_joinedin /trajectories_data.timestamp: video timestamp indexes. Should be continous. The real space between indexes should be1/frames per second.skeleton_id: corresponding row in the /trajectories_data table. It should be -1 if there is not a match (dropped frames).motion_modes: vector indicating if the worm ismoving forward (1),backwards (-1)or it ispaused (0).length:(microns)skeleton length calculated using/coordinates/skeleton.head_width,midbody_width,tail_width:(microns)contour width for each worm body region.area:(microns^2)contour area calculated using the shoelace formula.area_length_ratio:(microns)area/lengthwidth_length_ratio:(no units)midbody_width/lengthmax_amplitude:(microns)maximum amplitude of the skeleton along its major axis.amplitude_ratio:(no units)ratio between the maximum amplitudes on each side of the skeleton along its major axis. The smaller amplitude is the numerator and the larger the denominator.primary_wavelength,secondary_wavelength:(microns)larger and second larger peaks of the fourier transform of the skeleton rotated over its major axis.track_length:(microns)length of the line extending from head to its tail.eccentricity:(no units)eccentricity of the worm's body calculated using the contour moments.bend_count:(no units)the number of kinks (bends) in the skeleton.tail_to_head_orientation: direction the worm is facing is measured as the angle between the head and the tail. This feature needs to be changed since its value is with respect to the image frame of reference that does not have a real meaning unless we are using chemotaxis experiments.head_orientation(degrees)direction of the head measured as the angle between 1/6 of the worm body from the head and the head tip.tail_orientation(degrees)direction of the tail measured as the angle between 1/6 of the worm body from the tail and the tail tip.eigen_projection_1,eigen_projection_2,eigen_projection_3,eigen_projection_4,eigen_projection_5,eigen_projection_6:(no units)eigenworm coefficients calculated using the Stephens et al., 2008 method. The eigenworms are calculated by applying PCA to the angles between each subsequent skeleton point (an orientation-invariant representation). The PCA components are calculated on wild-type skeletons, and account for roughly 95% of the variance in N2 shapes. Another way of looking at this is that the worm shape is compressed with roughly 5% loss.head_bend_mean,neck_bend_mean,midbody_bend_mean,hips_bend_mean,tail_bend_mean:(degrees)mean of the angles along the skeleton for each worm body region.head_bend_sd,neck_bend_sd,midbody_bend_sd,hips_bend_sd,tail_bend_sd:(degrees)standard deviation of the angles along the skeleton for each worm body region. The sign is given by the corresponding_bend_mean.head_crawling_amplitude,head_crawling_frequency,midbody_crawling_amplitude,midbody_crawling_frequencytail_crawling_amplitude,tail_crawling_frequency: Frequency and amplitude of the largest peak of the fourier transform over a time window of the body part bend_mean.head_tip_speed,head_speed,midbody_speed,tail_speed,tail_tip_speed:(micrometers/seconds)body part speed. It is signed accordingly to the segment change of direction.head_tip_motion_direction,head_motion_direction,midbody_motion_direction,tail_motion_direction,tail_tip_motion_direction:(degrees/seconds)angular speed of the respective body part.foraging_amplitude: the largest foraging angle measured (nose bend) prior to returning to a straight, unbent position.foraging_speed:(degrees/seconds)foraging angular speed. It quantifies how fast the nose is moving.path_range:(micrometers)distance of the worm’s midbody from the path centroid.path_curvature:(radians/micrometers)the angle of the worm's path divided by the distance travelled.
worm_dwelling,head_dwelling,midbody_dwelling,tail_dwelling:(seconds)time duration a body part spends in a specific region of the plate. The worm path is subdivided in uniform grids where each element diagonal is equal to the body part mean width. The stored vector contains the time spend in each grid, excluding the grids that the body part never visited.
