Mercurial > repos > iuc > table_compute

comparison scripts/table_compute.py @ 2:02c3e335a695 draft

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"planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/table_compute commit d00a518202228b990aeeea2ec3f842501fd2ec09"
author iuc
date Fri, 13 Sep 2019 14:54:41 -0400
parents dddadbbac949
children 93a3ce78ce55
comparison
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1:dddadbbac949 2:02c3e335a695
2 """ 2 """
3 Table Compute tool - a wrapper around pandas with parameter input validation. 3 Table Compute tool - a wrapper around pandas with parameter input validation.
4 """ 4 """
5 5
6 6
7 __version__ = "0.9.1" 7 __version__ = "0.9.2"
8 8
9 import csv 9 import csv
10 import math 10 import math
11 from sys import argv 11 from sys import argv
12 12
263 263
264 # Get the main processing mode 264 # Get the main processing mode
265 mode = params["element_mode"] 265 mode = params["element_mode"]
266 if mode == "replace": 266 if mode == "replace":
267 replacement_val = params["element_replace"] 267 replacement_val = params["element_replace"]
268 out_table = data.mask(bool_mat, replacement_val) 268 out_table = data.mask(
269 bool_mat,
270 data.where(bool_mat).applymap(
271 lambda x: replacement_val.format(elem=x)
272 )
273 )
269 elif mode == "modify": 274 elif mode == "modify":
270 mod_op = Utils.getOneValueMathOp(params["element_modify_op"]) 275 mod_op = Utils.getOneValueMathOp(params["element_modify_op"])
271 out_table = data.mask( 276 out_table = data.mask(
272 bool_mat, data.where(bool_mat).applymap(mod_op) 277 bool_mat, data.where(bool_mat).applymap(mod_op)
273 ) 278 )
298 exit(-1) 303 exit(-1)
299 304
300 elif user_mode_single == "fulltable": 305 elif user_mode_single == "fulltable":
301 general_mode = params["mode"] 306 general_mode = params["mode"]
302 307
303 if general_mode == "melt": 308 if general_mode == "transpose":
309 out_table = data.T
310 elif general_mode == "melt":
304 melt_ids = params["MELT"]["melt_ids"] 311 melt_ids = params["MELT"]["melt_ids"]
305 melt_values = params["MELT"]["melt_values"] 312 melt_values = params["MELT"]["melt_values"]
306 313
307 out_table = pd.melt(data, id_vars=melt_ids, value_vars=melt_values) 314 out_table = pd.melt(data, id_vars=melt_ids, value_vars=melt_values)
308 elif general_mode == "pivot": 315 elif general_mode == "pivot":