修复了球面距离计算时nanbug

luobu-code · Jun 14, 2022 · c8856c4 · c8856c4
1 parent 5b9da67
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diff --git a/meteva/base/tool/math_tools.py b/meteva/base/tool/math_tools.py
@@ -308,11 +308,13 @@ def distance_on_earth_surface(lon1,lat1,lon2,lat2):
     :param lat2:
     :return:
     '''
+
     a1 = lon1 * math.pi/180
     b1 = lat1 * math.pi/180
     a2 = lon2 * math.pi/180
     b2 = lat2 * math.pi/180
 
     dis = meteva.base.ER * np.arccos(np.cos(b1)*np.cos(b2)*np.cos(a1-a2) + np.sin(b1)*np.sin(b2))
+    dis[np.isnan(dis)] =0
 
     return dis
diff --git a/tests/jupyter/showdoc/.ipynb_checkpoints/mem_position_score-checkpoint.ipynb b/tests/jupyter/showdoc/.ipynb_checkpoints/mem_position_score-checkpoint.ipynb
@@ -0,0 +1,164 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "%matplotlib inline\n",
+    "%load_ext autoreload\n",
+    "%autoreload 2\n",
+    "import meteva.method as mem\n",
+    "import meteva.base as meb\n",
+    "import numpy as np"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#生成算法测试数据\n",
+    "lon_ob = np.array([130,131,132,133])\n",
+    "lat_ob = np.array([30,31,32,33])\n",
+    "\n",
+    "lon_fo = np.array([131,132,133,134])\n",
+    "lat_fo = np.array([31,32,33,34])\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "#  位置误差\n",
+    "**<font face=\"黑体\" color=blue size = 5> distance(lon_ob,lat_ob,lon_fo,lat_fo,on_earth_surface = True)</font>** \n",
+    "   \n",
+    "计算两组位置之间的两两距离的平均。\n",
+    "\n",
+    "|参数|说明|    \n",
+    "|:--|:--|  \n",
+    "|**<font face=\"黑体\" color=blue size = 5>lon_ob</font>**|观测的经度，numpy数组|   \n",
+    "|**<font face=\"黑体\" color=blue size = 5>lat_ob</font>**|观测的纬度，numpy数组,和lon_ob的shape必须一致|   \n",
+    "|**<font face=\"黑体\" color=blue size = 5>lon_fo</font>**|预报的经度，numpy数组，numpy可以比lat_ob高一维（用于同时进行多家预报结果检验），lon_fo.shape低维与lat_ob.shape保持一致|   \n",
+    "|**<font face=\"黑体\" color=blue size = 5>lat_fo</font>**|预报的纬度，numpy数组，numpy可以比lat_ob高一维（用于同时进行多家预报结果检验），lat_fo.shape低维与lat_ob.shape保持一致,和lon_fo的shape必须一致|      \n",
+    "|<font face=\"黑体\" color=blue size=5>return</font>|位置误差的平均值，如果lat_fo和lat_ob的shape一致，说明只有一家预报，则返回实数，否则说明是在同时检验多家预报，返回结果为一维数组|   \n",
+    "\n",
+    "**调用示例：**  \n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "145.79061830031182\n"
+     ]
+    }
+   ],
+   "source": [
+    "dis = mem.distance(lon_ob,lat_ob,lon_fo,lat_fo)\n",
+    "print(dis)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "#  位置误差统计中间量\n",
+    "**<font face=\"黑体\" color=blue size = 5> tdis(lon_ob,lat_ob,lon_fo,lat_fo,on_earth_surface = True)</font>** \n",
+    "   \n",
+    "为方便开展并行计算，计算两组位置之间的误差的平均值统计两个中间量：样本数，位置误差总和。\n",
+    "\n",
+    "|参数|说明|    \n",
+    "|:--|:--|  \n",
+    "|**<font face=\"黑体\" color=blue size = 5>lon_ob</font>**|观测的经度，numpy数组|   \n",
+    "|**<font face=\"黑体\" color=blue size = 5>lat_ob</font>**|观测的纬度，numpy数组,和lon_ob的shape必须一致|   \n",
+    "|**<font face=\"黑体\" color=blue size = 5>lon_fo</font>**|预报的经度，numpy数组，numpy可以比lat_ob高一维（用于同时进行多家预报结果检验），lon_fo.shape低维与lat_ob.shape保持一致|   \n",
+    "|**<font face=\"黑体\" color=blue size = 5>lat_fo</font>**|预报的纬度，numpy数组，numpy可以比lat_ob高一维（用于同时进行多家预报结果检验），lat_fo.shape低维与lat_ob.shape保持一致,和lon_fo的shape必须一致|      \n",
+    "|<font face=\"黑体\" color=blue size=5>return</font>|根据预报和观测的风向数据，统计得到的样本数、位置误差的总和，lat_fo和lat_ob的shape一致，则说明只有一家预报，此时返回一维的数据，size= 2。 如果lat_fo和lat_ob的shape不一致，则说明有多个预报，则返回的数据shape = （预报成员数，2）|   \n",
+    "\n",
+    "**调用示例：**  \n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[  4.        583.1624732]\n"
+     ]
+    }
+   ],
+   "source": [
+    "tdis_array = mem.tdis(lon_ob,lat_ob,lon_fo,lat_fo)\n",
+    "print(tdis_array)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "#  位置误差（并行）\n",
+    "**<font face=\"黑体\" color=blue size = 5>distance_tdis(tdis_array)</font>**  \n",
+    "\n",
+    "基于中间统计量计算位置误差的平均值\n",
+    "\n",
+    "|参数|说明|    \n",
+    "|:--|:--|  \n",
+    "|**<font face=\"黑体\" color=blue size = 5>tdis_array</font>**|包含检验中间结果的多维数组，其中最后一维长度为2，分别记录了样本数数，位置误差的总和，它通常是tdis函数的计算结果，或者计算结果的累加|     \n",
+    "|<font face=\"黑体\" color=blue size=5>return</font>|位置误差的平均值，nasws_array少了最后一维|   \n",
+    "\n",
+    "**调用示例：**  "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "145.79061830031182\n"
+     ]
+    }
+   ],
+   "source": [
+    "dis = mem.distance_tdis(tdis_array)\n",
+    "print(dis)"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.7.6"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}