＆quot“ valueerror：阵列的条件形状必须与自我”相同。

Question

我正在尝试关注

from osgeo import gdal
from PIL import Image
import numpy as np
import matplotlib as mtp
import matplotlib.pyplot as plt
import pandas as pd
import geopandas as gpd
import earthpy.plot as ep
import rasterio
from rasterio.plot import reshape_as_raster, reshape_as_image

get_ipython().run_line_magic('matplotlib', 'inline')

pd.options.display.max_colwidth = 89


# In[2]:


#setting the path for image
S1_S2_stack = 'S1_S2_stack.tif'

#path to training and validation data
training_points = 'testing.shp'
validation_points = 'training.shp'


# In[3]:


colors = dict ((
    (0, (0,76,153,255)),  #wheat
    (1, (0,153,0,255)),   #corn
    (2, (255,0,0,255)),   #other
    (3, (255,153,51,255)),
    (4, (255,255,0,255))
    
))


# In[4]:


for k in colors:
    v = colors [k]
    _v = [_v / 255.0 for _v in v]
    colors[k] = _v
    
index_colors = [colors[key] if key in colors else (1,1,1,0) for key in range (0,5)]
cmap = plt.matplotlib.colors.ListedColormap(index_colors, 'Classification', 5)


# In[5]:


src = rasterio.open(S1_S2_stack)
bands = src.read()


# In[6]:


stack =src. read()
print(stack.shape)

fig, (ax1, ax2) = plt.subplots(1,2,figsize= (20,10))
ax1 = ep.plot_rgb(arr = stack, rgb =(3, 2, 1), stretch=True, ax = ax1, title = "RGB Composite - Sentinel-2")
stack_s1 =np.stack ((stack[28],stack[29],stack[29]/stack[28]))
ax2 = ep.plot_rgb(arr = stack_s1, rgb = (1,0,2), stretch=True, ax = ax2, title= "RGB Composite - Sentinel-1 (VV, VH, VV/VH)")
plt.tight_layout()


# In[7]:


img = src.read()
profile = src.profile
with rasterio.io.MemoryFile () as memfile:
    with memfile.open(**profile) as dst:
        for i in range(0, src.count):
            dst.write(img[i], i+1)
    dataset = memfile.open()

从这里起作用。但是，当我运行此代码时：

   #read points from shapefile
train_pts = gpd.read_file (training_points)
train_pts = train_pts[[ 'CID','class', 'POINT_X','POINT_Y']] #attribute fields in shapefile
train_pts.index = range(len(train_pts))
coords = [(x,y) for x, y in zip(train_pts.POINT_X, train_pts.POINT_Y)] #create list of point coordinates

#sample each band of raster dataset at each point in the coordinate list
train_pts ['Raster Value'] = [x for x in dataset.sample(coords)] #all band values saved as a list in the Raster Value column
#Unpack the raster value column to separate column for each band - band names retrieved from snappy in the video but I was looking for an option
train_pts[bands] = pd.DataFrame(train_pts['Raster Value'].tolist(), index = train_pts.index)
train_pts = train_pts.drop(['Raster Value'], axis=1) #drop raster value column
#change the values for last three classes 
train_pts['CID'] = train_pts['CID'].replace([7,8,15],[5,6,7])
train_pts.to.csv('train_pts.csv') #save as csv
train_pts.head () #see first column

我会收到以下错误：

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
Input In [9], in <cell line: 10>()
      8 train_pts ['Raster Value'] = [x for x in dataset.sample(coords)] #all band values saved as a list in the Raster Value column
      9 #Unpack the raster value column to separate column for each band - band names retrieved from snappy in the video but I was looking for an option
---> 10 train_pts[src1] = pd.DataFrame(train_pts['Raster Value'].tolist(), index = train_pts.index)
     11 train_pts = train_pts.drop(['Raster Value'], axis=1) #drop raster value column
     12 #change the values for last three classes 

File ~\.conda\envs\geocomp3_clone\lib\site-packages\pandas\core\frame.py:3643, in DataFrame.__setitem__(self, key, value)
   3641     self._setitem_frame(key, value)
   3642 elif isinstance(key, (Series, np.ndarray, list, Index)):
-> 3643     self._setitem_array(key, value)
   3644 elif isinstance(value, DataFrame):
   3645     self._set_item_frame_value(key, value)

File ~\.conda\envs\geocomp3_clone\lib\site-packages\pandas\core\frame.py:3685, in DataFrame._setitem_array(self, key, value)
   3680 else:
   3681     # Note: unlike self.iloc[:, indexer] = value, this will
   3682     #  never try to overwrite values inplace
   3684     if isinstance(value, DataFrame):
-> 3685         check_key_length(self.columns, key, value)
   3686         for k1, k2 in zip(key, value.columns):
   3687             self[k1] = value[k2]

File ~\.conda\envs\geocomp3_clone\lib\site-packages\pandas\core\indexers\utils.py:428, in check_key_length(columns, key, value)
    426 if columns.is_unique:
    427     if len(value.columns) != len(key):
--> 428         raise ValueError("Columns must be same length as key")
    429 else:
    430     # Missing keys in columns are represented as -1
    431     if len(columns.get_indexer_non_unique(key)[0]) != len(value.columns):

ValueError: Columns must be same length as key

我的问题如下：

1. 我用来导入的方法是否有问题 Shapefile的乐队？
2. 我需要在输入的代码中写下所有字段 ShapeFile的属性信息？还是我应该编辑这些 GIS程序中的字段？

Answer 1

则从频段说明中创建新的数据框列

如果您说

src = rasterio.open(S1_S2_stack)
bands = src.read()

然后是一个3维numpy ndarray （一系列的栅格帧）， 。将其用于索引 Train_pts [bands] ，其中 Train_pts_pts 是一个数据框，这是没有意义的。但是我认为您想参考乐队名称。如果是这样，请尝试 src.descriptions 而不是：

band_names = [*src.descriptions]
train_pts[band_names] = pd.DataFrame(train_pts['Raster Value'].tolist(), index = train_pts.index)

要知道

• band_names 的某些陷阱应该是列表，以便我们可以将它们用作 train_pts [band_names] trib_pts /代码>。至于 src.descriptions ，我们必须将其转换为 list 。
• 如果频段描述中有空或重复的值，我们需要以某种方式处理它们：

band_names = [f'{src.descriptions[i]}, band {i}' for i in range(1, src.count + 1)]

• 我们可以强制一些默认名称作为上一句话的替代方法：

band_names = [f'Band {i}' for i in range(1, src.count + 1)]