When an App is registered on Brainlife, a config.json
is automatically created based on the info the App creator enters via the BL GUI. There are four types of parameters:
NUMBER
STRING
ENUM
BOOL
So, it is impossible to enter a list of int
or a numpy nd.array
for instance. So, the values must be converted.
For now, we have decided not to read and convert Python dictionaries, so the BL user won’t be able to give a dictionary as a parameter value.
Case of a numpy.nd.array
It is impossible to enter a np.nd.array
in BL. So we register such parameter as a STRING
and ask the user to enter floats
separated by a comma: 10, 15, 20. In the config.json
, such parameter will be written as:
{ "param_notch_widths": "10, 15, 20" }
It was decided to enter numpy.nd.array
this way on BL to differentiate it from the way it was entered in the config.json.example
when the App is run locally (see Parameters conversion when the App runs locally) and it is easier to convert it into a numpy.nd.array
.
In the Python file, we added:
if isinstance(config['param_notch_widths'], str): config['param_notch_widths'] = list(map(float, config['param_notch_widths'].split(', '))) config['param_notch_widths'] = np.array(config['param_notch_widths'])
Case of a slice
It is also impossible to enter directly a slice
on BL. So we enter the parameter as a STRING
. In the config.json
, such parameter is written as follows:
{ config['param_picks_by_channel_indices']: "0, 10, 2" }
This parameter is entered the same way as a numpy.nd.array
. So far it is not an issue because no parameter is either a numpy.nd.array
or a slice
.
In the Python file, we added:
if isinstance(picks, str) and picks.find(",") != -1 and picks.find("[") == -1 and picks is not None: picks = list(map(int, picks.split(', '))) if len(picks) == 2: config['param_picks_by_channel_indices'] = slice(picks[0], picks[1]) elif len(picks) == 3: config['param_picks_by_channel_indices'] = slice(picks[0], picks[1], picks[2]) else: value_error_message = f"If you want to select channels using a slice, you must give two or three elements." raise ValueError(value_error_message)
Case of a tuple
A tuple
can not be entered on BL. So we registered the parameter as a STRING
. In the config.json
, such parameter is written as follows:
{ "param_baseline": 0, None }
To convert it into a tuple, in the Python file we added:
if config['param_baseline'] is not None: config['param_baseline'] = tuple(config['param_baseline'])
Case of a list of integers/floats
On Brainlife, when we enter a list, we have to use the type STRING
and so the list is considered as a string
, so they need to be converted.
Indeed, a list of floats
or integers
are written as follows in the config.json
:
{ param_picks_by_channel_types_or_names = "[0, 2, 1]" }
Don’t surround the elements in the list by quotes.
So, we first need to convert it into a list and then convert the elements of the list into the right type.
For a list of strings:
if isinstance(picks, str) and picks.find("[") != -1 and picks is not None: picks = picks.replace('[', '') picks = picks.replace(']', '') config['param_picks_by_channel_types_or_names'] = list(map(str, picks.split(', ')))
If you want to convert it into a list of floats
or ints
, just replace str
in list(map(str, picks.split(', ')))
by the type you want.
Cases when a parameter can be two types
When the App is run locally, this configuration is not an issue, but on Brainlife when you define the parameter, it must be either STRING
or NUMBER
. So when a parameter can be both a str
or a float
/ int
, we registered it as a STRING
on BL, and then we convert it as a float
or int
.
But we must be careful: we only want to convert a str
into float
/int
when the App runs on BL. For instance the parameter param_filter_length
can be “auto”, a str
with the duration in s, or ms, or a int
. So to be sure that the conversion into float
happens only on Brainlife and only when the user does want to use a float
:
if config['param_filter_length'] != "auto" and config['param_filter_length'].find("s") == -1: config['param_filter_length'] = int(config['param_filter_length'])
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