科学计算科研数据分析【免费下载链接】astropyAstronomy and astrophysics core library项目地址https://gitcode.com/gh_mirrors/as/astropy点击查看免费下载本文基于 astropy 官方文档 Custom Cosmology I/O formats 展开讲解如何向 astropy Cosmology 的统一 I/O 框架注册自定义格式一是面向内存对象转换的to_format/from_formatconvert_registry二是面向文件读写的read/writereadwrite_registry。读完后你可以照着文中完整示例为任意数据形态Row、JSON 等实现可复用的 Cosmology 序列化/反序列化并理解其底层注册、识别与回环验证机制。框架概览两套独立的注册表astropy.cosmology.io包提供了统一接口来读取、写出和转换Cosmology对象。用户入口是Cosmology类上的四个方法见 astropy/cosmology/io.py 的模块说明Cosmology.read/Cosmology.write从文件读入 / 写出文件Cosmology.from_format/Cosmology.to_format在 Python 对象如 dict、Table与Cosmology之间转换。这四个方法背后各挂着一套自定义注册表而不是Table等使用的全局注册表# astropy/cosmology/_src/io/connect.py readwrite_registry io_registry.UnifiedIORegistry() # L36read/write 用 convert_registry io_registry.UnifiedIORegistry() # L156from/to_format 用在 astropy/cosmology/_src/core.py 中它们以类变量形式绑定到Cosmologyfrom_format: ClassVar UnifiedReadWriteMethod(CosmologyFromFormat) to_format: ClassVar UnifiedReadWriteMethod(CosmologyToFormat) read: ClassVar UnifiedReadWriteMethod(CosmologyRead) write: ClassVar UnifiedReadWriteMethod(CosmologyWrite)因此为某个格式注册自定义解析器时需要拿到对应的注册表Cosmology.from_format.registry即convert_registry——用于to/from_formatCosmology.read.registry即readwrite_registry——用于read/write。每注册一个格式通常要提供三个函数reader解析为Cosmology、writer从Cosmology输出、identifier自动识别格式。注册表本身的 API 位于 astropy/io/registry通用框架说明见 docs/io/registry.rst。一个值得注意的机制是CosmologyRead/CosmologyFromFormat在被子类调用时例如FlatLambdaCDM.read(...)会自动注入关键字参数cosmology该子类并校验用户显式传入的cosmology参数必须与该类或其__qualname__一致否则抛出ValueError见 astropy/cosmology/_src/io/connect.py整个注册调用还会包在add_enabled_units(cu)上下文中使 astropy 宇宙学单位如km / (Mpc s)可用。自定义 to/from_format 格式convert_registry官方文档以astropy.table.Row为例演示了一个完整的 |Cosmology| ↔ |Row| 转换器。文档特意只手写 mapping 级别的逻辑而不直接复用内置解析器以便展示最完整的模式。注意真实的内置实现就在 astropy/cosmology/_src/io/builtin/row.py其from_row的写法与下面示例几乎一致同样是把 Row 转成 dict 后交给from_mapping。1. 编写 readerRow → Cosmology该函数应接收 1 个位置参数行对象和 2 个关键字参数move_to_meta多余字段如何处理与cosmology使用哪个Cosmology类。关于元数据处理的详细说明可以通过Cosmology.from_format.help(mapping)查看。 import copy from astropy.cosmology import Cosmology def from_table_row(row, *, move_to_metaFalse, cosmologyNone): ... # get name from column ... name row[name] if name in row.columns else None ... meta copy.deepcopy(row.meta) ... # turn row into mapping (dict of the arguments) ... mapping dict(row) ... mapping[name] name ... mapping.setdefault(cosmology, meta.pop(cosmology, None)) ... mapping[meta] meta ... # build cosmology from map ... return Cosmology.from_format(mapping, move_to_metamove_to_meta, ... cosmologycosmology)关键设计在于reader 并不自己解析每个物理参数而是把 Row 拼回一个 mapping再委托给内置的mapping格式Cosmology.from_format(mapping, ...)。move_to_meta与cosmology两个参数原样透传保证行为与内置格式一致。对照内置实现 astropy/cosmology/_src/io/builtin/mapping.py 中的from_mapping可以看到其核心逻辑是按rename映射重命名键并通过_rename_map保证重命名后的键不与原键冲突冲突会抛出ValueError从cosmology参数或 mapping 中的cosmology字段确定目标类字符串会通过_COSMOLOGY_CLASSES解析为类用inspect.signature(cosmology)bind_partialapply_defaults把类签名中的默认值填进来再逐个绑定 mapping 中出现的参数——这就是用具体子类解析时缺失参数会被类默认值补齐的底层机制剩余多余参数若构造函数有**kwargs则收入其中否则在move_to_metaTrue时合并进meta显式 metadata 优先否则抛出TypeError: there are unused parameters ...。