Spaces:
Running
Running
Update code/app.py
Browse filesupdate for mobile responsiveness
- code/app.py +848 -873
code/app.py
CHANGED
@@ -1,873 +1,848 @@
|
|
1 |
-
import panel as pn
|
2 |
-
import pandas as pd
|
3 |
-
import param
|
4 |
-
from bokeh.models.formatters import PrintfTickFormatter
|
5 |
-
|
6 |
-
|
7 |
-
|
8 |
-
|
9 |
-
|
10 |
-
|
11 |
-
|
12 |
-
|
13 |
-
|
14 |
-
|
15 |
-
|
16 |
-
|
17 |
-
|
18 |
-
|
19 |
-
|
20 |
-
|
21 |
-
|
22 |
-
|
23 |
-
|
24 |
-
|
25 |
-
return pn.widgets.tables.NumberFormatter(format="0
|
26 |
-
elif format_str == "%.
|
27 |
-
return pn.widgets.tables.NumberFormatter(format="0.
|
28 |
-
elif format_str == "%.
|
29 |
-
return pn.widgets.tables.NumberFormatter(format="0.
|
30 |
-
elif format_str == "
|
31 |
-
return pn.widgets.tables.NumberFormatter(format="
|
32 |
-
|
33 |
-
|
34 |
-
|
35 |
-
|
36 |
-
|
37 |
-
|
38 |
-
|
39 |
-
|
40 |
-
|
41 |
-
|
42 |
-
|
43 |
-
|
44 |
-
|
45 |
-
|
46 |
-
|
47 |
-
|
48 |
-
|
49 |
-
|
50 |
-
|
51 |
-
|
52 |
-
|
53 |
-
|
54 |
-
|
55 |
-
|
56 |
-
|
57 |
-
|
58 |
-
|
59 |
-
|
60 |
-
|
61 |
-
|
62 |
-
|
63 |
-
|
64 |
-
|
65 |
-
|
66 |
-
|
67 |
-
|
68 |
-
|
69 |
-
|
70 |
-
|
71 |
-
|
72 |
-
|
73 |
-
|
74 |
-
|
75 |
-
|
76 |
-
|
77 |
-
|
78 |
-
|
79 |
-
|
80 |
-
|
81 |
-
|
82 |
-
|
83 |
-
|
84 |
-
|
85 |
-
|
86 |
-
|
87 |
-
|
88 |
-
|
89 |
-
|
90 |
-
|
91 |
-
|
92 |
-
|
93 |
-
|
94 |
-
|
95 |
-
|
96 |
-
|
97 |
-
|
98 |
-
|
99 |
-
|
100 |
-
|
101 |
-
|
102 |
-
|
103 |
-
|
104 |
-
|
105 |
-
|
106 |
-
|
107 |
-
|
108 |
-
|
109 |
-
|
110 |
-
|
111 |
-
|
112 |
-
|
113 |
-
|
114 |
-
|
115 |
-
|
116 |
-
|
117 |
-
|
118 |
-
|
119 |
-
|
120 |
-
|
121 |
-
|
122 |
-
|
123 |
-
|
124 |
-
|
125 |
-
|
126 |
-
|
127 |
-
|
128 |
-
|
129 |
-
|
130 |
-
|
131 |
-
|
132 |
-
|
133 |
-
|
134 |
-
|
135 |
-
|
136 |
-
|
137 |
-
|
138 |
-
|
139 |
-
|
140 |
-
|
141 |
-
|
142 |
-
|
143 |
-
|
144 |
-
|
145 |
-
|
146 |
-
|
147 |
-
|
148 |
-
|
149 |
-
|
150 |
-
|
151 |
-
|
152 |
-
|
153 |
-
|
154 |
-
|
155 |
-
|
156 |
-
|
157 |
-
|
158 |
-
|
159 |
-
|
160 |
-
|
161 |
-
|
162 |
-
|
163 |
-
|
164 |
-
|
165 |
-
|
166 |
-
|
167 |
-
|
168 |
-
|
169 |
-
|
170 |
-
|
171 |
-
|
172 |
-
|
173 |
-
|
174 |
-
|
175 |
-
|
176 |
-
|
177 |
-
|
178 |
-
|
179 |
-
|
180 |
-
|
181 |
-
|
182 |
-
|
183 |
-
|
184 |
-
|
185 |
-
|
186 |
-
|
187 |
-
|
188 |
-
|
189 |
-
|
190 |
-
|
191 |
-
|
192 |
-
|
193 |
-
|
194 |
-
|
195 |
-
|
196 |
-
|
197 |
-
|
198 |
-
|
199 |
-
|
200 |
-
|
201 |
-
|
202 |
-
|
203 |
-
|
204 |
-
|
205 |
-
|
206 |
-
|
207 |
-
|
208 |
-
|
209 |
-
|
210 |
-
|
211 |
-
|
212 |
-
|
213 |
-
|
214 |
-
|
215 |
-
|
216 |
-
|
217 |
-
|
218 |
-
|
219 |
-
|
220 |
-
|
221 |
-
|
222 |
-
|
223 |
-
|
224 |
-
|
225 |
-
|
226 |
-
|
227 |
-
|
228 |
-
|
229 |
-
|
230 |
-
|
231 |
-
|
232 |
-
|
233 |
-
|
234 |
-
|
235 |
-
|
236 |
-
|
237 |
-
|
238 |
-
|
239 |
-
|
240 |
-
|
241 |
-
|
242 |
-
|
243 |
-
|
244 |
-
|
245 |
-
|
246 |
-
|
247 |
-
|
248 |
-
|
249 |
-
|
250 |
-
|
251 |
-
|
252 |
-
|
253 |
-
|
254 |
-
|
255 |
-
|
256 |
-
|
257 |
-
|
258 |
-
|
259 |
-
|
260 |
-
|
261 |
-
|
262 |
-
|
263 |
-
|
264 |
-
|
265 |
-
|
266 |
-
|
267 |
-
|
268 |
-
|
269 |
-
|
270 |
-
|
271 |
-
|
272 |
-
|
273 |
-
|
274 |
-
|
275 |
-
|
276 |
-
|
277 |
-
|
278 |
-
|
279 |
-
|
280 |
-
|
281 |
-
|
282 |
-
|
283 |
-
|
284 |
-
|
285 |
-
|
286 |
-
|
287 |
-
|
288 |
-
|
289 |
-
|
290 |
-
|
291 |
-
|
292 |
-
|
293 |
-
|
294 |
-
|
295 |
-
|
296 |
-
|
297 |
-
|
298 |
-
|
299 |
-
|
300 |
-
|
301 |
-
|
302 |
-
|
303 |
-
|
304 |
-
|
305 |
-
|
306 |
-
|
307 |
-
|
308 |
-
|
309 |
-
|
310 |
-
|
311 |
-
|
312 |
-
|
313 |
-
|
314 |
-
self.param.
