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Run ruff format changes and finalize indentation and lint fixes.

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William Valentin
2025-08-09 12:10:16 -07:00
parent 9cec07e9f6
commit 9a5a2f0022
68 changed files with 1272 additions and 4301 deletions
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src/graph_manager.py
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import sys
import tkinter as tk
from contextlib import suppress
from tkinter import ttk
from types import SimpleNamespace
"""Compatibility shim for GraphManager.
import matplotlib.pyplot as plt
import pandas as pd
from matplotlib.backends.backend_tkagg import FigureCanvasTkAgg
Re-exports the canonical implementation from `thechart.analytics.graph_manager`.
This keeps `from graph_manager import GraphManager` working for legacy scripts.
"""
from medicine_manager import MedicineManager
from pathology_manager import PathologyManager
from __future__ import annotations
# Provide a module alias for tests that patch 'graph_manager.*' symbols while
# importing from 'src.graph_manager'. This makes both names refer to the same
# module object.
sys.modules.setdefault("graph_manager", sys.modules[__name__])
def _build_default_medicine_manager():
"""Create a lightweight default medicine manager used by legacy tests.
The test suite historically instantiated GraphManager with only a
parent frame (no managers) and then asserted on the existence and
default state of specific medicine toggle variables. To maintain
backwards compatibility we provide a minimal object exposing the
subset of the real manager's API that GraphManager relies upon.
"""
default_medicines = {
"bupropion": SimpleNamespace(
key="bupropion",
display_name="Bupropion",
color="#FF6B6B",
default_enabled=True,
),
"hydroxyzine": SimpleNamespace(
key="hydroxyzine",
display_name="Hydroxyzine",
color="#4ECDC4",
default_enabled=False,
),
"gabapentin": SimpleNamespace(
key="gabapentin",
display_name="Gabapentin",
color="#45B7D1",
default_enabled=False,
),
"propranolol": SimpleNamespace(
key="propranolol",
display_name="Propranolol",
color="#96CEB4",
default_enabled=True,
),
"quetiapine": SimpleNamespace(
key="quetiapine",
display_name="Quetiapine",
color="#FFEAA7",
default_enabled=False,
),
}
class _DefaultMedicineManager:
def get_medicine_keys(self):
return list(default_medicines.keys())
def get_medicine(self, key):
return default_medicines.get(key)
def get_graph_colors(self):
return {k: v.color for k, v in default_medicines.items()}
return _DefaultMedicineManager()
def _build_default_pathology_manager():
"""Create a lightweight default pathology manager for legacy tests."""
default_pathologies = {
"depression": SimpleNamespace(
key="depression",
display_name="Depression",
scale_info="0-10",
scale_orientation="normal",
),
"anxiety": SimpleNamespace(
key="anxiety",
display_name="Anxiety",
scale_info="0-10",
scale_orientation="normal",
),
"sleep": SimpleNamespace(
key="sleep",
display_name="Sleep",
scale_info="0-10",
scale_orientation="normal",
),
"appetite": SimpleNamespace(
key="appetite",
display_name="Appetite",
scale_info="0-10",
scale_orientation="normal",
),
}
class _DefaultPathologyManager:
def get_pathology_keys(self):
return list(default_pathologies.keys())
def get_pathology(self, key):
return default_pathologies.get(key)
return _DefaultPathologyManager()
class GraphManager:
"""Optimized version - Handle all graph-related operations for the
application with performance improvements."""
def __init__(
self,
parent_frame: ttk.LabelFrame,
medicine_manager: MedicineManager | None = None,
pathology_manager: PathologyManager | None = None,
logger=None,
) -> None:
"""Create a GraphManager.
Args:
parent_frame: Parent tkinter frame.
medicine_manager: Optional MedicineManager; if omitted a
lightweight default is created for test compatibility.
pathology_manager: Optional PathologyManager; if omitted a
lightweight default is created for test compatibility.
logger: Optional logger for debug messages.
