|
1 | 1 | """ |
2 | | -IgorProIO Demo |
3 | | -=========================== |
| 2 | +IgorProIO Demo (BROKEN) |
| 3 | +======================= |
4 | 4 |
|
5 | 5 | """ |
6 | 6 |
|
|
17 | 17 | # Downloaded from Human Brain Project Collaboratory |
18 | 18 | # Digital Reconstruction of Neocortical Microcircuitry (nmc-portal) |
19 | 19 | # http://microcircuits.epfl.ch/#/animal/8ecde7d1-b2d2-11e4-b949-6003088da632 |
20 | | - |
21 | | - |
22 | | -datafile_url = "https://microcircuits.epfl.ch/data/released_data/B95.zip" |
23 | | -filename_zip = "B95.zip" |
24 | | -filename = "grouped_ephys/B95/B95_Ch0_IDRest_107.ibw" |
25 | | -urlretrieve(datafile_url, filename_zip) |
26 | | - |
27 | | -zip_ref = zipfile.ZipFile(filename_zip) # create zipfile object |
28 | | -zip_ref.extract(path=".", member=filename) # extract file to dir |
29 | | -zip_ref.close() |
30 | | - |
31 | | -###################################################### |
32 | | -# Once we have our data we can use `get_io` to find an |
33 | | -# io (Igor in this case). Then we read the analogsignals |
34 | | -# Finally we will make some nice plots |
35 | | -reader = get_io(filename) |
36 | | -signal = reader.read_analogsignal() |
37 | | -plt.plot(signal.times, signal) |
38 | | -plt.xlabel(signal.sampling_period.dimensionality) |
39 | | -plt.ylabel(signal.dimensionality) |
40 | | - |
41 | | -plt.show() |
| 20 | +# NOTE: this dataset is not found as the link is broken. |
| 21 | + |
| 22 | +# datafile_url = "https://microcircuits.epfl.ch/data/released_data/B95.zip" |
| 23 | +# filename_zip = "B95.zip" |
| 24 | +# filename = "grouped_ephys/B95/B95_Ch0_IDRest_107.ibw" |
| 25 | +# urlretrieve(datafile_url, filename_zip) |
| 26 | + |
| 27 | +# zip_ref = zipfile.ZipFile(filename_zip) # create zipfile object |
| 28 | +# zip_ref.extract(path=".", member=filename) # extract file to dir |
| 29 | +# zip_ref.close() |
| 30 | + |
| 31 | +# ###################################################### |
| 32 | +# # Once we have our data we can use `get_io` to find an |
| 33 | +# # io (Igor in this case). Then we read the analogsignals |
| 34 | +# # Finally we will make some nice plots |
| 35 | +# reader = get_io(filename) |
| 36 | +# signal = reader.read_analogsignal() |
| 37 | +# plt.plot(signal.times, signal) |
| 38 | +# plt.xlabel(signal.sampling_period.dimensionality) |
| 39 | +# plt.ylabel(signal.dimensionality) |
| 40 | + |
| 41 | +# plt.show() |
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