|
315 |
-
|
316 |
-
|
317 |
-
|
318 |
-
|
319 |
-
|
320 |
-
|
321 |
-
|
322 |
-
|
323 |
-
|
324 |
-
self.param.
|
325 |
-
|
326 |
-
|
327 |
-
|
328 |
-
|
329 |
-
|
330 |
-
|
331 |
-
|
332 |
-
|
333 |
-
|
334 |
-
self.param.
|
335 |
-
|
336 |
-
|
337 |
-
|
338 |
-
|
339 |
-
|
340 |
-
|
341 |
-
|
342 |
-
|
343 |
-
|
344 |
-
self.param.
|
345 |
-
|
346 |
-
|
347 |
-
|
348 |
-
|
349 |
-
|
350 |
-
|
351 |
-
|
352 |
-
|
353 |
-
|
354 |
-
self.param.
|
355 |
-
|
356 |
-
|
357 |
-
|
358 |
-
|
359 |
-
|
360 |
-
|
361 |
-
|
362 |
-
|
363 |
-
|
364 |
-
self.param.
|
365 |
-
|
366 |
-
|
367 |
-
|
368 |
-
|
369 |
-
|
370 |
-
|
371 |
-
|
372 |
-
|
373 |
-
|
374 |
-
self.param.
|
375 |
-
|
376 |
-
|
377 |
-
|
378 |
-
|
379 |
-
|
380 |
-
|
381 |
-
|
382 |
-
|
383 |
-
|
384 |
-
self.param.
|
385 |
-
|
386 |
-
|
387 |
-
|
388 |
-
|
389 |
-
|
390 |
-
|
391 |
-
|
392 |
-
|
393 |
-
|
394 |
-
|
395 |
-
|
396 |
-
|
397 |
-
|
398 |
-
|
399 |
-
|
400 |
-
|
401 |
-
|
402 |
-
|
403 |
-
|
404 |
-
|
405 |
-
|
406 |
-
|
407 |
-
|
408 |
-
|
409 |
-
|
410 |
-
|
411 |
-
|
412 |
-
|
413 |
-
|
414 |
-
|
415 |
-
|
416 |
-
|
417 |
-
|
418 |
-
|
419 |
-
|
420 |
-
|
421 |
-
|
422 |
-
|
423 |
-
|
424 |
-
|
425 |
-
|
426 |
-
|
427 |
-
|
428 |
-
|
429 |
-
|
430 |
-
|
431 |
-
|
432 |
-
|
433 |
-
|
434 |
-
|
435 |
-
|
436 |
-
|
437 |
-
|
438 |
-
|
439 |
-
|
440 |
-
|
441 |
-
|
442 |
-
|
443 |
-
|
444 |
-
|
445 |
-
|
446 |
-
|
447 |
-
|
448 |
-
|
449 |
-
|
450 |
-
|
451 |
-
|
452 |
-
|
453 |
-
|
454 |
-
|
455 |
-
|
456 |
-
|
457 |
-
|
458 |
-
|
459 |
-
|
460 |
-
"
|
461 |
-
"
|
462 |
-
"
|
463 |
-
"
|
464 |
-
"
|
465 |
-
"
|
466 |
-
|
467 |
-
|
468 |
-
|
469 |
-
|
470 |
-
|
471 |
-
|
472 |
-
|
473 |
-
|
474 |
-
|
475 |
-
|
476 |
-
|
477 |
-
|
478 |
-
|
479 |
-
|
480 |
-
|
481 |
-
|
482 |
-
|
483 |
-
|
484 |
-
|
485 |
-
|
486 |
-
|
487 |
-
|
488 |
-
|
489 |
-
|
490 |
-
|
491 |
-
|
492 |
-
self.
|
493 |
-
|
494 |
-
|
495 |
-
|
496 |
-
|
497 |
-
|
498 |
-
|
499 |
-
|
500 |
-
|
501 |
-
|
502 |
-
|
503 |
-
|
504 |
-
|
505 |
-
|
506 |
-
)
|
507 |
-
|
508 |
-
|
509 |
-
|
510 |
-
|
511 |
-
|
512 |
-
|
513 |
-
|
514 |
-
|
515 |
-
|
516 |
-
|
517 |
-
|
518 |
-
|
519 |
-
|
520 |
-
|
521 |
-
|
522 |
-
|
523 |
-
|
524 |
-
|
525 |
-
|
526 |
-
|
527 |
-
self.
|
528 |
-
|
529 |
-
|
530 |
-
|
531 |
-
|
532 |
-
|
533 |
-
|
534 |
-
|
535 |
-
|
536 |
-
self.
|
537 |
-
|
538 |
-
|
539 |
-
|
540 |
-
|
541 |
-
|
542 |
-
|
543 |
-
self.
|
544 |
-
|
545 |
-
|
546 |
-
|
547 |
-
|
548 |
-
|
549 |
-
|
550 |
-
|
551 |
-
|
552 |
-
|
553 |
-
|
554 |
-
|
555 |
-
|
556 |
-
|
557 |
-
|
558 |
-
|
559 |
-
|
560 |
-
|
561 |
-
|
562 |
-
)
|
563 |
-
|
564 |
-
|
565 |
-
|
566 |
-
|
567 |
-
|
568 |
-
|
569 |
-
|
570 |
-
self.
|
571 |
-
self.
|
572 |
-
|
573 |
-
|
574 |
-
|
575 |
-
|
576 |
-
self.
|
577 |
-
|
578 |
-
|
579 |
-
|
580 |
-
|
581 |
-
|
582 |
-
|
583 |
-
|
584 |
-
|
585 |
-
|
586 |
-
self.
|
587 |
-
|
588 |
-
|
589 |
-
|
590 |
-
|
591 |
-
|
592 |
-
|
593 |
-
self.
|
594 |
-
|
595 |
-
|
596 |
-
|
597 |
-
|
598 |
-
|
599 |
-
|
600 |
-
|
601 |
-
|
602 |
-
|
603 |
-
|
604 |
-
|
605 |
-
|
606 |
-
|
607 |
-
|
608 |
-
|
609 |
-
self.
|
610 |
-
self.
|
611 |
-
self.
|
612 |
-
|
613 |
-
|
614 |
-
self.
|
615 |
-
self.
|
616 |
-
|
617 |
-
|
618 |
-
|
619 |
-
|
620 |
-
|
621 |
-
|
622 |
-
|
623 |
-
|
624 |
-
|
625 |
-
|
626 |
-
|
627 |
-
|
628 |
-
|
629 |
-
|
630 |
-
|
631 |
-
|
632 |
-
|
633 |
-
|
634 |
-
|
635 |
-
|
636 |
-
|
637 |
-
|
638 |
-
|
639 |
-
|
640 |
-
self.
|
641 |
-
self.
|
642 |
-
|
643 |
-
|
644 |
-
|
645 |
-
|
646 |
-
self.
|
647 |
-
self.
|
648 |
-
|
649 |
-
|
650 |
-
|
651 |
-
|
652 |
-
|
653 |
-
|
654 |
-
|
655 |
-
|
656 |
-
|
657 |
-
|
658 |
-
|
659 |
-
|
660 |
-
|
661 |
-
|
662 |
-
|
663 |
-
|
664 |
-
|
665 |
-
|
666 |
-
|
667 |
-
|
668 |
-
|
669 |
-
|
670 |
-
|
671 |
-
|
672 |
-
|
673 |
-
|
674 |
-
"
|
675 |
-
"
|
676 |
-
"
|
677 |
-
|
678 |
-
|
679 |
-
|
680 |
-
|
681 |
-
|
682 |
-
|
683 |
-
|
684 |
-
self.
|
685 |
-
|
686 |
-
|
687 |
-
|
688 |
-
|
689 |
-
|
690 |
-
"Per Shift":
|
691 |
-
|
692 |
-
|
693 |
-
|
694 |
-
|
695 |
-
|
696 |
-
|
697 |
-
|
698 |
-
|
699 |
-
|
700 |
-
|
701 |
-
|
702 |
-
|
703 |
-
|
704 |
-
|
705 |
-
|
706 |
-
|
707 |
-
),
|
708 |
-
|
709 |
-
|
710 |
-
|
711 |
-
|
712 |
-
|
713 |
-
|
714 |
-
|
715 |
-
|
716 |
-
|
717 |
-
|
718 |
-
|
719 |
-
|
720 |
-
|
721 |
-
pn.
|
722 |
-
|
723 |
-
|
724 |
-
|
725 |
-
|
726 |
-
|
727 |
-
|
728 |
-
pn.
|
729 |
-
|
730 |
-
|
731 |
-
|
732 |
-
|
733 |
-
|
734 |
-
|
735 |
-
|
736 |
-
|
737 |
-
|
738 |
-
|
739 |
-
|
740 |
-
|
741 |
-
|
742 |
-
|
743 |
-
),
|
744 |
-
|
745 |
-
|
746 |
-
|
747 |
-
|
748 |
-
|
749 |
-
|
750 |
-
|
751 |
-
),
|
752 |
-
|
753 |
-
|
754 |
-
|
755 |
-
|
756 |
-
|
757 |
-
|
758 |
-
|
759 |
-
pn.
|
760 |
-
|
761 |
-
|
762 |
-
|
763 |
-
|
764 |
-
|
765 |
-
|
766 |
-
|
767 |
-
|
768 |
-
pn.pane.Markdown("
|
769 |
-
|
770 |
-
|
771 |
-
|
772 |
-
|
773 |
-
|
774 |
-
|
775 |
-
|
776 |
-
|
777 |
-
|
778 |
-
|
779 |
-
|
780 |
-
|
781 |
-
|
782 |
-
|
783 |
-
|
784 |
-
|
785 |
-
|
786 |
-
|
787 |
-
|
788 |
-
|
789 |
-
|
790 |
-
|
791 |
-
|
792 |
-
|
793 |
-
)
|
794 |
-
|
795 |
-
|
796 |
-
pn.pane.Markdown(
|
797 |
-
|
798 |
-
|
799 |
-
|
800 |
-
)
|
801 |
-
|
802 |
-
|
803 |
-
|
804 |
-
self.
|
805 |
-
|
806 |
-
|
807 |
-
|
808 |
-
|
809 |
-
|
810 |
-
|
811 |
-
|
812 |
-
|
813 |
-
|
814 |
-
|
815 |
-
|
816 |
-
|
817 |
-
|
818 |
-
|
819 |
-
|
820 |
-
|
821 |
-
|
822 |
-
|
823 |
-
|
824 |
-
|
825 |
-
|
826 |
-
|
827 |
-
|
828 |
-
|
829 |
-
|
830 |
-
|
831 |
-
|
832 |
-
|
833 |
-
|
834 |
-
|
835 |
-
|
836 |
-
|
837 |
-
|
838 |
-
|
839 |
-
|
840 |
-
|
841 |
-
|
842 |
-
|
843 |
-
|
844 |
-
|
845 |
-
|
846 |
-
|
847 |
-
|
848 |
-
|
849 |
-
return main_layout
|
850 |
-
|
851 |
-
|
852 |
-
estimator_app = CannabinoidEstimator()
|
853 |
-
# To run in a Panel server:
|
854 |
-
# pn.config.raw_css = custom_themes.get_base_css(custom_themes.DARK_THEME_VARS)
|
855 |
-
estimator_app.view().servable(title="CBx Revenue Estimator")
|
856 |
-
|
857 |
-
# Instantiate the template with widgets displayed in the sidebar
|
858 |
-
# template = pn.template.FastListTemplate(
|
859 |
-
# title="CBx Revenue Estimator (FastList Panel)",
|
860 |
-
# #theme = custom_themes.DarkTheme,
|
861 |
-
# #sidebar=[freq, phase],
|
862 |
-
# )
|
863 |
-
|
864 |
-
# template.main.append(estimator_app.view())
|
865 |
-
# template.servable()
|
866 |
-
|
867 |
-
if __name__ == "__main__":
|
868 |
-
pn.serve(
|
869 |
-
estimator_app.view(),
|
870 |
-
title="CBx Revenue Estimator (Panel)",
|
871 |
-
show=True,
|
872 |
-
port=5007,
|
873 |
-
)
|
|
|
1 |
+
import panel as pn
|
2 |
+
import pandas as pd
|
3 |
+
import param
|
4 |
+
from bokeh.models.formatters import PrintfTickFormatter
|
5 |
+
# from custom_themes import AIDefaultTheme, AIDarkTheme
|
6 |
+
|
7 |
+
|
8 |
+
# Initialize Panel extension for Tabulator and set a global sizing mode
|
9 |
+
pn.extension(
|
10 |
+
"tabulator",
|
11 |
+
sizing_mode="stretch_width",
|
12 |
+
template="fast",
|
13 |
+
# theme = AIDarkTheme,
|
14 |
+
)
|
15 |
+
|
16 |
+
# --- Styling Placeholders (as per user instruction) ---
|
17 |
+
slider_design = {}
|
18 |
+
slider_style = {}
|
19 |
+
slider_stylesheet = []
|
20 |
+
|
21 |
+
|
22 |
+
# --- Helper for NumberFormatters ---
|
23 |
+
def get_formatter(format_str):
|
24 |
+
if format_str == "%i":
|
25 |
+
return pn.widgets.tables.NumberFormatter(format="0")
|
26 |
+
elif format_str == "%.1f":
|
27 |
+
return pn.widgets.tables.NumberFormatter(format="0.0")
|
28 |
+
elif format_str == "%.2f":
|
29 |
+
return pn.widgets.tables.NumberFormatter(format="0.00")
|
30 |
+
elif format_str == "%.4f":
|
31 |
+
return pn.widgets.tables.NumberFormatter(format="0.0000")
|
32 |
+
elif format_str == "$%.02f":
|
33 |
+
return pn.widgets.tables.NumberFormatter(format="$0,0.00")
|
34 |
+
return format_str
|
35 |
+
|
36 |
+
|
37 |
+
class CannabinoidEstimator(param.Parameterized):
|
38 |
+
# --- Input Parameters ---
|
39 |
+
kg_processed_per_hour = param.Number(
|
40 |
+
default=150.0,
|
41 |
+
bounds=(0, 2000),
|
42 |
+
step=1.0,
|
43 |
+
label="Biomass processed per hour (kg)",
|
44 |
+
)
|
45 |
+
finished_product_yield_pct = param.Number(
|
46 |
+
default=60.0,
|
47 |
+
bounds=(0.01, 100),
|
48 |
+
step=0.01,
|
49 |
+
label="Product yield: CBx Weight Output / Weight Input (%)",
|
50 |
+
)
|
51 |
+
kwh_rate = param.Number(
|
52 |
+
default=0.25, bounds=(0.01, 5), step=0.01, label="Power rate ($ per kWh)"
|
53 |
+
)
|
54 |
+
water_cost_per_1000l = param.Number(
|
55 |
+
default=2.50,
|
56 |
+
bounds=(0.01, 10),
|
57 |
+
step=0.01,
|
58 |
+
label="Water rate ($ per 1000L / m3)",
|
59 |
+
)
|
60 |
+
consumables_per_kg_bio_rate = param.Number(
|
61 |
+
default=0.0032,
|
62 |
+
bounds=(0, 10),
|
63 |
+
step=0.0001,
|
64 |
+
label="Other Consumables rate ($ per kg biomass)",
|
65 |
+
)
|
66 |
+
kwh_per_kg_bio = param.Number(
|
67 |
+
default=0.25,
|
68 |
+
bounds=(0.05, 15),
|
69 |
+
step=0.01,
|
70 |
+
label="Power consumption (kWh per kg biomass)",
|
71 |
+
)
|
72 |
+
water_liters_consumed_per_kg_bio = param.Number(
|
73 |
+
default=3.0,
|
74 |
+
bounds=(0.1, 100),
|
75 |
+
step=0.1,
|
76 |
+
label="Water consumption (liters per kg biomass)",
|
77 |
+
)
|
78 |
+
consumables_per_kg_output = param.Number(
|
79 |
+
default=10.0,
|
80 |
+
bounds=(0, 100),
|
81 |
+
step=0.01,
|
82 |
+
label="Consumables per kg finished product ($)",
