import matplotlib.pyplot as plt
import matplotlib.colors as mcolors
from matplotlib.patches import Patch
import numpy as np
# 1. PASTE YOUR DATA HERE (T. pyriformis Toxicity (pIGC50, -log mg/L))
datos_crudos = """Bin Center % Frequency
-2.4 0.169851380042463
-2.2 0.679405520169851
-2 0.849256900212314
-1.8 1.31634819532909
-1.6 1.48619957537155
-1.4 1.86836518046709
-1.2 1.82590233545648
-1 2.84501061571125
-0.8 3.01486199575372
-0.6 3.82165605095541
-0.4 4.07643312101911
-0.2 4.79830148619958
0 4.11889596602972
0.2 5.30785562632696
0.4 6.02972399150743
0.6 6.58174097664544
0.8 6.4968152866242
1 6.07218683651805
1.2 6.36942675159236
1.4 6.41188959660297
1.6 6.96390658174098
1.8 5.98726114649681
2 4.84076433121019
2.2 4.11889596602972
2.4 2.33545647558386
2.6 1.18895966029724
2.8 0.424628450106157"""
# 2. PROCESSING
lineas = datos_crudos.strip().split('\n')[1:]
bins_array = []
freq_array = []
for linea in lineas:
b, f = linea.strip().split()
bins_array.append(float(b))
freq_array.append(float(f))
bins = np.array(bins_array)
freq = np.array(freq_array)
# Colors
def get_colors(b_array):
return ['#008000' if b < -0.5 else '#FFD700' if b <= 1.0 else '#B22222' for b in b_array]
colors_hex = get_colors(bins)
face_colors = [mcolors.to_rgba(c, alpha=0.60) for c in colors_hex]
edge_colors = [mcolors.to_rgba(c, alpha=0.90) for c in colors_hex]
# 3. PLOT
plt.figure(figsize=(7, 6))
plt.bar(bins, freq, width=0.18, color=face_colors, edgecolor=edge_colors, linewidth=1.5, zorder=2)
# 4. LABELS
plt.xlabel('T. pyriformis Toxicity (pIGC50, -log mg/L)', fontsize=12)
plt.ylabel('% Frequency', fontsize=12)
plt.title('Quantitative Aquatic Toxicity: T. pyriformis (pIGC50)', fontsize=14)
legend_elements = [
Patch(facecolor=mcolors.to_rgba('#008000', 0.6), edgecolor='#008000', label='Non-Toxic (< -0.5)'),
Patch(facecolor=mcolors.to_rgba('#FFD700', 0.6), edgecolor='#FFD700', label='Toxic (-0.5 to 1.0)'),
Patch(facecolor=mcolors.to_rgba('#B22222', 0.6), edgecolor='#B22222', label='Highly Toxic (> 1.0)')
]
plt.legend(handles=legend_elements, loc='upper left', framealpha=0.95, fontsize=10)
plt.grid(axis='y', linestyle=':', alpha=0.7, zorder=0)
plt.xlim(min(bins) - 0.2, max(bins) + 0.2)
plt.ylim(0, max(freq) * 1.2)
plt.tight_layout()
plt.show()