From 6ec4f6237970a9cbf4cb8defd42ab8620b6d7c92 Mon Sep 17 00:00:00 2001 From: "Tristan F." Date: Fri, 10 Oct 2025 06:32:06 +0000 Subject: [PATCH 01/16] refactor: separate statistic computation we also make it lazy --- spras/analysis/summary.py | 44 +++----------------- spras/statistics.py | 88 +++++++++++++++++++++++++++++++++++++++ 2 files changed, 94 insertions(+), 38 deletions(-) create mode 100644 spras/statistics.py diff --git a/spras/analysis/summary.py b/spras/analysis/summary.py index c8abc1cad..fd70db8f3 100644 --- a/spras/analysis/summary.py +++ b/spras/analysis/summary.py @@ -1,10 +1,11 @@ from pathlib import Path -from statistics import median from typing import Iterable import networkx as nx import pandas as pd +from spras.statistics import compute_statistics, statistics_options + def summarize_networks(file_paths: Iterable[Path], node_table: pd.DataFrame, algo_params: dict[str, dict], algo_with_params: list) -> pd.DataFrame: @@ -47,44 +48,11 @@ def summarize_networks(file_paths: Iterable[Path], node_table: pd.DataFrame, alg # Save the network name, number of nodes, number edges, and number of connected components nw_name = str(file_path) - number_nodes = nw.number_of_nodes() - number_edges = nw.number_of_edges() - ncc = nx.number_connected_components(nw) - - # Save the max/median degree, average clustering coefficient, and density - if number_nodes == 0: - max_degree = 0 - median_degree = 0.0 - density = 0.0 - else: - degrees = [deg for _, deg in nw.degree()] - max_degree = max(degrees) - median_degree = median(degrees) - density = nx.density(nw) - - cc = list(nx.connected_components(nw)) - # Save the max diameter - # Use diameter only for components with ≥2 nodes (singleton components have diameter 0) - diameters = [ - nx.diameter(nw.subgraph(c).copy()) if len(c) > 1 else 0 - for c in cc - ] - max_diameter = max(diameters, default=0) - - # Save the average path lengths - # Compute average shortest path length only for components with ≥2 nodes (undefined for singletons, set to 0.0) - avg_path_lengths = [ - nx.average_shortest_path_length(nw.subgraph(c).copy()) if len(c) > 1 else 0.0 - for c in cc - ] - - if len(avg_path_lengths) != 0: - avg_path_len = sum(avg_path_lengths) / len(avg_path_lengths) - else: - avg_path_len = 0.0 + + graph_statistics = compute_statistics(nw, statistics_options) # Initialize list to store current network information - cur_nw_info = [nw_name, number_nodes, number_edges, ncc, density, max_degree, median_degree, max_diameter, avg_path_len] + cur_nw_info = [nw_name, *graph_statistics] # Iterate through each node property and save the intersection with the current network for node_list in nodes_by_col: @@ -104,7 +72,7 @@ def summarize_networks(file_paths: Iterable[Path], node_table: pd.DataFrame, alg nw_info.append(cur_nw_info) # Prepare column names - col_names = ['Name', 'Number of nodes', 'Number of edges', 'Number of connected components', 'Density', 'Max degree', 'Median degree', 'Max diameter', 'Average path length'] + col_names = ['Name', *statistics_options] col_names.extend(nodes_by_col_labs) col_names.append('Parameter combination') diff --git a/spras/statistics.py b/spras/statistics.py new file mode 100644 index 000000000..843e5292a --- /dev/null +++ b/spras/statistics.py @@ -0,0 +1,88 @@ +""" +Graph statistics, used to power summary.py. + +We allow for arbitrary computation of any specific statistic on some graph, +computing more than necessary if we have dependencies. See the top level +`statistics_computation` dictionary for usage. +""" + +import itertools +import networkx as nx +from statistics import median +from typing import Callable + +def compute_degree(graph: nx.DiGraph) -> tuple[int, float]: + """ + Computes the (max, median) degree of a `graph`. + """ + # number_of_nodes is a cheap call + if graph.number_of_nodes() == 0: + return (0, 0.0) + else: + degrees = [deg for _, deg in graph.degree()] + return max(degrees), median(degrees) + +def compute_on_cc(graph: nx.DiGraph) -> tuple[int, float]: + cc = list(nx.connected_components(graph)) + # Save the max diameter + # Use diameter only for components with ≥2 nodes (singleton components have diameter 0) + diameters = [ + nx.diameter(graph.subgraph(c).copy()) if len(c) > 1 else 0 + for c in cc + ] + max_diameter = max(diameters, default=0) + + # Save the average path lengths + # Compute average shortest path length only for components with ≥2 nodes (undefined for singletons, set to 0.0) + avg_path_lengths = [ + nx.average_shortest_path_length(graph.subgraph(c).copy()) if len(c) > 1 else 0.0 + for c in cc + ] + + if len(avg_path_lengths) != 0: + avg_path_len = sum(avg_path_lengths) / len(avg_path_lengths) + else: + avg_path_len = 0.0 + + return max_diameter, avg_path_len + +# The type signature on here is quite bad. I would like to say that an n-tuple has n-outputs. +statistics_computation: dict[tuple[str, ...], Callable[[nx.DiGraph], tuple[float | int, ...]]] = { + ('Number of nodes',): lambda graph : (graph.number_of_nodes(),), + ('Number of edges',): lambda graph : (graph.number_of_edges(),), + ('Number of connected components',): lambda graph : (nx.number_connected_components(graph),), + ('Density',): lambda graph : (nx.density(graph),), + + ('Max degree', 'Median degree'): compute_degree, + ('Max diameter', 'Average path length'): compute_on_cc, +} + +# All of the keys inside statistics_computation, flattened. +statistics_options: list[str] = list(itertools.chain(*(list(key) for key in statistics_computation.keys()))) + +def compute_statistics(graph: nx.DiGraph, statistics: list[str]) -> dict[str, float | int]: + """ + Computes `statistics` for a graph corresponding to the top-level `statistics` dictionary + in this file. + """ + + # early-scan cutoff for statistics: + # we want to err as soon as possible + for stat in statistics: + if stat not in statistics_options: + raise RuntimeError(f"Statistic {stat} not a computable statistics! Available statistics: {statistics_options}") + + # now, we can compute statistics only + computed_statistics: dict[str, float | int] = dict() + for statistic_tuple, compute in statistics_computation.items(): + # when we want them + if not set(statistic_tuple).isdisjoint(set(statistics)): + computed_tuple = compute(graph) + assert len(statistic_tuple) == computed_tuple, f"bad tuple length for {statistic_tuple}" + + current_computed_statistics = zip(statistic_tuple, computed_tuple) + for stat, value in current_computed_statistics: + computed_statistics[stat] = value + + # (and return only the statistics we wanted) + return {key: computed_statistics[key] for key in statistics} From 9987189d8e0d9a9006ae1897cd44836500a5c906 Mon Sep 17 00:00:00 2001 From: "Tristan F." Date: Fri, 10 Oct 2025 06:48:54 +0000 Subject: [PATCH 02/16] fix: correct tuple assumption --- spras/statistics.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/spras/statistics.py b/spras/statistics.py index 843e5292a..ac91b80a9 100644 --- a/spras/statistics.py +++ b/spras/statistics.py @@ -78,7 +78,7 @@ def compute_statistics(graph: nx.DiGraph, statistics: list[str]) -> dict[str, fl # when we want them if not set(statistic_tuple).isdisjoint(set(statistics)): computed_tuple = compute(graph) - assert len(statistic_tuple) == computed_tuple, f"bad tuple length for {statistic_tuple}" + assert len(statistic_tuple) == len(computed_tuple), f"bad tuple length for {statistic_tuple}" current_computed_statistics = zip(statistic_tuple, computed_tuple) for stat, value in current_computed_statistics: From 25eef5e72aee4fb7aea6f6b5e9d11dff7fd5be16 Mon Sep 17 00:00:00 2001 From: "Tristan F." Date: Fri, 10 Oct 2025 07:06:46 +0000 Subject: [PATCH 03/16] fix: stably use graph statistic values --- spras/analysis/summary.