modify get_fy_awx function.

examples/retrieve_radar.ipynb

@@ -529,7 +529,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.7"
+   "version": "3.9.12"
   },
   "widgets": {
    "application/vnd.jupyter.widget-state+json": {

examples/retrieve_satellite.ipynb

@@ -0,0 +1,122 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "a4641c58-14f3-4e58-af01-3ed5cd2b8867",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "# 读取风云卫星数据"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "3b5bee50-0cae-47c6-9244-144ed1748708",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# set up things\n",
+    "%matplotlib inline\n",
+    "%load_ext autoreload\n",
+    "%autoreload 2\n",
+    "\n",
+    "import warnings\n",
+    "warnings.filterwarnings('ignore')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "1d813531-0813-4747-8066-c9cccad38773",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import numpy as np\n",
+    "\n",
+    "from nmc_met_io.read_satellite import read_awx_cloud"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "642923ce-9879-4599-83dc-de3b051aeac8",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "headinfo, data = read_awx_cloud(\"./samples/ANI_IR1_R04_20220331_2100_FY2G.AWX\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "2e4b15c0-73fc-4df0-98fc-c974778c2334",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "68"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "np.min(data)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "0c0fe240-f92b-429d-b7c1-479d00b1537b",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([1], dtype=int16)"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "headinfo['productCategory']"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Meteorology with Python",
+   "language": "python",
+   "name": "met"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.9.12"
+  },
+  "widgets": {
+   "application/vnd.jupyter.widget-state+json": {
+    "state": {},
+    "version_major": 2,
+    "version_minor": 0
+   }
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

nmc_met_io/retrieve_micaps_server.py

@@ -880,12 +880,12 @@ def get_fy_awx(directory, filename=None, suffix="*.AWX", units='', cache=True, c
                 ('dataRecordNumber', 'i2'),          # 产品数据占用记录数
                 ('productCategory', 'i2'),           # 产品类别, 1：静止, 2：极轨, 3：格点定量, 4：离散, 5: 图形和分析
                 ('compressMethod', 'i2'),            # 压缩方式, 0: 未压缩; 1 行程编码压缩; 2 LZW方式压缩; 3 特点方式压缩
-                ('formatString', 'S8'),              # 格式说明字符串, 'SAT2004'
+                ('formatString', 'S8'),              # 格式说明字符串, 'SAT2004', 'SAT98'为早期版本(不支持)
                 ('qualityFlag', 'i2')]               # 产品数据质量标记, 1 完全可靠; 2 基本可靠; 3 有缺值, 可用; 4 不可用
             head1_info = np.frombuffer(byteArray[0:40], dtype=head1_dtype)
             ind = 40
 
-            if head1_info['productCategory']:
+            if head1_info['productCategory'] == 1:
                 # the second class file head  二级文件头采用不定长方式，内容依据产品的不同而不同.
                 head2_dtype = [
                     ('satelliteName', 'S8'),                 # 卫星名
@@ -927,15 +927,16 @@ def get_fy_awx(directory, filename=None, suffix="*.AWX", units='', cache=True, c
                     table_B =  np.frombuffer(byteArray[ind:(ind + 256)], dtype='u1')
                     ind += 256
                 
-                # calibration table
+                # calibration table  定标数据块
                 calibration_table = None
                 if head2_info['dataLengthOfCalibration'] != 0:
-                    calibration_table = np.frombuffer(byteArray[ind:(ind + 2048)], dtype='i2')
+                    calibration_table = np.frombuffer(byteArray[ind:(ind + 2048)], dtype='u2')
                     calibration_table = calibration_table * 0.01
-                    if (np.array_equal(calibration_table[0::4], calibration_table[1::4]) and
-                        np.array_equal(calibration_table[0::4], calibration_table[2::4]) and
-                        np.array_equal(calibration_table[0::4], calibration_table[3::4])):
+                    #if (np.array_equal(calibration_table[0::4], calibration_table[1::4]) and
+                    #    np.array_equal(calibration_table[0::4], calibration_table[2::4]) and
+                    #    np.array_equal(calibration_table[0::4], calibration_table[3::4])):
                         # This is a trick, refer to http://bbs.06climate.com/forum.php?mod=viewthread&tid=89296
+                    #    calibration_table = calibration_table[0::4]
                     calibration_table = calibration_table[0::4]
                     ind += 2048
 
@@ -1036,6 +1037,8 @@ def get_fy_awx(directory, filename=None, suffix="*.AWX", units='', cache=True, c
     else:
         return None
 
+directory = "SATELLITE/FY2G/L1/IR1/EQUAL/"
+data = get_fy_awx(directory, cache=False)
 
 def get_fy_awxs(directory, filenames, allExists=True, pbar=False, **kargs):
     """