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%matplotlib inline
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import os
import mne
Configuration variables are read and written using the functions
:func:mne.get_config
and :func:mne.set_config
. To read a specific
configuration variable, pass its name to :func:~mne.get_config
as the
key
parameter (key
is the first parameter so you can pass it unnamed
if you want):
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print(mne.get_config('MNE_USE_CUDA'))
print(type(mne.get_config('MNE_USE_CUDA')))
Note that the string values read from the JSON file are not parsed in any
way, so :func:~mne.get_config
returns a string even for true/false config
values, rather than a Python boolean <bltin-boolean-values>
.
Similarly, :func:~mne.set_config
will only set string values (or None
values, to unset a variable):
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try:
mne.set_config('MNE_USE_CUDA', True)
except TypeError as err:
print(err)
If you're unsure whether a config variable has been set, there is a
convenient way to check it and provide a fallback in case it doesn't exist:
:func:~mne.get_config
has a default
parameter.
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print(mne.get_config('missing_config_key', default='fallback value'))
There are also two convenience modes of :func:~mne.get_config
. The first
will return a :class:dict
containing all config variables (and their
values) that have been set on your system; this is done by passing
key=None
(which is the default, so it can be omitted):
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print(mne.get_config()) # same as mne.get_config(key=None)
The second convenience mode will return a :class:tuple
of all the keys that
MNE-Python recognizes and uses, regardless of whether they've been set on
your system. This is done by passing an empty string ''
as the key
:
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print(mne.get_config(key=''))
It is possible to add config variables that are not part of the recognized
list, by passing any arbitrary key to :func:~mne.set_config
. This will
yield a warning, however, which is a nice check in cases where you meant to
set a valid key but simply misspelled it:
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mne.set_config('MNEE_USE_CUUDAA', 'false')
Let's delete that config variable we just created. To unset a config
variable, use :func:~mne.set_config
with value=None
. Since we're still
dealing with an unrecognized key (as far as MNE-Python is concerned) we'll
still get a warning, but the key will be unset:
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mne.set_config('MNEE_USE_CUUDAA', None)
assert 'MNEE_USE_CUUDAA' not in mne.get_config('')
MNE-Python stores configuration variables in a JSON
_ file. By default, this
file is located in :file:{%USERPROFILE%}\\.mne\\mne-python.json
on Windows
and :file:{$HOME}/.mne/mne-python.json
on Linux or macOS. You can get the
full path to the config file with :func:mne.get_config_path
.
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print(mne.get_config_path())
However it is not a good idea to directly edit files in the :file:.mne
directory; use the getting and setting functions described in the
previous section <config-get-set>
.
If for some reason you want to load the configuration from a different
location, you can pass the home_dir
parameter to
:func:~mne.get_config_path
, specifying the parent directory of the
:file:.mne
directory where the configuration file you wish to load is
stored.
For compatibility with :doc:MNE-C <../../install/mne_c>
, MNE-Python
also reads and writes environment variables
_ to specify configuration. This
is done with the same functions that read and write the JSON configuration,
and is controlled with the parameters use_env
and set_env
. By
default, :func:~mne.get_config
will check :data:os.environ
before
checking the MNE-Python JSON file; to check only the JSON file use
use_env=False
. To demonstrate, here's an environment variable that is not
specific to MNE-Python (and thus is not in the JSON config file):
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# make sure it's not in the JSON file (no error means our assertion held):
assert mne.get_config('PATH', use_env=False) is None
# but it *is* in the environment:
print(mne.get_config('PATH'))
Also by default, :func:~mne.set_config
will set values in both the JSON
file and in :data:os.environ
; to set a config variable only in the JSON
file use set_env=False
. Here we'll use :func:print
statement to confirm
that an environment variable is being created and deleted (we could have used
the Python assert statement <assert>
instead, but it doesn't print any
output when it succeeds so it's a little less obvious):
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mne.set_config('foo', 'bar', set_env=False)
print('foo' in os.environ.keys())
mne.set_config('foo', 'bar')
print('foo' in os.environ.keys())
mne.set_config('foo', None) # unsetting a key deletes var from environment
print('foo' in os.environ.keys())
One important configuration variable is MNE_LOGGING_LEVEL
. Throughout the
module, messages are generated describing the actions MNE-Python is taking
behind-the-scenes. How you set MNE_LOGGING_LEVEL
determines how many of
those messages you see. The default logging level on a fresh install of
MNE-Python is info
:
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print(mne.get_config('MNE_LOGGING_LEVEL'))
The logging levels that can be set as config variables are debug
,
info
, warning
, error
, and critical
. Around 90% of the log
messages in MNE-Python are info
messages, so for most users the choice is
between info
(tell me what is happening) and warning
(tell me only if
something worrisome happens). The debug
logging level is intended for
MNE-Python developers.
In an earlier section <config-get-set>
we saw how
:func:mne.set_config
is used to change the logging level for the current
Python session and all future sessions. To change the logging level only for
the current Python session, you can use :func:mne.set_log_level
instead.
The :func:~mne.set_log_level
function takes the same five string options
that are used for the MNE_LOGGING_LEVEL
config variable; additionally, it
can accept :class:int
or :class:bool
values that are equivalent to those
strings. The equivalencies are given in this table:
+----------+---------+---------+ | String | Integer | Boolean | +==========+=========+=========+ | DEBUG | 10 | | +----------+---------+---------+ | INFO | 20 | True | +----------+---------+---------+ | WARNING | 30 | False | +----------+---------+---------+ | ERROR | 40 | | +----------+---------+---------+ | CRITICAL | 50 | | +----------+---------+---------+
With many MNE-Python functions it is possible to change the logging level
temporarily for just that function call, by using the verbose
parameter.
To illustrate this, we'll load some sample data with different logging levels
set. First, with log level warning
:
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kit_data_path = os.path.join(os.path.abspath(os.path.dirname(mne.__file__)),
'io', 'kit', 'tests', 'data', 'test.sqd')
raw = mne.io.read_raw_kit(kit_data_path, verbose='warning')
No messages were generated, because none of the messages were of severity
"warning" or worse. Next, we'll load the same file with log level info
(the default level):
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raw = mne.io.read_raw_kit(kit_data_path, verbose='info')
This time, we got a few messages about extracting information from the file,
converting that information into the MNE-Python :class:~mne.Info
format,
etc. Finally, if we request debug
-level information, we get even more
detail:
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raw = mne.io.read_raw_kit(kit_data_path, verbose='debug')
We've been passing string values to the verbose
parameter, but we can see
from the table above <table-log-levels>
that verbose=True
will
give us the info
messages and verbose=False
will suppress them; this
is a useful shorthand to use in scripts, so you don't have to remember the
specific names of the different logging levels. One final note:
verbose=None
(which is the default for functions that have a verbose
parameter) will fall back on whatever logging level was most recently set by
:func:mne.set_log_level
, or if that hasn't been called during the current
Python session, it will fall back to the value of
mne.get_config('MNE_LOGGING_LEVEL')
.
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