Add testing framework (#25)

* add fixture

* add test files

* add pytest to dev env

* setup logging in main

* format

* format

* add debug statements

* setup for future testing

* setup for future testing

* test analyze functions in quantify

* move fixture

* import fixtures

* make tests a python package

* add workflow for tests

* fix workflow

* set logging level to INFO

* format

.github/workflows/test-dev.yml

@@ -0,0 +1,43 @@
+name: CI Workflow
+
+on:
+  push:
+    branches:
+      - '**'
+  pull_request:
+    types: [opened, reopened, synchronize]
+
+jobs:
+  tests:
+    name: Tests (${{ matrix.os }})
+    runs-on: ${{ matrix.os }}
+    strategy:
+      fail-fast: false
+      matrix:
+        os: ["ubuntu-22.04", "windows-2022", "macos-14"]
+        include:
+          - env_file: environment.yaml
+
+    steps:
+      - name: Checkout repo
+        uses: actions/checkout@v4
+
+      - name: Setup Conda
+        uses: conda-incubator/[email protected]
+        with:
+          miniforge-version: latest
+          conda-solver: "libmamba"
+          environment-file: ${{ matrix.env_file }}
+          activate-environment: ariadne_dev
+
+      - name: Print environment info
+        shell: bash -l {0}
+        run: |
+          which python
+          conda info
+          conda list
+          pip freeze
+
+      - name: Run tests
+        shell: bash -l {0}
+        run: pytest tests/

environment.yaml

@@ -9,6 +9,7 @@ dependencies:
   - numpy
   - scipy
   - matplotlib
+  - pytest # for testing
   - pip
   - pip:
     - -e .

src/ariadne_roots/main.py

@@ -16,6 +16,7 @@
 import copy
 import networkx as nx
 import json
+import logging
 
 from pathlib import Path
 from queue import Queue
@@ -28,14 +29,20 @@
 from ariadne_roots import quantify
 
 
+# Set up logging
+logging.basicConfig(
+    level=logging.INFO,
+    format="%(asctime)s - %(name)s - %(levelname)s - %(message)s",
+)
+
+
 class StartupUI:
     """Startup window interface."""
 
     def __init__(self, base):
         self.base = base
         self.base.geometry("350x200")
 
-
         # master frame
         self.frame = tk.Frame(self.base)
         self.frame.pack(side="top", fill="both", expand=True)
@@ -123,7 +130,7 @@ def __init__(self, base):
             self.menu, text="Zoom In (+)", command=None, state="disabled"
         )
         self.button_zoom_out = tk.Button(
-             self.menu, text="Zoom Out (-)", command=None, state="disabled"
+            self.menu, text="Zoom Out (-)", command=None, state="disabled"
         )
         self.button_import.pack(fill="x", side="top")
         self.button_prev.pack(fill="x", side="top")
@@ -208,11 +215,14 @@ def __init__(self, base):
 
     def ask_zoom_factor(self):
         """Prompt user to select a zoom factor after importing the first image."""
+
         def on_ok():
             try:
                 # Retrieve the scale factor from the statusbar
                 zoom = self.scale_factor
-                print(f"Zoom factor selected: {zoom}")  # Debug print, remove if unnecessary
+                print(
+                    f"Zoom factor selected: {zoom}"
+                )  # Debug print, remove if unnecessary
                 self.zoom_factor = zoom  # Store zoom factor
                 zoom_popup.destroy()
             except ValueError:
@@ -235,7 +245,6 @@ def on_cancel():
         cancel_button = tk.Button(zoom_popup, text="Cancel", command=on_cancel)
         cancel_button.pack(side="right", padx=20)
 
-
     def click_info(self, event):
         """Show node metadata on right click (for debugging)."""
         for n in self.tree.nodes:  # check click proximity to existing points
@@ -298,7 +307,6 @@ def import_image(self):
 
         self.frame_id = self.canvas.create_image(0, 0, image=self.img, anchor="nw")
 
