Merge pull request #59 from azogue/remove-scipy-dependency

📦️ Remove `scipy` dependency

.pre-commit-config.yaml

@@ -13,7 +13,7 @@ repos:
       - id: ruff-format
 
   - repo: "https://github.com/pre-commit/pre-commit-hooks"
-    rev: "v4.5.0"
+    rev: "v4.6.0"
     hooks:
       - id: "end-of-file-fixer"
       - id: "trailing-whitespace"

CHANGELOG.md

@@ -5,6 +5,15 @@ All notable changes to this project will be documented in this file.
 The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/),
 and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
 
+## [0.11.0] - 📦️ Remove scipy dependency - 2024-04-08
+
+##### Changes
+
+- ⚡️ Use simple **1D interpolator** to project lines, instead of `scipy.interpolate.interp1d`
+- ✅ Add tests for convex hulls of given points
+- ⚡️ Use simple **convex hull algorithm**, to compute zones to group annotated points, instead of using `scipy.spatial.ConvexHull`
+- 📦️ Bump version, removing `scipy` dependency
+
 ## [0.10.0] - 📦 Migrate to pydantic v2 - 2024-04-07
 
 Move to recent versions of `pydantic`, and also upgrade internal _linters_, moving to `ruff-format`

psychrochart/chartdata.py

@@ -18,11 +18,10 @@
     GetVapPresFromHumRatio,
     isIP,
 )
-from scipy.interpolate import interp1d
 
 from psychrochart.models.curves import PsychroCurve, PsychroCurves
 from psychrochart.models.styles import AnnotationStyle, CurveStyle
-from psychrochart.util import solve_curves_with_iteration
+from psychrochart.util import Interp1D, solve_curves_with_iteration
 
 f_vec_hum_ratio_from_vap_press = np.vectorize(GetHumRatioFromVapPres)
 f_vec_moist_air_enthalpy = np.vectorize(GetMoistAirEnthalpy)
@@ -273,12 +272,7 @@ def make_constant_enthalpy_lines(
         )
         / _factor_out_h()
     )
-    t_sat_interpolator = interp1d(
-        h_in_sat,
-        saturation_curve.x_data,
-        fill_value="extrapolate",
-        assume_sorted=True,
-    )
+    t_sat_interpolator = Interp1D(h_in_sat, saturation_curve.x_data)
     h_min = (
         GetMoistAirEnthalpy(
             dbt_min_seen or saturation_curve.x_data[0],
@@ -412,12 +406,7 @@ def make_constant_specific_volume_lines(
     temps_max_constant_v = f_vec_dry_temp_from_spec_vol(
         np.array(v_objective), w_humidity_ratio_min / _factor_out_w(), pressure
     )
-    t_sat_interpolator = interp1d(
-        v_in_sat,
-        saturation_curve.x_data,
-        fill_value="extrapolate",
-        assume_sorted=True,
-    )
+    t_sat_interpolator = Interp1D(v_in_sat, saturation_curve.x_data)
     t_sat_points = solve_curves_with_iteration(
         "CONSTANT VOLUME",
         v_objective,

psychrochart/plot_logic.py

@@ -10,7 +10,6 @@
 from matplotlib.axes import Axes
 from matplotlib.path import Path
 from matplotlib.text import Annotation
-from scipy.spatial import ConvexHull, QhullError
 
 from psychrochart.chart_entities import (
     ChartRegistry,
@@ -25,7 +24,7 @@
     PsychroCurves,
 )
 from psychrochart.models.styles import CurveStyle, ZoneStyle
-from psychrochart.util import mod_color
+from psychrochart.util import convex_hull_graham_scan, mod_color
 
 
 def _annotate_label(
@@ -427,33 +426,31 @@ def plot_annots_dbt_rh(ax: Axes, annots: ChartAnnots) -> dict[str, Artist]:
         line_gid = make_item_gid("point", name=point.label or name)
         reg_artist(line_gid, artist_point, annot_artists)
 
-    if ConvexHull is None or not annots.areas:
+    if not annots.areas:
         return annot_artists
 
     for convex_area in annots.areas:
-        int_points = np.array(
-            [annots.get_point_by_name(key) for key in convex_area.point_names]
-        )
+        raw_points = [
+            annots.get_point_by_name(key) for key in convex_area.point_names
+        ]
         try:
-            assert len(int_points) >= 3
-            hull = ConvexHull(int_points)
-        except (AssertionError, QhullError):  # pragma: no cover
-            logging.error(f"QhullError with points: {int_points}")
-            continue
+            points_hull_x, points_hull_y = convex_hull_graham_scan(raw_points)
+        except (AssertionError, IndexError):  # pragma: no cover
+            logging.error("Convex hull error with points: %s", raw_points)
+            return annot_artists
 
         area_gid = make_item_gid(
             "convexhull", name=",".join(convex_area.point_names)
         )
-        for i, simplex in enumerate(hull.simplices):
-            [artist_contour] = ax.plot(
-                int_points[simplex, 0],
-                int_points[simplex, 1],
-                **convex_area.line_style,
-            )
-            reg_artist(area_gid + f"_s{i+1}", artist_contour, annot_artists)
+        [artist_contour] = ax.plot(
+            [*points_hull_x, points_hull_x[0]],
+            [*points_hull_y, points_hull_y[0]],
+            **convex_area.line_style,
+        )
+        reg_artist(area_gid + "_edge", artist_contour, annot_artists)
         [artist_area] = ax.fill(
-            int_points[hull.vertices, 0],
-            int_points[hull.vertices, 1],
+            points_hull_x,
+            points_hull_y,
             **convex_area.fill_style,
         )
         reg_artist(area_gid, artist_area, annot_artists)