|
83 |
+
)
|
84 |
+
bio_cbx_pct = param.Number(
|
85 |
+
default=10.0, bounds=(0, 30), step=0.1, label="Cannabinoid (CBx) in biomass (%)"
|
86 |
+
)
|
87 |
+
bio_cost = param.Number(
|
88 |
+
default=3.0,
|
89 |
+
bounds=(0, 200),
|
90 |
+
step=0.25,
|
91 |
+
label="Biomass purchase cost ($ per kg)",
|
92 |
+
)
|
93 |
+
wholesale_cbx_price = param.Number(
|
94 |
+
default=220.0,
|
95 |
+
bounds=(25, 6000),
|
96 |
+
step=5.0,
|
97 |
+
label="Gross revenue ($ per kg output)",
|
98 |
+
)
|
99 |
+
wholesale_cbx_pct = param.Number(
|
100 |
+
default=99.9, bounds=(0, 100), step=0.01, label="CBx in finished product (%)"
|
101 |
+
)
|
102 |
+
batch_test_cost = param.Number(
|
103 |
+
default=1300.0,
|
104 |
+
bounds=(100, 5000),
|
105 |
+
step=25.0,
|
106 |
+
label="Per-batch testing/compliance costs ($)",
|
107 |
+
)
|
108 |
+
fixed_overhead_per_week = param.Number(
|
109 |
+
default=2000.0, bounds=(0, 10000), step=1.0, label="Weekly fixed costs ($)"
|
110 |
+
)
|
111 |
+
workers_per_shift = param.Number(
|
112 |
+
default=9.0, bounds=(1, 20), step=1.0, label="Workers per shift"
|
113 |
+
)
|
114 |
+
worker_hourly_rate = param.Number(
|
115 |
+
default=5.0, bounds=(0.25, 50), step=0.25, label="Worker loaded pay rate ($/hr)"
|
116 |
+
)
|
117 |
+
managers_per_shift = param.Number(
|
118 |
+
default=1.0, bounds=(1, 10), step=1.0, label="Supervisors per shift"
|
119 |
+
)
|
120 |
+
manager_hourly_rate = param.Number(
|
121 |
+
default=10.0,
|
122 |
+
bounds=(5.0, 50),
|
123 |
+
step=0.25,
|
124 |
+
label="Supervisor loaded pay rate ($/hr)",
|
125 |
+
)
|
126 |
+
processing_hours_per_shift = param.Number(
|
127 |
+
default=7.0, bounds=(0.25, 8.0), step=0.25, label="Processing hours per shift"
|
128 |
+
)
|
129 |
+
labour_hours_per_shift = param.Number(
|
130 |
+
default=8.0, bounds=(6.0, 12), step=0.25, label="Labor hours per shift"
|
131 |
+
)
|
132 |
+
shifts_per_day = param.Number(
|
133 |
+
default=3.0, bounds=(1, 10), step=1.0, label="Shifts per day"
|
134 |
+
)
|
135 |
+
shifts_per_week = param.Number(
|
136 |
+
default=21.0, bounds=(1, 28), step=1.0, label="Shifts per week"
|
137 |
+
)
|
138 |
+
|
139 |
+
kg_processed_per_shift = 0.0
|
140 |
+
labour_cost_per_shift = 0.0
|
141 |
+
variable_cost_per_shift = 0.0
|
142 |
+
overhead_cost_per_shift = 0.0
|
143 |
+
saleable_kg_per_kg_bio = 0.0
|
144 |
+
saleable_kg_per_shift = 0.0
|
145 |
+
saleable_kg_per_day = 0.0
|
146 |
+
saleable_kg_per_week = 0.0
|
147 |
+
biomass_kg_per_saleable_kg = 0.0
|
148 |
+
internal_cogs_per_kg_bio = 0.0
|
149 |
+
internal_cogs_per_shift = 0.0
|
150 |
+
internal_cogs_per_day = 0.0
|
151 |
+
internal_cogs_per_week = 0.0
|
152 |
+
internal_cogs_per_kg_output = 0.0
|
153 |
+
biomass_cost_per_shift = 0.0
|
154 |
+
biomass_cost_per_day = 0.0
|
155 |
+
biomass_cost_per_week = 0.0
|
156 |
+
biomass_cost_per_kg_output = 0.0
|
157 |
+
gross_rev_per_kg_bio = 0.0
|
158 |
+
gross_rev_per_shift = 0.0
|
159 |
+
gross_rev_per_day = 0.0
|
160 |
+
gross_rev_per_week = 0.0
|
161 |
+
net_rev_per_kg_bio = 0.0
|
162 |
+
net_rev_per_shift = 0.0
|
163 |
+
net_rev_per_day = 0.0
|
164 |
+
net_rev_per_week = 0.0
|
165 |
+
net_rev_per_kg_output = 0.0
|
166 |
+
operating_profit_pct = 0.0
|
167 |
+
resin_spread_pct = 0.0
|
168 |
+
|
169 |
+
money_data_df = param.DataFrame(pd.DataFrame())
|
170 |
+
profit_data_df = param.DataFrame(pd.DataFrame())
|
171 |
+
processing_data_df = param.DataFrame(pd.DataFrame())
|
172 |
+
|
173 |
+
def __init__(self, **params):
|
174 |
+
super().__init__(**params)
|
175 |
+
self._create_sliders()
|
176 |
+
self.money_table = pn.widgets.Tabulator(
|
177 |
+
self.money_data_df,
|
178 |
+
formatters=self._get_money_formatters(),
|
179 |
+
disabled=True,
|
180 |
+
layout="fit_data",
|
181 |
+
sizing_mode="fixed",
|
182 |
+
align="center",
|
183 |
+
show_index=False, # Hide index column
|
184 |
+
text_align={
|
185 |
+
" ": "right",
|
186 |
+
"$/kg Biomass": "center",
|
187 |
+
"$/kg Output": "center",
|
188 |
+
"Per Shift": "center",
|
189 |
+
"Per Day": "center",
|
190 |
+
"Per Week": "center",
|
191 |
+
},
|
192 |
+
)
|
193 |
+