然后注册到convert_registry convert_registry.register_reader(astropy.row, Cosmology, from_table_row)2. 编写 writerCosmology → Rowwriter 只需要Cosmology对象和一个*args用来吸收astropy.io.registry.UnifiedReadWriteCosmology.to_format的底层实现见 connect.py传递的多余信息 from astropy.table import QTable def to_table_row(cosmology, *args): ... p cosmology.to_format(mapping, cosmology_as_strTrue) ... meta p.pop(meta) ... # package parameters into lists for Table parsing ... params {k: [v] for k, v in p.items()} ... return QTable(params, metameta)[0] # return row convert_registry.register_writer(astropy.row, Cosmology, to_table_row)两个细节值得注意to_format(mapping, cosmology_as_strTrue)会把类对象换成类名如FlatLambdaCDM使输出可以放进 Table 的str13列。参数语义可对照 mapping.py 中to_mapping的文档所有参数值被包进单元素列表{k: [v] for ...}因为 Table 列必须是序列最后用QTable(...)[0]取出第一行即Row。这与内置to_rowbuiltin/row.py内部调to_table后返回table[0]的路径一致。3. 编写 identifier 并注册identifier 用于在用户不指定format时自动识别格式。签名是(origin, format, *args, **kwargs)origin为read或write对convert_registry而言待识别对象位于args[1]args[0]是目标类 from astropy.cosmology import Cosmology from astropy.table import Row def row_identify(origin, format, *args, **kwargs): ... Identify if object uses the Table format. ... if origin read: ... return isinstance(args[1], Row) and (format in (None, astropy.row)) ... return False convert_registry.register_identifier(astropy.row, Cosmology, row_identify)4. 回环验证注册完成后即可在Cosmology.from_format/Cosmology.to_format中使用 from astropy.cosmology import Planck18 row Planck18.to_format(astropy.row) row Row index0 cosmology name H0 Om0 Tcmb0 Neff m_nu Ob0 km / (Mpc s) K eV str13 str8 float64 float64 float64 float64 float64[3] float64 ------------- -------- ------------ ------- ------- ------- ----------- ------- FlatLambdaCDM Planck18 67.66 0.30966 2.7255 3.046 0.0 .. 0.06 0.04897 cosmo Cosmology.from_format(row) cosmo Planck18 # test it round-trips Truecosmo Planck18为True说明整个往返链路Cosmology → mapping → QTable/Row → mapping → Cosmology无信息丢失。测试目录 astropy/cosmology/_src/tests/io/ 中对内置 row 格式也有等价的回环测试可以参考。自定义 read/write 文件格式readwrite_registry文件级格式与对象级格式的区别在于reader 接收文件路径或文件对象writer 负责落盘。官方文档给出了一个完整的 |Cosmology| ↔ JSON 序列化器示例并且复用已注册的 mapping 格式来大幅简化实现——这是推荐做法。1. 编写 readerJSON → Cosmology函数接收 1 个位置参数文件对象或文件路径其余**kwargs透传给Cosmology.from_format由它处理元数据和目标Cosmology类细节同Cosmology.from_format.help(mapping) import json, os import astropy.units as u from astropy.cosmology import Cosmology from astropy.cosmology.io import readwrite_registry def read_json(filename, **kwargs): ... # read file, from path-like or file-like ... if isinstance(filename, (str, bytes, os.PathLike)): ... with open(filename, r) as file: ... data file.read() ... else: # file-like : this also handles errors in dumping ... data filename.read() ... mapping json.loads(data) # parse json mappable to dict ... # deserialize Quantity ... for k, v in mapping.items(): ... if isinstance(v, dict) and value in v and unit in v: ... mapping[k] u.Quantity(v[value], v[unit]) ... for k, v in mapping.get(meta, {}).items(): # also the metadata ... if isinstance(v, dict) and value in v and unit in v: ... mapping[meta][k] u.Quantity(v[value], v[unit]) ... return Cosmology.from_format(mapping, **kwargs) readwrite_registry.register_reader(json, Cosmology, read_json)这段代码的三个要点兼容路径与文件对象两种输入文件对象分支的注释指出它顺便处理写出时 dump 的错误u.Quantity不兼容原生 JSON反序列化约定为{value: ..., unit: ...