Hello I would like to display a 3D interpolation in a 1D basemap. However, I keep getting this error:
ValueError: condition must be a 1-d array
How can I convert the 3d array into a 1D array without the plot being consumed on the map.
The error occurs in line: plot_mesh_data(interpolation, grid,basemap)
The Data: https://filebin.net/n9mnzakasaf6tb0g
my code:`
from traceback import print_tb
import numpy as np
from pykrige.uk3d import UniversalKriging3D
from pykrige.kriging_tools import write_asc_grid
import pykrige.kriging_tools as kt
import matplotlib.pyplot as plt
from mpl_toolkits.basemap import Basemap
from matplotlib.patches import Path, PathPatch
import pandas as pd
def load_data():
df = pd.read_csv(r"File")
return(df)
def get_data(df):
return {
"lons": df['Longitude'],
"lats": df['Latitude'],
"alts": df['Altitude'],
"values": df['O18'],
}
def extend_data(data):
return {
"lons": np.concatenate([np.array([lon-360 for lon in data["lons"]]), data["lons"], np.array([lon+360 for lon in data["lons"]])]),
"lats": np.concatenate([data["lats"], data["lats"], data["lats"]]),
"alts": np.concatenate([data["alts"], data["alts"], data["alts"]]),
"values": np.concatenate([data["values"], data["values"], data["values"]]),
}
def generate_grid(data, basemap, delta=1):
grid = {
'lon': np.arange(-180, 180, delta),
'lat': np.arange(np.amin(data["lats"]), np.amax(data["lats"]), delta),
'alt': np.arange(np.amin(data["alts"]), np.amax(data["alts"]), delta)
}
grid["x"], grid["y"], grid["z"] = np.meshgrid(grid["lon"], grid["lat"], grid["alt"], indexing="ij")
grid["x"], grid["y"] = basemap(grid["x"], grid["y"])
return grid
def interpolate(data, grid):
uk3d = UniversalKriging3D(
data["lons"],
data["lats"],
data["alts"],
data["values"],
variogram_model='exponential',
drift_terms=["specified"],
specified_drift=[data["alts"]],
)
return uk3d.execute("grid", grid["lon"], grid["lat"], grid["alt"], specified_drift_arrays=[grid["z"]])
def prepare_map_plot():
figure, axes = plt.subplots(figsize=(10,10))
basemap = Basemap(projection='robin', lon_0=0, lat_0=0, resolution='h',area_thresh=1000,ax=axes)
return figure, axes, basemap
def plot_mesh_data(interpolation, grid, basemap):
colormesh = basemap.contourf(grid["x"], grid["y"],grid["z"], interpolation,32, cmap='RdBu_r')
color_bar = basemap.colorbar(colormesh,location='bottom',pad="10%")
df = load_data()
base_data = get_data(df)
figure, axes, basemap = prepare_map_plot()
grid = generate_grid(base_data, basemap, 90)
extended_data = extend_data(base_data)
interpolation, interpolation_error = interpolate(extended_data, grid)
plot_mesh_data(interpolation, grid,basemap)
Should I just develop a second grid which I use only for plotting the interpolated data?