File size: 19,112 Bytes
2f63916
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
import csv
import json
import sympy as sp
import re
import random
import itertools

# Load CSV file containing seed questions and maximal symbolic perturbations. 
csv_file_path = 'Seed_and_Max_Symbolic_Perturbations.csv'

with open(csv_file_path, 'r', encoding='utf-8') as cf:
    data = list(csv.DictReader(cf))  # Read CSV into list of dicts
cur_data_len = len(data)
print("Length of initial data: ", cur_data_len)  # Print initial dataset size

# Define symbolic variables that appear in the symbolic perturbations - and will be replaced by various expressions during variant generation.
x, A, B, F, G, H, N = sp.symbols('x A B F G H N', real=True)
Q = sp.symbols('Q', real=True, positive=True)


# Define symbolic perturbation characters and their corresponding sympy symbols
symnoise_char_list = ['A', 'B', 'F', 'G', 'H']
symnoise_sym_list = [A, B, F, G, H]
local_sym_dict = {'x': x, 'A': A, 'B': B, 'F': F, 'G': G, 'H': H, 'N': N, 'Q': Q}

# These sources contain explicit hypergeometric functions, which are marked by 'F' - so 'F' is not treated as a symbolic perturbation character. 
# The hg_ variables below represent this special treatment.
hypergeomatric_question_sources = ["ASyMOB\nHypergeometrics\nQ1", "ASyMOB\nHypergeometrics\nQ2", "ASyMOB\nHypergeometrics\nQ3", "ASyMOB\nHypergeometrics\nQ4"]
hg_symnoise_char_list = ['A', 'B', 'G', 'H']
hg_symnoise_sym_list = [A, B, G, H]
hg_local_sym_dict = {'x': x, 'A': A, 'B': B, 'G': G, 'H': H, 'N': N, 'Q': Q}


# List of easy equivalent forms (should simplify to 1)
equivalent_forms_easy = [
    sp.sin(-Q*x)**2 + sp.cos(Q*x)**2,
    -sp.sinh(Q*x)**2 + sp.cosh(Q*x)**2,
    (sp.log(x) * sp.log(Q,x))/sp.log(Q),
    Q * sp.Sum( x / (Q * 2**N) , (N, 1, sp.oo)) / x,
    (sp.exp(sp.I * Q * x) - sp.exp(-sp.I * Q * x)) / (2 * sp.I * sp.sin(Q * x))
]
# List of hard equivalent forms (should simplify to 1)
equivalent_forms_hard = [
    (sp.tan((Q-1)*x) + sp.tan(x)) / ((1 - sp.tan((Q-1)*x) * sp.tan(x)) * sp.tan(Q*x)),
    sp.sinh(sp.log(Q*x + sp.sqrt((Q*x)**2 + 1))) / (Q*x),
    (sp.log(x / sp.E, Q) + sp.log(sp.E, Q))/ sp.log(x, Q),
    Q * sp.Sum( (6 * x) / (Q * (N * sp.pi)**2) , (N, 1, sp.oo)) / x,
    -((1 + sp.exp(4 * sp.I * Q * x)) / (1 - sp.exp(4 * sp.I * Q * x))) * (2 * sp.tan(Q*x) / ((1 - sp.tan(Q*x)**2)) * sp.I)
]

# Test that all equivalent forms simplify to 1 and are numerically close to 1.
# Note that some expressions above do not simplify to 1 by sp.simplify - due to the CAS's limitations - but are evaluated correctly to 1 numerically.
# We still print the warning to raise user awareness.
equivalence_test_x = -2.5
equivalence_test_Q = 0.5
equivalence_test_margin = 1e-4
for form in (equivalent_forms_easy + equivalent_forms_hard):
    # Check if the form is equivalent to 1
    if sp.simplify(form) != 1 or (abs(form.subs(Q, equivalence_test_Q).subs(x, equivalence_test_x).evalf() - 1) > equivalence_test_margin):
        print(f"Form {form} is not equivalent to 1")
        print(f"{form} is simplified to {sp.simplify(form)}")
        print("Form is numerically evaluated to: ", form.subs(Q, equivalence_test_Q).subs(x, equivalence_test_x).evalf())
    
