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Diffstat (limited to 'docs/user_guide')
| -rw-r--r-- | docs/user_guide/areas_of_interest/aoi_matching.md | 48 | ||||
| -rw-r--r-- | docs/user_guide/areas_of_interest/heatmap.md | 40 | ||||
| -rw-r--r-- | docs/user_guide/areas_of_interest/introduction.md | 8 | ||||
| -rw-r--r-- | docs/user_guide/areas_of_interest/vision_cone_filtering.md | 18 | ||||
| -rw-r--r-- | docs/user_guide/gaze_features/gaze_movement.md | 163 | ||||
| -rw-r--r-- | docs/user_guide/gaze_features/gaze_position.md | 98 | ||||
| -rw-r--r-- | docs/user_guide/gaze_features/introduction.md | 7 | ||||
| -rw-r--r-- | docs/user_guide/gaze_features/scan_path.md | 169 | ||||
| -rw-r--r-- | docs/user_guide/timestamped_data/data_synchronisation.md | 106 | ||||
| -rw-r--r-- | docs/user_guide/timestamped_data/introduction.md | 6 | ||||
| -rw-r--r-- | docs/user_guide/timestamped_data/ordered_dictionary.md | 19 | ||||
| -rw-r--r-- | docs/user_guide/timestamped_data/pandas_dataframe_conversion.md | 41 | ||||
| -rw-r--r-- | docs/user_guide/timestamped_data/saving_and_loading.md | 14 |
13 files changed, 0 insertions, 737 deletions
diff --git a/docs/user_guide/areas_of_interest/aoi_matching.md b/docs/user_guide/areas_of_interest/aoi_matching.md deleted file mode 100644 index 60467f9..0000000 --- a/docs/user_guide/areas_of_interest/aoi_matching.md +++ /dev/null @@ -1,48 +0,0 @@ ---- -title: AOI matching ---- - -AOI matching -============ - -Once [AOI3DScene](../../argaze.md/#argaze.AreaOfInterest.AOI3DScene) is projected as [AOI2DScene](../../argaze.md/#argaze.AreaOfInterest.AOI2DScene), it could be needed to know which AOI is looked. - -The [AreaOfInterest](../../argaze.md/#argaze.AreaOfInterest.AOIFeatures.AreaOfInterest) class in [AOIFeatures](../../argaze.md/#argaze.AreaOfInterest.AOIFeatures) provides two ways to accomplish such task. - -## Pointer-based matching - -Test if 2D pointer is inside or not AOI using contains_point() method as illustrated below. - - - -``` python -pointer = (x, y) - -for name, aoi in aoi2D_scene.items(): - - if aoi.contains_point(pointer): - - # Do something with looked aoi - ... - -``` - -It is also possible to get where a pointer is looking inside an AOI provided that AOI is a rectangular plane: - -``` python - -inner_x, inner_y = aoi.inner_axis(pointer) - -``` - -## Circle-based matching - -As positions have limited accuracy, it is possible to define a radius around a pointer to test circle intersection with AOI. - - - -``` python - -intersection_shape, intersection_aoi_ratio, intersection_circle_ratio = aoi.circle_intersection(pointer, radius) - -``` diff --git a/docs/user_guide/areas_of_interest/heatmap.md b/docs/user_guide/areas_of_interest/heatmap.md deleted file mode 100644 index 450c033..0000000 --- a/docs/user_guide/areas_of_interest/heatmap.md +++ /dev/null @@ -1,40 +0,0 @@ ---- -title: Heatmap ---- - -Heatmap -========= - -[AOIFeatures](../../argaze.md/#argaze.AreaOfInterest.AOIFeatures) provides [Heatmap](../../argaze.md/#argaze.AreaOfInterest.AOIFeatures.Heatmap) class to draw heatmap image. - -## Point spread - -The **point_spread** method draw a gaussian point spread into heatmap image at a given pointer position. - - - -## Heatmap - -Heatmap visualisation allows to show where a pointer is most of the time. - - - -```python -from argaze.AreaOfInterest import AOIFeatures - -# Create heatmap of 800px * 600px resolution -heatmap = AOIFeatures.Heatmap((800, 600)) - -# Initialize heatmap -heatmap.init() - -# Assuming a pointer position (x, y) is moving inside frame -...: - - # Update heatmap at pointer position - heatmap.update((x, y), sigma=0.05) - - # Do something with heatmap image - ... heatmap.image - -```
