From 2663565490bd8f10c09a00f2b9f2277545cddc3f Mon Sep 17 00:00:00 2001 From: NMC-DAVE Date: Wed, 3 Jul 2019 22:07:05 +0800 Subject: [PATCH] Update get_station_data function. --- .gitignore | 208 +-- LICENSE | 1348 +++++++++--------- MANIFEST.in | 12 +- README.md | 84 +- nmc_met_io/DataBlock_pb2.py | 718 +++++----- nmc_met_io/__init__.py | 14 +- nmc_met_io/config.py | 62 +- nmc_met_io/read_grads.py | 132 +- nmc_met_io/read_micaps.py | 1874 ++++++++++++------------- nmc_met_io/read_radar.py | 228 +-- nmc_met_io/read_satellite.py | 358 ++--- nmc_met_io/retrieve_cimiss_history.py | 332 ++--- nmc_met_io/retrieve_cimiss_server.py | 868 ++++++------ nmc_met_io/retrieve_micaps_server.py | 1571 +++++++++++---------- setup.py | 126 +- 15 files changed, 3978 insertions(+), 3957 deletions(-) diff --git a/.gitignore b/.gitignore index 894a44c..60fbcad 100644 --- a/.gitignore +++ b/.gitignore @@ -1,104 +1,104 @@ -# Byte-compiled / optimized / DLL files -__pycache__/ -*.py[cod] -*$py.class - -# C extensions -*.so - -# Distribution / packaging -.Python -build/ -develop-eggs/ -dist/ -downloads/ -eggs/ -.eggs/ -lib/ -lib64/ -parts/ -sdist/ -var/ -wheels/ -*.egg-info/ -.installed.cfg -*.egg -MANIFEST - -# PyInstaller -# Usually these files are written by a python script from a template -# before PyInstaller builds the exe, so as to inject date/other infos into it. -*.manifest -*.spec - -# Installer logs -pip-log.txt -pip-delete-this-directory.txt - -# Unit test / coverage reports -htmlcov/ -.tox/ -.coverage -.coverage.* -.cache -nosetests.xml -coverage.xml -*.cover -.hypothesis/ -.pytest_cache/ - -# Translations -*.mo -*.pot - -# Django stuff: -*.log -local_settings.py -db.sqlite3 - -# Flask stuff: -instance/ -.webassets-cache - -# Scrapy stuff: -.scrapy - -# Sphinx documentation -docs/_build/ - -# PyBuilder -target/ - -# Jupyter Notebook -.ipynb_checkpoints - -# pyenv -.python-version - -# celery beat schedule file -celerybeat-schedule - -# SageMath parsed files -*.sage.py - -# Environments -.env -.venv -env/ -venv/ -ENV/ -env.bak/ -venv.bak/ - -# Spyder project settings -.spyderproject -.spyproject - -# Rope project settings -.ropeproject - -# mkdocs documentation -/site - -# mypy -.mypy_cache/ +# Byte-compiled / optimized / DLL files +__pycache__/ +*.py[cod] +*$py.class + +# C extensions +*.so + +# Distribution / packaging +.Python +build/ +develop-eggs/ +dist/ +downloads/ +eggs/ +.eggs/ +lib/ +lib64/ +parts/ +sdist/ +var/ +wheels/ +*.egg-info/ +.installed.cfg +*.egg +MANIFEST + +# PyInstaller +# Usually these files are written by a python script from a template +# before PyInstaller builds the exe, so as to inject date/other infos into it. +*.manifest +*.spec + +# Installer logs +pip-log.txt +pip-delete-this-directory.txt + +# Unit test / coverage reports +htmlcov/ +.tox/ +.coverage +.coverage.* +.cache +nosetests.xml +coverage.xml +*.cover +.hypothesis/ +.pytest_cache/ + +# Translations +*.mo +*.pot + +# Django stuff: +*.log +local_settings.py +db.sqlite3 + +# Flask stuff: +instance/ +.webassets-cache + +# Scrapy stuff: +.scrapy + +# Sphinx documentation +docs/_build/ + +# PyBuilder +target/ + +# Jupyter Notebook +.ipynb_checkpoints + +# pyenv +.python-version + +# celery beat schedule file +celerybeat-schedule + +# SageMath parsed files +*.sage.py + +# Environments +.env +.venv +env/ +venv/ +ENV/ +env.bak/ +venv.bak/ + +# Spyder project settings +.spyderproject +.spyproject + +# Rope project settings +.ropeproject + +# mkdocs documentation +/site + +# mypy +.mypy_cache/ diff --git a/LICENSE b/LICENSE index f288702..3877ae0 100644 --- a/LICENSE +++ b/LICENSE @@ -1,674 +1,674 @@ - GNU GENERAL PUBLIC LICENSE - Version 3, 29 June 2007 - - Copyright (C) 2007 Free Software Foundation, Inc. - Everyone is permitted to copy and distribute verbatim copies - of this license document, but changing it is not allowed. - - Preamble - - The GNU General Public License is a free, copyleft license for -software and other kinds of works. - - The licenses for most software and other practical works are designed -to take away your freedom to share and change the works. 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Disclaimer of Warranty. + + THERE IS NO WARRANTY FOR THE PROGRAM, TO THE EXTENT PERMITTED BY +APPLICABLE LAW. EXCEPT WHEN OTHERWISE STATED IN WRITING THE COPYRIGHT +HOLDERS AND/OR OTHER PARTIES PROVIDE THE PROGRAM "AS IS" WITHOUT WARRANTY +OF ANY KIND, EITHER EXPRESSED OR IMPLIED, INCLUDING, BUT NOT LIMITED TO, +THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR +PURPOSE. THE ENTIRE RISK AS TO THE QUALITY AND PERFORMANCE OF THE PROGRAM +IS WITH YOU. SHOULD THE PROGRAM PROVE DEFECTIVE, YOU ASSUME THE COST OF +ALL NECESSARY SERVICING, REPAIR OR CORRECTION. + + 16. Limitation of Liability. + + IN NO EVENT UNLESS REQUIRED BY APPLICABLE LAW OR AGREED TO IN WRITING +WILL ANY COPYRIGHT HOLDER, OR ANY OTHER PARTY WHO MODIFIES AND/OR CONVEYS +THE PROGRAM AS PERMITTED ABOVE, BE LIABLE TO YOU FOR DAMAGES, INCLUDING ANY +GENERAL, SPECIAL, INCIDENTAL OR CONSEQUENTIAL DAMAGES ARISING OUT OF THE +USE OR INABILITY TO USE THE PROGRAM (INCLUDING BUT NOT LIMITED TO LOSS OF +DATA OR DATA BEING RENDERED INACCURATE OR LOSSES SUSTAINED BY YOU OR THIRD +PARTIES OR A FAILURE OF THE PROGRAM TO OPERATE WITH ANY OTHER PROGRAMS), +EVEN IF SUCH HOLDER OR OTHER PARTY HAS BEEN ADVISED OF THE POSSIBILITY OF +SUCH DAMAGES. + + 17. Interpretation of Sections 15 and 16. + + If the disclaimer of warranty and limitation of liability provided +above cannot be given local legal effect according to their terms, +reviewing courts shall apply local law that most closely approximates +an absolute waiver of all civil liability in connection with the +Program, unless a warranty or assumption of liability accompanies a +copy of the Program in return for a fee. + + END OF TERMS AND CONDITIONS + + How to Apply These Terms to Your New Programs + + If you develop a new program, and you want it to be of the greatest +possible use to the public, the best way to achieve this is to make it +free software which everyone can redistribute and change under these terms. + + To do so, attach the following notices to the program. It is safest +to attach them to the start of each source file to most effectively +state the exclusion of warranty; and each file should have at least +the "copyright" line and a pointer to where the full notice is found. + + + Copyright (C) + + This program is free software: you can redistribute it and/or modify + it under the terms of the GNU General Public License as published by + the Free Software Foundation, either version 3 of the License, or + (at your option) any later version. + + This program is distributed in the hope that it will be useful, + but WITHOUT ANY WARRANTY; without even the implied warranty of + MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the + GNU General Public License for more details. + + You should have received a copy of the GNU General Public License + along with this program. If not, see . + +Also add information on how to contact you by electronic and paper mail. + + If the program does terminal interaction, make it output a short +notice like this when it starts in an interactive mode: + + Copyright (C) + This program comes with ABSOLUTELY NO WARRANTY; for details type `show w'. + This is free software, and you are welcome to redistribute it + under certain conditions; type `show c' for details. + +The hypothetical commands `show w' and `show c' should show the appropriate +parts of the General Public License. Of course, your program's commands +might be different; for a GUI interface, you would use an "about box". + + You should also get your employer (if you work as a programmer) or school, +if any, to sign a "copyright disclaimer" for the program, if necessary. +For more information on this, and how to apply and follow the GNU GPL, see +. + + The GNU General Public License does not permit incorporating your program +into proprietary programs. If your program is a subroutine library, you +may consider it more useful to permit linking proprietary applications with +the library. If this is what you want to do, use the GNU Lesser General +Public License instead of this License. But first, please read +. diff --git a/MANIFEST.in b/MANIFEST.in index 8fc2e55..4fb51e1 100644 --- a/MANIFEST.in +++ b/MANIFEST.in @@ -1,6 +1,6 @@ -include README.md -include LICENSE -recursive-exclude * __pycache__ -recursive-exclude * *.pyc -recursive-exclude * *.pyo -recursive-exclude * *.orig +include README.md +include LICENSE +recursive-exclude * __pycache__ +recursive-exclude * *.pyc +recursive-exclude * *.pyo +recursive-exclude * *.orig diff --git a/README.md b/README.md index 6829df5..2a63dbb 100644 --- a/README.md +++ b/README.md @@ -1,43 +1,43 @@ -# 气象数据读写及访问程序库 -提供对MICAPS文件, 卫星云图, 天气雷达等数据的读写, 并访问CIMISS和MICAPS CASSANDRA数据库文件等. - -Only Python 3 is supported. - -## Dependencies -Other required packages: - -- numpy -- scipy -- xarray -- pandas -- pyproj -- protobuf -- urllib3 -- python-dateutil - -## Install -Using the fellowing command to install packages: -``` - pip install git+git://github.com/nmcdev/nmc_met_io.git -``` - -or download the package and install: -``` - git clone --recursive https://github.com/nmcdev/nmc_met_io.git - cd nmc_met_io - python setup.py install -``` - -## 设置CIMISS和MICAPS服务器的地址及用户信息 -在系统用户目录下("C:\Users\用户名"), 新建文本文件config_met_io.ini, 里面内容模板为: -``` -[CIMISS] -DNS = xx.xx.xx.xx -USER_ID = xxxxxxxxx -PASSWORD = xxxxxxxx - -[MICAPS] -GDS_IP = xx.xx.xx.xx -GDS_PORT = xxxx -``` +# 气象数据读写及访问程序库 +提供对MICAPS文件, 卫星云图, 天气雷达等数据的读写, 并访问CIMISS和MICAPS CASSANDRA数据库文件等. + +Only Python 3 is supported. + +## Dependencies +Other required packages: + +- numpy +- scipy +- xarray +- pandas +- pyproj +- protobuf +- urllib3 +- python-dateutil + +## Install +Using the fellowing command to install packages: +``` + pip install git+git://github.com/nmcdev/nmc_met_io.git +``` + +or download the package and install: +``` + git clone --recursive https://github.com/nmcdev/nmc_met_io.git + cd nmc_met_io + python setup.py install +``` + +## 设置CIMISS和MICAPS服务器的地址及用户信息 +在系统用户目录下("C:\Users\用户名"), 新建文本文件config_met_io.ini, 里面内容模板为: +``` +[CIMISS] +DNS = xx.xx.xx.xx +USER_ID = xxxxxxxxx +PASSWORD = xxxxxxxx + +[MICAPS] +GDS_IP = xx.xx.xx.xx +GDS_PORT = xxxx +``` 这里xxxx用相应的地址, 接口和用户信息代替. \ No newline at end of file diff --git a/nmc_met_io/DataBlock_pb2.py b/nmc_met_io/DataBlock_pb2.py index e9fd80c..033f30d 100644 --- a/nmc_met_io/DataBlock_pb2.py +++ b/nmc_met_io/DataBlock_pb2.py @@ -1,359 +1,359 @@ - -# Generated by the protocol buffer compiler. DO NOT EDIT! -# source: DataBlock.proto - -import sys -_b=sys.version_info[0]<3 and (lambda x:x) or (lambda x:x.encode('latin1')) -from google.protobuf import descriptor as _descriptor -from google.protobuf import message as _message -from google.protobuf import reflection as _reflection -from google.protobuf import symbol_database as _symbol_database -from google.protobuf import descriptor_pb2 -# @@protoc_insertion_point(imports) - -_sym_db = _symbol_database.Default() - - -DESCRIPTOR = _descriptor.FileDescriptor( - name='DataBlock.proto', - package='', - syntax='proto3', - serialized_pb=_b('\n\x0f\x44\x61taBlock.proto\"E\n\x0cStringResult\x12\x11\n\terrorCode\x18\x01 \x01(\x05\x12\x14\n\x0c\x65rrorMessage\x18\x02 \x01(\t\x12\x0c\n\x04name\x18\x03 \x01(\t\"M\n\x0f\x42yteArrayResult\x12\x11\n\terrorCode\x18\x01 \x01(\x05\x12\x14\n\x0c\x65rrorMessage\x18\x02 \x01(\t\x12\x11\n\tbyteArray\x18\x03 \x01(\x0c\"h\n\x18StringAndByteArrayResult\x12\x11\n\terrorCode\x18\x01 \x01(\x05\x12\x14\n\x0c\x65rrorMessage\x18\x02 \x01(\t\x12\x10\n\x08\x64\x61taName\x18\x03 \x01(\t\x12\x11\n\tbyteArray\x18\x04 \x01(\x0c\"[\n\x0e\x46ileInfoResult\x12\x11\n\terrorCode\x18\x01 \x01(\x05\x12\x14\n\x0c\x65rrorMessage\x18\x02 \x01(\t\x12\x0e\n\x06isFile\x18\x03 \x01(\x08\x12\x10\n\x08\x66ileSize\x18\x04 \x01(\x03\"\x94\x01\n\tMapResult\x12\x11\n\terrorCode\x18\x01 \x01(\x05\x12\x14\n\x0c\x65rrorMessage\x18\x02 \x01(\t\x12,\n\tresultMap\x18\x03 \x03(\x0b\x32\x19.MapResult.ResultMapEntry\x1a\x30\n\x0eResultMapEntry\x12\x0b\n\x03key\x18\x01 \x01(\t\x12\r\n\x05value\x18\x02 \x01(\t:\x02\x38\x01\x42)\n\x1c\x63n.gov.cma.cimiss.gds.serverB\tDataBlockb\x06proto3') -) -_sym_db.RegisterFileDescriptor(DESCRIPTOR) - - - - -_STRINGRESULT = _descriptor.Descriptor( - name='StringResult', - full_name='StringResult', - filename=None, - file=DESCRIPTOR, - containing_type=None, - fields=[ - _descriptor.FieldDescriptor( - name='errorCode', full_name='StringResult.errorCode', index=0, - number=1, type=5, cpp_type=1, label=1, - has_default_value=False, default_value=0, - message_type=None, enum_type=None, containing_type=None, - is_extension=False, extension_scope=None, - options=None), - _descriptor.FieldDescriptor( - name='errorMessage', full_name='StringResult.errorMessage', index=1, - number=2, type=9, cpp_type=9, label=1, - has_default_value=False, default_value=_b("").decode('utf-8'), - message_type=None, enum_type=None, containing_type=None, - is_extension=False, extension_scope=None, - options=None), - _descriptor.FieldDescriptor( - name='name', full_name='StringResult.name', index=2, - number=3, type=9, cpp_type=9, label=1, - has_default_value=False, default_value=_b("").decode('utf-8'), - message_type=None, enum_type=None, containing_type=None, - is_extension=False, extension_scope=None, - options=None), - ], - extensions=[ - ], - nested_types=[], - enum_types=[ - ], - options=None, - is_extendable=False, - syntax='proto3', - extension_ranges=[], - oneofs=[ - ], - serialized_start=19, - serialized_end=88, -) - - -_BYTEARRAYRESULT = _descriptor.Descriptor( - name='ByteArrayResult', - full_name='ByteArrayResult', - filename=None, - file=DESCRIPTOR, - containing_type=None, - fields=[ - _descriptor.FieldDescriptor( - name='errorCode', full_name='ByteArrayResult.errorCode', index=0, - number=1, type=5, cpp_type=1, label=1, - has_default_value=False, default_value=0, - message_type=None, enum_type=None, containing_type=None, - is_extension=False, extension_scope=None, - options=None), - _descriptor.FieldDescriptor( - name='errorMessage', full_name='ByteArrayResult.errorMessage', index=1, - number=2, type=9, cpp_type=9, label=1, - has_default_value=False, default_value=_b("").decode('utf-8'), - message_type=None, enum_type=None, containing_type=None, - is_extension=False, extension_scope=None, - options=None), - _descriptor.FieldDescriptor( - name='byteArray', full_name='ByteArrayResult.byteArray', index=2, - number=3, type=12, cpp_type=9, label=1, - has_default_value=False, default_value=_b(""), - message_type=None, enum_type=None, containing_type=None, - is_extension=False, extension_scope=None, - options=None), - ], - extensions=[ - ], - nested_types=[], - enum_types=[ - ], - options=None, - is_extendable=False, - syntax='proto3', - extension_ranges=[], - oneofs=[ - ], - serialized_start=90, - serialized_end=167, -) - - -_STRINGANDBYTEARRAYRESULT = _descriptor.Descriptor( - name='StringAndByteArrayResult', - full_name='StringAndByteArrayResult', - filename=None, - file=DESCRIPTOR, - containing_type=None, - fields=[ - _descriptor.FieldDescriptor( - name='errorCode', full_name='StringAndByteArrayResult.errorCode', index=0, - number=1, type=5, cpp_type=1, label=1, - has_default_value=False, default_value=0, - message_type=None, enum_type=None, containing_type=None, - is_extension=False, extension_scope=None, - options=None), - _descriptor.FieldDescriptor( - name='errorMessage', full_name='StringAndByteArrayResult.errorMessage', index=1, - number=2, type=9, cpp_type=9, label=1, - has_default_value=False, default_value=_b("").decode('utf-8'), - message_type=None, enum_type=None, containing_type=None, - is_extension=False, extension_scope=None, - options=None), - _descriptor.FieldDescriptor( - name='dataName', full_name='StringAndByteArrayResult.dataName', index=2, - number=3, type=9, cpp_type=9, label=1, - has_default_value=False, default_value=_b("").decode('utf-8'), - message_type=None, enum_type=None, containing_type=None, - is_extension=False, extension_scope=None, - options=None), - _descriptor.FieldDescriptor( - name='byteArray', full_name='StringAndByteArrayResult.byteArray', index=3, - number=4, type=12, cpp_type=9, label=1, - has_default_value=False, default_value=_b(""), - message_type=None, enum_type=None, containing_type=None, - is_extension=False, extension_scope=None, - options=None), - ], - extensions=[ - ], - nested_types=[], - enum_types=[ - ], - options=None, - is_extendable=False, - syntax='proto3', - extension_ranges=[], - oneofs=[ - ], - serialized_start=169, - serialized_end=273, -) - - -_FILEINFORESULT = _descriptor.Descriptor( - name='FileInfoResult', - full_name='FileInfoResult', - filename=None, - file=DESCRIPTOR, - containing_type=None, - fields=[ - _descriptor.FieldDescriptor( - name='errorCode', full_name='FileInfoResult.errorCode', index=0, - number=1, type=5, cpp_type=1, label=1, - has_default_value=False, default_value=0, - message_type=None, enum_type=None, containing_type=None, - is_extension=False, extension_scope=None, - options=None), - _descriptor.FieldDescriptor( - name='errorMessage', full_name='FileInfoResult.errorMessage', index=1, - number=2, type=9, cpp_type=9, label=1, - has_default_value=False, default_value=_b("").decode('utf-8'), - message_type=None, enum_type=None, containing_type=None, - is_extension=False, extension_scope=None, - options=None), - _descriptor.FieldDescriptor( - name='isFile', full_name='FileInfoResult.isFile', index=2, - number=3, type=8, cpp_type=7, label=1, - has_default_value=False, default_value=False, - message_type=None, enum_type=None, containing_type=None, - is_extension=False, extension_scope=None, - options=None), - _descriptor.FieldDescriptor( - name='fileSize', full_name='FileInfoResult.fileSize', index=3, - number=4, type=3, cpp_type=2, label=1, - has_default_value=False, default_value=0, - message_type=None, enum_type=None, containing_type=None, - is_extension=False, extension_scope=None, - options=None), - ], - extensions=[ - ], - nested_types=[], - enum_types=[ - ], - options=None, - is_extendable=False, - syntax='proto3', - extension_ranges=[], - oneofs=[ - ], - serialized_start=275, - serialized_end=366, -) - - -_MAPRESULT_RESULTMAPENTRY = _descriptor.Descriptor( - name='ResultMapEntry', - full_name='MapResult.ResultMapEntry', - filename=None, - file=DESCRIPTOR, - containing_type=None, - fields=[ - _descriptor.FieldDescriptor( - name='key', full_name='MapResult.ResultMapEntry.key', index=0, - number=1, type=9, cpp_type=9, label=1, - has_default_value=False, default_value=_b("").decode('utf-8'), - message_type=None, enum_type=None, containing_type=None, - is_extension=False, extension_scope=None, - options=None), - _descriptor.FieldDescriptor( - name='value', full_name='MapResult.ResultMapEntry.value', index=1, - number=2, type=9, cpp_type=9, label=1, - has_default_value=False, default_value=_b("").decode('utf-8'), - message_type=None, enum_type=None, containing_type=None, - is_extension=False, extension_scope=None, - options=None), - ], - extensions=[ - ], - nested_types=[], - enum_types=[ - ], - options=_descriptor._ParseOptions(descriptor_pb2.MessageOptions(), _b('8\001')), - is_extendable=False, - syntax='proto3', - extension_ranges=[], - oneofs=[ - ], - serialized_start=469, - serialized_end=517, -) - -_MAPRESULT = _descriptor.Descriptor( - name='MapResult', - full_name='MapResult', - filename=None, - file=DESCRIPTOR, - containing_type=None, - fields=[ - _descriptor.FieldDescriptor( - name='errorCode', full_name='MapResult.errorCode', index=0, - number=1, type=5, cpp_type=1, label=1, - has_default_value=False, default_value=0, - message_type=None, enum_type=None, containing_type=None, - is_extension=False, extension_scope=None, - options=None), - _descriptor.FieldDescriptor( - name='errorMessage', full_name='MapResult.errorMessage', index=1, - number=2, type=9, cpp_type=9, label=1, - has_default_value=False, default_value=_b("").decode('utf-8'), - message_type=None, enum_type=None, containing_type=None, - is_extension=False, extension_scope=None, - options=None), - _descriptor.FieldDescriptor( - name='resultMap', full_name='MapResult.resultMap', index=2, - number=3, type=11, cpp_type=10, label=3, - has_default_value=False, default_value=[], - message_type=None, enum_type=None, containing_type=None, - is_extension=False, extension_scope=None, - options=None), - ], - extensions=[ - ], - nested_types=[_MAPRESULT_RESULTMAPENTRY, ], - enum_types=[ - ], - options=None, - is_extendable=False, - syntax='proto3', - extension_ranges=[], - oneofs=[ - ], - serialized_start=369, - serialized_end=517, -) - -_MAPRESULT_RESULTMAPENTRY.containing_type = _MAPRESULT -_MAPRESULT.fields_by_name['resultMap'].message_type = _MAPRESULT_RESULTMAPENTRY -DESCRIPTOR.message_types_by_name['StringResult'] = _STRINGRESULT -DESCRIPTOR.message_types_by_name['ByteArrayResult'] = _BYTEARRAYRESULT -DESCRIPTOR.message_types_by_name['StringAndByteArrayResult'] = _STRINGANDBYTEARRAYRESULT -DESCRIPTOR.message_types_by_name['FileInfoResult'] = _FILEINFORESULT -DESCRIPTOR.message_types_by_name['MapResult'] = _MAPRESULT - -StringResult = _reflection.GeneratedProtocolMessageType('StringResult', (_message.Message,), dict( - DESCRIPTOR = _STRINGRESULT, - __module__ = 'DataBlock_pb2' - # @@protoc_insertion_point(class_scope:StringResult) - )) -_sym_db.RegisterMessage(StringResult) - -ByteArrayResult = _reflection.GeneratedProtocolMessageType('ByteArrayResult', (_message.Message,), dict( - DESCRIPTOR = _BYTEARRAYRESULT, - __module__ = 'DataBlock_pb2' - # @@protoc_insertion_point(class_scope:ByteArrayResult) - )) -_sym_db.RegisterMessage(ByteArrayResult) - -StringAndByteArrayResult = _reflection.GeneratedProtocolMessageType('StringAndByteArrayResult', (_message.Message,), dict( - DESCRIPTOR = _STRINGANDBYTEARRAYRESULT, - __module__ = 'DataBlock_pb2' - # @@protoc_insertion_point(class_scope:StringAndByteArrayResult) - )) -_sym_db.RegisterMessage(StringAndByteArrayResult) - -FileInfoResult = _reflection.GeneratedProtocolMessageType('FileInfoResult', (_message.Message,), dict( - DESCRIPTOR = _FILEINFORESULT, - __module__ = 'DataBlock_pb2' - # @@protoc_insertion_point(class_scope:FileInfoResult) - )) -_sym_db.RegisterMessage(FileInfoResult) - -MapResult = _reflection.GeneratedProtocolMessageType('MapResult', (_message.Message,), dict( - - ResultMapEntry = _reflection.GeneratedProtocolMessageType('ResultMapEntry', (_message.Message,), dict( - DESCRIPTOR = _MAPRESULT_RESULTMAPENTRY, - __module__ = 'DataBlock_pb2' - # @@protoc_insertion_point(class_scope:MapResult.ResultMapEntry) - )) - , - DESCRIPTOR = _MAPRESULT, - __module__ = 'DataBlock_pb2' - # @@protoc_insertion_point(class_scope:MapResult) - )) -_sym_db.RegisterMessage(MapResult) -_sym_db.RegisterMessage(MapResult.ResultMapEntry) - - -DESCRIPTOR.has_options = True -DESCRIPTOR._options = _descriptor._ParseOptions(descriptor_pb2.FileOptions(), _b('\n\034cn.gov.cma.cimiss.gds.serverB\tDataBlock')) -_MAPRESULT_RESULTMAPENTRY.has_options = True -_MAPRESULT_RESULTMAPENTRY._options = _descriptor._ParseOptions(descriptor_pb2.MessageOptions(), _b('8\001')) -# @@protoc_insertion_point(module_scope) + +# Generated by the protocol buffer compiler. DO NOT EDIT! +# source: DataBlock.proto + +import sys +_b=sys.version_info[0]<3 and (lambda x:x) or (lambda x:x.encode('latin1')) +from google.protobuf import descriptor as _descriptor +from google.protobuf import message as _message +from google.protobuf import reflection as _reflection +from google.protobuf import symbol_database as _symbol_database +from google.protobuf import descriptor_pb2 +# @@protoc_insertion_point(imports) + +_sym_db = _symbol_database.Default() + + +DESCRIPTOR = _descriptor.FileDescriptor( + name='DataBlock.proto', + package='', + syntax='proto3', + serialized_pb=_b('\n\x0f\x44\x61taBlock.proto\"E\n\x0cStringResult\x12\x11\n\terrorCode\x18\x01 \x01(\x05\x12\x14\n\x0c\x65rrorMessage\x18\x02 \x01(\t\x12\x0c\n\x04name\x18\x03 \x01(\t\"M\n\x0f\x42yteArrayResult\x12\x11\n\terrorCode\x18\x01 \x01(\x05\x12\x14\n\x0c\x65rrorMessage\x18\x02 \x01(\t\x12\x11\n\tbyteArray\x18\x03 \x01(\x0c\"h\n\x18StringAndByteArrayResult\x12\x11\n\terrorCode\x18\x01 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number=1, type=5, cpp_type=1, label=1, + has_default_value=False, default_value=0, + message_type=None, enum_type=None, containing_type=None, + is_extension=False, extension_scope=None, + options=None), + _descriptor.FieldDescriptor( + name='errorMessage', full_name='StringResult.errorMessage', index=1, + number=2, type=9, cpp_type=9, label=1, + has_default_value=False, default_value=_b("").decode('utf-8'), + message_type=None, enum_type=None, containing_type=None, + is_extension=False, extension_scope=None, + options=None), + _descriptor.FieldDescriptor( + name='name', full_name='StringResult.name', index=2, + number=3, type=9, cpp_type=9, label=1, + has_default_value=False, default_value=_b("").decode('utf-8'), + message_type=None, enum_type=None, containing_type=None, + is_extension=False, extension_scope=None, + options=None), + ], + extensions=[ + ], + nested_types=[], + enum_types=[ + ], + options=None, + is_extendable=False, + syntax='proto3', + extension_ranges=[], + oneofs=[ + ], + serialized_start=19, + serialized_end=88, +) + + +_BYTEARRAYRESULT = _descriptor.Descriptor( + name='ByteArrayResult', + full_name='ByteArrayResult', + filename=None, + file=DESCRIPTOR, + containing_type=None, + fields=[ + _descriptor.FieldDescriptor( + name='errorCode', full_name='ByteArrayResult.errorCode', index=0, + number=1, type=5, cpp_type=1, label=1, + has_default_value=False, default_value=0, + message_type=None, enum_type=None, containing_type=None, + is_extension=False, extension_scope=None, + options=None), + _descriptor.FieldDescriptor( + name='errorMessage', full_name='ByteArrayResult.errorMessage', index=1, + number=2, type=9, cpp_type=9, label=1, + has_default_value=False, default_value=_b("").decode('utf-8'), + message_type=None, enum_type=None, containing_type=None, + is_extension=False, extension_scope=None, + options=None), + _descriptor.FieldDescriptor( + name='byteArray', full_name='ByteArrayResult.byteArray', index=2, + number=3, type=12, cpp_type=9, label=1, + has_default_value=False, default_value=_b(""), + message_type=None, enum_type=None, containing_type=None, + is_extension=False, extension_scope=None, + options=None), + ], + extensions=[ + ], + nested_types=[], + enum_types=[ + ], + options=None, + is_extendable=False, + syntax='proto3', + extension_ranges=[], + oneofs=[ + ], + serialized_start=90, + serialized_end=167, +) + + +_STRINGANDBYTEARRAYRESULT = _descriptor.Descriptor( + name='StringAndByteArrayResult', + full_name='StringAndByteArrayResult', + filename=None, + file=DESCRIPTOR, + containing_type=None, + fields=[ + _descriptor.FieldDescriptor( + name='errorCode', full_name='StringAndByteArrayResult.errorCode', index=0, + number=1, type=5, cpp_type=1, label=1, + has_default_value=False, default_value=0, + message_type=None, enum_type=None, containing_type=None, + is_extension=False, extension_scope=None, + options=None), + _descriptor.FieldDescriptor( + name='errorMessage', full_name='StringAndByteArrayResult.errorMessage', index=1, + number=2, type=9, cpp_type=9, label=1, + has_default_value=False, default_value=_b("").decode('utf-8'), + message_type=None, enum_type=None, containing_type=None, + is_extension=False, extension_scope=None, + options=None), + _descriptor.FieldDescriptor( + name='dataName', full_name='StringAndByteArrayResult.dataName', index=2, + number=3, type=9, cpp_type=9, label=1, + has_default_value=False, default_value=_b("").decode('utf-8'), + message_type=None, enum_type=None, containing_type=None, + is_extension=False, extension_scope=None, + options=None), + _descriptor.FieldDescriptor( + name='byteArray', full_name='StringAndByteArrayResult.byteArray', index=3, + number=4, type=12, cpp_type=9, label=1, + has_default_value=False, default_value=_b(""), + message_type=None, enum_type=None, containing_type=None, + is_extension=False, extension_scope=None, + options=None), + ], + extensions=[ + ], + nested_types=[], + enum_types=[ + ], + options=None, + is_extendable=False, + syntax='proto3', + extension_ranges=[], + oneofs=[ + ], + serialized_start=169, + serialized_end=273, +) + + +_FILEINFORESULT = _descriptor.Descriptor( + name='FileInfoResult', + full_name='FileInfoResult', + filename=None, + file=DESCRIPTOR, + containing_type=None, + fields=[ + _descriptor.FieldDescriptor( + name='errorCode', full_name='FileInfoResult.errorCode', index=0, + number=1, type=5, cpp_type=1, label=1, + has_default_value=False, default_value=0, + message_type=None, enum_type=None, containing_type=None, + is_extension=False, extension_scope=None, + options=None), + _descriptor.FieldDescriptor( + name='errorMessage', full_name='FileInfoResult.errorMessage', index=1, + number=2, type=9, cpp_type=9, label=1, + has_default_value=False, default_value=_b("").decode('utf-8'), + message_type=None, enum_type=None, containing_type=None, + is_extension=False, extension_scope=None, + options=None), + _descriptor.FieldDescriptor( + name='isFile', full_name='FileInfoResult.isFile', index=2, + number=3, type=8, cpp_type=7, label=1, + has_default_value=False, default_value=False, + message_type=None, enum_type=None, containing_type=None, + is_extension=False, extension_scope=None, + options=None), + _descriptor.FieldDescriptor( + name='fileSize', full_name='FileInfoResult.fileSize', index=3, + number=4, type=3, cpp_type=2, label=1, + has_default_value=False, default_value=0, + message_type=None, enum_type=None, containing_type=None, + is_extension=False, extension_scope=None, + options=None), + ], + extensions=[ + ], + nested_types=[], + enum_types=[ + ], + options=None, + is_extendable=False, + syntax='proto3', + extension_ranges=[], + oneofs=[ + ], + serialized_start=275, + serialized_end=366, +) + + +_MAPRESULT_RESULTMAPENTRY = _descriptor.Descriptor( + name='ResultMapEntry', + full_name='MapResult.ResultMapEntry', + filename=None, + file=DESCRIPTOR, + containing_type=None, + fields=[ + _descriptor.FieldDescriptor( + name='key', full_name='MapResult.ResultMapEntry.key', index=0, + number=1, type=9, cpp_type=9, label=1, + has_default_value=False, default_value=_b("").decode('utf-8'), + message_type=None, enum_type=None, containing_type=None, + is_extension=False, extension_scope=None, + options=None), + _descriptor.FieldDescriptor( + name='value', full_name='MapResult.ResultMapEntry.value', index=1, + number=2, type=9, cpp_type=9, label=1, + has_default_value=False, default_value=_b("").decode('utf-8'), + message_type=None, enum_type=None, containing_type=None, + is_extension=False, extension_scope=None, + options=None), + ], + extensions=[ + ], + nested_types=[], + enum_types=[ + ], + options=_descriptor._ParseOptions(descriptor_pb2.MessageOptions(), _b('8\001')), + is_extendable=False, + syntax='proto3', + extension_ranges=[], + oneofs=[ + ], + serialized_start=469, + serialized_end=517, +) + +_MAPRESULT = _descriptor.Descriptor( + name='MapResult', + full_name='MapResult', + filename=None, + file=DESCRIPTOR, + containing_type=None, + fields=[ + _descriptor.FieldDescriptor( + name='errorCode', full_name='MapResult.errorCode', index=0, + number=1, type=5, cpp_type=1, label=1, + has_default_value=False, default_value=0, + message_type=None, enum_type=None, containing_type=None, + is_extension=False, extension_scope=None, + options=None), + _descriptor.FieldDescriptor( + name='errorMessage', full_name='MapResult.errorMessage', index=1, + number=2, type=9, cpp_type=9, label=1, + has_default_value=False, default_value=_b("").decode('utf-8'), + message_type=None, enum_type=None, containing_type=None, + is_extension=False, extension_scope=None, + options=None), + _descriptor.FieldDescriptor( + name='resultMap', full_name='MapResult.resultMap', index=2, + number=3, type=11, cpp_type=10, label=3, + has_default_value=False, default_value=[], + message_type=None, enum_type=None, containing_type=None, + is_extension=False, extension_scope=None, + options=None), + ], + extensions=[ + ], + nested_types=[_MAPRESULT_RESULTMAPENTRY, ], + enum_types=[ + ], + options=None, + is_extendable=False, + syntax='proto3', + extension_ranges=[], + oneofs=[ + ], + serialized_start=369, + serialized_end=517, +) + +_MAPRESULT_RESULTMAPENTRY.containing_type = _MAPRESULT +_MAPRESULT.fields_by_name['resultMap'].message_type = _MAPRESULT_RESULTMAPENTRY +DESCRIPTOR.message_types_by_name['StringResult'] = _STRINGRESULT +DESCRIPTOR.message_types_by_name['ByteArrayResult'] = _BYTEARRAYRESULT +DESCRIPTOR.message_types_by_name['StringAndByteArrayResult'] = _STRINGANDBYTEARRAYRESULT +DESCRIPTOR.message_types_by_name['FileInfoResult'] = _FILEINFORESULT +DESCRIPTOR.message_types_by_name['MapResult'] = _MAPRESULT + +StringResult = _reflection.GeneratedProtocolMessageType('StringResult', (_message.Message,), dict( + DESCRIPTOR = _STRINGRESULT, + __module__ = 'DataBlock_pb2' + # @@protoc_insertion_point(class_scope:StringResult) + )) +_sym_db.RegisterMessage(StringResult) + +ByteArrayResult = _reflection.GeneratedProtocolMessageType('ByteArrayResult', (_message.Message,), dict( + DESCRIPTOR = _BYTEARRAYRESULT, + __module__ = 'DataBlock_pb2' + # @@protoc_insertion_point(class_scope:ByteArrayResult) + )) +_sym_db.RegisterMessage(ByteArrayResult) + +StringAndByteArrayResult = _reflection.GeneratedProtocolMessageType('StringAndByteArrayResult', (_message.Message,), dict( + DESCRIPTOR = _STRINGANDBYTEARRAYRESULT, + __module__ = 'DataBlock_pb2' + # @@protoc_insertion_point(class_scope:StringAndByteArrayResult) + )) +_sym_db.RegisterMessage(StringAndByteArrayResult) + +FileInfoResult = _reflection.GeneratedProtocolMessageType('FileInfoResult', (_message.Message,), dict( + DESCRIPTOR = _FILEINFORESULT, + __module__ = 'DataBlock_pb2' + # @@protoc_insertion_point(class_scope:FileInfoResult) + )) +_sym_db.RegisterMessage(FileInfoResult) + +MapResult = _reflection.GeneratedProtocolMessageType('MapResult', (_message.Message,), dict( + + ResultMapEntry = _reflection.GeneratedProtocolMessageType('ResultMapEntry', (_message.Message,), dict( + DESCRIPTOR = _MAPRESULT_RESULTMAPENTRY, + __module__ = 'DataBlock_pb2' + # @@protoc_insertion_point(class_scope:MapResult.ResultMapEntry) + )) + , + DESCRIPTOR = _MAPRESULT, + __module__ = 'DataBlock_pb2' + # @@protoc_insertion_point(class_scope:MapResult) + )) +_sym_db.RegisterMessage(MapResult) +_sym_db.RegisterMessage(MapResult.ResultMapEntry) + + +DESCRIPTOR.has_options = True +DESCRIPTOR._options = _descriptor._ParseOptions(descriptor_pb2.FileOptions(), _b('\n\034cn.gov.cma.cimiss.gds.serverB\tDataBlock')) +_MAPRESULT_RESULTMAPENTRY.has_options = True +_MAPRESULT_RESULTMAPENTRY._options = _descriptor._ParseOptions(descriptor_pb2.MessageOptions(), _b('8\001')) +# @@protoc_insertion_point(module_scope) diff --git a/nmc_met_io/__init__.py b/nmc_met_io/__init__.py index 58109b8..6be9fc8 100644 --- a/nmc_met_io/__init__.py +++ b/nmc_met_io/__init__.py @@ -1,7 +1,7 @@ -""" -dk_Met_IO is a package to read or retrieve meteorological data -from various data sources. -""" - -__author__ = "The R & D Center for Weather Forecasting Technology in NMC, CMA" -__version__ = '0.1.0' +""" +dk_Met_IO is a package to read or retrieve meteorological data +from various data sources. +""" + +__author__ = "The R & D Center for Weather Forecasting Technology in NMC, CMA" +__version__ = '0.1.0' diff --git a/nmc_met_io/config.py b/nmc_met_io/config.py index 8e8260d..2b97ea5 100644 --- a/nmc_met_io/config.py +++ b/nmc_met_io/config.py @@ -1,31 +1,31 @@ -# _*_ coding: utf-8 _*_ - -# Copyright (c) 2019 NMC Developers. -# Distributed under the terms of the GPL V3 License. - -""" -Read configure file. -""" - -import os -import configparser - - -def ConfigFetchError(Exception): - pass - - -def _get_config_from_rcfile(): - """ - Get configure information from config_dk_met_io.ini file. - """ - rc = os.path.normpath(os.path.expanduser("~/config_met_io.ini")) - try: - config = configparser.ConfigParser() - config.read(rc) - except IOError as e: - raise ConfigFetchError(str(e)) - except Exception as e: - raise ConfigFetchError(str(e)) - - return config +# _*_ coding: utf-8 _*_ + +# Copyright (c) 2019 NMC Developers. +# Distributed under the terms of the GPL V3 License. + +""" +Read configure file. +""" + +import os +import configparser + + +def ConfigFetchError(Exception): + pass + + +def _get_config_from_rcfile(): + """ + Get configure information from config_dk_met_io.ini file. + """ + rc = os.path.normpath(os.path.expanduser("~/config_met_io.ini")) + try: + config = configparser.ConfigParser() + config.read(rc) + except IOError as e: + raise ConfigFetchError(str(e)) + except Exception as e: + raise ConfigFetchError(str(e)) + + return config diff --git a/nmc_met_io/read_grads.py b/nmc_met_io/read_grads.py index e786d29..50f6c3b 100644 --- a/nmc_met_io/read_grads.py +++ b/nmc_met_io/read_grads.py @@ -1,66 +1,66 @@ -# _*_ coding: utf-8 _*_ - -# Copyright (c) 2019 NMC Developers. -# Distributed under the terms of the GPL V3 License. - -""" -Read grads data file. -""" - -import os -import re -from datetime import datetime -import numpy as np - - -def read_cmp_pre_hour_grid(files, start_lon=70.05, start_lat=15.05): - """ - Read SURF_CLI_CHN_MERGE_CMP_PRE_HOUR_GRID_0.1 data file - - :param files: a single or multiple data filenames. - :param start_lon: region lower left corner longitude. - :param start_lat: region lower left corner latitude. - :return: data and time - - :Examples: - >>> files = ("F:/201607/SURF_CLI_CHN_MERGE_CMP_" - "PRE_HOUR_GRID_0.10-2016070100.grd") - >>> data, time, lon, lat = read_cmp_pre_hour_grid(files) - """ - - # sort and count data files - if isinstance(files, str): - files = np.array([files]) - else: - files = np.array(files) - - # define coordinates - lon = np.arange(700) * 0.1 + start_lon - lat = np.arange(440) * 0.1 + start_lat - - # define variables - data = np.full((len(files), lat.size, lon.size), np.nan) - time = [] - - # loop every data file - for i, f in enumerate(files): - # check file exist - if not os.path.isfile(f): - return None, None, None, None - - # extract time information - ttime = re.search('\d{10}', os.path.basename(f)) - time.append(datetime.strptime(ttime.group(0), "%Y%m%d%H")) - - # read data - try: - tdata = np.fromfile( - f, dtype=np.dtype('float32')).reshape(2, len(lat), len(lon)) - tdata[tdata == -999.0] = np.nan # missing value - data[i, :, :] = tdata[0, :, :] - except IOError: - print("Can not read data from "+f) - continue - - # return value - return data, time, lon, lat +# _*_ coding: utf-8 _*_ + +# Copyright (c) 2019 NMC Developers. +# Distributed under the terms of the GPL V3 License. + +""" +Read grads data file. +""" + +import os +import re +from datetime import datetime +import numpy as np + + +def read_cmp_pre_hour_grid(files, start_lon=70.05, start_lat=15.05): + """ + Read SURF_CLI_CHN_MERGE_CMP_PRE_HOUR_GRID_0.1 data file + + :param files: a single or multiple data filenames. + :param start_lon: region lower left corner longitude. + :param start_lat: region lower left corner latitude. + :return: data and time + + :Examples: + >>> files = ("F:/201607/SURF_CLI_CHN_MERGE_CMP_" + "PRE_HOUR_GRID_0.10-2016070100.grd") + >>> data, time, lon, lat = read_cmp_pre_hour_grid(files) + """ + + # sort and count data files + if isinstance(files, str): + files = np.array([files]) + else: + files = np.array(files) + + # define coordinates + lon = np.arange(700) * 0.1 + start_lon + lat = np.arange(440) * 0.1 + start_lat + + # define variables + data = np.full((len(files), lat.size, lon.size), np.nan) + time = [] + + # loop every data file + for i, f in enumerate(files): + # check file exist + if not os.path.isfile(f): + return None, None, None, None + + # extract time information + ttime = re.search('\d{10}', os.path.basename(f)) + time.append(datetime.strptime(ttime.group(0), "%Y%m%d%H")) + + # read data + try: + tdata = np.fromfile( + f, dtype=np.dtype('float32')).reshape(2, len(lat), len(lon)) + tdata[tdata == -999.0] = np.nan # missing value + data[i, :, :] = tdata[0, :, :] + except IOError: + print("Can not read data from "+f) + continue + + # return value + return data, time, lon, lat diff --git a/nmc_met_io/read_micaps.py b/nmc_met_io/read_micaps.py index 1bdb550..aa68af3 100644 --- a/nmc_met_io/read_micaps.py +++ b/nmc_met_io/read_micaps.py @@ -1,937 +1,937 @@ -# -*- coding: utf-8 -*- - -# Copyright (c) 2019 NMC Developers. -# Distributed under the terms of the GPL V3 License. - -""" -Read micaps data file. -""" - -import os.path -import numpy as np -import xarray as xr -import pandas as pd -from datetime import datetime - - -def read_micaps_3(fname, limit=None): - """ - Read Micaps 3 type file (general scatter point) - - 1 此类数据主要用于非规范的站点填图。填图目前是单要素的。 - 2 此类数据除用于填图外，还可根据站点数据用有限元法直接画等值线 - (只要等值线条数大于 0)。各等值线的值由文件头中的等值线值1、 - 等值线值2 ...来决定。在这些等值线值中可选出一个为加粗线值。 - 3 等值线可以被限制在一个剪切区域内。剪切区域由一个闭合折线定义 - 该折线构成剪切区域的边缘。这个折线由剪切区域边缘线上的点数及 - 各点的经纬度决定。 - 4 当填的是地面要素时，文件头中的“层次”变为控制填图格式的标志： - -1 填6小时降水量。当降水量为0.0mm时填T，当降水量为0.1-0.9时 - 填一位小数，当降水量大于1时只填整数。 - -2 填24小时降水量。当降水量小于1mm时不填，大于等于1mm时只填整数。 - -3 填温度。只填整数。 - - 注意按照MICAPS3.2扩展的数据格式定义，在6小时雨量中，0.0表示微量降水 - 而不是无降水，上述类别数据填图属性中设置小数位数不起作用。考虑到实际 - 业务中使用的数据格式，修改为0.0时表示无降水，大于0并且小于0.1为微量降水 - 任意使用负值或9999表示降水为0，可能会导致数据分析中出现异常结果。 - - :param fname: micaps file name. - :param limit: region limit, [min_lat, min_lon, max_lat, max_lon] - :return: data, pandas type - - :Examples: - >>> data = read_micaps_3('Z:/data/surface/jiany_rr/r20/17032908.000') - - """ - - # check file exist - if not os.path.isfile(fname): - return None - - # read contents - try: - with open(fname, 'r') as f: - # txt = f.read().decode('GBK').replace('\n', ' ').split() - txt = f.read().replace('\n', ' ').split() - except IOError as err: - print("Micaps 3 file error: " + str(err)) - return None - - # head information - head_info = txt[2] - - # date and time - year = int(txt[3]) if len(txt[3]) == 4 else int(txt[3]) + 2000 - month = int(txt[4]) - day = int(txt[5]) - hour = int(txt[6]) - time = datetime(year, month, day, hour) - - # level - level = int(txt[7]) - - # contour information - n_contour = int(txt[8]) - pt = 9 - if n_contour > 0: - contours = np.array(txt[pt:(pt + n_contour - 1)]) - pt += n_contour - - # smooth and bold value - smoothCeof = float(txt[pt]) - pt += 1 - boldCeof = float(txt[pt]) - pt += 1 - - # boundary - n_bound = int(txt[pt]) - pt += 1 - if n_bound > 0: - bound = np.array(txt[pt:(pt + 2 * n_bound - 1)]) - pt += 2 * n_bound - - # number of elements and data - n_elements = int(txt[pt]) - pt += 1 - number = int(txt[pt]) - pt += 1 - - # cut data - txt = np.array(txt[pt:]) - txt.shape = [number, n_elements + 4] - - # initial data - columns = list(['ID', 'lon', 'lat', 'alt']) - columns.extend(['V%s' % x for x in range(n_elements)]) - data = pd.DataFrame(txt, columns=columns) - - # convert column type - data = data.ix[:, 1:].apply(pd.to_numeric) - - # cut the region - if limit is not None: - data = data[(limit[0] <= data['lat']) & (data['lat'] <= limit[2]) & - (limit[1] <= data['lon']) & (data['lon'] <= limit[3])] - - # check records - if len(data) == 0: - return None - - # add time - data['time'] = time - data['level'] = level - - # return - return data - - -def read_micaps_4(fname, limit=None): - """ - Read Micaps 4 type file (grid) - - :param fname: micaps file name. - :param limit: region limit, [min_lat, min_lon, max_lat, max_lon] - :return: data, xarray type - - :Examples: - >>> data = read_micaps_4('Z:/data/newecmwf_grib/pressure/17032008.006') - - """ - - # check file exist - if not os.path.isfile(fname): - return None - - # read contents - try: - with open(fname, encoding='gb18030', errors='ignore') as f: - # txt = f.read().decode('GBK').replace('\n', ' ').split() - txt = f.read().replace('\n', ' ').split() - except IOError as err: - print("Micaps 4 file error: " + str(err)) - return None - - # head information - head_info = txt[2] - - # date and time - year = int(txt[3]) if len(txt[3]) == 4 else int(txt[3]) + 2000 - month = int(txt[4]) - day = int(txt[5]) - hour = int(txt[6]) - fhour = int(txt[7]) - if hour >= 24: # some times, micaps file head change the order. - hour = int(txt[7]) - fhour = int(txt[6]) - - time = datetime(year, month, day, hour) - - # vertical level - level = float(txt[8]) - - # grid information - xint = float(txt[9]) - yint = float(txt[10]) - slon = float(txt[11]) - slat = float(txt[13]) - nlon = int(txt[15]) - nlat = int(txt[16]) - lon = slon + np.arange(nlon) * xint - lat = slat + np.arange(nlat) * yint - - # contour information - cnInterval = float(txt[17]) - cnStart = float(txt[18]) - cnEnd = float(txt[19]) - - # smooth and bold value - smoothCeof = float(txt[20]) - boldCeof = float(txt[21]) - - # extract data - data = (np.array(txt[22:])).astype(np.float) - data.shape = [nlat, nlon] - - # check latitude order - if lat[0] > lat[1]: - lat = lat[::-1] - data = data[::-1, :] - - # create xarray data - data = xr.DataArray(data, coords=[lat, lon], dims=['lat', 'lon']) - - # subset data - if limit is not None: - lat_bnds, lon_bnds = [limit[0], limit[2]], [limit[1], limit[3]] - data = data.sel(lat=slice(*lat_bnds), lon=slice(*lon_bnds)) - - # add attributes - data.attrs['time'] = time - data.attrs['fhour'] = fhour - data.attrs['level'] = level - data.attrs['head_info'] = head_info - data.attrs['cnInterval'] = cnInterval - data.attrs['cnStart'] = cnStart - data.attrs['cnEnd'] = cnEnd - data.attrs['smoothCeof'] = smoothCeof - data.attrs['boldCeof'] = boldCeof - - # return - return data - - -def read_micaps_11(fname, limit=None): - """ - Read Micaps 11 type file (grid u, v vector data) - - :param fname: micaps file name. - :param limit: region limit, [min_lat, min_lon, max_lat, max_lon] - :return: data, xarray type - - :Examples: - >>> data = read_micaps_4('Z:/data/newecmwf_grib/pressure/17032008.006') - - """ - - # check file exist - if not os.path.isfile(fname): - return None - - # read contents - try: - with open(fname, 'r') as f: - # txt = f.read().decode('GBK').replace('\n', ' ').split() - txt = f.read().replace('\n', ' ').split() - except IOError as err: - print("Micaps 4 file error: " + str(err)) - return None - - # head information - head_info = txt[2] - - # date and time - year = int(txt[3]) if len(txt[3]) == 4 else int(txt[3]) + 2000 - month = int(txt[4]) - day = int(txt[5]) - hour = int(txt[6]) - time = datetime(year, month, day, hour) - fhour = int(txt[7]) - - # vertical level - level = float(txt[8]) - - # grid information - xint = float(txt[9]) - yint = float(txt[10]) - slon = float(txt[11]) - slat = float(txt[13]) - nlon = int(txt[15]) - nlat = int(txt[16]) - lon = slon + np.arange(nlon) * xint - lat = slat + np.arange(nlat) * yint - - # extract data - data = (np.array(txt[17:])).astype(np.float) - data.shape = [2, nlat, nlon] - - # check latitude order - if lat[0] > lat[1]: - lat = lat[::-1] - data = data[:, ::-1, :] - - # create xarray data - uwind = np.squeeze(data[0, :, :]) - vwind = np.squeeze(data[1, :, :]) - speed = np.sqrt(uwind*uwind + vwind*vwind) - data = xr.Dataset({ - 'uwind': (['lat', 'lon'], uwind), - 'vwind': (['lat', 'lon'], vwind), - 'speed': (['lat', 'lon'], speed)}, - coords={'lat':lat, 'lon':lon}) - - # subset data - if limit is not None: - lat_bnds, lon_bnds = [limit[0], limit[2]], [limit[1], limit[3]] - data = data.sel(lat=slice(*lat_bnds), lon=slice(*lon_bnds)) - - # add attributes - data.attrs['time'] = time - data.attrs['fhour'] = fhour - data.attrs['level'] = level - data.attrs['head_info'] = head_info - - # return - return data - - -def read_micaps_14(fname): - """ - Read micaps 14 file (编辑图象的图元数据, 即交互操作结果数据). - - :param fname: micaps 14 filename. - :return: data dictionary - - :Examples: - >>> data = read_micaps_14("Z:/diamond/update/rr082008.024") - - """ - - # check file exist - if not os.path.isfile(fname): - return None - - # read contents - try: - with open(fname, 'r') as f: - txt = f.read().replace('\n', ' ').split() - except IOError as err: - print("Micaps 14 file error: " + str(err)) - return None - - # head information - head_info = txt[2] - - # date and time - year = int(txt[3]) if len(txt[3]) == 4 else int(txt[3]) + 2000 - month = int(txt[4]) - day = int(txt[5]) - hour = int(txt[6]) - time = datetime(year, month, day, hour) - fhour = int(txt[7]) - - # ====================================================== - # read lines - # ====================================================== - if 'LINES:' in txt: - # get the start position - idx = txt.index('LINES:') - - # number of lines - number = int(txt[idx+1]) - idx += 2 - - # loop every line - if number > 0: - # define data - line_width = [] - line_xyz_num = [] - line_xyz = [] - line_label_num = [] - line_label = [] - line_label_xyz = [] - - for i in range(number): - # line width - width = float(txt[idx]) - line_width.append(width) - idx += 1 - - # line xyz point number - xyz_num = int(txt[idx]) - line_xyz_num.append(xyz_num) - idx += 1 - - # line xyz - xyz = np.array(txt[idx:(idx + 3*xyz_num)]).astype(np.float) - xyz.shape = [xyz_num, 3] - line_xyz.append(xyz) - idx += xyz_num * 3 - - # line label - label = txt[idx] - line_label.append(label) - idx += 1 - - # line label number - label_num = int(txt[idx]) - line_label_num.append(label_num) - idx += 1 - - # label xyz - if label_num > 0: - label_xyz = np.array( - txt[idx:(idx + 3*label_num)]).astype(np.float) - label_xyz.shape = [label_num, 3] - line_label_xyz.append(label_xyz) - idx += label_num * 3 - else: - line_label_xyz.append([]) - - # construct line data type - lines = { - "line_width": line_width, "line_xyz_num": line_xyz_num, - "line_xyz": line_xyz, "line_label_num": line_label_num, - "line_label": line_label, "line_label_xyz": line_label_xyz} - else: - lines = {} - else: - lines = {} - - # ====================================================== - # read line symbols - # ====================================================== - if 'LINES_SYMBOL:' in txt: - # get the start position - idx = txt.index('LINES_SYMBOL:') - - # number of line symbols - number = int(txt[idx + 1]) - idx += 2 - - # loop every line symbol - if number > 0: - # define data - linesym_code = [] - linesym_width = [] - linesym_xyz_num = [] - linesym_xyz = [] - - for i in range(number): - # line symbol code - code = int(txt[idx]) - linesym_code.append(code) - idx += 1 - - # line width - width = float(txt[idx]) - linesym_width.append(width) - idx += 1 - - # line symbol xyz point number - xyz_num = int(txt[idx]) - linesym_xyz_num.append(xyz_num) - idx += 1 - - # line symbol xyz - xyz = np.array(txt[idx:(idx + 3*xyz_num)]).astype(np.float) - xyz.shape = [xyz_num, 3] - linesym_xyz.append(xyz) - idx += xyz_num * 3 - - # line symbol label - label = txt[idx] - idx += 1 - - # line symbol label number - label_num = int(txt[idx]) - idx += label_num * 3 + 1 - - lines_symbol = {"linesym_code": linesym_code, - "linesym_width": linesym_width, - "linesym_xyz_num": linesym_xyz_num, - "linesym_xyz": linesym_xyz} - else: - lines_symbol = {} - else: - lines_symbol = {} - - # ====================================================== - # read symbol - # ====================================================== - if "SYMBOLS:" in txt: - # start position of symbols - idx = txt.index("SYMBOLS:") - - # number of lines - number = int(txt[idx + 1]) - idx += 2 - - # loop every symbol - if number > 0: - # define data - symbol_code = [] - symbol_xyz = [] - symbol_value = [] - - for i in range(number): - # symbol code - code = int(txt[idx]) - symbol_code.append(code) - idx += 1 - - # symbol xyz - xyz = np.array(txt[idx:(idx + 3)]).astype(np.float) - symbol_xyz.append(xyz) - idx += 3 - - # symbol value - value = txt[idx] - symbol_value.append(value) - idx += 1 - - symbols = {"symbol_code": symbol_code, - "symbol_xyz": symbol_xyz, - "symbol_value": symbol_value} - else: - symbols = {} - else: - symbols = {} - - # ====================================================== - # read closed contours - # ====================================================== - if "CLOSED_CONTOURS:" in txt: - # get the start position - idx = txt.index('CLOSED_CONTOURS:') - - # number of lines - number = int(txt[idx + 1]) - idx += 2 - - # loop every closed contour - if number > 0: - # define data - cn_width = [] - cn_xyz_num = [] - cn_xyz = [] - cn_label_num = [] - cn_label = [] - cn_label_xyz = [] - - for i in range(number): - # line width - width = float(txt[idx]) - cn_width.append(width) - idx += 1 - - # line xyz point number - xyz_num = int(txt[idx]) - cn_xyz_num.append(xyz_num) - idx += 1 - - # line xyz - xyz = np.array(txt[idx:(idx + 3 * xyz_num)]).astype(np.float) - xyz.shape = [xyz_num, 3] - cn_xyz.append(xyz) - idx += 3 * xyz_num - - # line label - label = txt[idx] - cn_label.append(label) - idx += 1 - - # line label number - label_num = int(txt[idx]) - cn_label_num.append(label_num) - idx += 1 - - # label xyz - if label_num > 0: - label_xyz = np.array( - txt[idx:(idx + 3 * label_num)]).astype(np.float) - label_xyz.shape = [3, label_num] - cn_label_xyz.append(label_xyz) - idx += label_num * 3 - else: - cn_label_xyz.append([]) - - closed_contours = { - "cn_width": cn_width, "cn_xyz_num": cn_xyz_num, - "cn_xyz": cn_xyz, "cn_label": cn_label, - "cn_label_num": cn_label_num, "cn_label_xyz": cn_label_xyz} - else: - closed_contours = {} - else: - closed_contours = {} - - # ====================================================== - # read station situation - # ====================================================== - if "STATION_SITUATION" in txt: - # get the start position - idx = txt.index('STATION_SITUATION') - - # find data subscript - end_idx = idx + 1 - while txt[end_idx].isdigit() and end_idx < len(txt): - end_idx += 1 - if end_idx > idx + 1: - stations = np.array(txt[(idx+1):(end_idx)]) - stations.shape = [len(stations)//2, 2] - else: - stations = None - else: - stations = None - - # ====================================================== - # read weather regions - # ====================================================== - if "WEATHER_REGION:" in txt: - # get the start position - idx = txt.index('WEATHER_REGION:') - - # number of regions - number = int(txt[idx + 1]) - idx += 2 - - # loop every region - if number > 0: - # define data - weather_region_code = [] - weather_region_xyz_num = [] - weather_region_xyz = [] - - for i in range(number): - # region code - code = int(txt[idx]) - weather_region_code.append(code) - idx += 1 - - # region xyz point number - xyz_num = int(txt[idx]) - weather_region_xyz_num.append(xyz_num) - idx += 1 - - # region xyz point - xyz = np.array( - txt[idx:(idx + 3*xyz_num)]).astype(np.float) - xyz.shape = [xyz_num, 3] - weather_region_xyz.append(xyz) - idx += 3 * xyz_num - - weather_region = { - "weather_region_code": weather_region_code, - "weather_region_xyz_num": weather_region_xyz_num, - "weather_region_xyz": weather_region_xyz} - else: - weather_region = {} - else: - weather_region = {} - - # ====================================================== - # read fill area - # ====================================================== - if "FILLAREA:" in txt: - # get the start position - idx = txt.index('FILLAREA:') - - # number of regions - number = int(txt[idx + 1]) - idx += 2 - - # loop every fill area - if number > 0: - # define data - fillarea_code = [] - fillarea_num = [] - fillarea_xyz = [] - fillarea_type = [] - fillarea_color = [] - fillarea_frontcolor = [] - fillarea_backcolor = [] - fillarea_gradient_angle = [] - fillarea_graphics_type = [] - fillarea_frame = [] - - for i in range(number): - # code - code = int(txt[idx]) - fillarea_code.append(code) - idx += 1 - - # xyz point number - xyz_num = int(txt[idx]) - fillarea_num.append(xyz_num) - idx += 1 - - # xyz point - xyz = np.array( - txt[idx:(idx + 3 * xyz_num)]).astype(np.float) - xyz.shape = [xyz_num, 3] - fillarea_xyz.append(xyz) - idx += 3 * xyz_num - - # fill type - ftype = int(txt[idx]) - fillarea_type.append(ftype) - idx += 1 - - # line color - color = np.array(txt[idx:(idx + 4)]).astype(np.int) - fillarea_color.append(color) - idx += 4 - - # front color - front_color = np.array(txt[idx:(idx + 4)]).astype(np.int) - fillarea_frontcolor.append(front_color) - idx += 4 - - # background color - back_color = np.array(txt[idx:(idx + 4)]).astype(np.int) - fillarea_backcolor.append(back_color) - idx += 4 - - # color gradient angle - gradient_angle = float(txt[idx]) - fillarea_gradient_angle.append(gradient_angle) - idx += 1 - - # graphics type - graphics_type = int(txt[idx]) - fillarea_graphics_type.append(graphics_type) - idx += 1 - - # draw frame or not - frame = int(txt[idx]) - fillarea_frame.append(frame) - idx += 1 - - fill_area = { - "fillarea_code": fillarea_code, "fillarea_num": fillarea_num, - "fillarea_xyz": fillarea_xyz, "fillarea_type": fillarea_type, - "fillarea_color": fillarea_color, - "fillarea_frontcolor": fillarea_frontcolor, - "fillarea_backcolor": fillarea_backcolor, - "fillarea_gradient_angle": fillarea_gradient_angle, - "fillarea_graphics_type": fillarea_graphics_type, - "fillarea_frame": fillarea_frame} - else: - fill_area = {} - else: - fill_area = {} - - # ====================================================== - # read notes symbol - # ====================================================== - if "NOTES_SYMBOL:" in txt: - # get the start position - idx = txt.index('NOTES_SYMBOL:') - - # number of regions - number = int(txt[idx + 1]) - idx += 2 - - # loop every notes symbol - if number > 0: - # define data - nsymbol_code = [] - nsymbol_xyz = [] - nsymbol_charLen = [] - nsymbol_char = [] - nsymbol_angle = [] - nsymbol_fontLen = [] - nsymbol_fontName = [] - nsymbol_fontSize = [] - nsymbol_fontType = [] - nsymbol_color = [] - - for i in range(number): - # code - code = int(txt[idx]) - nsymbol_code.append(code) - idx += 1 - - # xyz - xyz = np.array(txt[idx:(idx + 3)]).astype(np.float) - nsymbol_xyz.append([xyz]) - idx += 3 - - # character length - char_len = int(txt[idx]) - nsymbol_charLen.append(char_len) - idx += 1 - - # characters - char = txt[idx] - nsymbol_char.append(char) - idx += 1 - - # character angle - angle = txt[idx] - nsymbol_angle.append(angle) - idx += 1 - - # font length - font_len = txt[idx] - nsymbol_fontLen.append(font_len) - idx += 1 - - # font name - font_name = txt[idx] - nsymbol_fontName.append(font_name) - idx += 1 - - # font size - font_size = txt[idx] - nsymbol_fontSize.append(font_size) - idx += 1 - - # font type - font_type = txt[idx] - nsymbol_fontType.append(font_type) - idx += 1 - - # color - color = np.array(txt[idx:(idx + 4)]).astype(np.int) - nsymbol_color.append(color) - idx += 4 - - notes_symbol = { - "nsymbol_code": nsymbol_code, - "nsymbol_xyz": nsymbol_xyz, - "nsymbol_charLen": nsymbol_charLen, - "nsymbol_char": nsymbol_char, - "nsymbol_angle": nsymbol_angle, - "nsymbol_fontLen": nsymbol_fontLen, - "nsymbol_fontName": nsymbol_fontName, - "nsymbol_fontSize": nsymbol_fontSize, - "nsymbol_fontType": nsymbol_fontType, - "nsymbol_color": nsymbol_color} - else: - notes_symbol = {} - else: - notes_symbol = {} - - # ====================================================== - # read lines symbols with property - # ====================================================== - if "WITHPROP_LINESYMBOLS:" in txt: - # get the start position - idx = txt.index('WITHPROP_LINESYMBOLS:') - - # number of regions - number = int(txt[idx + 1]) - idx += 2 - - # loop every line symbol - if number > 0: - # define data - plinesym_code = [] - plinesym_width = [] - plinesym_color = [] - plinesym_type = [] - plinesym_shadow = [] - plinesym_xyz_num = [] - plinesym_xyz = [] - plinesym_label = [] - plinesym_label_num = [] - plinesym_label_xyz = [] - - for i in range(number): - # line symbol code - code = int(txt[idx]) - plinesym_code.append(code) - idx += 1 - - # line width - width = float(txt[idx]) - plinesym_width.append(width) - idx += 1 - - # line color - color = np.array(txt[idx:(idx + 3)]).astype(np.int) - plinesym_color.append([color]) - idx += 3 - - # line type - ltype = int(txt[idx]) - plinesym_type.append(ltype) - idx += 1 - - # line shadow - shadow = int(txt[idx]) - plinesym_shadow.append(shadow) - idx += 1 - - # line symbol xyz point number - xyz_num = int(txt[idx]) - plinesym_xyz_num.append(xyz_num) - idx += 1 - - # line symbol xyz - xyz = np.array(txt[idx:(idx + 3 * xyz_num)]).astype(np.float) - xyz.shape = [xyz_num, 3] - plinesym_xyz.append(xyz) - idx += 3 * xyz_num - - # line symbol label - label = txt[idx] - plinesym_label.append(label) - idx += 1 - - # line label number - label_num = int(txt[idx]) - plinesym_label_num.append(label_num) - idx += 1 - - # label xyz - if label_num > 0: - label_xyz = np.array( - txt[idx:(idx + 3 * label_num)]).astype(np.float) - label_xyz.shape = [label_num, 3] - plinesym_label_xyz.append(label_xyz) - idx += label_num * 3 - else: - plinesym_label_xyz.append([]) - - plines_symbol = { - "plinesym_code": plinesym_code, - "plinesym_width": plinesym_width, - "plinesym_color": plinesym_color, - "plinesym_type": plinesym_type, - "plinesym_shadow": plinesym_shadow, - "plinesym_xyz_num": plinesym_xyz_num, - "plinesym_xyz": plinesym_xyz, - "plinesym_label": plinesym_label, - "plinesym_label_num": plinesym_label_num, - "plinesym_label_xyz": plinesym_label_xyz} - else: - plines_symbol = {} - else: - plines_symbol = {} - - # return data contents - return {"file_type": 14, - "time": time, - "fhour": fhour, - "lines": lines, - "lines_symbol": lines_symbol, - "symbols": symbols, - "closed_contours": closed_contours, - "stations": stations, - "weather_region": weather_region, - "fill_area": fill_area, - "notes_symbol": notes_symbol, - "plines_symbol": plines_symbol} - +# -*- coding: utf-8 -*- + +# Copyright (c) 2019 NMC Developers. +# Distributed under the terms of the GPL V3 License. + +""" +Read micaps data file. +""" + +import os.path +import numpy as np +import xarray as xr +import pandas as pd +from datetime import datetime + + +def read_micaps_3(fname, limit=None): + """ + Read Micaps 3 type file (general scatter point) + + 1 此类数据主要用于非规范的站点填图。填图目前是单要素的。 + 2 此类数据除用于填图外，还可根据站点数据用有限元法直接画等值线 + (只要等值线条数大于 0)。各等值线的值由文件头中的等值线值1、 + 等值线值2 ...来决定。在这些等值线值中可选出一个为加粗线值。 + 3 等值线可以被限制在一个剪切区域内。剪切区域由一个闭合折线定义 + 该折线构成剪切区域的边缘。这个折线由剪切区域边缘线上的点数及 + 各点的经纬度决定。 + 4 当填的是地面要素时，文件头中的“层次”变为控制填图格式的标志： + -1 填6小时降水量。当降水量为0.0mm时填T，当降水量为0.1-0.9时 + 填一位小数，当降水量大于1时只填整数。 + -2 填24小时降水量。当降水量小于1mm时不填，大于等于1mm时只填整数。 + -3 填温度。只填整数。 + + 注意按照MICAPS3.2扩展的数据格式定义，在6小时雨量中，0.0表示微量降水 + 而不是无降水，上述类别数据填图属性中设置小数位数不起作用。考虑到实际 + 业务中使用的数据格式，修改为0.0时表示无降水，大于0并且小于0.1为微量降水 + 任意使用负值或9999表示降水为0，可能会导致数据分析中出现异常结果。 + + :param fname: micaps file name. + :param limit: region limit, [min_lat, min_lon, max_lat, max_lon] + :return: data, pandas type + + :Examples: + >>> data = read_micaps_3('Z:/data/surface/jiany_rr/r20/17032908.000') + + """ + + # check file exist + if not os.path.isfile(fname): + return None + + # read contents + try: + with open(fname, 'r') as f: + # txt = f.read().decode('GBK').replace('\n', ' ').split() + txt = f.read().replace('\n', ' ').split() + except IOError as err: + print("Micaps 3 file error: " + str(err)) + return None + + # head information + head_info = txt[2] + + # date and time + year = int(txt[3]) if len(txt[3]) == 4 else int(txt[3]) + 2000 + month = int(txt[4]) + day = int(txt[5]) + hour = int(txt[6]) + time = datetime(year, month, day, hour) + + # level + level = int(txt[7]) + + # contour information + n_contour = int(txt[8]) + pt = 9 + if n_contour > 0: + contours = np.array(txt[pt:(pt + n_contour - 1)]) + pt += n_contour + + # smooth and bold value + smoothCeof = float(txt[pt]) + pt += 1 + boldCeof = float(txt[pt]) + pt += 1 + + # boundary + n_bound = int(txt[pt]) + pt += 1 + if n_bound > 0: + bound = np.array(txt[pt:(pt + 2 * n_bound - 1)]) + pt += 2 * n_bound + + # number of elements and data + n_elements = int(txt[pt]) + pt += 1 + number = int(txt[pt]) + pt += 1 + + # cut data + txt = np.array(txt[pt:]) + txt.shape = [number, n_elements + 4] + + # initial data + columns = list(['ID', 'lon', 'lat', 'alt']) + columns.extend(['V%s' % x for x in range(n_elements)]) + data = pd.DataFrame(txt, columns=columns) + + # convert column type + data = data.ix[:, 1:].apply(pd.to_numeric) + + # cut the region + if limit is not None: + data = data[(limit[0] <= data['lat']) & (data['lat'] <= limit[2]) & + (limit[1] <= data['lon']) & (data['lon'] <= limit[3])] + + # check records + if len(data) == 0: + return None + + # add time + data['time'] = time + data['level'] = level + + # return + return data + + +def read_micaps_4(fname, limit=None): + """ + Read Micaps 4 type file (grid) + + :param fname: micaps file name. + :param limit: region limit, [min_lat, min_lon, max_lat, max_lon] + :return: data, xarray type + + :Examples: + >>> data = read_micaps_4('Z:/data/newecmwf_grib/pressure/17032008.006') + + """ + + # check file exist + if not os.path.isfile(fname): + return None + + # read contents + try: + with open(fname, encoding='gb18030', errors='ignore') as f: + # txt = f.read().decode('GBK').replace('\n', ' ').split() + txt = f.read().replace('\n', ' ').split() + except IOError as err: + print("Micaps 4 file error: " + str(err)) + return None + + # head information + head_info = txt[2] + + # date and time + year = int(txt[3]) if len(txt[3]) == 4 else int(txt[3]) + 2000 + month = int(txt[4]) + day = int(txt[5]) + hour = int(txt[6]) + fhour = int(txt[7]) + if hour >= 24: # some times, micaps file head change the order. + hour = int(txt[7]) + fhour = int(txt[6]) + + time = datetime(year, month, day, hour) + + # vertical level + level = float(txt[8]) + + # grid information + xint = float(txt[9]) + yint = float(txt[10]) + slon = float(txt[11]) + slat = float(txt[13]) + nlon = int(txt[15]) + nlat = int(txt[16]) + lon = slon + np.arange(nlon) * xint + lat = slat + np.arange(nlat) * yint + + # contour information + cnInterval = float(txt[17]) + cnStart = float(txt[18]) + cnEnd = float(txt[19]) + + # smooth and bold value + smoothCeof = float(txt[20]) + boldCeof = float(txt[21]) + + # extract data + data = (np.array(txt[22:])).astype(np.float) + data.shape = [nlat, nlon] + + # check latitude order + if lat[0] > lat[1]: + lat = lat[::-1] + data = data[::-1, :] + + # create xarray data + data = xr.DataArray(data, coords=[lat, lon], dims=['lat', 'lon']) + + # subset data + if limit is not None: + lat_bnds, lon_bnds = [limit[0], limit[2]], [limit[1], limit[3]] + data = data.sel(lat=slice(*lat_bnds), lon=slice(*lon_bnds)) + + # add attributes + data.attrs['time'] = time + data.attrs['fhour'] = fhour + data.attrs['level'] = level + data.attrs['head_info'] = head_info + data.attrs['cnInterval'] = cnInterval + data.attrs['cnStart'] = cnStart + data.attrs['cnEnd'] = cnEnd + data.attrs['smoothCeof'] = smoothCeof + data.attrs['boldCeof'] = boldCeof + + # return + return data + + +def read_micaps_11(fname, limit=None): + """ + Read Micaps 11 type file (grid u, v vector data) + + :param fname: micaps file name. + :param limit: region limit, [min_lat, min_lon, max_lat, max_lon] + :return: data, xarray type + + :Examples: + >>> data = read_micaps_4('Z:/data/newecmwf_grib/pressure/17032008.006') + + """ + + # check file exist + if not os.path.isfile(fname): + return None + + # read contents + try: + with open(fname, 'r') as f: + # txt = f.read().decode('GBK').replace('\n', ' ').split() + txt = f.read().replace('\n', ' ').split() + except IOError as err: + print("Micaps 4 file error: " + str(err)) + return None + + # head information + head_info = txt[2] + + # date and time + year = int(txt[3]) if len(txt[3]) == 4 else int(txt[3]) + 2000 + month = int(txt[4]) + day = int(txt[5]) + hour = int(txt[6]) + time = datetime(year, month, day, hour) + fhour = int(txt[7]) + + # vertical level + level = float(txt[8]) + + # grid information + xint = float(txt[9]) + yint = float(txt[10]) + slon = float(txt[11]) + slat = float(txt[13]) + nlon = int(txt[15]) + nlat = int(txt[16]) + lon = slon + np.arange(nlon) * xint + lat = slat + np.arange(nlat) * yint + + # extract data + data = (np.array(txt[17:])).astype(np.float) + data.shape = [2, nlat, nlon] + + # check latitude order + if lat[0] > lat[1]: + lat = lat[::-1] + data = data[:, ::-1, :] + + # create xarray data + uwind = np.squeeze(data[0, :, :]) + vwind = np.squeeze(data[1, :, :]) + speed = np.sqrt(uwind*uwind + vwind*vwind) + data = xr.Dataset({ + 'uwind': (['lat', 'lon'], uwind), + 'vwind': (['lat', 'lon'], vwind), + 'speed': (['lat', 'lon'], speed)}, + coords={'lat':lat, 'lon':lon}) + + # subset data + if limit is not None: + lat_bnds, lon_bnds = [limit[0], limit[2]], [limit[1], limit[3]] + data = data.sel(lat=slice(*lat_bnds), lon=slice(*lon_bnds)) + + # add attributes + data.attrs['time'] = time + data.attrs['fhour'] = fhour + data.attrs['level'] = level + data.attrs['head_info'] = head_info + + # return + return data + + +def read_micaps_14(fname): + """ + Read micaps 14 file (编辑图象的图元数据, 即交互操作结果数据). + + :param fname: micaps 14 filename. + :return: data dictionary + + :Examples: + >>> data = read_micaps_14("Z:/diamond/update/rr082008.024") + + """ + + # check file exist + if not os.path.isfile(fname): + return None + + # read contents + try: + with open(fname, 'r') as f: + txt = f.read().replace('\n', ' ').split() + except IOError as err: + print("Micaps 14 file error: " + str(err)) + return None + + # head information + head_info = txt[2] + + # date and time + year = int(txt[3]) if len(txt[3]) == 4 else int(txt[3]) + 2000 + month = int(txt[4]) + day = int(txt[5]) + hour = int(txt[6]) + time = datetime(year, month, day, hour) + fhour = int(txt[7]) + + # ====================================================== + # read lines + # ====================================================== + if 'LINES:' in txt: + # get the start position + idx = txt.index('LINES:') + + # number of lines + number = int(txt[idx+1]) + idx += 2 + + # loop every line + if number > 0: + # define data + line_width = [] + line_xyz_num = [] + line_xyz = [] + line_label_num = [] + line_label = [] + line_label_xyz = [] + + for i in range(number): + # line width + width = float(txt[idx]) + line_width.append(width) + idx += 1 + + # line xyz point number + xyz_num = int(txt[idx]) + line_xyz_num.append(xyz_num) + idx += 1 + + # line xyz + xyz = np.array(txt[idx:(idx + 3*xyz_num)]).astype(np.float) + xyz.shape = [xyz_num, 3] + line_xyz.append(xyz) + idx += xyz_num * 3 + + # line label + label = txt[idx] + line_label.append(label) + idx += 1 + + # line label number + label_num = int(txt[idx]) + line_label_num.append(label_num) + idx += 1 + + # label xyz + if label_num > 0: + label_xyz = np.array( + txt[idx:(idx + 3*label_num)]).astype(np.float) + label_xyz.shape = [label_num, 3] + line_label_xyz.append(label_xyz) + idx += label_num * 3 + else: + line_label_xyz.append([]) + + # construct line data type + lines = { + "line_width": line_width, "line_xyz_num": line_xyz_num, + "line_xyz": line_xyz, "line_label_num": line_label_num, + "line_label": line_label, "line_label_xyz": line_label_xyz} + else: + lines = {} + else: + lines = {} + + # ====================================================== + # read line symbols + # ====================================================== + if 'LINES_SYMBOL:' in txt: + # get the start position + idx = txt.index('LINES_SYMBOL:') + + # number of line symbols + number = int(txt[idx + 1]) + idx += 2 + + # loop every line symbol + if number > 0: + # define data + linesym_code = [] + linesym_width = [] + linesym_xyz_num = [] + linesym_xyz = [] + + for i in range(number): + # line symbol code + code = int(txt[idx]) + linesym_code.append(code) + idx += 1 + + # line width + width = float(txt[idx]) + linesym_width.append(width) + idx += 1 + + # line symbol xyz point number + xyz_num = int(txt[idx]) + linesym_xyz_num.append(xyz_num) + idx += 1 + + # line symbol xyz + xyz = np.array(txt[idx:(idx + 3*xyz_num)]).astype(np.float) + xyz.shape = [xyz_num, 3] + linesym_xyz.append(xyz) + idx += xyz_num * 3 + + # line symbol label + label = txt[idx] + idx += 1 + + # line symbol label number + label_num = int(txt[idx]) + idx += label_num * 3 + 1 + + lines_symbol = {"linesym_code": linesym_code, + "linesym_width": linesym_width, + "linesym_xyz_num": linesym_xyz_num, + "linesym_xyz": linesym_xyz} + else: + lines_symbol = {} + else: + lines_symbol = {} + + # ====================================================== + # read symbol + # ====================================================== + if "SYMBOLS:" in txt: + # start position of symbols + idx = txt.index("SYMBOLS:") + + # number of lines + number = int(txt[idx + 1]) + idx += 2 + + # loop every symbol + if number > 0: + # define data + symbol_code = [] + symbol_xyz = [] + symbol_value = [] + + for i in range(number): + # symbol code + code = int(txt[idx]) + symbol_code.append(code) + idx += 1 + + # symbol xyz + xyz = np.array(txt[idx:(idx + 3)]).astype(np.float) + symbol_xyz.append(xyz) + idx += 3 + + # symbol value + value = txt[idx] + symbol_value.append(value) + idx += 1 + + symbols = {"symbol_code": symbol_code, + "symbol_xyz": symbol_xyz, + "symbol_value": symbol_value} + else: + symbols = {} + else: + symbols = {} + + # ====================================================== + # read closed contours + # ====================================================== + if "CLOSED_CONTOURS:" in txt: + # get the start position + idx = txt.index('CLOSED_CONTOURS:') + + # number of lines + number = int(txt[idx + 1]) + idx += 2 + + # loop every closed contour + if number > 0: + # define data + cn_width = [] + cn_xyz_num = [] + cn_xyz = [] + cn_label_num = [] + cn_label = [] + cn_label_xyz = [] + + for i in range(number): + # line width + width = float(txt[idx]) + cn_width.append(width) + idx += 1 + + # line xyz point number + xyz_num = int(txt[idx]) + cn_xyz_num.append(xyz_num) + idx += 1 + + # line xyz + xyz = np.array(txt[idx:(idx + 3 * xyz_num)]).astype(np.float) + xyz.shape = [xyz_num, 3] + cn_xyz.append(xyz) + idx += 3 * xyz_num + + # line label + label = txt[idx] + cn_label.append(label) + idx += 1 + + # line label number + label_num = int(txt[idx]) + cn_label_num.append(label_num) + idx += 1 + + # label xyz + if label_num > 0: + label_xyz = np.array( + txt[idx:(idx + 3 * label_num)]).astype(np.float) + label_xyz.shape = [3, label_num] + cn_label_xyz.append(label_xyz) + idx += label_num * 3 + else: + cn_label_xyz.append([]) + + closed_contours = { + "cn_width": cn_width, "cn_xyz_num": cn_xyz_num, + "cn_xyz": cn_xyz, "cn_label": cn_label, + "cn_label_num": cn_label_num, "cn_label_xyz": cn_label_xyz} + else: + closed_contours = {} + else: + closed_contours = {} + + # ====================================================== + # read station situation + # ====================================================== + if "STATION_SITUATION" in txt: + # get the start position + idx = txt.index('STATION_SITUATION') + + # find data subscript + end_idx = idx + 1 + while txt[end_idx].isdigit() and end_idx < len(txt): + end_idx += 1 + if end_idx > idx + 1: + stations = np.array(txt[(idx+1):(end_idx)]) + stations.shape = [len(stations)//2, 2] + else: + stations = None + else: + stations = None + + # ====================================================== + # read weather regions + # ====================================================== + if "WEATHER_REGION:" in txt: + # get the start position + idx = txt.index('WEATHER_REGION:') + + # number of regions + number = int(txt[idx + 1]) + idx += 2 + + # loop every region + if number > 0: + # define data + weather_region_code = [] + weather_region_xyz_num = [] + weather_region_xyz = [] + + for i in range(number): + # region code + code = int(txt[idx]) + weather_region_code.append(code) + idx += 1 + + # region xyz point number + xyz_num = int(txt[idx]) + weather_region_xyz_num.append(xyz_num) + idx += 1 + + # region xyz point + xyz = np.array( + txt[idx:(idx + 3*xyz_num)]).astype(np.float) + xyz.shape = [xyz_num, 3] + weather_region_xyz.append(xyz) + idx += 3 * xyz_num + + weather_region = { + "weather_region_code": weather_region_code, + "weather_region_xyz_num": weather_region_xyz_num, + "weather_region_xyz": weather_region_xyz} + else: + weather_region = {} + else: + weather_region = {} + + # ====================================================== + # read fill area + # ====================================================== + if "FILLAREA:" in txt: + # get the start position + idx = txt.index('FILLAREA:') + + # number of regions + number = int(txt[idx + 1]) + idx += 2 + + # loop every fill area + if number > 0: + # define data + fillarea_code = [] + fillarea_num = [] + fillarea_xyz = [] + fillarea_type = [] + fillarea_color = [] + fillarea_frontcolor = [] + fillarea_backcolor = [] + fillarea_gradient_angle = [] + fillarea_graphics_type = [] + fillarea_frame = [] + + for i in range(number): + # code + code = int(txt[idx]) + fillarea_code.append(code) + idx += 1 + + # xyz point number + xyz_num = int(txt[idx]) + fillarea_num.append(xyz_num) + idx += 1 + + # xyz point + xyz = np.array( + txt[idx:(idx + 3 * xyz_num)]).astype(np.float) + xyz.shape = [xyz_num, 3] + fillarea_xyz.append(xyz) + idx += 3 * xyz_num + + # fill type + ftype = int(txt[idx]) + fillarea_type.append(ftype) + idx += 1 + + # line color + color = np.array(txt[idx:(idx + 4)]).astype(np.int) + fillarea_color.append(color) + idx += 4 + + # front color + front_color = np.array(txt[idx:(idx + 4)]).astype(np.int) + fillarea_frontcolor.append(front_color) + idx += 4 + + # background color + back_color = np.array(txt[idx:(idx + 4)]).astype(np.int) + fillarea_backcolor.append(back_color) + idx += 4 + + # color gradient angle + gradient_angle = float(txt[idx]) + fillarea_gradient_angle.append(gradient_angle) + idx += 1 + + # graphics type + graphics_type = int(txt[idx]) + fillarea_graphics_type.append(graphics_type) + idx += 1 + + # draw frame or not + frame = int(txt[idx]) + fillarea_frame.append(frame) + idx += 1 + + fill_area = { + "fillarea_code": fillarea_code, "fillarea_num": fillarea_num, + "fillarea_xyz": fillarea_xyz, "fillarea_type": fillarea_type, + "fillarea_color": fillarea_color, + "fillarea_frontcolor": fillarea_frontcolor, + "fillarea_backcolor": fillarea_backcolor, + "fillarea_gradient_angle": fillarea_gradient_angle, + "fillarea_graphics_type": fillarea_graphics_type, + "fillarea_frame": fillarea_frame} + else: + fill_area = {} + else: + fill_area = {} + + # ====================================================== + # read notes symbol + # ====================================================== + if "NOTES_SYMBOL:" in txt: + # get the start position + idx = txt.index('NOTES_SYMBOL:') + + # number of regions + number = int(txt[idx + 1]) + idx += 2 + + # loop every notes symbol + if number > 0: + # define data + nsymbol_code = [] + nsymbol_xyz = [] + nsymbol_charLen = [] + nsymbol_char = [] + nsymbol_angle = [] + nsymbol_fontLen = [] + nsymbol_fontName = [] + nsymbol_fontSize = [] + nsymbol_fontType = [] + nsymbol_color = [] + + for i in range(number): + # code + code = int(txt[idx]) + nsymbol_code.append(code) + idx += 1 + + # xyz + xyz = np.array(txt[idx:(idx + 3)]).astype(np.float) + nsymbol_xyz.append([xyz]) + idx += 3 + + # character length + char_len = int(txt[idx]) + nsymbol_charLen.append(char_len) + idx += 1 + + # characters + char = txt[idx] + nsymbol_char.append(char) + idx += 1 + + # character angle + angle = txt[idx] + nsymbol_angle.append(angle) + idx += 1 + + # font length + font_len = txt[idx] + nsymbol_fontLen.append(font_len) + idx += 1 + + # font name + font_name = txt[idx] + nsymbol_fontName.append(font_name) + idx += 1 + + # font size + font_size = txt[idx] + nsymbol_fontSize.append(font_size) + idx += 1 + + # font type + font_type = txt[idx] + nsymbol_fontType.append(font_type) + idx += 1 + + # color + color = np.array(txt[idx:(idx + 4)]).astype(np.int) + nsymbol_color.append(color) + idx += 4 + + notes_symbol = { + "nsymbol_code": nsymbol_code, + "nsymbol_xyz": nsymbol_xyz, + "nsymbol_charLen": nsymbol_charLen, + "nsymbol_char": nsymbol_char, + "nsymbol_angle": nsymbol_angle, + "nsymbol_fontLen": nsymbol_fontLen, + "nsymbol_fontName": nsymbol_fontName, + "nsymbol_fontSize": nsymbol_fontSize, + "nsymbol_fontType": nsymbol_fontType, + "nsymbol_color": nsymbol_color} + else: + notes_symbol = {} + else: + notes_symbol = {} + + # ====================================================== + # read lines symbols with property + # ====================================================== + if "WITHPROP_LINESYMBOLS:" in txt: + # get the start position + idx = txt.index('WITHPROP_LINESYMBOLS:') + + # number of regions + number = int(txt[idx + 1]) + idx += 2 + + # loop every line symbol + if number > 0: + # define data + plinesym_code = [] + plinesym_width = [] + plinesym_color = [] + plinesym_type = [] + plinesym_shadow = [] + plinesym_xyz_num = [] + plinesym_xyz = [] + plinesym_label = [] + plinesym_label_num = [] + plinesym_label_xyz = [] + + for i in range(number): + # line symbol code + code = int(txt[idx]) + plinesym_code.append(code) + idx += 1 + + # line width + width = float(txt[idx]) + plinesym_width.append(width) + idx += 1 + + # line color + color = np.array(txt[idx:(idx + 3)]).astype(np.int) + plinesym_color.append([color]) + idx += 3 + + # line type + ltype = int(txt[idx]) + plinesym_type.append(ltype) + idx += 1 + + # line shadow + shadow = int(txt[idx]) + plinesym_shadow.append(shadow) + idx += 1 + + # line symbol xyz point number + xyz_num = int(txt[idx]) + plinesym_xyz_num.append(xyz_num) + idx += 1 + + # line symbol xyz + xyz = np.array(txt[idx:(idx + 3 * xyz_num)]).astype(np.float) + xyz.shape = [xyz_num, 3] + plinesym_xyz.append(xyz) + idx += 3 * xyz_num + + # line symbol label + label = txt[idx] + plinesym_label.append(label) + idx += 1 + + # line label number + label_num = int(txt[idx]) + plinesym_label_num.append(label_num) + idx += 1 + + # label xyz + if label_num > 0: + label_xyz = np.array( + txt[idx:(idx + 3 * label_num)]).astype(np.float) + label_xyz.shape = [label_num, 3] + plinesym_label_xyz.append(label_xyz) + idx += label_num * 3 + else: + plinesym_label_xyz.append([]) + + plines_symbol = { + "plinesym_code": plinesym_code, + "plinesym_width": plinesym_width, + "plinesym_color": plinesym_color, + "plinesym_type": plinesym_type, + "plinesym_shadow": plinesym_shadow, + "plinesym_xyz_num": plinesym_xyz_num, + "plinesym_xyz": plinesym_xyz, + "plinesym_label": plinesym_label, + "plinesym_label_num": plinesym_label_num, + "plinesym_label_xyz": plinesym_label_xyz} + else: + plines_symbol = {} + else: + plines_symbol = {} + + # return data contents + return {"file_type": 14, + "time": time, + "fhour": fhour, + "lines": lines, + "lines_symbol": lines_symbol, + "symbols": symbols, + "closed_contours": closed_contours, + "stations": stations, + "weather_region": weather_region, + "fill_area": fill_area, + "notes_symbol": notes_symbol, + "plines_symbol": plines_symbol} + diff --git a/nmc_met_io/read_radar.py b/nmc_met_io/read_radar.py index 98d26cf..f4c5032 100644 --- a/nmc_met_io/read_radar.py +++ b/nmc_met_io/read_radar.py @@ -1,114 +1,114 @@ -# -*- coding: utf-8 -*- - -# Copyright (c) 2019 NMC Developers. -# Distributed under the terms of the GPL V3 License. - -""" -Read CMA radar format file. -""" - -from array import array -import numpy as np - - -def read_cma_sa_radar(fname): - """ - Read CMA SA radar format file. - refer to - https://github.com/smft/CMA_SA_RADAR_READER/blob/master/read_RADAR.py - https://github.com/smft/CMA_SA_RADAR_READER/blob/master/barb_plot.py - for plot map. - - :param fname: file path name. - :return: data dictionary. - - """ - - # read data - flag = open(fname, "r") - data = np.asarray(array("B", flag.read())) - data = data.reshape([len(data)/2432, 2432]) - - # find elevation angle - if data[0, 72] == 11: - phi = [0.50, 0.50, 1.45, 1.45, 2.40, 3.35, 4.30, - 5.25, 6.2, 7.5, 8.7, 10, 12, 14, 16.7, 19.5] - if data[0, 72] == 21: - phi = [0.50, 0.50, 1.45, 1.45, 2.40, 3.35, 4.30, - 6.00, 9.00, 14.6, 19.5] - if data[0, 72] == 31: - phi = [0.50, 0.50, 1.50, 1.50, 2.50, 2.50, 3.50, 4.50] - if data[0, 72] == 32: - phi = [0.50, 0.50, 2.50, 3.50, 4.50] - - # define data - g1 = np.zeros([len(data), 460]) - h1 = np.zeros([len(data), 460]) - i1 = np.zeros([len(data), 460]) - j1 = np.zeros([len(data), 460]) - - # process data - count = 0 - while count < len(data): - print("径向数据编号 : ", count) - b1 = data[count, 44] + 256 * data[count, 45] # 仰角序数 - c1 = ((data[count, 36] + 256 * data[count, 37]) / - 8 * 180 / 4096) # 方位角 - d1 = data[count, 54] + 256 * data[count, 55] # 径向库 - print("仰角序数,方位角,径向库 : ", b1, c1, d1) - if d1 == 0: - count += 1 - continue - else: - count += 1 - i = 0 - while i < 460: - g1[count - 1, i] = phi[b1 - 1] # 仰角 - h1[count - 1, i] = c1 # 方位角 - i1[count - 1, i] = 0.5 + i - 1 # 径向 - if i > d1: # 反射率 - j1[count - 1, i] = 0 - else: - if data[count - 1, 128 + i] == 0: # 无数据 - j1[count - 1, i] = 0 - else: - if data[count - 1, 128 + i] == 1: # 距离模糊 - j1[count - 1, i] = 0 - else: # 数据正常 - j1[count - 1, i] = ((data[count - 1, 128 + i] - 2) / - 2 - 32) - i += 1 - - # calculate angle index - n = 3 - a2 = 0 # 仰角序数 - while a2 < len(data): - if data[a2, 44] > (n - 1): - break - a2 += 1 - a3 = a2 - while a3 < len(data): - if data[a3, 44] > n: - break - a3 += 1 - - # put data - yj = g1[a2:a3, :] # 仰角 - fwj = h1[a2:a3, :] # 方位角 - jx = i1[a2:a3, :] # 径向 - fsl = j1[a2:a3, :] # 反射率 - - # return data - return yj, fwj, jx, fsl - - -def sph2cart(elevation, azimuth, r): - """ - Convert spherical coordinates to cartesian. - """ - - ele, a = np.deg2rad([elevation, azimuth]) - x = r * np.cos(ele) * np.cos(a) - y = r * np.cos(ele) * np.sin(a) - z = r * np.sin(ele) - return x, y, z +# -*- coding: utf-8 -*- + +# Copyright (c) 2019 NMC Developers. +# Distributed under the terms of the GPL V3 License. + +""" +Read CMA radar format file. +""" + +from array import array +import numpy as np + + +def read_cma_sa_radar(fname): + """ + Read CMA SA radar format file. + refer to + https://github.com/smft/CMA_SA_RADAR_READER/blob/master/read_RADAR.py + https://github.com/smft/CMA_SA_RADAR_READER/blob/master/barb_plot.py + for plot map. + + :param fname: file path name. + :return: data dictionary. + + """ + + # read data + flag = open(fname, "r") + data = np.asarray(array("B", flag.read())) + data = data.reshape([len(data)/2432, 2432]) + + # find elevation angle + if data[0, 72] == 11: + phi = [0.50, 0.50, 1.45, 1.45, 2.40, 3.35, 4.30, + 5.25, 6.2, 7.5, 8.7, 10, 12, 14, 16.7, 19.5] + if data[0, 72] == 21: + phi = [0.50, 0.50, 1.45, 1.45, 2.40, 3.35, 4.30, + 6.00, 9.00, 14.6, 19.5] + if data[0, 72] == 31: + phi = [0.50, 0.50, 1.50, 1.50, 2.50, 2.50, 3.50, 4.50] + if data[0, 72] == 32: + phi = [0.50, 0.50, 2.50, 3.50, 4.50] + + # define data + g1 = np.zeros([len(data), 460]) + h1 = np.zeros([len(data), 460]) + i1 = np.zeros([len(data), 460]) + j1 = np.zeros([len(data), 460]) + + # process data + count = 0 + while count < len(data): + print("径向数据编号 : ", count) + b1 = data[count, 44] + 256 * data[count, 45] # 仰角序数 + c1 = ((data[count, 36] + 256 * data[count, 37]) / + 8 * 180 / 4096) # 方位角 + d1 = data[count, 54] + 256 * data[count, 55] # 径向库 + print("仰角序数,方位角,径向库 : ", b1, c1, d1) + if d1 == 0: + count += 1 + continue + else: + count += 1 + i = 0 + while i < 460: + g1[count - 1, i] = phi[b1 - 1] # 仰角 + h1[count - 1, i] = c1 # 方位角 + i1[count - 1, i] = 0.5 + i - 1 # 径向 + if i > d1: # 反射率 + j1[count - 1, i] = 0 + else: + if data[count - 1, 128 + i] == 0: # 无数据 + j1[count - 1, i] = 0 + else: + if data[count - 1, 128 + i] == 1: # 距离模糊 + j1[count - 1, i] = 0 + else: # 数据正常 + j1[count - 1, i] = ((data[count - 1, 128 + i] - 2) / + 2 - 32) + i += 1 + + # calculate angle index + n = 3 + a2 = 0 # 仰角序数 + while a2 < len(data): + if data[a2, 44] > (n - 1): + break + a2 += 1 + a3 = a2 + while a3 < len(data): + if data[a3, 44] > n: + break + a3 += 1 + + # put data + yj = g1[a2:a3, :] # 仰角 + fwj = h1[a2:a3, :] # 方位角 + jx = i1[a2:a3, :] # 径向 + fsl = j1[a2:a3, :] # 反射率 + + # return data + return yj, fwj, jx, fsl + + +def sph2cart(elevation, azimuth, r): + """ + Convert spherical coordinates to cartesian. + """ + + ele, a = np.deg2rad([elevation, azimuth]) + x = r * np.cos(ele) * np.cos(a) + y = r * np.cos(ele) * np.sin(a) + z = r * np.sin(ele) + return x, y, z diff --git a/nmc_met_io/read_satellite.py b/nmc_met_io/read_satellite.py index 5e9870c..0d0b970 100644 --- a/nmc_met_io/read_satellite.py +++ b/nmc_met_io/read_satellite.py @@ -1,179 +1,179 @@ -# -*- coding: utf-8 -*- - -# Copyright (c) 2019 NMC Developers. -# Distributed under the terms of the GPL V3 License. - -""" -Read FY satellite awx format file. -""" - -import numpy as np - - -def read_awx_cloud(fname): - """ - Read satellite awx format file. - - :param fname: file pathname. - :return: data list - """ - - # read part of binary - # refer to - # https://stackoverflow.com/questions/14245094/how-to-read-part-of-binary-file-with-numpy - - pass - - -def read_himawari(fname, resolution): - """ - Read the japan himawari satellite standard data file. - refere to - https://github.com/smft/Read_Himawari_binary_data/blob/master/read_Himawari.py - - :param fname: data file pathname. - :param resolution: data resolution. - - :return: data list. - """ - - # define resolution - if resolution == 1: - res = 12100000 - nlin = 1100 - ncol = 11000 - elif resolution == 2: - res = 3025000 - nlin = 550 - ncol = 5500 - else: - res = 48400000 - nlin = 2200 - ncol = 22000 - - # define binary file format - formation = [('bn', 'i1', 1), - ('bl', 'i2', 1), - ('thb', 'i2', 1), - ('bo', 'i1', 1), - ('sn', 'S1', 16), - ('pcn', 'S1', 16), - ('oa', 'S1', 4), - ('obf', 'S1', 2), - ('ot', 'i2', 1), - ('ost', 'float64', 1), - ('oet', 'float64', 1), - ('fct', 'float64', 1), - ('thl', 'i4', 1), - ('tdl', 'i4', 1), - ('qf1', 'i1', 1), - ('qf2', 'i1', 1), - ('qf3', 'i1', 1), - ('qf4', 'i1', 