# LaTeX representations of the easy and hard equivalent forms
eq_forms_latex_easy = [
 r'\sin^{2}{\left(- Q x \right)} + \cos^{2}{\left(Q x \right)}',
 r'- \sinh^{2}{\left(Q x \right)} + \cosh^{2}{\left(Q x \right)}',
 r'\frac{\ln(x) \cdot \log_{x}(Q)}{\ln(Q)}',
 r'\frac{Q \sum_{N=1}^{\infty} \frac{2^{- N} x}{Q}}{x}',
 r'- \frac{i \left(e^{i Q x} - e^{- i Q x}\right)}{2 \sin{\left(Q x \right)}}']
eq_forms_latex_hard = [
 r'\frac{\tan{\left(x \right)} + \tan{\left(x \left(Q - 1\right) \right)}}{\left(- \tan{\left(x \right)} \tan{\left(x \left(Q - 1\right) \right)} + 1\right) \tan{\left(Q x \right)}}',
 r'\frac{\sinh{\left(\log{\left(Q x + \sqrt{Q^{2} x^{2} + 1} \right)} \right)}}{Q x}',
 r'\frac{\log_Q\left(\frac{x}{e}\right) + \log_Q(e)}{\log_Q(x)}',
 r'\frac{Q \sum_{N=1}^{\infty} \frac{6 x}{\pi^{2} N^{2} Q}}{x}',
 r'- \frac{2 i \left(e^{4 i Q x} + 1\right) \tan{\left(Q x \right)}}{\left(1 - e^{4 i Q x}\right) \left(1 - \tan^{2}{\left(Q x \right)}\right)}']

def replace_in_dollars(s, old, new):
    # Replace 'old' with 'new' inside all $...$ math substrings in s
    def repl(match):
        return match.group(0).replace(old, new)
    return re.sub(r'\$(.*?)\$', repl, s)

def char_in_dollars(s, char):
    """Return True if char appears inside any $...$ substring in s."""
    matches = re.findall(r'\$(.*?)\$', s)
    return any(char in match for match in matches)

def check_for_problematic_symbols(sp_ans):
    """Check for problematic symbols in sp_ans, but allow infinities if they are only used as summation or integration limits."""
    # Check for NaN or zoo anywhere
    if sp_ans.has(sp.nan) or sp_ans.has(sp.zoo):
        return True
    # Check for oo or -oo not as summation/integration limits
    def has_bad_infinity(expr):
        # If it's a Sum or Integral, skip limits
        if isinstance(expr, (sp.Sum, sp.Integral)):
            # expr.limits is a tuple of tuples: (symbol, lower, upper)
            # Only check the function part, not the limits
            return has_bad_infinity(expr.function)
        # If it's an infinity itself, it's problematic
        if expr == sp.oo or expr == -sp.oo:
            return True
        # Recursively check args
        return any(has_bad_infinity(arg) for arg in getattr(expr, 'args', []))
    return has_bad_infinity(sp_ans)

# Generate symbolic and numeric variants for each item in the dataset
def generate_variants(items, symnoise_chars, symnoise_syms, sym_dict, cur_ind):
    next_ind = cur_ind
    new_items = []
    for item in items:
        latex_chall = item.get("Challenge")
        sp_sym_ans = sp.sympify(item.get("Answer in Sympy"), locals = sym_dict)
        source = item.get("Source")
        chars_in_latex = []
        syms_in_latex = []
        # Find which symbolic perturbation characters are present in the LaTeX challenge
        for i in range(len(symnoise_chars)):
            if char_in_dollars(latex_chall, symnoise_chars[i]):
                chars_in_latex.append(symnoise_chars[i])
                syms_in_latex.append(symnoise_syms[i])
        if len(chars_in_latex) == 0:
            print("No symbolic parameters found inside math expressions in source: ",source)

        item['Variation'] = f"Symbolic-{len(chars_in_latex)}"
            
        # Replace all symbols in symnoise_sym_list by 1 for equivalence perturbation answers.
        sp_sym_ans_ones = sp_sym_ans.subs(dict(zip(symnoise_syms, [1]*len(symnoise_syms))))
        # Check for problematic symbols in sp_sym_ans_ones
        if check_for_problematic_symbols(sp_sym_ans_ones):
            print(f"Warning: sp_sym_ans_ones for {item} contains problematic symbol(s): {sp_sym_ans_ones}")

        # Generate all permutations of easy/hard equivalent forms for all symbolic chars
        ordered_sets = list(itertools.permutations(range(len(eq_forms_latex_easy)), len(chars_in_latex)))
        for order in ordered_sets:
            # Substitute easy forms
            latex_chall_copy = latex_chall
            for i in range(len(chars_in_latex)):
                latex_chall_copy = replace_in_dollars(latex_chall_copy, chars_in_latex[i], r' \left(' + eq_forms_latex_easy[order[i]].replace('Q', chars_in_latex[i]) + r'\right) ' )
            next_ind += 1
            new_items.append({
                    "Index": str(next_ind),
                    "Challenge": latex_chall_copy,
                    "Answer in Sympy": str(sp_sym_ans_ones),
                    "Answer in Latex": "",
                    "Variation": "Equivalence-All-Easy",
                    "Source": source
                })
            # Substitute hard forms
            latex_chall_copy = latex_chall
            for i in range(len(chars_in_latex)):
                latex_chall_copy = replace_in_dollars(latex_chall_copy, chars_in_latex[i], r' \left(' + eq_forms_latex_hard[order[i]].replace('Q', chars_in_latex[i]) + r'\right) ' )
            next_ind += 1
            new_items.append({
                    "Index": str(next_ind),
                    "Challenge": latex_chall_copy,
                    "Answer in Sympy": str(sp_sym_ans_ones),
                    "Answer in Latex": "",
                    "Variation": "Equivalence-All-Hard",
                    "Source": source
                })

        # Generate single-symbolic substitutions (easy/hard) and numeric perturbation variants
        for i in range(len(chars_in_latex)):
            chars_left_in_latex = chars_in_latex.copy()
            chars_left_in_latex.pop(i)
            for j in range(len(eq_forms_latex_easy)):
                # Substitute one easy form
                latex_chall_copy = latex_chall
                replace_form = r' \left(' + eq_forms_latex_easy[j].replace('Q', chars_in_latex[i]) + r'\right) '
                latex_chall_copy = replace_in_dollars(latex_chall_copy, chars_in_latex[i], replace_form )
                for ch in chars_left_in_latex:
                    latex_chall_copy = replace_in_dollars(latex_chall_copy, ch, '')
                next_ind += 1
                new_items.append({
                        "Index": str(next_ind),
                        "Challenge": latex_chall_copy,
                        "Answer in Sympy": str(sp_sym_ans_ones),
                        "Answer in Latex": "",
                        "Variation": "Equivalence-One-Easy",
                        "Source": source
                    })
                # Substitute one hard form
                latex_chall_copy = latex_chall
                replace_form = r' \left(' + eq_forms_latex_hard[j].replace('Q', chars_in_latex[i]) + r'\right) '
                latex_chall_copy = replace_in_dollars(latex_chall_copy, chars_in_latex[i], replace_form)
                for ch in chars_left_in_latex:
                    latex_chall_copy = replace_in_dollars(latex_chall_copy, ch, '')
                next_ind += 1
                new_items.append({
                        "Index": str(next_ind),
                        "Challenge": latex_chall_copy,
                        "Answer in Sympy": str(sp_sym_ans_ones),
                        "Answer in Latex": "",
                        "Variation": "Equivalence-One-Hard",
                        "Source": source
                    })
                
