Quentin
3271fee5cc
服务：Spring Boot 3.2 + docx4j 8.3.9，POST /api/v3/server_office_file/file/parse
接受 .docx，返回 HTML（公式 → LaTeX，图片 → RustFS 外链）
公式支持三类来源：
- OMML（Word 2007+ 公式） → Python omml_mathml2latex
- MathType OLE 对象 → Ruby mathtype2mathml → MathML → LaTeX
- Word EQ 域（老教辅主力） → EqToLatexUtil（本次新增）
本次改动：
1. 新增 java-svc/.../core/EqToLatexUtil.java：
移植自 jby backend-services office-core，EQ 语法 → LaTeX
（\f→\dfrac、\r→\sqrt、\i→\int/\sum/\prod、\s→^{}/_{}、\b→\left\right、
\a→array、\x→\boxed/\overline、\o\al 堆叠、圈码、化学符号、极限、连等式）
品牌标记 JBYU* → WPU*，与采集端一致
2. CtoMathFinder：接上 EQ 分支（原为 not-ported 桩），域代码经
EqToLatexUtil.convert 转 LaTeX 写入 eqLatexMap（WPEQNUM 占位符）
3. WordParseUtil.dealPlaceholder：EQ 的 LaTeX 同样加 \( \) 包裹
（原先因 WPEQNUM 例外不加包裹，前端/MathJax 不渲染）
修前症状：教辅 Word 里分式/方程组/上下标整段丢失（如 {−1/3, 1} 变成 {－，1}）
修后实测：46 份教辅 2908 处 EQ 域全部还原，公式总数 2954 处、零未包裹残留
安全：application.yml（含 RustFS 密钥）不入库，提供 application.yml.example；
OssService 的 @Value 默认密钥已清空
305 lines
10 KiB
Python
305 lines
10 KiB
Python
"""
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Statistics strategy for statistical notation.
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This strategy handles formatting for statistical equations, including
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probability operators, distribution notation, and statistical symbols.
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"""
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from lxml import etree as ET
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from typing import Set
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from ..core.interfaces import Strategy
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# Import from existing data modules
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from ..data import UNICODE_TO_LATEX, MATH_FUNCTIONS, UNICODE_PASSTHROUGH
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class StatisticsStrategy(Strategy):
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"""
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Statistical notation strategy.
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This strategy provides formatting for statistical content:
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- Probability operators → \\Pr, \\operatorname{Var}, \\operatorname{Cov}
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- Expected value E remains italic (use mathvariant="double-struck" for \\mathbb{E})
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- Distribution notation → proper formatting
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- Statistical symbols → Greek letters, operators
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- Variables remain italic (LaTeX default)
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"""
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# Mathematical functions that get special LaTeX commands
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FUNCTIONS: Set[str] = MATH_FUNCTIONS
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# Statistical functions and operators (upright)
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# CRITICAL: 'E' is NOT in this list - it's just a regular identifier
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# Only use \mathbb{E} when there's explicit mathvariant="double-struck" attribute
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STATISTICAL_OPERATORS: Set[str] = {
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'Pr', # Probability
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# 'E', # Expected value - REMOVED: should remain italic unless mathvariant specified
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'Var', # Variance
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'Cov', # Covariance
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'Cor', # Correlation
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'SD', # Standard deviation
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'SE', # Standard error
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'MSE', # Mean squared error
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'RSS', # Residual sum of squares
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'SSE', # Sum of squared errors
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'Bias', # Bias
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'df', # degrees of freedom
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'logit', # Logit function
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'probit', # Probit function
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}
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# Distribution names (upright)
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DISTRIBUTIONS: Set[str] = {
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'Normal',
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'Binomial',
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'Poisson',
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'Exponential',
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'Uniform',
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'Gamma',
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'Beta',
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'Bernoulli',
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'Geometric',
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'Hypergeometric',
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'Multinomial',
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'NegativeBinomial',
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'Chi',
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'ChiSquared',
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'Student',
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'F',
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'Weibull',
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'Cauchy',
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'Laplace',
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'Logistic',
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'Pareto',
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}
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def __init__(self):
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"""Initialize the statistics strategy."""