}结构主参数和meta中的 Quantity 都要还原解析出 dict 后不再自行构造Cosmology而是交给Cosmology.from_format(mapping, **kwargs)——**kwargs中的cosmology/move_to_meta/rename等参数由 mapping 格式统一处理。2. 编写 writerCosmology → JSONwriter 需要Cosmology对象与文件对象/路径并需要一个布尔标志overwrite来定义覆盖已有文件的行为 def write_json(cosmology, file, *, overwriteFalse, **kwargs): ... data cosmology.to_format(mapping, cosmology_as_strTrue) # start by turning into dict ... # serialize Quantity ... for k, v in data.items(): ... if isinstance(v, u.Quantity): ... data[k] {value: v.value.tolist(), unit: str(v.unit)} ... for k, v in data.get(meta, {}).items(): # also serialize the metadata ... if isinstance(v, u.Quantity): ... data[meta][k] {value: v.value.tolist(), unit: str(v.unit)} ... ... if isinstance(file, (str, bytes, os.PathLike)): ... # check that file exists and whether to overwrite. ... if os.path.exists(file) and not overwrite: ... raise IOError(f{file} exists. Set overwrite to write over.) ... with open(file, w) as write_file: ... json.dump(data, write_file) ... else: ... json.dump(data, file) readwrite_registry.register_writer(json, Cosmology, write_json)注意v.value.tolist()把 ndarray 转成纯 Python 列表避免json.dump对 numpy 类型报错overwriteFalse默认时若文件已存在则抛错这是文件级 writer 的常见契约。仓库中有一份与文档示例几乎同构、且在 CI 中持续运行的实现——单元测试 astropy/cosmology/_src/tests/io/test_json.py它的read_json/write_json/json_identify三个函数与文档示例一一对应测试版用Path与OSError并把 Quantity 解析包进u.add_enabled_units(cu.redshift)上下文以支持红移单位还额外验证了用写入时同一子类读取部分信息文件时缺失参数会由类默认值补齐test_readwrite_json_subclass_partial_info。这可以作为自己实现文件级格式时的参考模板。3. identifier 与回环验证 def json_identify(origin, filepath, fileobj, *args, **kwargs): ... Identify if object uses the JSON format. ... return filepath is not None and filepath.endswith(.json) readwrite_registry.register_identifier(json, Cosmology, json_identify)文件级 identifier 的签名是(origin, filepath, fileobj, *args, **kwargs)按 astropy/io/registry/base.py 中register_identifier的说明filepath与fileobj任一可能为None两者都为None时 identifier 只能依赖args。按文件扩展名判断是最简单的可靠策略。注册后即可完成文件级读写回环 import tempfile from astropy.cosmology import Planck18 file tempfile.NamedTemporaryFile() Planck18.write(file.name, formatjson, overwriteTrue) with open(file.name) as f: f.readlines() [{cosmology: FlatLambdaCDM, name: Planck18, H0: {value: 67.66, unit: km / (Mpc s)}, Om0: 0.30966, ... cosmo Cosmology.read(file.name, formatjson) file.close() cosmo Planck18 # test it round-trips True输出的 JSON 中可以看到cosmology以字符串类名出现、H0被展开为{value: 67.66, unit: km / (Mpc s)}与 writer 的序列化约定完全对应。