#!/usr/bin/env python
# coding: utf-8

# # B cell annotations
# 
# In this notebook, we upload cell type annotations assigned by our domain experts. These annotations were generated using markers and by interactive investigation of our .h5ad files.
# 
# As these are derived from our .h5ad files, we'll connect them to the HISE analysis chain by chaching those files and using `hisepy.upload.upload_files()`.

# In[1]:


import hisepy
from datetime import date


# For B cells, this was done in two steps - all B cells that were clustered after Immunoglobulin removal, and with subclustering of non-effector memory B cells.
# 
# Here, we'll combine these steps to build the link in our reproducibility chain.

# In[2]:


in_files = [
    '99f83994-26ee-49af-a882-c1f2558daed2', # B cell .h5ad
    '51838754-b378-4f13-b447-82511bcd0a66'  # B Memory cell focus .h5ad
]
hise_res = hisepy.reader.cache_files(in_files)


# In[3]:


out_files = [
    'annotations/pbmc_ref_b-cells-no-ig_annotations_2024-03-08.csv',
    'annotations/pbmc_ref_b-cells-mem-no-ig_annotations_2024-03-08.csv'
]


# In[4]:


study_space_uuid = '64097865-486d-43b3-8f94-74994e0a72e0'
title = 'Ref. B cell annotations {d}'.format(d = date.today())


# In[5]:


hisepy.upload.upload_files(
    files = out_files,
    study_space_id = study_space_uuid,
    title = title,
    input_file_ids = in_files
)


# In[6]:


import session_info
session_info.show()


# In[ ]: