Synthesizer class#103
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marcosfrenkel merged 5 commits intotoolsforexperiments:mainfrom Mar 5, 2026
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…ract model() Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
marcosfrenkel
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Feb 25, 2026
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Could you add some implemented examples of how this would look like? You can have some generic functions (Gaussian, exponential, sine, etc.) and in the comments write how an example would look like.
How are the parameters handled? What should I do if I want to generate 2 different sets of data with different parameters?
labcore/data/synthesizer.py
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| def generate(self, coordinates): | ||
| return self.model(coordinates) + self.noise() |
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You are calling the self.noise() function here, but there is no way to pass a different std value when generating the data.
…ial, sine, and gaussian class implementations
… are now static methods. Parameters can be set at instantiation or overridden in generate().
… class model() signatures
marcosfrenkel
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Mar 4, 2026
labcore/data/datagen.py
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| import numpy as np | ||
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| import dataclasses |
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| import dataclasses | |
| from dataclasses import dataclass |
labcore/data/datagen.py
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| @dataclasses.dataclass |
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labcore/data/datagen.py
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| return np.random.normal(scale = std, size = len(coordinates)) | ||
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labcore/data/datagen.py
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labcore/data/datagen.py
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| return A * np.sin(2 * np.pi * coordinates * f + phi) + of | ||
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marcosfrenkel
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Mar 5, 2026
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Basic frame for data synthesizer.