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 вводов x, y и z в Contourf, и все они являются 2D и той же формой. < /P>
Кто -нибудь знает, откуда эта ошибка? как это будет в 2D -форме. < /p>
Пример кода: < /p>
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
Образец данных: < /p>
adonumber, x-координат, y-координат, z-координат, давление, скорость-магистра 2.104994697E-03, -2,185633883E-02, -8.094133146E+03, 4.686428765E+01
2,2,738908254E-02, 3.158549336E-03, -2.185629997E-02, -8.104864467E+03, 4.606212337E+01
3,2,757460451E-02, 5.167262860E-03, -2,185623337E-02, -8.093051020E+03, 4.495193692E+01
4,2,733931890E-02, 5.656880572E-03, -2,185622490E-02, -8.116433300E+03, 4.405860916e+01
5,2,759126430E-02, 6.070293390E-03, -2,185618260E-02, -8.084872243E+03, 4.428866265E+01
6,2,737704207E-02, 6.507508463E-03, -2.185627796E-02, -8.106663765E+03, 4.361527022E+01
7,2,762655064E-02, 0,000000000E+00, -2,185611682E-02, -8,057108514E+03, 7,720657592E+01
8,8,8,762655053E-02, 1.920716437E-05, -2,185609461E-02, -8,057029042E+03, 7.591235710E+01
9,2,762654491E-02, 4.228439350E-05, -2,185606795E-02, -8.057013286E+03, 7.368296305E+01
10,2.762653069E-02, 6.997596792E-05, -2,185603598E-02, -8,057068875E+03, 7.113144845E+01
11,2,762650289E-02, 1.032044066E-04, -2,185599766E-02, -8,057152704E+03, 6.841504839E+01
12,2,762645410E-02, 1.430766767E-04, -2,185595174E-02, -8.057232638E+03, 6.565721945E+01
13,2,740227795E-02, 1.197447086E-03, -2,185604704E-02, -8.086002417E+03, 4.769658095E+01
14,2,729995772E-02, 4.555508762E-03, -2,185613769E-02, -8,113811400E+03, 4,473595941E+01
15,2,762637329E-02, 1.909744910E-04, -2.185589666E-02, -8.057315245E+03, 6.283751408E+01
16,2,762624634E-02, 2.484489809E-04, -2,185583068E-02, -8,057450247E+03, 5,993119264E+01
17,2,762465252E-02, 6.184882281E-04, -2,185591455E-02, -8.059810059E+03, 5.089516358E+01
18,2,762605091E-02, 3.174151315E-04, -2,185575167E-02, -8.057686244E+03, 5.707278224E+01
19,2,762531127E-02, 4.994699682E-04, -2,185577109E-02, -8,058658000E+03, 5,248349769E+01
20,2,762366891E-02, 7.612957389E-04, -2,185583175E-02, -8.062030940E+03, 4.956215663E+01

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