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/spras/analysis/summary.py b/spras/analysis/summary.py index fd70db8f3..432dba0a4 100644 --- a/spras/analysis/summary.py +++ b/spras/analysis/summary.py @@ -52,7 +52,7 @@ def summarize_networks(file_paths: Iterable[Path], node_table: pd.DataFrame, alg graph_statistics = compute_statistics(nw, statistics_options) # Initialize list to store current network information - cur_nw_info = [nw_name, *graph_statistics] + cur_nw_info = [nw_name, *graph_statistics.values()] # Iterate through each node property and save the intersection with the current network for node_list in nodes_by_col: From cb373c130760c7040b16ec03ba1d2673e343465b Mon Sep 17 00:00:00 2001 From: "Tristan F." Date: Wed, 29 Oct 2025 17:56:22 -0700 Subject: [PATCH 04/16] style: fmt --- spras/config/config.py | 4 ++-- spras/statistics.py | 12 +++++++----- 2 files changed, 9 insertions(+), 7 deletions(-) diff --git a/spras/config/config.py b/spras/config/config.py index 22e655941..add815d9d 100644 --- a/spras/config/config.py +++ b/spras/config/config.py @@ -71,7 +71,7 @@ def __init__(self, raw_config: dict[str, Any]): self.container_prefix: str = DEFAULT_CONTAINER_PREFIX # A Boolean specifying whether to unpack singularity containers. Default is False self.unpack_singularity = False - # A Boolean indiciating whether to enable container runtime profiling (apptainer/singularity only) + # A Boolean indicating whether to enable container runtime profiling (apptainer/singularity only) self.enable_profiling = False # A dictionary to store configured datasets against which SPRAS will be run self.datasets = None @@ -308,7 +308,7 @@ def process_config(self, raw_config: RawConfig): if raw_config.container_registry and raw_config.container_registry.base_url != "" and raw_config.container_registry.owner != "": self.container_prefix = raw_config.container_registry.base_url + "/" + raw_config.container_registry.owner - if raw_config.enable_profiling and not raw_config.container_framework in ["singularity", "apptainer"]: + if raw_config.enable_profiling and raw_config.container_framework not in ["singularity", "apptainer"]: warnings.warn("enable_profiling is set to true, but the container framework is not singularity/apptainer. This setting will have no effect.") self.enable_profiling = raw_config.enable_profiling diff --git a/spras/statistics.py b/spras/statistics.py index ac91b80a9..49ae8b3fc 100644 --- a/spras/statistics.py +++ b/spras/statistics.py @@ -7,10 +7,12 @@ """ import itertools -import networkx as nx from statistics import median from typing import Callable +import networkx as nx + + def compute_degree(graph: nx.DiGraph) -> tuple[int, float]: """ Computes the (max, median) degree of a `graph`. @@ -43,7 +45,7 @@ def compute_on_cc(graph: nx.DiGraph) -> tuple[int, float]: avg_path_len = sum(avg_path_lengths) / len(avg_path_lengths) else: avg_path_len = 0.0 - + return max_diameter, avg_path_len # The type signature on here is quite bad. I would like to say that an n-tuple has n-outputs. @@ -52,7 +54,7 @@ def compute_on_cc(graph: nx.DiGraph) -> tuple[int, float]: ('Number of edges',): lambda graph : (graph.number_of_edges(),), ('Number of connected components',): lambda graph : (nx.number_connected_components(graph),), ('Density',): lambda graph : (nx.density(graph),), - + ('Max degree', 'Median degree'): compute_degree, ('Max diameter', 'Average path length'): compute_on_cc, } @@ -63,7 +65,7 @@ def compute_on_cc(graph: nx.DiGraph) -> tuple[int, float]: def compute_statistics(graph: nx.DiGraph, statistics: list[str]) -> dict[str, float | int]: """ Computes `statistics` for a graph corresponding to the top-level `statistics` dictionary - in this file. + in this file. """ # early-scan cutoff for statistics: @@ -71,7 +73,7 @@ def compute_statistics(graph: nx.DiGraph, statistics: list[str]) -> dict[str, fl for stat in statistics: if stat not in statistics_options: raise RuntimeError(f"Statistic {stat} not a computable statistics! Available statistics: {statistics_options}") - + # now, we can compute statistics only computed_statistics: dict[str, float | int] = dict() for statistic_tuple, compute in statistics_computation.items(): From 4640bc0c3fcf57f2427d2bb0200381d7ce8ad6cb Mon Sep 17 00:00:00 2001 From: "Tristan F." Date: Thu, 30 Oct 2025 01:13:01 +0000 Subject: [PATCH 05/16] feat: init intervals and heuristics --- spras/config/schema.py | 50 ++++++++++ spras/interval.py | 203 +++++++++++++++++++++++++++++++++++++++++ 2 files changed, 253 insertions(+) create mode 100644 spras/interval.py diff --git a/spras/config/schema.py b/spras/config/schema.py index 2b46aaf1c..fbacb8793 100644 --- a/spras/config/schema.py +++ b/spras/config/schema.py @@ -13,9 +13,12 @@ import re from typing import Annotated, Optional +import networkx as nx from pydantic import AfterValidator, BaseModel, ConfigDict, Field from spras.config.util import CaseInsensitiveEnum +from spras.interval import Interval +from spras.statistics import compute_statistics, statistics_options # Most options here have an `include` property, # which is meant to make disabling parts of the configuration easier. @@ -148,6 +151,51 @@ class ReconstructionSettings(BaseModel): model_config = ConfigDict(extra='forbid') +class GraphHeuristics(BaseModel): + number_of_nodes: list[Interval] = [] + number_of_edges: list[Interval] = [] + number_of_connected_components: list[Interval] = [] + density: list[Interval] = [] + + max_degree: list[Interval] = [] + median_degree: list[Interval] = [] + max_diameter: list[Interval] = [] + average_path_length: list[Interval] = [] + + def validate_graph(self, graph: nx.DiGraph): + statistics_dictionary = { + 'Number of nodes': self.number_of_nodes, + 'Number of edges': self.number_of_edges, + 'Number of connected components': self.number_of_connected_components, + 'Density': self.density, + 'Max degree': self.max_degree, + 'Median degree': self.median_degree, + 'Max diameter': self.max_diameter, + 'Average path length': self.average_path_length + } + + # quick assert: is statistics_dictionary exhaustive? + assert set(statistics_dictionary.keys()) == set(statistics_options) + + stats = compute_statistics( + graph, + list(k for k, v in statistics_dictionary.items() if len(v) == 0) + ) + + for key, value in stats.items(): + intervals = statistics_dictionary[key] + + matches_heuristics = False + for interval in intervals: + if interval.mem(value): + matches_heuristics = True + break + + if not matches_heuristics: + raise RuntimeError(f"Heuristic {key} with value {value} does not match {intervals}!") + + model_config = ConfigDict(extra='forbid') + class RawConfig(BaseModel): # TODO: move these container values to a nested container key container_framework: ContainerFramework = ContainerFramework.docker @@ -165,6 +213,8 @@ class RawConfig(BaseModel): reconstruction_settings: ReconstructionSettings + heuristics: GraphHeuristics = GraphHeuristics() + # We include use_attribute_docstrings here to preserve the docstrings # after attributes at runtime (for future JSON schema generation) model_config = ConfigDict(extra='forbid', use_attribute_docstrings=True) diff --git a/spras/interval.py b/spras/interval.py new file mode 100644 index 000000000..6771a228b --- /dev/null +++ b/spras/interval.py @@ -0,0 +1,203 @@ +""" +Utilities for defining inequality intervals (e.g. l < x <= u) + +For graph heuristics, we allow inequality intervals of the form (num) < (id)?. For example, +we can say "1500 <" for "1500 < x", or "1000 < x < 2000", etc. + +[If there is ever a library that does this, we should replace this code with that library.] +""" + +from enum import Enum +from typing import Any, Optional, Self +from pydantic import BaseModel, model_validator + +class Operand(Enum): + LT = "<" + LTE = "<=" + EQ = "=" + GTE = ">=" + GT = ">" + + @classmethod + def from_str(cls, string: str) -> Optional[Self]: + return next((enum for enum in list(cls) if enum.value == string), None) + + def is_closed(self) -> bool: + """Whether this is a closed inequality. We consider = to be closed.""" + match self: + case Operand.LTE: return True + case Operand.EQ: return True + case Operand.GT: return True + return False + + def as_closed(self): + """Closes an operand. Eq does not get modified.""" + match self: + case Operand.LT: return Operand.LTE + case Operand.GT: return Operand.GTE + return self + + def as_opened(self): + """Opens an operand. Eq does not get modified.""" + match self: + case Operand.LTE: return Operand.LT + case Operand.GTE: return Operand.GT + return self + + def with_closed(self, closed: bool): return self.as_closed() if closed else self.as_opened() + + def compare(self, left, right) -> bool: + match self: + case Operand.LT: return left < right + case Operand.LTE: return left <= right + case Operand.EQ: return left == right + case Operand.GTE: return left >= right + case Operand.GT: return left > right + + @classmethod + def combine(cls, left: Self, right: Self): + """Combines two operands, returning None if the operands don't combine well.""" + match (left, right): + case (Operand.LTE, Operand.LTE): return Operand.LTE + case (Operand.LT, Operand.LTE): return Operand.LT + case (Operand.LT, Operand.LT): return Operand.LT + case (Operand.EQ, op): return op + case (op, Operand.EQ): return op + case (Operand.GTE, Operand.GTE): return Operand.GTE + case (Operand.GT, Operand.GTE): return Operand.GT + case (Operand.GT, Operand.GT): return Operand.GT + return None + +class Interval(BaseModel): + lower: Optional[float] + upper: Optional[float] + lower_closed: bool + upper_closed: bool + + def mem(self, num: float) -> bool: + if self.lower is not None: + meets_lower = self.lower <= num if self.lower_closed else self.lower < num + else: + meets_lower = True + + if self.upper is not None: + meets_upper = num <= self.upper if self.upper_closed else num < self.upper + else: + meets_upper = True + + return meets_lower and meets_upper + + @classmethod + def single(cls, num: float) -> Self: + return cls(lower=num, upper=num, lower_closed=True, upper_closed=True) + + @classmethod + def left_operand(cls, operand: Operand, num: float) -> Self: + """Creates an interval whose operand is on the left (e.g. <300)""" + match operand: + case Operand.LT: return cls(lower=None, upper=num, lower_closed=False, upper_closed=False) + case Operand.LTE: return cls(lower=None, upper=num, lower_closed=True, upper_closed=False) + case Operand.EQ: return cls.single(num) + case Operand.GTE: return cls(lower=num, upper=None, lower_closed=False, upper_closed=False) + case Operand.GT: return cls(lower=num, upper=None, lower_closed=False, upper_closed=True) + + @classmethod + def right_operand(cls, num: float, operand: Operand) -> Self: + """Creates an interval whose operand is on the right (e.g. 300<)""" + match operand: + case Operand.LT: return cls(lower=num, upper=None, lower_closed=False, upper_closed=False) + case Operand.LTE: return cls(lower=num, upper=None, lower_closed=True, upper_closed=False) + case Operand.EQ: return cls.single(num) + case Operand.GTE: return cls(lower=None, upper=num, lower_closed=False, upper_closed=False) + case Operand.GT: return cls(lower=None, upper=num, lower_closed=False, upper_closed=True) + + @classmethod + def from_string(cls, input: str) -> Self: + tokens = [token.strip() for token in input.split(" ")] + + assert len(tokens) != 0 + + def parse_num(numstr: str) -> Optional[int]: + # Allow pythonic separators + try: + return int(numstr.replace("_", "")) + except: + return None + + def is_id(idstr: str) -> bool: return idstr.isidentifier() + + # Case 1: (id?) operand number + if is_id(tokens[0]): + # No other cases have an id at the beginning: we get rid of it. + tokens.pop() + + operand = Operand.from_str(tokens[0]) + if operand is not None: + # (cont.) Case 1: (id?) operand number + number = parse_num(tokens[1]) + assert number is not None, f"found operand {operand.value} and expected a number, but found {tokens[1]} instead." + return cls.left_operand(operand, number) + + # All other cases have a number + number = parse_num(tokens.pop()) + assert number is not None, f"expected an inequality, got {input} instead" + + # Case 2: number + if len(tokens) == 0: + return cls.single(number) + + # All other cases have an operand + operand = Operand.from_str(tokens.pop()) + assert operand is not None, f"got {number}, expected an operand afterward." + + # Case 3: number operand (id?) + if len(tokens) == 0 or len(tokens) == 1: + if len(tokens) == 1: assert is_id(tokens[1]) + return cls.right_operand(number, operand) + + # Case 4: number operand id operand number + id = tokens.pop() + assert is_id(id), f"got an inequality of the form {number} {operand.value} and expected nothing or another identifier, but got {id} instead." + + second_operand_str = tokens.pop() + second_operand = Operand.from_str(second_operand_str) + assert second_operand is not None, f"got an inequality of the form {number} {operand.value} {id} and was expecting an operand, but got {second_operand_str} instead." + + second_number_str = tokens.pop() + second_number = parse_num(second_number_str) + assert second_number is not None, f"got an inequality of the form {number} {operand.value} {id} {second_operand.value} and was expecting a number, but got {second_number_str} instead." + + # don't want equals operands in a double inequality (a < b < c) + assert operand is not Operand.EQ and second_operand is not Operand.EQ, f"in a double inequality, neither operand can be '='!" + + # are our two numbers valid? + combined_operand = Operand.combine(operand, second_operand) + assert combined_operand is not None, f"operands {operand.value} and {second_operand} must combine well with each other!" + assert combined_operand.compare(number, second_number), f"{number} {operand.value} {second_number} does not hold!" + + return cls( + lower=number, + upper=second_number, + lower_closed=operand.is_closed(), + upper_closed=second_operand.is_closed() + ) + + def __str__(self) -> str: + if not self.lower and not self.upper: return "{empty interval}" + if not self.lower: + return Operand.LT.with_closed(self.upper_closed).value + " " + str(self.upper) + if not self.upper: + return str(self.lower) + " " + Operand.LT.with_closed(self.lower_closed).value + + if self.lower == self.upper and self.lower_closed and self.upper_closed: return str(self.lower) + + return str(self.lower) + " " + Operand.LT.with_closed(self.lower_closed).value + " " + "x" \ + + Operand.LT.with_closed(self.upper_closed).value + str(self.upper) + + # For parsing Intervals automatically with pydantic. + @model_validator(mode="before") + @classmethod + def from_literal(cls, data: Any) -> Any: + if isinstance(data, str): + return cls.from_string(data) + return data From 898d568a49053467d74af1cb952bdceac400436d Mon Sep 17 00:00:00 2001 From: "Tristan F." Date: Wed, 29 Oct 2025 18:15:23 -0700 Subject: [PATCH 06/16] style: specify zip strict --- spras/statistics.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/spras/statistics.py b/spras/statistics.py index 49ae8b3fc..1ebe7cc62 100644 --- a/spras/statistics.py +++ b/spras/statistics.py @@ -82,7 +82,7 @@ def compute_statistics(graph: nx.DiGraph, statistics: list[str]) -> dict[str, fl computed_tuple = compute(graph) assert len(statistic_tuple) == len(computed_tuple), f"bad tuple length for {statistic_tuple}" - current_computed_statistics = zip(statistic_tuple, computed_tuple) + current_computed_statistics = zip(statistic_tuple, computed_tuple, strict=True) for stat, value in current_computed_statistics: computed_statistics[stat] = value From 8177ed665b13714e56991eaef8ee45e96c1f0dbb Mon Sep 17 00:00:00 2001 From: "Tristan F." Date: Thu, 30 Oct 2025 01:41:12 +0000 Subject: [PATCH 07/16] refactor: use heuristic error, mv heuristics outside of main schema file --- spras/config/heuristics.py | 69 ++++++++++++++++++++++++++++++++++++++ spras/config/schema.py | 49 +-------------------------- 2 files changed, 70 insertions(+), 48 deletions(-) create mode 100644 spras/config/heuristics.py diff --git a/spras/config/heuristics.py b/spras/config/heuristics.py new file mode 100644 index 000000000..3f42c6aba --- /dev/null +++ b/spras/config/heuristics.py @@ -0,0 +1,69 @@ +import networkx as nx +from pydantic import BaseModel, ConfigDict +from spras.interval import Interval +from spras.statistics import compute_statistics, statistics_options + +class GraphHeuristicError(RuntimeError): + """ + Represents an error arising from a graph algorithm output + not meeting the necessary graph heuristisc. + """ + failed_heuristics: list[tuple[str, float | int, list[Interval]]] + + @staticmethod + def to_string(failed_heuristics: list[tuple[str, float | int, list[Interval]]]): + return f"The following heuristics failed: {failed_heuristics}" + + def __init__(self, failed_heuristics: list[tuple[str, float | int, list[Interval]]]): + super().__init__(GraphHeuristicError.to_string(failed_heuristics)) + + self.failed_heuristics = failed_heuristics + + def __str__(self) -> str: + return GraphHeuristicError.to_string(self.failed_heuristics) + +class GraphHeuristics(BaseModel): + number_of_nodes: Interval | list[Interval] = [] + number_of_edges: Interval | list[Interval] = [] + number_of_connected_components: Interval | list[Interval] = [] + density: Interval | list[Interval] = [] + + max_degree: Interval | list[Interval] = [] + median_degree: Interval | list[Interval] = [] + max_diameter: Interval | list[Interval] = [] + average_path_length: Interval | list[Interval] = [] + + def validate_graph(self, graph: nx.DiGraph): + statistics_dictionary = { + 'Number of nodes': self.number_of_nodes, + 'Number of edges': self.number_of_edges, + 'Number of connected components': self.number_of_connected_components, + 'Density': self.density, + 'Max degree': self.max_degree, + 'Median degree': self.median_degree, + 'Max diameter': self.max_diameter, + 'Average path length': self.average_path_length + } + + # quick assert: is statistics_dictionary exhaustive? + assert set(statistics_dictionary.keys()) == set(statistics_options) + + stats = compute_statistics( + graph, + list(k for k, v in statistics_dictionary.items() if isinstance(v, list) and len(v) == 0) + ) + + failed_heuristics: list[tuple[str, float | int, list[Interval]]] = [] + for key, value in stats.items(): + intervals = statistics_dictionary[key] + if not isinstance(intervals, list): intervals = [intervals] + + for interval in intervals: + if interval.mem(value): + failed_heuristics.append((key, value, intervals)) + break + + if len(failed_heuristics) != 0: + raise GraphHeuristicError(failed_heuristics) + + model_config = ConfigDict(extra='forbid') diff --git a/spras/config/schema.py b/spras/config/schema.py index 846188e4c..3678a541c 100644 --- a/spras/config/schema.py +++ b/spras/config/schema.py @@ -13,13 +13,11 @@ import re from typing import Annotated, Optional -import networkx as nx from pydantic import AfterValidator, BaseModel, ConfigDict from spras.config.container_schema import ContainerSettings +from spras.config.heuristics import GraphHeuristics from spras.config.util import CaseInsensitiveEnum -from spras.interval import Interval -from spras.statistics import compute_statistics, statistics_options # Most options here have an `include` property, # which is meant to make disabling parts of the configuration easier. @@ -140,51 +138,6 @@ class ReconstructionSettings(BaseModel): model_config = ConfigDict(extra='forbid') -class GraphHeuristics(BaseModel): - number_of_nodes: list[Interval] = [] - number_of_edges: list[Interval] = [] - number_of_connected_components: list[Interval] = [] - density: list[Interval] = [] - - max_degree: list[Interval] = [] - median_degree: list[Interval] = [] - max_diameter: list[Interval] = [] - average_path_length: list[Interval] = [] - - def validate_graph(self, graph: nx.DiGraph): - statistics_dictionary = { - 'Number of nodes': self.number_of_nodes, - 'Number of edges': self.number_of_edges, - 'Number of connected components': self.number_of_connected_components, - 'Density': self.density, - 'Max degree': self.max_degree, - 'Median degree': self.median_degree, - 'Max diameter': self.max_diameter, - 'Average path length': self.average_path_length - } - - # quick assert: is statistics_dictionary exhaustive? - assert set(statistics_dictionary.keys()) == set(statistics_options) - - stats = compute_statistics( - graph, - list(k for k, v in statistics_dictionary.items() if len(v) == 0) - ) - - for key, value in stats.items(): - intervals = statistics_dictionary[key] - - matches_heuristics = False - for interval in intervals: - if interval.mem(value): - matches_heuristics = True - break - - if not matches_heuristics: - raise RuntimeError(f"Heuristic {key} with value {value} does not match {intervals}!") - - model_config = ConfigDict(extra='forbid') - class RawConfig(BaseModel): containers: ContainerSettings enable_profiling: bool = False From fac110847104dd77fa46bcb3d67bd8af4d4df6c7 Mon Sep 17 00:00:00 2001 From: "Tristan F." Date: Thu, 30 Oct 2025 06:34:20 +0000 Subject: [PATCH 08/16] fix: proper tokenization --- spras/config/heuristics.py | 4 +++- spras/interval.py | 30 ++++++++++++++++++------------ 2 files changed, 21 insertions(+), 13 deletions(-) diff --git a/spras/config/heuristics.py b/spras/config/heuristics.py index 3f42c6aba..99ecb4695 100644 --- a/spras/config/heuristics.py +++ b/spras/config/heuristics.py @@ -1,8 +1,10 @@ import networkx as nx from pydantic import BaseModel, ConfigDict + from spras.interval import Interval from spras.statistics import compute_statistics, statistics_options + class GraphHeuristicError(RuntimeError): """ Represents an error arising from a graph algorithm output @@ -18,7 +20,7 @@ def __init__(self, failed_heuristics: list[tuple[str, float | int, list[Interval super().