6 Commits

Author SHA1 Message Date
1e43c298d2 [Fix] Simplify Depth adjustment (#386)
Co-authored-by: Tim Lorsbach <tim@lorsba.ch>
Reviewed-on: enviPath/enviPy#386
2026-05-12 21:04:56 +12:00
b39fc7eaf8 [Fix] Update Node depth when adding new Edges to a Pathway (#384)
Co-authored-by: Tim Lorsbach <tim@lorsba.ch>
Reviewed-on: enviPath/enviPy#384
2026-05-12 09:40:35 +12:00
a2fc9f72cb [Feature] Make use of HalfLifeModel Enum (#383)
Co-authored-by: Tim Lorsbach <tim@lorsba.ch>
Reviewed-on: enviPath/enviPy#383
2026-05-12 09:23:56 +12:00
734b02767e [Fix] Update plotting imports and thread handling in Pepper class (#382)
- plt.subplot does not work reliably with async/ threads.
- Bug in thread run that would fail with env set (string to number)

Reviewed-on: enviPath/enviPy#382
Co-authored-by: Tobias O <tobias.olenyi@envipath.com>
Co-committed-by: Tobias O <tobias.olenyi@envipath.com>
2026-05-12 06:43:26 +12:00
9d70db2ca2 [Fix] Wrong indentation in welcome mail (#373)
Co-authored-by: Tim Lorsbach <tim@lorsba.ch>
Reviewed-on: enviPath/enviPy#373
2026-04-22 08:47:05 +12:00
fec26d0233 [Feature] Admin Actions for Activation and Affiliation Request (#372)
Co-authored-by: Tim Lorsbach <tim@lorsba.ch>
Reviewed-on: enviPath/enviPy#372
2026-04-22 08:36:31 +12:00
11 changed files with 276 additions and 77 deletions

View File

@ -1,5 +1,8 @@
import logging
from django.conf import settings as s
from django.contrib import admin
from django.contrib import messages
from .models import (
AdditionalInformation,
@ -29,6 +32,8 @@ from .models import (
Package = s.GET_PACKAGE_MODEL()
logger = logging.getLogger(__name__)
class AdditionalInformationAdmin(admin.ModelAdmin):
pass
@ -45,6 +50,113 @@ class UserAdmin(admin.ModelAdmin):
"date_joined",
]
actions = ["send_welcome_mail", "send_affiliation_mail"]
@admin.action(description="Send welcome mail")
def send_welcome_mail(self, request, queryset):
from django.core.mail import EmailMultiAlternatives
tpl = """Hello {username},
Your account has been successfully activated.
To log in, please visit
https://envipath.org/password_reset/
and request a new password.
If you have any questions or feedback, feel free to visit our community forum at
https://community.envipath.org/.
You do not need to register again for the forum - you can log in using your enviPath account by clicking "Log In" and then "Log in with enviPath."
Best regards,
The enviPath Team"""
users = []
for user in queryset:
if user.is_active:
logger.info(f"{user.username} already active - not sending mail again")
continue
try:
msg = EmailMultiAlternatives(
"Your enviPath Account Is Now Active",
tpl.format(username=user.username),
"admin@envipath.org",
[user.email],
bcc=["admin@envipath.org"],
)
msg.send(fail_silently=False)
user.is_active = True
user.password = "ASDF"
user.save()
users.append(user)
logger.info(f"{user.username} -> {user.email} mail sent")
except Exception as e:
logger.info(f"Error sending mail to {user.username}: {e}")
self.message_user(
request, f"Sent welcome mail to {[u.email for u in users]}", messages.SUCCESS
)
@admin.action(description="Send affiliation mail")
def send_affiliation_mail(self, request, queryset):
from django.core.mail import EmailMultiAlternatives
tpl = """Dear {username},
Thank you for your interest in enviPath!
Please note that the public enviPath system is intended for non-commercial use only.
We see that you registered using the email address {email}.
If possible, we kindly ask you to register using an official email address that reflects your affiliation (e.g., a university, NGO, or research organization).
If you would like us to update your account, simply reply to this email and let us know which address we should use.
We will then change it in our system, and you will receive a password reset email at the new address.
If you are registering with a company email address and are interested in commercial use, you are very welcome to book a meeting with us so we can discuss how we can best support you.
To book a meeting, please visit https://envipath.com/book
If changing to an affiliation email address is not possible, please contact us at registration@envipath.org
Best regards,
enviPath team"""
users = []
for user in queryset:
if user.is_active or user.contacted:
logger.info(
f"{user.username} already active or already contacted - not sending mail again"
)
continue
try:
msg = EmailMultiAlternatives(
"Regarding your enviPath registration",
tpl.format(username=user.username, email=user.email),
"admin@envipath.org",
[user.email],
bcc=["admin@envipath.org"],
)
msg.send(fail_silently=False)
user.contacted = True
user.save()
users.append(user)
logger.info(f"{user.username} -> {user.email} affiliation mail sent")
except Exception as e:
logger.info(f"Error sending mail to {user.username}: {e}")
self.message_user(
request, f"Sent affiliation mail to {[u.email for u in users]}", messages.SUCCESS
)
class UserPackagePermissionAdmin(admin.ModelAdmin):
pass

