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diff --git a/docs/user_guide/timestamped_data/data_synchronisation.md b/docs/user_guide/timestamped_data/data_synchronisation.md new file mode 100644 index 0000000..4454fa4 --- /dev/null +++ b/docs/user_guide/timestamped_data/data_synchronisation.md @@ -0,0 +1,106 @@ +Data synchronisation +==================== + +Recorded data needs to be synchronized to link them before further processings. + +The [TimeStampedBuffer](/argaze/#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/#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](/argaze/#argaze.DataStructures.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/#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](/argaze/#argaze.DataStructures.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/#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](/argaze/#argaze.DataStructures.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/#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 new file mode 100644 index 0000000..2cee263 --- /dev/null +++ b/docs/user_guide/timestamped_data/introduction.md @@ -0,0 +1,6 @@ +Timestamped data +================ + +Working with wearable eye tracker devices implies to handle various timestamped data like frames, gaze positions, pupils diameter, fixations, saccades, ... + +This section mainly refers to [DataStructures.TimeStampedBuffer](/argaze/#argaze.DataStructures.TimeStampedBuffer) class. diff --git a/docs/user_guide/timestamped_data/ordered_dictionary.md b/docs/user_guide/timestamped_data/ordered_dictionary.md new file mode 100644 index 0000000..8c93fc6 --- /dev/null +++ b/docs/user_guide/timestamped_data/ordered_dictionary.md @@ -0,0 +1,19 @@ +Ordered dictionary +================== + +[TimeStampedBuffer](/argaze/#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 new file mode 100644 index 0000000..caddb11 --- /dev/null +++ b/docs/user_guide/timestamped_data/pandas_dataframe_conversion.md @@ -0,0 +1,31 @@ +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. + +[TimeStampedBuffer](/argaze/#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| +|... |... |... |
\ No newline at end of file diff --git a/docs/user_guide/timestamped_data/saving_and_loading.md b/docs/user_guide/timestamped_data/saving_and_loading.md new file mode 100644 index 0000000..d3f2b9c --- /dev/null +++ b/docs/user_guide/timestamped_data/saving_and_loading.md @@ -0,0 +1,14 @@ +Saving and loading +================== + +[TimeStampedBuffer](/argaze/#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') + +``` |