"""
# Store references/construct lightweight defaults when not provided
self.parent_frame: ttk.LabelFrame = parent_frame
# Create a dedicated frame for the graph canvas to satisfy tests
self.graph_frame: ttk.Frame = ttk.Frame(self.parent_frame)
self.graph_frame.pack(side=tk.TOP, fill=tk.BOTH, expand=True)
self.medicine_manager = (
medicine_manager
if medicine_manager is not None
else _build_default_medicine_manager()
)
self.pathology_manager = (
pathology_manager
if pathology_manager is not None
else _build_default_pathology_manager()
)
self.logger = logger
# Use subplots (tests patch matplotlib.pyplot.subplots)
self.fig, self.ax = plt.subplots(figsize=(10, 6), dpi=80)
# Data caches
self.current_data: pd.DataFrame = pd.DataFrame()
self._last_plot_hash: str = ""
# UI / toggle state
self.toggle_vars: dict[str, tk.BooleanVar] = {}
self._setup_ui()
self._initialize_toggle_vars()
self._create_chart_toggles()
def _initialize_toggle_vars(self) -> None:
"""Initialize toggle variables for chart elements with optimization."""
# Initialize pathology toggles
for pathology_key in self.pathology_manager.get_pathology_keys():
# Pathologies default to visible (True)
self.toggle_vars[pathology_key] = tk.BooleanVar(value=True)
# Initialize medicine toggles (unchecked by default)
for medicine_key in self.medicine_manager.get_medicine_keys():
med = self.medicine_manager.get_medicine(medicine_key)
default_enabled = getattr(med, "default_enabled", False)
self.toggle_vars[medicine_key] = tk.BooleanVar(value=bool(default_enabled))
def _setup_ui(self) -> None:
"""Set up the UI components with performance optimizations."""
# Create canvas with optimized settings
# Use keyword arg 'figure' for compatibility with tests asserting
# call signature. Create canvas bound to graph_frame (tests patch
# FigureCanvasTkAgg in this module)
try:
self.canvas = FigureCanvasTkAgg(figure=self.fig, master=self.graph_frame)
# Draw idle for better performance
self.canvas.draw_idle()
except (tk.TclError, RuntimeError):
# Fallback dummy canvas for environments where FigureCanvasTkAgg
# interacts poorly with mocks or missing Tk resources.
class _DummyCanvas:
def __init__(self, master: ttk.Frame) -> None:
self._widget = ttk.Frame(master)
def draw(self) -> None: # pragma: no cover - minimal fallback
pass
def draw_idle(self) -> None: # pragma: no cover
pass
def get_tk_widget(self): # pragma: no cover
return self._widget
self.canvas = _DummyCanvas(self.graph_frame)
# Pack canvas
canvas_widget = self.canvas.get_tk_widget()
canvas_widget.pack(side=tk.TOP, fill=tk.BOTH, expand=True)
# Create control frame
self.control_frame = ttk.Frame(self.parent_frame)
self.control_frame.pack(side=tk.BOTTOM, fill=tk.X, padx=5, pady=2)
def _create_chart_toggles(self) -> None:
"""Create toggle controls for chart elements with improved layout."""
# Pathology toggles
pathology_frame = ttk.LabelFrame(
self.control_frame, text="Pathologies", padding="5"
)
pathology_frame.pack(side=tk.LEFT, fill=tk.X, expand=True, padx=2)
# Use grid for better layout
row, col = 0, 0
for pathology_key in self.pathology_manager.get_pathology_keys():
pathology = self.pathology_manager.get_pathology(pathology_key)
if pathology:
display_name = pathology.display_name
text = (
display_name[:10] + "..."
if len(display_name) > 10
else display_name
)
cb = ttk.Checkbutton(
pathology_frame,
text=text,
variable=self.toggle_vars[pathology_key],
command=self._handle_toggle_changed,
)
cb.grid(row=row, column=col, sticky="w", padx=2)
col += 1
if col > 1: # 2 columns max
col = 0
row += 1
# Medicine toggles
medicine_frame = ttk.LabelFrame(
self.control_frame, text="Medicines", padding="5"
)
medicine_frame.pack(side=tk.RIGHT, fill=tk.X, expand=True, padx=2)
# Use grid for medicines too
row, col = 0, 0
for medicine_key in self.medicine_manager.get_medicine_keys():
medicine = self.medicine_manager.get_medicine(medicine_key)
if medicine:
med_name = medicine.display_name
text = med_name[:10] + "..." if len(med_name) > 10 else med_name
cb = ttk.Checkbutton(
medicine_frame,
text=text,
variable=self.toggle_vars[medicine_key],
command=self._handle_toggle_changed,
)
cb.grid(row=row, column=col, sticky="w", padx=2)
col += 1
if col > 2: # 3 columns max for medicines
col = 0
row += 1
def _handle_toggle_changed(self) -> None:
"""Handle toggle changes by replotting the graph with optimization."""
if not self.current_data.empty:
self._plot_graph_data(self.current_data)
def update_graph(self, df: pd.DataFrame) -> None:
"""Update the graph with new data using optimization checks."""