            # Numeric perturbation: replace one symbol with a random integer of increasing digit length
            for noise_digits in range(1, 11):
                latex_chall_copy = latex_chall
                sp_sym_ans_copy = sp_sym_ans
                nn1 = random.randint(10**(noise_digits-1), 10**noise_digits - 1)
                sp_sym_ans_copy = sp_sym_ans_copy.subs(syms_in_latex[i], sp.UnevaluatedExpr(nn1), evaluate=False)
                while check_for_problematic_symbols(sp_sym_ans_copy):
                    print(f"Warning: Numeric-One noise for {item} contains problems: {sp_sym_ans_copy}. Retrying")
                    nn1 = random.randint(10**(noise_digits-1), 10**noise_digits - 1)
                    sp_sym_ans_copy = sp_sym_ans_copy.subs(syms_in_latex[i], sp.UnevaluatedExpr(nn1), evaluate=False)
                replace_form = r' \left(' + str(nn1) + r'\right) '
                latex_chall_copy = replace_in_dollars(latex_chall_copy, chars_in_latex[i], replace_form)
                for ch in chars_left_in_latex:
                    latex_chall_copy = replace_in_dollars(latex_chall_copy, ch, '')
                for sym in syms_in_latex:
                    sp_sym_ans_copy = sp_sym_ans_copy.subs(sym, 1)
                latex_chall_copy = re.sub(r'Assume.*?\.', '', latex_chall_copy)
                next_ind += 1
                new_items.append({
                    "Index": str(next_ind),
                    "Challenge": latex_chall_copy,
                    "Answer in Sympy": str(sp_sym_ans_copy),
                    "Answer in Latex": "",
                    "Variation": f"Numeric-One-{noise_digits}",
                    "Source": source
                })

            
        # Numeric perturbation: replace all symbols with random integers of increasing digit length
        for noise_digits in range(1, 11):
            latex_chall_copy = latex_chall
            sp_sym_ans_copy = sp_sym_ans
            nn_lst = [random.randint(10**(noise_digits-1), 10**noise_digits - 1) for _ in range(len(chars_in_latex))]
            for i in range(len(chars_in_latex)):
                sp_sym_ans_copy = sp_sym_ans_copy.subs(syms_in_latex[i], sp.UnevaluatedExpr(nn_lst[i]), evaluate=False)
            while check_for_problematic_symbols(sp_sym_ans_copy):
                print(f"Warning: Numeric-All noise for {item} contains problems: {sp_sym_ans_copy}. Retrying")
                nn_lst = [random.randint(10**(noise_digits-1), 10**noise_digits - 1) for _ in range(len(chars_in_latex))]
                for i in range(len(chars_in_latex)):
                    sp_sym_ans_copy = sp_sym_ans_copy.subs(syms_in_latex[i], sp.UnevaluatedExpr(nn_lst[i]), evaluate=False)
            for i in range(len(chars_in_latex)):
                latex_chall_copy = replace_in_dollars(latex_chall_copy, chars_in_latex[i], r' \left(' + str(nn_lst[i]) + r'\right) ' )

            # Remove "Assume ... ." clause from latex_chall if it exists
            latex_chall_copy = re.sub(r'Assume.*?\.', '', latex_chall_copy)

            # Add new item with rolling index
            next_ind += 1
            new_items.append({
                "Index": str(next_ind),
                "Challenge": latex_chall_copy,
                "Answer in Sympy": str(sp_sym_ans_copy),
                "Answer in Latex": "",
                "Variation": f"Numeric-All-{noise_digits}",
                "Source": source
            })
            
        # Generate variants with some symbols replaced by 1 (partial symbolic)
        for i in range(1, len(chars_in_latex)):
            oned_indexes = list(itertools.combinations(range(len(chars_in_latex)), i))
            for oned_set in oned_indexes:
                latex_chall_copy = latex_chall
                sp_sym_ans_copy = sp_sym_ans
                for ind in oned_set:
                    latex_chall_copy = replace_in_dollars(latex_chall_copy, chars_in_latex[ind], '')
                    sp_sym_ans_copy = sp_sym_ans_copy.subs(syms_in_latex[ind], 1)
                next_ind += 1
                new_items.append({
                    "Index": str(next_ind),
                    "Challenge": latex_chall_copy,
                    "Answer in Sympy": str(sp_sym_ans_copy),
                    "Answer in Latex": "",
                    "Variation": f"Symbolic-{len(chars_in_latex) - i}",
                    "Source": source
                })
    # Add new_items to data before writing output
    data.extend(new_items)