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pass
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def format_identifier(self, text: str, node: ET.Element) -> str:
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"""
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Format an identifier (<mi> element) for statistics.
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Args:
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text: The identifier text content
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node: The <mi> element node
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Returns:
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Formatted LaTeX string
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Logic:
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1. Mathematical functions → \\function (e.g., "sin" → "\\sin")
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2. Statistical operators → \\operatorname{op} (e.g., "Var" → "\\operatorname{Var}")
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3. Distribution names → \\mathrm{dist} (e.g., "Normal" → "\\mathrm{Normal}")
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4. Single letters → unchanged (variables remain italic)
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5. Greek letters → LaTeX symbols
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Examples:
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"Pr" → "\\Pr"
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"E" → "E" (expected value - remains italic unless mathvariant="double-struck")
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"Var" → "\\operatorname{Var}"
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"Normal" → "\\mathrm{Normal}"
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"μ" → "\\mu"
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"σ" → "\\sigma"
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"x" → "x" (random variable)
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"""
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# Check if it's a mathematical function
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if text in self.FUNCTIONS:
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return f"\\{text}"
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# Special statistical operators with LaTeX commands
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if text == 'Pr':
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return '\\Pr'
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elif text in self.STATISTICAL_OPERATORS:
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# CRITICAL: Do NOT automatically convert 'E' to \mathbb{E}!
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# Only apply \mathbb{} when there's explicit mathvariant="double-struck" attribute
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# The mi_visitor will handle mathvariant attributes properly.
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# In statistics mode, treat 'E' like other operators (upright but not blackboard bold)
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return f"\\operatorname{{{text}}}"
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# Distribution names (upright)
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if text in self.DISTRIBUTIONS:
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return f"\\mathrm{{{text}}}"
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# UNICODE_PASSTHROUGH: Keep certain symbols as Unicode for MathJax compatibility
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if text in UNICODE_PASSTHROUGH:
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return text
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# Check for Unicode symbols (Greek letters)
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if text in UNICODE_TO_LATEX:
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return UNICODE_TO_LATEX[text]
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# Handle multi-character strings
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if len(text) > 1:
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# Check if it contains Unicode (passthrough or convertible)
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has_unicode = any(char in UNICODE_TO_LATEX for char in text)
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has_passthrough = any(char in UNICODE_PASSTHROUGH for char in text)
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if has_unicode or has_passthrough:
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converted_parts = []
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for char in text:
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if char in UNICODE_PASSTHROUGH:
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converted_parts.append(char)
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elif char in UNICODE_TO_LATEX:
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converted_parts.append(UNICODE_TO_LATEX[char])
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elif char.isspace():
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converted_parts.append(' ')
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else:
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converted_parts.append(char)
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return ' '.join(converted_parts)
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# Default: return as-is (variables remain italic in LaTeX)
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return text
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def format_operator(self, text: str, node: ET.Element) -> str:
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"""
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Format an operator (<mo> element) for statistics.
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Args:
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text: The operator text content
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node: The <mo> element node
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Returns:
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Formatted LaTeX string
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Logic:
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1. Delimiters → __DELIM__ markers for later processing
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2. Unicode symbols → LaTeX equivalents (via UNICODE_TO_LATEX)
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3. Statistical symbols → proper notation (~, ∼, ≈, etc.)
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4. Standard operators → unchanged (+, -, *, /, =)
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Examples:
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"(" → "__DELIM__(__DELIM__"
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"~" → "\\sim" (distributed as)
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"∼" → "\\sim"
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"≈" → "\\approx"
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"∝" → "\\propto" (proportional to)
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"∈" → "\\in"
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"""
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# CRITICAL: Mark delimiters for potential scaling
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# This matches MathStrategy behavior
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if text in ("(", ")", "[", "]", "{", "}"):
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return f"__DELIM__{text}__DELIM__"
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# Special case: pipe can be absolute value delimiter
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if text == "|":
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return f"__DELIM__|__DELIM__"
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# Handle < and > specifically (LaTeX convention)
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if text == "<":
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return "\\lt"
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if text == ">":
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return "\\gt"
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# Tilde (distributed as)
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if text == '~' or text == '∼':
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return '\\sim'
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# UNICODE_PASSTHROUGH: Keep certain symbols as Unicode for MathJax compatibility
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if text in UNICODE_PASSTHROUGH:
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return text
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# Check for Unicode symbol mapping
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if text in UNICODE_TO_LATEX:
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return UNICODE_TO_LATEX[text]
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# Handle multi-character operators with Unicode
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if len(text) > 1:
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has_unicode = any(char in UNICODE_TO_LATEX for char in text)
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has_passthrough = any(char in UNICODE_PASSTHROUGH for char in text)
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if has_unicode or has_passthrough:
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converted_parts = []
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for char in text:
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if char in UNICODE_PASSTHROUGH:
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converted_parts.append(char)
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elif char in UNICODE_TO_LATEX:
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converted_parts.append(UNICODE_TO_LATEX[char])
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else:
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converted_parts.append(char)
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return ' '.join(converted_parts)
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# Default: return as-is
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return text
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def format_number(self, text: str, node: ET.Element) -> str:
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"""
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Format a number (<mn> element) for statistics.
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Args:
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text: The number text content
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node: The <mn> element node
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Returns:
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Formatted LaTeX string
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Logic:
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Numbers are returned as-is in statistics mode.
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Examples:
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"0.05" → "0.05" (p-value)
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"95" → "95" (confidence level)
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"""
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# Numbers are returned as-is
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return text
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def detect_context(self, equation_text: str) -> bool:
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"""
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Detect if an equation is statistical content.
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Args:
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equation_text: The full equation text
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Returns:
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True if likely statistics, False otherwise
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Detection indicators:
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- Statistical operators (Pr, E, Var, Cov)
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- Distribution notation (Normal, Binomial, etc.)
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- Greek letters commonly used in stats (μ, σ, β, α)
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- Tilde notation (X ~ Normal)
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- Statistical symbols (≈, ∝, ∼)
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Examples:
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"X ~ Normal(μ, σ²)" → True
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"E[X] = μ" → True
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"Var(X) = σ²" → True
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"sin(x) + cos(x)" → False
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"""
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# Check for statistical operators
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op_count = sum(1 for op in self.STATISTICAL_OPERATORS if op in equation_text)
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if op_count >= 1:
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return True
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# Check for distribution names
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dist_count = sum(1 for dist in self.DISTRIBUTIONS if dist in equation_text)
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if dist_count >= 1:
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return True
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# Check for tilde notation (distributed as)
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if '~' in equation_text or '∼' in equation_text:
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return True
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# Check for common Greek letters in statistics context
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stats_greek = ['μ', 'σ', 'β', 'α', 'θ', 'λ', 'ρ', 'τ', 'χ']
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greek_count = sum(1 for letter in stats_greek if letter in equation_text)
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if greek_count >= 2: # At least 2 Greek letters
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return True
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# Check for statistical patterns (p-value, confidence interval)
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import re
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if re.search(r'p\s*[<>=]?\s*0\.\d+', equation_text): # p-value
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return True
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if re.search(r'\d+%\s*(CI|confidence)', equation_text, re.IGNORECASE):
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return True
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return False
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@property
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def name(self) -> str:
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"""Get the strategy name."""
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return "statistics"
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def __repr__(self) -> str:
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"""String representation for debugging."""
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return f"StatisticsStrategy(operators={len(self.STATISTICAL_OPERATORS)}, distributions={len(self.DISTRIBUTIONS)})"
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