Basic tokenizer #6
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Lev1ty
reviewed
Jan 16, 2021
tokenizer
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| @@ -0,0 +1,24 @@ | |||
| import numpy as np | |||
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| def tokenizer( | |||
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Functions use imperative language.
Lev1ty
reviewed
Jan 16, 2021
tokenizer
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| for x in nucleotide_sequence: | ||
| if x == "A" or x == "a": | ||
| arr.append([0,counter]) # Map A to 0 | ||
| elif x == "C" or x == "c": | ||
| arr.append([1,counter]) # Map C to 1 | ||
| elif x == "G" or x == "g": | ||
| arr.append([2,counter]) # Map G to 2 | ||
| elif x == "T" or x == "t": | ||
| arr.append([3,counter]) # Map T to 3 |
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Could be faster here. Try defining a dict {'A': 0, 'C': 1, 'G': 2, 'T': 3} as a "Rosetta Stone" for tokenizing the base pairs
Lev1ty
reviewed
Jan 16, 2021
tokenizer
Outdated
| elif x == "T" or x == "t": | ||
| arr.append([3,counter]) # Map T to 3 | ||
| counter += 1 # Increment counter | ||
| np_arr = np.array(arr) # Convert finished array to a numpy array |
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Breaks single-responsibility principle. The function name claims it tokenizes a string, not additionally constructing a NumPy array.
Lev1ty
requested changes
Jan 16, 2021
Lev1ty
requested changes
Jan 16, 2021
| "G" : 2, | ||
| "T" : 3 | ||
| } # Declares the integers that correspond to each nucleotide | ||
| # counter = 0 |
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Remove the counter for clarity
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| for x in nucleotide_sequence: | ||
| arr.append(mappings[x]) # Adds a converted nucleotide to the end of the array |
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This can be replaced with a list comprehension, something like [mappings[x] for x in sequence]. List comprehensions are generally faster than for loops
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