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38 | 38 | }, |
39 | 39 | { |
40 | 40 | "cell_type": "code", |
41 | | - "execution_count": 5, |
| 41 | + "execution_count": 2, |
42 | 42 | "id": "f47af914-150a-4a57-8837-c12e14cb8802", |
43 | 43 | "metadata": {}, |
44 | 44 | "outputs": [], |
|
48 | 48 | }, |
49 | 49 | { |
50 | 50 | "cell_type": "code", |
51 | | - "execution_count": 2, |
| 51 | + "execution_count": 3, |
52 | 52 | "id": "c185164a-f1c6-483b-b013-f4d499889570", |
53 | 53 | "metadata": {}, |
54 | 54 | "outputs": [], |
|
93 | 93 | }, |
94 | 94 | { |
95 | 95 | "cell_type": "code", |
96 | | - "execution_count": 3, |
| 96 | + "execution_count": 4, |
97 | 97 | "id": "3733c540-de62-45a0-ba66-268397a38b49", |
98 | 98 | "metadata": {}, |
99 | 99 | "outputs": [], |
|
153 | 153 | }, |
154 | 154 | { |
155 | 155 | "cell_type": "code", |
156 | | - "execution_count": 4, |
| 156 | + "execution_count": 5, |
157 | 157 | "id": "08afcbcf-34a8-4450-a967-eb4ed5800ee1", |
158 | 158 | "metadata": {}, |
159 | 159 | "outputs": [], |
|
191 | 191 | "metadata": {}, |
192 | 192 | "outputs": [], |
193 | 193 | "source": [ |
194 | | - "def _generate_raw(legs:dict, allow_partial=True) -> None:\n", |
| 194 | + "def _generate_raw(legs:dict) -> None:\n", |
195 | 195 | " \"\"\"\n", |
196 | 196 | " Write out all legs found and their DG values, or indicate that they have failed.\n", |
197 | 197 | "\n", |
198 | 198 | " Parameters\n", |
199 | 199 | " ----------\n", |
200 | 200 | " legs : dict\n", |
201 | 201 | " Dict of legs to write out.\n", |
202 | | - " allow_partial : bool, optional\n", |
203 | | - " Unused for this function, since all results will be included.\n", |
204 | 202 | " \"\"\"\n", |
205 | 203 | " data = []\n", |
206 | 204 | " for ligpair, results in sorted(legs.items()):\n", |
|
230 | 228 | "metadata": {}, |
231 | 229 | "outputs": [], |
232 | 230 | "source": [ |
233 | | - "def _generate_ddg(legs:dict, allow_partial:bool) -> None:\n", |
| 231 | + "def _generate_ddg(legs:dict) -> None:\n", |
234 | 232 | " \"\"\"Compute and write out DDG values for the given legs.\n", |
235 | 233 | "\n", |
236 | 234 | " Parameters\n", |
237 | 235 | " ----------\n", |
238 | 236 | " legs : dict\n", |
239 | 237 | " Dict of legs to write out.\n", |
240 | | - " allow_partial : bool\n", |
241 | | - " If ``True``, no error will be thrown for incomplete or invalid results,\n", |
242 | | - " and DDGs will be reported for whatever valid results are found.\n", |
243 | 238 | " \"\"\"\n", |
244 | 239 | " data = []\n", |
245 | 240 | " for ligpair, results in sorted(legs.items()):\n", |
|
265 | 260 | "metadata": {}, |
266 | 261 | "outputs": [], |
267 | 262 | "source": [ |
268 | | - "def _generate_dg_mle(legs: dict, allow_partial: bool) -> None:\n", |
| 263 | + "def _generate_dg_mle(legs: dict) -> None:\n", |
269 | 264 | " \"\"\"Compute and write out DG values for the given legs.\n", |
270 | 265 | "\n", |
271 | 266 | " Parameters\n", |
272 | 267 | " ----------\n", |
273 | 268 | " legs : dict\n", |
274 | 269 | " Dict of legs to write out.\n", |
275 | | - " allow_partial : bool\n", |
276 | | - " If ``True``, no error will be thrown for incomplete or invalid results,\n", |
277 | | - " and DGs will be reported for whatever valid results are found.\n", |
278 | 270 | " \"\"\"\n", |
279 | 271 | " import networkx as nx\n", |
280 | 272 | " import numpy as np\n", |
281 | 273 | " from cinnabar.stats import mle\n", |
282 | 274 | "\n", |
283 | | - " DDGs = _generate_ddg(legs, allow_partial=allow_partial)\n", |
| 275 | + " DDGs = _generate_ddg(legs)\n", |
284 | 276 | " MLEs = []\n", |
285 | 277 | " expected_ligs = []\n", |
286 | 278 | "\n", |
|
417 | 409 | "metadata": {}, |
418 | 410 | "outputs": [], |
419 | 411 | "source": [ |
420 | | - "df_ddg = _generate_ddg(ddgs, allow_partial=True)\n", |
| 412 | + "df_ddg = _generate_ddg(ddgs)\n", |
421 | 413 | "df_ddg.to_csv('ddg.tsv', sep=\"\\t\", lineterminator=\"\\n\", index=False)" |
422 | 414 | ] |
423 | 415 | }, |
|
519 | 511 | "metadata": {}, |
520 | 512 | "outputs": [], |
521 | 513 | "source": [ |
522 | | - "df_dg = _generate_dg_mle(ddgs, allow_partial=True)\n", |
| 514 | + "df_dg = _generate_dg_mle(ddgs)\n", |
523 | 515 | "df_dg.to_csv('dg.tsv', sep=\"\\t\", lineterminator=\"\\n\", index=False)" |
524 | 516 | ] |
525 | 517 | }, |
|
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