from pynetdesign.modelling.io import *
from pynetdesign.visualization.utils import *
import matplotlib.pyplot as plt
from mpl_toolkits.axes_grid1 import make_axes_locatable
#import cmcrameri.cm as cmc
import pandas as pd
import numpy as np
import warnings
[docs]
def plot_stations_view(df: pd.DataFrame,
view: str = 'xy',
x_offset: float = None,
y_offset: float = None,
z_offset: float = None,
offset_perc: float = 0.1,
plot_names: bool = True,
station_marker_size: int = 100,
grid_points: np.ndarray = None,
grid_marker_size: int = 1,
use_warnings: bool = True):
r"""
Plots either a map view or side view of stations as filled triangles with name labels.
Optionally plots grid points as well. Color-codes the triangles based on noise level
and adds a colorbar.
Parameters
----------
df : :obj:`pandas.DataFrame`
Data frame containing station names, coordinates, and noise levels.
Expected columns: 'Name', 'X', 'Y', 'Z' (for side view), 'NoiseLevel'.
view : :obj:`str`, optional
Specifies the view to plot. Options are 'xy' (X-Y), 'xz' (X-Z), or 'yz' (Y-Z).
Default is 'xy'.
x_offset : :obj:`float`, optional
Offset added to the min and max X coordinates for axis limits.
If None, defaults to 10% of the X coordinate range.
y_offset : :obj:`float`, optional
Offset added to the min and max Y coordinates for axis limits.
If None, defaults to 10% of the Y coordinate range.
z_offset : :obj:`float`, optional
Offset added to the min and max Z coordinates for axis limits (side view only).
If None, defaults to 10% of the Z coordinate range.
offset_perc : :obj:`float`, optional, default: 0.1
Percentage of coordinate range to use as offset.
Used only if offset value is None.
plot_names : :obj:`bool`, optional, default: True
Flag to plot station names or not (True or False)
station_marker_size : :obj:`int`, optional, default: 100
Size of the station markers in the scatter plot
grid_points: :obj:`np.ndarray`, optional, default: None
Array of shape (ngrid, 3) representing grid points' coordinates (X, Y, Z).
grid_marker_size: :obj:`int`, optional, default: 10
Size of the grid points markers in the scatter plot
use_warnings: :obj:`bool`, optional, default: True
If True, enable warnings, if False, disable them.
Returns
-------
fig : :obj:`matplotlib.figure.Figure`
The figure object containing the plot.
ax : :obj:`matplotlib.axes.Axes`
The axes object of the plot.
cax : :obj:`matplotlib.axes.Axes`
The axes object for the colorbar.
cbar : :obj:`matplotlib.colorbar.Colorbar`
The colorbar object.
"""
# Validate view parameter
if view not in ['xy', 'xz', 'yz']:
raise ValueError("Invalid view specified. Choose 'xy', 'xz', or 'yz'.")
# Check if required columns exist
required_columns = ['X', 'Y', 'NoiseLevel']
if view in ['xz', 'yz']:
required_columns.append('Z')
for col in required_columns:
if col not in df.columns:
raise ValueError(f"The '{col}' column is missing in the geometry data.")
# Extract data from the dataframe
x = df['X']
y = df['Y']
if view in ['xz', 'yz']:
z = df['Z']
# Check if noise level units are consistent
if 'noise_unit' in df.attrs:
noise_level = df['NoiseLevel'].to_numpy()
clb_label = f"Noise Level ({df.attrs['noise_unit']})"
plot_clb = True
else:
noise_level = np.full(len(x), 0)
plot_clb = False
# Check if Name column can be used
if plot_names:
if 'Name' in df.columns:
names = df['Name']
else:
plot_names = False
if use_warnings:
warnings.warn("Can't plot station names: Name column is missing in the geometry data.")
