from striplog import Striplog, Interval, Component

# Create from intervals
intervals = [
    Interval(top=0, base=10, components=[Component({'lithology': 'sandstone'})]),
    Interval(top=10, base=25, components=[Component({'lithology': 'shale'})]),
    Interval(top=25, base=40, components=[Component({'lithology': 'limestone'})]),
]
strip = Striplog(intervals)

# Load from file
strip = Striplog.from_csv('lithology.csv')  # Columns: top, base, lithology

# Access and display
print(strip)
strip.plot()
df = strip.to_dataframe()

# CSV format: top,base,lithology
strip = Striplog.from_csv('lithology.csv')
strip.plot()

from striplog import Striplog, Lexicon

description = """
0.0 - 5.5 m: Fine to medium sandstone
5.5 - 12.0 m: Grey shale with silt laminations
12.0 - 18.5 m: Massive limestone, fossiliferous
"""
strip = Striplog.from_description(description, lexicon=lexicon)

# Get interval at depth
interval = strip.read_at(z=15)
print(interval.primary.lithology)

# Crop to depth range
subset = strip.crop((10, 30))

# Unique lithologies
lithologies = strip.unique('lithology')

# Net-to-gross for specific lithology
ntg = strip.net_to_gross(pattern={'lithology': 'sandstone'})
print(f"Sandstone: {ntg * 100:.1f}%")

# Merge adjacent same-lithology intervals
merged = strip.merge_neighbours()

import matplotlib.pyplot as plt

wells = [Striplog.from_csv(f'well{i}.csv') for i in range(1, 4)]
fig, axes = plt.subplots(1, 3, figsize=(10, 8), sharey=True)

for ax, well, name in zip(axes, wells, ['Well 1', 'Well 2', 'Well 3']):
    well.plot(ax=ax, legend=legend)
    ax.set_title(name)

plt.tight_layout()
plt.savefig('correlation.png')

strip.to_csv('output.csv')
strip.to_las('output.las')
strip.to_json('output.json')
df = strip.to_dataframe()