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#oceanographer_tools.py
import matplotlib.pyplot as plt
import os
import pandas as pd
import streamlit as st
import numpy as np
import gsw
from matplotlib.ticker import MaxNLocator
import logging
output_file = os.path.join('src', 'plotting_tools', 'temp_files', 'plot.png')
import uuid
# Add this function to generate unique image paths
def generate_unique_image_path():
figs_dir = os.path.join('tmp', 'figs')
os.makedirs(figs_dir, exist_ok=True)
unique_path = os.path.join(figs_dir, f'fig_{uuid.uuid4()}.png')
logging.debug(f"Generated unique image path: {unique_path}")
return unique_path
# Define the TS Diagram Plotting function
def plot_ts_diagram(main_title, temperature_col, salinity_col, dataset_df):
"""
Plots a TS (Temperature-Salinity) diagram from the provided DataFrame.
Parameters:
- main_title: Title for the plot.
- temperature_col: Column name for temperature data.
- salinity_col: Column name for salinity data.
"""
#dataset_path = os.path.join('data', 'current_data', 'dataset.csv')
df = dataset_df
# Find the minimum and maximum values of temperature and salinity
mint, maxt = df[temperature_col].min(), df[temperature_col].max()
mins, maxs = df[salinity_col].min(), df[salinity_col].max()
# Generate temperature and salinity ranges
tempL = np.linspace(mint - 0.5, maxt + 0.5, 156)
salL = np.linspace(mins - 0.5, maxs + 0.5, 156)
# Create a meshgrid of temperature and salinity
Tg, Sg = np.meshgrid(tempL, salL)
# Calculate seawater density
sigma_theta = gsw.sigma0(Sg, Tg)
# Plotting
fig, ax = plt.subplots(figsize=(10, 8))
# Plot isopycnals (lines of constant density)
cs = ax.contour(Sg, Tg, sigma_theta, colors='lightgray', linewidths=0.5, zorder=1)
cl = ax.clabel(cs, fontsize=8, inline=True, fmt='%.1f')
# Scatter plot with depth as the color if available, otherwise use density
if 'Depth [m]' in df.columns:
depth_col = 'Depth [m]'
elif 'Depth water [m]' in df.columns:
depth_col = 'Depth water [m]'
else:
depth_col = None
if depth_col:
sc = ax.scatter(df[salinity_col], df[temperature_col], c=df[depth_col],
cmap='viridis', s=5, alpha=0.7)
cb = plt.colorbar(sc)
cb.set_label('Depth [m]', rotation=270, labelpad=15)
else:
density = gsw.sigma0(df[salinity_col].values, df[temperature_col].values)
sc = ax.scatter(df[salinity_col], df[temperature_col], c=density,
cmap='viridis', s=5, alpha=0.7)
cb = plt.colorbar(sc)
cb.set_label('Density (kg m$^{-3}$)', rotation=270, labelpad=15)
ax.set_xlabel('Salinity [PSU]')
ax.set_ylabel('Potential Temperature θ [°C]')
ax.set_title(main_title, fontsize=14, fontweight='bold')
ax.xaxis.set_major_locator(MaxNLocator(nbins=6))
ax.yaxis.set_major_locator(MaxNLocator(nbins=8))
ax.tick_params(direction='out')
cb.ax.tick_params(direction='out')
# Add sigma_theta label
ax.text(0.02, 0.98, '$σ_θ$', transform=ax.transAxes, fontsize=12, va='top')
plt.tight_layout()
# Save the plot as a PNG file
output_file = generate_unique_image_path()
plt.savefig(output_file, format='png', dpi=300, transparent=False)
if os.path.exists(output_file):
st.session_state.new_plot_path = output_file
print(f"Plot saved to {output_file}")
return {"result": "TS Diagram generated successfully."}
else:
print("Failed to generate TS Diagram.")
return {"result": "Failed to generate TS Diagram."}
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