\ No newline at end of file diff --git a/docs/user_guide/areas_of_interest/introduction.md b/docs/user_guide/areas_of_interest/introduction.md deleted file mode 100644 index 9467963..0000000 --- a/docs/user_guide/areas_of_interest/introduction.md +++ /dev/null @@ -1,8 +0,0 @@ -About Areas Of Interest (AOI) -============================= - -The [AreaOfInterest submodule](../../argaze.md/#argaze.AreaOfInterest) allows to deal with AOI through a set of high level classes: - -* [AOIFeatures](../../argaze.md/#argaze.AreaOfInterest.AOIFeatures) -* [AOI3DScene](../../argaze.md/#argaze.AreaOfInterest.AOI3DScene) -* [AOI2DScene](../../argaze.md/#argaze.AreaOfInterest.AOI2DScene)
\ No newline at end of file diff --git a/docs/user_guide/areas_of_interest/vision_cone_filtering.md b/docs/user_guide/areas_of_interest/vision_cone_filtering.md deleted file mode 100644 index 5c377bf..0000000 --- a/docs/user_guide/areas_of_interest/vision_cone_filtering.md +++ /dev/null @@ -1,18 +0,0 @@ -Vision cone filtering -===================== - -The [AOI3DScene](../../argaze.md/#argaze.AreaOfInterest.AOI3DScene) provides cone clipping support in order to select only AOI which are inside vision cone field. - - - -``` python -# Transform scene into camera referential -aoi3D_camera = aoi3D_scene.transform(tvec, rmat) - -# Get aoi inside vision cone field -# The vision cone tip is positionned behind the head -aoi3D_inside, aoi3D_outside = aoi3D_camera.vision_cone(cone_radius=300, cone_height=150, cone_tip=[0., 0., -20.]) - -# Keep only aoi inside vision cone field -aoi3D_scene = aoi3D_scene.copy(exclude=aoi3D_outside.keys()) -``` diff --git a/docs/user_guide/gaze_features/gaze_movement.md b/docs/user_guide/gaze_features/gaze_movement.md deleted file mode 100644 index 83f67e1..0000000 --- a/docs/user_guide/gaze_features/gaze_movement.md +++ /dev/null @@ -1,163 +0,0 @@ -Gaze movement -============= - -## Definition - -!!! note - - *"The act of classifying eye movements into distinct events is, on a general level, driven by a desire to isolate different intervals of the data stream strongly correlated with certain oculomotor or cognitive properties."* - - Citation from ["One algorithm to rule them all? An evaluation and discussion of ten eye movement event-detection algorithms"](https://link.springer.com/article/10.3758/s13428-016-0738-9) article. - -[GazeFeatures](../../argaze.md/#argaze.GazeFeatures) defines abstract [GazeMovement](../../argaze.md/#argaze.GazeFeatures.GazeMovement) class, then abstract [Fixation](../../argaze.md/#argaze.GazeFeatures.Fixation) and [Saccade](../../argaze.md/#argaze.GazeFeatures.Saccade) classes which inherit from [GazeMovement](../../argaze.md/#argaze.GazeFeatures.GazeMovement). - -The **positions** [GazeMovement](../../argaze.md/#argaze.GazeFeatures.GazeMovement) attribute contain all [GazePositions](../../argaze.md/#argaze.GazeFeatures.GazePosition) belonging to itself. - - - -## Identification - -[GazeFeatures](../../argaze.md/#argaze.GazeFeatures) defines abstract [GazeMovementIdentifier](../../argaze.md/#argaze.GazeFeatures.GazeMovementIdentifier) classe to let add various identification algorithms. - -Some gaze movement identification algorithms are available thanks to [GazeAnalysis](../../argaze.md/#argaze.GazeAnalysis) submodule: - -* [Dispersion threshold identification (I-DT)](../../argaze.md/#argaze.GazeAnalysis.DispersionThresholdIdentification) -* [Velocity threshold identification (I-VT)](../../argaze.md/#argaze.GazeAnalysis.VelocityThresholdIdentification) - -### Identify method - -[GazeMovementIdentifier.identify](../../argaze.md/#argaze.GazeFeatures.GazeMovementIdentifier.identify) method allows to fed its identification algorithm with successive gaze positions to output Fixation, Saccade or any kind of GazeMovement instances. - -Here is a sample of code based on [I-DT](../../argaze.md/#argaze.GazeAnalysis.DispersionThresholdIdentification) algorithm