if grid_points is not None:
# Grid points are expected to be of shape (ngrid, 3), where each row is (x, y, z)
gx = grid_points[:, 0]
gy = grid_points[:, 1]
gz = grid_points[:, 2]
# Get limits from stations and grid points
xmin = min([x.min(), gx.min()])
xmax = max([x.max(), gx.max()])
ymin = min([y.min(), gy.min()])
ymax = max([y.max(), gy.max()])
if view in ['xz', 'yz']:
zmin = min([z.min(), gz.min()])
zmax = max([z.max(), gz.max()])
else:
# Get limits only from stations
xmin = x.min()
xmax = x.max()
ymin = y.min()
ymax = y.max()
if view in ['xz', 'yz']:
zmin = z.min()
zmax = z.max()
# Calculate offsets
if x_offset is None:
x_offset = offset_perc * (xmax - xmin)
if y_offset is None:
y_offset = offset_perc * (ymax - ymin)
if view in ['xz', 'yz'] and z_offset is None:
z_offset = offset_perc * (zmax - zmin)
if z_offset < 0.001 * (xmax - xmin + ymax - ymin):
z_offset = offset_perc * min(xmax - xmin, ymax - ymin)
# Create figure and axes
fig, ax = plt.subplots(figsize=(10, 10))
# Ensure equal scaling
ax.set_aspect('equal', 'box')
# First plot grid points if provided
if grid_points is not None:
if view == 'xy':
ax.scatter(gx, gy, color='gray', s=grid_marker_size, marker='s', zorder=1, label='Grid Points')
elif view == 'xz':
ax.scatter(gx, gz, color='gray', s=grid_marker_size, marker='s', zorder=1, label='Grid Points')
else: # view == 'yz'
ax.scatter(gy, gz, color='gray', s=grid_marker_size, marker='s', zorder=1, label='Grid Points')
# Plot based on the view
if view == 'xy':
scatter = ax.scatter(x, y, c=noise_level, cmap='viridis', s=station_marker_size, marker='^', zorder=2)
ax.set_xlim(xmin - x_offset, xmax + x_offset)
ax.set_ylim(ymin - y_offset, ymax + y_offset)
ax.set_xlabel('X Coordinate')
ax.set_ylabel('Y Coordinate')
ax.set_title('Map View of Stations')
elif view == 'xz':
scatter = ax.scatter(x, z, c=noise_level, cmap='viridis', s=station_marker_size, marker='^', zorder=2)
ax.set_xlim(xmin - x_offset, xmax + x_offset)
ax.set_ylim(zmax + z_offset, zmin - z_offset)
ax.set_xlabel('X Coordinate')
ax.set_ylabel('Z Coordinate')
ax.set_title('Side View of Stations: X-Z')
else: # view == 'yz'
scatter = ax.scatter(y, z, c=noise_level, cmap='viridis', s=station_marker_size, marker='^', zorder=2)
ax.set_xlim(ymin - y_offset, ymax + y_offset)
ax.set_ylim(zmax + z_offset, zmin - z_offset)
ax.set_xlabel('Y Coordinate')
ax.set_ylabel('Z Coordinate')
ax.set_title('Side View of Stations: Y-Z')
# Add labels to the points
if plot_names:
for i, name in enumerate(names):
name = name + " " # to make a gap between the name and the marker
if view == 'xy':
ax.text(x[i], y[i], name, fontsize=12, ha='right', va='bottom', zorder=3)
elif view == 'xz':
ax.text(x[i], z[i], name, fontsize=12, ha='right', va='bottom', zorder=3)
else: # view == 'yz'
ax.text(y[i], z[i], name, fontsize=12, ha='right', va='bottom', zorder=3)
# Add grid
ax.grid(True)
if plot_clb:
# Create colorbar
if view in ['xz', 'yz']:
bbox = ax.get_position()
cax_size_perc = 5 * bbox.width / bbox.height
divider = make_axes_locatable(ax)
cax = divider.append_axes("bottom", size=f"{cax_size_perc}%", pad=0.65)
cbar = plt.colorbar(scatter, cax=cax, orientation="horizontal")
cbar.set_label(clb_label, labelpad=15)
else:
divider = make_axes_locatable(ax)
cax = divider.append_axes("right", size="5%", pad=0.2)
cbar = plt.colorbar(scatter, cax=cax)
cbar.set_label(clb_label, rotation=270, labelpad=15)
else:
cax = None
cbar = None
plt.show()
return fig, ax, cax, cbar