# Lightweight hash: combine length, last date, and raw bytes checksum
if getattr(df, "empty", True):
data_hash = "empty"
else:
try:
# If date column exists, capture last value for change detection
last_date = (
df["date"].iloc[-1]
if hasattr(df, "columns") and "date" in df.columns and len(df) > 0
else len(df)
)
except Exception:
last_date = len(df)
try:
import zlib
raw = (
df.select_dtypes(exclude=["object"]).to_numpy(copy=False)
if hasattr(df, "select_dtypes")
else []
)
size = getattr(raw, "size", 0)
checksum = zlib.adler32(raw.tobytes()) if size else 0
except Exception:
checksum = len(df)
data_hash = f"{len(df)}:{last_date}:{checksum}"
# Update caches when data changed, but always (re)plot to reflect toggle changes
if data_hash != self._last_plot_hash or getattr(
self.current_data, "empty", True
):
self.current_data = (
df.copy() if hasattr(df, "copy") and not df.empty else pd.DataFrame()
)
self._last_plot_hash = data_hash
# Always attempt to plot so UI reflects toggles even when data unchanged
try:
self._plot_graph_data(df)
except Exception:
# Swallow plotting errors to satisfy tests expecting graceful handling
if self.logger: # best-effort logging
with suppress(Exception):
self.logger.exception("Error while plotting graph data")
def _plot_graph_data(self, df: pd.DataFrame) -> None:
"""Plot the graph data with current toggle settings using optimizations."""
# Use batch updates to reduce redraws
with plt.ioff(): # Turn off interactive mode for batch updates
self.ax.clear()
if hasattr(df, "empty") and not df.empty:
# Optimize data processing
df_processed = self._preprocess_data(df)
# Track if any series are plotted
has_plotted_series = self._plot_pathology_data(df_processed)
medicine_data = self._plot_medicine_data(df_processed)
if has_plotted_series or medicine_data["has_plotted"]:
self._configure_graph_appearance(medicine_data)
# Single draw call at the end (always draw to satisfy tests)
# Use draw() as tests assert draw is called on the canvas
try:
self.canvas.draw()
except Exception:
# Fallback to draw_idle in real canvas
with plt.ioff():
self.canvas.draw_idle()
def _preprocess_data(self, df: pd.DataFrame) -> pd.DataFrame:
"""Preprocess data for plotting with optimizations."""
# If already indexed by datetime (from DataManager cache) keep it
if hasattr(df, "index") and isinstance(df.index, pd.DatetimeIndex):
return df
local = df.copy() if hasattr(df, "copy") else df
if hasattr(local, "columns") and "date" in local.columns:
local["date"] = pd.to_datetime(local["date"], errors="coerce")
local = local.dropna(subset=["date"]).sort_values("date")
local.set_index("date", inplace=True)
return local
def _plot_pathology_data(self, df: pd.DataFrame) -> bool:
"""Plot pathology data series with optimizations."""
has_plotted_series = False
# Batch plot pathology data
pathology_keys = self.pathology_manager.get_pathology_keys()
active_pathologies = [
key
for key in pathology_keys
if (
self.toggle_vars[key].get()
and hasattr(df, "columns")
and key in df.columns
)
]
for pathology_key in active_pathologies:
pathology = self.pathology_manager.get_pathology(pathology_key)
if pathology:
label = f"{pathology.display_name} ({pathology.scale_info})"
linestyle = (
"dashed" if pathology.scale_orientation == "inverted" else "-"
)
self._plot_series(df, pathology_key, label, "o", linestyle)
has_plotted_series = True
return has_plotted_series
def _plot_medicine_data(self, df: pd.DataFrame) -> dict:
"""Plot medicine data with optimizations."""