1), - ('ffv', 'S1', 32), - ('fn', 'S1', 128), - ('null1', 'S1', 40), - ('bn2', 'i1', 1), - ('bl2', 'i2', 1), - ('nbpp', 'i2', 1), - ('noc', 'i2', 1), - ('nol', 'i2', 1), - ('cffdb', 'i1', 1), - ('null2', 'S1', 40), - ('bn3', 'i1', 1), - ('bl3', 'i2', 1), - ('sl', 'float64', 1), - ('CFAC', 'i4', 1), - ('LFAC', 'i4', 1), - ('COFF', 'float32', 1), - ('LOFF', 'float32', 1), - ('dfectvs', 'float64', 1), - ('eer', 'float64', 1), - ('epr', 'float64', 1), - ('var1', 'float64', 1), - ('var2', 'float64', 1), - ('var3', 'float64', 1), - ('cfsd', 'float64', 1), - ('rt', 'i2', 1), - ('rs', 'i2', 1), - ('null3', 'S1', 40), - ('bn4', 'i1', 1), - ('bl4', 'i2', 1), - ('ni', 'float64', 1), - ('ssplon', 'float64', 1), - ('ssplat', 'float64', 1), - ('dfects4', 'float64', 1), - ('nlat', 'float64', 1), - ('nlon', 'float64', 1), - ('sp', 'float64', 3), - ('mp', 'float64', 3), - ('null4', 'S1', 40), - ('bn5', 'i1', 1), - ('bl5', 'i2', 1), - ('bdn', 'i2', 1), - ('cwl', 'float64', 1), - ('vnobpp', 'i2', 1), - ('cvoep', 'uint16', 1), - ('cvoposa', 'uint16', 1), - ('gfcce', 'float64', 1), - ('cfcce', 'float64', 1), - ('c0', 'float64', 1), - ('c1', 'float64', 1), - ('c2', 'float64', 1), - ('C0', 'float64', 1), - ('C1', 'float64', 1), - ('C2', 'float64', 1), - ('sol', 'float64', 1), - ('pc', 'float64', 1), - ('bc', 'float64', 1), - ('null5', 'S1', 40), - ('b06n01', 'i1', 1), - ('b06n02', 'i2', 1), - ('b06n03', 'float64', 1), - ('b06n04', 'float64', 1), - ('b06n05', 'float64', 1), - ('b06n06', 'float64', 1), - ('b06n07', 'float64', 1), - ('b06n08', 'float64', 1), - ('b06n09', 'float64', 1), - ('b06n10', 'float64', 1), - ('b06n11', 'float32', 1), - ('b06n12', 'float32', 1), - ('b06n13', 'S1', 128), - ('b06n14', 'S1', 56), - ('b07n01', 'i1', 1), - ('b07n02', 'i2', 1), - ('b07n03', 'i1', 1), - ('b07n04', 'i1', 1), - ('b07n05', 'i2', 1), - ('b07n06', 'S1', 40), - ('b08n01', 'i1', 1), - ('b08n02', 'i2', 1), - ('b08n03', 'float32', 1), - ('b08n04', 'float32', 1), - ('b08n05', 'float64', 1), - ('b08n06', 'i2', 1), - ('b08n07', 'i2', 1), - ('b08n08', 'float32', 1), - ('b08n09', 'float32', 1), - ('b08n10', 'S1', 50), - ('b09n01', 'i1', 1), - ('b09n02', 'i2', 1), - ('b09n03', 'i2', 1), - ('b09n04', 'i2', 1), - ('b09n05', 'float64', 1), - ('b09n06', 'S1', 70), - ('b10n01', 'i1', 1), - ('b10n02', 'i4', 1), - ('b10n03', 'i2', 1), - ('b10n04', 'i2', 1), - ('b10n05', 'i2', 1), - ('b10n06', 'S1', 36), - ('b11n01', 'i1', 1), - ('b11n02', 'i2', 1), - ('b11n03', 'S1', 256), - ('b12n01', 'i2', res)] - - data = np.fromfile(fname, dtype=formation)['b12n01'].reshape(nlin, ncol) - - return list(data) +# -*- coding: utf-8 -*- + +# Copyright (c) 2019 NMC Developers. +# Distributed under the terms of the GPL V3 License. + +""" +Read FY satellite awx format file. +""" + +import numpy as np + + +def read_awx_cloud(fname): + """ + Read satellite awx format file. + + :param fname: file pathname. + :return: data list + """ + + # read part of binary + # refer to + # https://stackoverflow.com/questions/14245094/how-to-read-part-of-binary-file-with-numpy + + pass + + +def read_himawari(fname, resolution): + """ + Read the japan himawari satellite standard data file. + refere to + https://github.com/smft/Read_Himawari_binary_data/blob/master/read_Himawari.py + + :param fname: data file pathname. + :param resolution: data resolution. + + :return: data list. + """ + + # define resolution + if resolution == 1: + res = 12100000 + nlin = 1100 + ncol = 11000 + elif resolution == 2: + res = 3025000 + nlin = 550 + ncol = 5500 + else: + res = 48400000 + nlin = 2200 + ncol = 22000 + + # define binary file format + formation = [('bn', 'i1', 1), + ('bl', 'i2', 1), + ('thb', 'i2', 1), + ('bo', 'i1', 1), + ('sn', 'S1', 16), + ('pcn', 'S1', 16), + ('oa', 'S1', 4), + ('obf', 'S1', 2), + ('ot', 'i2', 1), + ('ost', 'float64', 1), + ('oet', 'float64', 1), + ('fct', 'float64', 1), + ('thl', 'i4', 1), + ('tdl', 'i4', 1), + ('qf1', 'i1', 1), + ('qf2', 'i1', 1), + ('qf3', 'i1', 1), + ('qf4', 'i1', 1), + ('ffv', 'S1', 32), + ('fn', 'S1', 128), + ('null1', 'S1', 40), + ('bn2', 'i1', 1), + ('bl2', 'i2', 1), + ('nbpp', 'i2', 1), + ('noc', 'i2', 1), + ('nol', 'i2', 1), + ('cffdb', 'i1', 1), + ('null2', 'S1', 40), + ('bn3', 'i1', 1), + ('bl3', 'i2', 1), + ('sl', 'float64', 1), + ('CFAC', 'i4', 1), + ('LFAC', 'i4', 1), + ('COFF', 'float32', 1), + ('LOFF', 'float32', 1), + ('dfectvs', 'float64', 1), + ('eer', 'float64', 1), + ('epr', 'float64', 1), + ('var1', 'float64', 1), + ('var2', 'float64', 1), + ('var3', 'float64', 1), + ('cfsd', 'float64', 1), + ('rt', 'i2', 1), + ('rs', 'i2', 1), + ('null3', 'S1', 40), + ('bn4', 'i1', 1), + ('bl4', 'i2', 1), + ('ni', 'float64', 1), + ('ssplon', 'float64', 1), + ('ssplat', 'float64', 1), + ('dfects4', 'float64', 1), + ('nlat', 'float64', 1), + ('nlon', 'float64', 1), + ('sp', 'float64', 3), + ('mp', 'float64', 3), + ('null4', 'S1', 40), + ('bn5', 'i1', 1), + ('bl5', 'i2', 1), + ('bdn', 'i2', 1), + ('cwl', 'float64', 1), + ('vnobpp', 'i2', 1), + ('cvoep', 'uint16', 1), + ('cvoposa', 'uint16', 1), + ('gfcce', 'float64', 1), + ('cfcce', 'float64', 1), + ('c0', 'float64', 1), + ('c1', 'float64', 1), + ('c2', 'float64', 1), + ('C0', 'float64', 1), + ('C1', 'float64', 1), + ('C2', 'float64', 1), + ('sol', 'float64', 1), + ('pc', 'float64', 1), + ('bc', 'float64', 1), + ('null5', 'S1', 40), + ('b06n01', 'i1', 1), + ('b06n02', 'i2', 1), + ('b06n03', 'float64', 1), + ('b06n04', 'float64', 1), + ('b06n05', 'float64', 1), + ('b06n06', 'float64', 1), + ('b06n07', 'float64', 1), + ('b06n08', 'float64', 1), + ('b06n09', 'float64', 1), + ('b06n10', 'float64', 1), + ('b06n11', 'float32', 1), + ('b06n12', 'float32', 1), + ('b06n13', 'S1', 128), + ('b06n14', 'S1', 56), + ('b07n01', 'i1', 1), + ('b07n02', 'i2', 1), + ('b07n03', 'i1', 1), + ('b07n04', 'i1', 1), + ('b07n05', 'i2', 1), + ('b07n06', 'S1', 40), + ('b08n01', 'i1', 1), + ('b08n02', 'i2', 1), + ('b08n03', 'float32', 1), + ('b08n04', 'float32', 1), + ('b08n05', 'float64', 1), + ('b08n06', 'i2', 1), + ('b08n07', 'i2', 1), + ('b08n08', 'float32', 1), + ('b08n09', 'float32', 1), + ('b08n10', 'S1', 50), + ('b09n01', 'i1', 1), + ('b09n02', 'i2', 1), + ('b09n03', 'i2', 1), + ('b09n04', 'i2', 1), + ('b09n05', 'float64', 1), + ('b09n06', 'S1', 70), + ('b10n01', 'i1', 1), + ('b10n02', 'i4', 1), + ('b10n03', 'i2', 1), + ('b10n04', 'i2', 1), + ('b10n05', 'i2', 1), + ('b10n06', 'S1', 36), + ('b11n01', 'i1', 1), + ('b11n02', 'i2', 1), + ('b11n03', 'S1', 256), + ('b12n01', 'i2', res)] + + data = np.fromfile(fname, dtype=formation)['b12n01'].reshape(nlin, ncol) + + return list(data) diff --git a/nmc_met_io/retrieve_cimiss_history.py b/nmc_met_io/retrieve_cimiss_history.py index 1254947..febaa61 100644 --- a/nmc_met_io/retrieve_cimiss_history.py +++ b/nmc_met_io/retrieve_cimiss_history.py @@ -1,166 +1,166 @@ -# -*- coding: utf-8 -*- - -# Copyright (c) 2019 NMC Developers. -# Distributed under the terms of the GPL V3 License. - -""" -Retrieve historical data from CIMISS service. -""" - -import os -import calendar -import urllib.request -import numpy as np -from nmc_met_io.retrieve_cimiss_server import cimiss_obs_by_time_range -from nmc_met_io.retrieve_cimiss_server import cimiss_obs_in_rect_by_time_range -from nmc_met_io.retrieve_cimiss_server import cimiss_obs_file_by_time_range - - -def get_day_hist_obs(years=np.arange(2000, 2011, 1), - month_range=(1, 12), - elements=None, - sta_levels=None, - outfname='day_rain_obs', - outdir='.'): - """ - Download historical daily observations and write to data files, - each month a file. - - :param years: years for historical data - :param month_range: month range each year, like (1, 12) - :param elements: elements for retrieve, 'ele1, ele2, ...' - :param sta_levels: station levels - :param outfname: output file name + '_year' + '_month' - :param outdir: output file directory - :return: output file names. - - :Example: - >>> get_day_hist_obs(years=np.arange(2000, 2016, 1), outdir="D:/") - - """ - - # check elements - if elements is None: - elements = "Station_Id_C,Station_Name,Datetime,Lat,Lon,PRE_Time_0808" - - # check output directory - if not os.path.exists(outdir): - os.makedirs(outdir) - - # define months - months = np.arange(1, 13, 1) - - # Because of the CIMISS data mount limit, - # so loop every year to download the data. - out_files = [] - for iy in years: - if calendar.isleap(iy): - last_day = ['31', '29', '31', '30', '31', '30', - '31', '31', '30', '31', '30', '31'] - else: - last_day = ['31', '28', '31', '30', '31', '30', - '31', '31', '30', '31', '30', '31'] - - for i, im in enumerate(months): - # check month range - if not (month_range[0] <= im <= month_range[1]): - continue - - month = '%02d' % im - start_time = str(iy) + month + '01' + '000000' - end_time = str(iy) + month + last_day[i] + '000000' - time_range = "[" + start_time + "," + end_time + "]" - - # retrieve observations from CIMISS server - data = cimiss_obs_by_time_range( - time_range, sta_levels=sta_levels, - data_code="SURF_CHN_MUL_DAY", elements=elements) - if data is None: - continue - - # save observation data to file - out_files.append(os.path.join( - outdir, outfname + "_" + str(iy) + "_" + month + ".pkl")) - data.to_pickle(out_files[-1]) - - return out_files - - -def get_mon_hist_obs(years=np.arange(2000, 2011, 1), - limit=(3, 73, 54, 136), - elements=None, - outfname='mon_surface_obs', - outdir='.'): - """ - Download historical monthly observations and write to data files, - each year a file. - - :param years: years for historical data - :param limit: spatial limit [min_lat, min_lon, max_lat, max_lon] - :param elements: elements for retrieve, 'ele1, ele2, ...' - :param outfname: output file name + 'year' - :param outdir: output file directory - :return: Output filenames - """ - - # check elements - if elements is None: - elements = ("Station_Id_C,Station_Name,Year," - "Mon,Lat,Lon,Alti,PRE_Time_0808") - - # check output directory - if not os.path.exists(outdir): - os.makedirs(outdir) - - # Loop every year to download the data. - out_files = [] - for iy in years: - # check out file - outfile = os.path.join(outdir, outfname + "_" + str(iy) + ".pkl") - if os.path.isfile(outfile): - continue - - # set time range - start_time = str(iy) + '0101' + '000000' - end_time = str(iy) + '1201' + '000000' - time_range = "[" + start_time + "," + end_time + "]" - - # retrieve observations from CIMISS server - data = cimiss_obs_in_rect_by_time_range( - time_range, limit, data_code='SURF_CHN_MUL_MON', - elements=elements) - if data is None: - continue - - # save observation data to file - out_files.append(outfile) - data.to_pickle(out_files[-1]) - - return out_files - - -def get_cmpas_hist_files(time_range, outdir='.'): - """ - Download CMAPS QPE gridded data files. - - Arguments: - time_range {string} -- time range for retrieve, - "[YYYYMMDDHHMISS,YYYYMMDDHHMISS]" - outdir {string} -- output directory. - - :Exampels: - >>> time_range = "[20180101000000,20180331230000]" - >>> get_cmpas_hist_files(time_range, outdir='G:/CMAPS') - """ - - # check output directory - if not os.path.exists(outdir): - os.makedirs(outdir) - - files = cimiss_obs_file_by_time_range( - time_range, data_code="SURF_CMPA_NRT_NC") - filenames = files['DS'] - for file in filenames: - outfile = os.path.join(outdir, file['FILE_NAME']) - if not os.path.isfile(outfile): - urllib.request.urlretrieve(file['FILE_URL'], outfile) +# -*- coding: utf-8 -*- + +# Copyright (c) 2019 NMC Developers. +# Distributed under the terms of the GPL V3 License. + +""" +Retrieve historical data from CIMISS service. +""" + +import os +import calendar +import urllib.request +import numpy as np +from nmc_met_io.retrieve_cimiss_server import cimiss_obs_by_time_range +from nmc_met_io.retrieve_cimiss_server import cimiss_obs_in_rect_by_time_range +from nmc_met_io.retrieve_cimiss_server import cimiss_obs_file_by_time_range + + +def get_day_hist_obs(years=np.arange(2000, 2011, 1), + month_range=(1, 12), + elements=None, + sta_levels=None, + outfname='day_rain_obs', + outdir='.'): + """ + Download historical daily observations and write to data files, + each month a file. + + :param years: years for historical data + :param month_range: month range each year, like (1, 12) + :param elements: elements for retrieve, 'ele1, ele2, ...' + :param sta_levels: station levels + :param outfname: output file name + '_year' + '_month' + :param outdir: output file directory + :return: output file names. + + :Example: + >>> get_day_hist_obs(years=np.arange(2000, 2016, 1), outdir="D:/") + + """ + + # check elements + if elements is None: + elements = "Station_Id_C,Station_Name,Datetime,Lat,Lon,PRE_Time_0808" + + # check output directory + if not os.path.exists(outdir): + os.makedirs(outdir) + + # define months + months = np.arange(1, 13, 1) + + # Because of the CIMISS data mount limit, + # so loop every year to download the data. + out_files = [] + for iy in years: + if calendar.isleap(iy): + last_day = ['31', '29', '31', '30', '31', '30', + '31', '31', '30', '31', '30', '31'] + else: + last_day = ['31', '28', '31', '30', '31', '30', + '31', '31', '30', '31', '30', '31'] + + for i, im in enumerate(months): + # check month range + if not (month_range[0] <= im <= month_range[1]): + continue + + month = '%02d' % im + start_time = str(iy) + month + '01' + '000000' + end_time = str(iy) + month + last_day[i] + '000000' + time_range = "[" + start_time + "," + end_time + "]" + + # retrieve observations from CIMISS server + data = cimiss_obs_by_time_range( + time_range, sta_levels=sta_levels, + data_code="SURF_CHN_MUL_DAY", elements=elements) + if data is None: + continue + + # save observation data to file + out_files.append(os.path.join( + outdir, outfname + "_" + str(iy) + "_" + month + ".pkl")) + data.to_pickle(out_files[-1]) + + return out_files + + +def get_mon_hist_obs(years=np.arange(2000, 2011, 1), + limit=(3, 73, 54, 136), + elements=None, + outfname='mon_surface_obs', + outdir='.'): + """ + Download historical monthly observations and write to data files, + each year a file. + + :param years: years for historical data + :param limit: spatial limit [min_lat, min_lon, max_lat, max_lon] + :param elements: elements for retrieve, 'ele1, ele2, ...' + :param outfname: output file name + 'year' + :param outdir: output file directory + :return: Output filenames + """ + + # check elements + if elements is None: + elements = ("Station_Id_C,Station_Name,Year," + "Mon,Lat,Lon,Alti,PRE_Time_0808") + + # check output directory + if not os.path.exists(outdir): + os.makedirs(outdir) + + # Loop every year to download the data. + out_files = [] + for iy in years: + # check out file + outfile = os.path.join(outdir, outfname + "_" + str(iy) + ".pkl") + if os.path.isfile(outfile): + continue + + # set time range + start_time = str(iy) + '0101' + '000000' + end_time = str(iy) + '1201' + '000000' + time_range = "[" + start_time + "," + end_time + "]" + + # retrieve observations from CIMISS server + data = cimiss_obs_in_rect_by_time_range( + time_range, limit, data_code='SURF_CHN_MUL_MON', + elements=elements) + if data is None: + continue + + # save observation data to file + out_files.append(outfile) + data.to_pickle(out_files[-1]) + + return out_files + + +def get_cmpas_hist_files(time_range, outdir='.'): + """ + Download CMAPS QPE gridded data files. + + Arguments: + time_range {string} -- time range for retrieve, + "[YYYYMMDDHHMISS,YYYYMMDDHHMISS]" + outdir {string} -- output directory. + + :Exampels: + >>> time_range = "[20180101000000,20180331230000]" + >>> get_cmpas_hist_files(time_range, outdir='G:/CMAPS') + """ + + # check output directory + if not os.path.exists(outdir): + os.makedirs(outdir) + + files = cimiss_obs_file_by_time_range( + time_range, data_code="SURF_CMPA_NRT_NC") + filenames = files['DS'] + for file in filenames: + outfile = os.path.join(outdir, file['FILE_NAME']) + if not os.path.isfile(outfile): + urllib.request.urlretrieve(file['FILE_URL'], outfile) diff --git a/nmc_met_io/retrieve_cimiss_server.py b/nmc_met_io/retrieve_cimiss_server.py index 3661aa1..a16d6b3 100644 --- a/nmc_met_io/retrieve_cimiss_server.py +++ b/nmc_met_io/retrieve_cimiss_server.py @@ -1,434 +1,434 @@ -# _*_ coding: utf-8 _*_ - -# Copyright (c) 2019 NMC Developers. -# Distributed under the terms of the GPL V3 License. - -""" -Retrieve the CIMISS data using REST API with pure python code. - -refer to: - http://10.20.76.55/cimissapiweb/MethodData_list.action - https://github.com/babybearming/CIMISSDataGet/blob/master/cimissRead_v0.1.py -""" - -import json -from datetime import datetime, timedelta -import urllib3 -import numpy as np -import pandas as pd -import xarray as xr -from nmc_met_io.config import _get_config_from_rcfile - - -def get_http_result(interface_id, params, data_format='json'): - """ - Get the http result from CIMISS REST api service. - - :param interface_id: MUSIC interface id. - :param params: dictionary for MUSIC parameters. - :param data_format: MUSIC server data format. - :return: - """ - - # set MUSIC server dns and user information - config = _get_config_from_rcfile() - dns = config['CIMISS']['DNS'] - user_id = config['CIMISS']['USER_ID'] - pwd = config['CIMISS']['PASSWORD'] - - # construct url - url = 'http://' + dns + '/cimiss-web/api?userId=' + user_id + \ - '&pwd=' + pwd + '&interfaceId=' + interface_id - - # params - for key in params: - url += '&' + key + '=' + params[key] - - # data format - url += '&dataFormat=' + data_format - - # request http contents - http = urllib3.PoolManager() - req = http.request('GET', url) - if req.status != 200: - print('Can not access the url: ' + url) - return None - - return req.data - - -def cimiss_obs_by_time_range(time_range, sta_levels=None, - data_code="SURF_CHN_MUL_HOR_N", - elements="Station_Id_C,Datetime,Lat,Lon,TEM"): - """ - Retrieve station records from CIMISS by time and station ID. - - :param time_range: time range for retrieve, - "[YYYYMMDDHHMISS, YYYYMMDDHHMISS]", - like"[201509010000,20150903060000]" - :param sta_levels: station levels, like "011,012,013" for standard, - base and general stations. - :param data_code: dataset code, like "SURF_CHN_MUL_HOR", - "SURF_CHN_MUL_HOR_N", and so on. - :param elements: elements for retrieve, 'ele1,ele2,...' - :return: observation records, pandas DataFrame type - - :Example: - >>> time_range = "[20180219000000,20180221000000]" - >>> sta_levels = "011,012,013" - >>> data_code = "SURF_CHN_MUL_DAY" - >>> elements = "Station_Id_C,Station_Name,Datetime,Lat,Lon,PRE_Time_0808" - >>> data = cimiss_obs_by_time_range(time_range, sta_levels=sta_levels, - data_code=data_code, elements=elements) - >>> print "retrieve successfully" if data is not None else "failed" - retrieve successfully - """ - - # set retrieve parameters - params = {'dataCode': data_code, - 'elements': elements, - 'timeRange': time_range} - if sta_levels is not None: - params['staLevels'] = sta_levels - - # interface id - interface_id = "getSurfEleByTimeRange" - - # retrieve data contents - contents = get_http_result(interface_id, params) - if contents is None: - return None - contents = json.loads(contents.decode('utf-8')) - if contents['returnCode'] != '0': - return None - - # construct pandas DataFrame - data = pd.DataFrame(contents['DS']) - - # return - return data - - -def cimiss_obs_by_time_and_id(times, data_code="SURF_CHN_MUL_HOR_N", - elements="Station_Id_C,Datetime,TEM", - sta_ids="54511"): - """ - Retrieve station records from CIMISS by time and station ID - - :param times: time for retrieve, 'YYYYMMDDHHMISS,YYYYMMDDHHMISS,...' - :param data_code: dataset code, like "SURF_CHN_MUL_HOR", - "SURF_CHN_MUL_HOR_N", and so on. - :param elements: elements for retrieve, 'ele1,ele2,...' - :param sta_ids: station ids, 'xxxxx,xxxxx,...' - :return: observation records, pandas DataFrame type - - :Example: - >>> data = cimiss_obs_by_time_and_id('20170318000000') - """ - - # set retrieve parameters - params = {'dataCode': data_code, - 'elements': elements, - 'times': times, - 'staIds': sta_ids, - 'orderby': "Datetime:ASC"} - - # interface id - interface_id = "getSurfEleByTimeAndStaID" - - # retrieve data contents - contents = get_http_result(interface_id, params) - if contents is None: - return None - contents = json.loads(contents.decode('utf-8')) - if contents['returnCode'] != '0': - return None - - # construct pandas DataFrame - data = pd.DataFrame(contents['DS']) - - # return - return data - - -def cimiss_obs_in_rect_by_time(times, limit, data_code="SURF_CHN_MUL_HOR_N", - elements="Station_Id_C,Datetime,Lat,Lon,TEM"): - """ - Retrieve station records from CIMISS in region by time. - - :param times: times for retrieve, 'YYYYMMDDHHMISS,YYYYMMDDHHMISS,...' - :param limit: [min_lat, min_lon, max_lat, max_lon] - :param data_code: dataset code, like "SURF_CHN_MUL_HOR", - "SURF_CHN_MUL_HOR_N", and so on - :param elements: elements for retrieve, 'ele1,ele2,...' - :return: observation records, pandas DataFrame type - - :Example: - >>> data = cimiss_obs_in_rect_by_time('20170320000000', [35, 110, 45, 120]) - """ - - # set retrieve parameters - params = {'dataCode': data_code, - 'elements': elements, - 'times': times, - 'minLat': '{:.10f}'.format(limit[0]), - 'minLon': '{:.10f}'.format(limit[1]), - 'maxLat': '{:.10f}'.format(limit[2]), - 'maxLon': '{:.10f}'.format(limit[3]), - 'orderby': "Datetime:ASC"} - - # interface id - interface_id = "getSurfEleInRectByTime" - - # retrieve data contents - contents = get_http_result(interface_id, params) - if contents is None: - return None - contents = json.loads(contents.decode('utf-8')) - if contents['returnCode'] != '0': - return None - - # construct pandas DataFrame - data = pd.DataFrame(contents['DS']) - - # return - return data - - -def cimiss_obs_in_rect_by_time_range( - time_range, limit, - data_code="SURF_CHN_MUL_HOR_N", - elements="Station_Id_C,Datetime,Lat,Lon,TEM"): - """ - Retrieve observation records from CIMISS by rect and time range. - - :param time_range: time range for retrieve, - "[YYYYMMDDHHMISS,YYYYMMDDHHMISS]" - :param limit: (min_lat, min_lon, max_lat, max_lon) - :param data_code: dataset code, like "SURF_CHN_MUL_HOR", - "SURF_CHN_MUL_HOR_N", and so on. - :param elements: elements for retrieve, 'ele1,ele2,...' - :return: observation records, pandas DataFrame type - - :Example: - >>> elements = ("Station_Id_C,Station_Id_d,Station_Name," - "Station_levl,Datetime,Lat,Lon,PRE_Time_0808") - >>> time_range = "[20160801000000,20160801000000]" - >>> data_code = "SURF_CHN_MUL_DAY" - >>> data = cimiss_obs_in_rect_by_time_range( - time_range,[35,110,45,120], data_code=data_code, - elements=elements) - """ - - # set retrieve parameters - params = {'dataCode': data_code, - 'elements': elements, - 'timeRange': time_range, - 'minLat': '{:.10f}'.format(limit[0]), - 'minLon': '{:.10f}'.format(limit[1]), - 'maxLat': '{:.10f}'.format(limit[2]), - 'maxLon': '{:.10f}'.format(limit[3]), - 'orderby': "Datetime:ASC"} - - # interface id - interface_id = "getSurfEleInRectByTimeRange" - - # retrieve data contents - contents = get_http_result(interface_id, params) - if contents is None: - return None - contents = json.loads(contents.decode('utf-8')) - if contents['returnCode'] != '0': - return None - - # construct pandas DataFrame - data = pd.DataFrame(contents['DS']) - - # return - return data - - -def cimiss_obs_grid_by_time( - time_str, data_code="SURF_CMPA_RT_NC", fcst_ele="PRE"): - """ - Retrieve surface analysis grid products, - like CMPAS-V2.1融合降水分析实时数据产品（NC）. - For SURF_CMPA_RT_NC, this function will retrieve - the 0.01 resolution data and take long time. - - :param time_str: analysis time string, like "2017100800" - :param data_code: data code - :param fcst_ele: elements - :return: data, xarray type - - :Example: - >>> time_str = "2017110612" - >>> data_code = "SURF_CMPA_RT_NC" - >>> data = cimiss_obs_grid_by_time(time_str, data_code=data_code, - fcst_ele="PRE") - """ - - # set retrieve parameters - params = {'dataCode': data_code, - 'time': time_str + "0000", - 'fcstEle': fcst_ele} - - # set interface id - interface_id = "getSurfEleGridByTime" - - # retrieve data contents - contents = get_http_result(interface_id, params) - if contents is None: - return None - contents = json.loads(contents.decode('utf-8')) - if contents['returnCode'] != '0': - return None - - # get time information - time = datetime.strptime(time_str, '%Y%m%d%H') - - # extract coordinates and data - start_lat = float(contents['startLat']) - start_lon = float(contents['startLon']) - nlon = int(contents['lonCount']) - nlat = int(contents['latCount']) - dlon = float(contents['lonStep']) - dlat = float(contents['latStep']) - lon = start_lon + np.arange(nlon) * dlon - lat = start_lat + np.arange(nlat) * dlat - name = contents['fieldNames'] - units = contents['fieldUnits'] - - # construct xarray - data = np.array(contents['DS']) - data = data[np.newaxis, ...] - data = xr.DataArray(data, coords=[time, lat, lon], - dims=['time', 'lat', 'lon'], name=name) - - # add attributes - data.attrs['units'] = units - data.attrs['organization'] = 'Created by NMC.' - - # return data - return data - - -def cimiss_obs_file_by_time_range(time_range, - data_code="SURF_CMPA_RT_NC"): - """ - Retrieve CIMISS data file information. - - :param time_range: time range for retrieve, - "[YYYYMMDDHHMISS,YYYYMMDDHHMISS]" - :param data_code: data code - :return: dictionary - - :Examples: - >>> time_range = "[20180401000000,20180402000000]" - >>> files = cimiss_obs_file_by_time_range(time_range) - >>> filenames = files['DS'] - >>> print(files['DS'][0]['FILE_URL']) - """ - - # set retrieve parameters - params = {'dataCode': data_code, - 'timeRange': time_range} - - # set interface id - interface_id = "getSurfFileByTimeRange" - - # retrieve data contents - contents = get_http_result(interface_id, params) - if contents is None: - return None - contents = json.loads(contents.decode('utf-8')) - if contents['returnCode'] != '0': - return None - - # return - return contents - - -def cimiss_model_by_time(init_time_str, limit=None, - data_code='NAFP_FOR_FTM_HIGH_EC_GLB', - fcst_level=0, valid_time=0, fcst_ele="TEF2"): - """ - Retrieve grid data from CIMISS service. - - :param init_time_str: model run time, like "2016081712" - :param limit: [min_lat, min_lon, max_lat, max_lon] - :param data_code: MUSIC data code, default is "NAFP_FOR_FTM_HIGH_EC_GLB" - :param fcst_level: vertical level, default is 0. - :param valid_time: forecast element, default is 2m temperature "TEF2" - :param fcst_ele: forecast hour, default is 0 - :return: - """ - - # set retrieve parameters - if limit is None: - params = {'dataCode': data_code, - 'time': init_time_str + '0000', - 'fcstLevel': '{:d}'.format(fcst_level), - 'validTime': '{:d}'.format(valid_time), - 'fcstEle': fcst_ele} - - interface_id = 'getNafpEleGridByTimeAndLevelAndValidtime' - else: - params = {'dataCode': data_code, - 'time': init_time_str + '0000', - 'minLat': '{:.10f}'.format(limit[0]), - "minLon": '{:.10f}'.format(limit[1]), - "maxLat": '{:.10f}'.format(limit[2]), - "maxLon": '{:.10f}'.format(limit[3]), - 'fcstLevel': '{:d}'.format(fcst_level), - 'validTime': '{:d}'.format(valid_time), - 'fcstEle': fcst_ele} - - interface_id = 'getNafpEleGridInRectByTimeAndLevelAndValidtime' - - # retrieve data contents - contents = get_http_result(interface_id, params) - if contents is None: - return None - contents = json.loads(contents.decode('utf-8')) - if contents['returnCode'] != '0': - return None - - # get time information - init_time = datetime.strptime(init_time_str, '%Y%m%d%H') - fhour = valid_time - time = init_time + timedelta(hours=fhour) - - # extract coordinates and data - start_lat = float(contents['startLat']) - start_lon = float(contents['startLon']) - nlon = int(contents['lonCount']) - nlat = int(contents['latCount']) - dlon = float(contents['lonStep']) - dlat = float(contents['latStep']) - lon = start_lon + np.arange(nlon)*dlon - lat = start_lat + np.arange(nlat)*dlat - name = contents['fieldNames'] - units = contents['fieldUnits'] - - # construct xarray - data = np.array(contents['DS']) - if fcst_level == 0: - data = data[np.newaxis, ...] - data = xr.DataArray(data, coords=[time, lat, lon], - dims=['time', 'lat', 'lon'], name=name) - else: - data = data[np.newaxis, np.newaxis, ...] - data = xr.DataArray(data, coords=[time, fcst_level, lat, lon], - dims=['time', 'level', 'lat', 'lon'], name=name) - - # add time coordinates - data.coords['init_time'] = ('time', init_time) - data.coords['fhour'] = ('time', fhour) - - # add attributes - data.attrs['units'] = units - data.attrs['organization'] = 'Created by NMC.' - - # return data - return data +# _*_ coding: utf-8 _*_ + +# Copyright (c) 2019 NMC Developers. +# Distributed under the terms of the GPL V3 License. + +""" +Retrieve the CIMISS data using REST API with pure python code. + +refer to: + http://10.20.76.55/cimissapiweb/MethodData_list.action + https://github.com/babybearming/CIMISSDataGet/blob/master/cimissRead_v0.1.py +""" + +import json +from datetime import datetime, timedelta +import urllib3 +import numpy as np +import pandas as pd +import xarray as xr +from nmc_met_io.config import _get_config_from_rcfile + + +def get_http_result(interface_id, params, data_format='json'): + """ + Get the http result from CIMISS REST api service. + + :param interface_id: MUSIC interface id. + :param params: dictionary for MUSIC parameters. + :param data_format: MUSIC server data format. + :return: + """ + + # set MUSIC server dns and user information + config = _get_config_from_rcfile() + dns = config['CIMISS']['DNS'] + user_id = config['CIMISS']['USER_ID'] + pwd = config['CIMISS']['PASSWORD'] + + # construct url + url = 'http://' + dns + '/cimiss-web/api?userId=' + user_id + \ + '&pwd=' + pwd + '&interfaceId=' + interface_id + + # params + for key in params: + url += '&' + key + '=' + params[key] + + # data format + url += '&dataFormat=' + data_format + + # request http contents + http = urllib3.PoolManager() + req = http.request('GET', url) + if req.status != 200: + print('Can not access the url: ' + url) + return None + + return req.data + + +def cimiss_obs_by_time_range(time_range, sta_levels=None, + data_code="SURF_CHN_MUL_HOR_N", + elements="Station_Id_C,Datetime,Lat,Lon,TEM"): + """ + Retrieve station records from CIMISS by time and station ID. + + :param time_range: time range for retrieve, + "[YYYYMMDDHHMISS, YYYYMMDDHHMISS]", + like"[201509010000,20150903060000]" + :param sta_levels: station levels, like "011,012,013" for standard, + base and general stations. + :param data_code: dataset code, like "SURF_CHN_MUL_HOR", + "SURF_CHN_MUL_HOR_N", and so on. + :param elements: elements for retrieve, 'ele1,ele2,...' + :return: observation records, pandas DataFrame type + + :Example: + >>> time_range = "[20180219000000,20180221000000]" + >>> sta_levels = "011,012,013" + >>> data_code = "SURF_CHN_MUL_DAY" + >>> elements = "Station_Id_C,Station_Name,Datetime,Lat,Lon,PRE_Time_0808" + >>> data = cimiss_obs_by_time_range(time_range, sta_levels=sta_levels, + data_code=data_code, elements=elements) + >>> print "retrieve successfully" if data is not None else "failed" + retrieve successfully + """ + + # set retrieve parameters + params = {'dataCode': data_code, + 'elements': elements, + 'timeRange': time_range} + if sta_levels is not None: + params['staLevels'] = sta_levels + + # interface id + interface_id = "getSurfEleByTimeRange" + + # retrieve data contents + contents = get_http_result(interface_id, params) + if contents is None: + return None + contents = json.loads(contents.decode('utf-8')) + if contents['returnCode'] != '0': + return None + + # construct pandas DataFrame + data = pd.DataFrame(contents['DS']) + + # return + return data + + +def cimiss_obs_by_time_and_id(times, data_code="SURF_CHN_MUL_HOR_N", + elements="Station_Id_C,Datetime,TEM", + sta_ids="54511"): + """ + Retrieve station records from CIMISS by time and station ID + + :param times: time for retrieve, 'YYYYMMDDHHMISS,YYYYMMDDHHMISS,...' + :param data_code: dataset code, like "SURF_CHN_MUL_HOR", + "SURF_CHN_MUL_HOR_N", and so on. + :param elements: elements for retrieve, 'ele1,ele2,...' + :param sta_ids: station ids, 'xxxxx,xxxxx,...' + :return: observation records, pandas DataFrame type + + :Example: + >>> data = cimiss_obs_by_time_and_id('20170318000000') + """ + + # set retrieve parameters + params = {'dataCode': data_code, + 'elements': elements, + 'times': times, + 'staIds': sta_ids, + 'orderby': "Datetime:ASC"} + + # interface id + interface_id = "getSurfEleByTimeAndStaID" + + # retrieve data contents + contents = get_http_result(interface_id, params) + if contents is None: + return None + contents = json.loads(contents.decode('utf-8')) + if contents['returnCode'] != '0': + return None + + # construct pandas DataFrame + data = pd.DataFrame(contents['DS']) + + # return + return data + + +def cimiss_obs_in_rect_by_time(times, limit, data_code="SURF_CHN_MUL_HOR_N", + elements="Station_Id_C,Datetime,Lat,Lon,TEM"): + """ + Retrieve station records from CIMISS in region by time. + + :param times: times for retrieve, 'YYYYMMDDHHMISS,YYYYMMDDHHMISS,...' + :param limit: [min_lat, min_lon, max_lat, max_lon] + :param data_code: dataset code, like "SURF_CHN_MUL_HOR", + "SURF_CHN_MUL_HOR_N", and so on + :param elements: elements for retrieve, 'ele1,ele2,...' + :return: observation records, pandas DataFrame type + + :Example: + >>> data = cimiss_obs_in_rect_by_time('20170320000000', [35, 110, 45, 120]) + """ + + # set retrieve parameters + params = {'dataCode': data_code, + 'elements': elements, + 'times': times, + 'minLat': '{:.10f}'.format(limit[0]), + 'minLon': '{:.10f}'.format(limit[1]), + 'maxLat': '{:.10f}'.format(limit[2]), + 'maxLon': '{:.10f}'.format(limit[3]), + 'orderby': "Datetime:ASC"} + + # interface id + interface_id = "getSurfEleInRectByTime" + + # retrieve data contents + contents = get_http_result(interface_id, params) + if contents is None: + return None + contents = json.loads(contents.decode('utf-8')) + if contents['returnCode'] != '0': + return None + + # construct pandas DataFrame + data = pd.DataFrame(contents['DS']) + + # return + return data + + +def cimiss_obs_in_rect_by_time_range( + time_range, limit, + data_code="SURF_CHN_MUL_HOR_N", + elements="Station_Id_C,Datetime,Lat,Lon,TEM"): + """ + Retrieve observation records from CIMISS by rect and time range. + + :param time_range: time range for retrieve, + "[YYYYMMDDHHMISS,YYYYMMDDHHMISS]" + :param limit: (min_lat, min_lon, max_lat, max_lon) + :param data_code: dataset code, like "SURF_CHN_MUL_HOR", + "SURF_CHN_MUL_HOR_N", and so on. + :param elements: elements for retrieve, 'ele1,ele2,...' + :return: observation records, pandas DataFrame type + + :Example: + >>> elements = ("Station_Id_C,Station_Id_d,Station_Name," + "Station_levl,Datetime,Lat,Lon,PRE_Time_0808") + >>> time_range = "[20160801000000,20160801000000]" + >>> data_code = "SURF_CHN_MUL_DAY" + >>> data = cimiss_obs_in_rect_by_time_range( + time_range,[35,110,45,120], data_code=data_code, + elements=elements) + """ + + # set retrieve parameters + params = {'dataCode': data_code, + 'elements': elements, + 'timeRange': time_range, + 'minLat': '{:.10f}'.format(limit[0]), + 'minLon': '{:.10f}'.format(limit[1]), + 'maxLat': '{:.10f}'.format(limit[2]), + 'maxLon': '{:.10f}'.format(limit[3]), + 'orderby': "Datetime:ASC"} + + # interface id + interface_id = "getSurfEleInRectByTimeRange" + + # retrieve data contents + contents = get_http_result(interface_id, params) + if contents is None: + return None + contents = json.loads(contents.decode('utf-8')) + if contents['returnCode'] != '0': + return None + + # construct pandas DataFrame + data = pd.DataFrame(contents['DS']) + + # return + return data + + +def cimiss_obs_grid_by_time( + time_str, data_code="SURF_CMPA_RT_NC", fcst_ele="PRE"): + """ + Retrieve surface analysis grid products, + like CMPAS-V2.1融合降水分析实时数据产品（NC）. + For SURF_CMPA_RT_NC, this function will retrieve + the 0.01 resolution data and take long time. + + :param time_str: analysis time string, like "2017100800" + :param data_code: data code + :param fcst_ele: elements + :return: data, xarray type + + :Example: + >>> time_str = "2017110612" + >>> data_code = "SURF_CMPA_RT_NC" + >>> data = cimiss_obs_grid_by_time(time_str, data_code=data_code, + fcst_ele="PRE") + """ + + # set retrieve parameters + params = {'dataCode': data_code, + 'time': time_str + "0000", + 'fcstEle': fcst_ele} + + # set interface id + interface_id = "getSurfEleGridByTime" + + # retrieve data contents + contents = get_http_result(interface_id, params) + if contents is None: + return None + contents = json.loads(contents.decode('utf-8')) + if contents['returnCode'] != '0': + return None + + # get time information + time = datetime.strptime(time_str, '%Y%m%d%H') + + # extract coordinates and data + start_lat = float(contents['startLat']) + start_lon = float(contents['startLon']) + nlon = int(contents['lonCount']) + nlat = int(contents['latCount']) + dlon = float(contents['lonStep']) + dlat = float(contents['latStep']) + lon = start_lon + np.arange(nlon) * dlon + lat = start_lat + np.arange(nlat) * dlat + name = contents['fieldNames'] + units = contents['fieldUnits'] + + # construct xarray + data = np.array(contents['DS']) + data = data[np.newaxis, ...] + data = xr.DataArray(data, coords=[time, lat, lon], + dims=['time', 'lat', 'lon'], name=name) + + # add attributes + data.attrs['units'] = units + data.attrs['organization'] = 'Created by NMC.' + + # return data + return data + + +def cimiss_obs_file_by_time_range(time_range, + data_code="SURF_CMPA_RT_NC"): + """ + Retrieve CIMISS data file information. + + :param time_range: time range for retrieve, + "[YYYYMMDDHHMISS,YYYYMMDDHHMISS]" + :param data_code: data code + :return: dictionary + + :Examples: + >>> time_range = "[20180401000000,20180402000000]" + >>> files = cimiss_obs_file_by_time_range(time_range) + >>> filenames = files['DS'] + >>> print(files['DS'][0]['FILE_URL']) + """ + + # set retrieve parameters + params = {'dataCode': data_code, + 'timeRange': time_range} + + # set interface id + interface_id = "getSurfFileByTimeRange" + + # retrieve data contents + contents = get_http_result(interface_id, params) + if contents is None: + return None + contents = json.loads(contents.decode('utf-8')) + if contents['returnCode'] != '0': + return None + + # return + return contents + + +def cimiss_model_by_time(init_time_str, limit=None, + data_code='NAFP_FOR_FTM_HIGH_EC_GLB', + fcst_level=0, valid_time=0, fcst_ele="TEF2"): + """ + Retrieve grid data from CIMISS service. + + :param init_time_str: model run time, like "2016081712" + :param limit: [min_lat, min_lon, max_lat, max_lon] + :param data_code: MUSIC data code, default is "NAFP_FOR_FTM_HIGH_EC_GLB" + :param fcst_level: vertical level, default is 0. + :param valid_time: forecast element, default is 2m temperature "TEF2" + :param fcst_ele: forecast hour, default is 0 + :return: + """ + + # set retrieve parameters + if limit is None: + params = {'dataCode': data_code, + 'time': init_time_str + '0000', + 'fcstLevel': '{:d}'.format(fcst_level), + 'validTime': '{:d}'.format(valid_time), + 'fcstEle': fcst_ele} + + interface_id = 'getNafpEleGridByTimeAndLevelAndValidtime' + else: + params = {'dataCode': data_code, + 'time': init_time_str + '0000', + 'minLat': '{:.10f}'.format(limit[0]), + "minLon": '{:.10f}'.format(limit[1]), + "maxLat": '{:.10f}'.format(limit[2]), + "maxLon": '{:.10f}'.format(limit[3]), + 'fcstLevel': '{:d}'.format(fcst_level), + 'validTime': '{:d}'.format(valid_time), + 'fcstEle': fcst_ele} + + interface_id = 'getNafpEleGridInRectByTimeAndLevelAndValidtime' + + # retrieve data contents + contents = get_http_result(interface_id, params) + if contents is None: + return None + contents = json.loads(contents.decode('utf-8')) + if contents['returnCode'] != '0': + return None + + # get time information + init_time = datetime.strptime(init_time_str, '%Y%m%d%H') + fhour = valid_time + time = init_time + timedelta(hours=fhour) + + # extract coordinates and data + start_lat = float(contents['startLat']) + start_lon = float(contents['startLon']) + nlon = int(contents['lonCount']) + nlat = int(contents['latCount']) + dlon = float(contents['lonStep']) + dlat = float(contents['latStep']) + lon = start_lon + np.arange(nlon)*dlon + lat = start_lat + np.arange(nlat)*dlat + name = contents['fieldNames'] + units = contents['fieldUnits'] + + # construct xarray + data = np.array(contents['DS']) + if fcst_level == 0: + data = data[np.newaxis, ...] + data = xr.DataArray(data, coords=[time, lat, lon], + dims=['time', 'lat', 'lon'], name=name) + else: + data = data[np.newaxis, np.newaxis, ...] + data = xr.DataArray(data, coords=[time, fcst_level, lat, lon], + dims=['time', 'level', 'lat', 'lon'], name=name) + + # add time coordinates + data.coords['init_time'] = ('time', init_time) + data.coords['fhour'] = ('time', fhour) + + # add attributes + data.attrs['units'] = units + data.attrs['organization'] = 'Created by NMC.' + + # return data + return data diff --git a/nmc_met_io/retrieve_micaps_server.py b/nmc_met_io/retrieve_micaps_server.py index 2d0ccc4..fe8d62e 100644 --- a/nmc_met_io/retrieve_micaps_server.py +++ b/nmc_met_io/retrieve_micaps_server.py @@ -1,775 +1,796 @@ -# -*- coding: utf-8 -*- - -# Copyright (c) 2019 NMC Developers. -# Distributed under the terms of the GPL V3 License. - -""" -This is the retrieve module which get data from MICAPS cassandra service -with Python API. - -Checking url, like: -http://10.32.8.164:8080/DataService?requestType=getLatestDataName&directory=ECMWF_HR/TMP/850&fileName=&filter=*.024 -""" - -import re -import http.client -from datetime import datetime, timedelta -import numpy as np -import xarray as xr -import pandas as pd -from nmc_met_io import DataBlock_pb2 -from nmc_met_io.config import _get_config_from_rcfile - - -def get_http_result(host, port, url): - """ - Get the http contents. - """ - - http_client = None - try: - http_client = http.client.HTTPConnection(host, port, timeout=120) - http_client.request('GET', url) - - response = http_client.getresponse() - return response.status, response.read() - except Exception as e: - print(e) - return 0, - finally: - if http_client: - http_client.close() - - -class GDSDataService: - def __init__(self): - # set MICAPS GDS服务器地址 - config = _get_config_from_rcfile() - self.gdsIp = config['MICAPS']['GDS_IP'] - self.gdsPort = config['MICAPS']['GDS_PORT'] - - def getLatestDataName(self, directory, filter): - return get_http_result( - self.gdsIp, self.gdsPort, "/DataService" + - self.get_concate_url("getLatestDataName", directory, "", filter)) - - def getData(self, directory, fileName): - return get_http_result( - self.gdsIp, self.gdsPort, "/DataService" + - self.get_concate_url("getData", directory, fileName, "")) - - # 将请求参数拼接到url - def get_concate_url(self, requestType, directory, fileName, filter): - url = "" - url += "?requestType=" + requestType - url += "&directory=" + directory - url += "&fileName=" + fileName - url += "&filter=" + filter - return url - - -def get_model_grid(directory, filename=None, suffix="*.024"): - """ - Retrieve numeric model grid forecast from MICAPS cassandra service. - Support ensemble member forecast. - - :param directory: the data directory on the service - :param filename: the data filename, if none, will be the latest file. - :param suffix: the filename filter pattern which will be used to - find the specified file. - :return: data, xarray type - - :Examples: - >>> data = get_model_grid("ECMWF_HR/TMP/850") - >>> data_ens = get_model_grid("ECMWF_ENSEMBLE/RAW/HGT/500", - filename='18021708.024') - """ - - # connect to data service - service = GDSDataService() - - # get data file name - if filename is None: - try: - status, response = service.getLatestDataName(directory, suffix) - except ValueError: - print('Can not retrieve data from ' + directory) - return None - StringResult = DataBlock_pb2.StringResult() - if status == 200: - StringResult.ParseFromString(response) - if StringResult is not None: - filename = StringResult.name - if filename == '': - return None - else: - return None - - # get data contents - try: - status, response = service.getData(directory, filename) - except ValueError: - print('Can not retrieve data' + filename + ' from ' + directory) - return None - ByteArrayResult = DataBlock_pb2.ByteArrayResult() - if status == 200: - ByteArrayResult.ParseFromString(response) - if ByteArrayResult is not None: - byteArray = ByteArrayResult.byteArray - - # define head information structure (278 bytes) - head_dtype = [('discriminator', 'S4'), ('type', 'i2'), - ('modelName', 'S20'), ('element', 'S50'), - ('description', 'S30'), ('level', 'f4'), - ('year', 'i4'), ('month', 'i4'), ('day', 'i4'), - ('hour', 'i4'), ('timezone', 'i4'), - ('period', 'i4'), ('startLongitude', 'f4'), - ('endLongitude', 'f4'), ('longitudeGridSpace', 'f4'), - ('longitudeGridNumber', 'i4'), - ('startLatitude', 'f4'), ('endLatitude', 