pymaid.get_user_contributions¶

pymaid.get_user_contributions(x, teams=None, remote_instance=None)[source]¶

Return number of nodes and synapses contributed by each user.

This is essentially a wrapper for pymaid.get_contributor_statistics() - if you are also interested in e.g. construction time, review time, etc. you may want to consider using get_contributor_statistics() instead.

Parameters:

x –
Which neurons to check. Can be either:
1. skeleton IDs (int or str)
2. neuron name (str, must be exact match)
3. annotation: e.g. ‘annotation:PN right’
4. CatmaidNeuron or CatmaidNeuronList object
dict (teams) –
Teams to group contributions for. Users must be logins:
```
{'teamA': ['user1', 'user2'], 'team2': ['user3'], ...]}
```
Users not part of any team, will be grouped as team 'others'.
optional –
Teams to group contributions for. Users must be logins:
```
{'teamA': ['user1', 'user2'], 'team2': ['user3'], ...]}
```
Users not part of any team, will be grouped as team 'others'.
remote_instance (CatmaidInstance, optional) – Either pass explicitly or define globally.

Returns:

DataFrame in which each row represents a user:

   user  nodes  presynapses  postsynapses  nodes_reviewed
0
1
...

Return type:

pandas.DataFrame

Examples

>>> import matplotlib.pyplot as plt
>>> # Get contributors for a single neuron
>>> cont = pymaid.get_user_contributions(2333007)
>>> # Get top 10 (by node contribution)
>>> top10 = cont.iloc[:10].set_index('user')
>>> # Plot as bar chart
>>> ax = top10.plot(kind='bar')
>>> plt.show()

>>> # Plot relative contributions
>>> cont = pymaid.get_user_contributions(2333007)
>>> cont = cont.set_index('user')
>>> # Normalize
>>> cont_rel = cont / cont.sum(axis=0).values
>>> # Plot contributors with >5% node contributions
>>> ax = cont_rel[cont_rel.nodes > .05].plot(kind='bar')
>>> plt.show()