forked from enviPath/enviPy
Compare commits
4 Commits
feature/en
...
pre_frontp
| Author | SHA1 | Date | |
|---|---|---|---|
| 34589efbde | |||
| 1cccefa991 | |||
| e26d5a21e3 | |||
| 98d62e1d1f |
@ -16,3 +16,5 @@ POSTGRES_PORT=
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# MAIL
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EMAIL_HOST_USER=
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EMAIL_HOST_PASSWORD=
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# MATOMO
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MATOMO_SITE_ID
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116
.gitea/workflows/ci.yaml
Normal file
116
.gitea/workflows/ci.yaml
Normal file
@ -0,0 +1,116 @@
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name: CI
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on:
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pull_request:
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branches:
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- develop
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workflow_dispatch:
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jobs:
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test:
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runs-on: ubuntu-latest
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services:
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postgres:
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image: postgres:16
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env:
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POSTGRES_USER: ${{ vars.POSTGRES_USER }}
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POSTGRES_PASSWORD: ${{ secrets.POSTGRES_PASSWORD }}
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POSTGRES_DB: ${{ vars.POSTGRES_DB }}
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ports:
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- ${{ vars.POSTGRES_PORT}}:5432
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options: >-
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--health-cmd="pg_isready -U postgres"
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--health-interval=10s
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--health-timeout=5s
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--health-retries=5
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#redis:
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# image: redis:7
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# ports:
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# - 6379:6379
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# options: >-
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# --health-cmd "redis-cli ping"
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# --health-interval=10s
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# --health-timeout=5s
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# --health-retries=5
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env:
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RUNNER_TOOL_CACHE: /toolcache
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EP_DATA_DIR: /opt/enviPy/
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ALLOWED_HOSTS: 127.0.0.1,localhost
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DEBUG: True
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LOG_LEVEL: DEBUG
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MODEL_BUILDING_ENABLED: True
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APPLICABILITY_DOMAIN_ENABLED: True
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ENVIFORMER_PRESENT: True
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ENVIFORMER_DEVICE: cpu
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FLAG_CELERY_PRESENT: False
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PLUGINS_ENABLED: True
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SERVER_URL: http://localhost:8000
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ADMIN_APPROVAL_REQUIRED: True
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REGISTRATION_MANDATORY: True
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LOG_DIR: ''
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# DB
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POSTGRES_SERVICE_NAME: postgres
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POSTGRES_DB: ${{ vars.POSTGRES_DB }}
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POSTGRES_USER: ${{ vars.POSTGRES_USER }}
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POSTGRES_PASSWORD: ${{ secrets.POSTGRES_PASSWORD }}
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POSTGRES_PORT: 5432
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# SENTRY
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SENTRY_ENABLED: False
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# MS ENTRA
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MS_ENTRA_ENABLED: False
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steps:
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- name: Checkout repository
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uses: actions/checkout@v4
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- name: Install system tools via apt
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run: |
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sudo apt-get update
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sudo apt-get install -y postgresql-client redis-tools openjdk-11-jre-headless
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- name: Setup ssh
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run: |
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echo "${{ secrets.ENVIPY_CI_PRIVATE_KEY }}" > ~/.ssh/id_ed25519
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chmod 600 ~/.ssh/id_ed25519
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ssh-keyscan git.envipath.com >> ~/.ssh/known_hosts
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eval $(ssh-agent -s)
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ssh-add ~/.ssh/id_ed25519
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- name: Install pnpm
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uses: pnpm/action-setup@v4
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with:
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version: 10
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- name: Use Node.js
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uses: actions/setup-node@v4
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with:
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node-version: 20
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cache: "pnpm"
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- name: Install uv
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uses: astral-sh/setup-uv@v6
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with:
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enable-cache: true
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- name: Setup venv
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run: |
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uv sync --locked --all-extras --dev
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- name: Wait for services
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run: |
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until pg_isready -h postgres -U postgres; do sleep 2; done
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# until redis-cli -h redis ping; do sleep 2; done
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- name: Run Django migrations
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run: |
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source .venv/bin/activate
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python manage.py migrate --noinput
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- name: Run Django tests
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run: |
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source .venv/bin/activate
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python manage.py test tests --exclude-tag slow
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@ -92,6 +92,8 @@ TEMPLATES = [
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},
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]
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ALLOWED_HTML_TAGS = {'b', 'i', 'u', 'br', 'em', 'mark', 'p', 's', 'strong'}
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WSGI_APPLICATION = "envipath.wsgi.application"
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# Database
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@ -357,3 +359,6 @@ if MS_ENTRA_ENABLED:
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MS_ENTRA_AUTHORITY = f"https://login.microsoftonline.com/{MS_ENTRA_TENANT_ID}"
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MS_ENTRA_REDIRECT_URI = os.environ["MS_REDIRECT_URI"]
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MS_ENTRA_SCOPES = os.environ.get("MS_SCOPES", "").split(",")
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# Site ID 10 -> beta.envipath.org
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MATOMO_SITE_ID = os.environ.get("MATOMO_SITE_ID", "10")
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@ -4,6 +4,7 @@ import json
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from typing import Union, List, Optional, Set, Dict, Any
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from uuid import UUID
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import nh3
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from django.contrib.auth import get_user_model
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from django.db import transaction
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from django.conf import settings as s
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@ -185,6 +186,12 @@ class UserManager(object):
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def create_user(
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username, email, password, set_setting=True, add_to_group=True, *args, **kwargs
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):
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# Clean for potential XSS
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clean_username = nh3.clean(username).strip()
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clean_email = nh3.clean(email).strip()
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if clean_username != username or clean_email != email:
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# This will be caught by the try in view.py/register
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raise ValueError("Invalid username or password")
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# avoid circular import :S
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from .tasks import send_registration_mail
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@ -262,8 +269,9 @@ class GroupManager(object):
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@staticmethod
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def create_group(current_user, name, description):
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g = Group()
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g.name = name
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g.description = description
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# Clean for potential XSS
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g.name = nh3.clean(name, tags=s.ALLOWED_HTML_TAGS).strip()
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g.description = nh3.clean(description, tags=s.ALLOWED_HTML_TAGS).strip()
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g.owner = current_user
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g.save()
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@ -518,8 +526,13 @@ class PackageManager(object):
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@transaction.atomic
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def create_package(current_user, name: str, description: str = None):
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p = Package()
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p.name = name
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p.description = description
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# Clean for potential XSS
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p.name = nh3.clean(name, tags=s.ALLOWED_HTML_TAGS).strip()
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if description is not None and description.strip() != "":
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p.description = nh3.clean(description.strip(), tags=s.ALLOWED_HTML_TAGS).strip()
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p.save()
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up = UserPackagePermission()
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@ -1094,28 +1107,29 @@ class SettingManager(object):
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model: EPModel = None,
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model_threshold: float = None,
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):
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s = Setting()
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s.name = name
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s.description = description
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s.max_nodes = max_nodes
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s.max_depth = max_depth
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s.model = model
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s.model_threshold = model_threshold
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new_s = Setting()
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# Clean for potential XSS
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new_s.name = nh3.clean(name, tags=s.ALLOWED_HTML_TAGS).strip()
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new_s.description = nh3.clean(description, tags=s.ALLOWED_HTML_TAGS).strip()
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new_s.max_nodes = max_nodes
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new_s.max_depth = max_depth
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new_s.model = model
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new_s.model_threshold = model_threshold
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s.save()
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new_s.save()
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if rule_packages is not None:
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for r in rule_packages:
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s.rule_packages.add(r)
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s.save()
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new_s.rule_packages.add(r)
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new_s.save()
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usp = UserSettingPermission()
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usp.user = user
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usp.setting = s
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usp.setting = new_s
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usp.permission = Permission.ALL[0]
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usp.save()
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return s
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return new_s
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@staticmethod
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def get_default_setting(user: User):
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@ -1544,7 +1558,7 @@ class SPathway(object):
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if self.prediction_setting.model.app_domain:
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app_domain_assessment = self.prediction_setting.model.app_domain.assess(
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sub.smiles
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)[0]
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)
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if self.persist is not None:
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n = self.snode_persist_lookup[sub]
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@ -1577,9 +1591,7 @@ class SPathway(object):
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if self.prediction_setting.model:
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if self.prediction_setting.model.app_domain:
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app_domain_assessment = (
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self.prediction_setting.model.app_domain.assess(c)[
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0
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]
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self.prediction_setting.model.app_domain.assess(c)
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)
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self.smiles_to_node[c] = SNode(
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442
epdb/models.py
442
epdb/models.py
@ -11,6 +11,7 @@ from typing import Union, List, Optional, Dict, Tuple, Set, Any
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from uuid import uuid4
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import math
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import joblib
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import nh3
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import numpy as np
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from django.conf import settings as s
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from django.contrib.auth.models import AbstractUser
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@ -28,7 +29,14 @@ from sklearn.metrics import precision_score, recall_score, jaccard_score
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from sklearn.model_selection import ShuffleSplit
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from utilities.chem import FormatConverter, ProductSet, PredictionResult, IndigoUtils
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from utilities.ml import Dataset, ApplicabilityDomainPCA, EnsembleClassifierChain, RelativeReasoning
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from utilities.ml import (
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RuleBasedDataset,
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ApplicabilityDomainPCA,
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EnsembleClassifierChain,
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RelativeReasoning,
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EnviFormerDataset,
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Dataset,
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)
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logger = logging.getLogger(__name__)
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@ -802,14 +810,16 @@ class Compound(EnviPathModel, AliasMixin, ScenarioMixin, ChemicalIdentifierMixin
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c = Compound()
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c.package = package
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if name is None or name.strip() == "":
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if name is not None:
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# Clean for potential XSS
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name = nh3.clean(name, tags=s.ALLOWED_HTML_TAGS).strip()
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if name is None or name == "":
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name = f"Compound {Compound.objects.filter(package=package).count() + 1}"
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c.name = name
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# We have a default here only set the value if it carries some payload
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if description is not None and description.strip() != "":
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c.description = description.strip()
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c.description = nh3.clean(description, tags=s.ALLOWED_HTML_TAGS).strip()
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c.save()
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@ -981,11 +991,11 @@ class CompoundStructure(EnviPathModel, AliasMixin, ScenarioMixin, ChemicalIdenti
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raise ValueError("Unpersisted Compound! Persist compound first!")
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cs = CompoundStructure()
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# Clean for potential XSS
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if name is not None:
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cs.name = name
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cs.name = nh3.clean(name, tags=s.ALLOWED_HTML_TAGS).strip()
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if description is not None:
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cs.description = description
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cs.description = nh3.clean(description, tags=s.ALLOWED_HTML_TAGS).strip()
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||||
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cs.smiles = smiles
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cs.compound = compound
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@ -1187,21 +1197,29 @@ class SimpleAmbitRule(SimpleRule):
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r = SimpleAmbitRule()
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r.package = package
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if name is None or name.strip() == "":
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if name is not None:
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name = nh3.clean(name, tags=s.ALLOWED_HTML_TAGS).strip()
|
||||
|
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if name is None or name == "":
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name = f"Rule {Rule.objects.filter(package=package).count() + 1}"
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|
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r.name = name
|
||||
|
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if description is not None and description.strip() != "":
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r.description = description
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r.description = nh3.clean(description, tags=s.ALLOWED_HTML_TAGS).strip()
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r.smirks = smirks
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|
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if reactant_filter_smarts is not None and reactant_filter_smarts.strip() != "":
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r.reactant_filter_smarts = reactant_filter_smarts
|
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if not FormatConverter.is_valid_smarts(reactant_filter_smarts.strip()):
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raise ValueError(f'Reactant Filter SMARTS "{reactant_filter_smarts}" is invalid!')
|
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else:
|
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r.reactant_filter_smarts = reactant_filter_smarts.strip()
|
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|
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if product_filter_smarts is not None and product_filter_smarts.strip() != "":
|
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r.product_filter_smarts = product_filter_smarts
|
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if not FormatConverter.is_valid_smarts(product_filter_smarts.strip()):
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raise ValueError(f'Product Filter SMARTS "{product_filter_smarts}" is invalid!')
|
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else:
|
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r.product_filter_smarts = product_filter_smarts.strip()
|
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|
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r.save()
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return r
|
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@ -1402,12 +1420,11 @@ class Reaction(EnviPathModel, AliasMixin, ScenarioMixin, ReactionIdentifierMixin
|
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|
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r = Reaction()
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r.package = package
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# Clean for potential XSS
|
||||
if name is not None and name.strip() != "":
|
||||
r.name = name
|
||||
|
||||
r.name = nh3.clean(name, tags=s.ALLOWED_HTML_TAGS).strip()
|
||||
if description is not None and name.strip() != "":
|
||||
r.description = description
|
||||
r.description = nh3.clean(description, tags=s.ALLOWED_HTML_TAGS).strip()
|
||||
|
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r.multi_step = multi_step
|
||||
|
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@ -1573,12 +1590,14 @@ class Pathway(EnviPathModel, AliasMixin, ScenarioMixin):
|
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while len(queue):
|
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current = queue.pop()
|
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processed.add(current)
|
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|
||||
nodes.append(current.d3_json())
|
||||
|
||||
for e in self.edges.filter(start_nodes=current).distinct():
|
||||
for prod in e.end_nodes.all():
|
||||
if prod not in queue and prod not in processed:
|
||||
queue.append(prod)
|
||||
for e in self.edges:
|
||||
if current in e.start_nodes.all():
|
||||
for prod in e.end_nodes.all():
|
||||
if prod not in queue and prod not in processed:
|
||||
queue.append(prod)
|
||||
|
||||
# We shouldn't lose or make up nodes...
|
||||
assert len(nodes) == len(self.nodes)
|
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@ -1713,14 +1732,15 @@ class Pathway(EnviPathModel, AliasMixin, ScenarioMixin):
|
||||
):
|
||||
pw = Pathway()
|
||||
pw.package = package
|
||||
|
||||
if name is None or name.strip() == "":
|
||||
if name is not None:
|
||||
# Clean for potential XSS
|
||||
name = nh3.clean(name, tags=s.ALLOWED_HTML_TAGS).strip()
|
||||
if name is None or name == "":
|
||||
name = f"Pathway {Pathway.objects.filter(package=package).count() + 1}"
|
||||
|
||||
pw.name = name
|
||||
|
||||
if description is not None and description.strip() != "":
|
||||
pw.description = description
|
||||
pw.description = nh3.clean(description, tags=s.ALLOWED_HTML_TAGS).strip()
|
||||
|
||||
pw.save()
|
||||
try:
|
||||
@ -2015,11 +2035,16 @@ class Edge(EnviPathModel, AliasMixin, ScenarioMixin):
|
||||
for node in end_nodes:
|
||||
e.end_nodes.add(node)
|
||||
|
||||
if name is None:
|
||||
# Clean for potential XSS
|
||||
# Cleaning technically not needed as it is also done in Reaction.create, including it here for consistency
|
||||
if name is not None:
|
||||
name = nh3.clean(name, tags=s.ALLOWED_HTML_TAGS).strip()
|
||||
if name is None or name == "":
|
||||
name = f"Reaction {pathway.package.reactions.count() + 1}"
|
||||
|
||||
if description is None:
|
||||
description = s.DEFAULT_VALUES["description"]
|
||||
description = nh3.clean(description, tags=s.ALLOWED_HTML_TAGS).strip()
|
||||
|
||||
r = Reaction.create(
|
||||
pathway.package,
|
||||
@ -2173,7 +2198,7 @@ class PackageBasedModel(EPModel):
|
||||
|
||||
applicable_rules = self.applicable_rules
|
||||
reactions = list(self._get_reactions())
|
||||
ds = Dataset.generate_dataset(reactions, applicable_rules, educts_only=True)
|
||||
ds = RuleBasedDataset.generate_dataset(reactions, applicable_rules, educts_only=True)
|
||||
|
||||
end = datetime.now()
|
||||
logger.debug(f"build_dataset took {(end - start).total_seconds()} seconds")
|
||||
@ -2182,7 +2207,7 @@ class PackageBasedModel(EPModel):
|
||||
ds.save(f)
|
||||
return ds
|
||||
|
||||
def load_dataset(self) -> "Dataset":
|
||||
def load_dataset(self) -> "Dataset | RuleBasedDataset | EnviFormerDataset":
|
||||
ds_path = os.path.join(s.MODEL_DIR, f"{self.uuid}_ds.pkl")
|
||||
return Dataset.load(ds_path)
|
||||
|
||||
@ -2223,7 +2248,7 @@ class PackageBasedModel(EPModel):
|
||||
self.model_status = self.BUILT_NOT_EVALUATED
|
||||
self.save()
|
||||
|
||||
def evaluate_model(self, multigen: bool, eval_packages: List["Package"] = None):
|
||||
def evaluate_model(self, multigen: bool, eval_packages: List["Package"] = None, **kwargs):
|
||||
if self.model_status != self.BUILT_NOT_EVALUATED:
|
||||
raise ValueError(f"Can't evaluate a model in state {self.model_status}!")
|
||||
|
||||
@ -2341,37 +2366,39 @@ class PackageBasedModel(EPModel):
|
||||
eval_reactions = list(
|
||||
Reaction.objects.filter(package__in=self.eval_packages.all()).distinct()
|
||||
)
|
||||
ds = Dataset.generate_dataset(eval_reactions, self.applicable_rules, educts_only=True)
|
||||
ds = RuleBasedDataset.generate_dataset(
|
||||
eval_reactions, self.applicable_rules, educts_only=True
|
||||
)
|
||||
if isinstance(self, RuleBasedRelativeReasoning):
|
||||
X = np.array(ds.X(exclude_id_col=False, na_replacement=None))
|
||||
y = np.array(ds.y(na_replacement=np.nan))
|
||||
X = ds.X(exclude_id_col=False, na_replacement=None).to_numpy()
|
||||
y = ds.y(na_replacement=np.nan).to_numpy()
|
||||
else:
|
||||
X = np.array(ds.X(na_replacement=np.nan))
|
||||
y = np.array(ds.y(na_replacement=np.nan))
|
||||
X = ds.X(na_replacement=np.nan).to_numpy()
|
||||
y = ds.y(na_replacement=np.nan).to_numpy()
|
||||
single_gen_result = evaluate_sg(self.model, X, y, np.arange(len(X)), self.threshold)
|
||||
self.eval_results = self.compute_averages([single_gen_result])
|
||||
else:
|
||||
ds = self.load_dataset()
|
||||
|
||||
if isinstance(self, RuleBasedRelativeReasoning):
|
||||
X = np.array(ds.X(exclude_id_col=False, na_replacement=None))
|
||||
y = np.array(ds.y(na_replacement=np.nan))
|
||||
X = ds.X(exclude_id_col=False, na_replacement=None).to_numpy()
|
||||
y = ds.y(na_replacement=np.nan).to_numpy()
|
||||
else:
|
||||
X = np.array(ds.X(na_replacement=np.nan))
|
||||
y = np.array(ds.y(na_replacement=np.nan))
|
||||
X = ds.X(na_replacement=np.nan).to_numpy()
|
||||
y = ds.y(na_replacement=np.nan).to_numpy()
|
||||
|
||||
n_splits = 20
|
||||
n_splits = kwargs.get("n_splits", 20)
|
||||
|
||||
shuff = ShuffleSplit(n_splits=n_splits, test_size=0.25, random_state=42)
|
||||
splits = list(shuff.split(X))
|
||||
|
||||
from joblib import Parallel, delayed
|
||||
|
||||
models = Parallel(n_jobs=10)(
|
||||
models = Parallel(n_jobs=min(10, len(splits)))(
|
||||
delayed(train_func)(X, y, train_index, self._model_args())
|
||||
for train_index, _ in splits
|
||||
)
|
||||
evaluations = Parallel(n_jobs=10)(
|
||||
evaluations = Parallel(n_jobs=min(10, len(splits)))(
|
||||
delayed(evaluate_sg)(model, X, y, test_index, self.threshold)
|
||||
for model, (_, test_index) in zip(models, splits)
|
||||
)
|
||||
@ -2539,14 +2566,15 @@ class RuleBasedRelativeReasoning(PackageBasedModel):
|
||||
):
|
||||
rbrr = RuleBasedRelativeReasoning()
|
||||
rbrr.package = package
|
||||
|
||||
if name is None or name.strip() == "":
|
||||
if name is not None:
|
||||
# Clean for potential XSS
|
||||
name = nh3.clean(name, tags=s.ALLOWED_HTML_TAGS).strip()
|
||||
if name is None or name == "":
|
||||
name = f"RuleBasedRelativeReasoning {RuleBasedRelativeReasoning.objects.filter(package=package).count() + 1}"
|
||||
|
||||
rbrr.name = name
|
||||
|
||||
if description is not None and description.strip() != "":
|
||||
rbrr.description = description
|
||||
rbrr.description = nh3.clean(description, tags=s.ALLOWED_HTML_TAGS).strip()
|
||||
|
||||
if threshold is None or (threshold <= 0 or 1 <= threshold):
|
||||
raise ValueError("Threshold must be a float between 0 and 1.")
|
||||
@ -2583,11 +2611,11 @@ class RuleBasedRelativeReasoning(PackageBasedModel):
|
||||
|
||||
return rbrr
|
||||
|
||||
def _fit_model(self, ds: Dataset):
|
||||
def _fit_model(self, ds: RuleBasedDataset):
|
||||
X, y = ds.X(exclude_id_col=False, na_replacement=None), ds.y(na_replacement=None)
|
||||
model = RelativeReasoning(
|
||||
start_index=ds.triggered()[0],
|
||||
end_index=ds.triggered()[1],
|
||||
end_index=ds.triggered()[-1],
|
||||
)
|
||||
model.fit(X, y)
|
||||
return model
|
||||
@ -2597,7 +2625,7 @@ class RuleBasedRelativeReasoning(PackageBasedModel):
|
||||
return {
|
||||
"clz": "RuleBaseRelativeReasoning",
|
||||
"start_index": ds.triggered()[0],
|
||||
"end_index": ds.triggered()[1],
|
||||
"end_index": ds.triggered()[-1],
|
||||
}
|
||||
|
||||
def _save_model(self, model):
|
||||
@ -2643,14 +2671,15 @@ class MLRelativeReasoning(PackageBasedModel):
|
||||
):
|
||||
mlrr = MLRelativeReasoning()
|
||||
mlrr.package = package
|
||||
|
||||
if name is None or name.strip() == "":
|
||||
if name is not None:
|
||||
# Clean for potential XSS
|
||||
name = nh3.clean(name, tags=s.ALLOWED_HTML_TAGS).strip()
|
||||
if name is None or name == "":
|
||||
name = f"MLRelativeReasoning {MLRelativeReasoning.objects.filter(package=package).count() + 1}"
|
||||
|
||||
mlrr.name = name
|
||||
|
||||
if description is not None and description.strip() != "":
|
||||
mlrr.description = description
|
||||
mlrr.description = nh3.clean(description, tags=s.ALLOWED_HTML_TAGS).strip()
|
||||
|
||||
if threshold is None or (threshold <= 0 or 1 <= threshold):
|
||||
raise ValueError("Threshold must be a float between 0 and 1.")
