From fd2e2c2534f7734782adcf7a528650c862ef0414 Mon Sep 17 00:00:00 2001 From: jebus Date: Thu, 27 Nov 2025 10:28:04 +1300 Subject: [PATCH] [Fix] Post Modern UI deploy Bugfixes (#240) Co-authored-by: Tim Lorsbach Reviewed-on: https://git.envipath.com/enviPath/enviPy/pulls/240 --- envipath/settings.py | 2 +- epdb/models.py | 28 ++++-- epdb/views.py | 21 +++-- templates/actions/objects/model.html | 36 ++++---- templates/collections/objects_list.html | 2 +- .../modals/objects/evaluate_model_modal.html | 1 - .../objects/generic_set_aliases_modal.html | 1 + .../modals/objects/set_license_modal.html | 2 +- utilities/ml.py | 87 ++++++++++++++----- 9 files changed, 127 insertions(+), 53 deletions(-) diff --git a/envipath/settings.py b/envipath/settings.py index 81363f92..3cac2c1a 100644 --- a/envipath/settings.py +++ b/envipath/settings.py @@ -366,7 +366,7 @@ LOGIN_EXEMPT_URLS = [ "/cookie-policy", "/about", "/contact", - "/jobs", + "/careers", "/cite", "/legal", ] diff --git a/epdb/models.py b/epdb/models.py index d44783e2..7fefa928 100644 --- a/epdb/models.py +++ b/epdb/models.py @@ -2282,6 +2282,13 @@ class PackageBasedModel(EPModel): return Dataset.load(ds_path) def retrain(self): + # Reset eval fields + self.eval_results = {} + self.eval_packages.clear() + self.model_status = False + self.save() + + # Do actual retrain self.build_dataset() self.build_model() @@ -2319,7 +2326,7 @@ class PackageBasedModel(EPModel): self.save() def evaluate_model(self, multigen: bool, eval_packages: List["Package"] = None, **kwargs): - if self.model_status != self.BUILT_NOT_EVALUATED: + if self.model_status not in [self.BUILT_NOT_EVALUATED, self.FINISHED]: raise ValueError(f"Can't evaluate a model in state {self.model_status}!") if multigen: @@ -2327,9 +2334,12 @@ class PackageBasedModel(EPModel): self.save() if eval_packages is not None: + self.eval_packages.clear() for p in eval_packages: self.eval_packages.add(p) + self.eval_results = {} + self.model_status = self.EVALUATING self.save() @@ -2383,9 +2393,14 @@ class PackageBasedModel(EPModel): recall = {f"{t:.2f}": [] for t in thresholds} # Note: only one root compound supported at this time - root_compounds = [ - [p.default_node_label.smiles for p in p.root_nodes][0] for p in pathways - ] + root_compounds = [] + for pw in pathways: + if pw.root_nodes: + root_compounds.append(pw.root_nodes[0].default_node_label) + else: + logger.info( + f"Skipping MG Eval of Pathway {pw.name} ({pw.uuid}) as it has no root compounds!" + ) # As we need a Model Instance in our setting, get a fresh copy from db, overwrite the serialized mode and # pass it to the setting used in prediction @@ -3192,7 +3207,7 @@ class EnviFormer(PackageBasedModel): return args def evaluate_model(self, multigen: bool, eval_packages: List["Package"] = None, **kwargs): - if self.model_status != self.BUILT_NOT_EVALUATED: + if self.model_status not in [self.BUILT_NOT_EVALUATED, self.FINISHED]: raise ValueError(f"Can't evaluate a model in state {self.model_status}!") if multigen: @@ -3200,9 +3215,12 @@ class EnviFormer(PackageBasedModel): self.save() if eval_packages is not None: + self.eval_packages.clear() for p in eval_packages: self.eval_packages.add(p) + self.eval_results = {} + self.model_status = self.EVALUATING self.save() diff --git a/epdb/views.py b/epdb/views.py index 57ab0a43..accce6f1 100644 --- a/epdb/views.py +++ b/epdb/views.py @@ -5,6 +5,7 @@ from typing import Any, Dict, List import nh3 from django.conf import settings as s from django.contrib.auth import get_user_model +from django.core.exceptions import BadRequest from django.http import HttpResponse, HttpResponseBadRequest, HttpResponseNotAllowed, JsonResponse from django.shortcuts import redirect, render from django.urls import reverse @@ -319,7 +320,7 @@ def get_base_context(request, for_user=None) -> Dict[str, Any]: def _anonymous_or_real(request): - if request.user.is_authenticated and not request.user.is_anonymous: + if request.user and (request.user.is_authenticated and not request.user.is_anonymous): return request.user return get_user_model().objects.get(username="anonymous") @@ -1261,8 +1262,12 @@ def package_compounds(request, package_uuid): compound_name = request.POST.get("compound-name") compound_smiles = request.POST.get("compound-smiles") compound_description = request.POST.get("compound-description") - - c = Compound.create(current_package, compound_smiles, compound_name, compound_description) + try: + c = Compound.create( + current_package, compound_smiles, compound_name, compound_description + ) + except ValueError as e: + raise BadRequest(str(e)) return redirect(c.url) @@ -2819,14 +2824,18 @@ def settings(request): context = get_base_context(request) if request.method == "GET": + context = get_base_context(request) + context["title"] = "enviPath - Settings" + context["object_type"] = "setting" - # Even if settings are aready in "meta", for consistency add it on root level - context["settings"] = SettingManager.get_all_settings(current_user) context["breadcrumbs"] = [ {"Home": s.SERVER_URL}, {"Group": s.SERVER_URL + "/setting"}, ] - return + + context["objects"] = SettingManager.get_all_settings(current_user) + + return render(request, "collections/objects_list.html", context) elif request.method == "POST": if s.DEBUG: for k, v in request.POST.items(): diff --git a/templates/actions/objects/model.html b/templates/actions/objects/model.html index 5f58feda..0172b363 100644 --- a/templates/actions/objects/model.html +++ b/templates/actions/objects/model.html @@ -7,22 +7,26 @@ Edit Model -