View File

@ -1967,6 +1967,9 @@ def add_pathway_edge(request, package_uuid, pathway_uuid, e: Form[CreateEdge]):
description=e.edgeReason,
)
# Update depths as sideeffect of above operation
pw.update_depths()
return redirect(new_e.url)
except ValueError:
return 403, {"message": "Adding Edge failed!"}

View File

@ -995,52 +995,9 @@ class PackageManager(object):
print("Fixing Node depths...")
total_pws = Pathway.objects.filter(package=pack).count()
for p, pw in enumerate(Pathway.objects.filter(package=pack)):
in_count = defaultdict(lambda: 0)
out_count = defaultdict(lambda: 0)
for e in pw.edges:
# TODO check if this will remain
for react in e.start_nodes.all():
out_count[str(react.uuid)] += 1
for prod in e.end_nodes.all():
in_count[str(prod.uuid)] += 1
root_nodes = []
for n in pw.nodes:
num_parents = in_count[str(n.uuid)]
if num_parents == 0:
# must be a root node or unconnected node
if n.depth != 0:
n.depth = 0
n.save()
# Only root node may have children
if out_count[str(n.uuid)] > 0:
root_nodes.append(n)
levels = [root_nodes]
seen = set()
# Do a bfs to determine depths starting with level 0 a.k.a. root nodes
for i, level_nodes in enumerate(levels):
new_level = []
for n in level_nodes:
for e in n.out_edges.all():
for prod in e.end_nodes.all():
if str(prod.uuid) not in seen:
old_depth = prod.depth
if old_depth != i + 1:
prod.depth = i + 1
prod.save()
new_level.append(prod)
seen.add(str(n.uuid))
if new_level:
levels.append(new_level)
pw.update_depths()
print(f"{p + 1}/{total_pws} fixed.", end="\r")
return pack

View File

@ -0,0 +1,17 @@
# Generated by Django 6.0.3 on 2026-04-21 19:56
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
("epdb", "0023_alter_compoundstructure_options_and_more"),
]
operations = [
migrations.AddField(
model_name="user",
name="contacted",
field=models.BooleanField(blank=True, null=True),
),
]