|
||||
@ -2685,11 +2714,11 @@ class MLRelativeReasoning(PackageBasedModel):
|
||||
|
||||
return mlrr
|
||||
|
||||
def _fit_model(self, ds: Dataset):
|
||||
def _fit_model(self, ds: RuleBasedDataset):
|
||||
X, y = ds.X(na_replacement=np.nan), ds.y(na_replacement=np.nan)
|
||||
|
||||
model = EnsembleClassifierChain(**s.DEFAULT_MODEL_PARAMS)
|
||||
model.fit(X, y)
|
||||
model.fit(X.to_numpy(), y.to_numpy())
|
||||
return model
|
||||
|
||||
def _model_args(self):
|
||||
@ -2712,7 +2741,7 @@ class MLRelativeReasoning(PackageBasedModel):
|
||||
start = datetime.now()
|
||||
ds = self.load_dataset()
|
||||
classify_ds, classify_prods = ds.classification_dataset([smiles], self.applicable_rules)
|
||||
pred = self.model.predict_proba(classify_ds.X())
|
||||
pred = self.model.predict_proba(classify_ds.X().to_numpy())
|
||||
|
||||
res = MLRelativeReasoning.combine_products_and_probs(
|
||||
self.applicable_rules, pred[0], classify_prods[0]
|
||||
@ -2757,7 +2786,9 @@ class ApplicabilityDomain(EnviPathModel):
|
||||
|
||||
@cached_property
|
||||
def training_set_probs(self):
|
||||
return joblib.load(os.path.join(s.MODEL_DIR, f"{self.model.uuid}_train_probs.pkl"))
|
||||
ds = self.model.load_dataset()
|
||||
col_ids = ds.block_indices("prob")
|
||||
return ds[:, col_ids]
|
||||
|
||||
def build(self):
|
||||
ds = self.model.load_dataset()
|
||||
@ -2765,9 +2796,9 @@ class ApplicabilityDomain(EnviPathModel):
|
||||
start = datetime.now()
|
||||
|
||||
# Get Trainingset probs and dump them as they're required when using the app domain
|
||||
probs = self.model.model.predict_proba(ds.X())
|
||||
f = os.path.join(s.MODEL_DIR, f"{self.model.uuid}_train_probs.pkl")
|
||||
joblib.dump(probs, f)
|
||||
probs = self.model.model.predict_proba(ds.X().to_numpy())
|
||||
ds.add_probs(probs)
|
||||
ds.save(os.path.join(s.MODEL_DIR, f"{self.model.uuid}_ds.pkl"))
|
||||
|
||||
ad = ApplicabilityDomainPCA(num_neighbours=self.num_neighbours)
|
||||
ad.build(ds)
|
||||
@ -2790,15 +2821,20 @@ class ApplicabilityDomain(EnviPathModel):
|
||||
joblib.dump(ad, f)
|
||||
|
||||
def assess(self, structure: Union[str, "CompoundStructure"]):
|
||||
return self.assess_batch([structure])[0]
|
||||
|
||||
def assess_batch(self, structures: List["CompoundStructure | str"]):
|
||||
ds = self.model.load_dataset()
|
||||
|
||||
if isinstance(structure, CompoundStructure):
|
||||
smiles = structure.smiles
|
||||
else:
|
||||
smiles = structure
|
||||
smiles = []
|
||||
for struct in structures:
|
||||
if isinstance(struct, CompoundStructure):
|
||||
smiles.append(structures.smiles)
|
||||
else:
|
||||
smiles.append(structures)
|
||||
|
||||
assessment_ds, assessment_prods = ds.classification_dataset(
|
||||
[structure], self.model.applicable_rules
|
||||
structures, self.model.applicable_rules
|
||||
)
|
||||
|
||||
# qualified_neighbours_per_rule is a nested dictionary structured as:
|
||||
@ -2812,82 +2848,61 @@ class ApplicabilityDomain(EnviPathModel):
|
||||
# it identifies all training structures that have the same trigger reaction activated (i.e., value 1).
|
||||
# This is used to find "qualified neighbours" — training examples that share the same triggered feature
|
||||
# with a given assessment structure under a particular rule.
|
||||
qualified_neighbours_per_rule: Dict[int, Dict[int, List[int]]] = defaultdict(
|
||||
lambda: defaultdict(list)
|
||||
)
|
||||
qualified_neighbours_per_rule: Dict = {}
|
||||
|
||||
for rule_idx, feature_index in enumerate(range(*assessment_ds.triggered())):
|
||||
feature = ds.columns[feature_index]
|
||||
if feature.startswith("trig_"):
|
||||
# TODO unroll loop
|
||||
for i, cx in enumerate(assessment_ds.X(exclude_id_col=False)):
|
||||
if int(cx[feature_index]) == 1:
|
||||
for j, tx in enumerate(ds.X(exclude_id_col=False)):
|
||||
if int(tx[feature_index]) == 1:
|
||||
qualified_neighbours_per_rule[i][rule_idx].append(j)
|
||||
import polars as pl
|
||||
|
||||
probs = self.training_set_probs
|
||||
# preds = self.model.model.predict_proba(assessment_ds.X())
|
||||
# Select only the triggered columns
|
||||
for i, row in enumerate(assessment_ds[:, assessment_ds.triggered()].iter_rows(named=True)):
|
||||
# Find the rules the structure triggers. For each rule, filter the training dataset to rows that also
|
||||
# trigger that rule.
|
||||
train_trig = {
|
||||
trig_uuid.split("_")[-1]: ds.filter(pl.col(trig_uuid).eq(1))
|
||||
for trig_uuid, value in row.items()
|
||||
if value == 1
|
||||
}
|
||||
qualified_neighbours_per_rule[i] = train_trig
|
||||
rule_to_i = {str(r.uuid): i for i, r in enumerate(self.model.applicable_rules)}
|
||||
preds = self.model.combine_products_and_probs(
|
||||
self.model.applicable_rules,
|
||||
self.model.model.predict_proba(assessment_ds.X())[0],
|
||||
self.model.model.predict_proba(assessment_ds.X().to_numpy())[0],
|
||||
assessment_prods[0],
|
||||
)
|
||||
|
||||
assessments = list()
|
||||
|
||||
# loop through our assessment dataset
|
||||
for i, instance in enumerate(assessment_ds):
|
||||
for i, instance in enumerate(assessment_ds[:, assessment_ds.struct_features()]):
|
||||
rule_reliabilities = dict()
|
||||
local_compatibilities = dict()
|
||||
neighbours_per_rule = dict()
|
||||
neighbor_probs_per_rule = dict()
|
||||
|
||||
# loop through rule indices together with the collected neighbours indices from train dataset
|
||||
for rule_idx, vals in qualified_neighbours_per_rule[i].items():
|
||||
# collect the train dataset instances and store it along with the index (a.k.a. row number) of the
|
||||
# train dataset
|
||||
train_instances = []
|
||||
for v in vals:
|
||||
train_instances.append((v, ds.at(v)))
|
||||
|
||||
# sf is a tuple with start/end index of the features
|
||||
sf = ds.struct_features()
|
||||
|
||||
# compute tanimoto distance for all neighbours
|
||||
# result ist a list of tuples with train index and computed distance
|
||||
for rule_uuid, train_instances in qualified_neighbours_per_rule[i].items():
|
||||
# compute tanimoto distance for all neighbours and add to dataset
|
||||
dists = self._compute_distances(
|
||||
instance.X()[0][sf[0] : sf[1]],
|
||||
[ti[1].X()[0][sf[0] : sf[1]] for ti in train_instances],
|
||||
assessment_ds[i, assessment_ds.struct_features()].to_numpy()[0],
|
||||
train_instances[:, train_instances.struct_features()].to_numpy(),
|
||||
)
|
||||
|
||||
dists_with_index = list()
|
||||
for ti, dist in zip(train_instances, dists):
|
||||
dists_with_index.append((ti[0], dist[1]))
|
||||
train_instances = train_instances.with_columns(dist=pl.Series(dists))
|
||||
|
||||
# sort them in a descending way and take at most `self.num_neighbours`
|
||||
dists_with_index = sorted(dists_with_index, key=lambda x: x[1], reverse=True)
|
||||
dists_with_index = dists_with_index[: self.num_neighbours]
|
||||
|
||||
# TODO: Should this be descending? If we want the most similar then we want values close to zero (ascending)
|
||||
train_instances = train_instances.sort("dist", descending=True)[
|
||||
: self.num_neighbours
|
||||
]
|
||||
# compute average distance
|
||||
rule_reliabilities[rule_idx] = (
|
||||
sum([d[1] for d in dists_with_index]) / len(dists_with_index)
|
||||
if len(dists_with_index) > 0
|
||||
else 0.0
|
||||
rule_reliabilities[rule_uuid] = (
|
||||
train_instances.select(pl.mean("dist")).fill_nan(0.0).item()
|
||||
)
|
||||
|
||||
# for local_compatibility we'll need the datasets for the indices having the highest similarity
|
||||
neighbour_datasets = [(d[0], ds.at(d[0])) for d in dists_with_index]
|
||||
local_compatibilities[rule_idx] = self._compute_compatibility(
|
||||
rule_idx, probs, neighbour_datasets
|
||||
local_compatibilities[rule_uuid] = self._compute_compatibility(
|
||||
rule_uuid, train_instances
|
||||
)
|
||||
neighbours_per_rule[rule_idx] = [
|
||||
CompoundStructure.objects.get(uuid=ds[1].structure_id())
|
||||
for ds in neighbour_datasets
|
||||
]
|
||||
neighbor_probs_per_rule[rule_idx] = [
|
||||
probs[d[0]][rule_idx] for d in dists_with_index
|
||||
]
|
||||
neighbours_per_rule[rule_uuid] = list(
|
||||
CompoundStructure.objects.filter(uuid__in=train_instances["structure_id"])
|
||||
)
|
||||
neighbor_probs_per_rule[rule_uuid] = train_instances[f"prob_{rule_uuid}"].to_list()
|
||||
|
||||
ad_res = {
|
||||
"ad_params": {
|
||||
@ -2898,23 +2913,21 @@ class ApplicabilityDomain(EnviPathModel):
|
||||
"local_compatibility_threshold": self.local_compatibilty_threshold,
|
||||
},
|
||||
"assessment": {
|
||||
"smiles": smiles,
|
||||
"inside_app_domain": self.pca.is_applicable(instance)[0],
|
||||
"smiles": smiles[i],
|
||||
"inside_app_domain": self.pca.is_applicable(assessment_ds[i])[0],
|
||||
},
|
||||
}
|
||||
|
||||
transformations = list()
|
||||
for rule_idx in rule_reliabilities.keys():
|
||||
rule = Rule.objects.get(
|
||||
uuid=instance.columns[instance.observed()[0] + rule_idx].replace("obs_", "")
|
||||
)
|
||||
for rule_uuid in rule_reliabilities.keys():
|
||||
rule = Rule.objects.get(uuid=rule_uuid)
|
||||
|
||||
rule_data = rule.simple_json()
|
||||
rule_data["image"] = f"{rule.url}?image=svg"
|
||||
|
||||
neighbors = []
|
||||
for n, n_prob in zip(
|
||||
neighbours_per_rule[rule_idx], neighbor_probs_per_rule[rule_idx]
|
||||
neighbours_per_rule[rule_uuid], neighbor_probs_per_rule[rule_uuid]
|
||||
):
|
||||
neighbor = n.simple_json()
|
||||
neighbor["image"] = f"{n.url}?image=svg"
|
||||
@ -2931,14 +2944,14 @@ class ApplicabilityDomain(EnviPathModel):
|
||||
|
||||
transformation = {
|
||||
"rule": rule_data,
|
||||
"reliability": rule_reliabilities[rule_idx],
|
||||
"reliability": rule_reliabilities[rule_uuid],
|
||||
# We're setting it here to False, as we don't know whether "assess" is called during pathway
|
||||
# prediction or from Model Page. For persisted Nodes this field will be overwritten at runtime
|
||||
"is_predicted": False,
|
||||
"local_compatibility": local_compatibilities[rule_idx],
|
||||
"probability": preds[rule_idx].probability,
|
||||
"local_compatibility": local_compatibilities[rule_uuid],
|
||||
"probability": preds[rule_to_i[rule_uuid]].probability,
|
||||
"transformation_products": [
|
||||
x.product_set for x in preds[rule_idx].product_sets
|
||||
x.product_set for x in preds[rule_to_i[rule_uuid]].product_sets
|
||||
],
|
||||
"times_triggered": ds.times_triggered(str(rule.uuid)),
|
||||
"neighbors": neighbors,
|
||||
@ -2956,32 +2969,24 @@ class ApplicabilityDomain(EnviPathModel):
|
||||
def _compute_distances(classify_instance: List[int], train_instances: List[List[int]]):
|
||||
from utilities.ml import tanimoto_distance
|
||||
|
||||
distances = [
|
||||
(i, tanimoto_distance(classify_instance, train))
|
||||
for i, train in enumerate(train_instances)
|
||||
]
|
||||
distances = [tanimoto_distance(classify_instance, train) for train in train_instances]
|
||||
return distances
|
||||
|
||||
@staticmethod
|
||||
def _compute_compatibility(rule_idx: int, preds, neighbours: List[Tuple[int, "Dataset"]]):
|
||||
tp, tn, fp, fn = 0.0, 0.0, 0.0, 0.0
|
||||
def _compute_compatibility(self, rule_idx: int, neighbours: "RuleBasedDataset"):
|
||||
accuracy = 0.0
|
||||
import polars as pl
|
||||
|
||||
for n in neighbours:
|
||||
obs = n[1].y()[0][rule_idx]
|
||||
pred = preds[n[0]][rule_idx]
|
||||
if obs and pred:
|
||||
tp += 1
|
||||
elif not obs and pred:
|
||||
fp += 1
|
||||
elif obs and not pred:
|
||||
fn += 1
|
||||
else:
|
||||
tn += 1
|
||||
# Jaccard Index
|
||||
if tp + tn > 0.0:
|
||||
accuracy = (tp + tn) / (tp + tn + fp + fn)
|
||||
|
||||
obs_pred = neighbours.select(
|
||||
obs=pl.col(f"obs_{rule_idx}").cast(pl.Boolean),
|
||||
pred=pl.col(f"prob_{rule_idx}") >= self.model.threshold,
|
||||
)
|
||||
# Compute tp, tn, fp, fn using polars expressions
|
||||
tp = obs_pred.filter((pl.col("obs")) & (pl.col("pred"))).height
|
||||
tn = obs_pred.filter((~pl.col("obs")) & (~pl.col("pred"))).height
|
||||
fp = obs_pred.filter((~pl.col("obs")) & (pl.col("pred"))).height
|
||||
fn = obs_pred.filter((pl.col("obs")) & (~pl.col("pred"))).height
|
||||
if tp + tn > 0.0:
|
||||
accuracy = (tp + tn) / (tp + tn + fp + fn)
|
||||
return accuracy
|
||||
|
||||
|
||||
@ -3001,14 +3006,15 @@ class EnviFormer(PackageBasedModel):
|
||||
):
|
||||
mod = EnviFormer()
|
||||
mod.package = package
|
||||
|
||||
if name is None or name.strip() == "":
|
||||
if name is not None:
|
||||
# Clean for potential XSS
|
||||
name = nh3.clean(name, tags=s.ALLOWED_HTML_TAGS).strip()
|
||||
if name is None or name == "":
|
||||
name = f"EnviFormer {EnviFormer.objects.filter(package=package).count() + 1}"
|
||||
|
||||
mod.name = name
|
||||
|
||||
if description is not None and description.strip() != "":
|
||||
mod.description = description
|
||||
mod.description = nh3.clean(description, tags=s.ALLOWED_HTML_TAGS).strip()
|
||||
|
||||
if threshold is None or (threshold <= 0 or 1 <= threshold):
|
||||
raise ValueError("Threshold must be a float between 0 and 1.")
|
||||
@ -3082,44 +3088,24 @@ class EnviFormer(PackageBasedModel):
|
||||
self.save()
|
||||
|
||||
start = datetime.now()
|
||||
# Standardise reactions for the training data, EnviFormer ignores stereochemistry currently
|
||||
co2 = {"C(=O)=O", "O=C=O"}
|
||||
ds = []
|
||||
for reaction in self._get_reactions():
|
||||
educts = ".".join(
|
||||
[
|
||||
FormatConverter.standardize(smile.smiles, remove_stereo=True)
|
||||
for smile in reaction.educts.all()
|
||||
]
|
||||
)
|
||||
products = ".".join(
|
||||
[
|
||||
FormatConverter.standardize(smile.smiles, remove_stereo=True)
|
||||
for smile in reaction.products.all()
|
||||
]
|
||||
)
|
||||
if products not in co2:
|
||||
ds.append(f"{educts}>>{products}")
|
||||
ds = EnviFormerDataset.generate_dataset(self._get_reactions())
|
||||
|
||||
end = datetime.now()
|
||||
logger.debug(f"build_dataset took {(end - start).total_seconds()} seconds")
|
||||
f = os.path.join(s.MODEL_DIR, f"{self.uuid}_ds.json")
|
||||
with open(f, "w") as d_file:
|
||||
json.dump(ds, d_file)
|
||||
ds.save(f)
|
||||
return ds
|
||||
|
||||
def load_dataset(self) -> "Dataset":
|
||||
def load_dataset(self):
|
||||
ds_path = os.path.join(s.MODEL_DIR, f"{self.uuid}_ds.json")
|
||||
with open(ds_path) as d_file:
|
||||
ds = json.load(d_file)
|
||||
return ds
|
||||
return EnviFormerDataset.load(ds_path)
|
||||
|
||||
def _fit_model(self, ds):
|
||||
# Call to enviFormer's fine_tune function and return the model
|
||||
from enviformer.finetune import fine_tune
|
||||
|
||||
start = datetime.now()
|
||||
model = fine_tune(ds, s.MODEL_DIR, str(self.uuid), device=s.ENVIFORMER_DEVICE)
|
||||
model = fine_tune(ds.X(), ds.y(), s.MODEL_DIR, str(self.uuid), device=s.ENVIFORMER_DEVICE)
|
||||
end = datetime.now()
|
||||
logger.debug(f"EnviFormer finetuning took {(end - start).total_seconds():.2f} seconds")
|
||||
return model
|
||||
@ -3135,7 +3121,7 @@ class EnviFormer(PackageBasedModel):
|
||||
args = {"clz": "EnviFormer"}
|
||||
return args
|
||||
|
||||
def evaluate_model(self, multigen: bool, eval_packages: List["Package"] = None):
|
||||
def evaluate_model(self, multigen: bool, eval_packages: List["Package"] = None, **kwargs):
|
||||
if self.model_status != self.BUILT_NOT_EVALUATED:
|
||||
raise ValueError(f"Can't evaluate a model in state {self.model_status}!")
|
||||
|
||||
@ -3150,21 +3136,20 @@ class EnviFormer(PackageBasedModel):
|
||||
self.model_status = self.EVALUATING
|
||||
self.save()
|
||||
|
||||
def evaluate_sg(test_reactions, predictions, model_thresh):
|
||||
def evaluate_sg(test_ds, predictions, model_thresh):
|
||||
# Group the true products of reactions with the same reactant together
|
||||
assert len(test_ds) == len(predictions)
|
||||
true_dict = {}
|
||||
for r in test_reactions:
|
||||
reactant, true_product_set = r.split(">>")
|
||||
for r in test_ds:
|
||||
reactant, true_product_set = r
|
||||
true_product_set = {p for p in true_product_set.split(".")}
|
||||
true_dict[reactant] = true_dict.setdefault(reactant, []) + [true_product_set]
|
||||
assert len(test_reactions) == len(predictions)
|
||||
assert sum(len(v) for v in true_dict.values()) == len(test_reactions)
|
||||
|
||||
# Group the predicted products of reactions with the same reactant together
|
||||
pred_dict = {}
|
||||
for k, pred in enumerate(predictions):
|
||||
pred_smiles, pred_proba = zip(*pred.items())
|
||||
reactant, true_product = test_reactions[k].split(">>")
|
||||
reactant, _ = test_ds[k, "educts"], test_ds[k, "products"]
|
||||
pred_dict.setdefault(reactant, {"predict": [], "scores": []})
|
||||
for smiles, proba in zip(pred_smiles, pred_proba):
|
||||
smiles = set(smiles.split("."))