self.profit_table = pn.widgets.Tabulator(
|
194 |
+
self.profit_data_df,
|
195 |
+
disabled=True,
|
196 |
+
layout="fit_data_table",
|
197 |
+
sizing_mode="fixed",
|
198 |
+
align="center",
|
199 |
+
show_index=False, # Hide index column
|
200 |
+
text_align={
|
201 |
+
"Metric": "right",
|
202 |
+
"Value": "center",
|
203 |
+
},
|
204 |
+
)
|
205 |
+
self.processing_table = pn.widgets.Tabulator(
|
206 |
+
self.processing_data_df,
|
207 |
+
formatters={},
|
208 |
+
disabled=True,
|
209 |
+
layout="fit_data_table",
|
210 |
+
sizing_mode="fixed",
|
211 |
+
align="center",
|
212 |
+
show_index=False, # Hide index column
|
213 |
+
text_align={
|
214 |
+
"Metric (Per Shift)": "right",
|
215 |
+
"Value": "center",
|
216 |
+
},
|
217 |
+
)
|
218 |
+
self._update_calculations()
|
219 |
+
|
220 |
+
def _create_sliders(self):
|
221 |
+
self.kg_processed_per_hour_slider = pn.widgets.EditableFloatSlider.from_param(
|
222 |
+
self.param.kg_processed_per_hour,
|
223 |
+
name=self.param.kg_processed_per_hour.label,
|
224 |
+
fixed_start=self.param.kg_processed_per_hour.bounds[0],
|
225 |
+
fixed_end=self.param.kg_processed_per_hour.bounds[1],
|
226 |
+
design=slider_design,
|
227 |
+
styles=slider_style,
|
228 |
+
stylesheets=slider_stylesheet,
|
229 |
+
# format="0",
|
230 |
+
format=PrintfTickFormatter(format="%i kg"),
|
231 |
+
)
|
232 |
+
self.finished_product_yield_pct_slider = (
|
233 |
+
pn.widgets.EditableFloatSlider.from_param(
|
234 |
+
self.param.finished_product_yield_pct,
|
235 |
+
name=self.param.finished_product_yield_pct.label,
|
236 |
+
fixed_start=self.param.finished_product_yield_pct.bounds[0],
|
237 |
+
fixed_end=self.param.finished_product_yield_pct.bounds[1],
|
238 |
+
design=slider_design,
|
239 |
+
styles=slider_style,
|
240 |
+
stylesheets=slider_stylesheet,
|
241 |
+
format="0.00",
|
242 |
+
)
|
243 |
+
)
|
244 |
+
self.kwh_rate_slider = pn.widgets.EditableFloatSlider.from_param(
|
245 |
+
self.param.kwh_rate,
|
246 |
+
name=self.param.kwh_rate.label,
|
247 |
+
fixed_start=self.param.kwh_rate.bounds[0],
|
248 |
+
fixed_end=self.param.kwh_rate.bounds[1],
|
249 |
+
design=slider_design,
|
250 |
+
styles=slider_style,
|
251 |
+
stylesheets=slider_stylesheet,
|
252 |
+
format="0.00",
|
253 |
+
# format=PrintfTickFormatter(format='%.2f per kWh'),
|
254 |
+
)
|
255 |
+
self.water_cost_per_1000l_slider = pn.widgets.EditableFloatSlider.from_param(
|
256 |
+
self.param.water_cost_per_1000l,
|
257 |
+
name=self.param.water_cost_per_1000l.label,
|
258 |
+
fixed_start=self.param.water_cost_per_1000l.bounds[0],
|
259 |
+
fixed_end=self.param.water_cost_per_1000l.bounds[1],
|
260 |
+
design=slider_design,
|
261 |
+
styles=slider_style,
|
262 |
+
stylesheets=slider_stylesheet,
|
263 |
+
format="0.00",
|
264 |
+
)
|
265 |
+
self.consumables_per_kg_bio_rate_slider = (
|
266 |
+
pn.widgets.EditableFloatSlider.from_param(
|
267 |
+
self.param.consumables_per_kg_bio_rate,
|
268 |
+
name=self.param.consumables_per_kg_bio_rate.label,
|
269 |
+
fixed_start=self.param.consumables_per_kg_bio_rate.bounds[0],
|
270 |
+
fixed_end=self.param.consumables_per_kg_bio_rate.bounds[1],
|
271 |
+
design=slider_design,
|
272 |
+
styles=slider_style,
|
273 |
+
stylesheets=slider_stylesheet,
|
274 |
+
format="0.0000",
|
275 |
+
)
|
276 |
+
)
|
277 |
+
self.kwh_per_kg_bio_slider = pn.widgets.EditableFloatSlider.from_param(
|
278 |
+
self.param.kwh_per_kg_bio,
|
279 |
+
name=self.param.kwh_per_kg_bio.label,
|
280 |
+
fixed_start=self.param.kwh_per_kg_bio.bounds[0],
|
281 |
+
fixed_end=self.param.kwh_per_kg_bio.bounds[1],
|
282 |
+
design=slider_design,
|
283 |
+
styles=slider_style,
|
284 |
+
stylesheets=slider_stylesheet,
|
285 |
+
format="0.00",
|
286 |
+
)
|
287 |
+
self.water_liters_consumed_per_kg_bio_slider = (
|
288 |
+
pn.widgets.EditableFloatSlider.from_param(
|
289 |
+
self.param.water_liters_consumed_per_kg_bio,
|
290 |
+
name=self.param.water_liters_consumed_per_kg_bio.label,
|
291 |
+
fixed_start=self.param.water_liters_consumed_per_kg_bio.bounds[0],
|
292 |
+
fixed_end=self.param.water_liters_consumed_per_kg_bio.bounds[1],
|
293 |
+
design=slider_design,
|
294 |
+