View File

@ -0,0 +1,56 @@
# Generated by Django 6.0.3 on 2026-05-11 20:25
from django.db import migrations
from envipy_additional_information import HalfLife, HalfLifeModel, HalfLifeWS
MAPPING = {
"": HalfLifeModel.OTHER,
"HS-SFO": HalfLifeModel.HS_SFO,
"FOMC": HalfLifeModel.FOMC,
"FOTC": HalfLifeModel.DFOP,
"FMOC": HalfLifeModel.FOMC,
"DFOP": HalfLifeModel.DFOP,
"SFO + SFO": HalfLifeModel.SFO_SFO,
"FOMC-SFO": HalfLifeModel.FOMC_SFO,
"first order kinetics": HalfLifeModel.SFO,
"SFO²": HalfLifeModel.SFO,
"HS": HalfLifeModel.HS,
"top down": HalfLifeModel.OTHER,
"SFO": HalfLifeModel.SFO,
"First Order": HalfLifeModel.SFO,
"SFO/SFO": HalfLifeModel.SFO_SFO,
"FOMC + SFO": HalfLifeModel.FOMC_SFO,
"true": HalfLifeModel.SFO,
"SFO-SFO": HalfLifeModel.SFO_SFO,
"DFOP-SFO": HalfLifeModel.DFOP_SFO,
}
def forward_func(apps, schema_editor):
AdditionalInformation = apps.get_model("epdb", "AdditionalInformation")
hls = AdditionalInformation.objects.filter(type="HalfLife")
for hl in hls:
data = hl.data
data["model"] = MAPPING[data["model"]].value
hl.data = HalfLife(**data).model_dump(mode="json")
hl.save()
hlws = AdditionalInformation.objects.filter(type="HalfLifeWS")
for hl in hlws:
data = hl.data
data["model"] = MAPPING[data["model"]].value
hl.data = HalfLifeWS(**data).model_dump(mode="json")
hl.save()
class Migration(migrations.Migration):
dependencies = [
("epdb", "0024_user_contacted"),
]
operations = [
migrations.RunPython(forward_func, reverse_code=migrations.RunPython.noop),
]

View File

@ -75,6 +75,7 @@ class User(AbstractUser):
blank=False,
)
is_reviewer = models.BooleanField(default=False)
contacted = models.BooleanField(null=True, blank=True)
USERNAME_FIELD = "email"
REQUIRED_FIELDS = ["username"]
@ -2177,6 +2178,56 @@ class Pathway(EnviPathModel, AliasMixin, ScenarioMixin, AdditionalInformationMix
):
return Edge.create(self, start_nodes, end_nodes, rule, name=name, description=description)
def update_depths(self):
# Collect number of in and out links per node
in_count = defaultdict(lambda: 0)
out_count = defaultdict(lambda: 0)
for e in self.edges:
for react in e.start_nodes.all():
out_count[str(react.uuid)] += 1
for prod in e.end_nodes.all():
in_count[str(prod.uuid)] += 1
depth_map = {}
depth_map[0] = list()
for n in self.nodes:
num_parents = in_count[str(n.uuid)]
if num_parents == 0:
# must be a root node or unconnected node
if n.depth != 0:
n.depth = 0
n.save()
# Only root node may have children
if out_count[str(n.uuid)] > 0:
depth_map[0].append(n)
# At most depth len(nodes) is possible
for i in range(self.nodes.count()):
level_nodes = depth_map.get(i, [])
if len(level_nodes) == 0:
break
unique_next_level = set()
for n in level_nodes:
for e in self.edges:
if n in e.start_nodes.all():
for p in e.end_nodes.all():
unique_next_level.add(p)
if len(unique_next_level) > 0:
depth_map[i + 1] = list(unique_next_level)
for depth, nodes in depth_map.items():
for n in nodes:
if n.depth != depth:
n.depth = depth
n.save()
class Node(EnviPathModel, AliasMixin, ScenarioMixin, AdditionalInformationMixin):
pathway = models.ForeignKey(

View File

@ -2506,6 +2506,9 @@ def package_pathway_edges(request, package_uuid, pathway_uuid):
substrate_nodes, product_nodes, name=edge_name, description=edge_description
)
# Update depths as sideeffect of above operation
current_pathway.update_depths()
return redirect(current_pathway.url)
else:

View File

@ -46,7 +46,7 @@ class PepperPrediction(PropertyPrediction):
import matplotlib.patches as mpatches
import numpy as np
from matplotlib import pyplot as plt
from matplotlib.figure import Figure
from scipy import stats
"""
@ -101,7 +101,8 @@ class PepperPrediction(PropertyPrediction):
mask_red = x > vp
# Plot
fig, ax = plt.subplots(figsize=(9, 5.5))
fig = Figure(figsize=(9, 5.5))
ax = fig.subplots()
ax.plot(x, y, color="#1f4e79", lw=2, label="Lognormal PDF")
if np.any(mask_green):
@ -146,13 +147,12 @@ class PepperPrediction(PropertyPrediction):
]
ax.legend(handles=patches, frameon=True)
plt.tight_layout()
fig.tight_layout()
# --- Export to SVG string ---
buf = io.StringIO()
fig.savefig(buf, format="svg", bbox_inches="tight")
svg = buf.getvalue()
plt.close(fig)
buf.close()
return svg

View File

@ -187,8 +187,9 @@ class Pepper:
groups = [group for group in dataset.group_by("structure_id")]
# Unless explicitly set compute everything serial
if os.environ.get("N_PEPPER_THREADS", 1) > 1:
results = Parallel(n_jobs=os.environ["N_PEPPER_THREADS"])(
n_threads = int(os.environ.get("N_PEPPER_THREADS", 1))
if n_threads > 1:
results = Parallel(n_jobs=n_threads)(
delayed(compute_bayes_per_group)(group[1])
for group in dataset.group_by("structure_id")
)

View File

@ -64,7 +64,7 @@
import logging
from envipy_additional_information import HalfLife, HalfLifeWS
from envipy_additional_information import HalfLife, HalfLifeWS, HalfLifeModel
from envipy_additional_information.information import Interval
from envipy_additional_information.parsers import (
AcidityParser,
@ -473,17 +473,12 @@ def build_additional_information_from_request(request, type_):
comment = get_parameter_or_empty_string(request, "comment")
source = get_parameter_or_empty_string(request, "source")
first_order = get_parameter_or_empty_string(request, "firstOrder")
# first_order = get_parameter_or_empty_string(request, "firstOrder")
model = get_parameter_or_empty_string(request, "model")
fit = get_parameter_or_empty_string(request, "fit")
if first_order != "":
if model != "":
raise ValueError("not both, model and firstOrder can be set!")
if first_order == "true":
model = "SFO"
else:
logger.info("firstOrder is set to false which is not meaningful")
if model:
model = HalfLifeModel(model.upper())
return HalfLife(model=model, fit=fit, comment=comment, dt50=i, source=source)
@ -508,6 +503,10 @@ def build_additional_information_from_request(request, type_):
comment_ws = get_parameter_or_empty_string(request, "comment_ws")
source_ws = get_parameter_or_empty_string(request, "source_ws")
model_ws = get_parameter_or_empty_string(request, "model_ws")
if model_ws:
model_ws = HalfLifeModel(model_ws.upper())
fit_ws = get_parameter_or_empty_string(request, "fit_ws")
dt50_total = IntervalParser.from_string(hl_ws_total)

