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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') - -``` |