styles=slider_style,
|
295 |
+
stylesheets=slider_stylesheet,
|
296 |
+
format="0.0",
|
297 |
+
)
|
298 |
+
)
|
299 |
+
self.consumables_per_kg_output_slider = (
|
300 |
+
pn.widgets.EditableFloatSlider.from_param(
|
301 |
+
self.param.consumables_per_kg_output,
|
302 |
+
name=self.param.consumables_per_kg_output.label,
|
303 |
+
fixed_start=self.param.consumables_per_kg_output.bounds[0],
|
304 |
+
fixed_end=self.param.consumables_per_kg_output.bounds[1],
|
305 |
+
design=slider_design,
|
306 |
+
styles=slider_style,
|
307 |
+
stylesheets=slider_stylesheet,
|
308 |
+
format="0.00",
|
309 |
+
)
|
310 |
+
)
|
311 |
+
self.bio_cbx_pct_slider = pn.widgets.EditableFloatSlider.from_param(
|
312 |
+
self.param.bio_cbx_pct,
|
313 |
+
name=self.param.bio_cbx_pct.label,
|
314 |
+
fixed_start=self.param.bio_cbx_pct.bounds[0],
|
315 |
+
fixed_end=self.param.bio_cbx_pct.bounds[1],
|
316 |
+
design=slider_design,
|
317 |
+
styles=slider_style,
|
318 |
+
stylesheets=slider_stylesheet,
|
319 |
+
format="0.0",
|
320 |
+
)
|
321 |
+
self.bio_cost_slider = pn.widgets.EditableFloatSlider.from_param(
|
322 |
+
self.param.bio_cost,
|
323 |
+
name=self.param.bio_cost.label,
|
324 |
+
fixed_start=self.param.bio_cost.bounds[0],
|
325 |
+
fixed_end=self.param.bio_cost.bounds[1],
|
326 |
+
design=slider_design,
|
327 |
+
styles=slider_style,
|
328 |
+
stylesheets=slider_stylesheet,
|
329 |
+
format="0.00",
|
330 |
+
)
|
331 |
+
self.wholesale_cbx_price_slider = pn.widgets.EditableFloatSlider.from_param(
|
332 |
+
self.param.wholesale_cbx_price,
|
333 |
+
name=self.param.wholesale_cbx_price.label,
|
334 |
+
fixed_start=self.param.wholesale_cbx_price.bounds[0],
|
335 |
+
fixed_end=self.param.wholesale_cbx_price.bounds[1],
|
336 |
+
design=slider_design,
|
337 |
+
styles=slider_style,
|
338 |
+
stylesheets=slider_stylesheet,
|
339 |
+
format="0",
|
340 |
+
)
|
341 |
+
self.wholesale_cbx_pct_slider = pn.widgets.EditableFloatSlider.from_param(
|
342 |
+
self.param.wholesale_cbx_pct,
|
343 |
+
name=self.param.wholesale_cbx_pct.label,
|
344 |
+
fixed_start=self.param.wholesale_cbx_pct.bounds[0],
|
345 |
+
fixed_end=self.param.wholesale_cbx_pct.bounds[1],
|
346 |
+
design=slider_design,
|
347 |
+
styles=slider_style,
|
348 |
+
stylesheets=slider_stylesheet,
|
349 |
+
format="0.00",
|
350 |
+
)
|
351 |
+
self.batch_test_cost_slider = pn.widgets.EditableFloatSlider.from_param(
|
352 |
+
self.param.batch_test_cost,
|
353 |
+
name=self.param.batch_test_cost.label,
|
354 |
+
fixed_start=self.param.batch_test_cost.bounds[0],
|
355 |
+
fixed_end=self.param.batch_test_cost.bounds[1],
|
356 |
+
design=slider_design,
|
357 |
+
styles=slider_style,
|
358 |
+
stylesheets=slider_stylesheet,
|
359 |
+
format="0",
|
360 |
+
)
|
361 |
+
self.fixed_overhead_per_week_slider = pn.widgets.EditableFloatSlider.from_param(
|
362 |
+
self.param.fixed_overhead_per_week,
|
363 |
+
name=self.param.fixed_overhead_per_week.label,
|
364 |
+
fixed_start=self.param.fixed_overhead_per_week.bounds[0],
|
365 |
+
fixed_end=self.param.fixed_overhead_per_week.bounds[1],
|
366 |
+
design=slider_design,
|
367 |
+
styles=slider_style,
|
368 |
+
stylesheets=slider_stylesheet,
|
369 |
+
format="0",
|
370 |
+
)
|
371 |
+
self.workers_per_shift_slider = pn.widgets.EditableFloatSlider.from_param(
|
372 |
+
self.param.workers_per_shift,
|
373 |
+
name=self.param.workers_per_shift.label,
|
374 |
+
fixed_start=self.param.workers_per_shift.bounds[0],
|
375 |
+
fixed_end=self.param.workers_per_shift.bounds[1],
|
376 |
+
design=slider_design,
|
377 |
+
styles=slider_style,
|
378 |
+
stylesheets=slider_stylesheet,
|
379 |
+
format="0",
|
380 |
+
)
|
381 |
+
self.worker_hourly_rate_slider = pn.widgets.EditableFloatSlider.from_param(
|
382 |
+
self.param.worker_hourly_rate,
|
383 |
+
name=self.param.worker_hourly_rate.label,
|
384 |
+
fixed_start=self.param.worker_hourly_rate.bounds[0],
|
385 |
+
fixed_end=self.param.worker_hourly_rate.bounds[1],
|
386 |
+
design=slider_design,
|
387 |
+
styles=slider_style,
|
388 |
+
stylesheets=slider_stylesheet,
|
389 |
+
format="0.00",
|
390 |
+
)
|
391 |
+