  • - - Evaluate Model -
    • -
  • - - Retrain Model -
    • + {% if model.model_status == 'BUILT_NOT_EVALUATED' or model.model_status == 'FINISHED' %} +
  • + + Evaluate Model +
    • + {% endif %} + {% if model.model_status == 'BUILT_NOT_EVALUATED' or model.model_status == 'FINISHED' %} +
  • + + Retrain Model +
    • + {% endif %}
  • -
      +
        {% for obj in objects %} {% if object_type == 'user' %}
      • diff --git a/templates/modals/objects/evaluate_model_modal.html b/templates/modals/objects/evaluate_model_modal.html index ae2f364e..d07dabc1 100644 --- a/templates/modals/objects/evaluate_model_modal.html +++ b/templates/modals/objects/evaluate_model_modal.html @@ -45,7 +45,6 @@ name="model-evaluation-packages" class="select select-bordered w-full h-48" multiple - required > {% for obj in meta.readable_packages %} diff --git a/templates/modals/objects/generic_set_aliases_modal.html b/templates/modals/objects/generic_set_aliases_modal.html index 43b26333..0e891322 100644 --- a/templates/modals/objects/generic_set_aliases_modal.html +++ b/templates/modals/objects/generic_set_aliases_modal.html @@ -65,6 +65,7 @@ method: 'POST', headers: { 'Content-Type': 'application/x-www-form-urlencoded', + 'X-CSRFToken': document.querySelector('[name=csrfmiddlewaretoken]').value }, body: formData }); diff --git a/templates/modals/objects/set_license_modal.html b/templates/modals/objects/set_license_modal.html index a005495d..07bd1111 100644 --- a/templates/modals/objects/set_license_modal.html +++ b/templates/modals/objects/set_license_modal.html @@ -52,7 +52,7 @@ }" @close="reset()" > -
        +

        Set License

        diff --git a/utilities/ml.py b/utilities/ml.py index 5df5dce8..06e80dcf 100644 --- a/utilities/ml.py +++ b/utilities/ml.py @@ -26,26 +26,38 @@ from utilities.chem import FormatConverter, PredictionResult logger = logging.getLogger(__name__) if TYPE_CHECKING: - from epdb.models import Rule, CompoundStructure, Reaction + from epdb.models import Rule, CompoundStructure 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__ + 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: # 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") + 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.df = pl.DataFrame( + data=data, schema=columns, orient="row", infer_schema_length=None + ) 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) + 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 add_row(self, row: List[str | int | float]): @@ -90,7 +102,9 @@ class Dataset(ABC): """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 + 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 @@ -111,9 +125,7 @@ class Dataset(ABC): return self.df.to_numpy() def __repr__(self): - return ( - f"<{self.__class__.__name__} #rows={len(self.df)} #cols={len(self.columns)}>" - ) + return f"<{self.__class__.__name__} #rows={len(self.df)} #cols={len(self.columns)}>" def __len__(self): return len(self.df) @@ -130,9 +142,25 @@ class Dataset(ABC): 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 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) @@ -149,7 +177,9 @@ 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]) + 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_") @@ -200,7 +230,12 @@ class RuleBasedDataset(Dataset): return res @staticmethod - def generate_dataset(reactions, applicable_rules, educts_only=True, feat_funcs: List["Callable | Descriptor"]=None): + 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 @@ -253,7 +288,7 @@ class RuleBasedDataset(Dataset): smi = cs.smiles try: smi = FormatConverter.standardize(smi, remove_stereo=True) - except Exception as e: + except Exception: logger.debug(f"Standardizing SMILES failed for {smi}") standardized_products.append(smi) if len(set(standardized_products).difference(triggered[key])) == 0: @@ -266,10 +301,12 @@ class RuleBasedDataset(Dataset): 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]) + 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): @@ -337,7 +374,9 @@ class RuleBasedDataset(Dataset): 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.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"): @@ -910,6 +949,10 @@ def prune_graph(graph, threshold): """ Removes edges with probability below the threshold, then keep the subgraph reachable from the root node. """ + + if graph.number_of_nodes() == 0: + return + while True: try: cycle = nx.find_cycle(graph)