如何按纬度和经度插值数据？

Question

我有一个包含非结构化数据、纬度和经度的数据集

如何通过反距离加权对数据进行插值？

当我使用scipy.griddata时，90度仰角周围的点是不合理的

有什么解决办法吗？

谢谢。

Answer 1

您可以尝试使用plotly 绘制它，它会为您提供交互式绘图。您可以验证terrain 中每个点的值。

详情可参考以下代码。

import plotly.graph_objects as go
import numpy as np
import pandas as pd

# Read data from a csv
url = 'https://raw.githubusercontent.com/patel999jay/Bedford_python/master/bathy_bedford.csv'
z_data = pd.read_csv(url)
# z_data.head() # to see dataframe head
# Read data from a csv
url = 'https://raw.githubusercontent.com/patel999jay/Bedford_python/master/bathy_bedford.csv'
z_data = pd.read_csv(url, index_col=0)

z = z_data.values
sh_0, sh_1 = z.shape
x, y = np.linspace(44.66875, 44.74791667, sh_0), np.linspace(-63.69791667, -63.52708333, sh_1) # This is lat and long
fig = go.Figure(data=[go.Surface(z=z, x=x, y=y,colorscale='Viridis')])
fig.update_traces(contours_z=dict(show=True, usecolormap=True,
                                  highlightcolor="limegreen", project_z=True))
fig.update_layout(title='Bedford Basin Elevation',xaxis_title="Latitude", 
                  yaxis_title="Longitude",autosize=False,
                  width=900, height=900, 
                  margin=dict(l=65, r=50, b=65, t=90))
fig.update_layout(scene = dict(
                    xaxis_title='Latitude',
                    yaxis_title='Longitude',
                    zaxis_title='Elevation'),
                    margin=dict(r=20, b=10, l=10, t=10))  
fig.update_layout(coloraxis_colorbar=dict(
    title="Elevation",
    thicknessmode="pixels", thickness=50,
    lenmode="pixels", len=200,
    yanchor="top", y=1,
    ticks="outside", ticksuffix="",
    dtick=5
))
fig.show()

如果你想使用matplotlib，那么你可以参考下面的代码。

import numpy as np
import matplotlib.pyplot as plt
from matplotlib import cm
import matplotlib.gridspec as gridspec
import matplotlib as mpl
# from matplotlib.ticker import LinearLocator, FormatStrFormatter
from matplotlib import rc, rcParams
from mpl_toolkits.mplot3d import Axes3D
from scipy.interpolate import griddata
import pandas as pd

url ="https://raw.githubusercontent.com/patel999jay/Bedford_python/master/POINT_DATA_TITLE.csv"
df = pd.read_csv(url)
# df.head() # see dataframe head

# 2D-arrays from DataFrame
x1 = np.linspace(df['x'].min(), df['x'].max(), len(df['x'].unique()))
y1 = np.linspace(df['y'].min(), df['y'].max(), len(df['y'].unique()))

"""
x, y via meshgrid for vectorized evaluation of
2 scalar/vector fields over 2-D grids, given
one-dimensional coordinate arrays x1, x2,..., xn.
"""

x2, y2 = np.meshgrid(x1, y1)

# Interpolate unstructured D-dimensional data.
z2 = griddata((df['x'], df['y']), df['z'], (x2, y2), method='cubic')

# Ready to plot

fig = plt.figure(211,figsize=(15,20))
ax = fig.add_subplot(211, projection='3d')
spec = gridspec.GridSpec(ncols=1, nrows=2,
                         height_ratios=[4, 1])

surf = ax.plot_surface(x2, y2, z2, rstride=1, cstride=1, cmap=cm.terrain,
                       linewidth=1, antialiased=False)
ax.view_init(25,-55)

cset = ax.contourf(x2, y2, z2, zdir='z2', offset=-5, cmap=cm.terrain, antialiased=True)

rcParams['legend.fontsize'] = 20

rc('text', usetex=True)
rc('axes', linewidth=2)
rc('font', weight='bold')

ax.xaxis.set_tick_params(labelsize=20)
ax.yaxis.set_tick_params(labelsize=20)
ax.zaxis.set_tick_params(labelsize=20)
ax.set_zticks([-70, -50, -30, -10, 10, 30, 50, 70, 90, 110])
plt.title(r'\textbf{Bedford Basin Bathymatry}', fontsize=20)
plt.xlabel(r'\textbf{Latitude}', fontsize=20, labelpad= 23)
plt.ylabel(r'\textbf{Longitude}', fontsize=20, labelpad= 20)
ax.set_zlabel(r'\textbf{Elevation}', fontsize=20, labelpad= 10)

P.S.：您能否提供您的问题的最小可复制示例，然后我可以相应地更新我的答案。现在我正在使用随机数据。