-
         # create gif iterator for pagination
         self.iterframes = ImageSequence.Iterator(self.file)
         self.frame_index = 0
@@ -343,9 +351,8 @@ def import_image(self):
         self.canvas.bind("-", self.zoom_out)
 
         # Prompt user to choose zoom factor after importing the first image
-        #if not hasattr(self, 'zoom_factor'):
-            #self.ask_zoom_factor()
-
+        # if not hasattr(self, 'zoom_factor'):
+        # self.ask_zoom_factor()
 
     def change_frame(self, next_index):
         """Move frames in the GIF."""
@@ -494,8 +501,6 @@ def insert(self, event=None):
             if not self.prox_override:
                 self.override()
 
-
-
     def change_root(self, event=None):
         """Clear current tree, prompt for a new root, and reinitialize."""
 
@@ -517,19 +522,18 @@ def change_root(self, event=None):
         # Prompt for a new plant ID assignment and create a new tree
         self.tree.popup(self.base)
 
-
-# Zoom function
-    #zoom in
+    # Zoom function
+    # zoom in
     def zoom_in(self):
         self.scale_factor *= 1.5  # Increase scale
         self.update_image()
-        self.update_statusbar()   # Update the status bar with zoom info
+        self.update_statusbar()  # Update the status bar with zoom info
 
     # Zoom out
     def zoom_out(self):
         self.scale_factor /= 1.5  # Decrease scale
         self.update_image()
-        self.update_statusbar()   # Update the status bar with zoom info
+        self.update_statusbar()  # Update the status bar with zoom info
 
     def update_image(self):
         """Update the image on the canvas based on the scale factor."""
@@ -557,8 +561,8 @@ def update_statusbar(self):
         """Update the status bar text with scale factor and other information."""
         self.statusbar.config(
             text=f"{self.canvas.curr_coords}, {self.day_indicator}, "
-                 f"{self.override_indicator}, {self.inserting_indicator}, "
-                 f"Zoom Scale: {self.scale_factor}"
+            f"{self.override_indicator}, {self.inserting_indicator}, "
+            f"Zoom Scale: {self.scale_factor}"
         )
 
     def draw_edge(self, parent_node, child_node):
@@ -808,6 +812,7 @@ def make_file(self, event=None):
             json.dump(s, h)
             print(f"wrote to output {output_name}")
 
+
 class Node:
     """An (x,y,0) point along a root."""
 
@@ -918,7 +923,6 @@ def updater():
 
         base.wait_window(top)  # wait for a button to be pressed
 
-
     ##########################
     def insert_child(self, current_node, new):
         """Assign child when using insertion mode."""
@@ -977,7 +981,9 @@ def index_LRs(self):
             current_node = q.get()
             # arbitrarily, we assign LR indices left-to-right
             # sort by x-coordinate
-            current_node_children = sorted(current_node.children, key=lambda x: x.relcoords[0])
+            current_node_children = sorted(
+                current_node.children, key=lambda x: x.relcoords[0]
+            )
 
             for n in current_node_children:
                 if n.root_degree is None:  # only index nodes that haven't been already
@@ -1079,6 +1085,16 @@ def import_file(self):
                     w = csv.DictWriter(csvfile, fieldnames=results.keys())
                     w.writerow(results)
 
+                # debug
+                logging.debug(f"Total root length: {results['Total root length']}")
+                logging.debug(f"Travel distance: {results['Travel distance']}")
+                logging.debug(
+                    f"Total root length (random): {results['Total root length (random)']}"
+                )
+                logging.debug(
+                    f"Travel distance (random): {results['Travel distance (random)']}"
+                )
+
                 # make pareto plot and save
                 quantify.plot_all(
                     front,

src/ariadne_roots/pareto_functions.py

@@ -180,7 +180,9 @@ def pareto_cost(total_root_length, total_travel_distance, alpha):
     return cost
 
 
-def pareto_cost_3d_path_tortuosity(total_root_length, total_travel_distance, total_path_coverage, alpha, beta):
+def pareto_cost_3d_path_tortuosity(
+    total_root_length, total_travel_distance, total_path_coverage, alpha, beta
+):
     """
     Computes the pareto cost.
 