注册表 API 细节与清理注册与解除注册从 astropy/io/registry/core.py 可以看到register_reader/register_writer的完整签名registry.register_reader(data_format, data_class, function, forceFalse, priority0) registry.register_writer(data_format, data_class, function, forceFalse, priority0) registry.register_identifier(data_format, data_class, identifier, forceFalse) # base.py L213重复注册同一(format, class)组合且forceFalse时会抛出IORegistryErroralready definedpriority用于在多个候选格式都匹配时择优数值越高越优先unregister_reader/unregister_writer/unregister_identifier用于移除注册若格式不存在同样抛IORegistryErrorget_reader(format, class)可查询当前注册的函数未命中时错误信息中会附带该类的可用格式表_get_format_table_str。官方文档示例在结尾特意清理了注册状态避免示例污染 doctest 环境 from astropy.io.registry import IORegistryError readwrite_registry.unregister_reader(json, Cosmology) readwrite_registry.unregister_writer(json, Cosmology) readwrite_registry.unregister_identifier(json, Cosmology) try: ... readwrite_registry.get_reader(json, Cosmology) ... except IORegistryError: ... pass这一注册—测试—注销的三段式与 test_json.py 中 fixture 的 setup/teardown 写法注册时加forceTrueyield后逐一unregister_*一致是写测试时的最佳实践。查看可用格式注册表会把注册结果反映到方法的help()与list_formats()中。当前内置格式摘自 docs/cosmology/io/index.rst Cosmology.read.list_formats() Format Read Write Auto-identify ---------- ---- ----- ------------- ascii.ecsv Yes Yes Yes ascii.html Yes Yes Yes ascii.mrt Yes Yes Yes Cosmology.write.list_formats() Format Read Write Auto-identify ----------- ---- ----- ------------- ascii.ecsv Yes Yes Yes ascii.html Yes Yes Yes ascii.latex No Yes Yes ascii.mrt Yes Yes Yes Cosmology.to_format.list_formats() Format Read Write Auto-identify ----------------- ---- ----- ------------- astropy.cosmology Yes Yes Yes astropy.model Yes Yes Yes astropy.row Yes Yes Yes astropy.table Yes Yes Yes mapping Yes Yes Yes yaml Yes Yes NoAuto-identify 列即为是否注册了 identifier如yaml只有 Yes/Yes/No说明它必须显式传formatyaml。你注册的第三方格式会同样出现在这两张表中。实践要点小结先想好复用哪一层能用内置mapping格式做胶水的就不要直接手写参数解析——两个官方示例Row、JSON都是这样实现的行为自动与move_to_meta、cosmology、rename等语义保持一致两套注册表不要混用对象级格式注册到convert_registryCosmology.from_format.registry文件级格式注册到readwrite_registryCosmology.read.registry注册错表会导致list_formats中出现却调不到identifier 决定自动识别能力文件级建议用扩展名等强信号JSON 例对象级建议用isinstance判断Row 例并在format已显式指定时放行Quantity 需要自定义编解码u.Quantity与 JSON 等文本格式不兼容{value: ..., unit: ...}约定 遍历meta是两个官方示例共同采用的方案以回环断言收尾Cosmology.from_format(cosmo.to_format(...)) cosmo或文件级的Cosmology.read是验证实现正确性的最简方式官方示例与 astropy/cosmology/_src/tests/io/ 下的测试均以此为标准动作。更多背景I/O 总览见 docs/cosmology/io/index.rst内置格式ascii.ecsv、astropy.table、mapping、yaml等的参数细节见 docs/cosmology/io/builtin.rst字段重命名与子类读取行为见 docs/cosmology/io/details.rst通用 I/O 注册框架见 docs/io/registry.rst。赞分享科学计算科研数据分析【免费下载链接】astropyAstronomy and astrophysics core library项目地址https://gitcode.com/gh_mirrors/as/astropy点击查看免费下载相关推荐astropy Cosmology 内置 I/O 格式详解Cosmology 对象的转换、读写与源码实现astropy Cosmology 内置 I/O 格式详解Cosmology 对象的转换、读写与源码实现 本文基于 astropy 官方文档 Built in科学计算科研数据分析astropy 宇宙学模块开发者指南default_cosmology、自定义 Cosmology 与 I/O 互操作astropy 宇宙学模块开发者指南default_cosmology、自定义 Cosmology 与 I/O 互操作 本文基于 astropy 官方开发者文科学计算科研数据分析网页视频怎么下载猫抓从资源嗅探到 M3U8 合并的 3 步完整流程网页视频怎么下载猫抓从资源嗅探到 M3U8 合并的 3 步完整流程 猫抓cat catch是一款浏览器资源嗅探扩展打开网页后自动列出其中的 MP4、M3音视频上一篇Dear ImGui 自写渲染后端如何支持 ImGuiBackendFlags_RendererHasTextures1.92下一篇Gin 开启 HTTP/2 服务推送RunTLS 环境下怎么用 Writer.Pusher 预推静态资源创作声明：本文部分内容由AI辅助生成（AIGC），仅供参考 astropy Cosmology 自定义 I/O 格式实战：为 to/from_format 与 read/write 注册扩展解析器