# Generate 'Numeric-All-2-S' variants - the 'Variance' subset
def generate_NA2S(items, symnoise_chars, symnoise_syms, sym_dict, cur_ind, noise_digits, reps_num):
    next_ind = cur_ind
    new_items = []

    for item in items:
        latex_chall = item.get("Challenge")
        sp_sym_ans = sp.sympify(item.get("Answer in Sympy"), locals = sym_dict)
        source = item.get("Source")
        chars_in_latex = []
        syms_in_latex = []
        # Find which symbolic noise characters are present in the LaTeX challenge
        for i in range(len(symnoise_chars)):
            if char_in_dollars(latex_chall, symnoise_chars[i]):
                chars_in_latex.append(symnoise_chars[i])
                syms_in_latex.append(symnoise_syms[i])
        if len(chars_in_latex) == 0:
            print("No symbolic parameters found inside math expressions in source: ",source)
        
        for _ in range(reps_num):
            latex_chall_copy = latex_chall
            sp_sym_ans_copy = sp_sym_ans
            # Generate random integer values for all symbolic chars
            nn_lst = [random.randint(10**(noise_digits-1), 10**(noise_digits) - 1) for _ in range(len(chars_in_latex))]
            for i in range(len(chars_in_latex)):
                sp_sym_ans_copy = sp_sym_ans_copy.subs(syms_in_latex[i], sp.UnevaluatedExpr(nn_lst[i]), evaluate=False)

            while check_for_problematic_symbols(sp_sym_ans_copy):
                print(f"Warning: Numeric-All noise for {item} contains problems: {sp_sym_ans_copy}. Retrying")
                nn_lst = [random.randint(10**(noise_digits-1), 10**noise_digits - 1) for _ in range(len(chars_in_latex))]
                for i in range(len(chars_in_latex)):
                    sp_sym_ans_copy = sp_sym_ans_copy.subs(syms_in_latex[i], sp.UnevaluatedExpr(nn_lst[i]), evaluate=False)

            for i in range(len(chars_in_latex)):
                latex_chall_copy = replace_in_dollars(latex_chall_copy, chars_in_latex[i], r' \left(' + str(nn_lst[i]) + r'\right) ' )
                
            # Remove "Assume ... ." clause from latex_chall if it exists
            latex_chall_copy = re.sub(r'Assume.*?\.', '', latex_chall_copy)
            next_ind += 1
            new_items.append({
                "Index": str(next_ind),
                "Challenge": latex_chall_copy,
                "Answer in Sympy": str(sp_sym_ans_copy),
                "Answer in Latex": "",
                "Variation": f"Numeric-All-{noise_digits}-S",
                "Source": source
            })
    # Add new_items to data before writing output
    data.extend(new_items)


# Split items into regular and hypergeometric symbolic questions
sym_var_items = [item for item in data if (item.get('Variation', '').strip() == 'Symbolic' and item.get('Source') not in hypergeomatric_question_sources)]
hypergeometric_sym_var_items = [item for item in data if (item.get('Variation', '').strip() == 'Symbolic' and item.get('Source') in hypergeomatric_question_sources)]

# Generate all variants for regular and hypergeometric items
generate_variants(sym_var_items, symnoise_char_list, symnoise_sym_list, local_sym_dict, cur_data_len)
cur_data_len = len(data)
generate_variants(hypergeometric_sym_var_items, hg_symnoise_char_list, hg_symnoise_sym_list, hg_local_sym_dict, cur_data_len)
cur_data_len = len(data)
generate_NA2S(sym_var_items, symnoise_char_list, symnoise_sym_list, local_sym_dict, cur_data_len, 2, 50)
cur_data_len = len(data)
generate_NA2S(hypergeometric_sym_var_items, hg_symnoise_char_list, hg_symnoise_sym_list, hg_local_sym_dict, cur_data_len, 2, 50)
cur_data_len = len(data)
print("Final size of the ASyMOB dataset is: " ,cur_data_len) 

# Write the full dataset to a JSON file
output_json_path = 'Full_ASyMOB_Dataset.json'
with open(output_json_path, 'w', encoding='utf-8') as jf:
    json.dump(data, jf, ensure_ascii=False, indent=2)