Each time frame can be labeled according to any of the following events definitions (modified from the Supplementary Material of Yemini et al.:
-
forward: the worm is moving in forward motion. It is defined over a period of 0.5 seconds where the worm travels at least 5% of its mean length and its speed is at least 5% of its length per second. The worm must maintain this conditions almost continuously with interruptions not longer than 0.25 seconds (the interruptions allow for quick contradictory movements such as head withdrawal, body contractions, and segmentation noise). -
backward: the worm is moving in backward motion. Same asforwardexcept the midbody speed sign must be negative. -
paused: the worm is moving motion is paused. It is defined over a period of 0.5 seconds where the forward and backward speed does not exceed 2.5% of the worms length per second. Similarly toforwardthe maximum permissible interruption must be less than 0.25 seconds. -
omega_turns: the worm bends are used to find a contiguous sequence of frames wherein a large bend travels from the worm’s head, through its midbody, to its tail. The worm’s body is separated into three equal parts from its head to its tail. The mean supplementary angle is measured along each third. For omega turns, this angle must initially exceed 30° at the first but not the last third of the body (the head but not the tail). The middle third must then exceed 30°. And finally, the last but not the first third of the body must exceed 30° (the tail but not the head). This sequence of a 30° mean supplementary angle, passing continuously along the worm from head to tail, is labeled an omega turn event. -
upsilon_turns: computed nearly identically to theomega_turnbut they capture all events that escaped being labeled omega turns, wherein the mean supplementary angle exceeded 15° on one side of the worm (the first or last third of the body) while not exceeding 30° on the opposite end. -
coils: this feature is currently deactivated. It should use the annotations produced by segWorm during skeletonization. The original algorithm is based on the ratio between the contour midbody and head/tail width.
For each of the event each of the following features are calculated:
*_distance:(micromenters)distance travelled during the events.inter_*_distance:(micromenters)distance travelled between different events.*_time:(seconds)time durations of each event.inter_*_time:(seconds)time between different events.*_frequency:(1/seconds)how often an event occurs per time unit(n_events/total_time).*_time_ratio:(no units)ratio between the time spend at the event over the total trajectory time.*_distance_ratio:(no units)ratio between the total distance travelled during an event and the total distance travelled during the whole trajectory.
Set of features calculated by subdividing and reducing the features in /features_timeseries and the /features_events/worm_* .
The subdivisions can be done by movement type or/and by signed data. A feature was subdivided when the corresponding subfix is in its name. If a feature name does not contain any subdivision subfix then the reduction was applied on all the original data.
The movement subdivision are only valid for features in /features_timeseries and are:
*_forward: worm is moving forwards (motion_modes == 1).*_paused: worm is paused (motion_modes == 0).*_backward: worm is moving backwards (motion_modes == -1).
The signed data subdivision are only applied to data where the sign have meaning, e.g. midbody_speed or midbody_bend_mean and not in features like area or length. The signed data subdivisions are:
*_neg: only the negative data is considered.*_pos: only the positive data is considered.*_abs: the absolute value of the data is taken before doing the reduction.
The reduction can be done by any of the following operations on a given subdivision. The data is saved in the corresponding table name.
P10th: 10th percentile.P90th: 90th percentile.means: mean value.medians: median value (50th percentile).
Finally, there are some tables that have the subfix _split. For this tables long trajectories are splitted in shorter ones of at most split_traj_time seconds before calculating the features. This is done as an attempt to balance uneven track sizes. Otherwise a trajectory that was followed for the whole duration of the video will be counted as a single feature vector, while a trajectory that was lost and found several times will be counted as many feature vectors. This is because each time a worm is lost it would be assigned a new id when it is found again.
basename_featuresN.hdf5 (Tierpsy Features)
Same as /trajectories_data but using the video timestamp to drop duplicated or interpolate missing frames. The columns plate_worm_id, is_good_skel, has_skeleton, int_map_id are removed and the following columns are added:
was_skeletonized: flag to indiciate if this skeleton was originally skeletonized or it was obtained by interpolation.old_trajectory_data_index: helper columns that indicates the corresponding row in the\trajectories_dataon thebasename_skeletons.hdf5.