to illustrate how to use it: - -``` python -from argaze import GazeFeatures -from argaze.GazeAnalysis import DispersionThresholdIdentification - -# Create a gaze movement identifier based on dispersion algorithm with 50px max deviation 200 ms max duration thresholds -gaze_movement_identifier = DispersionThresholdIdentification.GazeMovementIdentifier(50, 200) - -# Assuming that timestamped gaze positions are provided through live stream or later data reading -...: - - gaze_movement = gaze_movement_identifier.identify(timestamp, gaze_position) - - # Fixation identified - if GazeFeatures.is_fixation(gaze_movement): - - # Access to first gaze position of identified fixation - start_ts, start_position = gaze_movement.positions.first - - # Access to fixation duration - print('duration: {gaze_movement.duration}') - - # Iterate over all gaze positions of identified fixation - for ts, position in gaze_movement.positions.items(): - - # Do something with each fixation position - ... - - # Saccade identified - elif GazeFeatures.is_saccade(gaze_movement): - - # Access to first gaze position of identified saccade - start_ts, start_position = gaze_movement.positions.first - - # Access to saccade amplitude - print('amplitude: {gaze_movement.amplitude}') - - # Iterate over all gaze positions of identified saccade - for ts, position in gaze_movement.positions.items(): - - # Do something with each saccade position - ... - - # No gaze movement identified - else: - - continue - -``` - -### Browse method - -[GazeMovementIdentifier.browse](../../argaze.md/#argaze.GazeFeatures.GazeMovementIdentifier.browse) method allows to pass a [TimeStampedGazePositions](../../argaze.md/#argaze.GazeFeatures.TimeStampedGazePositions) buffer to apply identification algorithm on all gaze positions inside. - -Identified gaze movements are returned through: - -* [TimeStampedGazeMovements](../../argaze.md/#argaze.GazeFeatures.TimeStampedGazeMovements) instance where all fixations are stored by starting gaze position timestamp. -* [TimeStampedGazeMovements](../../argaze.md/#argaze.GazeFeatures.TimeStampedGazeMovements) instance where all saccades are stored by starting gaze position timestamp. -* [TimeStampedGazeStatus](../../argaze.md/#argaze.GazeFeatures.TimeStampedGazeStatus) instance where all gaze positions are linked to a fixation or saccade index. - -``` python -# Assuming that timestamped gaze positions are provided through data reading - -ts_fixations, ts_saccades, ts_status = gaze_movement_identifier.browse(ts_gaze_positions) - -``` - -* ts_fixations would look like: - -|timestamp|positions |duration|dispersion|focus | -|:--------|:-------------------------------------------------------------|:-------|:---------|:--------| -|60034 |{"60034":[846,620], "60044":[837,641], "60054":[835,649], ...}|450 |40 |(840,660)| -|60504 |{"60504":[838,667], "60514":[838,667], "60524":[837,669], ...}|100 |38 |(834,651)| -|... |... |... |.. |... | - -* ts_saccades would look like: - -|timestamp|positions |duration| -|:--------|:---------------------------------------|:-------| -|60484 |{"60484":[836, 669], "60494":[837, 669]}|10 | -|60594 |{"60594":[833, 613], "60614":[927, 601]}|20 | -|... |... |... | - -* ts_status would look like: - -|timestamp|position |type |index| -|:--------|:---------|:-------|:----| -|60034 |(846, 620)|Fixation|1 | -|60044 |(837, 641)|Fixation|1 | -|... |... |... |. | -|60464 |(836, 668)|Fixation|1 | -|60474 |(836, 668)|Fixation|1 | -|60484 |(836, 669)|Saccade |1 | -|60494 |(837, 669)|Saccade |1 | -|60504 |(838, 667)|Fixation|2 | -|60514 |(838, 667)|Fixation|2 | -|... |... |... |. | -|60574 |(825, 629)|Fixation|2 | -|60584 |(829, 615)|Fixation|2 | -|60594 |(833, 613)|Saccade |2 | -|60614 |(927, 601)|Saccade |2 | -|60624 |(933, 599)|Fixation|3 | -|60634 |(934, 603)|Fixation|3 | -|... |... |... |. | - - -!!! note - [TimeStampedGazeMovements](../../argaze.md/#argaze.GazeFeatures.TimeStampedGazeMovements), [TimeStampedGazeMovements](../../argaze.md/#argaze.GazeFeatures.TimeStampedGazeMovements) and [TimeStampedGazeStatus](../../argaze.md/#argaze.GazeFeatures.TimeStampedGazeStatus) classes inherit from [TimeStampedBuffer](../../argaze.md/#argaze.DataStructures.TimeStampedBuffer) class. - - Read [Timestamped data](../timestamped_data/introduction.md) section to understand all features it provides. - -### Generator method - -[GazeMovementIdentifier](../../argaze.md/#argaze.GazeFeatures.GazeMovementIdentifier) can be called with a [TimeStampedGazePositions](../../argaze.md/#argaze.GazeFeatures.TimeStampedGazePositions) buffer in argument to generate gaze movement each time one is identified. - -``` python -# Assuming that timestamped gaze positions are provided through data reading - -for ts, gaze_movement in gaze_movement_identifier(ts_gaze_positions): - - # Fixation identified - if GazeFeatures.is_fixation(gaze_movement): - - # Do something with each fixation - ... - - # Saccade identified - elif GazeFeatures.is_saccade(gaze_movement): - - # Do something with each saccade - ... -```
\ No newline at end of file diff --git a/docs/user_guide/gaze_features/gaze_position.md b/docs/user_guide/gaze_features/gaze_position.md deleted file mode 100644 index 48495b4..0000000 --- a/docs/user_guide/gaze_features/gaze_position.md +++ /dev/null @@ -1,98 +0,0 @@ -Gaze position -============= - -[GazeFeatures](../../argaze.md/#argaze.GazeFeatures) defines a [GazePosition](../../argaze.md/#argaze.GazeFeatures.GazePosition) class to handle point coordinates with a precision value. - -``` python -from argaze import GazeFeatures - -# Define a basic gaze position -gaze_position = GazeFeatures.GazePosition((123, 456)) - -# Define a gaze position with a precision value -gaze_position = GazeFeatures.GazePosition((789, 765), precision=10) - -# Access to gaze position value and precision -print(f'position: {gaze_position.value}') -print(f'precision: {gaze_position.precision}') - -``` - -## Validity - -[GazeFeatures](../../argaze.md/#argaze.GazeFeatures) defines also a [UnvalidGazePosition](../../argaze.md/#argaze.GazeFeatures.UnvalidGazePosition) class that inherits from [GazePosition](../../argaze.md/#argaze.GazeFeatures.GazePosition) to handle case where no gaze position exists because of any specific device reason. - -``` python -from argaze import GazeFeatures - -# Define a basic unvalid gaze position -gaze_position = GazeFeatures.UnvalidGazePosition() - -# Define a basic unvalid gaze position with a message value -gaze_position = GazeFeatures.UnvalidGazePosition("Something bad happened") - -# Access to gaze position validity -print(f'validity: {gaze_position.valid}') - -``` - -## Distance - -[GazePosition](../../argaze.md/#argaze.GazeFeatures.GazePosition) class provides a **distance** method to calculate the distance to another gaze position instance. - - - -``` python -# Distance between A and B positions -d = gaze_position_A.distance(gaze_position_B) -``` - -## Overlapping - -[GazePosition](../../argaze.md/#argaze.GazeFeatures.GazePosition) class provides an **overlap** method to test if a gaze position overlaps another one considering their precisions. - - - -``` python -# Check that A overlaps B -if gaze_position_A.overlap(gaze_position_B): - - # Do something if A overlaps B - ... - -# Check that A overlaps B and B overlaps A -if gaze_position_A.overlap(gaze_position_B, both=True): - - # Do something if A overlaps B AND B overlaps A - ... -``` - -## Timestamped gaze positions - -[TimeStampedGazePositions](../../argaze.md/#argaze.GazeFeatures.TimeStampedGazePositions) inherits from [TimeStampedBuffer](../../argaze.md/#argaze.DataStructures.TimeStampedBuffer) class