科学计算科研数据分析【免费下载链接】astropyAstronomy and astrophysics core library项目地址https://gitcode.com/gh_mirrors/as/astropy点击查看免费下载本文基于 astropy 官方文档 Custom Cosmology I/O formats 展开讲解如何向 astropy Cosmology 的统一 I/O 框架注册自定义格式一是面向内存对象转换的to_format/from_formatconvert_registry二是面向文件读写的read/writereadwrite_registry。读完后你可以照着文中完整示例为任意数据形态Row、JSON 等实现可复用的 Cosmology 序列化/反序列化并理解其底层注册、识别与回环验证机制。框架概览两套独立的注册表astropy.cosmology.io包提供了统一接口来读取、写出和转换Cosmology对象。用户入口是Cosmology类上的四个方法见 astropy/cosmology/io.py 的模块说明Cosmology.read/Cosmology.write从文件读入 / 写出文件Cosmology.from_format/Cosmology.to_format在 Python 对象如 dict、Table与Cosmology之间转换。这四个方法背后各挂着一套自定义注册表而不是Table等使用的全局注册表# astropy/cosmology/_src/io/connect.py readwrite_registry io_registry.UnifiedIORegistry() # L36read/write 用 convert_registry io_registry.UnifiedIORegistry() # L156from/to_format 用在 astropy/cosmology/_src/core.py 中它们以类变量形式绑定到Cosmologyfrom_format: ClassVar UnifiedReadWriteMethod(CosmologyFromFormat) to_format: ClassVar UnifiedReadWriteMethod(CosmologyToFormat) read: ClassVar UnifiedReadWriteMethod(CosmologyRead) write: ClassVar UnifiedReadWriteMethod(CosmologyWrite)因此为某个格式注册自定义解析器时需要拿到对应的注册表Cosmology.from_format.registry即convert_registry——用于to/from_formatCosmology.read.registry即readwrite_registry——用于read/write。每注册一个格式通常要提供三个函数reader解析为Cosmology、writer从Cosmology输出、identifier自动识别格式。注册表本身的 API 位于 astropy/io/registry通用框架说明见 docs/io/registry.rst。一个值得注意的机制是CosmologyRead/CosmologyFromFormat在被子类调用时例如FlatLambdaCDM.read(...)会自动注入关键字参数cosmology该子类并校验用户显式传入的cosmology参数必须与该类或其__qualname__一致否则抛出ValueError见 astropy/cosmology/_src/io/connect.py整个注册调用还会包在add_enabled_units(cu)上下文中使 astropy 宇宙学单位如km / (Mpc s)可用。自定义 to/from_format 格式convert_registry官方文档以astropy.table.Row为例演示了一个完整的 |Cosmology| ↔ |Row| 转换器。文档特意只手写 mapping 级别的逻辑而不直接复用内置解析器以便展示最完整的模式。注意真实的内置实现就在 astropy/cosmology/_src/io/builtin/row.py其from_row的写法与下面示例几乎一致同样是把 Row 转成 dict 后交给from_mapping。1. 编写 readerRow → Cosmology该函数应接收 1 个位置参数行对象和 2 个关键字参数move_to_meta多余字段如何处理与cosmology使用哪个Cosmology类。关于元数据处理的详细说明可以通过Cosmology.from_format.help(mapping)查看。 import copy from astropy.cosmology import Cosmology def from_table_row(row, *, move_to_metaFalse, cosmologyNone): ... # get name from column ... name row[name] if name in row.columns else None ... meta copy.deepcopy(row.meta) ... # turn row into mapping (dict of the arguments) ... mapping dict(row) ... mapping[name] name ... mapping.setdefault(cosmology, meta.pop(cosmology, None)) ... mapping[meta] meta ... # build cosmology from map ... return Cosmology.from_format(mapping, move_to_metamove_to_meta, ... cosmologycosmology)关键设计在于reader 并不自己解析每个物理参数而是把 Row 拼回一个 mapping再委托给内置的mapping格式Cosmology.from_format(mapping, ...)。move_to_meta与cosmology两个参数原样透传保证行为与内置格式一致。对照内置实现 astropy/cosmology/_src/io/builtin/mapping.py 中的from_mapping可以看到其核心逻辑是按rename映射重命名键并通过_rename_map保证重命名后的键不与原键冲突冲突会抛出ValueError从cosmology参数或 mapping 中的cosmology字段确定目标类字符串会通过_COSMOLOGY_CLASSES解析为类用inspect.signature(cosmology)bind_partialapply_defaults把类签名中的默认值填进来再逐个绑定 mapping 中出现的参数——这就是用具体子类解析时缺失参数会被类默认值补齐的底层机制剩余多余参数若构造函数有**kwargs则收入其中否则在move_to_metaTrue时合并进meta显式 metadata 优先否则抛出TypeError: there are unused parameters ...。