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Commit 30ba861a authored by Jan Fousek's avatar Jan Fousek
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HDG access check and request

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notebooks/demo.ipynb
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%% Cell type:markdown id:ef541df6-5c1a-4a0f-a069-24f110a7bf1d tags: %% Cell type:markdown id:ef541df6-5c1a-4a0f-a069-24f110a7bf1d tags:
## 1000BRAINS study, connectivity data ## 1000BRAINS study, connectivity data
%% Cell type:code id:5b441713-77b4-4e57-a188-9959c09784bd tags: %% Cell type:code id:5b441713-77b4-4e57-a188-9959c09784bd tags:
``` python ``` python
from tvb_ebrains_data import Brains1000Dataset from tvb_ebrains_data import Brains1000Dataset
``` ```
%% Output
2022-02-11 11:40:43,461 - WARNING - tvb.simulator.common - psutil module not available: no warnings will be issued when a
simulation may require more memory than available
INFO log level set to INFO
/home/izaak/local_repos/nostromo/tvb-ebrains-data/env/lib/python3.6/site-packages/tvb/datatypes/surfaces.py:63: UserWarning: Geodesic distance module is unavailable; some functionality for surfaces will be unavailable.
warnings.warn(msg)
WARNING Token required outside collaboratory environment. Set EBRAINS_TOKEN in the environment or provide directly.
%% Cell type:code id:2f47000a-9bbe-4ecb-bac1-b09490af7d7b tags: %% Cell type:code id:2f47000a-9bbe-4ecb-bac1-b09490af7d7b tags:
``` python ``` python
dataset = Brains1000Dataset() dataset = Brains1000Dataset()
print(dataset.__doc__) print(dataset.__doc__)
``` ```
%% Output %% Output
Caspers, S. et al (2021). Caspers, S. et al (2021).
1000BRAINS study, connectivity data. 1000BRAINS study, connectivity data.
https://doi.org/10.25493/6640-3XH v1.0: https://doi.org/10.25493/61QA-KP8
v1.1: https://doi.org/10.25493/6640-3XH
%% Cell type:code id:af94d470-386c-4b33-ab1a-5c4b9482c535 tags:
``` python
dataset.have_access()
```
%% Output
True
%% Cell type:markdown id:38af980a-7a02-4a13-947a-729f84494c96 tags:
If the call above returns `False`, the access request can be triggered by visiting the KG page of the dataset, or calling:
```python
dataset.request_access()
```
%% Cell type:code id:f608b41a-2bff-47b6-b30d-c99810cdb1f4 tags: %% Cell type:code id:f608b41a-2bff-47b6-b30d-c99810cdb1f4 tags:
``` python ``` python
subjs = dataset.list_subjects() subjs = dataset.list_subjects()
``` ```
%% Cell type:code id:e4c15491-0fbe-4339-b11c-dd9305a3be9d tags: %% Cell type:code id:e4c15491-0fbe-4339-b11c-dd9305a3be9d tags:
``` python ``` python
len(set(subjs)), subjs[:10] len(set(subjs)), subjs[:10]
``` ```
%% Output %% Output
(1031, (1031,
['sub_00000', ['sub_00000',
'sub_00001', 'sub_00001',
'sub_00002', 'sub_00002',
'sub_00003', 'sub_00003',
'sub_00004', 'sub_00004',
'sub_00005', 'sub_00005',
'sub_00006', 'sub_00006',
'sub_00007', 'sub_00007',
'sub_00008', 'sub_00008',
'sub_00009']) 'sub_00009'])
%% Cell type:code id:c6c583f3-8efe-4758-9ebb-6e9d9681cbb1 tags: %% Cell type:code id:c6c583f3-8efe-4758-9ebb-6e9d9681cbb1 tags:
``` python ``` python
W = dataset.load_sc('sub_00008') W = dataset.load_sc('sub_00008')
``` ```
%% Cell type:code id:4709f50f-8284-4a41-9de7-c357a9514399 tags: %% Cell type:code id:4709f50f-8284-4a41-9de7-c357a9514399 tags:
``` python ``` python
W.shape W.shape
``` ```
%% Output %% Output
(100, 100) (100, 100)
%% Cell type:markdown id:d5996ac2-f8cd-49ac-91a6-cd8c0938e15d tags: %% Cell type:markdown id:d5996ac2-f8cd-49ac-91a6-cd8c0938e15d tags:
## Parcellation-based structural connectomes (HCP) ## Parcellation-based structural connectomes (HCP)
%% Cell type:code id:2e5431ed-cbfe-42bb-9357-b4f292eae0cf tags: %% Cell type:code id:2e5431ed-cbfe-42bb-9357-b4f292eae0cf tags:
``` python ``` python
from tvb_ebrains_data import HCPDataset from tvb_ebrains_data import HCPDataset
``` ```
%% Cell type:code id:8954ff48-9b28-4dd9-95f6-02de0924e817 tags: %% Cell type:code id:8954ff48-9b28-4dd9-95f6-02de0924e817 tags:
``` python ``` python
dataset = HCPDataset() dataset = HCPDataset()
``` ```
%% Cell type:code id:a9c1fd3c-fac1-4208-bc97-d18b375263d0 tags: %% Cell type:code id:a9c1fd3c-fac1-4208-bc97-d18b375263d0 tags:
``` python ``` python
print(dataset.__doc__) print(dataset.__doc__)
``` ```
%% Output %% Output
Domhof, J. W. M., Jung, K., Eickhoff, S. B., & Popovych, O. V. (2021). Domhof, J. W. M., Jung, K., Eickhoff, S. B., & Popovych, O. V. (2021).