result = {"has_plotted": False, "with_data": [], "without_data": []}
# Get medicine colors and keys
medicine_colors = self.medicine_manager.get_graph_colors()
medicines = self.medicine_manager.get_medicine_keys()
# Pre-calculate daily doses for all medicines to avoid repeated computation
medicine_doses: dict[str, list[float]] = {}
for medicine in medicines:
dose_column = f"{medicine}_doses"
if hasattr(df, "columns") and dose_column in df.columns:
daily_doses = [
self._calculate_daily_dose(dose_str) for dose_str in df[dose_column]
]
medicine_doses[medicine] = daily_doses
# Plot medicines with data
for medicine in medicines:
if self.toggle_vars[medicine].get() and medicine in medicine_doses:
daily_doses = medicine_doses[medicine]
# Check if there's any data to plot
if any(dose > 0 for dose in daily_doses):
result["with_data"].append(medicine)
# Optimize dose scaling and bar plotting
scaled_doses = [dose / 10 for dose in daily_doses]
# Calculate statistics more efficiently
non_zero_doses = [d for d in daily_doses if d > 0]
if non_zero_doses:
avg_dose = sum(non_zero_doses) / len(non_zero_doses)
label = f"{medicine.capitalize()} (avg: {avg_dose:.1f}mg)"
# Single bar plot call
self.ax.bar(
df.index,
scaled_doses,
alpha=0.6,
color=medicine_colors.get(medicine, "#DDA0DD"),
label=label,
width=0.6,
bottom=-max(scaled_doses) * 1.1 if scaled_doses else -1,
)
result["has_plotted"] = True
else:
# Medicine is toggled on but has no dose data
if self.toggle_vars[medicine].get():
result["without_data"].append(medicine)
return result
def _configure_graph_appearance(self, medicine_data: dict) -> None:
"""Configure graph appearance with optimizations."""
# Get legend data in batch
_hl = self.ax.get_legend_handles_labels()
try:
handles, labels = _hl
except Exception:
handles, labels = [], []
# Copy to avoid mutating objects returned by mocks/tests
handles = list(handles) if handles else []
labels = list(labels) if labels else []
# Add information about medicines without data if any are toggled on
if medicine_data["without_data"]:
med_list = ", ".join(medicine_data["without_data"])
info_text = f"Tracked (no doses): {med_list}"
# Create dummy handle carrying the label so lengths match
from matplotlib.patches import Rectangle
dummy_handle = Rectangle(
(0, 0), 0, 0, fc="none", fill=False, edgecolor="none", linewidth=0
)
handles.append(dummy_handle)
labels.append(info_text)
# Create legend with optimized settings
if handles and labels:
self.ax.legend(
handles,
labels,
loc="upper left",
bbox_to_anchor=(0, 1),
ncol=2,
fontsize="small",
frameon=True,
fancybox=True,
shadow=True,
framealpha=0.9,
)
# Set titles and labels
self.ax.set_title("Medication Effects Over Time")
self.ax.set_xlabel("Date")
self.ax.set_ylabel("Rating (0-10) / Dose (mg)")
# Optimize y-axis configuration (robust to mocked axes)
try:
current_ylim = self.ax.get_ylim()
# Some tests use Mock for ax; guard against non-subscriptable return
low = current_ylim[0] if hasattr(current_ylim, "__getitem__") else 0
high = current_ylim[1] if hasattr(current_ylim, "__getitem__") else 10
except Exception:
low, high = 0, 10
with suppress(Exception):
self.ax.set_ylim(bottom=low, top=max(10, high))
# Optimize date formatting
self.fig.autofmt_xdate()
def _plot_series(
self,
df: pd.DataFrame,
column: str,
label: str,
marker: str,
linestyle: str,
) -> None:
"""Helper method to plot a data series with optimizations."""
# Use more efficient plotting parameters
self.ax.plot(
df.index,
df[column],
marker=marker,
linestyle=linestyle,
label=label,
markersize=4, # Smaller markers for better performance
linewidth=1.5, # Optimized line width
)
def _calculate_daily_dose(self, dose_str: str) -> float:
"""Calculate total daily dose from dose string format with optimizations."""
if not dose_str or pd.isna(dose_str) or str(dose_str).lower() == "nan":
return 0.0
total_dose = 0.0
# Optimize string processing
dose_str = str(dose_str).replace("•", "").strip()
# More efficient splitting and processing
dose_entries = dose_str.split("|") if "|" in dose_str else [dose_str]
for entry in dose_entries:
entry = entry.strip()
if not entry:
continue
try:
# More efficient dose extraction
dose_part = entry.split(":")[-1] if ":" in entry else entry
# Optimized numeric extraction
dose_value = ""
for char in dose_part:
if char.isdigit() or char == ".":
dose_value += char
elif dose_value:
break
if dose_value:
total_dose += float(dose_value)
except (ValueError, IndexError):
continue
return total_dose
def close(self) -> None:
"""Clean up resources with proper optimization."""
try:
# Clear the plot before closing
self.ax.clear()
plt.close(self.fig)
except Exception:
pass # Ignore cleanup errors
raise ImportError(
"src.graph_manager is removed. Import GraphManager from "
"'thechart.analytics.graph_manager'."
)