然后注册到convert_registry convert_registry.register_reader(astropy.row, Cosmology, from_table_row)2. 编写 writerCosmology → Rowwriter 只需要Cosmology对象和一个*args用来吸收astropy.io.registry.UnifiedReadWriteCosmology.to_format的底层实现见 connect.py传递的多余信息 from astropy.table import QTable def to_table_row(cosmology, *args): ... p cosmology.to_format(mapping, cosmology_as_strTrue) ... meta p.pop(meta) ... # package parameters into lists for Table parsing ... params {k: [v] for k, v in p.items()} ... return QTable(params, metameta)[0] # return row convert_registry.register_writer(astropy.row, Cosmology, to_table_row)两个细节值得注意to_format(mapping, cosmology_as_strTrue)会把类对象换成类名如FlatLambdaCDM使输出可以放进 Table 的str13列。参数语义可对照 mapping.py 中to_mapping的文档所有参数值被包进单元素列表{k: [v] for ...}因为 Table 列必须是序列最后用QTable(...)[0]取出第一行即Row。这与内置to_rowbuiltin/row.py内部调to_table后返回table[0]的路径一致。3. 编写 identifier 并注册identifier 用于在用户不指定format时自动识别格式。签名是(origin, format, *args, **kwargs)origin为read或write对convert_registry而言待识别对象位于args[1]args[0]是目标类 from astropy.cosmology import Cosmology from astropy.table import Row def row_identify(origin, format, *args, **kwargs): ... Identify if object uses the Table format. ... if origin read: ... return isinstance(args[1], Row) and (format in (None, astropy.row)) ... return False convert_registry.register_identifier(astropy.row, Cosmology, row_identify)4. 回环验证注册完成后即可在Cosmology.from_format/Cosmology.to_format中使用 from astropy.cosmology import Planck18 row Planck18.to_format(astropy.row) row Row index0 cosmology name H0 Om0 Tcmb0 Neff m_nu Ob0 km / (Mpc s) K eV str13 str8 float64 float64 float64 float64 float64[3] float64 ------------- -------- ------------ ------- ------- ------- ----------- ------- FlatLambdaCDM Planck18 67.66 0.30966 2.7255 3.046 0.0 .. 0.06 0.04897 cosmo Cosmology.from_format(row) cosmo Planck18 # test it round-trips Truecosmo Planck18为True说明整个往返链路Cosmology → mapping → QTable/Row → mapping → Cosmology无信息丢失。测试目录 astropy/cosmology/_src/tests/io/ 中对内置 row 格式也有等价的回环测试可以参考。自定义 read/write 文件格式readwrite_registry文件级格式与对象级格式的区别在于reader 接收文件路径或文件对象writer 负责落盘。官方文档给出了一个完整的 |Cosmology| ↔ JSON 序列化器示例并且复用已注册的 mapping 格式来大幅简化实现——这是推荐做法。1. 编写 readerJSON → Cosmology函数接收 1 个位置参数文件对象或文件路径其余**kwargs透传给Cosmology.from_format由它处理元数据和目标Cosmology类细节同Cosmology.from_format.help(mapping) import json, os import astropy.units as u from astropy.cosmology import Cosmology from astropy.cosmology.io import readwrite_registry def read_json(filename, **kwargs): ... # read file, from path-like or file-like ... if isinstance(filename, (str, bytes, os.PathLike)): ... with open(filename, r) as file: ... data file.read() ... else: # file-like : this also handles errors in dumping ... data filename.read() ... mapping json.loads(data) # parse json mappable to dict ... # deserialize Quantity ... for k, v in mapping.items(): ... if isinstance(v, dict) and value in v and unit in v: ... mapping[k] u.Quantity(v[value], v[unit]) ... for k, v in mapping.get(meta, {}).items(): # also the metadata ... if isinstance(v, dict) and value in v and unit in v: ... mapping[meta][k] u.Quantity(v[value], v[unit]) ... return Cosmology.from_format(mapping, **kwargs) readwrite_registry.register_reader(json, Cosmology, read_json)这段代码的三个要点兼容路径与文件对象两种输入文件对象分支的注释指出它顺便处理写出时 dump 的错误u.Quantity不兼容原生 JSON反序列化约定为{value: ..., unit: ...