Parcellation-based structural and resting-state functional brain Parcellation-based structural and resting-state functional brain
connectomes of a healthy cohort [Data set]. EBRAINS. connectomes of a healthy cohort [Data set]. EBRAINS.
https://doi.org/10.25493%2F81EV-ZVT https://doi.org/10.25493%2F81EV-ZVT
%% Cell type:code id:fc84c8f1-5dc9-47ed-8df2-f14a747fa709 tags: %% Cell type:code id:fc84c8f1-5dc9-47ed-8df2-f14a747fa709 tags:
``` python ``` python
dataset.list_parcellations() dataset.list_parcellations()
``` ```
%% Output %% Output
['031-MIST', ['031-MIST',
'038-CraddockSCorr2Level', '038-CraddockSCorr2Level',
'048-HarvardOxfordMaxProbThr0', '048-HarvardOxfordMaxProbThr0',
'056-CraddockSCorr2Level', '056-CraddockSCorr2Level',
'056-MIST', '056-MIST',
'070-DesikanKilliany', '070-DesikanKilliany',
'079-Shen2013', '079-Shen2013',
'086-EconomoKoskinas', '086-EconomoKoskinas',
'092-AALV2', '092-AALV2',
'096-HarvardOxfordMaxProbThr0', '096-HarvardOxfordMaxProbThr0',
'100-Schaefer17Networks', '100-Schaefer17Networks',
'103-MIST', '103-MIST',
'108-CraddockSCorr2Level', '108-CraddockSCorr2Level',
'150-Destrieux', '150-Destrieux',
'156-Shen2013', '156-Shen2013',
'160-CraddockSCorr2Level', '160-CraddockSCorr2Level',
'167-MIST', '167-MIST',
'200-Schaefer17Networks', '200-Schaefer17Networks',
'210-Brainnetome'] '210-Brainnetome']
%% Cell type:code id:286635b0-99e2-42c2-889a-dc1126752df7 tags: %% Cell type:code id:286635b0-99e2-42c2-889a-dc1126752df7 tags:
``` python ``` python
subjs = dataset.list_subjects(parcellation='200-Schaefer17Networks') subjs = dataset.list_subjects(parcellation='200-Schaefer17Networks')
len(subjs), subjs[:10] len(subjs), subjs[:10]
``` ```
%% Output %% Output
(200, ['000', '001', '002', '003', '004', '005', '006', '007', '008', '009']) (200, ['000', '001', '002', '003', '004', '005', '006', '007', '008', '009'])
%% Cell type:code id:00af414e-941a-408d-ae3a-0010f430e00a tags: %% Cell type:code id:00af414e-941a-408d-ae3a-0010f430e00a tags:
``` python ``` python
W, D = dataset.load_sc(subject='003', parcellation='200-Schaefer17Networks') W, D = dataset.load_sc(subject='003', parcellation='200-Schaefer17Networks')
``` ```
%% Cell type:code id:44bfe644-8822-4075-b828-844c92d8b507 tags: %% Cell type:code id:44bfe644-8822-4075-b828-844c92d8b507 tags:
``` python ``` python
W.shape, D.shape W.shape, D.shape
``` ```
%% Output %% Output
((200, 200), (200, 200)) ((200, 200), (200, 200))
......
tvb_ebrains_data/data.py
+ 27
− 3
View file @ 30ba861a
...@@ -71,8 +71,28 @@ class DataProxyConnectivityDataset: ...@@ -71,8 +71,28 @@ class DataProxyConnectivityDataset:
def load_sc(self, subject): def load_sc(self, subject):
raise NotImplementedError() raise NotImplementedError()
def have_access(self):
response = requests.get(
url = f'{self.DATA_PROXY_ENDPOINT}/datasets/{self.BUCKET_NAME}/stats',
headers = self.AUTHORIZATION_HEADERS
)
if response.ok:
return True
elif response.status_code == 401:
return False
else:
raise Exception(f'Failed request: {response.reason}')
def request_access(self):
response = requests.post(
url = f'{self.DATA_PROXY_ENDPOINT}/datasets/{self.BUCKET_NAME}',
headers = self.AUTHORIZATION_HEADERS
)
if not response.ok:
raise Exception(f'Failed request: {response.reason}')
else:
print('Request for access submitted, check mail.')
class HCPDataset(DataProxyConnectivityDataset): class HCPDataset(DataProxyConnectivityDataset):
...@@ -114,11 +134,15 @@ class Brains1000Dataset(DataProxyConnectivityDataset): ...@@ -114,11 +134,15 @@ class Brains1000Dataset(DataProxyConnectivityDataset):
Caspers, S. et al (2021). Caspers, S. et al (2021).
1000BRAINS study, connectivity data. 1000BRAINS study, connectivity data.
https://doi.org/10.25493/6640-3XH v1.0: https://doi.org/10.25493/61QA-KP8
v1.1: https://doi.org/10.25493/6640-3XH
""" """
def __init__(self, version='v1.1', token=None): def __init__(self, version='v1.1', token=None):
self.version = version self.version = version
super().__init__(bucket_name="83407c06-b494-4307-861e-d06a5aecdf8a", token=token) if version=='v1.1':
super().__init__(bucket_name="83407c06-b494-4307-861e-d06a5aecdf8a", token=token)
elif version=='v1.0':
super().__init__(bucket_name="e428cb6b-0110-4205-94ac-533ca5de6bb5", token=token)
def list_subjects(self): # TODO cache this ? def list_subjects(self): # TODO cache this ?
prefix = f'{self.version}/Julich-Brain/Streamlines' prefix = f'{self.version}/Julich-Brain/Streamlines'
......
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