@@ -193,21 +195,25 @@ def pareto_cost_3d_path_tortuosity(total_root_length, total_travel_distance, tot
     When alpha = gamma = 0, beta = 1 => cost = total_travel_distance will be minimized
     When beta = gamma = 0, alpha = 1 => cost = total_root_length will be minimized
 
-    total_root_length: the sum of the lengths of the edges in the root network 
+    total_root_length: the sum of the lengths of the edges in the root network
         (a.k.a. material cost, wiring cost)
     total_travel_distance: the sum of the lengths of the shortest paths from every
-        lateral root tip to the base node of the network. (a.k.a. the satellite cost, 
+        lateral root tip to the base node of the network. (a.k.a. the satellite cost,
         conduction delay)
-    total_path_coverage: the sum of the tortuosity of all the root paths. The tortuosity per 
-        path is defined as the ratio of the actual path length to the shortest path 
-        length between the root and the root tip. The total root coverage is the sum of 
+    total_path_coverage: the sum of the tortuosity of all the root paths. The tortuosity per
+        path is defined as the ratio of the actual path length to the shortest path
+        length between the root and the root tip. The total root coverage is the sum of
         the tortuosity of all the root paths.
     """
     assert 0 <= alpha <= 1
     assert 0 <= beta <= 1
 
     gamma = 1 - alpha - beta
-    cost = alpha * total_root_length + beta * total_travel_distance - gamma * total_path_coverage
+    cost = (
+        alpha * total_root_length
+        + beta * total_travel_distance
+        - gamma * total_path_coverage
+    )
 
     return cost
 
@@ -501,14 +507,14 @@ def pareto_steiner_fast_3d_path_tortuosity(G, alpha, beta):
     When alpha = gamma = 0, beta = 1 => cost = total_travel_distance will be minimized
     When beta = gamma = 0, alpha = 1 => cost = total_root_length will be minimized
 
-    total_root_length: the sum of the lengths of the edges in the root network 
+    total_root_length: the sum of the lengths of the edges in the root network
         (a.k.a. material cost, wiring cost)
     total_travel_distance: the sum of the lengths of the shortest paths from every
-        lateral root tip to the base node of the network. (a.k.a. the satellite cost, 
+        lateral root tip to the base node of the network. (a.k.a. the satellite cost,
         conduction delay)
-    total_path_coverage: the sum of the tortuosity of all the root paths. The tortuosity per 
-        path is defined as the ratio of the actual path length to the shortest path 
-        length between the root and the root tip. The total root coverage is the sum of 
+    total_path_coverage: the sum of the tortuosity of all the root paths. The tortuosity per
+        path is defined as the ratio of the actual path length to the shortest path
+        length between the root and the root tip. The total root coverage is the sum of
         the tortuosity of all the root paths.
 
     The algorithm uses a greedy approach: always take the edge that will reduce the
@@ -703,7 +709,9 @@ def pareto_steiner_fast_3d_path_tortuosity(G, alpha, beta):
             H.nodes[n2]["distance_to_base"] = (
                 node_dist(H, n2, u) + H.nodes[u]["distance_to_base"]
             )
-            H.nodes[n2]["straight_distance_to_base"] = H.nodes[n2]["distance_to_base"] / node_dist(H, n2, base_node)
+            H.nodes[n2]["straight_distance_to_base"] = H.nodes[n2][
+                "distance_to_base"
+            ] / node_dist(H, n2, base_node)
 
         added_nodes += 1
     return H

tests/conftest.py

@@ -0,0 +1,3 @@
+from tests.fixtures import *
+
+# Import the test data from the fixtures.py file