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real_multi_modality #459

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11 changes: 11 additions & 0 deletions .gitignore
Original file line number Diff line number Diff line change
Expand Up @@ -14,3 +14,14 @@ temp_data
*.egg*
__pycache__
build/
*.log

#ignore example result
examples/**/*.h5ad
examples/tuning/**/*.yaml
examples/tuning/**/*.csv
examples/tuning/**/*.sh
examples/tuning/**/*.h5
examples/tuning/**/*.tar.gz
examples/tuning/**/*.tif
examples/tuning/**/*.txt
2 changes: 1 addition & 1 deletion .pre-commit-config.yaml
Original file line number Diff line number Diff line change
Expand Up @@ -33,7 +33,7 @@ repos:
args: [--line-width, "120", --profile, black]

- repo: https://github.com/PyCQA/docformatter
rev: v1.7.5
rev: eb1df34
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hooks:
- id: docformatter
name: Format docstring
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64 changes: 32 additions & 32 deletions README.md

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101 changes: 101 additions & 0 deletions dance/atlas/data_dropbox_upload.py
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Upload data to dropbox and get the download link

Original file line number Diff line number Diff line change
@@ -0,0 +1,101 @@
import json
import os
import pathlib

import dropbox
import numpy as np
import pandas as pd
import scanpy as sc
from dropbox.exceptions import ApiError, AuthError

from dance.utils import logger


def upload_file_to_dropbox(dropbox_path, access_token, local_path):
dbx = dropbox.Dropbox(access_token)

# Verify access token
try:
dbx.users_get_current_account()
except AuthError as err:
print("ERROR: Invalid access token; please check your access token.")
return None
try:
file_upload(dbx=dbx, local_path=local_path, remote_path=dropbox_path)
print("Upload successful.")
except ApiError as err:
print(f"API error: {err}")
return None


def file_upload(dbx: dropbox.Dropbox, local_path: pathlib.Path, remote_path: str):
CHUNKSIZE = 100 * 1024 * 1024
upload_session_start_result = dbx.files_upload_session_start(b'')
cursor = dropbox.files.UploadSessionCursor(session_id=upload_session_start_result.session_id, offset=0)
with local_path.open("rb") as f:
while True:
data = f.read(CHUNKSIZE)
if data == b"":
break
logger.debug("Pushing %d bytes", len(data))
dbx.files_upload_session_append_v2(data, cursor)
cursor.offset += len(data)
commit = dropbox.files.CommitInfo(path=remote_path)
dbx.files_upload_session_finish(b'', cursor, commit)


def create_shared_link(dbx, dropbox_path):
"""Create or get existing shared link.

:param dbx: Dropbox object
:param dropbox_path: File path on Dropbox
:return: Shared link URL

"""
try:
links = dbx.sharing_list_shared_links(path=dropbox_path, direct_only=True).links
if links:
# If shared link already exists, return the first one
return links[0].url
else:
# Create a new shared link
link = dbx.sharing_create_shared_link_with_settings(dropbox_path)
return link.url
except ApiError as err:
print(f"Error creating shared link: {err}")
return None


def get_link(data_fname, local_path, ACCESS_TOKEN, DROPBOX_DEST_PATH):
DROPBOX_DEST_PATH = DROPBOX_DEST_PATH + "/" + data_fname

upload_file_to_dropbox(dropbox_path=DROPBOX_DEST_PATH, access_token=ACCESS_TOKEN, local_path=local_path)

# Create Dropbox object to get shared link
dbx = dropbox.Dropbox(ACCESS_TOKEN)
# Get shared link
shared_link = create_shared_link(dbx, DROPBOX_DEST_PATH)
if shared_link:
# Dropbox shared link defaults to `dl=0` at the end, which means preview in browser.
# change it to `dl=1`.
download_link = shared_link.replace('&dl=0', '&dl=1')
print(f"Download link: {download_link}")
return download_link
else:
print("Unable to get shared link.")


def get_ans(data: sc.AnnData, tissue: str, dataset_id: str, local_path, ACCESS_TOKEN, DROPBOX_DEST_PATH):
# keys=["species","tissue","dataset","split","celltype_fname","celltype_url","data_fname","data_url"]
ans = {}
ans["species"] = "human"
ans["tissue"] = tissue.capitalize()
ans["dataset"] = data.n_obs
ans["split"] = "train"
ans["celltype_fname"] = ""
ans["celltype_url"] = ""
ans["data_fname"] = f"train_human_{tissue.capitalize()}{dataset_id}_data.h5ad"
ans["data_url"] = get_link(data_fname=ans["data_fname"].split("_", 1)[1], local_path=local_path,
ACCESS_TOKEN=ACCESS_TOKEN, DROPBOX_DEST_PATH=DROPBOX_DEST_PATH)
ans["is_ALL_Integer"] = np.all(np.equal(data.X.data, data.X.data.astype(int)))
return ans
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