Numpy互操作-iObjects Python with JupyterHub for K8s

Numpy是Python科学计算的常用库，也在机器学习领域具有重要的作用。Numpy主要实现矩阵运算功能，这里的教程将地理空间数据集与Numpy实现相互转换，从而可以将Python的更多通用库用于地理空间分析，包括矢量和栅格数据的转换。进一步，可以利用Pandas和GeoPandas的相关功能。

• 镜像构建-iObjects Python with JupyterHub for K8s
• Pandas快速入门
• GeoPandas官方中文文档--译著

from iobjectspy import (datasetvector_to_numpy_array,numpy_array_to_datasetvector,datasetraster_to_numpy_array,numpy_array_to_datasetraster)
import numpy as np
import os

# 设置示例数据路径
#example_data_dir = ''
example_data_dir = '/home/jovyan/data/smdata/'# 设置结果输出路径
out_dir = os.path.join(example_data_dir, 'out')

if not os.path.exists(out_dir):os.makedirs(out_dir)def vector_to_numpy_test():"""读取矢量数据集 Town_P 到 numpy 数组中"""narray1 = datasetvector_to_numpy_array(os.path.join(example_data_dir, 'example_data.udb/Landuse_R'), export_spatial=True)print(narray1.dtype)print(narray1[:10])narray = datasetvector_to_numpy_array(os.path.join(example_data_dir, 'example_data.udb/Town_P'), export_spatial=True)if narray is None:print('读取矢量数据集到 numpy 数组失败')else:print('ndarray.ndim : ' + str(narray.ndim))print('ndarray.dtype : ' + str(narray.dtype))print(narray[:10])print(narray['SmX'][:10])print('读取矢量数据集到 numpy 数组成功')xy_array = np.c_[narray['SmX'], narray['SmY']][:10]print(xy_array.ndim)print(xy_array.dtype)print(xy_array)try:# 使用 hdbscan 做层次聚类,并将结果在 matplotlib 显示% matplotlib inlinefrom hdbscan import HDBSCANimport matplotlib.pyplot as pltxy_c = np.c_[narray['SmX'], narray['SmY']]hdb = HDBSCAN(min_cluster_size=10).fit(xy_c)hdb_labels = hdb.labels_n_clusters_hdb_ = len(set(hdb_labels)) - (1 if -1 in hdb_labels else 0)hdb_unique_labels = set(hdb_labels)hdb_colors = plt.cm.Spectral(np.linspace(0, 1, len(hdb_unique_labels)))fig = plt.figure(figsize=plt.figaspect(1))hdb_axis = fig.add_subplot('111')for k, col in zip(hdb_unique_labels, hdb_colors):if k == -1:col = 'k'hdb_axis.plot(xy_c[hdb_labels == k, 0], xy_c[hdb_labels == k, 1], 'o', markerfacecolor=col,markeredgecolor='k', markersize=6)hdb_axis.set_title('HDBSCAN\nEstimated number of clusters: %d' % n_clusters_hdb_)plt.show()except ImportError:passdef numpy_to_vector_test():"""写入数据到矢量数据集中"""narray = np.empty(10, dtype=[('ID', 'int32'), ('X', 'float64'), ('Y', 'float64'), ('NAME', 'U10')])narray[0] = 1, 116.380351, 39.93393099, '什刹海'narray[1] = 2, 116.365305, 39.89622499, '广安门内'narray[2] = 3, 116.427342, 39.89467499, '崇文门外'narray[3] = 4, 116.490881, 39.96567299, '酒仙桥'narray[4] = 5, 116.447486, 39.93767799, '三里屯'narray[5] = 6, 116.347435, 40.08078599, '回龙观'narray[6] = 7, 116.407196, 39.83895899, '大红门'narray[7] = 8, 116.396915, 39.88371499, '天桥'narray[8] = 9, 116.334522, 40.03594199, '清河'narray[9] = 10, 116.03008, 39.87852799, '潭柘寺'print(narray)result = numpy_array_to_datasetvector(narray, os.path.join(out_dir, 'out_numpy_array.udb'), x_col='X', y_col='Y')if result is not None:if isinstance(result, str):if isinstance(result, str):print('从 numpy 数组中写入数据到矢量数据集 %s 成功' % result)else:print('从 numpy 数组中写入数据到矢量数据集 %s 成功' % result.name)else:print('从 numpy 数组中写入数据到矢量数据集失败')def raster_to_numpy_test():"""从栅格数据 DEM 中读取数据到 numpy 数组中"""narray = datasetraster_to_numpy_array(os.path.join(example_data_dir, 'example_data.udb/DEM'))if narray is None:print('读取栅格数据集到 numpy 数组失败')else:print('ndarray.ndim : ' + str(narray.ndim))print('ndarray.dtype : ' + str(narray.dtype))print(narray)print('读取栅格数据集到 numpy 数组成功')numpy_array_to_datasetraster(narray, 0.001, 0.001, os.path.join(out_dir, 'out_numpy_array.udb'), as_grid=False)def numpy_to_raster_test():"""从 numpy 的数组二进制文件中加载数据,写道栅格数据集中"""narray = np.load(os.path.join(example_data_dir, 'dem.npy'))print(narray)result = numpy_array_to_datasetraster(narray, 0.001, 0.001, os.path.join(example_data_dir, 'out_numpy_array.udb'),as_grid=True)if result is not None:if isinstance(result, str):print('从 numpy 数组中写入数据到栅格数据集 %s 成功' % result)else:print('从 numpy 数组中写入数据到栅格数据集 %s 成功' % result.name)else:print('从 numpy 数组中写入数据到栅格数据集失败')