}结构主参数和meta中的 Quantity 都要还原解析出 dict 后不再自行构造Cosmology而是交给Cosmology.from_format(mapping, **kwargs)——**kwargs中的cosmology/move_to_meta/rename等参数由 mapping 格式统一处理。2. 编写 writerCosmology → JSONwriter 需要Cosmology对象与文件对象/路径并需要一个布尔标志overwrite来定义覆盖已有文件的行为 def write_json(cosmology, file, *, overwriteFalse, **kwargs): ... data cosmology.to_format(mapping, cosmology_as_strTrue) # start by turning into dict ... # serialize Quantity ... for k, v in data.items(): ... if isinstance(v, u.Quantity): ... data[k] {value: v.value.tolist(), unit: str(v.unit)} ... for k, v in data.get(meta, {}).items(): # also serialize the metadata ... if isinstance(v, u.Quantity): ... data[meta][k] {value: v.value.tolist(), unit: str(v.unit)} ... ... if isinstance(file, (str, bytes, os.PathLike)): ... # check that file exists and whether to overwrite. ... if os.path.exists(file) and not overwrite: ... raise IOError(f{file} exists. Set overwrite to write over.) ... with open(file, w) as write_file: ... json.dump(data, write_file) ... else: ... json.dump(data, file) readwrite_registry.register_writer(json, Cosmology, write_json)注意v.value.tolist()把 ndarray 转成纯 Python 列表避免json.dump对 numpy 类型报错overwriteFalse默认时若文件已存在则抛错这是文件级 writer 的常见契约。仓库中有一份与文档示例几乎同构、且在 CI 中持续运行的实现——单元测试 astropy/cosmology/_src/tests/io/test_json.py它的read_json/write_json/json_identify三个函数与文档示例一一对应测试版用Path与OSError并把 Quantity 解析包进u.add_enabled_units(cu.redshift)上下文以支持红移单位还额外验证了用写入时同一子类读取部分信息文件时缺失参数会由类默认值补齐test_readwrite_json_subclass_partial_info。这可以作为自己实现文件级格式时的参考模板。3. identifier 与回环验证 def json_identify(origin, filepath, fileobj, *args, **kwargs): ... Identify if object uses the JSON format. ... return filepath is not None and filepath.endswith(.json) readwrite_registry.register_identifier(json, Cosmology, json_identify)文件级 identifier 的签名是(origin, filepath, fileobj, *args, **kwargs)按 astropy/io/registry/base.py 中register_identifier的说明filepath与fileobj任一可能为None两者都为None时 identifier 只能依赖args。按文件扩展名判断是最简单的可靠策略。注册后即可完成文件级读写回环 import tempfile from astropy.cosmology import Planck18 file tempfile.NamedTemporaryFile() Planck18.write(file.name, formatjson, overwriteTrue) with open(file.name) as f: f.readlines() [{cosmology: FlatLambdaCDM, name: Planck18, H0: {value: 67.66, unit: km / (Mpc s)}, Om0: 0.30966, ... cosmo Cosmology.read(file.name, formatjson) file.close() cosmo Planck18 # test it round-trips True输出的 JSON 中可以看到cosmology以字符串类名出现、H0被展开为{value: 67.66, unit: km / (Mpc s)}与 writer 的序列化约定完全对应。