Matplotlib contourf входной массив ошибка ⇐ Python

[Anonymous]

Я пытаюсь построить контуры давления экспортируемых данных CFD. Я создал прямоугольную сетку, отфильтровал ее на основе импортированных координат и интерполированных импортированных данных на фильтрованной сетке. Я проверил фигуры и количество размеров входов x, y и z в Contourf, и все они 2D и та же форма. < /P>
Кто -нибудь знает, откуда эта ошибка?import pandas as pd
import numpy as np
import scipy
import matplotlib.pyplot as plt
import matplotlib

# Read data

input_filename = 'period_rot_shadow_vel-mag_p-stat.txt'
df_results = pd.read_csv(input_filename,
sep =',', skiprows = 1,
names = ['nodenumber', 'X', 'Y', 'Z','p_stat', 'vel_mag'])

#get the size of the data to generate the same size array
x_data_min = df_results['X'].min()
x_data_max = df_results['X'].max()
y_data_min = df_results['Y'].min()
y_data_max = df_results['Y'].max()

#from max and min values calculate the range (size) for both axis
x_size = np.abs(x_data_max) + np.abs(x_data_min)
y_size = np.abs(y_data_max) + np.abs(y_data_min)

rect_mesh_spacing = 0.001

#number of points on each edge is calculated from the x_size and spacing, +1 is added so that we always
#cover the whole area covered in exported data
N_x_steps = int(x_size/rect_mesh_spacing) + 1
N_y_steps = int(y_size/rect_mesh_spacing) + 1

#create an empty list to fill with the values
rect_mesh_x_axis = np.array([])
rect_mesh_y_axis = np.array([])

#for loop to fill the list of evenly spaced value in the x axis
for i in range(0, N_x_steps):
x = x_data_min + i * rect_mesh_spacing
rect_mesh_x_axis = np.append(rect_mesh_x_axis, x)

for i in range(0, N_y_steps):
y = y_data_min + i * rect_mesh_spacing
rect_mesh_y_axis = np.append(rect_mesh_y_axis, y)

#use meshgrid function to create a rectangular grid, meshgrid returns a tuple of ndarrays
xx, yy = np.meshgrid(rect_mesh_x_axis, rect_mesh_y_axis)

#create an array from meshgrid points
xy_mesh = np.array((xx,yy)).T

#define input coordinates (imporeted data point coordinates) as numpy arrays
input_coords = np.array(list(zip(df_results['X'].to_numpy(), df_results['Y'].to_numpy())))

# scipy.spatial.KDTree function is used to lookup nearest-neighbour for defined points
tree = scipy.spatial.KDTree(input_coords)

dist, idx = tree.query(xy_mesh)
#define the radius of lookup of vicinity of points
radius = (rect_mesh_spacing + rect_mesh_spacing) / 2
distance_filter = dist

Подробнее здесь: https://stackoverflow.com/questions/796 ... apes-error