34
uv.lock generated
View File

@ -894,7 +894,7 @@ provides-extras = ["ms-login", "dev", "pepper-plugin"]
[[package]]
name = "envipy-additional-information"
version = "0.4.2"
source = { git = "ssh://git@git.envipath.com/enviPath/enviPy-additional-information.git?branch=develop#0a608c85c73a6ef5c38afea87d2b57fb43f01a70" }
source = { git = "ssh://git@git.envipath.com/enviPath/enviPy-additional-information.git?branch=develop#676dae1c5678539beac637b87e49b9dadfdfd85a" }
dependencies = [
{ name = "pydantic" },
]
@ -2763,9 +2763,9 @@ dependencies = [
{ name = "typing-extensions", marker = "sys_platform != 'linux' and sys_platform != 'win32'" },
]
wheels = [
{ url = "https://download-r2.pytorch.org/whl/cpu/torch-2.8.0-cp312-none-macosx_11_0_arm64.whl", hash = "sha256:a47b7986bee3f61ad217d8a8ce24605809ab425baf349f97de758815edd2ef54" },
{ url = "https://download-r2.pytorch.org/whl/cpu/torch-2.8.0-cp313-cp313t-macosx_14_0_arm64.whl", hash = "sha256:fbe2e149c5174ef90d29a5f84a554dfaf28e003cb4f61fa2c8c024c17ec7ca58" },
{ url = "https://download-r2.pytorch.org/whl/cpu/torch-2.8.0-cp313-none-macosx_11_0_arm64.whl", hash = "sha256:057efd30a6778d2ee5e2374cd63a63f63311aa6f33321e627c655df60abdd390" },
{ url = "https://download-r2.pytorch.org/whl/cpu/torch-2.8.0-cp312-none-macosx_11_0_arm64.whl", hash = "sha256:a47b7986bee3f61ad217d8a8ce24605809ab425baf349f97de758815edd2ef54", upload-time = "2025-10-01T23:35:50Z" },
{ url = "https://download-r2.pytorch.org/whl/cpu/torch-2.8.0-cp313-cp313t-macosx_14_0_arm64.whl", hash = "sha256:fbe2e149c5174ef90d29a5f84a554dfaf28e003cb4f61fa2c8c024c17ec7ca58", upload-time = "2025-10-01T23:35:52Z" },
{ url = "https://download-r2.pytorch.org/whl/cpu/torch-2.8.0-cp313-none-macosx_11_0_arm64.whl", hash = "sha256:057efd30a6778d2ee5e2374cd63a63f63311aa6f33321e627c655df60abdd390", upload-time = "2025-10-01T23:35:55Z" },
]
[[package]]
@ -2785,19 +2785,19 @@ dependencies = [
{ name = "typing-extensions", marker = "sys_platform == 'linux' or sys_platform == 'win32'" },
]
wheels = [
{ url = "https://download-r2.pytorch.org/whl/cpu/torch-2.8.0%2Bcpu-cp312-cp312-linux_s390x.whl", hash = "sha256:0e34e276722ab7dd0dffa9e12fe2135a9b34a0e300c456ed7ad6430229404eb5" },
{ url = "https://download-r2.pytorch.org/whl/cpu/torch-2.8.0%2Bcpu-cp312-cp312-manylinux_2_28_aarch64.whl", hash = "sha256:610f600c102386e581327d5efc18c0d6edecb9820b4140d26163354a99cd800d" },
{ url = "https://download-r2.pytorch.org/whl/cpu/torch-2.8.0%2Bcpu-cp312-cp312-manylinux_2_28_x86_64.whl", hash = "sha256:cb9a8ba8137ab24e36bf1742cb79a1294bd374db570f09fc15a5e1318160db4e" },
{ url = "https://download-r2.pytorch.org/whl/cpu/torch-2.8.0%2Bcpu-cp312-cp312-win_amd64.whl", hash = "sha256:2be20b2c05a0cce10430cc25f32b689259640d273232b2de357c35729132256d" },
{ url = "https://download-r2.pytorch.org/whl/cpu/torch-2.8.0%2Bcpu-cp312-cp312-win_arm64.whl", hash = "sha256:99fc421a5d234580e45957a7b02effbf3e1c884a5dd077afc85352c77bf41434" },