|
||||
@ -3199,7 +3184,7 @@ class EnviFormer(PackageBasedModel):
|
||||
break
|
||||
|
||||
# Recall is TP (correct) / TP + FN (len(test_reactions))
|
||||
rec = {f"{k:.2f}": v / len(test_reactions) for k, v in correct.items()}
|
||||
rec = {f"{k:.2f}": v / len(test_ds) for k, v in correct.items()}
|
||||
# Precision is TP (correct) / TP + FP (predicted)
|
||||
prec = {
|
||||
f"{k:.2f}": v / predicted[k] if predicted[k] > 0 else 0 for k, v in correct.items()
|
||||
@ -3278,47 +3263,35 @@ class EnviFormer(PackageBasedModel):
|
||||
|
||||
# If there are eval packages perform single generation evaluation on them instead of random splits
|
||||
if self.eval_packages.count() > 0:
|
||||
ds = []
|
||||
for reaction in Reaction.objects.filter(
|
||||
package__in=self.eval_packages.all()
|
||||
).distinct():
|
||||
educts = ".".join(
|
||||
[
|
||||
FormatConverter.standardize(smile.smiles, remove_stereo=True)
|
||||
for smile in reaction.educts.all()
|
||||
]
|
||||
)
|
||||
products = ".".join(
|
||||
[
|
||||
FormatConverter.standardize(smile.smiles, remove_stereo=True)
|
||||
for smile in reaction.products.all()
|
||||
]
|
||||
)
|
||||
ds.append(f"{educts}>>{products}")
|
||||
test_result = self.model.predict_batch([smirk.split(">>")[0] for smirk in ds])
|
||||
ds = EnviFormerDataset.generate_dataset(
|
||||
Reaction.objects.filter(package__in=self.eval_packages.all()).distinct()
|
||||
)
|
||||
test_result = self.model.predict_batch(ds.X())
|
||||
single_gen_result = evaluate_sg(ds, test_result, self.threshold)
|
||||
self.eval_results = self.compute_averages([single_gen_result])
|
||||
else:
|
||||
from enviformer.finetune import fine_tune
|
||||
|
||||
ds = self.load_dataset()
|
||||
n_splits = 20
|
||||
n_splits = kwargs.get("n_splits", 20)
|
||||
shuff = ShuffleSplit(n_splits=n_splits, test_size=0.1, random_state=42)
|
||||
|
||||
# Single gen eval is done in one loop of train then evaluate rather than storing all n_splits trained models
|
||||
# this helps reduce the memory footprint.
|
||||
single_gen_results = []
|
||||
for split_id, (train_index, test_index) in enumerate(shuff.split(ds)):
|
||||
train = [ds[i] for i in train_index]
|
||||
test = [ds[i] for i in test_index]
|
||||
train = ds[train_index]
|
||||
test = ds[test_index]
|
||||
start = datetime.now()
|
||||
model = fine_tune(train, s.MODEL_DIR, str(split_id), device=s.ENVIFORMER_DEVICE)
|
||||
model = fine_tune(
|
||||
train.X(), train.y(), s.MODEL_DIR, str(split_id), device=s.ENVIFORMER_DEVICE
|
||||
)
|
||||
end = datetime.now()
|
||||
logger.debug(
|
||||
f"EnviFormer finetuning took {(end - start).total_seconds():.2f} seconds"
|
||||
)
|
||||
model.to(s.ENVIFORMER_DEVICE)
|
||||
test_result = model.predict_batch([smirk.split(">>")[0] for smirk in test])
|
||||
test_result = model.predict_batch(test.X())
|
||||
single_gen_results.append(evaluate_sg(test, test_result, self.threshold))
|
||||
|
||||
self.eval_results = self.compute_averages(single_gen_results)
|
||||
@ -3397,23 +3370,12 @@ class EnviFormer(PackageBasedModel):
|
||||
):
|
||||
overlap += 1
|
||||
continue
|
||||
educts = ".".join(
|
||||
[
|
||||
FormatConverter.standardize(smile.smiles, remove_stereo=True)
|
||||
for smile in reaction.educts.all()
|
||||
]
|
||||
)
|
||||
products = ".".join(
|
||||
[
|
||||
FormatConverter.standardize(smile.smiles, remove_stereo=True)
|
||||
for smile in reaction.products.all()
|
||||
]
|
||||
)
|
||||
train_reactions.append(f"{educts}>>{products}")
|
||||
train_reactions.append(reaction)
|
||||
train_ds = EnviFormerDataset.generate_dataset(train_reactions)
|
||||
logging.debug(
|
||||
f"{overlap} compounds had to be removed from multigen split due to overlap within pathways"
|
||||
)
|
||||
model = fine_tune(train_reactions, s.MODEL_DIR, f"mg_{split_id}")
|
||||
model = fine_tune(train_ds.X(), train_ds.y(), s.MODEL_DIR, f"mg_{split_id}")
|
||||
multi_gen_results.append(evaluate_mg(model, test_pathways, self.threshold))
|
||||
|
||||
self.eval_results.update(
|
||||
@ -3462,41 +3424,44 @@ class Scenario(EnviPathModel):
|
||||
scenario_type: str,
|
||||
additional_information: List["EnviPyModel"],
|
||||
):
|
||||
s = Scenario()
|
||||
s.package = package
|
||||
|
||||
if name is None or name.strip() == "":
|
||||
new_s = Scenario()
|
||||
new_s.package = package
|
||||
if name is not None:
|
||||
# Clean for potential XSS
|
||||
name = nh3.clean(name, tags=s.ALLOWED_HTML_TAGS).strip()
|
||||
if name is None or name == "":
|
||||
name = f"Scenario {Scenario.objects.filter(package=package).count() + 1}"
|
||||
|
||||
s.name = name
|
||||
new_s.name = name
|
||||
|
||||
if description is not None and description.strip() != "":
|
||||
s.description = description
|
||||
new_s.description = nh3.clean(description, tags=s.ALLOWED_HTML_TAGS).strip()
|
||||
|
||||
if scenario_date is not None and scenario_date.strip() != "":
|
||||
s.scenario_date = scenario_date
|
||||
new_s.scenario_date = nh3.clean(scenario_date).strip()
|
||||
|
||||
if scenario_type is not None and scenario_type.strip() != "":
|
||||
s.scenario_type = scenario_type
|
||||
new_s.scenario_type = scenario_type
|
||||
|
||||
add_inf = defaultdict(list)
|
||||
|
||||
for info in additional_information:
|
||||
cls_name = info.__class__.__name__
|
||||
ai_data = json.loads(info.model_dump_json())
|
||||
# Clean for potential XSS hidden in the additional information fields.
|
||||
ai_data = json.loads(nh3.clean(info.model_dump_json()).strip())
|
||||
ai_data["uuid"] = f"{uuid4()}"
|
||||
add_inf[cls_name].append(ai_data)
|
||||
|
||||
s.additional_information = add_inf
|
||||
new_s.additional_information = add_inf
|
||||
|
||||
s.save()
|
||||
new_s.save()
|
||||
|
||||
return s
|
||||
return new_s
|
||||
|
||||
@transaction.atomic
|
||||
def add_additional_information(self, data: "EnviPyModel"):
|
||||
cls_name = data.__class__.__name__
|
||||
ai_data = json.loads(data.model_dump_json())
|
||||
# Clean for potential XSS hidden in the additional information fields.
|
||||
ai_data = json.loads(nh3.clean(data.model_dump_json()).strip())
|
||||
ai_data["uuid"] = f"{uuid4()}"
|
||||
|
||||
if cls_name not in self.additional_information:
|
||||
@ -3531,7 +3496,8 @@ class Scenario(EnviPathModel):
|
||||
new_ais = defaultdict(list)
|
||||
for k, vals in data.items():
|
||||
for v in vals:
|
||||
ai_data = json.loads(v.model_dump_json())
|
||||
# Clean for potential XSS hidden in the additional information fields.
|
||||
ai_data = json.loads(nh3.clean(v.model_dump_json()).strip())
|
||||
if hasattr(v, "uuid"):
|
||||
ai_data["uuid"] = str(v.uuid)
|
||||
else:
|
||||
|
||||
@ -172,7 +172,6 @@ def predict(
|
||||
|
||||
except Exception as e:
|
||||
pw.kv.update({"status": "failed"})
|
||||
pw.kv.update(**{"error": str(e)})
|
||||
pw.save()
|
||||
|
||||
if JobLog.objects.filter(task_id=self.request.id).exists():
|
||||
|
||||
118
epdb/views.py
118
epdb/views.py
@ -10,6 +10,7 @@ from django.urls import reverse
|
||||
from django.views.decorators.csrf import csrf_exempt
|
||||
from envipy_additional_information import NAME_MAPPING
|
||||
from oauth2_provider.decorators import protected_resource
|
||||
import nh3
|
||||
|
||||
from utilities.chem import FormatConverter, IndigoUtils
|
||||
from utilities.decorators import package_permission_required
|
||||
@ -85,7 +86,10 @@ def login(request):
|
||||
from django.contrib.auth import authenticate
|
||||
from django.contrib.auth import login
|
||||
|
||||
username = request.POST.get("username")
|
||||
username = request.POST.get("username").strip()
|
||||
if username != request.POST.get("username"):
|
||||
context["message"] = "Login failed!"
|
||||
return render(request, "static/login.html", context)
|
||||
password = request.POST.get("password")
|
||||
|
||||
# Get email for username and check if the account is active
|
||||
@ -237,6 +241,7 @@ def get_base_context(request, for_user=None) -> Dict[str, Any]:
|
||||
"enabled_features": s.FLAGS,
|
||||
"debug": s.DEBUG,
|
||||
"external_databases": ExternalDatabase.get_databases(),
|
||||
"site_id": s.MATOMO_SITE_ID,
|
||||
},
|
||||
}
|
||||
|
||||
@ -669,7 +674,8 @@ def search(request):
|
||||
|
||||
if request.method == "GET":
|
||||
package_urls = request.GET.getlist("packages")
|
||||
searchterm = request.GET.get("search")
|
||||
searchterm = request.GET.get("search").strip()
|
||||
|
||||
mode = request.GET.get("mode")
|
||||
|
||||
# add HTTP_ACCEPT check to differentiate between index and ajax call
|
||||
@ -770,7 +776,6 @@ def package_models(request, package_uuid):
|
||||
|
||||
elif request.method == "POST":
|
||||
log_post_params(request)
|
||||
|
||||
name = request.POST.get("model-name")
|
||||
description = request.POST.get("model-description")
|
||||
|
||||
@ -891,7 +896,7 @@ def package_model(request, package_uuid, model_uuid):
|
||||
return JsonResponse(res, safe=False)
|
||||
|
||||
else:
|
||||
app_domain_assessment = current_model.app_domain.assess(stand_smiles)[0]
|
||||
app_domain_assessment = current_model.app_domain.assess(stand_smiles)
|
||||
return JsonResponse(app_domain_assessment, safe=False)
|
||||
|
||||
context = get_base_context(request)
|
||||
@ -935,8 +940,14 @@ def package_model(request, package_uuid, model_uuid):
|
||||
else:
|
||||
return HttpResponseBadRequest()
|
||||
else:
|
||||
name = request.POST.get("model-name", "").strip()
|
||||
description = request.POST.get("model-description", "").strip()
|
||||
# TODO: Move cleaning to property updater
|
||||
name = request.POST.get("model-name")
|
||||
if name is not None:
|
||||
name = nh3.clean(name, tags=s.ALLOWED_HTML_TAGS).strip()
|
||||
|
||||
description = request.POST.get("model-description")
|
||||
if description is not None:
|
||||
description = nh3.clean(description, tags=s.ALLOWED_HTML_TAGS).strip()
|
||||
|
||||
if any([name, description]):
|
||||
if name:
|
||||
@ -1038,8 +1049,16 @@ def package(request, package_uuid):
|
||||
else:
|
||||
return HttpResponseBadRequest()
|
||||
|
||||
# TODO: Move cleaning to property updater
|
||||
new_package_name = request.POST.get("package-name")
|
||||
if new_package_name is not None:
|
||||
new_package_name = nh3.clean(new_package_name, tags=s.ALLOWED_HTML_TAGS).strip()
|
||||
|
||||
new_package_description = request.POST.get("package-description")
|
||||
if new_package_description is not None:
|
||||
new_package_description = nh3.clean(
|
||||
new_package_description, tags=s.ALLOWED_HTML_TAGS
|
||||
).strip()
|
||||
|
||||
grantee_url = request.POST.get("grantee")
|
||||
read = request.POST.get("read") == "on"
|
||||
@ -1148,7 +1167,7 @@ def package_compounds(request, package_uuid):
|
||||
|
||||
elif request.method == "POST":
|
||||
compound_name = request.POST.get("compound-name")
|
||||
compound_smiles = request.POST.get("compound-smiles")
|
||||
compound_smiles = request.POST.get("compound-smiles").strip()
|
||||
compound_description = request.POST.get("compound-description")
|
||||
|
||||
c = Compound.create(current_package, compound_smiles, compound_name, compound_description)
|
||||
@ -1201,8 +1220,16 @@ def package_compound(request, package_uuid, compound_uuid):
|
||||
|
||||
return JsonResponse({"success": current_compound.url})
|
||||
|
||||
new_compound_name = request.POST.get("compound-name", "").strip()
|
||||
new_compound_description = request.POST.get("compound-description", "").strip()
|
||||
# TODO: Move cleaning to property updater
|
||||
new_compound_name = request.POST.get("compound-name")
|
||||
if new_compound_name is not None:
|
||||
new_compound_name = nh3.clean(new_compound_name, tags=s.ALLOWED_HTML_TAGS).strip()
|
||||
|
||||
new_compound_description = request.POST.get("compound-description")
|
||||
if new_compound_description is not None:
|
||||
new_compound_description = nh3.clean(
|
||||
new_compound_description, tags=s.ALLOWED_HTML_TAGS
|
||||
).strip()
|
||||
|
||||
if new_compound_name:
|
||||
current_compound.name = new_compound_name
|
||||
@ -1267,7 +1294,7 @@ def package_compound_structures(request, package_uuid, compound_uuid):
|
||||
|
||||
elif request.method == "POST":
|
||||
structure_name = request.POST.get("structure-name")
|
||||
structure_smiles = request.POST.get("structure-smiles")
|
||||
structure_smiles = request.POST.get("structure-smiles").strip()
|
||||
structure_description = request.POST.get("structure-description")
|
||||
|
||||
try:
|
||||
@ -1338,8 +1365,16 @@ def package_compound_structure(request, package_uuid, compound_uuid, structure_u
|
||||
else:
|
||||
return HttpResponseBadRequest()
|
||||
|
||||
new_structure_name = request.POST.get("compound-structure-name", "").strip()
|
||||
new_structure_description = request.POST.get("compound-structure-description", "").strip()
|
||||
# TODO: Move cleaning to property updater
|
||||
new_structure_name = request.POST.get("compound-structure-name")
|
||||
if new_structure_name is not None:
|
||||
new_structure_name = nh3.clean(new_structure_name, tags=s.ALLOWED_HTML_TAGS).strip()
|
||||
|
||||
new_structure_description = request.POST.get("compound-structure-description")
|
||||
if new_structure_description is not None:
|
||||
new_structure_description = nh3.clean(
|
||||
new_structure_description, tags=s.ALLOWED_HTML_TAGS
|
||||
).strip()
|
||||
|
||||
if new_structure_name:
|
||||
current_structure.name = new_structure_name
|
||||
@ -1441,11 +1476,11 @@ def package_rules(request, package_uuid):
|
||||
|
||||
# Obtain parameters as required by rule type
|
||||
if rule_type == "SimpleAmbitRule":
|
||||
params["smirks"] = request.POST.get("rule-smirks")
|
||||
params["smirks"] = request.POST.get("rule-smirks").strip()
|
||||
params["reactant_filter_smarts"] = request.POST.get("rule-reactant-smarts")
|
||||
params["product_filter_smarts"] = request.POST.get("rule-product-smarts")
|
||||
elif rule_type == "SimpleRDKitRule":
|
||||
params["reaction_smarts"] = request.POST.get("rule-reaction-smarts")
|
||||
params["reaction_smarts"] = request.POST.get("rule-reaction-smarts").strip()
|
||||
elif rule_type == "ParallelRule":
|
||||
pass
|
||||
elif rule_type == "SequentialRule":
|
||||
@ -1546,8 +1581,14 @@ def package_rule(request, package_uuid, rule_uuid):
|
||||
|
||||
return JsonResponse({"success": current_rule.url})
|
||||
|
||||
rule_name = request.POST.get("rule-name", "").strip()
|
||||
rule_description = request.POST.get("rule-description", "").strip()
|
||||
# TODO: Move cleaning to property updater
|
||||
rule_name = request.POST.get("rule-name")
|
||||
if rule_name is not None:
|
||||
rule_name = nh3.clean(rule_name, tags=s.ALLOWED_HTML_TAGS).strip()
|
||||
|
||||
rule_description = request.POST.get("rule-description")
|
||||
if rule_description is not None:
|
||||
rule_description = nh3.clean(rule_description, tags=s.ALLOWED_HTML_TAGS).strip()
|
||||
|
||||
if rule_name:
|
||||
current_rule.name = rule_name
|
||||
@ -1636,8 +1677,8 @@ def package_reactions(request, package_uuid):
|
||||
elif request.method == "POST":
|
||||
reaction_name = request.POST.get("reaction-name")
|
||||
reaction_description = request.POST.get("reaction-description")
|
||||
reactions_smirks = request.POST.get("reaction-smirks")
|
||||
|
||||
reactions_smirks = request.POST.get("reaction-smirks").strip()
|
||||
educts = reactions_smirks.split(">>")[0].split(".")
|
||||
products = reactions_smirks.split(">>")[1].split(".")
|
||||
|
||||
@ -1698,8 +1739,16 @@ def package_reaction(request, package_uuid, reaction_uuid):
|
||||
|
||||
return JsonResponse({"success": current_reaction.url})
|
||||
|
||||
new_reaction_name = request.POST.get("reaction-name", "").strip()
|
||||
new_reaction_description = request.POST.get("reaction-description", "").strip()
|
||||
# TODO: Move cleaning to property updater
|
||||
new_reaction_name = request.POST.get("reaction-name")
|
||||
if new_reaction_name is not None:
|
||||
new_reaction_name = nh3.clean(new_reaction_name, tags=s.ALLOWED_HTML_TAGS).strip()
|
||||
|
||||
new_reaction_description = request.POST.get("reaction-description")
|
||||
if new_reaction_description is not None:
|
||||
new_reaction_description = nh3.clean(
|
||||
new_reaction_description, tags=s.ALLOWED_HTML_TAGS
|
||||
).strip()
|
||||
|
||||
if new_reaction_name:
|
||||
current_reaction.name = new_reaction_name
|
||||
@ -1776,8 +1825,9 @@ def package_pathways(request, package_uuid):
|
||||
|
||||
name = request.POST.get("name")
|
||||
description = request.POST.get("description")
|
||||
pw_mode = request.POST.get("predict", "predict").strip()
|
||||
|
||||
smiles = request.POST.get("smiles", "").strip()
|
||||
pw_mode = request.POST.get("predict", "predict").strip()
|
||||
|
||||
if "smiles" in request.POST and smiles == "":
|
||||
return error(
|
||||
@ -1786,8 +1836,6 @@ def package_pathways(request, package_uuid):
|
||||
"Pathway prediction failed due to missing or empty SMILES",
|
||||
)
|
||||
|
||||
smiles = smiles.strip()
|
||||
|
||||
try:
|
||||
stand_smiles = FormatConverter.standardize(smiles)
|
||||
except ValueError:
|
||||
@ -1946,8 +1994,14 @@ def package_pathway(request, package_uuid, pathway_uuid):
|
||||
|
||||
return JsonResponse({"success": current_pathway.url})
|
||||
|
||||
# TODO: Move cleaning to property updater
|
||||
pathway_name = request.POST.get("pathway-name")
|
||||
if pathway_name is not None:
|
||||
pathway_name = nh3.clean(pathway_name, tags=s.ALLOWED_HTML_TAGS).strip()
|
||||
|
||||
pathway_description = request.POST.get("pathway-description")
|
||||
if pathway_description is not None:
|
||||
pathway_description = nh3.clean(pathway_description, tags=s.ALLOWED_HTML_TAGS).strip()
|
||||
|
||||
if any([pathway_name, pathway_description]):
|
||||
if pathway_name is not None and pathway_name.strip() != "":
|
||||
@ -2035,8 +2089,8 @@ def package_pathway_nodes(request, package_uuid, pathway_uuid):
|
||||
elif request.method == "POST":
|
||||
node_name = request.POST.get("node-name")
|
||||
node_description = request.POST.get("node-description")
|
||||
node_smiles = request.POST.get("node-smiles")
|
||||
|
||||
node_smiles = request.POST.get("node-smiles").strip()
|
||||
current_pathway.add_node(node_smiles, name=node_name, description=node_description)
|
||||
|
||||
return redirect(current_pathway.url)
|
||||
@ -2198,9 +2252,9 @@ def package_pathway_edges(request, package_uuid, pathway_uuid):
|
||||
|
||||
elif request.method == "POST":
|
||||
log_post_params(request)
|
||||
|
||||
edge_name = request.POST.get("edge-name")
|
||||
edge_description = request.POST.get("edge-description")
|
||||
|
||||
edge_substrates = request.POST.getlist("edge-substrates")
|
||||
edge_products = request.POST.getlist("edge-products")
|
||||
|
||||
@ -2287,7 +2341,7 @@ def package_scenarios(request, package_uuid):
|
||||
"all", False
|
||||
):
|
||||
scens = Scenario.objects.filter(package=current_package).order_by("name")
|
||||
res = [{"name": s.name, "url": s.url, "uuid": s.uuid} for s in scens]
|
||||
res = [{"name": s_.name, "url": s_.url, "uuid": s_.uuid} for s_ in scens]
|
||||
return JsonResponse(res, safe=False)
|
||||
|
||||
context = get_base_context(request)
|
||||
@ -2335,21 +2389,21 @@ def package_scenarios(request, package_uuid):
|
||||
"name": "soil",
|
||||
"widgets": [
|
||||
HTMLGenerator.generate_html(ai, prefix=f"soil_{0}")
|
||||
for ai in [x for s in SOIL_ADDITIONAL_INFORMATION.values() for x in s]
|
||||
for ai in [x for sv in SOIL_ADDITIONAL_INFORMATION.values() for x in sv]
|
||||
],
|
||||
},
|
||||
"Sludge Data": {
|
||||
"name": "sludge",
|
||||
"widgets": [
|
||||
HTMLGenerator.generate_html(ai, prefix=f"sludge_{0}")
|
||||
for ai in [x for s in SLUDGE_ADDITIONAL_INFORMATION.values() for x in s]
|
||||
for ai in [x for sv in SLUDGE_ADDITIONAL_INFORMATION.values() for x in sv]
|
||||
],
|
||||
},
|
||||
"Water-Sediment System Data": {
|
||||
"name": "sediment",
|
||||
"widgets": [
|
||||
HTMLGenerator.generate_html(ai, prefix=f"sediment_{0}")
|
||||
for ai in [x for s in SEDIMENT_ADDITIONAL_INFORMATION.values() for x in s]
|
||||
for ai in [x for sv in SEDIMENT_ADDITIONAL_INFORMATION.values() for x in sv]
|
||||
],
|
||||
},
|
||||
}
|
||||
@ -2364,6 +2418,7 @@ def package_scenarios(request, package_uuid):
|
||||
|
||||
scenario_name = request.POST.get("scenario-name")
|
||||
scenario_description = request.POST.get("scenario-description")
|
||||
|
||||
scenario_date_year = request.POST.get("scenario-date-year")
|
||||
scenario_date_month = request.POST.get("scenario-date-month")
|
||||
scenario_date_day = request.POST.get("scenario-date-day")
|
||||
@ -2377,9 +2432,9 @@ def package_scenarios(request, package_uuid):
|
||||
scenario_type = request.POST.get("scenario-type")
|
||||
|
||||
additional_information = HTMLGenerator.build_models(request.POST.dict())
|
||||
additional_information = [x for s in additional_information.values() for x in s]
|
||||
additional_information = [x for sv in additional_information.values() for x in sv]
|
||||
|
||||
s = Scenario.create(
|
||||
new_scen = Scenario.create(
|
||||
current_package,
|
||||
name=scenario_name,
|
||||
description=scenario_description,
|
||||
@ -2388,7 +2443,7 @@ def package_scenarios(request, package_uuid):
|
||||
additional_information=additional_information,
|
||||
)
|
||||
|
||||
return redirect(s.url)
|
||||
return redirect(new_scen.url)
|
||||
else:
|
||||
return HttpResponseNotAllowed(
|
||||
[
|
||||
@ -2688,6 +2743,7 @@ def settings(request):
|
||||
|
||||
name = request.POST.get("prediction-setting-name")
|
||||
description = request.POST.get("prediction-setting-description")
|
||||
|
||||
new_default = request.POST.get("prediction-setting-new-default", "off") == "on"
|
||||
|
||||
max_nodes = min(
|
||||
|
||||
Binary file not shown.
Binary file not shown.