to handle especially gaze positions. - -### Import from dataframe - -It is possible to load timestamped gaze positions from a [Pandas DataFrame](https://pandas.pydata.org/docs/getting_started/intro_tutorials/01_table_oriented.html#min-tut-01-tableoriented) object. - -```python -import pandas - -# Load gaze positions from a CSV file into Panda Dataframe -dataframe = pandas.read_csv('gaze_positions.csv', delimiter="\t", low_memory=False) - -# Convert Panda dataframe into TimestampedGazePositions buffer precising the use of each specific column labels -ts_gaze_positions = GazeFeatures.TimeStampedGazePositions.from_dataframe(dataframe, timestamp = 'Recording timestamp [ms]', x = 'Gaze point X [px]', y = 'Gaze point Y [px]') - -``` -### Iterator - -Like [TimeStampedBuffer](../../argaze.md/#argaze.DataStructures.TimeStampedBuffer), [TimeStampedGazePositions](../../argaze.md/#argaze.GazeFeatures.TimeStampedGazePositions) class provides iterator feature: - -```python -for timestamp, gaze_position in ts_gaze_positions.items(): - - # Do something with each gaze position - ... - -``` diff --git a/docs/user_guide/gaze_features/introduction.md b/docs/user_guide/gaze_features/introduction.md deleted file mode 100644 index bf818ba..0000000 --- a/docs/user_guide/gaze_features/introduction.md +++ /dev/null @@ -1,7 +0,0 @@ -Gaze analysis -============= - -This section refers to: - -* [GazeFeatures](../../argaze.md/#argaze.GazeFeatures) -* [GazeAnalysis](../../argaze.md/#argaze.GazeAnalysis)
\ No newline at end of file diff --git a/docs/user_guide/gaze_features/scan_path.md b/docs/user_guide/gaze_features/scan_path.md deleted file mode 100644 index 46af28b..0000000 --- a/docs/user_guide/gaze_features/scan_path.md +++ /dev/null @@ -1,169 +0,0 @@ -Scan path -========= - -[GazeFeatures](../../argaze.md/#argaze.GazeFeatures) defines classes to handle successive fixations/saccades and analyse their spatial or temporal properties. - -## Fixation based scan path - -### Definition - -The [ScanPath](../../argaze.md/#argaze.GazeFeatures.ScanPath) class is defined as a list of [ScanSteps](../../argaze.md/#argaze.GazeFeatures.ScanStep) which are defined as a fixation and a consecutive saccade. - - - -As fixations and saccades are identified, the scan path is built by calling respectively [append_fixation](../../argaze.md/#argaze.GazeFeatures.ScanPath.append_fixation) and [append_saccade](../../argaze.md/#argaze.GazeFeatures.ScanPath.append_saccade) methods. - -### Analysis - -[GazeFeatures](../../argaze.md/#argaze.GazeFeatures) defines abstract [ScanPathAnalyzer](../../argaze.md/#argaze.GazeFeatures.ScanPathAnalyzer) classe to let add various analysis algorithms. - -Some scan path analysis are available thanks to [GazeAnalysis](../../argaze.md/#argaze.GazeAnalysis) submodule: - -* [K-Coefficient](../../argaze.md/#argaze.GazeAnalysis.KCoefficient) -* [Nearest Neighbor Index](../../argaze.md/#argaze.GazeAnalysis.NearestNeighborIndex) -* [Exploit Explore Ratio](../../argaze.md/#argaze.GazeAnalysis.ExploitExploreRatio) - -### Example - -Here is a sample of code to illustrate how to built a scan path and analyze it: - -``` python -from argaze import GazeFeatures -from argaze.GazeAnalysis import KCoefficient - -# Create a empty scan path -scan_path = GazeFeatures.ScanPath() - -# Create a K coefficient analyzer -kc_analyzer = KCoefficient.ScanPathAnalyzer() - -# Assuming a gaze movement is identified at ts time -...: - - # Fixation identified - if GazeFeatures.is_fixation(gaze_movement): - - # Append fixation to scan path : no step is created - scan_path.append_fixation(ts, gaze_movement) - - # Saccade identified - elif GazeFeatures.is_saccade(gaze_movement): - - # Append saccade to scan path : a new step should be created - new_step = scan_path.append_saccade(data_ts, gaze_movement) - - # Analyse