@@ -94,7 +94,7 @@ We need to set the:
9494
9595`` datashuttle `` supports connecting to the central storage machine
9696either as a mounted drive or through SHH. \
97- See [ Set up configs for transfer(set-up-a-project-for-transfer)
97+ See [ Set up configs for transfer] ( set-up-a-project-for-transfer )
9898for detailed instructions for
9999connecting a mounted drive or by using SSH.
100100
@@ -198,7 +198,7 @@ from datashuttle import DataShuttle
198198project = DataShuttle(" my_first_project" )
199199```
200200
201- Next, we will use the ` make_config_file() ` method set the
201+ Next, we will use the [ ] ( make_config_file() ) method set the
202202configurations ('configs') for our project.
203203
204204
@@ -220,7 +220,7 @@ project.make_config_file(
220220)
221221```
222222
223- If you want to change any config in the future, use the ` update_config_file() ` method
223+ If you want to change any config in the future, use the [ ] ( update_config_file() ) method
224224
225225``` python
226226project.update_config_file(
@@ -328,7 +328,7 @@ Finally, click `Create Folders` to create the project folders.
328328:::
329329:::{tab-item} Python API
330330:sync: python
331- We will create project folders with the ` create_folders() ` method.
331+ We will create project folders with the [ ] ( create_folders() ) method.
332332
333333Following the [ NeuroBlueprint] ( https://neuroblueprint.neuroinformatics.dev/ )
334334style we will call the first subject ` sub-001 ` . Additional key-value pairs
@@ -360,8 +360,8 @@ An error will be raised if names break with the specification and
360360the folders will not be created.
361361```
362362
363- Two useful methods to automate folder creation are ` get_next_sub() ` and
364- ` get_next_ses() ` . These can be used to automatically get the next subject
363+ Two useful methods to automate folder creation are [ ] ( get_next_sub() ) and
364+ [ ] ( get_next_ses() ) . These can be used to automatically get the next subject
365365and session names in a project.
366366
367367To get the next subject in this project (` sub-002 ` ) and the next
@@ -450,7 +450,7 @@ Finally, hover the mouse over the `Directory Tree` and press `CTRL+R` to refresh
450450:::{tab-item} Python API
451451:sync: python
452452
453- ` create_folders() ` returns the full filepaths of created datatype folders.
453+ [ ] ( create_folders() ) returns the full filepaths of created datatype folders.
454454
455455These can be used in acquisition scripts to save data to these folders:
456456
@@ -543,7 +543,7 @@ Next, we will use `Custom` transfers to move only a subset of the dataset.
543543:::{tab-item} Python API
544544:sync: python
545545
546- ` upload_entire_project() ` is a high level method that uploads all files
546+ [ ] ( upload_entire_project() ) is a high level method that uploads all files
547547in the project.
548548This includes both the ` rawdata ` and ` derivatives ` top-level folders—see the
549549[ NeuroBlueprint specification] ( https://neuroblueprint.neuroinformatics.dev/latest/specification.html )
@@ -560,7 +560,7 @@ All files will be uploaded from the local version of the project to central stor
560560Navigating to the ` central_path ` in your systems file browser, the newly transferred data
561561will have appeared.
562562
563- Other methods (e.g. ` upload_rawdata() ` and ` upload_custom() ` ) provide customisable
563+ Other methods (e.g. [ ] ( upload_rawdata() ) and [ ] ( upload_custom() ) ) provide customisable
564564transfers (and every ` upload ` method has an equivalent ` download ` method).
565565
566566See the [ How to Transfer Data] ( how-to-transfer-data ) page for full details
@@ -683,8 +683,8 @@ of files will now be available in the **local path**.
683683:::{tab-item} Python API
684684:sync: python
685685
686- We will use the ` download_custom() ` method (the download equivalent method of
687- the ` upload_custom() ` ).
686+ We will use the [ ] ( download_custom() ) method (the download equivalent method of
687+ the [ ] ( upload_custom() ) ).
688688
689689Convenience tags can be used to make downloading subsets of data easier:
690690
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