In [1]:
import pandas as pd
import pymaid
rm = pymaid.CatmaidInstancepymaid.CatmaidInstance('server_url', 'api_token', 'http_user', 'http_password')
In [2]:
n = pymaid.get_neuron(16)
In [3]:
# Get all connectors
cn = n.connectors
# Add a column with the URL to coordinates
cn['URL'] = pymaid.url_to_coordinates(cn,
stack_id = 5,
active_node_id = cn.connector_id.values)
cn.head()
Out[3]:
In [4]:
cn.to_csv('filename.csv')
In [5]:
cn.to_clipboard()
In [6]:
pre = cn[cn.relation == 0]
In [7]:
ran = pre.sample(frac=1)
ran.head()
Out[7]:
In [8]:
post_details = pymaid.get_connector_details(n.postsynapses)
post_details.head()
Out[8]:
In [9]:
post_details[post_details.presynaptic_to_node.isnull()]
Out[9]:
In [10]:
# Now get the locations
locs = pymaid.get_node_location(post_details.presynaptic_to_node.values)
locs.head()
Out[10]:
In [11]:
cn_merged = pd.merge(post_details.set_index('presynaptic_to_node'),
locs.set_index('node_id'),
left_index=True, right_index=True)
cn_merged.head()
Out[11]:
In [12]:
cn_merged['url'] = pymaid.url_to_coordinates(cn_merged, stack_id=5)
cn_merged['neuron_name'] = cn_merged.presynaptic_to.astype(str).map(pymaid.get_names(cn_merged.presynaptic_to.values))
cn_merged['has_soma'] = cn_merged.presynaptic_to.map(pymaid.has_soma(cn_merged.presynaptic_to.values))
cn_merged.head()
Out[12]:
In [13]:
cn_merged = cn_merged[['presynaptic_to', 'neuron_name', 'has_soma', 'connector_id', 'x', 'y', 'z', 'url']]
cn_merged.head()
Out[13]:
In [14]:
cn_merged.sample(frac=1).to_clipboard()