scan path - if new_step: - - K = kc_analyzer.analyze(scan_path) - - # Do something with K metric - ... -``` - -## AOI based scan path - -### Definition - -The [AOIScanPath](../../argaze.md/#argaze.GazeFeatures.AOIScanPath) class is defined as a list of [AOIScanSteps](../../argaze.md/#argaze.GazeFeatures.AOIScanStep) which are defined as set of consecutives fixations looking at a same Area Of Interest (AOI) and a consecutive saccade. - - - -As fixations and saccades are identified, the scan path is built by calling respectively [append_fixation](../../argaze.md/#argaze.GazeFeatures.AOIScanPath.append_fixation) and [append_saccade](../../argaze.md/#argaze.GazeFeatures.AOIScanPath.append_saccade) methods. - -### Analysis - -[GazeFeatures](../../argaze.md/#argaze.GazeFeatures) defines abstract [AOIScanPathAnalyzer](../../argaze.md/#argaze.GazeFeatures.AOIScanPathAnalyzer) classe to let add various analysis algorithms. - -Some scan path analysis are available thanks to [GazeAnalysis](../../argaze.md/#argaze.GazeAnalysis) submodule: - -* [Transition matrix](../../argaze.md/#argaze.GazeAnalysis.TransitionMatrix) -* [Entropy](../../argaze.md/#argaze.GazeAnalysis.Entropy) -* [Lempel-Ziv complexity](../../argaze.md/#argaze.GazeAnalysis.LempelZivComplexity) -* [N-Gram](../../argaze.md/#argaze.GazeAnalysis.NGram) -* [K-modified coefficient](../../argaze.md/#argaze.GazeAnalysis.KCoefficient) - -### Example - -Here is a sample of code to illustrate how to built a AOI scan path and analyze it: - -``` python -from argaze import GazeFeatures -from argaze.GazeAnalysis import LempelZivComplexity - -# Assuming all AOI names are listed -... - -# Create a empty AOI scan path -aoi_scan_path = GazeFeatures.AOIScanPath(aoi_names) - -# Create a Lempel-Ziv complexity analyzer -lzc_analyzer = LempelZivComplexity.AOIScanPathAnalyzer() - -# Assuming a gaze movement is identified at ts time -...: - - # Fixation identified - if GazeFeatures.is_fixation(gaze_movement): - - # Assuming fixation is detected as inside an AOI - ... - - # Append fixation to AOI scan path : a new step should be created - new_step = aoi_scan_path.append_fixation(ts, gaze_movement, looked_aoi_name) - - # Analyse AOI scan path - if new_step: - - LZC = kc_analyzer.analyze(aoi_scan_path) - - # Do something with LZC metric - ... - - # Saccade identified - elif GazeFeatures.is_saccade(gaze_movement): - - # Append saccade to scan path : no step is created - aoi_scan_path.append_saccade(data_ts, gaze_movement) - -``` - -### Advanced - -The [AOIScanPath](../../argaze.md/#argaze.GazeFeatures.AOIScanPath) class provides some advanced features to analyse it. - -#### Letter sequence - -When a new [AOIScanStep](../../argaze.md/#argaze.GazeFeatures.AOIScanStep) is created, the [AOIScanPath](../../argaze.md/#argaze.GazeFeatures.AOIScanPath) internally affects a unique letter index related to its AOI to ease pattern analysis. -Then, the [AOIScanPath letter_sequence](../../argaze.md/#argaze.GazeFeatures.AOIScanPath.letter_sequence) property returns the concatenation of each [AOIScanStep](../../argaze.md/#argaze.GazeFeatures.AOIScanStep) letter. -The [AOIScanPath get_letter_aoi](../../argaze.md/#argaze.GazeFeatures.AOIScanPath.get_letter_aoi) method helps to get back the AOI related to a letter index. - -``` python -# Assuming the following AOI scan path is built: Foo > Bar > Shu > Foo -aoi_scan_path = ... - -# Letter sequence representation should be: 'ABCA' -print(aoi_scan_path.letter_sequence) - -# Output should be: 'Bar' -print(aoi_scan_path.get_letter_aoi('B')) - -``` - -#### Transition matrix - -When a new [AOIScanStep](../../argaze.md/#argaze.GazeFeatures.AOIScanStep) is created, the [AOIScanPath](../../argaze.md/#argaze.GazeFeatures.AOIScanPath) internally counts the number of transitions from an AOI to another AOI to