__init__(GraphHeuristicError.to_string(failed_heuristics)) self.failed_heuristics = failed_heuristics - + def __str__(self) -> str: return GraphHeuristicError.to_string(self.failed_heuristics) diff --git a/spras/interval.py b/spras/interval.py index 6771a228b..6b304075d 100644 --- a/spras/interval.py +++ b/spras/interval.py @@ -7,10 +7,14 @@ [If there is ever a library that does this, we should replace this code with that library.] """ +import tokenize from enum import Enum +from io import BytesIO from typing import Any, Optional, Self + from pydantic import BaseModel, model_validator + class Operand(Enum): LT = "<" LTE = "<=" @@ -21,7 +25,7 @@ class Operand(Enum): @classmethod def from_str(cls, string: str) -> Optional[Self]: return next((enum for enum in list(cls) if enum.value == string), None) - + def is_closed(self) -> bool: """Whether this is a closed inequality. We consider = to be closed.""" match self: @@ -43,7 +47,7 @@ def as_opened(self): case Operand.LTE: return Operand.LT case Operand.GTE: return Operand.GT return self - + def with_closed(self, closed: bool): return self.as_closed() if closed else self.as_opened() def compare(self, left, right) -> bool: @@ -53,7 +57,7 @@ def compare(self, left, right) -> bool: case Operand.EQ: return left == right case Operand.GTE: return left >= right case Operand.GT: return left > right - + @classmethod def combine(cls, left: Self, right: Self): """Combines two operands, returning None if the operands don't combine well.""" @@ -79,12 +83,12 @@ def mem(self, num: float) -> bool: meets_lower = self.lower <= num if self.lower_closed else self.lower < num else: meets_lower = True - + if self.upper is not None: meets_upper = num <= self.upper if self.upper_closed else num < self.upper else: meets_upper = True - + return meets_lower and meets_upper @classmethod @@ -113,8 +117,10 @@ def right_operand(cls, num: float, operand: Operand) -> Self: @classmethod def from_string(cls, input: str) -> Self: - tokens = [token.strip() for token in input.split(" ")] - + # We can't do a normal string#split here for cases like "1500<" + tokens = [t.string for t in tokenize.tokenize(BytesIO(input.encode('utf-8')).readline) if t.string != ""] + tokens.pop() # drop utf-8 indicator + assert len(tokens) != 0 def parse_num(numstr: str) -> Optional[int]: @@ -130,18 +136,18 @@ def is_id(idstr: str) -> bool: return idstr.isidentifier() if is_id(tokens[0]): # No other cases have an id at the beginning: we get rid of it. tokens.pop() - + operand = Operand.from_str(tokens[0]) if operand is not None: # (cont.) Case 1: (id?) operand number number = parse_num(tokens[1]) assert number is not None, f"found operand {operand.value} and expected a number, but found {tokens[1]} instead." return cls.left_operand(operand, number) - + # All other cases have a number number = parse_num(tokens.pop()) assert number is not None, f"expected an inequality, got {input} instead" - + # Case 2: number if len(tokens) == 0: return cls.single(number) @@ -158,7 +164,7 @@ def is_id(idstr: str) -> bool: return idstr.isidentifier() # Case 4: number operand id operand number id = tokens.pop() assert is_id(id), f"got an inequality of the form {number} {operand.value} and expected nothing or another identifier, but got {id} instead." - + second_operand_str = tokens.pop() second_operand = Operand.from_str(second_operand_str) assert second_operand is not None, f"got an inequality of the form {number} {operand.value} {id} and was expecting an operand, but got {second_operand_str} instead." @@ -174,7 +180,7 @@ def is_id(idstr: str) -> bool: return idstr.isidentifier() combined_operand = Operand.combine(operand, second_operand) assert combined_operand is not None, f"operands {operand.value} and {second_operand} must combine well with each other!" assert combined_operand.compare(number, second_number), f"{number} {operand.value} {second_number} does not hold!" - + return cls( lower=number, upper=second_number, From 2e0d8d0faec96ffd5fcfb49496645f9464e3f24c Mon Sep 17 00:00:00 2001 From: "Tristan F." Date: Thu, 30 Oct 2025 07:13:24 +0000 Subject: [PATCH 09/16] fix(interval): correct parsing --- spras/interval.py | 16 ++++++++-------- test/test_interval.py | 6 ++++++ 2 files changed, 14 insertions(+), 8 deletions(-) create mode 100644 test/test_interval.py diff --git a/spras/interval.py b/spras/interval.py index 6b304075d..52e4ab802 100644 --- a/spras/interval.py +++ b/spras/interval.py @@ -119,7 +119,7 @@ def right_operand(cls, num: float, operand: Operand) -> Self: def from_string(cls, input: str) -> Self: # We can't do a normal string#split here for cases like "1500<" tokens = [t.string for t in tokenize.tokenize(BytesIO(input.encode('utf-8')).readline) if t.string != ""] - tokens.pop() # drop utf-8 indicator + tokens.pop(0) # drop utf-8 indicator assert len(tokens) != 0 @@ -135,7 +135,7 @@ def is_id(idstr: str) -> bool: return idstr.isidentifier() # Case 1: (id?) operand number if is_id(tokens[0]): # No other cases have an id at the beginning: we get rid of it. - tokens.pop() + tokens.pop(0) operand = Operand.from_str(tokens[0]) if operand is not None: @@ -145,15 +145,15 @@ def is_id(idstr: str) -> bool: return idstr.isidentifier() return cls.left_operand(operand, number) # All other cases have a number - number = parse_num(tokens.pop()) - assert number is not None, f"expected an inequality, got {input} instead" + number = parse_num(tokens.pop(0)) + assert number is not None, f"expected a number, got {input} instead" # Case 2: number if len(tokens) == 0: return cls.single(number) # All other cases have an operand - operand = Operand.from_str(tokens.pop()) + operand = Operand.from_str(tokens.pop(0)) assert operand is not None, f"got {number}, expected an operand afterward." # Case 3: number operand (id?) @@ -162,14 +162,14 @@ def is_id(idstr: str) -> bool: return idstr.isidentifier() return cls.right_operand(number, operand) # Case 4: number operand id operand number - id = tokens.pop() + id = tokens.pop(0) assert is_id(id), f"got an inequality of the form {number} {operand.value} and expected nothing or another identifier, but got {id} instead." - second_operand_str = tokens.pop() + second_operand_str = tokens.pop(0) second_operand = Operand.from_str(second_operand_str) assert second_operand is not None, f"got an inequality of the form {number} {operand.value} {id} and was expecting an operand, but got {second_operand_str} instead." - second_number_str = tokens.pop() + second_number_str = tokens.pop(0) second_number = parse_num(second_number_str) assert second_number is not None, f"got an inequality of the form {number} {operand.value} {id} {second_operand.value} and was expecting a number, but got {second_number_str} instead." diff --git a/test/test_interval.py b/test/test_interval.py new file mode 100644 index 000000000..e263817bc --- /dev/null +++ b/test/test_interval.py @@ -0,0 +1,6 @@ +from spras.interval import Interval + +class TestInterval: + def test_number(self): + assert Interval.single(5) == Interval(lower=5, upper=5, lower_closed=True, upper_closed=True) + assert Interval.from_string("5") == Interval.single(5) From 183c3ad874fad9096ced9aa4cc4c6ccd88769687 Mon Sep 17 00:00:00 2001 From: "Tristan F." Date: Thu, 30 Oct 2025 07:30:19 +0000 Subject: [PATCH 10/16] fix(interval): correct other parsing mistakes --- spras/interval.py | 53 ++++++++++++++++++++++++++++--------------- test/test_interval.py | 11 +++++++++ 2 files changed, 46 insertions(+), 18 deletions(-) diff --git a/spras/interval.py b/spras/interval.py index 52e4ab802..7e5f6c663 100644 --- a/spras/interval.py +++ b/spras/interval.py @@ -10,7 +10,7 @@ import tokenize from enum import Enum from io import BytesIO -from typing import Any, Optional, Self +from typing import Any, Optional, Self, cast from pydantic import BaseModel, model_validator @@ -31,7 +31,7 @@ def is_closed(self) -> bool: match self: case Operand.LTE: return True case Operand.EQ: return True - case Operand.GT: return True + case Operand.GTE: return True return False def as_closed(self): @@ -57,6 +57,14 @@ def compare(self, left, right) -> bool: case Operand.EQ: return left == right case Operand.GTE: return left >= right case Operand.GT: return left > right + + def flip(self): + match self: + case Operand.LT: return Operand.GT + case Operand.LTE: return Operand.GTE + case Operand.EQ: return Operand.EQ + case Operand.GTE: return Operand.LTE + case Operand.GT: return Operand.LT @classmethod def combine(cls, left: Self, right: Self): @@ -64,11 +72,13 @@ def combine(cls, left: Self, right: Self): match (left, right): case (Operand.LTE, Operand.LTE): return Operand.LTE case (Operand.LT, Operand.LTE): return Operand.LT + case (Operand.LTE, Operand.LT): return Operand.LT case (Operand.LT, Operand.LT): return Operand.LT case (Operand.EQ, op): return op case (op, Operand.EQ): return op case (Operand.GTE, Operand.GTE): return Operand.GTE case (Operand.GT, Operand.GTE): return Operand.GT + case (Operand.GTE, Operand.GT): return Operand.GT case (Operand.GT, Operand.GT): return Operand.GT return None @@ -108,12 +118,8 @@ def left_operand(cls, operand: Operand, num: float) -> Self: @classmethod def right_operand(cls, num: float, operand: Operand) -> Self: """Creates an interval whose operand is on the right (e.g. 300<)""" - match operand: - case Operand.LT: return cls(lower=num, upper=None, lower_closed=False, upper_closed=False) - case Operand.LTE: return cls(lower=num, upper=None, lower_closed=True, upper_closed=False) - case Operand.EQ: return cls.single(num) - case Operand.GTE: return cls(lower=None, upper=num, lower_closed=False, upper_closed=False) - case Operand.GT: return cls(lower=None, upper=num, lower_closed=False, upper_closed=True) + # TODO: remove cast? + return cast(Self, Interval.left_operand(operand.flip(), num)) @classmethod def from_string(cls, input: str) -> Self: @@ -158,7 +164,7 @@ def is_id(idstr: str) -> bool: return idstr.isidentifier() # Case 3: number operand (id?) if len(tokens) == 0 or len(tokens) == 1: - if len(tokens) == 1: assert is_id(tokens[1]) + if len(tokens) == 1: assert is_id(tokens[0]) return cls.right_operand(number, operand) # Case 4: number operand id operand number @@ -178,15 +184,23 @@ def is_id(idstr: str) -> bool: return idstr.isidentifier() # are our two numbers valid? combined_operand = Operand.combine(operand, second_operand) - assert combined_operand is not None, f"operands {operand.value} and {second_operand} must combine well with each other!" + assert combined_operand is not None, f"operands {operand.value} and {second_operand.value} must combine well with each other!" assert combined_operand.compare(number, second_number), f"{number} {operand.value} {second_number} does not hold!" - return cls( - lower=number, - upper=second_number, - lower_closed=operand.is_closed(), - upper_closed=second_operand.is_closed() - ) + if combined_operand.as_opened() == Operand.LT: + return cls( + lower=number, + upper=second_number, + lower_closed=operand.is_closed(), + upper_closed=second_operand.is_closed() + ) + else: + return cls( + lower=second_number, + upper=number, + lower_closed=second_operand.is_closed(), + upper_closed=operand.is_closed() + ) def __str__(self) -> str: if not self.lower and not self.upper: return "{empty interval}" @@ -197,8 +211,11 @@ def __str__(self) -> str: if self.lower == self.upper and self.lower_closed and self.upper_closed: return str(self.lower) - return str(self.lower) + " " + Operand.LT.with_closed(self.lower_closed).value + " " + "x" \ - + Operand.LT.with_closed(self.upper_closed).value + str(self.upper) + return str(self.lower) + " " + Operand.LT.with_closed(self.lower_closed).value + " x " \ + + Operand.LT.with_closed(self.upper_closed).value + " " + str(self.upper) + + def __repr__(self) -> str: + return f"Interval[{str(self)}]" # For parsing Intervals automatically with pydantic. @model_validator(mode="before") diff --git a/test/test_interval.py b/test/test_interval.py index e263817bc..1c3b69a61 100644 --- a/test/test_interval.py +++ b/test/test_interval.py @@ -4,3 +4,14 @@ class TestInterval: def test_number(self): assert Interval.single(5) == Interval(lower=5, upper=5, lower_closed=True, upper_closed=True) assert Interval.from_string("5") == Interval.single(5) + + def test_string_permutations(self): + assert Interval.from_string("<5") == Interval.from_string("< 5") + assert Interval.from_string("5<") == Interval.from_string("5 < x") + assert Interval.from_string("6<") == Interval.from_string("x > 6") + assert Interval.from_string("100 <") == Interval.from_string(">100") + assert Interval.from_string("200 >= x > 100") == Interval.from_string("100 < x <= 200") + + def test_orientation(self): + assert Interval.from_string("10<").upper is None + assert Interval.from_string("10<").lower == 10.0 From 0b6e01f59bfc1e8a25f525194d6548c82a0b11b9 Mon Sep 17 00:00:00 2001 From: "Tristan F.-R." Date: Thu, 6 Nov 2025 00:02:39 +0000 Subject: [PATCH 11/16] feat: integrate heuristics --- Snakefile | 1 + spras/config/heuristics.py | 15 +++++++++++++++ spras/interval.py | 2 +- spras/util.py | 2 ++ test/test_interval.py | 5 +++-- 5 files changed, 22 insertions(+), 3 deletions(-) diff --git a/Snakefile b/Snakefile index 02f019e8d..ffb5c9f8c 100644 --- a/Snakefile +++ b/Snakefile @@ -295,6 +295,7 @@ rule parse_output: params = reconstruction_params(wildcards.algorithm, wildcards.params).copy() params['dataset'] = input.dataset_file runner.parse_output(wildcards.algorithm, input.raw_file, output.standardized_file, params) + _config.config.heuristics.validate_graph_from_file(output.standardized_file) # TODO: reuse in the future once we make summary work for mixed graphs. See https://github.com/Reed-CompBio/spras/issues/128 # Collect summary statistics for a single pathway diff --git a/spras/config/heuristics.py b/spras/config/heuristics.py index 99ecb4695..2c003fe64 100644 --- a/spras/config/heuristics.py +++ b/spras/config/heuristics.py @@ -1,3 +1,5 @@ +import os + import networkx as nx from pydantic import BaseModel, ConfigDict @@ -69,3 +71,16 @@ def validate_graph(self, graph: nx.DiGraph): raise GraphHeuristicError(failed_heuristics) model_config = ConfigDict(extra='forbid') + + def validate_graph_from_file(self, path: str | os.PathLike): + # TODO: re-use from summary.py once we have a mixed/hypergraph library + G = nx.read_edgelist(path, data=(('weight', float), ('Direction', str)), create_using=nx.DiGraph) + + # We explicitly use `list` here to stop add_edge + # from expanding our iterator infinitely. + for source, target, data in list(G.edges(data=True)): + if data["Direction"] == 'U': + G.add_edge(target, source, data) + pass + + return self.validate_graph(G) diff --git a/spras/interval.py b/spras/interval.py index 7e5f6c663..266997fd5 100644 --- a/spras/interval.py +++ b/spras/interval.py @@ -57,7 +57,7 @@ def compare(self, left, right) -> bool: case Operand.EQ: return left == right case Operand.GTE: return left >= right case Operand.GT: return left > right - + def flip(self): match self: case Operand.LT: return Operand.GT diff --git a/spras/util.py b/spras/util.py index ce2cc2f96..594a2a3ad 100644 --- a/spras/util.py +++ b/spras/util.py @@ -102,6 +102,8 @@ def raw_pathway_df(raw_pathway_file: str, sep: str = '\t', header: int = None) - return df +def output_pathw + def duplicate_edges(df: pd.DataFrame) -> tuple[pd.DataFrame, bool]: """ diff --git a/test/test_interval.py b/test/test_interval.py index 1c3b69a61..840f8d057 100644 --- a/test/test_interval.py +++ b/test/test_interval.py @@ -1,17 +1,18 @@ from spras.interval import Interval + class TestInterval: def test_number(self): assert Interval.single(5) == Interval(lower=5, upper=5, lower_closed=True, upper_closed=True) assert Interval.from_string("5") == Interval.single(5) - + def test_string_permutations(self): assert Interval.from_string("<5") == Interval.from_string("< 5") assert Interval.from_string("5<") == Interval.from_string("5 < x") assert Interval.from_string("6<") == Interval.from_string("x > 6") assert Interval.from_string("100 <") == Interval.from_string(">100") assert Interval.from_string("200 >= x > 100") == Interval.from_string("100 < x <= 200") - + def test_orientation(self): assert Interval.from_string("10<").upper is None assert Interval.from_string("10<").lower == 10.0 From 33e004f92c2ca09ee7956633f3fb210a5dcd83d8 Mon Sep 17 00:00:00 2001 From: "Tristan F.