if __name__ == '__main__':# 读取矢量数据集到 numpy 数组成功vector_to_numpy_test()# 从 numpy 数组中写入数据到矢量数据集中成功numpy_to_vector_test()# 读取栅格数据集到 numpy 数组成功raster_to_numpy_test()# 从 numpy 数组中写入数据到栅格数据集中成功numpy_to_raster_test()

[('LANDTYPE', '<U4'), ('Area', '<f4'), ('Area_1', '<i2'), ('SmX', '<f8'), ('SmY', '<f8'), ('SmPerimeter', '<f8'), ('SmArea', '<f8')]
[('用材林', 132., 132, 116.47779337, 40.87251703, 0.75917921, 1.40894401e-02)('用材林',  97.,  97, 116.6540059 , 40.94696274, 0.4945153 , 1.03534475e-02)('灌丛',  36.,  36, 116.58451795, 40.98712283, 0.25655489, 3.89923745e-03)('灌丛',  36.,  36, 116.89611418, 40.76792703, 0.59237713, 3.81791878e-03)('用材林',   1.,   1, 116.37943683, 40.91435429, 0.03874328, 7.08450886e-05)('灌丛', 126., 126, 116.49117083, 40.78302383, 0.53664074, 1.34577856e-02)('用材林',  83.,  83, 116.69943237, 40.74456848, 0.39696365, 8.83225363e-03)('用材林', 128., 128, 116.8129727 , 40.69116153, 0.56949408, 1.35877743e-02)('用材林',  29.,  29, 116.24543769, 40.71076092, 0.30082509, 3.07221559e-03)('灌丛', 467., 467, 116.43290772, 40.50875567, 1.91745792, 4.95537433e-02)]
ndarray.ndim : 1
ndarray.dtype : [('NAME', '<U9'), ('SmX', '<f8'), ('SmY', '<f8')]
[('百尺竿乡', 115.917748, 39.53525099) ('什刹海', 116.380351, 39.93393099)('月坛', 116.344828, 39.91476099) ('广安门内', 116.365305, 39.89622499)('牛街', 116.36388 , 39.88680299) ('崇文门外', 116.427342, 39.89467499)('永定门外', 116.402249, 39.86559299) ('崔各庄', 116.515447, 39.99966499)('小关', 116.411727, 39.97737199) ('潘家园', 116.467911, 39.87179299)]
[115.917748 116.380351 116.344828 116.365305 116.36388  116.427342116.402249 116.515447 116.411727 116.467911]
读取矢量数据集到 numpy 数组成功
2
float64
[[115.917748    39.53525099][116.380351    39.93393099][116.344828    39.91476099][116.365305    39.89622499][116.36388     39.88680299][116.427342    39.89467499][116.402249    39.86559299][116.515447    39.99966499][116.411727    39.97737199][116.467911    39.87179299]]
[( 1, 116.380351, 39.93393099, '什刹海')( 2, 116.365305, 39.89622499, '广安门内')( 3, 116.427342, 39.89467499, '崇文门外')( 4, 116.490881, 39.96567299, '酒仙桥') ( 5, 116.447486, 39.93767799, '三里屯')( 6, 116.347435, 40.08078599, '回龙观') ( 7, 116.407196, 39.83895899, '大红门')( 8, 116.396915, 39.88371499, '天桥') ( 9, 116.334522, 40.03594199, '清河')(10, 116.03008 , 39.87852799, '潭柘寺')]
从 numpy 数组中写入数据到矢量数据集 NewDataset 成功
DEM
ndarray.ndim : 2
ndarray.dtype : int16
[[ 360  357  353 ... 1373 1320 1265][ 349  353  355 ... 1354 1292 1259][ 353  358  356 ... 1375 1341 1319]...[ 741  756  745 ...  819  836  860][ 700  713  718 ...  821  848  872][ 684  696  696 ...  828  854  880]]
读取栅格数据集到 numpy 数组成功
[[ 360  357  353 ... 1373 1320 1265][ 349  353  355 ... 1354 1292 1259][ 353  358  356 ... 1375 1341 1319]...[ 741  756  745 ...  819  836  860][ 700  713  718 ...  821  848  872][ 684  696  696 ...  828  854  880]]
从 numpy 数组中写入数据到栅格数据集 NewDataset 成功