adding download function

docs/tutorials/nbs/demo_data_scimap.ipynb

@@ -13,57 +13,85 @@
    "id": "19f306b3-25e3-4130-995e-382d59b74d2b",
    "metadata": {},
    "source": [
-    "A short guide to downloading our exemplar data for trying out the **scimap toolbox**.\n",
-    "\n",
-    "Navigate to the Harvard Dataverse website and download the exemplar data (see screenshot below!)\n",
+    "A short guide to downloading our demo data for trying out the **scimap toolbox**."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "dfa7001e-ac43-4e2e-ab77-6c899dcee781",
+   "metadata": {},
+   "source": [
+    "**You can download the data in two methods:**\n",
     "\n",
-    "Data: https://doi.org/10.7910/DVN/C45JWT"
+    "1. Utilize the built-in download function of scimap.\n",
+    "2. Visit the website through your browser and manually download the data."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "cc076a7d-528f-4115-a907-e21fb9fb8d54",
+   "metadata": {},
+   "source": [
+    "### 1. Built in function"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "d99d5348-fe28-4676-acd1-7c651f8c5fc1",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import scimap as sm"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "92580b41-d8b0-4472-b666-1863848d9e11",
+   "id": "eb92e132-674c-47f0-b4a0-65a75eb8058b",
    "metadata": {},
    "outputs": [],
-   "source": []
+   "source": [
+    "# Provide a download directory\n",
+    "download_directory = ''\n",
+    "sm.hl.downloadDemoData (download_directory)"
+   ]
   },
   {
    "cell_type": "markdown",
-   "id": "13c8e569-21f0-4bfe-86db-33c4eb47651d",
+   "id": "7b01408a-6505-468e-b384-be5316afd352",
    "metadata": {},
    "source": [
-    "- Click on the \"Access Dataset\" → \"Original Format ZIP\" button.\n",
-    "- Wait for the download to complete. The size of the file is approximately 40 MB.\n",
-    "- Unzip the downloaded file to access the data.\n",
-    "  \n",
-    "To ensure that you can follow the tutorial correctly, please make sure that the following folder structure (screenshot below) is maintained:\n",
-    "\n"
+    "A zipped data folder will appear in the specified directory. Simply unzip it, and you'll be all set to start."
    ]
   },
   {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "fd533e27-b744-4ecb-9834-84527f5432a9",
+   "cell_type": "markdown",
+   "id": "83a9cf87-7904-46b1-9d52-45f4780cb30f",
    "metadata": {},
-   "outputs": [],
-   "source": []
+   "source": [
+    "### 2. Download from Zonodo"
+   ]
   },
   {
    "cell_type": "markdown",
-   "id": "15b3e78f-7464-4bd8-9a95-e953a80f1b48",
+   "id": "17a4ece7-4a97-40a4-be25-4d247ebb1f8a",
    "metadata": {},
    "source": [
-    "If you have any questions or encounter any issues while following the tutorial, please don't hesitate to contact us for assistance."
+    "- Go to [Zonodo](https://zenodo.org/records/10845625)\n",
+    "- Click on the download button\n",
+    "- unzip the downloaded file\n",
+    "\n",
+    "DOI: [10.5281/zenodo.10845624](https://zenodo.org/records/10845625)"
    ]
   },
   {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "d74d7aeb-0bda-4448-9eb9-3d040cfb8ec6",
+   "cell_type": "markdown",
+   "id": "15b3e78f-7464-4bd8-9a95-e953a80f1b48",
    "metadata": {},
-   "outputs": [],
-   "source": []
+   "source": [
+    "If you have any questions or encounter any issues while following the tutorial, please don't hesitate to contact us for assistance."
+   ]
   }
  ],
  "metadata": {

pyproject.toml

@@ -1,7 +1,7 @@
 [tool.poetry]
 
 name = "SCIMAP"
-version = "1.3.14"
+version = "1.3.15"
 description = "Spatial Single-Cell Analysis Toolkit"
 
 license = "MIT"

scimap/helpers/__init__.py

@@ -1 +1 @@
-from .rename import renamefrom .classify import classifyfrom .scimap_to_csv import scimap_to_csvfrom .addROI_omero import addROI_omerofrom .animate import animatefrom .dropFeatures import dropFeaturesfrom .merge_adata_obs import merge_adata_obs
+from .rename import renamefrom .classify import classifyfrom .scimap_to_csv import scimap_to_csvfrom .addROI_omero import addROI_omerofrom .animate import animatefrom .dropFeatures import dropFeaturesfrom .merge_adata_obs import merge_adata_obsfrom .downloadDemoData import downloadDemoData

scimap/helpers/downloadDemoData.py

@@ -0,0 +1,41 @@
+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+"""
+Created on Wed Mar 20 15:04:25 2024
+@author: aj
+"""
+
+import requests
+import os
+
+def downloadDemoData(directory):
+
+    # Ensure the target directory exists
+    if not os.path.exists(directory):
+        os.makedirs(directory)
+        print(f"Created directory: {directory}")
+
+    # Get record details from Zenodo API
+    api_url = f"https://zenodo.org/api/records/10845625"
+    response = requests.get(api_url)
+    if response.status_code != 200:
+        print(f"Failed to retrieve record details. HTTP status code: {response.status_code}")
+        return
+
+    # Extract file links from the record information
+    record_data = response.json()
+    files = record_data.get('files', [])
+
+    # Download each file
+    for file_info in files:
+        file_url = file_info['links']['self']
+        filename = file_info['key']
+        save_path = os.path.join(directory, filename)
+
+        # Download the file
+        print(f"Downloading {filename}...")
+        with requests.get(file_url, stream=True) as file_response:
+            with open(save_path, 'wb') as file:
+                for chunk in file_response.iter_content(chunk_size=8192):
+                    file.write(chunk)
+        print(f"Downloaded {filename} to {save_path}")