{ url = "https://download-r2.pytorch.org/whl/cpu/torch-2.8.0%2Bcpu-cp313-cp313-linux_s390x.whl", hash = "sha256:8b5882276633cf91fe3d2d7246c743b94d44a7e660b27f1308007fdb1bb89f7d" },
{ url = "https://download-r2.pytorch.org/whl/cpu/torch-2.8.0%2Bcpu-cp313-cp313-manylinux_2_28_aarch64.whl", hash = "sha256:a5064b5e23772c8d164068cc7c12e01a75faf7b948ecd95a0d4007d7487e5f25" },
{ url = "https://download-r2.pytorch.org/whl/cpu/torch-2.8.0%2Bcpu-cp313-cp313-manylinux_2_28_x86_64.whl", hash = "sha256:8f81dedb4c6076ec325acc3b47525f9c550e5284a18eae1d9061c543f7b6e7de" },
{ url = "https://download-r2.pytorch.org/whl/cpu/torch-2.8.0%2Bcpu-cp313-cp313-win_amd64.whl", hash = "sha256:e1ee1b2346ade3ea90306dfbec7e8ff17bc220d344109d189ae09078333b0856" },
{ url = "https://download-r2.pytorch.org/whl/cpu/torch-2.8.0%2Bcpu-cp313-cp313-win_arm64.whl", hash = "sha256:64c187345509f2b1bb334feed4666e2c781ca381874bde589182f81247e61f88" },
{ url = "https://download-r2.pytorch.org/whl/cpu/torch-2.8.0%2Bcpu-cp313-cp313t-manylinux_2_28_aarch64.whl", hash = "sha256:af81283ac671f434b1b25c95ba295f270e72db1fad48831eb5e4748ff9840041" },
{ url = "https://download-r2.pytorch.org/whl/cpu/torch-2.8.0%2Bcpu-cp313-cp313t-manylinux_2_28_x86_64.whl", hash = "sha256:a9dbb6f64f63258bc811e2c0c99640a81e5af93c531ad96e95c5ec777ea46dab" },
{ url = "https://download-r2.pytorch.org/whl/cpu/torch-2.8.0%2Bcpu-cp313-cp313t-win_amd64.whl", hash = "sha256:6d93a7165419bc4b2b907e859ccab0dea5deeab261448ae9a5ec5431f14c0e64" },
{ url = "https://download-r2.pytorch.org/whl/cpu/torch-2.8.0%2Bcpu-cp312-cp312-linux_s390x.whl", hash = "sha256:0e34e276722ab7dd0dffa9e12fe2135a9b34a0e300c456ed7ad6430229404eb5", upload-time = "2025-10-01T23:33:41Z" },
{ url = "https://download-r2.pytorch.org/whl/cpu/torch-2.8.0%2Bcpu-cp312-cp312-manylinux_2_28_aarch64.whl", hash = "sha256:610f600c102386e581327d5efc18c0d6edecb9820b4140d26163354a99cd800d", upload-time = "2025-10-01T23:33:45Z" },
{ url = "https://download-r2.pytorch.org/whl/cpu/torch-2.8.0%2Bcpu-cp312-cp312-manylinux_2_28_x86_64.whl", hash = "sha256:cb9a8ba8137ab24e36bf1742cb79a1294bd374db570f09fc15a5e1318160db4e", upload-time = "2025-10-01T23:33:48Z" },
{ url = "https://download-r2.pytorch.org/whl/cpu/torch-2.8.0%2Bcpu-cp312-cp312-win_amd64.whl", hash = "sha256:2be20b2c05a0cce10430cc25f32b689259640d273232b2de357c35729132256d", upload-time = "2025-10-01T23:33:52Z" },
{ url = "https://download-r2.pytorch.org/whl/cpu/torch-2.8.0%2Bcpu-cp312-cp312-win_arm64.whl", hash = "sha256:99fc421a5d234580e45957a7b02effbf3e1c884a5dd077afc85352c77bf41434", upload-time = "2025-10-01T23:34:10Z" },
{ url = "https://download-r2.pytorch.org/whl/cpu/torch-2.8.0%2Bcpu-cp313-cp313-linux_s390x.whl", hash = "sha256:8b5882276633cf91fe3d2d7246c743b94d44a7e660b27f1308007fdb1bb89f7d", upload-time = "2025-10-01T23:34:15Z" },
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