-R." Date: Thu, 6 Nov 2025 00:56:20 +0000 Subject: [PATCH 12/16] fix: drop random code --- spras/util.py | 2 -- 1 file changed, 2 deletions(-) diff --git a/spras/util.py b/spras/util.py index 594a2a3ad..ce2cc2f96 100644 --- a/spras/util.py +++ b/spras/util.py @@ -102,8 +102,6 @@ def raw_pathway_df(raw_pathway_file: str, sep: str = '\t', header: int = None) - return df -def output_pathw - def duplicate_edges(df: pd.DataFrame) -> tuple[pd.DataFrame, bool]: """ From c675eced3b62b8a62204d9f6105628e1cdc09045 Mon Sep 17 00:00:00 2001 From: "Tristan F." Date: Thu, 6 Nov 2025 02:22:45 +0000 Subject: [PATCH 13/16] fix: make undirected for determining number of connected components --- spras/statistics.py | 5 +++-- 1 file changed, 3 insertions(+), 2 deletions(-) diff --git a/spras/statistics.py b/spras/statistics.py index 1ebe7cc62..222051d23 100644 --- a/spras/statistics.py +++ b/spras/statistics.py @@ -24,7 +24,8 @@ def compute_degree(graph: nx.DiGraph) -> tuple[int, float]: degrees = [deg for _, deg in graph.degree()] return max(degrees), median(degrees) -def compute_on_cc(graph: nx.DiGraph) -> tuple[int, float]: +def compute_on_cc(directed_graph: nx.DiGraph) -> tuple[int, float]: + graph: nx.Graph = directed_graph.to_undirected() cc = list(nx.connected_components(graph)) # Save the max diameter # Use diameter only for components with ≥2 nodes (singleton components have diameter 0) @@ -52,7 +53,7 @@ def compute_on_cc(graph: nx.DiGraph) -> tuple[int, float]: statistics_computation: dict[tuple[str, ...], Callable[[nx.DiGraph], tuple[float | int, ...]]] = { ('Number of nodes',): lambda graph : (graph.number_of_nodes(),), ('Number of edges',): lambda graph : (graph.number_of_edges(),), - ('Number of connected components',): lambda graph : (nx.number_connected_components(graph),), + ('Number of connected components',): lambda graph : (nx.number_connected_components(graph.to_undirected()),), ('Density',): lambda graph : (nx.density(graph),), ('Max degree', 'Median degree'): compute_degree, From 1cdaf121c84e08bb8a2c9c607e3286ffdbfdda0a Mon Sep 17 00:00:00 2001 From: "Tristan F." Date: Wed, 5 Nov 2025 18:23:13 -0800 Subject: [PATCH 14/16] fix: specify heuristics in wrapping config object --- Snakefile | 2 ++ spras/config/config.py | 2 ++ spras/config/heuristics.py | 4 ++-- 3 files changed, 6 insertions(+), 2 deletions(-) diff --git a/Snakefile b/Snakefile index ffb5c9f8c..65e24f15d 100644 --- a/Snakefile +++ b/Snakefile @@ -295,6 +295,8 @@ rule parse_output: params = reconstruction_params(wildcards.algorithm, wildcards.params).copy() params['dataset'] = input.dataset_file runner.parse_output(wildcards.algorithm, input.raw_file, output.standardized_file, params) + # TODO: cache heuristics result, store partial heuristics configuration file + # to allow this rule to update when heuristics change _config.config.heuristics.validate_graph_from_file(output.standardized_file) # TODO: reuse in the future once we make summary work for mixed graphs. See https://github.com/Reed-CompBio/spras/issues/128 diff --git a/spras/config/config.py b/spras/config/config.py index 25e6f72de..51d3daf3b 100644 --- a/spras/config/config.py +++ b/spras/config/config.py @@ -78,6 +78,8 @@ def __init__(self, raw_config: dict[str, Any]): self.container_settings = ProcessedContainerSettings.from_container_settings(parsed_raw_config.containers, self.hash_length) # The list of algorithms to run in the workflow. Each is a dict with 'name' as an expected key. self.algorithms = None + # The heuristic handler + self.heuristics = parsed_raw_config.heuristics # A nested dict mapping algorithm names to dicts that map parameter hashes to parameter combinations. # Only includes algorithms that are set to be run with 'include: true'. self.algorithm_params = None diff --git a/spras/config/heuristics.py b/spras/config/heuristics.py index 2c003fe64..f5f9ea24c 100644 --- a/spras/config/heuristics.py +++ b/spras/config/heuristics.py @@ -74,13 +74,13 @@ def validate_graph(self, graph: nx.DiGraph): def validate_graph_from_file(self, path: str | os.PathLike): # TODO: re-use from summary.py once we have a mixed/hypergraph library - G = nx.read_edgelist(path, data=(('weight', float), ('Direction', str)), create_using=nx.DiGraph) + G: nx.DiGraph = nx.read_edgelist(path, data=(('Rank', str), ('Direction', str)), create_using=nx.DiGraph) # We explicitly use `list` here to stop add_edge # from expanding our iterator infinitely. for source, target, data in list(G.edges(data=True)): if data["Direction"] == 'U': - G.add_edge(target, source, data) + G.add_edge(target, source, data=data) pass return self.validate_graph(G) From 7b290dcb636309534ec3ccdeae06d34a1c077f1b Mon Sep 17 00:00:00 2001 From: "Tristan F." Date: Thu, 6 Nov 2025 08:31:13 +0000 Subject: [PATCH 15/16] feat: interval and heuristic testing --- spras/config/heuristics.py | 33 +++++++++++++++++++------ spras/interval.py | 30 +++++++++++++--------- test/heuristics/__init__.py | 0 test/heuristics/fixtures/empty.txt | 0 test/heuristics/fixtures/nonempty.txt | 1 + test/heuristics/fixtures/undirected.txt | 1 + test/heuristics/test_heuristics.py | 26 +++++++++++++++++++ test/test_interval.py | 3 +++ 8 files changed, 76 insertions(+), 18 deletions(-) create mode 100644 test/heuristics/__init__.py create mode 100644 test/heuristics/fixtures/empty.txt create mode 100644 test/heuristics/fixtures/nonempty.txt create mode 100644 test/heuristics/fixtures/undirected.txt create mode 100644 test/heuristics/test_heuristics.py diff --git a/spras/config/heuristics.py b/spras/config/heuristics.py index f5f9ea24c..52c4839c6 100644 --- a/spras/config/heuristics.py +++ b/spras/config/heuristics.py @@ -6,25 +6,40 @@ from spras.interval import Interval from spras.statistics import compute_statistics, statistics_options +all = ['GraphHeuristicsError', 'GraphHeuristic'] -class GraphHeuristicError(RuntimeError): +class GraphHeuristicsError(RuntimeError): """ Represents an error arising from a graph algorithm output not meeting the necessary graph heuristisc. """ failed_heuristics: list[tuple[str, float | int, list[Interval]]] + @staticmethod + def format_failed_heuristic(heuristic: tuple[str, float | int, list[Interval]]) -> str: + name, desired, intervals = heuristic + if len(intervals) == 1: + interval_string = str(intervals[0]) + else: + formatted_intervals = ", ".join([str(interval) for interval in intervals]) + interval_string = f"one of the intervals ({formatted_intervals})" + return f"{name} expected {desired} in interval {interval_string}" @staticmethod def to_string(failed_heuristics: list[tuple[str, float | int, list[Interval]]]): - return f"The following heuristics failed: {failed_heuristics}" + formatted_heuristics = [ + GraphHeuristicsError.format_failed_heuristic(heuristic) for heuristic in failed_heuristics + ] + + formatted_heuristics = "\n".join([f"- {formatted_heuristics}" for heuristic in formatted_heuristics]) + return f"The following heuristics failed:\n{formatted_heuristics}" def __init__(self, failed_heuristics: list[tuple[str, float | int, list[Interval]]]): - super().__init__(GraphHeuristicError.to_string(failed_heuristics)) + super().