4
pnpm-lock.yaml
generated
Normal file
4
pnpm-lock.yaml
generated
Normal file
@ -0,0 +1,4 @@
|
||||
lockfileVersion: 6.0
|
||||
specifiers: {}
|
||||
dependencies: {}
|
||||
packages: {}
|
||||
@ -27,10 +27,12 @@ dependencies = [
|
||||
"scikit-learn>=1.6.1",
|
||||
"sentry-sdk[django]>=2.32.0",
|
||||
"setuptools>=80.8.0",
|
||||
"nh3==0.3.2",
|
||||
"polars==1.35.1",
|
||||
]
|
||||
|
||||
[tool.uv.sources]
|
||||
enviformer = { git = "ssh://git@git.envipath.com/enviPath/enviformer.git", rev = "v0.1.2" }
|
||||
enviformer = { git = "ssh://git@git.envipath.com/enviPath/enviformer.git", rev = "v0.1.4" }
|
||||
envipy-plugins = { git = "ssh://git@git.envipath.com/enviPath/enviPy-plugins.git", rev = "v0.1.0" }
|
||||
envipy-additional-information = { git = "ssh://git@git.envipath.com/enviPath/enviPy-additional-information.git", rev = "v0.1.7"}
|
||||
envipy-ambit = { git = "ssh://git@git.envipath.com/enviPath/enviPy-ambit.git" }
|
||||
|
||||
@ -1,6 +1,5 @@
|
||||
{% extends "framework.html" %}
|
||||
{% load static %}
|
||||
{% load envipytags %}
|
||||
{% block content %}
|
||||
|
||||
<div class="panel-group" id="reviewListAccordion">
|
||||
|
||||
@ -192,7 +192,7 @@
|
||||
<div class="panel-body list-group-item" id="ReviewedContent">
|
||||
{% if object_type == 'package' %}
|
||||
{% for obj in reviewed_objects %}
|
||||
<a class="list-group-item" href="{{ obj.url }}">{{ obj.name }}
|
||||
<a class="list-group-item" href="{{ obj.url }}">{{ obj.name|safe }}
|
||||
<span class="glyphicon glyphicon-star" aria-hidden="true"
|
||||
style="float:right" data-toggle="tooltip"
|
||||
data-placement="top" title="" data-original-title="Reviewed">
|
||||
@ -201,7 +201,7 @@
|
||||
{% endfor %}
|
||||
{% else %}
|
||||
{% for obj in reviewed_objects|slice:":50" %}
|
||||
<a class="list-group-item" href="{{ obj.url }}">{{ obj.name }}{# <i>({{ obj.package.name }})</i> #}
|
||||
<a class="list-group-item" href="{{ obj.url }}">{{ obj.name|safe }}{# <i>({{ obj.package.name }})</i> #}
|
||||
<span class="glyphicon glyphicon-star" aria-hidden="true"
|
||||
style="float:right" data-toggle="tooltip"
|
||||
data-placement="top" title="" data-original-title="Reviewed">
|
||||
@ -221,11 +221,11 @@
|
||||
<div class="panel-body list-group-item" id="UnreviewedContent">
|
||||
{% if object_type == 'package' %}
|
||||
{% for obj in unreviewed_objects %}
|
||||
<a class="list-group-item" href="{{ obj.url }}">{{ obj.name }}</a>
|
||||
<a class="list-group-item" href="{{ obj.url }}">{{ obj.name|safe }}</a>
|
||||
{% endfor %}
|
||||
{% else %}
|
||||
{% for obj in unreviewed_objects|slice:":50" %}
|
||||
<a class="list-group-item" href="{{ obj.url }}">{{ obj.name }}</a>
|
||||
<a class="list-group-item" href="{{ obj.url }}">{{ obj.name|safe }}</a>
|
||||
{% endfor %}
|
||||
{% endif %}
|
||||
</div>
|
||||
@ -236,9 +236,9 @@
|
||||
<ul class='list-group'>
|
||||
{% for obj in objects %}
|
||||
{% if object_type == 'user' %}
|
||||
<a class="list-group-item" href="{{ obj.url }}">{{ obj.username }}</a>
|
||||
<a class="list-group-item" href="{{ obj.url }}">{{ obj.username|safe }}</a>
|
||||
{% else %}
|
||||
<a class="list-group-item" href="{{ obj.url }}">{{ obj.name }}</a>
|
||||
<a class="list-group-item" href="{{ obj.url }}">{{ obj.name|safe }}</a>
|
||||
{% endif %}
|
||||
{% endfor %}
|
||||
</ul>
|
||||
|
||||
@ -56,7 +56,7 @@
|
||||
(function () {
|
||||
var u = "//matomo.envipath.com/";
|
||||
_paq.push(['setTrackerUrl', u + 'matomo.php']);
|
||||
_paq.push(['setSiteId', '10']);
|
||||
_paq.push(['setSiteId', '{{ meta.site_id }}']);
|
||||
var d = document, g = d.createElement('script'), s = d.getElementsByTagName('script')[0];
|
||||
g.async = true;
|
||||
g.src = u + 'matomo.js';
|
||||
|
||||
@ -26,12 +26,12 @@
|
||||
{% endif %}
|
||||
<h4 class="panel-title">
|
||||
<a id="{{ obj.id }}-link" data-toggle="collapse" data-parent="#migration-detail"
|
||||
href="#{{ obj.id }}">{{ obj.name }}</a>
|
||||
href="#{{ obj.id }}">{{ obj.name|safe }}</a>
|
||||
</h4>
|
||||
</div>
|
||||
<div id="{{ obj.id }}" class="panel-collapse collapse {% if not obj.status %}in{% endif %}">
|
||||
<div class="panel-body list-group-item">
|
||||
<a class="list-group-item" href="{{ obj.detail_url }}">{{ obj.name }} Migration Detail Page</a>
|
||||
<a class="list-group-item" href="{{ obj.detail_url }}">{{ obj.name|safe }} Migration Detail Page</a>
|
||||
</div>
|
||||
</div>
|
||||
{% endfor %}
|
||||
|
||||
@ -27,7 +27,7 @@
|
||||
{% endif %}
|
||||
<h4 class="panel-title">
|
||||
<a id="{{ obj.id }}-link" data-toggle="collapse" data-parent="#migration-detail"
|
||||
href="#{{ obj.id }}">{{ obj.name }}</a>
|
||||
href="#{{ obj.id }}">{{ obj.name|safe }}</a>
|
||||
</h4>
|
||||
</div>
|
||||
<div id="{{ obj.id }}" class="panel-collapse collapse {% if not obj.status %}in{% endif %}">
|
||||
|
||||
@ -1,3 +1,4 @@
|
||||
|
||||
<div class="modal fade" tabindex="-1" id="new_model_modal" role="dialog" aria-labelledby="new_model_modal"
|
||||
aria-hidden="true">
|
||||
<div class="modal-dialog modal-lg">
|
||||
@ -47,14 +48,14 @@
|
||||
<option disabled>Reviewed Packages</option>
|
||||
{% for obj in meta.readable_packages %}
|
||||
{% if obj.reviewed %}
|
||||
<option value="{{ obj.url }}">{{ obj.name }}</option>
|
||||
<option value="{{ obj.url }}">{{ obj.name|safe }}</option>
|
||||
{% endif %}
|
||||
{% endfor %}
|
||||
|
||||
<option disabled>Unreviewed Packages</option>
|
||||
{% for obj in meta.readable_packages %}
|
||||
{% if not obj.reviewed %}
|
||||
<option value="{{ obj.url }}">{{ obj.name }}</option>
|
||||
<option value="{{ obj.url }}">{{ obj.name|safe }}</option>
|
||||
{% endif %}
|
||||
{% endfor %}
|
||||
</select>
|
||||
@ -68,14 +69,14 @@
|
||||
<option disabled>Reviewed Packages</option>
|
||||
{% for obj in meta.readable_packages %}
|
||||
{% if obj.reviewed %}
|
||||
<option value="{{ obj.url }}">{{ obj.name }}</option>
|
||||
<option value="{{ obj.url }}">{{ obj.name|safe }}</option>
|
||||
{% endif %}
|
||||
{% endfor %}
|
||||
|
||||
<option disabled>Unreviewed Packages</option>
|
||||
{% for obj in meta.readable_packages %}
|
||||
{% if not obj.reviewed %}
|
||||
<option value="{{ obj.url }}">{{ obj.name }}</option>
|
||||
<option value="{{ obj.url }}">{{ obj.name|safe }}</option>
|
||||
{% endif %}
|
||||
{% endfor %}
|
||||
</select>
|
||||
|
||||
@ -1,3 +1,4 @@
|
||||
|
||||
{% load static %}
|
||||
<div class="modal fade" tabindex="-1" id="new_pathway_modal" role="dialog" aria-labelledby="new_pathway_modal"
|
||||
aria-hidden="true" style="overflow-y: auto;">
|
||||
@ -111,7 +112,7 @@
|
||||
|
||||
<select id="settingSelect" name="settingSelect" class="form-control">
|
||||
{% for setting in available_settings %}
|
||||
<option value="{{ setting.id }}">{{ setting.name }}</option>
|
||||
<option value="{{ setting.id }}">{{ setting.name|safe }}</option>
|
||||
{% endfor %}
|
||||
</select>
|
||||
<p></p>
|
||||
|
||||
@ -1,3 +1,4 @@
|
||||
|
||||
{% load static %}
|
||||
|
||||
<div id="new_prediction_setting_modal" class="modal" tabindex="-1">
|
||||
@ -40,14 +41,14 @@
|
||||
<option disabled>Reviewed Packages</option>
|
||||
{% for obj in meta.readable_packages %}
|
||||
{% if obj.reviewed %}
|
||||
<option value="{{ obj.url }}">{{ obj.name }}</option>
|
||||
<option value="{{ obj.url }}">{{ obj.name|safe }}</option>
|
||||
{% endif %}
|
||||
{% endfor %}
|
||||
|
||||
<option disabled>Unreviewed Packages</option>
|
||||
{% for obj in meta.readable_packages %}
|
||||
{% if not obj.reviewed %}
|
||||
<option value="{{ obj.url }}">{{ obj.name }}</option>
|
||||
<option value="{{ obj.url }}">{{ obj.name|safe }}</option>
|
||||
{% endif %}
|
||||
{% endfor %}
|
||||
</select>
|
||||
@ -57,7 +58,7 @@
|
||||
<select id="model-based-prediction-setting-model" name="model-based-prediction-setting-model" class="form-control" data-width='100%'>
|
||||
<option disabled selected>Select the model</option>
|
||||
{% for m in models %}
|
||||
<option value="{{ m.url }}">{{ m.name }}</option>
|
||||
<option value="{{ m.url }}">{{ m.name|safe }}</option>
|
||||
{% endfor %}
|
||||
</select>
|
||||
<label for="model-based-prediction-setting-threshold">Threshold</label>
|
||||
|
||||
@ -1,3 +1,4 @@
|
||||
|
||||
{% load static %}
|
||||
<div class="modal fade bs-modal-lg" id="add_pathway_edge_modal" tabindex="-1" aria-labelledby="add_pathway_edge_modal"
|
||||
aria-modal="true"
|
||||
@ -36,7 +37,7 @@
|
||||
<select id="add_pathway_edge_substrates" name="edge-substrates"
|
||||
data-actions-box='true' class="form-control" multiple data-width='100%'>
|
||||
{% for n in pathway.nodes %}
|
||||
<option data-smiles="{{ n.default_node_label.smiles }}" value="{{ n.url }}">{{ n.default_node_label.name }}</option>
|
||||
<option data-smiles="{{ n.default_node_label.smiles }}" value="{{ n.url }}">{{ n.default_node_label.name|safe }}</option>
|
||||
{% endfor %}
|
||||
</select>
|
||||
</div>
|
||||
@ -47,7 +48,7 @@
|
||||
<select id="add_pathway_edge_products" name="edge-products"
|
||||
data-actions-box='true' class="form-control" multiple data-width='100%'>
|
||||
{% for n in pathway.nodes %}
|
||||
<option data-smiles="{{ n.default_node_label.smiles }}" value="{{ n.url }}">{{ n.default_node_label.name }}</option>
|
||||
<option data-smiles="{{ n.default_node_label.smiles }}" value="{{ n.url }}">{{ n.default_node_label.name|safe }}</option>
|
||||
{% endfor %}
|
||||
</select>
|
||||
</div>
|
||||
|
||||
@ -1,3 +1,4 @@
|
||||
|
||||
{% load static %}
|
||||
<!-- Delete Edge -->
|
||||
<div id="delete_pathway_edge_modal" class="modal" tabindex="-1">
|
||||
@ -19,7 +20,7 @@
|
||||
data-actions-box='true' class="form-control" data-width='100%'>
|
||||
<option value="" disabled selected>Select Reaction to delete</option>
|
||||
{% for e in pathway.edges %}
|
||||
<option value="{{ e.url }}">{{ e.edge_label.name }}</option>
|
||||
<option value="{{ e.url }}">{{ e.edge_label.name|safe }}</option>
|
||||
{% endfor %}
|
||||
</select>
|
||||
<input type="hidden" id="hidden" name="hidden" value="delete"/>
|
||||
|
||||
@ -1,4 +1,5 @@
|
||||
{% load static %}
|
||||
|
||||
<!-- Delete Node -->
|
||||
<div id="delete_pathway_node_modal" class="modal" tabindex="-1">
|
||||
<div class="modal-dialog">
|
||||
@ -19,7 +20,7 @@
|
||||
data-actions-box='true' class="form-control" data-width='100%'>
|
||||
<option value="" disabled selected>Select Compound to delete</option>
|
||||
{% for n in pathway.nodes %}
|
||||
<option value="{{ n.url }}">{{ n.default_node_label.name }}</option>
|
||||
<option value="{{ n.url }}">{{ n.default_node_label.name|safe }}</option>
|
||||
{% endfor %}
|
||||
</select>
|
||||
<input type="hidden" id="hidden" name="hidden" value="delete"/>
|
||||
|
||||
@ -1,3 +1,4 @@
|
||||
|
||||
{% load static %}
|
||||
<!-- Edit Compound -->
|
||||
<div id="edit_compound_modal" class="modal" tabindex="-1">
|
||||
@ -15,12 +16,12 @@
|
||||
{% csrf_token %}
|
||||
<p>
|
||||
<label for="compound-name">Name</label>
|
||||
<input id="compound-name" class="form-control" name="compound-name" value="{{ compound.name}}">
|
||||
<input id="compound-name" class="form-control" name="compound-name" value="{{ compound.name|safe}}">
|
||||
</p>
|
||||
<p>
|
||||
<label for="compound-description">Description</label>
|
||||
<input id="compound-description" type="text" class="form-control"
|
||||
value="{{ compound.description }}"
|
||||
value="{{ compound.description|safe }}"
|
||||
name="compound-description">
|
||||
</p>
|
||||
</form>
|
||||
|
||||
@ -1,3 +1,4 @@
|
||||
|
||||
{% load static %}
|
||||
<!-- Edit Compound -->
|
||||
<div id="edit_compound_structure_modal" class="modal" tabindex="-1">
|
||||
@ -15,12 +16,12 @@
|
||||
{% csrf_token %}
|
||||
<p>
|
||||
<label for="compound-structure-name">Name</label>
|
||||
<input id="compound-structure-name" class="form-control" name="compound-structure-name" value="{{ compound_structure.name }}">
|
||||
<input id="compound-structure-name" class="form-control" name="compound-structure-name" value="{{ compound_structure.name|safe }}">
|
||||
</p>
|
||||
<p>
|
||||
<label for="compound-structure-description">Description</label>
|
||||
<input id="compound-structure-description" type="text" class="form-control"
|
||||
value="{{ compound_structure.description }}" name="compound-structure-description">
|
||||
value="{{ compound_structure.description|safe }}" name="compound-structure-description">
|
||||
</p>
|
||||
</form>
|
||||
</div>
|
||||
|
||||
@ -1,3 +1,4 @@
|
||||
|
||||
{% load static %}
|
||||
<!-- Edit Package Permission -->
|
||||
<div id="edit_group_member_modal" class="modal" tabindex="-1">
|
||||
@ -39,7 +40,7 @@
|
||||
{% endfor %}
|
||||
<option disabled>Groups</option>
|
||||
{% for g in groups %}
|
||||
<option value="{{ g.url }}">{{ g.name }}</option>
|
||||
<option value="{{ g.url }}">{{ g.name|safe }}</option>
|
||||
{% endfor %}
|
||||
</select>
|
||||
<input type="hidden" name="action" value="add">
|
||||
@ -81,7 +82,7 @@
|
||||
accept-charset="UTF-8" action="" data-remote="true" method="post">
|
||||
{% csrf_token %}
|
||||
<div class="col-xs-8">
|
||||
{{ g.name }}
|
||||
{{ g.name|safe }}
|
||||
<input type="hidden" name="member" value="{{ g.url }}"/>
|
||||
<input type="hidden" name="action" value="remove">
|
||||
</div>
|
||||
|
||||
@ -1,3 +1,4 @@
|
||||
|
||||
{% load static %}
|
||||
<!-- Edit Model -->
|
||||
<div id="edit_model_modal" class="modal" tabindex="-1">
|
||||
@ -16,12 +17,12 @@
|
||||
<p>
|
||||
<label for="model-name">Name</label>
|
||||
<input id="model-name" type="text" class="form-control" name="model-name"
|
||||
value="{{ model.name }}">
|
||||
value="{{ model.name|safe }}">
|
||||
</p>
|
||||
<p>
|
||||
<label for="model-description">Description</label>
|
||||
<input id="model-description" type="text" class="form-control" name="model-description"
|
||||
value="{{ model.description }}">
|
||||
value="{{ model.description|safe }}">
|
||||
</p>
|
||||
</form>
|
||||
</div>
|
||||
|
||||
@ -1,3 +1,4 @@
|
||||
|
||||
{% load static %}
|
||||
<!-- Edit Node -->
|
||||
<div id="edit_node_modal" class="modal" tabindex="-1">
|
||||
@ -15,12 +16,12 @@
|
||||
{% csrf_token %}
|
||||
<p>
|
||||
<label for="node-name">Name</label>
|
||||
<input id="node-name" class="form-control" name="node-name" value="{{ node.name}}">
|
||||
<input id="node-name" class="form-control" name="node-name" value="{{ node.name|safe}}">
|
||||
</p>
|
||||
<p>
|
||||
<label for="node-description">Description</label>
|
||||
<input id="node-description" type="text" class="form-control"
|
||||
value="{{ node.description }}"
|
||||
value="{{ node.description|safe }}"
|
||||
name="node-description">
|
||||
</p>
|
||||
</form>
|
||||
|
||||
@ -1,3 +1,4 @@
|
||||
|
||||
{% load static %}
|
||||
<!-- Edit Package -->
|
||||
<div id="edit_package_modal" class="modal" tabindex="-1">
|
||||
@ -15,12 +16,12 @@
|
||||
{% csrf_token %}
|
||||
<p>
|
||||
<label for="package-name">Name</label>
|
||||
<input id="package-name" class="form-control" name="package-name" value="{{ package.name}}">
|
||||
<input id="package-name" class="form-control" name="package-name" value="{{ package.name|safe}}">
|
||||
</p>
|
||||
<p>
|
||||
<label for="package-description">Description</label>
|
||||
<input id="package-description" type="text" class="form-control"
|
||||
value="{{ package.description }}"
|
||||
value="{{ package.description|safe }}"
|
||||
name="package-description">
|
||||
</p>
|
||||
</form>
|
||||
|
||||
@ -1,3 +1,4 @@
|
||||
|
||||
{% load static %}
|
||||
<!-- Edit Package Permission -->
|
||||
<div id="edit_package_permissions_modal" class="modal" tabindex="-1">
|
||||
@ -46,7 +47,7 @@
|
||||
{% endfor %}
|
||||
<option disabled>Groups</option>
|
||||
{% for g in groups %}
|
||||
<option value="{{ g.url }}">{{ g.name }}</option>
|
||||
<option value="{{ g.url }}">{{ g.name|safe }}</option>
|
||||
{% endfor %}
|
||||
</select>
|
||||
</div>
|
||||
@ -100,7 +101,7 @@
|
||||
accept-charset="UTF-8" action="" data-remote="true" method="post">
|
||||
{% csrf_token %}
|
||||
<div class="col-xs-4">
|
||||
{{ gp.group.name }}
|
||||
{{ gp.group.name|safe }}
|
||||
<input type="hidden" name="grantee" value="{{ gp.group.url }}"/>
|
||||
</div>
|
||||
<div class="col-xs-2">
|
||||
|
||||
@ -1,3 +1,4 @@
|
||||
|
||||
{% load static %}
|
||||
<!-- Edit Pathway -->
|
||||
<div id="edit_pathway_modal" class="modal" tabindex="-1">
|
||||
@ -15,12 +16,12 @@
|
||||
{% csrf_token %}
|
||||
<p>
|
||||
<label for="pathway-name">Name</label>
|
||||
<input id="pathway-name" class="form-control" name="pathway-name" value="{{ pathway.name }}">
|
||||
<input id="pathway-name" class="form-control" name="pathway-name" value="{{ pathway.name|safe }}">
|
||||
</p>
|
||||
<p>
|
||||
<label for="pathway-description">Description</label>
|
||||
<textarea id="pathway-description" type="text" class="form-control" name="pathway-description"
|
||||
rows="10">{{ pathway.description }}</textarea>
|
||||
rows="10">{{ pathway.description|safe }}</textarea>
|
||||
</p>
|
||||
</form>
|
||||
</div>
|
||||
|
||||
@ -32,7 +32,7 @@
|
||||
<td colspan="2">
|
||||
<select id="model" name="model" class="form-control" data-width='100%'>
|
||||
{% for m in models %}
|
||||
<option value="{{ m.id }}" {% if user.prediction_settings.model.url == m.url %}selected{% endif %}>{{ m.name }}</option>
|
||||
<option value="{{ m.id }}" {% if user.prediction_settings.model.url == m.url %}selected{% endif %}>{{ m.name|safe }}</option>
|
||||
{% endfor %}
|
||||
</select>
|
||||
</td>
|
||||
|
||||
@ -1,3 +1,4 @@
|
||||
|
||||
{% load static %}
|
||||
<!-- Edit Reaction -->
|
||||
<div id="edit_reaction_modal" class="modal" tabindex="-1">
|
||||
@ -14,12 +15,12 @@
|
||||
{% csrf_token %}
|
||||
<p>
|
||||
<label for="reaction-name">Name</label>
|
||||
<input id="reaction-name" class="form-control" name="reaction-name" value="{{ reaction.name }}">
|
||||
<input id="reaction-name" class="form-control" name="reaction-name" value="{{ reaction.name|safe }}">