注册表 API 细节与清理注册与解除注册从 astropy/io/registry/core.py 可以看到register_reader/register_writer的完整签名registry.register_reader(data_format, data_class, function, forceFalse, priority0) registry.register_writer(data_format, data_class, function, forceFalse, priority0) registry.register_identifier(data_format, data_class, identifier, forceFalse) # base.py L213重复注册同一(format, class)组合且forceFalse时会抛出IORegistryErroralready definedpriority用于在多个候选格式都匹配时择优数值越高越优先unregister_reader/unregister_writer/unregister_identifier用于移除注册若格式不存在同样抛IORegistryErrorget_reader(format, class)可查询当前注册的函数未命中时错误信息中会附带该类的可用格式表_get_format_table_str。官方文档示例在结尾特意清理了注册状态避免示例污染 doctest 环境 from astropy.io.registry import IORegistryError readwrite_registry.unregister_reader(json, Cosmology) readwrite_registry.unregister_writer(json, Cosmology) readwrite_registry.unregister_identifier(json, Cosmology) try: ... readwrite_registry.get_reader(json, Cosmology) ... except IORegistryError: ... pass这一注册—测试—注销的三段式与 test_json.py 中 fixture 的 setup/teardown 写法注册时加forceTrueyield后逐一unregister_*一致是写测试时的最佳实践。查看可用格式注册表会把注册结果反映到方法的help()与list_formats()中。当前内置格式摘自 docs/cosmology/io/index.rst Cosmology.read.list_formats() Format Read Write Auto-identify ---------- ---- ----- ------------- ascii.ecsv Yes Yes Yes ascii.html Yes Yes Yes ascii.mrt Yes Yes Yes Cosmology.write.list_formats() Format Read Write Auto-identify ----------- ---- ----- ------------- ascii.ecsv Yes Yes Yes ascii.html Yes Yes Yes ascii.latex No Yes Yes ascii.mrt Yes Yes Yes Cosmology.to_format.list_formats() Format Read Write Auto-identify ----------------- ---- ----- ------------- astropy.cosmology Yes Yes Yes astropy.model Yes Yes Yes astropy.row Yes Yes Yes astropy.table Yes Yes Yes mapping Yes Yes Yes yaml Yes Yes NoAuto-identify 列即为是否注册了 identifier如yaml只有 Yes/Yes/No说明它必须显式传formatyaml。你注册的第三方格式会同样出现在这两张表中。实践要点小结先想好复用哪一层能用内置mapping格式做胶水的就不要直接手写参数解析——两个官方示例Row、JSON都是这样实现的行为自动与move_to_meta、cosmology、rename等语义保持一致两套注册表不要混用对象级格式注册到convert_registryCosmology.from_format.registry文件级格式注册到readwrite_registryCosmology.read.registry注册错表会导致list_formats中出现却调不到identifier 决定自动识别能力文件级建议用扩展名等强信号JSON 例对象级建议用isinstance判断Row 例并在format已显式指定时放行Quantity 需要自定义编解码u.Quantity与 JSON 等文本格式不兼容{value: ..., unit: ...}约定 遍历meta是两个官方示例共同采用的方案以回环断言收尾Cosmology.from_format(cosmo.to_format(...)) cosmo或文件级的Cosmology.read是验证实现正确性的最简方式官方示例与 astropy/cosmology/_src/tests/io/ 下的测试均以此为标准动作。更多背景I/O 总览见 docs/cosmology/io/index.rst内置格式ascii.ecsv、astropy.table、mapping、yaml等的参数细节见 docs/cosmology/io/builtin.rst字段重命名与子类读取行为见 docs/cosmology/io/details.rst通用 I/O 注册框架见 docs/io/registry.rst。赞分享科学计算科研数据分析【免费下载链接】astropyAstronomy and astrophysics core library项目地址https://gitcode.com/gh_mirrors/as/astropy点击查看免费下载相关推荐astropy Cosmology 内置 I/O 格式详解Cosmology 对象的转换、读写与源码实现astropy Cosmology 内置 I/O 格式详解Cosmology 对象的转换、读写与源码实现 本文基于 astropy 官方文档 Built in科学计算科研数据分析astropy 宇宙学模块开发者指南default_cosmology、自定义 Cosmology 与 I/O 互操作astropy 宇宙学模块开发者指南default_cosmology、自定义 Cosmology 与 I/O 互操作 本文基于 astropy 官方开发者文科学计算科研数据分析网页视频怎么下载猫抓从资源嗅探到 M3U8 合并的 3 步完整流程网页视频怎么下载猫抓从资源嗅探到 M3U8 合并的 3 步完整流程 猫抓cat catch是一款浏览器资源嗅探扩展打开网页后自动列出其中的 MP4、M3音视频上一篇Dear ImGui 自写渲染后端如何支持 ImGuiBackendFlags_RendererHasTextures1.92下一篇Gin 开启 HTTP/2 服务推送RunTLS 环境下怎么用 Writer.Pusher 预推静态资源创作声明：本文部分内容由AI辅助生成（AIGC），仅供参考