__init__(GraphHeuristicsError.to_string(failed_heuristics)) self.failed_heuristics = failed_heuristics def __str__(self) -> str: - return GraphHeuristicError.to_string(self.failed_heuristics) + return GraphHeuristicsError.to_string(self.failed_heuristics) class GraphHeuristics(BaseModel): number_of_nodes: Interval | list[Interval] = [] @@ -54,7 +69,7 @@ def validate_graph(self, graph: nx.DiGraph): stats = compute_statistics( graph, - list(k for k, v in statistics_dictionary.items() if isinstance(v, list) and len(v) == 0) + list(k for k, v in statistics_dictionary.items() if not isinstance(v, list) or len(v) != 0) ) failed_heuristics: list[tuple[str, float | int, list[Interval]]] = [] @@ -63,16 +78,20 @@ def validate_graph(self, graph: nx.DiGraph): if not isinstance(intervals, list): intervals = [intervals] for interval in intervals: - if interval.mem(value): + if not interval.mem(value): failed_heuristics.append((key, value, intervals)) break if len(failed_heuristics) != 0: - raise GraphHeuristicError(failed_heuristics) + raise GraphHeuristicsError(failed_heuristics) model_config = ConfigDict(extra='forbid') def validate_graph_from_file(self, path: str | os.PathLike): + """ + Takes in a graph produced by PRM#parse_output, + and throws a GraphHeuristicsError if it fails the heuristics in `self`. + """ # TODO: re-use from summary.py once we have a mixed/hypergraph library G: nx.DiGraph = nx.read_edgelist(path, data=(('Rank', str), ('Direction', str)), create_using=nx.DiGraph) diff --git a/spras/interval.py b/spras/interval.py index 266997fd5..b65f87a7c 100644 --- a/spras/interval.py +++ b/spras/interval.py @@ -10,9 +10,10 @@ import tokenize from enum import Enum from io import BytesIO -from typing import Any, Optional, Self, cast +from typing import Any, ClassVar, Optional, Self, cast -from pydantic import BaseModel, model_validator +from pydantic import model_serializer, model_validator +from pydantic.dataclasses import dataclass class Operand(Enum): @@ -82,7 +83,10 @@ def combine(cls, left: Self, right: Self): case (Operand.GT, Operand.GT): return Operand.GT return None -class Interval(BaseModel): +@dataclass +class Interval: + EMPTY_STRING: ClassVar[str] = "{empty interval}" + lower: Optional[float] upper: Optional[float] lower_closed: bool @@ -110,10 +114,10 @@ def left_operand(cls, operand: Operand, num: float) -> Self: """Creates an interval whose operand is on the left (e.g. <300)""" match operand: case Operand.LT: return cls(lower=None, upper=num, lower_closed=False, upper_closed=False) - case Operand.LTE: return cls(lower=None, upper=num, lower_closed=True, upper_closed=False) + case Operand.LTE: return cls(lower=None, upper=num, lower_closed=False, upper_closed=True) case Operand.EQ: return cls.single(num) - case Operand.GTE: return cls(lower=num, upper=None, lower_closed=False, upper_closed=False) - case Operand.GT: return cls(lower=num, upper=None, lower_closed=False, upper_closed=True) + case Operand.GTE: return cls(lower=num, upper=None, lower_closed=True, upper_closed=False) + case Operand.GT: return cls(lower=num, upper=None, lower_closed=False, upper_closed=False) @classmethod def right_operand(cls, num: float, operand: Operand) -> Self: @@ -203,10 +207,10 @@ def is_id(idstr: str) -> bool: return idstr.isidentifier() ) def __str__(self) -> str: - if not self.lower and not self.upper: return "{empty interval}" - if not self.lower: + if self.lower is None and self.upper is None: return Interval.EMPTY_STRING + if self.lower is None: return Operand.LT.with_closed(self.upper_closed).value + " " + str(self.upper) - if not self.upper: + if self.upper is None: return str(self.lower) + " " + Operand.LT.with_closed(self.lower_closed).value if self.lower == self.upper and self.lower_closed and self.upper_closed: return str(self.lower) @@ -221,6 +225,10 @@ def __repr__(self) -> str: @model_validator(mode="before") @classmethod def from_literal(cls, data: Any) -> Any: - if isinstance(data, str): - return cls.from_string(data) + if isinstance(data, int) or isinstance(data, float) or isinstance(data, str): + return vars(cls.from_string(str(data))) return data + + @model_serializer(mode='plain') + def serialize_model(self) -> str: + return str(self) diff --git a/test/heuristics/__init__.py b/test/heuristics/__init__.py new file mode 100644 index 000000000..e69de29bb diff --git a/test/heuristics/fixtures/empty.txt b/test/heuristics/fixtures/empty.txt new file mode 100644 index 000000000..e69de29bb diff --git a/test/heuristics/fixtures/nonempty.txt b/test/heuristics/fixtures/nonempty.txt new file mode 100644 index 000000000..8e9f8ac96 --- /dev/null +++ b/test/heuristics/fixtures/nonempty.txt @@ -0,0 +1 @@ +A B 1 D diff --git a/test/heuristics/fixtures/undirected.txt b/test/heuristics/fixtures/undirected.txt new file mode 100644 index 000000000..627d30073 --- /dev/null +++ b/test/heuristics/fixtures/undirected.txt @@ -0,0 +1 @@ +A B 1 U diff --git a/test/heuristics/test_heuristics.py b/test/heuristics/test_heuristics.py new file mode 100644 index 000000000..3512915e0 --- /dev/null +++ b/test/heuristics/test_heuristics.py @@ -0,0 +1,26 @@ +from pathlib import Path +import pytest + +from spras.config.heuristics import GraphHeuristics, GraphHeuristicsError + +FIXTURES_DIR = Path('test', 'heuristics', 'fixtures') + +class TestHeuristics: + def parse(self, heuristics: dict) -> GraphHeuristics: + return GraphHeuristics.model_validate(heuristics) + + def test_nonempty(self): + self.parse({ 'number_of_nodes': '>0', 'number_of_edges': '1' } + ).validate_graph_from_file(FIXTURES_DIR / 'nonempty.txt') + + def test_empty(self): + self.parse({ 'number_of_nodes': '<1' } + ).validate_graph_from_file(FIXTURES_DIR / 'empty.txt') + + with pytest.raises(GraphHeuristicsError): + self.parse({ 'number_of_nodes': '0<' } + ).validate_graph_from_file(FIXTURES_DIR / 'empty.txt') + + def test_undirected(self): + self.parse({ 'number_of_nodes': '1 < x < 3', 'number_of_edges': 2 } + ).validate_graph_from_file(FIXTURES_DIR / 'undirected.txt') \ No newline at end of file diff --git a/test/test_interval.py b/test/test_interval.py index 840f8d057..1481d1a79 100644 --- a/test/test_interval.py +++ b/test/test_interval.py @@ -6,6 +6,9 @@ def test_number(self): assert Interval.single(5) == Interval(lower=5, upper=5, lower_closed=True, upper_closed=True) assert Interval.from_string("5") == Interval.single(5) + def test_interval_gt_0(self): + assert Interval.from_string(">0") == Interval(lower=0, upper=None, lower_closed=False, upper_closed=False) + def test_string_permutations(self): assert Interval.from_string("<5") == Interval.from_string("< 5") assert Interval.from_string("5<") == Interval.from_string("5 < x") From 4844fd6917bb1fe7ee7006d82bfa3e73c6830fbb Mon Sep 17 00:00:00 2001 From: "Tristan F." Date: Thu, 6 Nov 2025 08:33:32 +0000 Subject: [PATCH 16/16] style: fmt --- test/heuristics/test_heuristics.py | 5 +++-- 1 file changed, 3 insertions(+), 2 deletions(-) diff --git a/test/heuristics/test_heuristics.py b/test/heuristics/test_heuristics.py index 3512915e0..8011f5377 100644 --- a/test/heuristics/test_heuristics.py +++ b/test/heuristics/test_heuristics.py @@ -1,4 +1,5 @@ from pathlib import Path + import pytest from spras.config.heuristics import GraphHeuristics, GraphHeuristicsError @@ -16,11 +17,11 @@ def test_nonempty(self): def test_empty(self): self.parse({ 'number_of_nodes': '<1' } ).validate_graph_from_file(FIXTURES_DIR / 'empty.txt') - + with pytest.raises(GraphHeuristicsError): self.parse({ 'number_of_nodes': '0<' } ).validate_graph_from_file(FIXTURES_DIR / 'empty.txt') def test_undirected(self): self.parse({ 'number_of_nodes': '1 < x < 3', 'number_of_edges': 2 } - ).validate_graph_from_file(FIXTURES_DIR / 'undirected.txt') \ No newline at end of file + ).validate_graph_from_file(FIXTURES_DIR / 'undirected.txt')