|
||||
</p>
|
||||
<p>
|
||||
<label for="reaction-description">Description</label>
|
||||
<input id="reaction-description" type="text" class="form-control"
|
||||
value="{{ reaction.description }}" name="reaction-description">
|
||||
value="{{ reaction.description|safe }}" name="reaction-description">
|
||||
</p>
|
||||
</form>
|
||||
</div>
|
||||
|
||||
@ -1,3 +1,4 @@
|
||||
|
||||
{% load static %}
|
||||
<!-- Edit Rule -->
|
||||
<div id="edit_rule_modal" class="modal" tabindex="-1">
|
||||
@ -14,12 +15,12 @@
|
||||
{% csrf_token %}
|
||||
<p>
|
||||
<label for="rule-name">Name</label>
|
||||
<input id="rule-name" class="form-control" name="rule-name" value="{{ rule.name }}">
|
||||
<input id="rule-name" class="form-control" name="rule-name" value="{{ rule.name|safe }}">
|
||||
</p>
|
||||
<p>
|
||||
<label for="rule-description">Description</label>
|
||||
<input id="rule-description" type="text" class="form-control"
|
||||
value="{{ rule.description }}" name="rule-description">
|
||||
value="{{ rule.description|safe }}" name="rule-description">
|
||||
</p>
|
||||
</form>
|
||||
</div>
|
||||
|
||||
@ -1,3 +1,4 @@
|
||||
|
||||
{% load static %}
|
||||
<!-- Edit User -->
|
||||
<div id="edit_user_modal" class="modal" tabindex="-1">
|
||||
@ -18,7 +19,7 @@
|
||||
<select id="default-package" name="default-package" class="form-control" data-width='100%'>
|
||||
<option disabled>Select a Package</option>
|
||||
{% for p in meta.writeable_packages %}
|
||||
<option value="{{ p.url }}" {% if p.id == meta.user.default_package.id %}selected{% endif %}>{{ p.name }}</option>
|
||||
<option value="{{ p.url }}" {% if p.id == meta.user.default_package.id %}selected{% endif %}>{{ p.name|safe }}</option>
|
||||
{% endfor %}
|
||||
</select>
|
||||
</p>
|
||||
@ -27,7 +28,7 @@
|
||||
<select id="default-group" name="default-group" class="form-control" data-width='100%'>
|
||||
<option disabled>Select a Group</option>
|
||||
{% for g in meta.available_groups %}
|
||||
<option value="{{ g.url }}" {% if g.id == meta.user.default_group.id %}selected{% endif %}>{{ g.name }}</option>
|
||||
<option value="{{ g.url }}" {% if g.id == meta.user.default_group.id %}selected{% endif %}>{{ g.name|safe }}</option>
|
||||
{% endfor %}
|
||||
</select>
|
||||
</p>
|
||||
@ -36,7 +37,7 @@
|
||||
<select id="default-prediction-setting" name="default-prediction-setting" class="form-control" data-width='100%'>
|
||||
<option disabled>Select a Setting</option>
|
||||
{% for s in meta.available_settings %}
|
||||
<option value="{{ s.url }}" {% if s.id == meta.user.default_setting.id %}selected{% endif %}>{{ s.name }}</option>
|
||||
<option value="{{ s.url }}" {% if s.id == meta.user.default_setting.id %}selected{% endif %}>{{ s.name|safe }}</option>
|
||||
{% endfor %}
|
||||
</select>
|
||||
</p>
|
||||
|
||||
@ -1,3 +1,4 @@
|
||||
|
||||
<div class="modal fade" tabindex="-1" id="evaluate_model_modal" role="dialog" aria-labelledby="evaluate_model_modal"
|
||||
aria-hidden="true">
|
||||
<div class="modal-dialog modal-lg">
|
||||
@ -24,14 +25,14 @@
|
||||
<option disabled>Reviewed Packages</option>
|
||||
{% for obj in meta.readable_packages %}
|
||||
{% if obj.reviewed %}
|
||||
<option value="{{ obj.url }}">{{ obj.name }}</option>
|
||||
<option value="{{ obj.url }}">{{ obj.name|safe }}</option>
|
||||
{% endif %}
|
||||
{% endfor %}
|
||||
|
||||
<option disabled>Unreviewed Packages</option>
|
||||
{% for obj in meta.readable_packages %}
|
||||
{% if not obj.reviewed %}
|
||||
<option value="{{ obj.url }}">{{ obj.name }}</option>
|
||||
<option value="{{ obj.url }}">{{ obj.name|safe }}</option>
|
||||
{% endif %}
|
||||
{% endfor %}
|
||||
</select>
|
||||
|
||||
@ -1,3 +1,4 @@
|
||||
|
||||
{% load static %}
|
||||
<!-- Copy Object -->
|
||||
<div id="generic_copy_object_modal" class="modal" tabindex="-1">
|
||||
@ -18,7 +19,7 @@
|
||||
data-width='100%'>
|
||||
<option disabled selected>Select Target Package</option>
|
||||
{% for p in meta.writeable_packages %}
|
||||
<option value="{{ p.url }}">{{ p.name }}</option>`
|
||||
<option value="{{ p.url }}">{{ p.name|safe }}</option>`
|
||||
{% endfor %}
|
||||
</select>
|
||||
<input type="hidden" name="hidden" value="copy">
|
||||
|
||||
@ -1,3 +1,4 @@
|
||||
|
||||
{% load static %}
|
||||
|
||||
<style>
|
||||
@ -55,7 +56,7 @@
|
||||
<button type="button" class="close" data-dismiss="modal" aria-label="Close">
|
||||
<span aria-hidden="true">×</span>
|
||||
</button>
|
||||
<h4 class="modal-title">Set Aliases for {{ current_object.name }}</h4>
|
||||
<h4 class="modal-title">Set Aliases for {{ current_object.name|safe }}</h4>
|
||||
</div>
|
||||
<div class="modal-body">
|
||||
<form id="set_aliases_modal_form" accept-charset="UTF-8" action="{{ current_object.url }}"
|
||||
|
||||
@ -1,3 +1,4 @@
|
||||
|
||||
{% load static %}
|
||||
<!-- Delete Object -->
|
||||
<div id="generic_set_external_reference_modal" class="modal" tabindex="-1">
|
||||
@ -23,7 +24,7 @@
|
||||
{% if entity == object_type %}
|
||||
{% for db in databases %}
|
||||
<option id="db-select-{{ db.database.pk }}" data-input-placeholder="{{ db.placeholder }}"
|
||||
value="{{ db.database.id }}">{{ db.database.name }}</option>`
|
||||
value="{{ db.database.id }}">{{ db.database.name|safe }}</option>`
|
||||
{% endfor %}
|
||||
{% endif %}
|
||||
{% endfor %}
|
||||
|
||||
@ -1,3 +1,4 @@
|
||||
|
||||
{% load static %}
|
||||
<div class="modal fade bs-modal-lg" id="set_scenario_modal" tabindex="-1" aria-labelledby="set_scenario_modal"
|
||||
aria-modal="true" role="dialog">
|
||||
@ -7,7 +8,7 @@
|
||||
<button type="button" class="close" data-dismiss="modal" aria-label="Close">
|
||||
<span aria-hidden="true">×</span>
|
||||
</button>
|
||||
<h4 class="modal-title">Set Scenarios for {{ current_object.name }}</h4>
|
||||
<h4 class="modal-title">Set Scenarios for {{ current_object.name|safe }}</h4>
|
||||
</div>
|
||||
<div class="modal-body">
|
||||
<div id="loading_scenario_div" class="text-center"></div>
|
||||
|
||||
@ -1,3 +1,4 @@
|
||||
|
||||
<div class="modal fade"
|
||||
tabindex="-1"
|
||||
id="manage_api_token_modal"
|
||||
@ -41,7 +42,7 @@
|
||||
<div class="input-group">
|
||||
<input type="hidden" name="hidden" value="delete">
|
||||
<input type="hidden" name="token-id" value="{{ t.pk }}">
|
||||
<input type="text" class="form-control" value="{{ t.name }}" disabled>
|
||||
<input type="text" class="form-control" value="{{ t.name|safe }}" disabled>
|
||||
<span class="input-group-btn">
|
||||
<button type="submit" class="btn btn-danger">Delete</button>
|
||||
</span>
|
||||
|
||||
@ -56,7 +56,7 @@
|
||||
<option disabled>Select a Setting</option>
|
||||
{% for s in meta.available_settings %}
|
||||
<option value="{{ s.url }}"{% if s.id == meta.user.default_setting.id %}selected{% endif %}>
|
||||
{{ s.name }}{% if s.id == meta.user.default_setting.id %} <i>(User default)</i>{% endif %}
|
||||
{{ s.name|safe }}{% if s.id == meta.user.default_setting.id %} <i>(User default)</i>{% endif %}
|
||||
</option>
|
||||
{% endfor %}
|
||||
</select>
|
||||
|
||||
@ -13,7 +13,7 @@
|
||||
<div class="panel-group" id="rule-detail">
|
||||
<div class="panel panel-default">
|
||||
<div class="panel-heading" id="headingPanel" style="font-size:2rem;height: 46px">
|
||||
{{ rule.name }}
|
||||
{{ rule.name|safe }}
|
||||
<div id="actionsButton"
|
||||
style="float: right;font-weight: normal;font-size: medium;position: relative; top: 50%; transform: translateY(-50%);z-index:100;display: none;"
|
||||
class="dropdown"><a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button"
|
||||
@ -60,7 +60,7 @@
|
||||
<div id="rule-reaction-patterns" class="panel-collapse collapse in">
|
||||
<div class="panel-body list-group-item">
|
||||
{% for r in rule.srs %}
|
||||
<a class="list-group-item" href="{{ r.url }}">{{ r.name }}</a>
|
||||
<a class="list-group-item" href="{{ r.url }}">{{ r.name|safe }}</a>
|
||||
<div align="center">
|
||||
<p>
|
||||
{{r.as_svg|safe}}
|
||||
@ -81,7 +81,7 @@
|
||||
<div id="rule-scenario" class="panel-collapse collapse in">
|
||||
<div class="panel-body list-group-item">
|
||||
{% for s in rule.scenarios.all %}
|
||||
<a class="list-group-item" href="{{ s.url }}">{{ s.name }} <i>({{ s.package.name }})</i></a>
|
||||
<a class="list-group-item" href="{{ s.url }}">{{ s.name|safe }} <i>({{ s.package.name|safe }})</i></a>
|
||||
{% endfor %}
|
||||
</div>
|
||||
</div>
|
||||
|
||||
@ -15,7 +15,7 @@
|
||||
<div class="panel-group" id="compound-detail">
|
||||
<div class="panel panel-default">
|
||||
<div class="panel-heading" id="headingPanel" style="font-size:2rem;height: 46px">
|
||||
{{ compound.name }}
|
||||
{{ compound.name|safe }}
|
||||
<div id="actionsButton"
|
||||
style="float: right;font-weight: normal;font-size: medium;position: relative; top: 50%; transform: translateY(-50%);z-index:100;display: none;"
|
||||
class="dropdown"><a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button"
|
||||
@ -64,7 +64,7 @@
|
||||
</div>
|
||||
<div id="compound-desc" class="panel-collapse collapse in">
|
||||
<div class="panel-body list-group-item">
|
||||
{{ compound.description }}
|
||||
{{ compound.description|safe }}
|
||||
</div>
|
||||
</div>
|
||||
|
||||
@ -133,7 +133,7 @@
|
||||
<div id="compound-reaction" class="panel-collapse collapse in">
|
||||
<div class="panel-body list-group-item">
|
||||
{% for r in compound.related_reactions %}
|
||||
<a class="list-group-item" href="{{ r.url }}">{{ r.name }} <i>({{ r.package.name }})</i></a>
|
||||
<a class="list-group-item" href="{{ r.url }}">{{ r.name|safe }} <i>({{ r.package.name|safe }})</i></a>
|
||||
{% endfor %}
|
||||
</div>
|
||||
</div>
|
||||
@ -150,7 +150,7 @@
|
||||
<div id="compound-pathway" class="panel-collapse collapse in">
|
||||
<div class="panel-body list-group-item">
|
||||
{% for r in compound.related_pathways %}
|
||||
<a class="list-group-item" href="{{ r.url }}">{{ r.name }} <i>({{ r.package.name }})</i></a>
|
||||
<a class="list-group-item" href="{{ r.url }}">{{ r.name|safe }} <i>({{ r.package.name|safe }})</i></a>
|
||||
{% endfor %}
|
||||
</div>
|
||||
</div>
|
||||
@ -167,7 +167,7 @@
|
||||
<div id="compound-scenario" class="panel-collapse collapse in">
|
||||
<div class="panel-body list-group-item">
|
||||
{% for s in compound.scenarios.all %}
|
||||
<a class="list-group-item" href="{{ s.url }}">{{ s.name }} <i>({{ s.package.name }})</i></a>
|
||||
<a class="list-group-item" href="{{ s.url }}">{{ s.name|safe }} <i>({{ s.package.name|safe }})</i></a>
|
||||
{% endfor %}
|
||||
</div>
|
||||
</div>
|
||||
|
||||
@ -13,7 +13,7 @@
|
||||
<div class="panel-group" id="compound-structure-detail">
|
||||
<div class="panel panel-default">
|
||||
<div class="panel-heading" id="headingPanel" style="font-size:2rem;height: 46px">
|
||||
{{ compound_structure.name }}
|
||||
{{ compound_structure.name|safe }}
|
||||
<div id="actionsButton"
|
||||
style="float: right;font-weight: normal;font-size: medium;position: relative; top: 50%; transform: translateY(-50%);z-index:100;display: none;"
|
||||
class="dropdown"><a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button"
|
||||
@ -28,7 +28,7 @@
|
||||
</div>
|
||||
</div>
|
||||
<div class="panel-body">
|
||||
<p> {{ compound_structure.description }} </p>
|
||||
<p> {{ compound_structure.description|safe }} </p>
|
||||
</div>
|
||||
|
||||
<!-- Image -->
|
||||
@ -86,7 +86,7 @@
|
||||
<div id="compound-structure-scenario" class="panel-collapse collapse in">
|
||||
<div class="panel-body list-group-item">
|
||||
{% for s in compound_structure.scenarios.all %}
|
||||
<a class="list-group-item" href="{{ s.url }}">{{ s.name }} <i>({{ s.package.name }})</i></a>
|
||||
<a class="list-group-item" href="{{ s.url }}">{{ s.name|safe }} <i>({{ s.package.name|safe }})</i></a>
|
||||
{% endfor %}
|
||||
</div>
|
||||
</div>
|
||||
|
||||
@ -12,7 +12,7 @@
|
||||
<div class="panel-group" id="edge-detail">
|
||||
<div class="panel panel-default">
|
||||
<div class="panel-heading" id="headingPanel" style="font-size:2rem;height: 46px">
|
||||
{{ edge.edge_label.name }}
|
||||
{{ edge.edge_label.name|safe }}
|
||||
<div id="actionsButton"
|
||||
style="float: right;font-weight: normal;font-size: medium;position: relative; top: 50%; transform: translateY(-50%);z-index:100;display: none;"
|
||||
class="dropdown"><a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button"
|
||||
@ -36,7 +36,7 @@
|
||||
</div>
|
||||
<div id="edge-desc" class="panel-collapse collapse in">
|
||||
<div class="panel-body list-group-item">
|
||||
{{ edge.description }}
|
||||
{{ edge.description|safe }}
|
||||
</div>
|
||||
</div>
|
||||
|
||||
@ -82,12 +82,12 @@
|
||||
<div id="edge-description-smiles" class="panel-collapse collapse in">
|
||||
<div class="panel-body list-group-item">
|
||||
{% for educt in edge.start_nodes.all %}
|
||||
<a class="btn btn-default" href="{{ educt.url }}">{{ educt.name }}</a>
|
||||
<a class="btn btn-default" href="{{ educt.url }}">{{ educt.name|safe }}</a>
|
||||
{% endfor %}
|
||||
<span class="glyphicon glyphicon-arrow-right" style="margin-left:5em;margin-right:5em;"
|
||||
aria-hidden="true"></span>
|
||||
{% for product in edge.end_nodes.all %}
|
||||
<a class="btn btn-default" href="{{ product.url }}">{{ product.name }}</a>
|
||||
<a class="btn btn-default" href="{{ product.url }}">{{ product.name|safe }}</a>
|
||||
{% endfor %}
|
||||
</div>
|
||||
</div>
|
||||
@ -116,7 +116,7 @@
|
||||
<div id="edge-rules" class="panel-collapse collapse in">
|
||||
<div class="panel-body list-group-item">
|
||||
{% for r in edge.edge_label.rules.all %}
|
||||
<a class="list-group-item" href="{{ r.url }}">{{ r.name }}</a>
|
||||
<a class="list-group-item" href="{{ r.url }}">{{ r.name|safe }}</a>
|
||||
{% endfor %}
|
||||
</div>
|
||||
</div>
|
||||
@ -132,7 +132,7 @@
|
||||
<div id="edge-scenario" class="panel-collapse collapse in">
|
||||
<div class="panel-body list-group-item">
|
||||
{% for s in edge.scenarios.all %}
|
||||
<a class="list-group-item" href="{{ s.url }}">{{ s.name }} <i>({{ s.package.name }})</i></a>
|
||||
<a class="list-group-item" href="{{ s.url }}">{{ s.name|safe }} <i>({{ s.package.name|safe }})</i></a>
|
||||
{% endfor %}
|
||||
</div>
|
||||
</div>
|
||||
|
||||
@ -11,7 +11,7 @@
|
||||
<div class="panel-group" id="package-detail">
|
||||
<div class="panel panel-default">
|
||||
<div class="panel-heading" id="headingPanel" style="font-size:2rem;height: 46px">
|
||||
{{ group.name }}
|
||||
{{ group.name|safe }}
|
||||
<div id="actionsButton"
|
||||
style="float: right;font-weight: normal;font-size: medium;position: relative; top: 50%; transform: translateY(-50%);z-index:100;display: none;"
|
||||
class="dropdown"><a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button"
|
||||
@ -26,7 +26,7 @@
|
||||
</div>
|
||||
</div>
|
||||
<div class="panel-body">
|
||||
<p> {{ group.description }} </p>
|
||||
<p> {{ group.description|safe }} </p>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
@ -39,10 +39,10 @@
|
||||
</div>
|
||||
<ul class="list-group">
|
||||
{% for um in group.user_member.all %}
|
||||
<a class="list-group-item" href="{{ um.url }}">{{ um.username }}</a>
|
||||
<a class="list-group-item" href="{{ um.url }}">{{ um.username|safe }}</a>
|
||||
{% endfor %}
|
||||
{% for gm in group.group_member.all %}
|
||||
<a class="list-group-item" href="{{ gm.url }}">{{ gm.name }}</a>
|
||||
<a class="list-group-item" href="{{ gm.url }}">{{ gm.name|safe }}</a>
|
||||
{% endfor %}
|
||||
</ul>
|
||||
</div>
|
||||
@ -56,7 +56,7 @@
|
||||
</div>
|
||||
<ul class="list-group">
|
||||
{% for p in packages %}
|
||||
<a class="list-group-item" href="{{ p.url }}">{{ p.name }}</a>
|
||||
<a class="list-group-item" href="{{ p.url }}">{{ p.name|safe }}</a>
|
||||
{% endfor %}
|
||||
</ul>
|
||||
</div>
|
||||
|
||||
@ -1,6 +1,5 @@
|
||||
{% extends "framework.html" %}
|
||||
{% load static %}
|
||||
{% load envipytags %}
|
||||
{% block content %}
|
||||
|
||||
{% block action_modals %}
|
||||
@ -18,7 +17,7 @@
|
||||
<div class="panel-group" id="model-detail">
|
||||
<div class="panel panel-default">
|
||||
<div class="panel-heading" id="headingPanel" style="font-size:2rem;height: 46px">
|
||||
{{ model.name }}
|
||||
{{ model.name|safe }}
|
||||
<div id="actionsButton"
|
||||
style="float: right;font-weight: normal;font-size: medium;position: relative; top: 50%; transform: translateY(-50%);z-index:100;display: none;"
|
||||
class="dropdown"><a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button"
|
||||
@ -33,7 +32,7 @@
|
||||
</div>
|
||||
</div>
|
||||
<div class="panel-body">
|
||||
<p> {{ model.description }} </p>
|
||||
<p> {{ model.description|safe }} </p>
|
||||
</div>
|
||||
{% if model|classname == 'MLRelativeReasoning' or model|classname == 'RuleBasedRelativeReasoning'%}
|
||||
<!-- Rule Packages -->
|
||||
@ -46,7 +45,7 @@
|
||||
<div id="rule-package" class="panel-collapse collapse in">
|
||||
<div class="panel-body list-group-item">
|
||||
{% for p in model.rule_packages.all %}
|
||||
<a class="list-group-item" href="{{ p.url }}">{{ p.name }}</a>
|
||||
<a class="list-group-item" href="{{ p.url }}">{{ p.name|safe }}</a>
|
||||
{% endfor %}
|
||||
</div>
|
||||
</div>
|
||||
@ -60,7 +59,7 @@
|
||||
<div id="reaction-package" class="panel-collapse collapse in">
|
||||
<div class="panel-body list-group-item">
|
||||
{% for p in model.data_packages.all %}
|
||||
<a class="list-group-item" href="{{ p.url }}">{{ p.name }}</a>
|
||||
<a class="list-group-item" href="{{ p.url }}">{{ p.name|safe }}</a>
|
||||
{% endfor %}
|
||||
</div>
|
||||
</div>
|
||||
@ -75,7 +74,7 @@
|
||||
<div id="eval-package" class="panel-collapse collapse in">
|
||||
<div class="panel-body list-group-item">
|
||||
{% for p in model.eval_packages.all %}
|
||||
<a class="list-group-item" href="{{ p.url }}">{{ p.name }}</a>
|
||||
<a class="list-group-item" href="{{ p.url }}">{{ p.name|safe }}</a>
|
||||
{% endfor %}
|
||||
</div>
|
||||
</div>
|
||||
|
||||
@ -12,7 +12,7 @@
|
||||
<div class="panel-group" id="node-detail">
|
||||
<div class="panel panel-default">
|
||||
<div class="panel-heading" id="headingPanel" style="font-size:2rem;height: 46px">
|
||||
{{ node.name }}
|
||||
{{ node.name|safe }}
|
||||
<div id="actionsButton"
|
||||
style="float: right;font-weight: normal;font-size: medium;position: relative; top: 50%; transform: translateY(-50%);z-index:100;display: none;"
|
||||
class="dropdown"><a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button"
|
||||
@ -39,7 +39,7 @@
|
||||
</div>
|
||||
<div id="node-desc" class="panel-collapse collapse in">
|
||||
<div class="panel-body list-group-item">
|
||||
{{ node.description }}
|
||||
{{ node.description|safe }}
|
||||
</div>
|
||||
</div>
|
||||
|
||||
@ -98,7 +98,7 @@
|
||||
<div id="node-scenario" class="panel-collapse collapse in">
|
||||
<div class="panel-body list-group-item">
|
||||
{% for s in node.scenarios.all %}
|
||||
<a class="list-group-item" href="{{ s.url }}">{{ s.name }} <i>({{ s.package.name }})</i></a>
|
||||
<a class="list-group-item" href="{{ s.url }}">{{ s.name|safe }} <i>({{ s.package.name|safe }})</i></a>
|
||||
{% endfor %}
|
||||
</div>
|
||||
</div>
|
||||
|
||||
@ -14,7 +14,7 @@
|
||||
<div class="panel-group" id="package-detail">
|
||||
<div class="panel panel-default">
|
||||
<div class="panel-heading" id="headingPanel" style="font-size:2rem;height: 46px">
|
||||
{{ package.name }}
|
||||
{{ package.name|safe }}
|
||||
<div id="actionsButton"
|
||||
style="float: right;font-weight: normal;font-size: medium;position: relative; top: 50%; transform: translateY(-50%);z-index:100;display: none;"
|
||||
class="dropdown"><a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button"
|
||||
|
||||
@ -98,7 +98,7 @@
|
||||
<div class="panel-group" id="pwAccordion">
|
||||
<div class="panel panel-default">
|
||||
<div class="panel-heading" id="headingPanel" style="font-size:2rem;height: 46px">
|
||||
{{ pathway.name }}
|
||||
{{ pathway.name|safe }}
|
||||
</div>
|
||||
</div>
|
||||
<div class="panel panel-default panel-heading list-group-item" style="background-color:silver">
|
||||
@ -236,7 +236,7 @@
|
||||
<div id="pathway-scenario" class="panel-collapse collapse in">
|
||||
<div class="panel-body list-group-item">
|
||||
{% for s in pathway.scenarios.all %}
|
||||
<a class="list-group-item" href="{{ s.url }}">{{ s.name }} <i>({{ s.package.name }})</i></a>
|
||||
<a class="list-group-item" href="{{ s.url }}">{{ s.name|safe }} <i>({{ s.package.name|safe }})</i></a>
|
||||
{% endfor %}
|
||||
</div>
|
||||
</div>
|
||||
@ -266,7 +266,7 @@
|
||||
<td colspan="2">
|
||||
<li class="list-group-item">
|
||||
<a href="{{ pathway.setting.model.url }}">
|
||||
{{ pathway.setting.model.name }}
|
||||
{{ pathway.setting.model.name|safe }}
|
||||
</a>
|
||||
</li>
|
||||
</td>
|
||||
@ -299,7 +299,7 @@
|
||||
{% for p in pathway.setting.rule_packages.all %}
|
||||
<li class="list-group-item">
|
||||
<a href="{{ p.url }}">
|
||||
{{ p.name }}
|
||||
{{ p.name|safe }}
|
||||
</a>
|
||||
</li>
|
||||
{% endfor %}
|
||||
|
||||
@ -14,7 +14,7 @@
|
||||
<div class="panel-group" id="reaction-detail">
|
||||
<div class="panel panel-default">
|
||||
<div class="panel-heading" id="headingPanel" style="font-size:2rem;height: 46px">
|
||||
{{ reaction.name }}
|
||||
{{ reaction.name|safe }}
|
||||
<div id="actionsButton"
|
||||
style="float: right;font-weight: normal;font-size: medium;position: relative; top: 50%; transform: translateY(-50%);z-index:100;display: none;"
|
||||
class="dropdown"><a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button"
|
||||
@ -38,7 +38,7 @@
|
||||
</div>
|
||||
<div id="reaction-desc" class="panel-collapse collapse in">
|
||||
<div class="panel-body list-group-item">
|
||||
{{ reaction.description }}
|
||||
{{ reaction.description|safe }}
|
||||
</div>
|
||||
</div>
|
||||
|
||||
@ -84,12 +84,12 @@
|
||||
<div id="reaction-description-smiles" class="panel-collapse collapse in">
|
||||
<div class="panel-body list-group-item">
|
||||
{% for educt in reaction.educts.all %}
|
||||
<a class="btn btn-default" href="{{ educt.url }}">{{ educt.name }}</a>
|
||||
<a class="btn btn-default" href="{{ educt.url }}">{{ educt.name|safe }}</a>
|
||||
{% endfor %}
|
||||
<span class="glyphicon glyphicon-arrow-right" style="margin-left:5em;margin-right:5em;"
|
||||
aria-hidden="true"></span>
|
||||
{% for product in reaction.products.all %}
|
||||
<a class="btn btn-default" href="{{ product.url }}">{{ product.name }}</a>
|
||||
<a class="btn btn-default" href="{{ product.url }}">{{ product.name|safe }}</a>
|
||||
{% endfor %}
|
||||
</div>
|
||||
</div>
|
||||
@ -118,7 +118,7 @@
|
||||
<div id="reaction-rules" class="panel-collapse collapse in">
|
||||
<div class="panel-body list-group-item">
|
||||
{% for r in reaction.rules.all %}
|
||||
<a class="list-group-item" href="{{ r.url }}">{{ r.name }}</a>
|
||||
<a class="list-group-item" href="{{ r.url }}">{{ r.name|safe }}</a>
|
||||
{% endfor %}
|
||||
</div>
|
||||
</div>
|
||||
@ -152,7 +152,7 @@
|
||||
<div id="reaction-pathway" class="panel-collapse collapse in">
|
||||
<div class="panel-body list-group-item">
|
||||
{% for r in reaction.related_pathways %}
|
||||
<a class="list-group-item" href="{{ r.url }}">{{ r.name }}</a>
|
||||
<a class="list-group-item" href="{{ r.url }}">{{ r.name|safe }}</a>
|
||||
{% endfor %}
|
||||
</div>
|
||||
</div>
|
||||
@ -168,7 +168,7 @@
|
||||
<div id="reaction-scenario" class="panel-collapse collapse in">
|
||||
<div class="panel-body list-group-item">
|
||||
{% for s in reaction.scenarios.all %}
|
||||
<a class="list-group-item" href="{{ s.url }}">{{ s.name }} <i>({{ s.package.name }})</i></a>
|
||||
<a class="list-group-item" href="{{ s.url }}">{{ s.name|safe }} <i>({{ s.package.name|safe }})</i></a>
|
||||
{% endfor %}
|
||||
</div>
|
||||
</div>
|
||||
|
||||
@ -10,7 +10,7 @@
|
||||
<div class="panel-group" id="scenario-detail">
|
||||
<div class="panel panel-default">
|
||||
<div class="panel-heading" id="headingPanel" style="font-size:2rem;height: 46px">
|
||||
{{ scenario.name }}
|
||||
{{ scenario.name|safe }}
|
||||
<div id="actionsButton"
|
||||
style="float: right;font-weight: normal;font-size: medium;position: relative; top: 50%; transform: translateY(-50%);z-index:100;display: none;"
|
||||
class="dropdown"><a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button"
|
||||
@ -30,7 +30,7 @@
|
||||
<div class="panel panel-default">
|
||||
<div class="panel-heading">Description</div>
|
||||
<div class="panel-body">
|
||||
{{ scenario.description }}
|
||||
{{ scenario.description|safe }}
|
||||
<br>
|
||||
{{ scenario.scenario_type }}
|
||||
<br>
|
||||
|
||||
@ -13,7 +13,7 @@
|
||||
<div class="panel-group" id="rule-detail">
|
||||
<div class="panel panel-default">
|
||||
<div class="panel-heading" id="headingPanel" style="font-size:2rem;height: 46px">
|
||||
{{ rule.name }}
|
||||
{{ rule.name|safe }}
|
||||
<div id="actionsButton"
|
||||
style="float: right;font-weight: normal;font-size: medium;position: relative; top: 50%; transform: translateY(-50%);z-index:100;display: none;"
|
||||
class="dropdown"><a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button"
|
||||
@ -29,7 +29,7 @@
|
||||
</div>
|
||||
<div class="panel-body">
|
||||
<p>
|
||||
{{ rule.description }}
|
||||
{{ rule.description|safe }}
|
||||
</p>
|
||||
</div>
|
||||
|
||||
@ -145,7 +145,7 @@
|
||||
<div id="rule-composite-rule" class="panel-collapse collapse in">
|
||||
<div class="panel-body list-group-item">
|
||||
{% for cr in rule.parallelrule_set.all %}
|
||||
<a class="list-group-item" href="{{ cr.url }}">{{ cr.name }}</a>
|
||||
<a class="list-group-item" href="{{ cr.url }}">{{ cr.name|safe }}</a>
|
||||
{% endfor %}
|
||||
</div>
|
||||
</div>
|
||||
@ -162,7 +162,7 @@
|
||||
<div id="rule-scenario" class="panel-collapse collapse in">
|
||||
<div class="panel-body list-group-item">
|
||||
{% for s in rule.scenarios.all %}
|
||||
<a class="list-group-item" href="{{ s.url }}">{{ s.name }}</a>
|
||||
<a class="list-group-item" href="{{ s.url }}">{{ s.name|safe }}</a>
|
||||
{% endfor %}
|
||||
</div>
|
||||
</div>
|
||||
@ -179,7 +179,7 @@
|
||||
<div id="rule-reaction" class="panel-collapse collapse">
|
||||
<div class="panel-body list-group-item">
|
||||
{% for r in rule.related_reactions %}
|
||||
<a class="list-group-item" href="{{ r.url }}">{{ r.name }}</a>
|
||||
<a class="list-group-item" href="{{ r.url }}">{{ r.name|safe }}</a>
|
||||
{% endfor %}
|
||||
</div>
|
||||
</div>
|
||||
@ -196,7 +196,7 @@
|
||||
<div id="rule-pathway" class="panel-collapse collapse">
|
||||
<div class="panel-body list-group-item">
|
||||
{% for r in rule.related_pathways %}
|
||||
<a class="list-group-item" href="{{ r.url }}">{{ r.name }}</a>
|
||||
<a class="list-group-item" href="{{ r.url }}">{{ r.name|safe }}</a>
|
||||
{% endfor %}
|
||||
</div>
|
||||
</div>
|
||||
|
||||
@ -41,7 +41,7 @@
|
||||
<div id="default-package" class="panel-collapse collapse in">
|
||||
<div class="panel-body list-group-item">
|
||||
<li class="list-group-item">
|
||||
<a href="{{ user.default_package.url }}"> {{ user.default_package.name }}</a>
|
||||
<a href="{{ user.default_package.url }}"> {{ user.default_package.name|safe }}</a>
|
||||
</li>
|
||||
</div>
|
||||
</div>
|
||||
@ -58,7 +58,7 @@
|
||||
<div class="panel-body list-group-item">
|
||||
{% for g in meta.available_groups %}
|
||||
<li class="list-group-item">
|
||||
<a href="{{ g.url }}"> {{ g.name }}</a>
|
||||
<a href="{{ g.url }}"> {{ g.name|safe }}</a>
|
||||
</li>
|
||||
{% endfor %}
|
||||
</div>
|
||||
@ -90,7 +90,7 @@
|
||||
<td colspan="2">
|
||||
<li class="list-group-item">
|
||||
<a href="{{user.default_setting.model.url}}">
|
||||
{{ user.default_setting.model.name }}
|
||||
{{ user.default_setting.model.name|safe }}
|
||||
</a>
|
||||
</li>
|
||||
</td>
|
||||
@ -123,7 +123,7 @@
|
||||
{% for p in user.default_setting.rule_packages.all %}
|
||||
<li class="list-group-item">
|
||||
<a href="{{p.url}}">
|
||||
{{ p.name }}
|
||||
{{ p.name|safe }}
|
||||
</a>
|
||||
</li>
|
||||
{% endfor %}
|
||||
|
||||
@ -18,7 +18,7 @@
|
||||
</head>
|
||||
<body>
|
||||
<p></p>
|
||||
{{ pathway.name }}
|
||||
{{ pathway.name|safe }}
|
||||
<div id="viz">
|
||||
<svg width="2000" height="2000"> <!-- Sehr großes SVG für Zoom -->
|
||||
<defs>
|
||||
|
||||
@ -11,13 +11,13 @@
|
||||
<option disabled>Reviewed Packages</option>
|
||||
{% endif %}
|
||||
{% for obj in reviewed_objects %}
|
||||
<option value="{{ obj.url }}" selected>{{ obj.name }}</option>
|
||||
<option value="{{ obj.url }}" selected>{{ obj.name|safe }}</option>
|
||||
{% endfor %}
|
||||
{% if unreviewed_objects %}
|
||||
<option disabled>Unreviewed Packages</option>
|
||||
{% endif %}
|
||||
{% for obj in unreviewed_objects %}
|
||||
<option value="{{ obj.url }}">{{ obj.name }}</option>
|
||||
<option value="{{ obj.url }}">{{ obj.name|safe }}</option>
|
||||
{% endfor %}
|
||||
</select>
|
||||
</div>
|
||||
|
||||
@ -1,8 +1,10 @@
|
||||
import os.path
|
||||
from tempfile import TemporaryDirectory
|
||||
from django.test import TestCase
|
||||
|
||||
from epdb.logic import PackageManager
|
||||
from epdb.models import Reaction, Compound, User, Rule
|
||||
from utilities.ml import Dataset
|
||||
from epdb.models import Reaction, Compound, User, Rule, Package
|
||||
from utilities.chem import FormatConverter
|
||||
from utilities.ml import RuleBasedDataset, EnviFormerDataset
|
||||
|
||||
|
||||
class DatasetTest(TestCase):
|
||||
@ -41,12 +43,108 @@ class DatasetTest(TestCase):
|
||||
super(DatasetTest, cls).setUpClass()
|
||||
cls.user = User.objects.get(username="anonymous")
|
||||
cls.package = PackageManager.create_package(cls.user, "Anon Test Package", "No Desc")
|
||||
cls.BBD_SUBSET = Package.objects.get(name="Fixtures")
|
||||
|
||||
def test_smoke(self):
|
||||
def test_generate_dataset(self):
|
||||
"""Test generating dataset does not crash"""
|
||||
self.generate_rule_dataset()
|
||||
|
||||
def test_indexing(self):
|
||||
"""Test indexing a few different ways to check for crashes"""
|
||||
ds, reactions, rules = self.generate_rule_dataset()
|
||||
print(ds[5])
|
||||
print(ds[2, 5])
|
||||
print(ds[3:6, 2:8])
|
||||
print(ds[:2, "structure_id"])
|
||||
|
||||
def test_add_rows(self):
|
||||
"""Test adding one row and adding multiple rows"""
|
||||
ds, reactions, rules = self.generate_rule_dataset()
|
||||
ds.add_row(list(ds.df.row(1)))
|
||||
ds.add_rows([list(ds.df.row(i)) for i in range(5)])
|
||||
|
||||
def test_times_triggered(self):
|
||||
"""Check getting times triggered for a rule id"""
|
||||
ds, reactions, rules = self.generate_rule_dataset()
|
||||
print(ds.times_triggered(rules[0].uuid))
|
||||
|
||||
def test_block_indices(self):
|
||||
"""Test the usages of _block_indices"""
|
||||
ds, reactions, rules = self.generate_rule_dataset()
|
||||
print(ds.struct_features())
|
||||
print(ds.triggered())
|
||||
print(ds.observed())
|
||||
|
||||
def test_structure_id(self):
|
||||
"""Check getting a structure id from row index"""
|
||||
ds, reactions, rules = self.generate_rule_dataset()
|
||||
print(ds.structure_id(0))
|
||||
|
||||
def test_x(self):
|
||||
"""Test getting X portion of the dataframe"""
|
||||
ds, reactions, rules = self.generate_rule_dataset()
|
||||
print(ds.X().df.head())
|
||||
|
||||
def test_trig(self):
|
||||
"""Test getting the triggered portion of the dataframe"""
|
||||
ds, reactions, rules = self.generate_rule_dataset()
|
||||
print(ds.trig().df.head())
|
||||
|
||||
def test_y(self):
|
||||
"""Test getting the Y portion of the dataframe"""
|
||||
ds, reactions, rules = self.generate_rule_dataset()
|
||||
print(ds.y().df.head())
|
||||
|
||||
def test_classification_dataset(self):
|
||||
"""Test making the classification dataset"""
|
||||
ds, reactions, rules = self.generate_rule_dataset()
|
||||
compounds = [c.default_structure for c in Compound.objects.filter(package=self.BBD_SUBSET)]
|
||||
class_ds, products = ds.classification_dataset(compounds, rules)
|
||||
print(class_ds.df.head(5))
|
||||
print(products[:5])
|
||||
|
||||
def test_extra_features(self):
|
||||
reactions = [r for r in Reaction.objects.filter(package=self.BBD_SUBSET)]
|
||||
applicable_rules = [r for r in Rule.objects.filter(package=self.BBD_SUBSET)]
|
||||
ds = RuleBasedDataset.generate_dataset(reactions, applicable_rules, feat_funcs=[FormatConverter.maccs, FormatConverter.morgan])
|
||||
print(ds.shape)
|
||||
|
||||
def test_to_arff(self):
|
||||
"""Test exporting the arff version of the dataset"""
|
||||
ds, reactions, rules = self.generate_rule_dataset()
|
||||
ds.to_arff("dataset_arff_test.arff")
|
||||
|
||||
def test_save_load(self):
|
||||
"""Test saving and loading dataset"""
|
||||
with TemporaryDirectory() as tmpdir:
|
||||
ds, reactions, rules = self.generate_rule_dataset()
|
||||
ds.save(os.path.join(tmpdir, "save_dataset.pkl"))
|
||||
ds_loaded = RuleBasedDataset.load(os.path.join(tmpdir, "save_dataset.pkl"))
|
||||
self.assertTrue(ds.df.equals(ds_loaded.df))
|
||||
|
||||
def test_dataset_example(self):
|
||||
"""Test with a concrete example checking dataset size"""
|
||||
reactions = [r for r in Reaction.objects.filter(package=self.package)]
|
||||
applicable_rules = [self.rule1]
|
||||
|
||||
ds = Dataset.generate_dataset(reactions, applicable_rules)
|
||||
ds = RuleBasedDataset.generate_dataset(reactions, applicable_rules)
|
||||
|
||||
self.assertEqual(len(ds.y()), 1)
|
||||
self.assertEqual(sum(ds.y()[0]), 1)
|
||||
self.assertEqual(ds.y().df.item(), 1)
|
||||
|
||||
def test_enviformer_dataset(self):
|
||||
ds, reactions = self.generate_enviformer_dataset()
|
||||
print(ds.X().head())
|
||||
print(ds.y().head())
|
||||
|
||||
def generate_rule_dataset(self):
|
||||
"""Generate a RuleBasedDataset from test package data"""
|
||||
reactions = [r for r in Reaction.objects.filter(package=self.BBD_SUBSET)]
|
||||
applicable_rules = [r for r in Rule.objects.filter(package=self.BBD_SUBSET)]
|
||||
ds = RuleBasedDataset.generate_dataset(reactions, applicable_rules)
|
||||
return ds, reactions, applicable_rules
|
||||
|
||||
def generate_enviformer_dataset(self):
|
||||
reactions = [r for r in Reaction.objects.filter(package=self.BBD_SUBSET)]
|
||||
ds = EnviFormerDataset.generate_dataset(reactions)
|
||||
return ds, reactions
|
||||
|
||||
@ -42,13 +42,11 @@ class EnviFormerTest(TestCase):
|
||||
threshold = float(0.5)
|
||||
data_package_objs = [self.BBD_SUBSET]
|
||||
eval_packages_objs = [self.BBD_SUBSET]
|
||||
mod = EnviFormer.create(
|
||||
self.package, data_package_objs, eval_packages_objs, threshold=threshold
|
||||
)
|
||||
mod = EnviFormer.create(self.package, data_package_objs, threshold=threshold)
|
||||
|
||||
mod.build_dataset()
|
||||
mod.build_model()
|
||||
mod.evaluate_model(True, eval_packages_objs)
|
||||
mod.evaluate_model(True, eval_packages_objs, n_splits=2)
|
||||
|
||||
mod.predict("CCN(CC)C(=O)C1=CC(=CC=C1)C")
|
||||
|
||||
@ -57,12 +55,9 @@ class EnviFormerTest(TestCase):
|
||||
with self.settings(MODEL_DIR=tmpdir):
|
||||
threshold = float(0.5)
|
||||
data_package_objs = [self.BBD_SUBSET]
|
||||
eval_packages_objs = [self.BBD_SUBSET]
|
||||
mods = []
|
||||
for _ in range(4):
|
||||
mod = EnviFormer.create(
|
||||
self.package, data_package_objs, eval_packages_objs, threshold=threshold
|
||||
)
|
||||
mod = EnviFormer.create(self.package, data_package_objs, threshold=threshold)
|
||||
mod.build_dataset()
|
||||
mod.build_model()
|
||||
mods.append(mod)
|
||||
@ -73,15 +68,11 @@ class EnviFormerTest(TestCase):
|
||||
|
||||
# Test pathway prediction
|
||||
times = [measure_predict(mods[1], self.BBD_SUBSET.pathways[0].pk) for _ in range(5)]
|
||||
print(
|
||||
f"First pathway prediction took {times[0]} seconds, subsequent ones took {times[1:]}"
|
||||
)
|
||||
print(f"First pathway prediction took {times[0]} seconds, subsequent ones took {times[1:]}")