Same as /blob_features in basename_skeletons.hdf5.
Same as /food_cnt_coord in basename_skeletons.hdf5.
Contour and skeleton coordinates after smoothing. This table is linked to /trajectories_data by the column skeleton_id. An skeleton_id value of -1 means that that that specific time point was not skeletonized.
worm_index: trajectory index. Same asworm_index_joinedin /trajectories_data.timestamp: video timestamp indexes. Should be continous. The real space between indexes should be1/frames per second.
Time Series Features:
speed_{body_part}: speed respect to the body part centroid. It is signed accordingly to the segment change of direction. Availablebody_parts=head_tip,head_base,neck,midbody,hips,tail_base,tail_tip.speed: same asspeed_{body_part}but using the wormbody.angular_velocity_{body_part}: angular speed of a specific body segments. Availablebody_parts=head_tip,head_base,neck,midbody,hips,tail_base,tail_tip.angular_velocity: same asangular_velocity_{body_part}but using the wormbody.relative_to_body_speed_midbody:relative_to_{body_part1}_radial_{body_part2}:relative_to_{body_part1}_angular_{body_part2}:
| body_part1 | body_part2 |
|---|---|
| body | head_tip |
| body | neck |
| body | hips |
| body | tail_tip |
| neck | head_tip |
| head_base | head_tip |
| hips | tail_tip |
| tail_base | tail_tip |
length:(microns)skeleton length calculated using/coordinates/skeleton.area:(microns^2)contour area calculated using the shoelace formula.width_{body_part}:(microns)contour width for each worm body region. Available body_parts=head_base,midbody,tail_base.major_axis,minor_axis:(microns)features calculated using minAreaRect.major_axis=box_length,minor_axis=box_width.quirkiness:sqrt(1 - minor_axis^2 / major_axis^2).eigen_projection_[1-7]: eigenworm coefficients calculated using the Stephens et al., 2008 method.curvature_{body_part}: curvature of a specific point in the body. Availablebody_parts=head,neck,midbody,hips,tail.curvature_mean_{body_part}: mean curvature of a specific body range. Availablebody_parts=head,neck,midbody,hips,tail.curvature_std_{body_part}: standard deviation curvature of a specific body range. Availablebody_parts=head,neck,midbody,hips,tail.orientation_food_edge: orientation of the head to tail vector respect to the closest point in the food contour. It is negative if the worm head is pointing outside the food and positive if it is pointing towards the food.dist_from_food_edge: distance of the worm centroid respect to closest point in the food contour. It is negative if the worm is outside the food, an positive if it is inside.path_curvature_{body_part}: curvature along the centroid path of the respectivebody part. Availablebody_parts=body,head,midbody,tail.
Time derivatives:
d_*: Time derivative of the timeseries features.
Event flags vectors:
motion_mode:(no units)vector indicating if the worm ismoving forward (1),backwards (-1)or it ispaused (0).food_region:(no units)vector indicating if the worm position related to the food patchinside (1),edge (0)oroutside (-1).turn:(no units)vector indicating if the worm is turning (inter (1)) or not (intra (1)).
Auxiliar columns:
head_tail_distance:(microns)Euclidian Distance from the first to the last skeleton segment.coord_{x/y}_{body_part}:(microns)Centroid coordinates from a specific body_part. Availablebody_parts=body,head,midbody,tail.
This table contains the plate average for each corresponding feature stat according to the transformations explained here.
name: feature name summary. The prefix correspond to one of the features in/timeseries_data. The meaning of the postfix is explained in the table below.value: corresponding value
| postfix | meaning |
|---|---|
| 10th | 10th percentil |
| 50th | 50th percentil |
| 90th | 90th percentil |
| IQR | interquantile distance between the 25th to 75th percentile |
| norm | data normalized by the skeleton length |
| abs | use the absolute value a ventral/dorsal signed feature |
| w_forward | only the points when the worm is going forwards |
| w_backward | only the points when the worm is going barwards |
| w_paused | only the points when the worm is paused |