'f4'), - ('latitudeGridSpace', 'f4'), - ('latitudeGridNumber', 'i4'), - ('isolineStartValue', 'f4'), - ('isolineEndValue', 'f4'), - ('isolineSpace', 'f4'), - ('perturbationNumber', 'i2'), - ('ensembleTotalNumber', 'i2'), - ('minute', 'i2'), ('second', 'i2'), - ('Extent', 'S92')] - - # read head information - head_info = np.fromstring(byteArray[0:278], dtype=head_dtype) - - # get required grid information - data_type = head_info['type'][0] - nlon = head_info['longitudeGridNumber'][0] - nlat = head_info['latitudeGridNumber'][0] - nmem = head_info['ensembleTotalNumber'][0] - - # define data structure - if data_type == 4: - data_dtype = [('data', 'f4', (nlat, nlon))] - data_len = nlat * nlon * 4 - elif data_type == 11: - data_dtype = [('data', 'f4', (2, nlat, nlon))] - data_len = 2 * nlat * nlon * 4 - else: - raise Exception("Data type is not supported") - - # read data - if nmem == 0: - data = np.fromstring(byteArray[278:], dtype=data_dtype) - data = np.squeeze(data['data']) - else: - if data_type == 4: - data = np.full((nmem, nlat, nlon), np.nan) - else: - data = np.full((2, nmem, nlat, nlon), np.nan) - ind = 0 - for imem in range(nmem): - head_info_mem = np.fromstring( - byteArray[ind:(ind+278)], dtype=head_dtype) - ind += 278 - data_mem = np.fromstring( - byteArray[ind:(ind+data_len)], dtype=data_dtype) - ind += data_len - number = head_info_mem['perturbationNumber'][0] - if data_type == 4: - data[number, :, :] = np.squeeze(data_mem['data']) - else: - data[:, number, :, :] = np.squeeze(data_mem['data']) - - # construct longitude and latitude coordinates - slon = head_info['startLongitude'][0] - dlon = head_info['longitudeGridSpace'][0] - slat = head_info['startLatitude'][0] - dlat = head_info['latitudeGridSpace'][0] - lon = np.arange(nlon) * dlon + slon - lat = np.arange(nlat) * dlat + slat - level = np.array([head_info['level'][0]]) - - # construct initial time and forecast hour - init_time = datetime(head_info['year'][0], head_info['month'][0], - head_info['day'][0], head_info['hour'][0]) - fhour = np.array([head_info['period'][0]], dtype=np.float) - time = init_time + timedelta(hours=fhour[0]) - init_time = np.array([init_time], dtype='datetime64[m]') - time = np.array([time], dtype='datetime64[m]') - - # construct ensemble number - if nmem != 0: - number = np.arange(nmem) - - # create to xarray - if data_type == 4: - if nmem == 0: - if level[0] == 0: - data = data[np.newaxis, ...] - data = xr.DataArray( - data, coords=[time, lat, lon], - dims=['time', 'lat', 'lon'], name="data") - else: - data = data[np.newaxis, np.newaxis, ...] - data = xr.DataArray( - data, coords=[time, level, lat, lon], - dims=['time', 'level', 'lat', 'lon'], - name="data") - else: - if level[0] == 0: - data = data[np.newaxis, ...] - data = xr.DataArray( - data, coords=[time, number, lat, lon], - dims=['time', 'number', 'lat', 'lon'], - name="data") - else: - data = data[np.newaxis, :, np.newaxis, ...] - data = xr.DataArray( - data, coords=[time, number, level, lat, lon], - dims=['time', 'number', 'level', 'lat', 'lon'], - name="data") - elif data_type == 11: - if nmem == 0: - speed = np.squeeze(data[0, :, :]) - angle = np.squeeze(data[1, :, :]) - if level[0] == 0: - speed = speed[np.newaxis, ...] - angle = angle[np.newaxis, ...] - data = xr.Dataset({ - 'speed': (['time', 'lat', 'lon'], speed), - 'angle': (['time', 'lat', 'lon'], angle)}, - coords={'lon': lon, 'lat': lat, 'time': time}) - else: - speed = speed[np.newaxis, np.newaxis, ...] - angle = angle[np.newaxis, np.newaxis, ...] - data = xr.Dataset({ - 'speed': (['time', 'level', 'lat', 'lon'], speed), - 'angle': (['time', 'level', 'lat', 'lon'], angle)}, - coords={'lon': lon, 'lat': lat, 'level': level, - 'time': time}) - else: - speed = np.squeeze(data[0, :, :, :]) - angle = np.squeeze(data[1, :, :, :]) - if level[0] == 0: - speed = speed[np.newaxis, ...] - angle = angle[np.newaxis, ...] - data = xr.Dataset({ - 'speed': ( - ['time', 'number', 'lat', 'lon'], speed), - 'angle': ( - ['time', 'number', 'lat', 'lon'], angle)}, - coords={ - 'lon': lon, 'lat': lat, 'number': number, - 'time': time}) - else: - speed = speed[np.newaxis, :, np.newaxis, ...] - angle = angle[np.newaxis, :, np.newaxis, ...] - data = xr.Dataset({ - 'speed': ( - ['time', 'number', 'level', 'lat', 'lon'], - speed), - 'angle': ( - ['time', 'number', 'level', 'lat', 'lon'], - angle)}, - coords={ - 'lon': lon, 'lat': lat, 'level': level, - 'number': number, 'time': time}) - # add time coordinates - data.coords['init_time'] = ('time', init_time) - data.coords['fhour'] = ('time', fhour) - - # add attributes - data.attrs['data_directory'] = directory - data.attrs['data_filename'] = filename - data.attrs['organization'] = 'Created by NMC.' - - # return data - return data - - else: - return None - else: - return None - - -def get_station_data(directory, filename=None, suffix="*.000"): - """ - Retrieve station data from MICAPS cassandra service. - - :param directory: the data directory on the service - :param filename: the data filename, if none, will be the latest file. - :param suffix: the filename filter pattern which will - be used to find the specified file. - :return: pandas DataFrame. - - :example: - >>> data = get_station_data("SURFACE/PLOT_10MIN") - """ - - # connect to data service - service = GDSDataService() - - # get data file name - if filename is None: - try: - status, response = service.getLatestDataName(directory, suffix) - except ValueError: - print('Can not retrieve data from ' + directory) - return None - StringResult = DataBlock_pb2.StringResult() - if status == 200: - StringResult.ParseFromString(response) - if StringResult is not None: - filename = StringResult.name - if filename == '': - return None - else: - return None - - # get data contents - try: - status, response = service.getData(directory, filename) - except ValueError: - print('Can not retrieve data' + filename + ' from ' + directory) - return None - ByteArrayResult = DataBlock_pb2.ByteArrayResult() - if status == 200: - ByteArrayResult.ParseFromString(response) - if ByteArrayResult is not None: - byteArray = ByteArrayResult.byteArray - - # define head structure - head_dtype = [('discriminator', 'S4'), ('type', 'i2'), - ('description', 'S100'), - ('level', 'f4'), ('levelDescription', 'S50'), - ('year', 'i4'), ('month', 'i4'), ('day', 'i4'), - ('hour', 'i4'), ('minute', 'i4'), ('second', 'i4'), - ('Timezone', 'i4'), ('extent', 'S100')] - - # read head information - head_info = np.fromstring(byteArray[0:288], dtype=head_dtype) - ind = 288 - - # read the number of stations - station_number = np.fromstring( - byteArray[ind:(ind+4)], dtype='i4')[0] - ind += 4 - - # read the number of elements - element_number = np.fromstring( - byteArray[ind:(ind+2)], dtype='i2')[0] - ind += 2 - - # construct record structure - element_type_map = { - 1: 'b1', 2: 'i2', 3: 'i4', 4: 'i8', 5: 'f4', 6: 'f8', 7: 'S1'} - element_map = {} - for i in range(element_number): - element_id = str( - np.fromstring(byteArray[ind:(ind+2)], dtype='i2')[0]) - ind += 2 - element_type = np.fromstring( - byteArray[ind:(ind+2)], dtype='i2')[0] - ind += 2 - element_map[element_id] = element_type_map[element_type] - - # loop every station to retrieve record - record_head_dtype = [ - ('ID', 'i4'), ('lon', 'f4'), ('lat', 'f4'), ('numb', 'i2')] - records = [] - for i in range(station_number): - record_head = np.fromstring( - byteArray[ind:(ind+14)], dtype=record_head_dtype) - ind += 14 - record = { - 'ID': record_head['ID'][0], 'lon': record_head['lon'][0], - 'lat': record_head['lat'][0]} - for j in range(record_head['numb'][0]): # the record element number is not same, missing value is not included. - element_id = str( - np.fromstring(byteArray[ind:(ind + 2)], dtype='i2')[0]) - ind += 2 - element_type = element_map[element_id] - element_len = int(element_type[1]) - record[element_id] = np.fromstring( - byteArray[ind:(ind + element_len)], - dtype=element_type)[0] - ind += element_len - records += [record] - - # convert to pandas data frame - records = pd.DataFrame(records) - records.set_index('ID') - - # get time - time = datetime( - head_info['year'][0], head_info['month'][0], - head_info['day'][0], head_info['hour'][0], - head_info['minute'][0], head_info['second'][0]) - records['time'] = time - - # change column name for common observation - records.rename(columns={ - '1001': 'precipitation', '1201': 'visibility_1min'}, - inplace=True) - - # return - return records - else: - return None - else: - return None - - -def get_fy_awx(directory, filename=None, suffix="*.AWX"): - """ - Retrieve FY satellite cloud awx format file. - - :param directory: the data directory on the service - :param filename: the data filename, if none, will be the latest file. - :param suffix: the filename filter pattern which will be used to - find the specified file. - :return: satellite information and data. - - :Examples: - >>> directory = "SATELLITE/FY2E/L1/IR1/EQUAL" - >>> data = get_fy_awx(directory) - """ - - # connect to data service - service = GDSDataService() - - # get data file name - if filename is None: - try: - status, response = service.getLatestDataName(directory, suffix) - except ValueError: - print('Can not retrieve data from ' + directory) - return None - StringResult = DataBlock_pb2.StringResult() - if status == 200: - StringResult.ParseFromString(response) - if StringResult is not None: - filename = StringResult.name - if filename == '': - return None - else: - return None - - # get data contents - try: - status, response = service.getData(directory, filename) - except ValueError: - print('Can not retrieve data' + filename + ' from ' + directory) - return None - ByteArrayResult = DataBlock_pb2.ByteArrayResult() - if status == 200: - ByteArrayResult.ParseFromString(response) - if ByteArrayResult is not None: - byteArray = ByteArrayResult.byteArray - - # define head structure - head_dtype = [ - ('SAT96', 'S12'), # SAT96 filename - ('byteSequence', 'i2'), # integer number byte sequence - ('firstClassHeadLength', 'i2'), - ('secondClassHeadLength', 'i2'), - ('padDataLength', 'i2'), - ('recordLength', 'i2'), - ('headRecordNumber', 'i2'), - ('dataRecordNumber', 'i2'), - ('productCategory', 'i2'), - ('compressMethod', 'i2'), - ('formatString', 'S8'), - ('qualityFlag', 'i2'), - ('satelliteName', 'S8'), - ('year', 'i2'), ('month', 'i2'), - ('day', 'i2'), ('hour', 'i2'), - ('minute', 'i2'), - ('channel', 'i2'), - ('flagOfProjection', 'i2'), - ('widthOfImage', 'i2'), - ('heightOfImage', 'i2'), - ('scanLineNumberOfImageTopLeft', 'i2'), - ('pixelNumberOfImageTopLeft', 'i2'), - ('sampleRatio', 'i2'), - ('latitudeOfNorth', 'i2'), - ('latitudeOfSouth', 'i2'), - ('longitudeOfWest', 'i2'), - ('longitudeOfEast', 'i2'), - ('centerLatitudeOfProjection', 'i2'), - ('centerLongitudeOfProjection', 'i2'), - ('standardLatitude1', 'i2'), - ('standardLatitude2', 'i2'), - ('horizontalResolution', 'i2'), - ('verticalResolution', 'i2'), - ('overlapFlagGeoGrid', 'i2'), - ('overlapValueGeoGrid', 'i2'), - ('dataLengthOfColorTable', 'i2'), - ('dataLengthOfCalibration', 'i2'), - ('dataLengthOfGeolocation', 'i2'), - ('reserved', 'i2')] - head_info = np.fromstring(byteArray[0:104], dtype=head_dtype) - ind = 104 - - # head rest information - head_rest_len = (head_info['recordLength'][0].astype(np.int) * - head_info['headRecordNumber'][0] - ind) - head_rest = np.fromstring( - byteArray[ind:(ind + head_rest_len)], - dtype='u1', count=head_rest_len) - ind += head_rest_len - - # retrieve data records - data_len = (head_info['recordLength'][0].astype(np.int) * - head_info['dataRecordNumber'][0]) - data = np.fromstring( - byteArray[ind:(ind + data_len)], dtype='u1', - count=data_len) - data.shape = (head_info['recordLength'][0], - head_info['dataRecordNumber'][0]) - - # return - return head_info, data - else: - return None - else: - return None - - -def get_radar_mosaic(directory, filename=None, suffix="*.LATLON"): - """ - 该程序主要用于读取和处理中国气象局CRaMS系统的雷达回波全国拼图数据. - - :param directory: the data directory on the service - :param filename: the data filename, if none, will be the latest file. - :param suffix: the filename filter pattern which will be used to - find the specified file. - :return: xarray object. - - :Example: - >>> data = get_radar_mosaic("RADARMOSAIC/CREF/") - """ - - # connect to data service - service = GDSDataService() - - # get data file name - if filename is None: - try: - status, response = service.getLatestDataName(directory, suffix) - except ValueError: - print('Can not retrieve data from ' + directory) - return None - StringResult = DataBlock_pb2.StringResult() - if status == 200: - StringResult.ParseFromString(response) - if StringResult is not None: - filename = StringResult.name - if filename == '': - return None - else: - return None - - # get data contents - try: - status, response = service.getData(directory, filename) - except ValueError: - print('Can not retrieve data' + filename + ' from ' + directory) - return None - ByteArrayResult = DataBlock_pb2.ByteArrayResult() - if status == 200: - ByteArrayResult.ParseFromString(response) - if ByteArrayResult is not None: - byteArray = ByteArrayResult.byteArray - - # define head structure - head_dtype = [ - ('description', 'S128'), - # product name, QREF=基本反射率, CREF=组合反射率, - # VIL=液态水含量, OHP=一小时降水 - ('name', 'S32'), - ('organization', 'S16'), - ('grid_flag', 'u2'), # 经纬网格数据标识，固定值19532 - ('data_byte', 'i2'), # 数据单元字节数，固定值2 - ('slat', 'f4'), # 数据区的南纬（度） - ('wlon', 'f4'), # 数据区的西经（度） - ('nlat', 'f4'), # 数据区的北纬（度） - ('elon', 'f4'), # 数据区的东经（度） - ('clat', 'f4'), # 数据区中心纬度（度） - ('clon', 'f4'), # 数据区中心经度（度） - ('rows', 'i4'), # 数据区的行数 - ('cols', 'i4'), # 每行数据的列数 - ('dlat', 'f4'), # 纬向分辨率（度） - ('dlon', 'f4'), # 经向分辨率（度） - ('nodata', 'f4'), # 无数据区的编码值 - ('levelbybtes', 'i4'), # 单层数据字节数 - ('levelnum', 'i2'), # 数据层个数 - ('amp', 'i2'), # 数值放大系数 - ('compmode', 'i2'), # 数据压缩存储时为1，否则为0 - ('dates', 'u2'), # 数据观测时间，为1970年1月1日以来的天数 - ('seconds', 'i4'), # 数据观测时间的秒数 - ('min_value', 'i2'), # 放大后的数据最小取值 - ('max_value', 'i2'), # 放大后的数据最大取值 - ('reserved', 'i2', 6) # 保留字节 - ] - - # read head information - head_info = np.fromstring(byteArray[0:256], dtype=head_dtype) - ind = 256 - - # define data variable - rows = head_info['rows'][0] - cols = head_info['cols'][0] - dlat = head_info['dlat'][0] - dlon = head_info['dlon'][0] - data = np.full(rows*cols, -9999, dtype=np.int32) - - # put data into array - while ind < len(byteArray): - irow = np.fromstring(byteArray[ind:(ind + 2)], dtype='i2')[0] - ind += 2 - icol = np.fromstring(byteArray[ind:(ind + 2)], dtype='i2')[0] - ind += 2 - if irow == -1 or icol == -1: - break - nrec = np.fromstring(byteArray[ind:(ind + 2)], dtype='i2')[0] - ind += 2 - recd = np.fromstring( - byteArray[ind:(ind + 2*nrec)], dtype='i2', count=nrec) - ind += 2*nrec - position = (irow-1)*cols+icol-1 - data[position:(position+nrec)] = recd - 1 - - # reshape data - data.shape = (rows, cols) - - # set longitude and latitude coordinates - lats = head_info['nlat'][0] - np.arange(rows)*dlat - dlat/2.0 - lons = head_info['wlon'][0] - np.arange(cols)*dlon - dlon/2.0 - - # reverse latitude axis - data = np.flip(data, 0) - lats = lats[::-1] - - # set time coordinates - time = datetime(1970, 1, 1) + timedelta( - days=head_info['dates'][0].astype(np.float64), - seconds=head_info['seconds'][0].astype(np.float64)) - time = np.array([time], dtype='datetime64[m]') - data = np.expand_dims(data, axis=0) - - # create xarray - data = xr.DataArray( - data, coords=[time, lats, lons], - dims=['time', 'latitude', 'longitude'], - name="radar_mosaic") - - # return - return data - else: - return None - else: - return None - - -def get_tlogp(directory, filename=None, suffix="*.000"): - """ - 该程序用于读取micaps服务器上TLOGP数据信息, 文件格式与MICAPS第5类格式相同. - - :param directory: the data directory on the service - :param filename: the data filename, if none, will be the latest file. - :param suffix: the filename filter pattern which will be used to - find the specified file. - :return: pandas DataFrame object. - - >>> data = get_tlogp("UPPER_AIR/TLOGP/") - """ - - # connect to data service - service = GDSDataService() - - # get data file name - if filename is None: - try: - status, response = service.getLatestDataName(directory, suffix) - except ValueError: - print('Can not retrieve data from ' + directory) - return None - StringResult = DataBlock_pb2.StringResult() - if status == 200: - StringResult.ParseFromString(response) - if StringResult is not None: - filename = StringResult.name - if filename == '': - return None - else: - return None - - # get data contents - try: - status, response = service.getData(directory, filename) - except ValueError: - print('Can not retrieve data' + filename + ' from ' + directory) - return None - ByteArrayResult = DataBlock_pb2.ByteArrayResult() - if status == 200: - ByteArrayResult.ParseFromString(response) - if ByteArrayResult is not None: - byteArray = ByteArrayResult.byteArray - - # decode bytes to string - txt = byteArray.decode("utf-8") - txt = list(filter(None, re.split(' |\n', txt))) - - # observation date and time - if len(txt[3]) < 4: - year = int(txt[3]) + 2000 - else: - year = int(txt[3]) - month = int(txt[4]) - day = int(txt[5]) - hour = int(txt[6]) - time = datetime(year, month, day, hour) - - # the number of records - number = int(txt[7]) - if number < 1: - return None - - # cut the data - txt = txt[8:] - - # put the data into dictionary - index = 0 - records = [] - while index < len(txt): - # get the record information - ID = txt[index].strip() - lon = float(txt[index+1]) - lat = float(txt[index+2]) - alt = float(txt[index+3]) - number = int(int(txt[index+4])/6) - index += 5 - - # get the sounding records - for i in range(number): - record = { - 'ID': ID, 'lon': lon, 'lat': lat, 'alt': alt, - 'time': time, - 'p': float(txt[index]), 'h': float(txt[index+1]), - 't': float(txt[index+2]), 'td': float(txt[index+3]), - 'wind_angle': float(txt[index+4]), - 'wind_speed': float(txt[index+5])} - records.append(record) - index += 6 - - # transform to pandas data frame - records = pd.DataFrame(records) - records.set_index('ID') - - # return - return records - else: - return None - else: - return None - +# -*- coding: utf-8 -*- + +# Copyright (c) 2019 NMC Developers. +# Distributed under the terms of the GPL V3 License. + +""" +This is the retrieve module which get data from MICAPS cassandra service +with Python API. + +Checking url, like: +http://10.32.8.164:8080/DataService?requestType=getLatestDataName&directory=ECMWF_HR/TMP/850&fileName=&filter=*.024 +""" + +import re +import http.client +from datetime import datetime, timedelta +import numpy as np +import xarray as xr +import pandas as pd +from nmc_met_io import DataBlock_pb2 +from nmc_met_io.config import _get_config_from_rcfile + + +def get_http_result(host, port, url): + """ + Get the http contents. + """ + + http_client = None + try: + http_client = http.client.HTTPConnection(host, port, timeout=120) + http_client.request('GET', url) + + response = http_client.getresponse() + return response.status, response.read() + except Exception as e: + print(e) + return 0, + finally: + if http_client: + http_client.close() + + +class GDSDataService: + def __init__(self): + # set MICAPS GDS服务器地址 + config = _get_config_from_rcfile() + self.gdsIp = config['MICAPS']['GDS_IP'] + self.gdsPort = config['MICAPS']['GDS_PORT'] + + def getLatestDataName(self, directory, filter): + return get_http_result( + self.gdsIp, self.gdsPort, "/DataService" + + self.get_concate_url("getLatestDataName", directory, "", filter)) + + def getData(self, directory, fileName): + return get_http_result( + self.gdsIp, self.gdsPort, "/DataService" + + self.get_concate_url("getData", directory, fileName, "")) + + # 将请求参数拼接到url + def get_concate_url(self, requestType, directory, fileName, filter): + url = "" + url += "?requestType=" + requestType + url += "&directory=" + directory + url += "&fileName=" + fileName + url += "&filter=" + filter + return url + + +def get_model_grid(directory, filename=None, suffix="*.024"): + """ + Retrieve numeric model grid forecast from MICAPS cassandra service. + Support ensemble member forecast. + + :param directory: the data directory on the service + :param filename: the data filename, if none, will be the latest file. + :param suffix: the filename filter pattern which will be used to + find the specified file. + :return: data, xarray type + + :Examples: + >>> data = get_model_grid("ECMWF_HR/TMP/850") + >>> data_ens = get_model_grid("ECMWF_ENSEMBLE/RAW/HGT/500", + filename='18021708.024') + """ + + # connect to data service + service = GDSDataService() + + # get data file name + if filename is None: + try: + status, response = service.getLatestDataName(directory, suffix) + except ValueError: + print('Can not retrieve data from ' + directory) + return None + StringResult = DataBlock_pb2.StringResult() + if status == 200: + StringResult.ParseFromString(response) + if StringResult is not None: + filename = StringResult.name + if filename == '': + return None + else: + return None + + # get data contents + try: + status, response = service.getData(directory, filename) + except ValueError: + print('Can not retrieve data' + filename + ' from ' + directory) + return None + ByteArrayResult = DataBlock_pb2.ByteArrayResult() + if status == 200: + ByteArrayResult.ParseFromString(response) + if ByteArrayResult is not None: + byteArray = ByteArrayResult.byteArray + + # define head information structure (278 bytes) + head_dtype = [('discriminator', 'S4'), ('type', 'i2'), + ('modelName', 'S20'), ('element', 'S50'), + ('description', 'S30'), ('level', 'f4'), + ('year', 'i4'), ('month', 'i4'), ('day', 'i4'), + ('hour', 'i4'), ('timezone', 'i4'), + ('period', 'i4'), ('startLongitude', 'f4'), + ('endLongitude', 'f4'), ('longitudeGridSpace', 'f4'), + ('longitudeGridNumber', 'i4'), + ('startLatitude', 'f4'), ('endLatitude', 'f4'), + ('latitudeGridSpace', 'f4'), + ('latitudeGridNumber', 'i4'), + ('isolineStartValue', 'f4'), + ('isolineEndValue', 'f4'), + ('isolineSpace', 'f4'), + ('perturbationNumber', 'i2'), + ('ensembleTotalNumber', 'i2'), + ('minute', 'i2'), ('second', 'i2'), + ('Extent', 'S92')] + + # read head information + head_info = np.fromstring(byteArray[0:278], dtype=head_dtype) + + # get required grid information + data_type = head_info['type'][0] + nlon = head_info['longitudeGridNumber'][0] + nlat = head_info['latitudeGridNumber'][0] + nmem = head_info['ensembleTotalNumber'][0] + + # define data structure + if data_type == 4: + data_dtype = [('data', 'f4', (nlat, nlon))] + data_len = nlat * nlon * 4 + elif data_type == 11: + data_dtype = [('data', 'f4', (2, nlat, nlon))] + data_len = 2 * nlat * nlon * 4 + else: + raise Exception("Data type is not supported") + + # read data + if nmem == 0: + data = np.fromstring(byteArray[278:], dtype=data_dtype) + data = np.squeeze(data['data']) + else: + if data_type == 4: + data = np.full((nmem, nlat, nlon), np.nan) + else: + data = np.full((2, nmem, nlat, nlon), np.nan) + ind = 0 + for imem in range(nmem): + head_info_mem = np.fromstring( + byteArray[ind:(ind+278)], dtype=head_dtype) + ind += 278 + data_mem = np.fromstring( + byteArray[ind:(ind+data_len)], dtype=data_dtype) + ind += data_len + number = head_info_mem['perturbationNumber'][0] + if data_type == 4: + data[number, :, :] = np.squeeze(data_mem['data']) + else: + data[:, number, :, :] = np.squeeze(data_mem['data']) + + # construct longitude and latitude coordinates + slon = head_info['startLongitude'][0] + dlon = head_info['longitudeGridSpace'][0] + slat = head_info['startLatitude'][0] + dlat = head_info['latitudeGridSpace'][0] + lon = np.arange(nlon) * dlon + slon + lat = np.arange(nlat) * dlat + slat + level = np.array([head_info['level'][0]]) + + # construct initial time and forecast hour + init_time = datetime(head_info['year'][0], head_info['month'][0], + head_info['day'][0], head_info['hour'][0]) + fhour = np.array([head_info['period'][0]], dtype=np.float) + time = init_time + timedelta(hours=fhour[0]) + init_time = np.array([init_time], dtype='datetime64[m]') + time = np.array([time], dtype='datetime64[m]') + + # construct ensemble number + if nmem != 0: + number = np.arange(nmem) + + # create to xarray + if data_type == 4: + if nmem == 0: + if level[0] == 0: + data = data[np.newaxis, ...] + data = xr.DataArray( + data, coords=[time, lat, lon], + dims=['time', 'lat', 'lon'], name="data") + else: + data = data[np.newaxis, np.newaxis, ...] + data = xr.DataArray( + data, coords=[time, level, lat, lon], + dims=['time', 'level', 'lat', 'lon'], + name="data") + else: + if level[0] == 0: + data = data[np.newaxis, ...] + data = xr.DataArray( + data, coords=[time, number, lat, lon], + dims=['time', 'number', 'lat', 'lon'], + name="data") + else: + data = data[np.newaxis, :, np.newaxis, ...] + data = xr.DataArray( + data, coords=[time, number, level, lat, lon], + dims=['time', 'number', 'level', 'lat', 'lon'], + name="data") + elif data_type == 11: + if nmem == 0: + speed = np.squeeze(data[0, :, :]) + angle = np.squeeze(data[1, :, :]) + if level[0] == 0: + speed = speed[np.newaxis, ...] + angle = angle[np.newaxis, ...] + data = xr.Dataset({ + 'speed': (['time', 'lat', 'lon'], speed), + 'angle': (['time', 'lat', 'lon'], angle)}, + coords={'lon': lon, 'lat': lat, 'time': time}) + else: + speed = speed[np.newaxis, np.newaxis, ...] + angle = angle[np.newaxis, np.newaxis, ...] + data = xr.Dataset({ + 'speed': (['time', 'level', 'lat', 'lon'], speed), + 'angle': (['time', 'level', 'lat', 'lon'], angle)}, + coords={'lon': lon, 'lat': lat, 'level': level, + 'time': time}) + else: + speed = np.squeeze(data[0, :, :, :]) + angle = np.squeeze(data[1, :, :, :]) + if level[0] == 0: + speed = speed[np.newaxis, ...] + angle = angle[np.newaxis, ...] + data = xr.Dataset({ + 'speed': ( + ['time', 'number', 'lat', 'lon'], speed), + 'angle': ( + ['time', 'number', 'lat', 'lon'], angle)}, + coords={ + 'lon': lon, 'lat': lat, 'number': number, + 'time': time}) + else: + speed = speed[np.newaxis, :, np.newaxis, ...] + angle = angle[np.newaxis, :, np.newaxis, ...] + data = xr.Dataset({ + 'speed': ( + ['time', 'number', 'level', 'lat', 'lon'], + speed), + 'angle': ( + ['time', 'number', 'level', 'lat', 'lon'], + angle)}, + coords={ + 'lon': lon, 'lat': lat, 'level': level, + 'number': number, 'time': time}) + # add time coordinates + data.coords['init_time'] = ('time', init_time) + data.coords['fhour'] = ('time', fhour) + + # add attributes + data.attrs['data_directory'] = directory + data.attrs['data_filename'] = filename + data.attrs['organization'] = 'Created by NMC.' + + # return data + return data + + else: + return None + else: + return None + + +def get_station_data(directory, filename=None, suffix="*.000"): + """ + Retrieve station data from MICAPS cassandra service. + + :param directory: the data directory on the service + :param filename: the data filename, if none, will be the latest file. + :param suffix: the filename filter pattern which will + be used to find the specified file. + :return: pandas DataFrame. + + :example: + >>> data = get_station_data("SURFACE/PLOT_10MIN") + """ + + # connect to data service + service = GDSDataService() + + # get data file name + if filename is None: + try: + status, response = service.getLatestDataName(directory, suffix) + except ValueError: + print('Can not retrieve data from ' + directory) + return None + StringResult = DataBlock_pb2.StringResult() + if status == 200: + StringResult.ParseFromString(response) + if StringResult is not None: + filename = StringResult.name + if filename == '': + return None + else: + return None + + # get data contents + try: + status, response = service.getData(directory, filename) + except ValueError: + print('Can not retrieve data' + filename + ' from ' + directory) + return None + ByteArrayResult = DataBlock_pb2.ByteArrayResult() + if status == 200: + ByteArrayResult.ParseFromString(response) + if ByteArrayResult is not None: + byteArray = ByteArrayResult.byteArray + + # define head structure + head_dtype = [('discriminator', 'S4'), ('type', 'i2'), + ('description', 'S100'), + ('level', 'f4'), ('levelDescription', 'S50'), + ('year', 'i4'), ('month', 'i4'), ('day', 'i4'), + ('hour', 'i4'), ('minute', 'i4'), ('second', 'i4'), + ('Timezone', 'i4'), ('extent', 'S100')] + + # read head information + head_info = np.fromstring(byteArray[0:288], dtype=head_dtype) + ind = 288 + + # read the number of stations + station_number = np.fromstring( + byteArray[ind:(ind+4)], dtype='i4')[0] + ind += 4 + + # read the number of elements + element_number = np.fromstring( + byteArray[ind:(ind+2)], dtype='i2')[0] + ind += 2 + + # construct record structure + element_type_map = { + 1: 'b1', 2: 'i2', 3: 'i4', 4: 'i8', 5: 'f4', 6: 'f8', 7: 'S1'} + element_map = {} + for i in range(element_number): + element_id = str( + np.fromstring(byteArray[ind:(ind+2)], dtype='i2')[0]) + ind += 2 + element_type = np.fromstring( + byteArray[ind:(ind+2)], dtype='i2')[0] + ind += 2 + element_map[element_id] = element_type_map[element_type] + + # loop every station to retrieve record + record_head_dtype = [ + ('ID', 'i4'), ('lon', 'f4'), ('lat', 'f4'), ('numb', 'i2')] + records = [] + for i in range(station_number): + record_head = np.fromstring( + byteArray[ind:(ind+14)], dtype=record_head_dtype) + ind += 14 + record = { + 'ID': record_head['ID'][0], 'lon': record_head['lon'][0], + 'lat': record_head['lat'][0]} + for j in range(record_head['numb'][0]): # the record element number is not same, missing value is not included. + element_id = str( + np.fromstring(byteArray[ind:(ind + 2)], dtype='i2')[0]) + ind += 2 + element_type = element_map[element_id] + element_len = int(element_type[1]) + record[element_id] = np.fromstring( + byteArray[ind:(ind + element_len)], + dtype=element_type)[0] + ind += element_len + records += [record] + + # convert to pandas data frame + records = pd.DataFrame(records) + records.set_index('ID') + + # get time + time = datetime( + head_info['year'][0], head_info['month'][0], + head_info['day'][0], head_info['hour'][0], + head_info['minute'][0], head_info['second'][0]) + records['time'] = time + + # change column name for common observation + records.rename(columns={'3': 'alt', + '201': 'wind_angle', '203': 'wind_speed', '205': 'wind_angle_1m_avg', '207': 'wind_speed_1m_avg', + '209': 'wind_angle_2m_avg', '211': 'wind_speed_2m_avg', '213': 'wind_angle_10m_avg', '215': 'wind_speed_10m_avg', + '217': 'wind_angle_max', '219': 'wind_speed_max', '221': 'wind_angle_instant', '223': 'wind_speed_instant', + '225': 'gust_angle', '227': 'gust_speed', '229': 'gust_angle_6h', '231': 'gust_speed_6h', + '233': 'gust_angle_12h', '235': 'gust_speed_12h', '237': 'wind_power', + '401': 'sea_level_pressure', '403': 'pressure_3h_trend', '405': 'pressure_24h_trend', + '407': 'station_pressure', '409': 'pressure_max', '411': 'pressure_min', '413': 'pressure', + '415': 'pressure_day_avg', '417': 'slp_day_avg', '419': 'hight', '421': 'geopotential_hight', + '601': 'temp', '603': 'temp_max', '605': 'temp_min', '607': 'temp_24h_trend', + '609': 'temp_24h_max', '611':'temp_24h_min', '613': 'temp_dav_avg', + '801': 'dewpoint', '803': 'dewpoint_depression', '805': 'relative_humidity', + '807': 'relative_humidity_min', '809': 'relative_humidity_day_avg', + '811': 'water_vapor_pressure', '813': 'water_vapor_pressure_day_avg', + '1001': 'rain', '1003': 'rain_1h', '1005': 'rain_3h', '1007': 'rain_6h', '1009': 'rain_12h', '1013': 'rain_day', + '1015': 'rain_20-08', '1017': 'rain_08-20', '1019': 'rain_20-20', '1021': 'rain_08-08', + '1023': 'evaporation', '1025': 'evaporation_large', '1027': 'precipitable_water', + '1201': 'vis_1min', '1203': 'vis_10min', '1205': 'vis_min', '1207': 'vis_manual', + '1401': 'total_cloud_cover', '1403': 'low_cloud_cover', '1405': 'cloud_base_hight', + '1407': 'low_cloud', '1409': 'middle_cloud', '1411': 'high_cloud', + '1413': 'tcc_day_avg', '1415': 'lcc_day_avg', '1417': 'cloud_cover', '1419': 'cloud_type', + '1601': 'weather_current', '1603': 'weather_past_1', '1606': 'weather_past_2', + '2001': 'surface_temp', '2003': 'surface_temp_max', '2005': 'surface_temp_min'}, + inplace=True) + + # return + return records + else: + return None + else: + return None + + +def get_fy_awx(directory, filename=None, suffix="*.AWX"): + """ + Retrieve FY satellite cloud awx format file. + + :param directory: the data directory on the service + :param filename: the data filename, if none, will be the latest file. + :param suffix: the filename filter pattern which will be used to + find the specified file. + :return: satellite information and data. + + :Examples: + >>> directory = "SATELLITE/FY2E/L1/IR1/EQUAL" + >>> data = get_fy_awx(directory) + """ + + # connect to data service + service = GDSDataService() + + # get data file name + if filename is None: + try: + status, response = service.getLatestDataName(directory, suffix) + except ValueError: + print('Can not retrieve data from ' + directory) + return None + StringResult = DataBlock_pb2.StringResult() + if status == 200: + StringResult.ParseFromString(response) + if StringResult is not None: + filename = StringResult.name + if filename == '': + return None + else: + return None + + # get data contents + try: + status, response = service.getData(directory, filename) + except ValueError: + print('Can not retrieve data' + filename + ' from ' + directory) + return None + ByteArrayResult = DataBlock_pb2.ByteArrayResult() + if status == 200: + ByteArrayResult.ParseFromString(response) + if ByteArrayResult is not None: + byteArray = ByteArrayResult.byteArray + + # define head structure + head_dtype = [ + ('SAT96', 'S12'), # SAT96 filename + ('byteSequence', 'i2'), # integer number byte sequence + ('firstClassHeadLength', 'i2'), + ('secondClassHeadLength', 'i2'), + ('padDataLength', 'i2'), + ('recordLength', 'i2'), + ('headRecordNumber', 'i2'), + ('dataRecordNumber', 'i2'), + ('productCategory', 'i2'), + ('compressMethod', 'i2'), + ('formatString', 'S8'), + ('qualityFlag', 'i2'), + ('satelliteName', 'S8'), + ('year', 'i2'), ('month', 'i2'), + ('day', 'i2'), ('hour', 'i2'), + ('minute', 'i2'), + ('channel', 'i2'), + ('flagOfProjection', 'i2'), + ('widthOfImage', 'i2'), + ('heightOfImage', 'i2'), + ('scanLineNumberOfImageTopLeft', 'i2'), + ('pixelNumberOfImageTopLeft', 'i2'), + ('sampleRatio', 'i2'), + ('latitudeOfNorth', 'i2'), + ('latitudeOfSouth', 'i2'), + ('longitudeOfWest', 'i2'), + ('longitudeOfEast', 'i2'), + ('centerLatitudeOfProjection', 'i2'), + ('centerLongitudeOfProjection', 'i2'), + ('standardLatitude1', 'i2'), + ('standardLatitude2', 'i2'), + ('horizontalResolution', 'i2'), + ('verticalResolution', 'i2'), + ('overlapFlagGeoGrid', 'i2'), + ('overlapValueGeoGrid', 'i2'), + ('dataLengthOfColorTable', 'i2'), + ('dataLengthOfCalibration', 'i2'), + ('dataLengthOfGeolocation', 'i2'), + ('reserved', 'i2')] + head_info = np.fromstring(byteArray[0:104], dtype=head_dtype) + ind = 104 + + # head rest information + head_rest_len = (head_info['recordLength'][0].astype(np.int) * + head_info['headRecordNumber'][0] - ind) + head_rest = np.fromstring( + byteArray[ind:(ind + head_rest_len)], + dtype='u1', count=head_rest_len) + ind += head_rest_len + + # retrieve data records + data_len = (head_info['recordLength'][0].astype(np.int) * + head_info['dataRecordNumber'][0]) + data = np.fromstring( + byteArray[ind:(ind + data_len)], dtype='u1', + count=data_len) + data.shape = (head_info['recordLength'][0], + head_info['dataRecordNumber'][0]) + + # return + return head_info, data + else: + return None + else: + return None + + +def get_radar_mosaic(directory, filename=None, suffix="*.LATLON"): + """ + 该程序主要用于读取和处理中国气象局CRaMS系统的雷达回波全国拼图数据. + + :param directory: the data directory on the service + :param filename: the data filename, if none, will be the latest file. + :param suffix: the filename filter pattern which will be used to + find the specified file. + :return: xarray object. + + :Example: + >>> data = get_radar_mosaic("RADARMOSAIC/CREF/") + """ + + # connect to data service + service = GDSDataService() + + # get data file name + if filename is None: + try: + status, response = service.getLatestDataName(directory, suffix) + except ValueError: + print('Can not retrieve data from ' + directory) + return None + StringResult = DataBlock_pb2.StringResult() + if status == 200: + StringResult.ParseFromString(response) + if StringResult is not None: + filename = StringResult.name + if filename == '': + return None + else: + return None + + # get data contents + try: + status, response = service.getData(directory, filename) + except ValueError: + print('Can not retrieve data' + filename + ' from ' + directory) + return None + ByteArrayResult = DataBlock_pb2.ByteArrayResult() + if status == 200: + ByteArrayResult.ParseFromString(response) + if ByteArrayResult is not None: + byteArray = ByteArrayResult.byteArray + + # define head structure + head_dtype = [ + ('description', 'S128'), + # product name, QREF=基本反射率, CREF=组合反射率, + # VIL=液态水含量, OHP=一小时降水 + ('name', 'S32'), + ('organization', 'S16'), + ('grid_flag', 'u2'), # 经纬网格数据标识，固定值19532 + ('data_byte', 'i2'), # 数据单元字节数，固定值2 + ('slat', 'f4'), # 数据区的南纬（度） + ('wlon', 'f4'), # 数据区的西经（度） + ('nlat', 'f4'), # 数据区的北纬（度） + ('elon', 'f4'), # 数据区的东经（度） + ('clat', 'f4'), # 数据区中心纬度（度） + ('clon', 'f4'), # 数据区中心经度（度） + ('rows', 'i4'), # 数据区的行数 + ('cols', 'i4'), # 每行数据的列数 + ('dlat', 'f4'), # 纬向分辨率（度） + ('dlon', 'f4'), # 经向分辨率（度） + ('nodata', 'f4'), # 无数据区的编码值 + ('levelbybtes', 'i4'), # 单层数据字节数 + ('levelnum', 'i2'), # 数据层个数 + ('amp', 'i2'), # 数值放大系数 + ('compmode', 'i2'), # 数据压缩存储时为1，否则为0 + ('dates', 'u2'), # 数据观测时间，为1970年1月1日以来的天数 + ('seconds', 'i4'), # 数据观测时间的秒数 + ('min_value', 'i2'), # 放大后的数据最小取值 + ('max_value', 'i2'), # 放大后的数据最大取值 + ('reserved', 'i2', 6) # 保留字节 + ] + + # read head information + head_info = np.fromstring(byteArray[0:256], dtype=head_dtype) + ind = 256 + + # define data variable + rows = head_info['rows'][0] + cols = head_info['cols'][0] + dlat = head_info['dlat'][0] + dlon = head_info['dlon'][0] + data = np.full(rows*cols, -9999, dtype=np.int32) + + # put data into array + while ind < len(byteArray): + irow = np.fromstring(byteArray[ind:(ind + 2)], dtype='i2')[0] + ind += 2 + icol = np.fromstring(byteArray[ind:(ind + 2)], dtype='i2')[0] + ind += 2 + if irow == -1 or icol == -1: + break + nrec = np.fromstring(byteArray[ind:(ind + 2)], dtype='i2')[0] + ind += 2 + recd = np.fromstring( + byteArray[ind:(ind + 2*nrec)], dtype='i2', count=nrec) + ind += 2*nrec + position = (irow-1)*cols+icol-1 + data[position:(position+nrec)] = recd - 1 + + # reshape data + data.shape = (rows, cols) + + # set longitude and latitude coordinates + lats = head_info['nlat'][0] - np.arange(rows)*dlat - dlat/2.0 + lons = head_info['wlon'][0] - np.arange(cols)*dlon - dlon/2.0 + + # reverse latitude axis + data = np.flip(data, 0) + lats = lats[::-1] + + # set time coordinates + time = datetime(1970, 1, 1) + timedelta( + days=head_info['dates'][0].astype(np.float64), + seconds=head_info['seconds'][0].astype(np.float64)) + time = np.array([time], dtype='datetime64[m]') + data = np.expand_dims(data, axis=0) + + # create xarray + data = xr.DataArray( + data, coords=[time, lats, lons], + dims=['time', 'latitude', 'longitude'], + name="radar_mosaic") + + # return + return data + else: + return None + else: + return None + + +def get_tlogp(directory, filename=None, suffix="*.000"): + """ + 该程序用于读取micaps服务器上TLOGP数据信息, 文件格式与MICAPS第5类格式相同. + + :param directory: the data directory on the service + :param filename: the data filename, if none, will be the latest file. + :param suffix: the filename filter pattern which will be used to + find the specified file. + :return: pandas DataFrame object. + + >>> data = get_tlogp("UPPER_AIR/TLOGP/") + """ + + # connect to data service + service = GDSDataService() + + # get data file name + if filename is None: + try: + status, response = service.getLatestDataName(directory, suffix) + except ValueError: + print('Can not retrieve data from ' + directory) + return None + StringResult = DataBlock_pb2.StringResult() + if status == 200: + StringResult.ParseFromString(response) + if StringResult is not None: + filename = StringResult.name + if filename == '': + return None + else: + return None + + # get data contents + try: + status, response = service.getData(directory, filename) + except ValueError: + print('Can not retrieve data' + filename + ' from ' + directory) + return None + ByteArrayResult = DataBlock_pb2.ByteArrayResult() + if status == 200: + ByteArrayResult.ParseFromString(response) + if ByteArrayResult is not None: + byteArray = ByteArrayResult.byteArray + + # decode bytes to string + txt = byteArray.decode("utf-8") + txt = list(filter(None, re.split(' |\n', txt))) + + # observation date and time + if len(txt[3]) < 4: + year = int(txt[3]) + 2000 + else: + year = int(txt[3]) + month = int(txt[4]) + day = int(txt[5]) + hour = int(txt[6]) + time = datetime(year, month, day, hour) + + # the number of records + number = int(txt[7]) + if number < 1: + return None + + # cut the data + txt = txt[8:] + + # put the data into dictionary + index = 0 + records = [] + while index < len(txt): + # get the record information + ID = txt[index].strip() + lon = float(txt[index+1]) + lat = float(txt[index+2]) + alt = float(txt[index+3]) + number = int(int(txt[index+4])/6) + index += 5 + + # get the sounding records + for i in range(number): + record = { + 'ID': ID, 'lon': lon, 'lat': lat, 'alt': alt, + 'time': time, + 'p': float(txt[index]), 'h': float(txt[index+1]), + 't': float(txt[index+2]), 'td': float(txt[index+3]), + 'wind_angle': float(txt[index+4]), + 'wind_speed': float(txt[index+5])} + records.append(record) + index += 6 + + # transform to pandas data frame + records = pd.DataFrame(records) + records.set_index('ID') + + # return + return records + else: + return None + else: + return None + diff --git a/setup.py b/setup.py index a200892..c72b2e8 100644 --- a/setup.py +++ b/setup.py @@ -1,63 +1,63 @@ -# _*_ coding: utf-8 _*_ - -from os import path -from setuptools import find_packages, setup -from codecs import open - - -name = 'nmc_met_io' -author = __import__(name).__author__ -version = __import__(name).__version__ - -here = path.abspath(path.dirname(__file__)) - -# Get the long description from the README file -with open(path.join(here, 'README.md'), encoding='utf-8') as f: - long_description = f.read() - -setup( - name=name, - - version=version, - - description=("Collection of tools for I/O or" - "accessing meteorological data."), - long_description=long_description, - - # author - author=author, - author_email='kan.dai@foxmail.com', - - # LICENSE - license='GPL3', - - classifiers=[ - 'Development Status :: 3 - Alpha', - 'Intended Audience :: Developers', - 'Programming Language :: Python :: 3', - ], - - packages=find_packages(exclude=['docs', 'tests', 'build', 'dist']), - include_package_data=True, - exclude_package_data={'': ['.gitignore']}, - - install_requires=['numpy>=1.12.1', - 'scipy>=0.19.0', - 'xarray>=0.9.6', - 'pandas>=0.20.0', - 'pyproj>=1.9.5.1', - 'protobuf>=3.5.0', - 'urllib3>=1.20', - 'python-dateutil'] -) - -# development mode (DOS command): -# python setup.py develop -# python setup.py develop --uninstall - -# build mode： -# python setup.py build --build-base=D:/test/python/build - -# distribution mode: -# python setup.py sdist # create source tar.gz file in /dist -# python setup.py bdist_wheel # create wheel binary in /dist +# _*_ coding: utf-8 _*_ + +from os import path +from setuptools import find_packages, setup +from codecs import open + + +name = 'nmc_met_io' +author = __import__(name).__author__ +version = __import__(name).__version__ + +here = path.abspath(path.dirname(__file__)) + +# Get the long description from the README file +with open(path.join(here, 'README.md'), encoding='utf-8') as f: + long_description = f.read() + +setup( + name=name, + + version=version, + + description=("Collection of tools for I/O or" + "accessing meteorological data."), + long_description=long_description, + + # author + author=author, + author_email='kan.dai@foxmail.com', + + # LICENSE + license='GPL3', + + classifiers=[ + 'Development Status :: 3 - Alpha', + 'Intended Audience :: Developers', + 'Programming Language :: Python :: 3', + ], + + packages=find_packages(exclude=['docs', 'tests', 'build', 'dist']), + include_package_data=True, + exclude_package_data={'': ['.gitignore']}, + + install_requires=['numpy>=1.12.1', + 'scipy>=0.19.0', + 'xarray>=0.9.6', + 'pandas>=0.20.0', + 'pyproj>=1.9.5.1', + 'protobuf>=3.5.0', + 'urllib3>=1.20', + 'python-dateutil'] +) + +# development mode (DOS command): +# python setup.py develop +# python setup.py develop --uninstall + +# build mode： +# python setup.py build --build-base=D:/test/python/build + +# distribution mode: +# python setup.py sdist # create source tar.gz file in /dist +# python setup.py bdist_wheel # create wheel binary in /dist