ease Markov chain analysis. -Then, the [AOIScanPath transition_matrix](../../argaze.md/#argaze.GazeFeatures.AOIScanPath.transition_matrix) property returns a [Pandas DataFrame](https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.html) where indexes are transition departures and columns are transition destinations. - -Here is an exemple of transition matrix for the following [AOIScanPath](../../argaze.md/#argaze.GazeFeatures.AOIScanPath): Foo > Bar > Shu > Foo > Bar - -| |Foo|Bar|Shu| -|:--|:--|:--|:--| -|Foo|0 |2 |0 | -|Bar|0 |0 |1 | -|Shu|1 |0 |0 | - - -#### Fixations count - -The [AOIScanPath fixations_count](../../argaze.md/#argaze.GazeFeatures.AOIScanPath.fixations_count) method returns the total number of fixations in the whole scan path and a dictionary to get the fixations count per AOI. diff --git a/docs/user_guide/timestamped_data/data_synchronisation.md b/docs/user_guide/timestamped_data/data_synchronisation.md deleted file mode 100644 index 5190eab..0000000 --- a/docs/user_guide/timestamped_data/data_synchronisation.md +++ /dev/null @@ -1,106 +0,0 @@ -Data synchronisation -==================== - -Recorded data needs to be synchronized to link them before further processings. - -The [TimeStampedBuffer](../../argaze.md/#argaze.DataStructures.TimeStampedBuffer) class provides various methods to help in such task. - -## Pop last before - - - -The code below shows how to use [pop_last_before](../../argaze.md/#argaze.DataStructures.TimeStampedBuffer.pop_last_before) method in order to synchronise two timestamped data buffers with different timestamps: - -``` python -from argaze import DataStructures - -# Assuming A_data_record and B_data_record are TimeStampedBuffer instances with different timestamps - -for A_ts, A_data in A_data_record.items(): - - try: - - # Get nearest B data before current A data and remove all B data before (including the returned one) - B_ts, B_data = B_data_record.pop_last_before(A_ts) - - # No data stored before A_ts timestamp - except KeyError: - - pass - -``` - -## Pop last until - - - -The code below shows how to use [pop_last_until](../../argaze.md/#argaze.DataStructures.TimeStampedBuffer.pop_last_until) method in order to synchronise two timestamped data buffers with different timestamps: - -``` python -from argaze import DataStructures - -# Assuming A_data_record and B_data_record are TimeStampedBuffer instances with different timestamps - -for A_ts, A_data in A_data_record.items(): - - try: - - # Get nearest B data after current A data and remove all B data before - B_ts, B_data = B_data_record.pop_last_until(A_ts) - - # No data stored until A_ts timestamp - except KeyError: - - pass - -``` - -## Get last before - - - -The code below shows how to use [get_last_before](../../argaze.md/#argaze.DataStructures.TimeStampedBuffer.get_last_before) method in order to synchronise two timestamped data buffers with different timestamps: - -``` python -from argaze import DataStructures - -# Assuming A_data_record and B_data_record are TimeStampedBuffer instances with different timestamps - -for A_ts, A_data in A_data_record.items(): - - try: - - # Get nearest B data before current A data - B_ts, B_data = B_data_record.get_last_before(A_ts) - - # No data stored before A_ts timestamp - except KeyError: - - pass - -``` - -## Get last until - - - -The code below shows how to use [get_last_until](../../argaze.md/#argaze.DataStructures.TimeStampedBuffer.get_last_until) method in order to synchronise two timestamped data buffers with different timestamps: - -``` python -from argaze import DataStructures - -# Assuming A_data_record and B_data_record are TimeStampedBuffer instances with different timestamps - -for A_ts, A_data in A_data_record.items(): - - try: - - # Get nearest B data after current A data - B_ts, B_data = B_data_record.get_last_until(A_ts) - - # No data stored until A_ts timestamp - except KeyError: - - pass - -``` diff --git a/docs/user_guide/timestamped_data/introduction.md b/docs/user_guide/timestamped_data/introduction.md deleted file mode 100644 index 974e2be..0000000 --- a/docs/user_guide/timestamped_data/introduction.md +++ /dev/null @@ -1,6 +0,0 @@ -Timestamped data -================ - -Working with wearable eye tracker devices implies to handle various timestamped data like gaze positions, pupills diameter, fixations, saccades, ... - -This section mainly refers to [DataStructures.TimeStampedBuffer](../../argaze.md/#argaze.DataStructures.TimeStampedBuffer) class. diff --git a/docs/user_guide/timestamped_data/ordered_dictionary.md b/docs/user_guide/timestamped_data/ordered_dictionary.md deleted file mode 100644 index 64dd899..0000000 --- a/docs/user_guide/timestamped_data/ordered_dictionary.md +++ /dev/null @@ -1,19 +0,0 @@ -Ordered dictionary -================== - -[TimeStampedBuffer](../../argaze.md/#argaze.DataStructures.TimeStampedBuffer) class inherits from [OrderedDict](https://docs.python.org/3/library/collections.html#collections.OrderedDict) as data are de facto ordered by time. - -Any data type can be stored using int or float keys as timestamp. - -```python -from argaze import DataStructures - -# Create a timestamped data buffer -ts_data = DataStructures.TimeStampedBuffer() - -# Store any data type using numeric keys -ts_data[0] = 123 -ts_data[0.1] = "message" -ts_data[0.23] = {"key": value} -... -``` diff --git a/docs/user_guide/timestamped_data/pandas_dataframe_conversion.md b/docs/user_guide/timestamped_data/pandas_dataframe_conversion.md deleted file mode 100644 index 7614e73..0000000 --- a/docs/user_guide/timestamped_data/pandas_dataframe_conversion.md +++ /dev/null @@ -1,41 +0,0 @@ ---- -title: Pandas DataFrame conversion ---- - -Pandas DataFrame conversion -=========================== - -A [Pandas DataFrame](https://pandas.pydata.org/docs/getting_started/intro_tutorials/01_table_oriented.html#min-tut-01-tableoriented) is a python data structure allowing powerful table processings. - -## Export as dataframe - -[TimeStampedBuffer](../../argaze.md/#argaze.DataStructures.TimeStampedBuffer) instance can be converted into dataframe provided that data values are stored as dictionaries. - -```python -from argaze import DataStructures - -# Create a timestamped data buffer -ts_data = DataStructures.TimeStampedBuffer() - -# Store various data as dictionary -ts_data[10] = {"A_key": 0, "B_key": 0.123}} -ts_data[20] = {"A_key": 4, "B_key": 0.567}} -ts_data[30] = {"A_key": 8, "B_key": 0.901}} -... - -# Convert timestamped data buffer into dataframe -ts_buffer_dataframe = ts_buffer.as_dataframe() -``` - -ts_buffer_dataframe would look like: - -|timestamp|A_key|B_key| -|:--------|:----|:----| -|10 |0 |0.123| -|20 |4 |0.567| -|30 |8 |0.901| -|... |... |... | - -## Import from dataframe - -Reversely, [TimeStampedBuffer](../../argaze.md/#argaze.DataStructures.TimeStampedBuffer) instance can be created from dataframe, as a result of which each dataframe columns label will become a key of data value dictionary. Notice that the column containing timestamp values have to be called 'timestamp'. diff --git a/docs/user_guide/timestamped_data/saving_and_loading.md b/docs/user_guide/timestamped_data/saving_and_loading.md deleted file mode 100644 index 4e6a094..0000000 --- a/docs/user_guide/timestamped_data/saving_and_loading.md +++ /dev/null @@ -1,14 +0,0 @@ -Saving and loading -================== - -[TimeStampedBuffer](../../argaze.md/#argaze.DataStructures.TimeStampedBuffer) instance can be saved as and loaded from JSON file format. - -```python - -# Save -ts_data.to_json('./data.json') - -# Load -ts_data = DataStructures.TimeStampedBuffer.from_json('./data.json') - -``` |