import matplotlib.pyplot as plt
import matplotlib.colors as mcolors
from matplotlib.patches import Patch
import numpy as np
from scipy.interpolate import PchipInterpolator

# 1. PASTE YOUR DATA HERE
datos_crudos = """Bin Center	% Frequency
0	0.212314225053079
0.05	7.5583864118896
0.1	8.6624203821656
0.15	7.13375796178344
0.2	5.56263269639066
0.25	4.45859872611465
0.3	3.94904458598726
0.35	3.82165605095541
0.4	3.43949044585987
0.45	3.69426751592357
0.5	3.90658174097665
0.55	3.56687898089172
0.6	4.07643312101911
0.65	4.28874734607219
0.7	4.71337579617834
0.75	4.37367303609342
0.8	4.96815286624204
0.85	6.4968152866242
0.9	7.77070063694268
0.95	6.62420382165605
1	0.721868365180467"""

# 2. AUTOMATIC PROCESSING
lineas = datos_crudos.strip().split('\n')[1:] 
bins_array = []
freq_array = []

for linea in lineas:
    # Supports both tabs and spaces
    partes = linea.strip().split('\t')
    if len(partes) < 2:
        partes = linea.strip().split()
    bins_array.append(float(partes[0]))
    freq_array.append(float(partes[1]))

bins = np.array(bins_array)
freq = np.array(freq_array)
mean_val = np.average(bins, weights=freq)

# Smooth interpolation for data trend
interpolator = PchipInterpolator(bins, freq)
x_fit = np.linspace(min(bins), max(bins), 500)
y_fit = interpolator(x_fit)
y_fit = np.clip(y_fit, 0, None)

# Ecological Traffic Light
def get_colors(b_array):
    return ['#008000' if b < 0.4 else '#FFD700' if b <= 0.7 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. CREATION OF THE GRAPH
plt.figure(figsize=(7, 6))

plt.bar(bins, freq, width=0.04, color=face_colors, edgecolor=edge_colors, linewidth=1.5, zorder=2)

# 4. LABELS AND TITLES
plt.xlabel('Aquatic Toxicity Probability (EC50 < 100 ppm)', fontsize=12)
plt.ylabel('% Frequency', fontsize=12)
plt.title('Aquatic Environmental Hazard: Toxicity in Crustaceans (D. magna)', fontsize=14)

legend_elements = [
    Patch(facecolor=mcolors.to_rgba('#008000', 0.6), edgecolor='#008000', label='Non-Toxic / Safe (< 0.4)'),
    Patch(facecolor=mcolors.to_rgba('#FFD700', 0.6), edgecolor='#FFD700', label='Moderate Risk (0.4 - 0.7)'),
    Patch(facecolor=mcolors.to_rgba('#B22222', 0.6), edgecolor='#B22222', label='High Toxicity (> 0.7)')
]
plt.legend(handles=legend_elements, loc='upper center', framealpha=0.95, fontsize=10)

plt.grid(axis='y', linestyle=':', alpha=0.7, zorder=0)
plt.xlim(-0.05, 1.05)
plt.ylim(0, max(freq) * 1.15) 
plt.tight_layout()

plt.show()