Mercurial > repos > bgruening > sklearn_sample_generator
annotate association_rules.py @ 42:daf580dc95da draft
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
author | bgruening |
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date | Wed, 09 Aug 2023 13:01:51 +0000 |
parents | 7f8fa89929e0 |
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0f460421b212
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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1 import argparse |
0f460421b212
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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2 import json |
0f460421b212
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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3 import warnings |
0f460421b212
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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4 |
0f460421b212
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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5 import pandas as pd |
0f460421b212
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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6 from mlxtend.frequent_patterns import association_rules, fpgrowth |
0f460421b212
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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7 from mlxtend.preprocessing import TransactionEncoder |
0f460421b212
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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8 |
0f460421b212
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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9 |
41
7f8fa89929e0
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
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10 def main( |
7f8fa89929e0
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
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11 inputs, |
7f8fa89929e0
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
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12 infile, |
7f8fa89929e0
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
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13 outfile, |
7f8fa89929e0
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
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14 min_support=0.5, |
7f8fa89929e0
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
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15 min_confidence=0.5, |
7f8fa89929e0
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
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16 min_lift=1.0, |
7f8fa89929e0
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
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17 min_conviction=1.0, |
7f8fa89929e0
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
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18 max_length=None, |
7f8fa89929e0
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
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19 ): |
37
0f460421b212
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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20 """ |
0f460421b212
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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21 Parameter |
0f460421b212
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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22 --------- |
0f460421b212
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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23 input : str |
0f460421b212
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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24 File path to galaxy tool parameter |
0f460421b212
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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25 |
0f460421b212
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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26 infile : str |
0f460421b212
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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27 File paths of input vector |
0f460421b212
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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28 |
0f460421b212
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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29 outfile : str |
0f460421b212
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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30 File path to output matrix |
0f460421b212
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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31 |
0f460421b212
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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32 min_support: float |
0f460421b212
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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33 Minimum support |
0f460421b212
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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34 |
0f460421b212
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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35 min_confidence: float |
0f460421b212
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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36 Minimum confidence |
0f460421b212
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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37 |
0f460421b212
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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38 min_lift: float |
0f460421b212
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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39 Minimum lift |
0f460421b212
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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40 |
0f460421b212
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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41 min_conviction: float |
0f460421b212
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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42 Minimum conviction |
0f460421b212
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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43 |
0f460421b212
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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44 max_length: int |
0f460421b212
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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45 Maximum length |
0f460421b212
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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46 |
0f460421b212
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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47 """ |
41
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
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48 warnings.simplefilter("ignore") |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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49 |
41
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
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50 with open(inputs, "r") as param_handler: |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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51 params = json.load(param_handler) |
0f460421b212
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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52 |
41
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
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53 input_header = params["header0"] |
7f8fa89929e0
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
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54 header = "infer" if input_header else None |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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55 |
0f460421b212
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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56 with open(infile) as fp: |
0f460421b212
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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57 lines = fp.read().splitlines() |
0f460421b212
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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58 |
0f460421b212
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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59 if header is not None: |
0f460421b212
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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60 lines = lines[1:] |
0f460421b212
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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61 |
0f460421b212
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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62 dataset = [] |
0f460421b212
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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63 for line in lines: |
0f460421b212
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64 line_items = line.split("\t") |
0f460421b212
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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65 dataset.append(line_items) |
0f460421b212
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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66 |
0f460421b212
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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67 # TransactionEncoder learns the unique labels in the dataset and transforms the |
0f460421b212
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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68 # input dataset (a Python list of lists) into a one-hot encoded NumPy boolean array |
0f460421b212
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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69 te = TransactionEncoder() |
0f460421b212
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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70 te_ary = te.fit_transform(dataset) |
0f460421b212
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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71 |
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72 # Turn the encoded NumPy array into a DataFrame |
0f460421b212
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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73 df = pd.DataFrame(te_ary, columns=te.columns_) |
0f460421b212
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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74 |
0f460421b212
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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75 # Extract frequent itemsets for association rule mining |
0f460421b212
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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76 # use_colnames: Use DataFrames' column names in the returned DataFrame instead of column indices |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
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77 frequent_itemsets = fpgrowth( |
7f8fa89929e0
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
parents:
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78 df, min_support=min_support, use_colnames=True, max_len=max_length |
7f8fa89929e0
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
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79 ) |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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80 |
0f460421b212
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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81 # Get association rules, with confidence larger than min_confidence |
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82 rules = association_rules( |
7f8fa89929e0
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
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83 frequent_itemsets, metric="confidence", min_threshold=min_confidence |
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84 ) |
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85 |
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86 # Filter association rules, keeping rules with lift and conviction larger than min_liftand and min_conviction |
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87 rules = rules[(rules["lift"] >= min_lift) & (rules["conviction"] >= min_conviction)] |
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88 |
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89 # Convert columns from frozenset to list (more readable) |
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90 rules["antecedents"] = rules["antecedents"].apply(list) |
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91 rules["consequents"] = rules["consequents"].apply(list) |
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92 |
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93 # The next 3 steps are intended to fix the order of the association |
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94 # rules generated, so tests that rely on diff'ing a desired output |
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95 # with an expected output can pass |
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96 |
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97 # 1) Sort entry in every row/column for columns 'antecedents' and 'consequents' |
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98 rules["antecedents"] = rules["antecedents"].apply(lambda row: sorted(row)) |
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99 rules["consequents"] = rules["consequents"].apply(lambda row: sorted(row)) |
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100 |
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101 # 2) Create two temporary string columns to sort on |
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102 rules["ant_str"] = rules["antecedents"].apply(lambda row: " ".join(row)) |
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103 rules["con_str"] = rules["consequents"].apply(lambda row: " ".join(row)) |
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104 |
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105 # 3) Sort results so they are re-producable |
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106 rules.sort_values(by=["ant_str", "con_str"], inplace=True) |
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107 del rules["ant_str"] |
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108 del rules["con_str"] |
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109 rules.reset_index(drop=True, inplace=True) |
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110 |
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111 # Write association rules and metrics to file |
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112 rules.to_csv(outfile, sep="\t", index=False) |
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113 |
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114 |
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115 if __name__ == "__main__": |
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116 aparser = argparse.ArgumentParser() |
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117 aparser.add_argument("-i", "--inputs", dest="inputs", required=True) |
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118 aparser.add_argument("-y", "--infile", dest="infile", required=True) |
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119 aparser.add_argument("-o", "--outfile", dest="outfile", required=True) |
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120 aparser.add_argument("-s", "--support", dest="support", default=0.5) |
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121 aparser.add_argument("-c", "--confidence", dest="confidence", default=0.5) |
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122 aparser.add_argument("-l", "--lift", dest="lift", default=1.0) |
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123 aparser.add_argument("-v", "--conviction", dest="conviction", default=1.0) |
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124 aparser.add_argument("-t", "--length", dest="length", default=5) |
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125 args = aparser.parse_args() |
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126 |
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127 main( |
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128 args.inputs, |
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129 args.infile, |
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130 args.outfile, |
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131 min_support=float(args.support), |
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132 min_confidence=float(args.confidence), |
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133 min_lift=float(args.lift), |
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134 min_conviction=float(args.conviction), |
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135 max_length=int(args.length), |
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136 ) |