psychrochart/process_logic.py

@@ -9,7 +9,6 @@
     SetUnitSystem,
     SI,
 )
-from scipy.interpolate import interp1d
 
 from psychrochart.chartdata import (
     get_rh_max_min_in_limits,
@@ -24,6 +23,7 @@
 from psychrochart.chartzones import make_zone_curve
 from psychrochart.models.config import ChartConfig, ChartLimits, DEFAULT_ZONES
 from psychrochart.models.curves import PsychroChartModel
+from psychrochart.util import Interp1D
 
 spec_vol_vec = np.vectorize(psy.GetMoistAirVolume)
 
@@ -53,10 +53,9 @@ def _gen_interior_lines(config: ChartConfig, chart: PsychroChartModel) -> None:
     # check if sat curve cuts x-axis with T > config.dbt_min
     dbt_min_seen: float | None = None
     if chart.saturation.y_data[0] < config.w_min:
-        temp_sat_interpolator = interp1d(
+        temp_sat_interpolator = Interp1D(
             chart.saturation.y_data,
             chart.saturation.x_data,
-            assume_sorted=True,
         )
         dbt_min_seen = temp_sat_interpolator(config.w_min)
 

psychrochart/util.py

@@ -9,6 +9,88 @@
 TESTING_MODE = os.getenv("PYTEST_CURRENT_TEST") is not None
 
 
+class Interp1D:
+    """Simple 1D interpolation with extrapolation."""
+
+    def __init__(self, x: Sequence[float], y: Sequence[float]):
+        self.x = np.array(x)
+        self.y = np.array(y)
+
+    def __call__(self, x_new: float) -> float:
+        """Linear interpolation with extrapolation."""
+        # Perform linear interpolation
+        for i in range(len(self.x) - 1):
+            if self.x[i] <= x_new <= self.x[i + 1]:
+                slope = (self.y[i + 1] - self.y[i]) / (
+                    self.x[i + 1] - self.x[i]
+                )
+                return float(self.y[i] + slope * (x_new - self.x[i]))
+
+        # Extrapolation
+        assert x_new < self.x[0] or x_new > self.x[-1]
+        i = 1 if x_new < self.x[0] else -1
+        slope = (self.y[i] - self.y[i - 1]) / (self.x[i] - self.x[i - 1])
+        return float(self.y[i] + slope * (x_new - self.x[i]))
+
+
+def orientation(
+    p: tuple[float, float],
+    q: tuple[float, float],
+    r: tuple[float, float],
+) -> int:
+    """
+    Function to find orientation of ordered triplet (p, q, r).
+    Returns:
+    0 : Colinear points
+    1 : Clockwise points
+    2 : Counterclockwise points
+    """
+    val = (q[1] - p[1]) * (r[0] - q[0]) - (q[0] - p[0]) * (r[1] - q[1])
+    if val == 0:  # pragma: no cover
+        return 0  # Colinear
+    elif val > 0:
+        return 1  # Clockwise
+    else:
+        return 2  # Counterclockwise
+
+
+def convex_hull_graham_scan(
+    points: list[tuple[float, float]],
+) -> tuple[list[float], list[float]]:
+    """Function to compute the convex hull of a set of 2-D points."""
+    # If number of points is less than 3, convex hull is not possible
+    numpoints = len(points)
+    assert numpoints >= 3
+
+    # Find the leftmost point
+    leftp = min(points)
+
+    # Sort points based on polar angle with respect to the leftmost point
+    sorted_points = sorted(
+        [p for p in points if p != leftp],
+        key=lambda x: (
+            np.arctan2(x[1] - leftp[1], x[0] - leftp[0]),
+            x[0],
+            x[1],
+        ),
+    )
+
+    # Initialize an empty stack to store points on the convex hull
+    # Start from the leftmost point and proceed to build the convex hull
+    hull = [leftp, sorted_points[0]]
+    for i in range(1, len(sorted_points)):
+        while (
+            len(hull) > 1
+            and orientation(hull[-2], hull[-1], sorted_points[i]) != 2
+        ):
+            hull.pop()
+        hull.append(sorted_points[i])
+
+    hull_x, hull_y = list(zip(*hull))
+    assert len(hull_x) >= 2
+    return list(hull_x), list(hull_y)
+
+
 def _iter_solver(
     initial_value: np.ndarray,
     objective_value: np.ndarray,

pyproject.toml

@@ -62,7 +62,7 @@ log_date_format = "%Y-%m-%d %H:%M:%S"
 
 [tool.poetry]
 name = "psychrochart"
-version = "0.10.0"
+version = "0.11.0"
 description = "A python 3 library to make psychrometric charts and overlay information on them"
 authors = ["Eugenio Panadero <[email protected]>"]
 packages = [
@@ -92,7 +92,6 @@ include = ["CHANGELOG.md"]
 [tool.poetry.dependencies]
 python = ">=3.10,<3.13"
 matplotlib = ">=3.7"
-scipy = ">=1.10"
 psychrolib = ">=2.5"
 pydantic = ">=2.3.0"
 python-slugify = ">=8.0.1"