|
||||
|
||||
# Test eviction by performing three prediction with every model, twice.
|
||||
times = defaultdict(list)
|
||||
for _ in range(
|
||||
2
|
||||
): # Eviction should cause the second iteration here to have to reload the models
|
||||
for _ in range(2): # Eviction should cause the second iteration here to have to reload the models
|
||||
for mod in mods:
|
||||
for _ in range(3):
|
||||
times[mod.pk].append(measure_predict(mod))
|
||||
|
||||
@ -4,7 +4,7 @@ import numpy as np
|
||||
from django.test import TestCase
|
||||
|
||||
from epdb.logic import PackageManager
|
||||
from epdb.models import User, MLRelativeReasoning, Package
|
||||
from epdb.models import User, MLRelativeReasoning, Package, RuleBasedRelativeReasoning
|
||||
|
||||
|
||||
class ModelTest(TestCase):
|
||||
@ -17,7 +17,7 @@ class ModelTest(TestCase):
|
||||
cls.package = PackageManager.create_package(cls.user, "Anon Test Package", "No Desc")
|
||||
cls.BBD_SUBSET = Package.objects.get(name="Fixtures")
|
||||
|
||||
def test_smoke(self):
|
||||
def test_mlrr(self):
|
||||
with TemporaryDirectory() as tmpdir:
|
||||
with self.settings(MODEL_DIR=tmpdir):
|
||||
threshold = float(0.5)
|
||||
@ -35,21 +35,9 @@ class ModelTest(TestCase):
|
||||
description="Created MLRelativeReasoning in Testcase",
|
||||
)
|
||||
|
||||
# mod = RuleBasedRelativeReasoning.create(
|
||||
# self.package,
|
||||
# rule_package_objs,
|
||||
# data_package_objs,
|
||||
# eval_packages_objs,
|
||||
# threshold=threshold,
|
||||
# min_count=5,
|
||||
# max_count=0,
|
||||
# name='ECC - BBD - 0.5',
|
||||
# description='Created MLRelativeReasoning in Testcase',
|
||||
# )
|
||||
|
||||
mod.build_dataset()
|
||||
mod.build_model()
|
||||
mod.evaluate_model(True, eval_packages_objs)
|
||||
mod.evaluate_model(True, eval_packages_objs, n_splits=2)
|
||||
|
||||
results = mod.predict("CCN(CC)C(=O)C1=CC(=CC=C1)C")
|
||||
|
||||
@ -70,3 +58,57 @@ class ModelTest(TestCase):
|
||||
|
||||
# from pprint import pprint
|
||||
# pprint(mod.eval_results)
|
||||
|
||||
def test_applicability(self):
|
||||
with TemporaryDirectory() as tmpdir:
|
||||
with self.settings(MODEL_DIR=tmpdir):
|
||||
threshold = float(0.5)
|
||||
|
||||
rule_package_objs = [self.BBD_SUBSET]
|
||||
data_package_objs = [self.BBD_SUBSET]
|
||||
eval_packages_objs = [self.BBD_SUBSET]
|
||||
|
||||
mod = MLRelativeReasoning.create(
|
||||
self.package,
|
||||
rule_package_objs,
|
||||
data_package_objs,
|
||||
threshold=threshold,
|
||||
name="ECC - BBD - 0.5",
|
||||
description="Created MLRelativeReasoning in Testcase",
|
||||
build_app_domain=True, # To test the applicability domain this must be True
|
||||
app_domain_num_neighbours=5,
|
||||
app_domain_local_compatibility_threshold=0.5,
|
||||
app_domain_reliability_threshold=0.5,
|
||||
)
|
||||
|
||||
mod.build_dataset()
|
||||
mod.build_model()
|
||||
mod.evaluate_model(True, eval_packages_objs, n_splits=2)
|
||||
|
||||
results = mod.predict("CCN(CC)C(=O)C1=CC(=CC=C1)C")
|
||||
|
||||
def test_rbrr(self):
|
||||
with TemporaryDirectory() as tmpdir:
|
||||
with self.settings(MODEL_DIR=tmpdir):
|
||||
threshold = float(0.5)
|
||||
|
||||
rule_package_objs = [self.BBD_SUBSET]
|
||||
data_package_objs = [self.BBD_SUBSET]
|
||||
eval_packages_objs = [self.BBD_SUBSET]
|
||||
|
||||
mod = RuleBasedRelativeReasoning.create(
|
||||
self.package,
|
||||
rule_package_objs,
|
||||
data_package_objs,
|
||||
threshold=threshold,
|
||||
min_count=5,
|
||||
max_count=0,
|
||||
name='ECC - BBD - 0.5',
|
||||
description='Created MLRelativeReasoning in Testcase',
|
||||
)
|
||||
|
||||
mod.build_dataset()
|
||||
mod.build_model()
|
||||
mod.evaluate_model(True, eval_packages_objs, n_splits=2)
|
||||
|
||||
results = mod.predict("CCN(CC)C(=O)C1=CC(=CC=C1)C")
|
||||
|
||||
@ -29,7 +29,7 @@ class RuleTest(TestCase):
|
||||
self.assertEqual(r.name, "bt0022-2833")
|
||||
self.assertEqual(
|
||||
r.description,
|
||||
"Dihalomethyl derivative + Halomethyl derivative > 1-Halo-1-methylalcohol derivative + 1-Methylalcohol derivative",
|
||||
"Dihalomethyl derivative + Halomethyl derivative > 1-Halo-1-methylalcohol derivative + 1-Methylalcohol derivative",
|
||||
)
|
||||
|
||||
def test_smirks_are_trimmed(self):
|
||||
|
||||
@ -2,13 +2,12 @@ import logging
|
||||
import re
|
||||
from abc import ABC
|
||||
from collections import defaultdict
|
||||
from typing import List, Optional, Dict, TYPE_CHECKING, Union
|
||||
from typing import List, Optional, Dict, TYPE_CHECKING
|
||||
|
||||
from indigo import Indigo, IndigoException, IndigoObject
|
||||
from indigo.renderer import IndigoRenderer
|
||||
from rdkit import Chem, rdBase
|
||||
from rdkit.Chem import MACCSkeys, Descriptors
|
||||
from rdkit.Chem import rdchem
|
||||
from rdkit.Chem import MACCSkeys, Descriptors, rdFingerprintGenerator
|
||||
from rdkit.Chem import rdChemReactions
|
||||
from rdkit.Chem.Draw import rdMolDraw2D
|
||||
from rdkit.Chem.MolStandardize import rdMolStandardize
|
||||
@ -91,15 +90,8 @@ class FormatConverter(object):
|
||||
return Chem.MolToSmiles(mol, canonical=canonical)
|
||||
|
||||
@staticmethod
|
||||
def InChIKey(mol_or_smiles: Union[rdchem.Mol | str]):
|
||||
if isinstance(mol_or_smiles, str):
|
||||
mol_or_smiles = mol_or_smiles.replace("~", "")
|
||||
mol_or_smiles = FormatConverter.from_smiles(mol_or_smiles)
|
||||
|
||||
if mol_or_smiles is None:
|
||||
return None
|
||||
|
||||
return Chem.MolToInchiKey(mol_or_smiles)
|
||||
def InChIKey(smiles):
|
||||
return Chem.MolToInchiKey(FormatConverter.from_smiles(smiles))
|
||||
|
||||
@staticmethod
|
||||
def InChI(smiles):
|
||||
@ -115,6 +107,13 @@ class FormatConverter(object):
|
||||
bitvec = MACCSkeys.GenMACCSKeys(mol)
|
||||
return bitvec.ToList()
|
||||
|
||||
@staticmethod
|
||||
def morgan(smiles, radius=3, fpSize=2048):
|
||||
finger_gen = rdFingerprintGenerator.GetMorganGenerator(radius=radius, fpSize=fpSize)
|
||||
mol = Chem.MolFromSmiles(smiles)
|
||||
fp = finger_gen.GetFingerprint(mol)
|
||||
return fp.ToList()
|
||||
|
||||
@staticmethod
|
||||
def get_functional_groups(smiles: str) -> List[str]:
|
||||
res = list()
|
||||
@ -256,6 +255,30 @@ class FormatConverter(object):
|
||||
except Exception:
|
||||
return False
|
||||
|
||||
@staticmethod
|
||||
def is_valid_smarts(smarts: str) -> bool:
|
||||
"""
|
||||
Checks whether a given string is a valid SMARTS pattern.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
smarts : str
|
||||
The SMARTS string to validate.
|
||||
|
||||
Returns
|
||||
-------
|
||||
bool
|
||||
True if the SMARTS string is valid, False otherwise.
|
||||
"""
|
||||
if not isinstance(smarts, str) or not smarts.strip():
|
||||
return False
|
||||
|
||||
try:
|
||||
mol = Chem.MolFromSmarts(smarts)
|
||||
return mol is not None
|
||||
except Exception:
|
||||
return False
|
||||
|
||||
@staticmethod
|
||||
def apply(
|
||||
smiles: str,
|
||||
@ -296,8 +319,7 @@ class FormatConverter(object):
|
||||
product = GetMolFrags(product, asMols=True)
|
||||
for p in product:
|
||||
p = FormatConverter.standardize(
|
||||
Chem.MolToSmiles(p).replace("~", ""),
|
||||
remove_stereo=remove_stereo,
|
||||
Chem.MolToSmiles(p), remove_stereo=remove_stereo
|
||||
)
|
||||
prods.append(p)
|
||||
|
||||
|
||||
@ -35,7 +35,6 @@ from epdb.models import (
|
||||
RuleBasedRelativeReasoning,
|
||||
Scenario,
|
||||
SequentialRule,
|
||||
Setting,
|
||||
SimpleAmbitRule,
|
||||
SimpleRDKitRule,
|
||||
SimpleRule,
|
||||
@ -1259,46 +1258,3 @@ class PathwayUtils:
|
||||
res[edge.url] = rule_chain
|
||||
|
||||
return res
|
||||
|
||||
def _find_intermediates(self, data_pathway, pred_pathway):
|
||||
pass
|
||||
|
||||
def engineer(self, setting: "Setting"):
|
||||
from epdb.logic import SPathway
|
||||
|
||||
# get a fresh copy
|
||||
pw = Pathway.objects.get(id=self.pathway.pk)
|
||||
|
||||
root_nodes = [n.default_node_label.smiles for n in pw.root_nodes]
|
||||
|
||||
if len(root_nodes) != 1:
|
||||
logger.warning(f"Pathway {pw.name} has {len(root_nodes)} root nodes")
|
||||
return
|
||||
|
||||
spw = SPathway(root_nodes[0], None, setting)
|
||||
|
||||
level = 0
|
||||
while not spw.done:
|
||||
spw.predict_step(from_depth=level)
|
||||
level += 1
|
||||
|
||||
# Generate Node / SMILES mapping
|
||||
node_mapping = {}
|
||||
from utilities.chem import FormatConverter
|
||||
|
||||
for node in pw.nodes:
|
||||
for snode in spw.smiles_to_node.values():
|
||||
data_smiles = node.default_node_label.smiles
|
||||
pred_smiles = snode.smiles
|
||||
|
||||
data_key = FormatConverter.InChIKey(data_smiles.replace("~", ""))
|
||||
pred_key = FormatConverter.InChIKey(pred_smiles.replace("~", ""))
|
||||
|
||||
if data_key == pred_key:
|
||||
node_mapping[snode] = node
|
||||
|
||||
print(node_mapping)
|
||||
|
||||
return spw
|
||||
|
||||
pass
|
||||
|
||||
550
utilities/ml.py
550
utilities/ml.py
@ -5,11 +5,14 @@ import logging
|
||||
from collections import defaultdict
|
||||
from datetime import datetime
|
||||
from pathlib import Path
|
||||
from typing import List, Dict, Set, Tuple, TYPE_CHECKING
|
||||
from typing import List, Dict, Set, Tuple, TYPE_CHECKING, Callable
|
||||
from abc import ABC, abstractmethod
|
||||
|
||||
import networkx as nx
|
||||
import numpy as np
|
||||
from envipy_plugins import Descriptor
|
||||
from numpy.random import default_rng
|
||||
import polars as pl
|
||||
from sklearn.base import BaseEstimator, ClassifierMixin
|
||||
from sklearn.decomposition import PCA
|
||||
from sklearn.dummy import DummyClassifier
|
||||
@ -26,70 +29,281 @@ if TYPE_CHECKING:
|
||||
from epdb.models import Rule, CompoundStructure, Reaction
|
||||
|
||||
|
||||
class Dataset:
|
||||
def __init__(
|
||||
self, columns: List[str], num_labels: int, data: List[List[str | int | float]] = None
|
||||
):
|
||||
self.columns: List[str] = columns
|
||||
self.num_labels: int = num_labels
|
||||
|
||||
if data is None:
|
||||
self.data: List[List[str | int | float]] = list()
|
||||
class Dataset(ABC):
|
||||
def __init__(self, columns: List[str] = None, data: List[List[str | int | float]] | pl.DataFrame = None):
|
||||
if isinstance(data, pl.DataFrame): # Allows for re-creation of self in cases like indexing with __getitem__
|
||||
self.df = data
|
||||
else:
|
||||
self.data = data
|
||||
# Build either an empty dataframe with columns or fill it with list of list data
|
||||
if data is not None and len(columns) != len(data[0]):
|
||||
raise ValueError(f"Header and Data are not aligned {len(columns)} columns vs. {len(data[0])} columns")
|
||||
if columns is None:
|
||||
raise ValueError("Columns can't be None if data is not already a DataFrame")
|
||||
self.df = pl.DataFrame(data=data, schema=columns, orient="row", infer_schema_length=None)
|
||||
|
||||
self.num_features: int = len(columns) - self.num_labels
|
||||
self._struct_features: Tuple[int, int] = self._block_indices("feature_")
|
||||
self._triggered: Tuple[int, int] = self._block_indices("trig_")
|
||||
self._observed: Tuple[int, int] = self._block_indices("obs_")
|
||||
def add_rows(self, rows: List[List[str | int | float]]):
|
||||
"""Add rows to the dataset. Extends the polars dataframe stored in self"""
|
||||
if len(self.columns) != len(rows[0]):
|
||||
raise ValueError(f"Header and Data are not aligned {len(self.columns)} columns vs. {len(rows[0])} columns")
|
||||
new_rows = pl.DataFrame(data=rows, schema=self.columns, orient="row", infer_schema_length=None)
|
||||
self.df.extend(new_rows)
|
||||
|
||||
def _block_indices(self, prefix) -> Tuple[int, int]:
|
||||
def add_row(self, row: List[str | int | float]):
|
||||
"""See add_rows"""
|
||||
self.add_rows([row])
|
||||
|
||||
def block_indices(self, prefix) -> List[int]:
|
||||
"""Find the indexes in column labels that has the prefix"""
|
||||
indices: List[int] = []
|
||||
for i, feature in enumerate(self.columns):
|
||||
if feature.startswith(prefix):
|
||||
indices.append(i)
|
||||
return indices
|
||||
|
||||
return min(indices), max(indices)
|
||||
@property
|
||||
def columns(self) -> List[str]:
|
||||
"""Use the polars dataframe columns"""
|
||||
return self.df.columns
|
||||
|
||||
def structure_id(self):
|
||||
return self.data[0][0]
|
||||
@property
|
||||
def shape(self):
|
||||
return self.df.shape
|
||||
|
||||
def add_row(self, row: List[str | int | float]):
|
||||
if len(self.columns) != len(row):
|
||||
raise ValueError(f"Header and Data are not aligned {len(self.columns)} vs. {len(row)}")
|
||||
self.data.append(row)
|
||||
@abstractmethod
|
||||
def X(self, **kwargs):
|
||||
pass
|
||||
|
||||
def times_triggered(self, rule_uuid) -> int:
|
||||
idx = self.columns.index(f"trig_{rule_uuid}")
|
||||
@abstractmethod
|
||||
def y(self, **kwargs):
|
||||
pass
|
||||
|
||||
times_triggered = 0
|
||||
for row in self.data:
|
||||
if row[idx] == 1:
|
||||
times_triggered += 1
|
||||
|
||||
return times_triggered
|
||||
|
||||
def struct_features(self) -> Tuple[int, int]:
|
||||
return self._struct_features
|
||||
|
||||
def triggered(self) -> Tuple[int, int]:
|
||||
return self._triggered
|
||||
|
||||
def observed(self) -> Tuple[int, int]:
|
||||
return self._observed
|
||||
|
||||
def at(self, position: int) -> Dataset:
|
||||
return Dataset(self.columns, self.num_labels, [self.data[position]])
|
||||
|
||||
def limit(self, limit: int) -> Dataset:
|
||||
return Dataset(self.columns, self.num_labels, self.data[:limit])
|
||||
@staticmethod
|
||||
@abstractmethod
|
||||
def generate_dataset(reactions, *args, **kwargs):
|
||||
pass
|
||||
|
||||
def __iter__(self):
|
||||
return (self.at(i) for i, _ in enumerate(self.data))
|
||||
"""Use polars iter_rows for iterating over the dataset"""
|
||||
return self.df.iter_rows()
|
||||
|
||||
def __getitem__(self, item):
|
||||
"""Item is passed to polars allowing for advanced indexing.
|
||||
See https://docs.pola.rs/api/python/stable/reference/dataframe/api/polars.DataFrame.__getitem__.html#polars.DataFrame.__getitem__"""
|
||||
res = self.df[item]
|
||||
if isinstance(res, pl.DataFrame): # If we get a dataframe back from indexing make new self with res dataframe
|
||||
return self.__class__(data=res)
|
||||
else: # If we don't get a dataframe back (likely base type, int, str, float etc.) return the item
|
||||
return res
|
||||
|
||||
def save(self, path: "Path | str"):
|
||||
import pickle
|
||||
|
||||
with open(path, "wb") as fh:
|
||||
pickle.dump(self, fh)
|
||||
|
||||
@staticmethod
|
||||
def load(path: "str | Path") -> "Dataset":
|
||||
import pickle
|
||||
|
||||
return pickle.load(open(path, "rb"))
|
||||
|
||||
def to_numpy(self):
|
||||
return self.df.to_numpy()
|
||||
|
||||
def __repr__(self):
|
||||
return (
|
||||
f"<{self.__class__.__name__} #rows={len(self.df)} #cols={len(self.columns)}>"
|
||||
)
|
||||
|
||||
def __len__(self):
|
||||
return len(self.df)
|
||||
|
||||
def iter_rows(self, named=False):
|
||||
return self.df.iter_rows(named=named)
|
||||
|
||||
def filter(self, *predicates, **constraints):
|
||||
return self.__class__(data=self.df.filter(*predicates, **constraints))
|
||||
|
||||
def select(self, *exprs, **named_exprs):
|
||||
return self.__class__(data=self.df.select(*exprs, **named_exprs))
|
||||
|
||||
def with_columns(self, *exprs, **name_exprs):
|
||||
return self.__class__(data=self.df.with_columns(*exprs, **name_exprs))
|
||||
|
||||
def sort(self, by, *more_by, descending=False, nulls_last=False, multithreaded=True, maintain_order=False):
|
||||
return self.__class__(data=self.df.sort(by, *more_by, descending=descending, nulls_last=nulls_last,
|
||||
multithreaded=multithreaded, maintain_order=maintain_order))
|
||||
|
||||
def item(self, row=None, column=None):
|
||||
return self.df.item(row, column)
|
||||
|
||||
def fill_nan(self, value):
|
||||
return self.__class__(data=self.df.fill_nan(value))
|
||||
|
||||
@property
|
||||
def height(self):
|
||||
return self.df.height
|
||||
|
||||
|
||||
class RuleBasedDataset(Dataset):
|
||||
def __init__(self, num_labels=None, columns=None, data=None):
|
||||
super().__init__(columns, data)
|
||||
# Calculating num_labels allows functions like getitem to be in the base Dataset as it unifies the init.
|
||||
self.num_labels: int = num_labels if num_labels else sum([1 for c in self.columns if "obs_" in c])
|
||||
# Pre-calculate the ids of columns for features/labels, useful later in X and y
|
||||
self._struct_features: List[int] = self.block_indices("feature_")
|
||||
self._triggered: List[int] = self.block_indices("trig_")
|
||||
self._observed: List[int] = self.block_indices("obs_")
|
||||
self.feature_cols: List[int] = self._struct_features + self._triggered
|
||||
self.num_features: int = len(self.feature_cols)
|
||||
self.has_probs = False
|
||||
|
||||
def times_triggered(self, rule_uuid) -> int:
|
||||
"""Count how many times a rule is triggered by the number of rows with one in the rules trig column"""
|
||||
return self.df.filter(pl.col(f"trig_{rule_uuid}") == 1).height
|
||||
|
||||
def struct_features(self) -> List[int]:
|
||||
return self._struct_features
|
||||
|
||||
def triggered(self) -> List[int]:
|
||||
return self._triggered
|
||||
|
||||
def observed(self) -> List[int]:
|
||||
return self._observed
|
||||
|
||||
def structure_id(self, index: int):
|
||||
"""Get the UUID of a compound"""
|
||||
return self.item(index, "structure_id")
|
||||
|
||||
def X(self, exclude_id_col=True, na_replacement=0):
|
||||
"""Get all the feature and trig columns"""
|
||||
_col_ids = self.feature_cols
|
||||
if not exclude_id_col:
|
||||
_col_ids = [0] + _col_ids
|
||||
res = self[:, _col_ids]
|
||||
if na_replacement is not None:
|
||||
res.df = res.df.fill_null(na_replacement)
|
||||
return res
|
||||
|
||||
def trig(self, na_replacement=0):
|
||||
"""Get all the trig columns"""
|
||||
res = self[:, self._triggered]
|
||||
if na_replacement is not None:
|
||||
res.df = res.df.fill_null(na_replacement)
|
||||
return res
|
||||
|
||||
def y(self, na_replacement=0):
|
||||
"""Get all the obs columns"""
|
||||
res = self[:, self._observed]
|
||||
if na_replacement is not None:
|
||||
res.df = res.df.fill_null(na_replacement)
|
||||
return res
|
||||
|
||||
@staticmethod
|
||||
def generate_dataset(reactions, applicable_rules, educts_only=True, feat_funcs: List["Callable | Descriptor"]=None):
|
||||
if feat_funcs is None:
|
||||
feat_funcs = [FormatConverter.maccs]
|
||||
_structures = set() # Get all the structures
|
||||
for r in reactions:
|
||||
_structures.update(r.educts.all())
|
||||
if not educts_only:
|
||||
_structures.update(r.products.all())
|
||||
|
||||
compounds = sorted(_structures, key=lambda x: x.url)
|
||||
triggered: Dict[str, Set[str]] = defaultdict(set)
|
||||
observed: Set[str] = set()
|
||||
|
||||
# Apply rules on collected compounds and store tps
|
||||
for i, comp in enumerate(compounds):
|
||||
logger.debug(f"{i + 1}/{len(compounds)}...")
|
||||
|
||||
for rule in applicable_rules:
|
||||
product_sets = rule.apply(comp.smiles)
|
||||
if len(product_sets) == 0:
|
||||
continue
|
||||
|
||||
key = f"{rule.uuid} + {comp.uuid}"
|
||||
if key in triggered:
|
||||
logger.info(f"{key} already present. Duplicate reaction?")
|
||||
|
||||
for prod_set in product_sets:
|
||||
for smi in prod_set:
|
||||
try:
|
||||
smi = FormatConverter.standardize(smi, remove_stereo=True)
|
||||
except Exception:
|
||||
logger.debug(f"Standardizing SMILES failed for {smi}")
|
||||
triggered[key].add(smi)
|
||||
|
||||
for i, r in enumerate(reactions):
|
||||
logger.debug(f"{i + 1}/{len(reactions)}...")
|
||||
|
||||
if len(r.educts.all()) != 1:
|
||||
logger.debug(f"Skipping {r.url} as it has {len(r.educts.all())} substrates!")
