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3
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1 from __future__ import print_function
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2
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3 import gzip
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4 import logging
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5 import os
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6 import shutil
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7 import subprocess
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8 import tempfile
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9 import json
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10
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11 import pysam
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12 from bx.seq.twobit import TWOBIT_MAGIC_NUMBER, TWOBIT_MAGIC_NUMBER_SWAP, TWOBIT_MAGIC_SIZE
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13
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14 from galaxy.datatypes import metadata
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15 from galaxy.datatypes.metadata import DictParameter, ListParameter, MetadataElement, MetadataParameter
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16
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17 from binary import Binary
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18 from text import Json
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19
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20 log = logging.getLogger(__name__)
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21
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22 class pppmodel(Json):
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23 file_ext = ".model"
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24 #edam_format = "format_3746"
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25
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26 MetadataElement(name="models", default=[], desc="Models", param=MetadataParameter, readonly=True, visible=False, optional=True, no_value=[])
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27 MetadataElement(name="npop_dict", default={}, desc="Model population count", param=MetadataParameter, readonly=True, visible=False, optional=True, no_value={})
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28
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29 # Update as format becomes more defined
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30 def set_peek(self, dataset, is_multi_byte=False):
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31 if not dataset.dataset.purged:
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32 dataset.blurb = "Model File"
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33
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34 # Update as format becomes more defined
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35 '''
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36 def sniff(self, filename):
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37 try:
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38 json.loads(filename.file_name)
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39 return True
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40 except Exception:
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41 return False
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42 '''
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43
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44 def set_meta(self, dataset, **kwd):
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45 if dataset.has_data():
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46 with open(dataset.file_name) as model_file:
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47 try:
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48 model_list = json.load(model_file)
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49 except Exception:
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50 return
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51
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52 # Assign models
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53 models = [model_dict['name'] for model_dict in model_list if 'name' in model_dict]
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54
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55 # Assign population count per model
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56 npop_dict = dict([(model_dict['name'], len(model_dict['pops'])) for model_dict in model_list if 'name' in model_dict])
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57
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58 dataset.metadata.models = models
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59 dataset.metadata.npop_dict = npop_dict
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