|
||||
continue
|
||||
|
||||
for comp in r.educts.all():
|
||||
for rule in applicable_rules:
|
||||
key = f"{rule.uuid} + {comp.uuid}"
|
||||
if key not in triggered:
|
||||
continue
|
||||
|
||||
# standardize products from reactions for comparison
|
||||
standardized_products = []
|
||||
for cs in r.products.all():
|
||||
smi = cs.smiles
|
||||
try:
|
||||
smi = FormatConverter.standardize(smi, remove_stereo=True)
|
||||
except Exception as e:
|
||||
logger.debug(f"Standardizing SMILES failed for {smi}")
|
||||
standardized_products.append(smi)
|
||||
if len(set(standardized_products).difference(triggered[key])) == 0:
|
||||
observed.add(key)
|
||||
feat_columns = []
|
||||
for feat_func in feat_funcs:
|
||||
if isinstance(feat_func, Descriptor):
|
||||
feats = feat_func.get_molecule_descriptors(compounds[0].smiles)
|
||||
else:
|
||||
feats = feat_func(compounds[0].smiles)
|
||||
start_i = len(feat_columns)
|
||||
feat_columns.extend([f"feature_{start_i + i}" for i, _ in enumerate(feats)])
|
||||
ds_columns = (["structure_id"] +
|
||||
feat_columns +
|
||||
[f"trig_{r.uuid}" for r in applicable_rules] +
|
||||
[f"obs_{r.uuid}" for r in applicable_rules])
|
||||
rows = []
|
||||
|
||||
for i, comp in enumerate(compounds):
|
||||
# Features
|
||||
feats = []
|
||||
for feat_func in feat_funcs:
|
||||
if isinstance(feat_func, Descriptor):
|
||||
feat = feat_func.get_molecule_descriptors(comp.smiles)
|
||||
else:
|
||||
feat = feat_func(comp.smiles)
|
||||
feats.extend(feat)
|
||||
trig = []
|
||||
obs = []
|
||||
for rule in applicable_rules:
|
||||
key = f"{rule.uuid} + {comp.uuid}"
|
||||
# Check triggered
|
||||
if key in triggered:
|
||||
trig.append(1)
|
||||
else:
|
||||
trig.append(0)
|
||||
# Check obs
|
||||
if key in observed:
|
||||
obs.append(1)
|
||||
elif key not in triggered:
|
||||
obs.append(None)
|
||||
else:
|
||||
obs.append(0)
|
||||
rows.append([str(comp.uuid)] + feats + trig + obs)
|
||||
ds = RuleBasedDataset(len(applicable_rules), ds_columns, data=rows)
|
||||
return ds
|
||||
|
||||
def classification_dataset(
|
||||
self, structures: List[str | "CompoundStructure"], applicable_rules: List["Rule"]
|
||||
) -> Tuple[Dataset, List[List[PredictionResult]]]:
|
||||
) -> Tuple[RuleBasedDataset, List[List[PredictionResult]]]:
|
||||
classify_data = []
|
||||
classify_products = []
|
||||
for struct in structures:
|
||||
@ -113,186 +327,18 @@ class Dataset:
|
||||
else:
|
||||
trig.append(0)
|
||||
prods.append([])
|
||||
|
||||
classify_data.append([struct_id] + features + trig + ([-1] * len(trig)))
|
||||
new_row = [struct_id] + features + trig + ([-1] * len(trig))
|
||||
if self.has_probs:
|
||||
new_row += [-1] * len(trig)
|
||||
classify_data.append(new_row)
|
||||
classify_products.append(prods)
|
||||
ds = RuleBasedDataset(len(applicable_rules), self.columns, data=classify_data)
|
||||
return ds, classify_products
|
||||
|
||||
return Dataset(
|
||||
columns=self.columns, num_labels=self.num_labels, data=classify_data
|
||||
), classify_products
|
||||
|
||||
@staticmethod
|
||||
def generate_dataset(
|
||||
reactions: List["Reaction"], applicable_rules: List["Rule"], educts_only: bool = True
|
||||
) -> Dataset:
|
||||
_structures = set()
|
||||
|
||||
for r in reactions:
|
||||
for e in r.educts.all():
|
||||
_structures.add(e)
|
||||
|
||||
if not educts_only:
|
||||
for e in r.products:
|
||||
_structures.add(e)
|
||||
|
||||
compounds = sorted(_structures, key=lambda x: x.url)
|
||||
|
||||
triggered: Dict[str, Set[str]] = defaultdict(set)
|
||||
observed: Set[str] = set()
|
||||
|
||||
# Apply rules on collected compounds and store tps
|
||||
for i, comp in enumerate(compounds):
|
||||
logger.debug(f"{i + 1}/{len(compounds)}...")
|
||||
|
||||
for rule in applicable_rules:
|
||||
product_sets = rule.apply(comp.smiles)
|
||||
|
||||
if len(product_sets) == 0:
|
||||
continue
|
||||
|
||||
key = f"{rule.uuid} + {comp.uuid}"
|
||||
|
||||
if key in triggered:
|
||||
logger.info(f"{key} already present. Duplicate reaction?")
|
||||
|
||||
for prod_set in product_sets:
|
||||
for smi in prod_set:
|
||||
try:
|
||||
smi = FormatConverter.standardize(smi, remove_stereo=True)
|
||||
except Exception:
|
||||
# :shrug:
|
||||
logger.debug(f"Standardizing SMILES failed for {smi}")
|
||||
pass
|
||||
|
||||
triggered[key].add(smi)
|
||||
|
||||
for i, r in enumerate(reactions):
|
||||
logger.debug(f"{i + 1}/{len(reactions)}...")
|
||||
|
||||
if len(r.educts.all()) != 1:
|
||||
logger.debug(f"Skipping {r.url} as it has {len(r.educts.all())} substrates!")
|
||||
continue
|
||||
|
||||
for comp in r.educts.all():
|
||||
for rule in applicable_rules:
|
||||
key = f"{rule.uuid} + {comp.uuid}"
|
||||
|
||||
if key not in triggered:
|
||||
continue
|
||||
|
||||
# standardize products from reactions for comparison
|
||||
standardized_products = []
|
||||
for cs in r.products.all():
|
||||
smi = cs.smiles
|
||||
|
||||
try:
|
||||
smi = FormatConverter.standardize(smi, remove_stereo=True)
|
||||
except Exception as e:
|
||||
# :shrug:
|
||||
logger.debug(f"Standardizing SMILES failed for {smi}")
|
||||
pass
|
||||
|
||||
standardized_products.append(smi)
|
||||
|
||||
if len(set(standardized_products).difference(triggered[key])) == 0:
|
||||
observed.add(key)
|
||||
else:
|
||||
pass
|
||||
|
||||
ds = None
|
||||
|
||||
for i, comp in enumerate(compounds):
|
||||
# Features
|
||||
feat = FormatConverter.maccs(comp.smiles)
|
||||
trig = []
|
||||
obs = []
|
||||
|
||||
for rule in applicable_rules:
|
||||
key = f"{rule.uuid} + {comp.uuid}"
|
||||
|
||||
# Check triggered
|
||||
if key in triggered:
|
||||
trig.append(1)
|
||||
else:
|
||||
trig.append(0)
|
||||
|
||||
# Check obs
|
||||
if key in observed:
|
||||
obs.append(1)
|
||||
elif key not in triggered:
|
||||
obs.append(None)
|
||||
else:
|
||||
obs.append(0)
|
||||
|
||||
if ds is None:
|
||||
header = (
|
||||
["structure_id"]
|
||||
+ [f"feature_{i}" for i, _ in enumerate(feat)]
|
||||
+ [f"trig_{r.uuid}" for r in applicable_rules]
|
||||
+ [f"obs_{r.uuid}" for r in applicable_rules]
|
||||
)
|
||||
ds = Dataset(header, len(applicable_rules))
|
||||
|
||||
ds.add_row([str(comp.uuid)] + feat + trig + obs)
|
||||
|
||||
return ds
|
||||
|
||||
def X(self, exclude_id_col=True, na_replacement=0):
|
||||
res = self.__getitem__(
|
||||
(slice(None), slice(1 if exclude_id_col else 0, len(self.columns) - self.num_labels))
|
||||
)
|
||||
if na_replacement is not None:
|
||||
res = [[x if x is not None else na_replacement for x in row] for row in res]
|
||||
return res
|
||||
|
||||
def trig(self, na_replacement=0):
|
||||
res = self.__getitem__((slice(None), slice(self._triggered[0], self._triggered[1])))
|
||||
if na_replacement is not None:
|
||||
res = [[x if x is not None else na_replacement for x in row] for row in res]
|
||||
return res
|
||||
|
||||
def y(self, na_replacement=0):
|
||||
res = self.__getitem__((slice(None), slice(len(self.columns) - self.num_labels, None)))
|
||||
if na_replacement is not None:
|
||||
res = [[x if x is not None else na_replacement for x in row] for row in res]
|
||||
return res
|
||||
|
||||
def __getitem__(self, key):
|
||||
if not isinstance(key, tuple):
|
||||
raise TypeError("Dataset must be indexed with dataset[rows, columns]")
|
||||
|
||||
row_key, col_key = key
|
||||
|
||||
# Normalize rows
|
||||
if isinstance(row_key, int):
|
||||
rows = [self.data[row_key]]
|
||||
else:
|
||||
rows = self.data[row_key]
|
||||
|
||||
# Normalize columns
|
||||
if isinstance(col_key, int):
|
||||
res = [row[col_key] for row in rows]
|
||||
else:
|
||||
res = [
|
||||
[row[i] for i in range(*col_key.indices(len(row)))]
|
||||
if isinstance(col_key, slice)
|
||||
else [row[i] for i in col_key]
|
||||
for row in rows
|
||||
]
|
||||
|
||||
return res
|
||||
|
||||
def save(self, path: "Path"):
|
||||
import pickle
|
||||
|
||||
with open(path, "wb") as fh:
|
||||
pickle.dump(self, fh)
|
||||
|
||||
@staticmethod
|
||||
def load(path: "Path") -> "Dataset":
|
||||
import pickle
|
||||
|
||||
return pickle.load(open(path, "rb"))
|
||||
def add_probs(self, probs):
|
||||
col_names = [f"prob_{self.columns[r_id].split('_')[-1]}" for r_id in self._observed]
|
||||
self.df = self.df.with_columns(*[pl.Series(name, probs[:, j]) for j, name in enumerate(col_names)])
|
||||
self.has_probs = True
|
||||
|
||||
def to_arff(self, path: "Path"):
|
||||
arff = f"@relation 'enviPy-dataset: -C {self.num_labels}'\n"
|
||||
@ -304,7 +350,7 @@ class Dataset:
|
||||
arff += f"@attribute {c} {{0,1}}\n"
|
||||
|
||||
arff += "\n@data\n"
|
||||
for d in self.data:
|
||||
for d in self:
|
||||
ys = ",".join([str(v if v is not None else "?") for v in d[-self.num_labels :]])
|
||||
xs = ",".join([str(v if v is not None else "?") for v in d[: self.num_features]])
|
||||
arff += f"{ys},{xs}\n"
|
||||
@ -313,10 +359,40 @@ class Dataset:
|
||||
fh.write(arff)
|
||||
fh.flush()
|
||||
|
||||
def __repr__(self):
|
||||
return (
|
||||
f"<Dataset #rows={len(self.data)} #cols={len(self.columns)} #labels={self.num_labels}>"
|
||||
)
|
||||
|
||||
class EnviFormerDataset(Dataset):
|
||||
def __init__(self, columns=None, data=None):
|
||||
super().__init__(columns, data)
|
||||
|
||||
def X(self):
|
||||
"""Return the educts"""
|
||||
return self["educts"]
|
||||
|
||||
def y(self):
|
||||
"""Return the products"""
|
||||
return self["products"]
|
||||
|
||||
@staticmethod
|
||||
def generate_dataset(reactions, *args, **kwargs):
|
||||
# Standardise reactions for the training data
|
||||
stereo = kwargs.get("stereo", False)
|
||||
rows = []
|
||||
for reaction in reactions:
|
||||
e = ".".join(
|
||||
[
|
||||
FormatConverter.standardize(smile.smiles, remove_stereo=not stereo)
|
||||
for smile in reaction.educts.all()
|
||||
]
|
||||
)
|
||||
p = ".".join(
|
||||
[
|
||||
FormatConverter.standardize(smile.smiles, remove_stereo=not stereo)
|
||||
for smile in reaction.products.all()
|
||||
]
|
||||
)
|
||||
rows.append([e, p])
|
||||
ds = EnviFormerDataset(["educts", "products"], rows)
|
||||
return ds
|
||||
|
||||
|
||||
class SparseLabelECC(BaseEstimator, ClassifierMixin):
|
||||
@ -498,7 +574,7 @@ class EnsembleClassifierChain:
|
||||
self.classifiers = []
|
||||
|
||||
if self.num_labels is None:
|
||||
self.num_labels = len(Y[0])
|
||||
self.num_labels = Y.shape[1]
|
||||
|
||||
for p in range(self.num_chains):
|
||||
logger.debug(f"{datetime.now()} fitting {p + 1}/{self.num_chains}")
|
||||
@ -529,7 +605,7 @@ class RelativeReasoning:
|
||||
|
||||
def fit(self, X, Y):
|
||||
n_instances = len(Y)
|
||||
n_attributes = len(Y[0])
|
||||
n_attributes = Y.shape[1]
|
||||
|
||||
for i in range(n_attributes):
|
||||
for j in range(n_attributes):
|
||||
@ -541,8 +617,8 @@ class RelativeReasoning:
|
||||
countboth = 0
|
||||
|
||||
for k in range(n_instances):
|
||||
vi = Y[k][i]
|
||||
vj = Y[k][j]
|
||||
vi = Y[k, i]
|
||||
vj = Y[k, j]
|
||||
|
||||
if vi is None or vj is None:
|
||||
continue
|
||||
@ -598,7 +674,7 @@ class ApplicabilityDomainPCA(PCA):
|
||||
self.min_vals = None
|
||||
self.max_vals = None
|
||||
|
||||
def build(self, train_dataset: "Dataset"):
|
||||
def build(self, train_dataset: "RuleBasedDataset"):
|
||||
# transform
|
||||
X_scaled = self.scaler.fit_transform(train_dataset.X())
|
||||
# fit pca
|
||||
@ -612,7 +688,7 @@ class ApplicabilityDomainPCA(PCA):
|
||||
instances_pca = self.transform(instances_scaled)
|
||||
return instances_pca
|
||||
|
||||
def is_applicable(self, classify_instances: "Dataset"):
|
||||
def is_applicable(self, classify_instances: "RuleBasedDataset"):
|
||||
instances_pca = self.__transform(classify_instances.X())
|
||||
|
||||
is_applicable = []
|
||||
|
||||
213
uv.lock
generated
213
uv.lock
generated
@ -1,6 +1,10 @@
|
||||
version = 1
|
||||
revision = 3
|
||||
revision = 2
|
||||
requires-python = ">=3.12"
|
||||
resolution-markers = [
|
||||
"sys_platform == 'linux' or sys_platform == 'win32'",
|
||||
"sys_platform != 'linux' and sys_platform != 'win32'",
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "aiohappyeyeballs"
|
||||
@ -176,6 +180,19 @@ wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/c9/af/0dcccc7fdcdf170f9a1585e5e96b6fb0ba1749ef6be8c89a6202284759bd/celery-5.5.3-py3-none-any.whl", hash = "sha256:0b5761a07057acee94694464ca482416b959568904c9dfa41ce8413a7d65d525", size = 438775, upload-time = "2025-06-01T11:08:09.94Z" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "celery-stubs"
|
||||
version = "0.1.3"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
dependencies = [
|
||||
{ name = "mypy" },
|
||||
{ name = "typing-extensions" },
|
||||
]
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/98/14/b853ada8706a3a301396566b6dd405d1cbb24bff756236a12a01dbe766a4/celery-stubs-0.1.3.tar.gz", hash = "sha256:0fb5345820f8a2bd14e6ffcbef2d10181e12e40f8369f551d7acc99d8d514919", size = 46583, upload-time = "2023-02-10T02:20:11.837Z" }
|
||||
wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/1c/7a/4ab2347d13f1f59d10a7337feb9beb002664119f286036785284c6bec150/celery_stubs-0.1.3-py3-none-any.whl", hash = "sha256:dfb9ad27614a8af028b2055bb4a4ae99ca5e9a8d871428a506646d62153218d7", size = 89085, upload-time = "2023-02-10T02:20:09.409Z" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "certifi"
|
||||
version = "2025.10.5"
|
||||
@ -525,13 +542,14 @@ wheels = [
|
||||
[[package]]
|
||||
name = "enviformer"
|
||||
version = "0.1.0"
|
||||
source = { git = "ssh://git@git.envipath.com/enviPath/enviformer.git?rev=v0.1.2#3f28f60cfa1df814cf7559303b5130933efa40ae" }
|
||||
source = { git = "ssh://git@git.envipath.com/enviPath/enviformer.git?rev=v0.1.4#7094be5767748fd63d4a84a5d71f06cf02ba07f3" }
|
||||
dependencies = [
|
||||
{ name = "joblib" },
|
||||
{ name = "lightning" },
|
||||
{ name = "pytorch-lightning" },
|
||||
{ name = "scikit-learn" },
|
||||
{ name = "torch" },
|
||||
{ name = "torch", version = "2.8.0", source = { registry = "https://pypi.org/simple" }, marker = "sys_platform != 'linux' and sys_platform != 'win32'" },
|
||||
{ name = "torch", version = "2.8.0+cu128", source = { registry = "https://download.pytorch.org/whl/cu128" }, marker = "sys_platform == 'linux' or sys_platform == 'win32'" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
@ -546,7 +564,6 @@ dependencies = [
|
||||
{ name = "django-ninja" },
|
||||
{ name = "django-oauth-toolkit" },
|
||||
{ name = "django-polymorphic" },
|
||||
{ name = "django-stubs" },
|
||||
{ name = "enviformer" },
|
||||
{ name = "envipy-additional-information" },
|
||||
{ name = "envipy-ambit" },
|
||||
@ -554,6 +571,8 @@ dependencies = [
|
||||
{ name = "epam-indigo" },
|
||||
{ name = "gunicorn" },
|
||||
{ name = "networkx" },
|
||||
{ name = "nh3" },
|
||||
{ name = "polars" },
|
||||
{ name = "psycopg2-binary" },
|
||||
{ name = "python-dotenv" },
|
||||
{ name = "rdkit" },
|
||||
@ -566,6 +585,8 @@ dependencies = [
|
||||
|
||||
[package.optional-dependencies]
|
||||
dev = [
|
||||
{ name = "celery-stubs" },
|
||||
{ name = "django-stubs" },
|
||||
{ name = "poethepoet" },
|
||||
{ name = "pre-commit" },
|
||||
{ name = "ruff" },
|
||||
@ -577,22 +598,25 @@ ms-login = [
|
||||
[package.metadata]
|
||||
requires-dist = [
|
||||
{ name = "celery", specifier = ">=5.5.2" },
|
||||
{ name = "celery-stubs", marker = "extra == 'dev'", specifier = "==0.1.3" },
|
||||
{ name = "django", specifier = ">=5.2.1" },
|
||||
{ name = "django-extensions", specifier = ">=4.1" },
|
||||
{ name = "django-model-utils", specifier = ">=5.0.0" },
|
||||
{ name = "django-ninja", specifier = ">=1.4.1" },
|
||||
{ name = "django-oauth-toolkit", specifier = ">=3.0.1" },
|
||||
{ name = "django-polymorphic", specifier = ">=4.1.0" },
|
||||
{ name = "django-stubs", specifier = ">=5.2.4" },
|
||||
{ name = "enviformer", git = "ssh://git@git.envipath.com/enviPath/enviformer.git?rev=v0.1.2" },
|
||||
{ name = "envipy-additional-information", git = "ssh://git@git.envipath.com/enviPath/enviPy-additional-information.git?rev=v0.1.4" },
|
||||
{ name = "django-stubs", marker = "extra == 'dev'", specifier = ">=5.2.4" },
|
||||
{ name = "enviformer", git = "ssh://git@git.envipath.com/enviPath/enviformer.git?rev=v0.1.4" },
|
||||
{ name = "envipy-additional-information", git = "ssh://git@git.envipath.com/enviPath/enviPy-additional-information.git?rev=v0.1.7" },
|
||||
{ name = "envipy-ambit", git = "ssh://git@git.envipath.com/enviPath/enviPy-ambit.git" },
|
||||
{ name = "envipy-plugins", git = "ssh://git@git.envipath.com/enviPath/enviPy-plugins.git?rev=v0.1.0" },
|
||||
{ name = "epam-indigo", specifier = ">=1.30.1" },
|
||||
{ name = "gunicorn", specifier = ">=23.0.0" },
|
||||
{ name = "msal", marker = "extra == 'ms-login'", specifier = ">=1.33.0" },
|
||||
{ name = "networkx", specifier = ">=3.4.2" },
|
||||
{ name = "nh3", specifier = "==0.3.2" },
|
||||
{ name = "poethepoet", marker = "extra == 'dev'", specifier = ">=0.37.0" },
|
||||
{ name = "polars", specifier = "==1.35.1" },
|
||||
{ name = "pre-commit", marker = "extra == 'dev'", specifier = ">=4.3.0" },
|
||||
{ name = "psycopg2-binary", specifier = ">=2.9.10" },
|
||||
{ name = "python-dotenv", specifier = ">=1.1.0" },
|
||||
@ -608,8 +632,8 @@ provides-extras = ["ms-login", "dev"]
|
||||
|
||||
[[package]]
|
||||
name = "envipy-additional-information"
|
||||
version = "0.1.0"
|
||||
source = { git = "ssh://git@git.envipath.com/enviPath/enviPy-additional-information.git?rev=v0.1.4#4da604090bf7cf1f3f552d69485472dbc623030a" }
|
||||
version = "0.1.7"
|
||||
source = { git = "ssh://git@git.envipath.com/enviPath/enviPy-additional-information.git?rev=v0.1.7#d02a5d5e6a931e6565ea86127813acf7e4b33a30" }
|
||||
dependencies = [
|
||||
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|
||||
{ name = "packaging" },
|
||||
{ name = "torch" },
|
||||
{ name = "torch", version = "2.8.0", source = { registry = "https://pypi.org/simple" }, marker = "sys_platform != 'linux' and sys_platform != 'win32'" },
|
||||
{ name = "torch", version = "2.8.0+cu128", source = { registry = "https://download.pytorch.org/whl/cu128" }, marker = "sys_platform == 'linux' or sys_platform == 'win32'" },
|
||||
]
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/85/2e/48a887a59ecc4a10ce9e8b35b3e3c5cef29d902c4eac143378526e7485cb/torchmetrics-1.8.2.tar.gz", hash = "sha256:cf64a901036bf107f17a524009eea7781c9c5315d130713aeca5747a686fe7a5", size = 580679, upload-time = "2025-09-03T14:00:54.077Z" }
|
||||
wheels = [
|
||||
@ -2032,7 +2193,7 @@ name = "triton"
|
||||
version = "3.4.0"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
dependencies = [
|
||||
{ name = "setuptools" },
|
||||
{ name = "setuptools", marker = "sys_platform == 'linux' or sys_platform == 'win32'" },
|
||||
]
|
||||
wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/d0/66/b1eb52839f563623d185f0927eb3530ee4d5ffe9d377cdaf5346b306689e/triton-3.4.0-cp312-cp312-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:31c1d84a5c0ec2c0f8e8a072d7fd150cab84a9c239eaddc6706c081bfae4eb04", size = 155560068, upload-time = "2025-07-30T19:58:37.081Z" },
|
||||
|
||||
Reference in New Issue
Block a user