self.managers_per_shift_slider = pn.widgets.EditableFloatSlider.from_param(
|
392 |
+
self.param.managers_per_shift,
|
393 |
+
name=self.param.managers_per_shift.label,
|
394 |
+
fixed_start=self.param.managers_per_shift.bounds[0],
|
395 |
+
fixed_end=self.param.managers_per_shift.bounds[1],
|
396 |
+
design=slider_design,
|
397 |
+
styles=slider_style,
|
398 |
+
stylesheets=slider_stylesheet,
|
399 |
+
format="0",
|
400 |
+
)
|
401 |
+
self.manager_hourly_rate_slider = pn.widgets.EditableFloatSlider.from_param(
|
402 |
+
self.param.manager_hourly_rate,
|
403 |
+
name=self.param.manager_hourly_rate.label,
|
404 |
+
fixed_start=self.param.worker_hourly_rate.default, # Keeping original logic as per file
|
405 |
+
fixed_end=self.param.manager_hourly_rate.bounds[1],
|
406 |
+
design=slider_design,
|
407 |
+
styles=slider_style,
|
408 |
+
stylesheets=slider_stylesheet,
|
409 |
+
format="0.00",
|
410 |
+
)
|
411 |
+
|
412 |
+
self.labour_hours_per_shift_slider = pn.widgets.EditableFloatSlider.from_param(
|
413 |
+
self.param.labour_hours_per_shift,
|
414 |
+
name=self.param.labour_hours_per_shift.label,
|
415 |
+
fixed_start=self.param.labour_hours_per_shift.bounds[
|
416 |
+
0
|
417 |
+
], # Changed in previous request
|
418 |
+
fixed_end=self.param.labour_hours_per_shift.bounds[1],
|
419 |
+
design=slider_design,
|
420 |
+
styles=slider_style,
|
421 |
+
stylesheets=slider_stylesheet,
|
422 |
+
format="0.00",
|
423 |
+
)
|
424 |
+
|
425 |
+
self.processing_hours_per_shift_slider = (
|
426 |
+
pn.widgets.EditableFloatSlider.from_param(
|
427 |
+
self.param.processing_hours_per_shift,
|
428 |
+
name=self.param.processing_hours_per_shift.label,
|
429 |
+
fixed_start=self.param.processing_hours_per_shift.bounds[0],
|
430 |
+
fixed_end=self.labour_hours_per_shift, # Changed in previous request
|
431 |
+
design=slider_design,
|
432 |
+
styles=slider_style,
|
433 |
+
stylesheets=slider_stylesheet,
|
434 |
+
format="0.00",
|
435 |
+
)
|
436 |
+
)
|
437 |
+
|
438 |
+
self.shifts_per_day_slider = pn.widgets.EditableFloatSlider.from_param(
|
439 |
+
self.param.shifts_per_day,
|
440 |
+
name=self.param.shifts_per_day.label,
|
441 |
+
fixed_start=self.param.shifts_per_day.bounds[0],
|
442 |
+
fixed_end=self.param.shifts_per_day.bounds[1],
|
443 |
+
design=slider_design,
|
444 |
+
styles=slider_style,
|
445 |
+
stylesheets=slider_stylesheet,
|
446 |
+
format="0",
|
447 |
+
)
|
448 |
+
self.shifts_per_week_slider = pn.widgets.EditableFloatSlider.from_param(
|
449 |
+
self.param.shifts_per_week,
|
450 |
+
name=self.param.shifts_per_week.label,
|
451 |
+
fixed_start=self.param.shifts_per_week.bounds[0],
|
452 |
+
fixed_end=self.param.shifts_per_week.bounds[1],
|
453 |
+
design=slider_design,
|
454 |
+
styles=slider_style,
|
455 |
+
stylesheets=slider_stylesheet,
|
456 |
+
format="0",
|
457 |
+
)
|
458 |
+
|
459 |
+
@param.depends(
|
460 |
+
"kg_processed_per_hour",
|
461 |
+
"finished_product_yield_pct",
|
462 |
+
"kwh_rate",
|
463 |
+
"water_cost_per_1000l",
|
464 |
+
"consumables_per_kg_bio_rate",
|
465 |
+
"kwh_per_kg_bio",
|
466 |
+
"water_liters_consumed_per_kg_bio",
|
467 |
+
"consumables_per_kg_output",
|
468 |
+
"bio_cbx_pct",
|
469 |
+
"bio_cost",
|
470 |
+
"wholesale_cbx_price",
|
471 |
+
"wholesale_cbx_pct",
|
472 |
+
"batch_test_cost",
|
473 |
+
"fixed_overhead_per_week",
|
474 |
+
"workers_per_shift",
|
475 |
+
"worker_hourly_rate",
|
476 |
+
"managers_per_shift",
|
477 |
+
"manager_hourly_rate",
|
478 |
+
"labour_hours_per_shift",
|
479 |
+
"processing_hours_per_shift",
|
480 |
+
"shifts_per_day",
|
481 |
+
"shifts_per_week",
|
482 |
+
watch=True,
|
483 |
+
)
|
484 |
+
def _update_calculations(self, *events):
|
485 |
+
self.kg_processed_per_shift = (
|
486 |
+
self.processing_hours_per_shift * self.kg_processed_per_hour
|
487 |
+
)
|
488 |
+
if self.shifts_per_week == 0:
|
489 |
+
self.shifts_per_week = 1
|
490 |
+
|
491 |
+
self._calc_saleable_kg()
|
492 |
+
self._calc_biomass_cost()
|
493 |
+
self._calc_cogs()
|
494 |
+
self._calc_gross_revenue()
|
495 |
+
self._calc_net_revenue()
|
496 |
+
|
497 |
+
self.operating_profit_pct = (
|
498 |
+
(self.net_rev_per_kg_bio / self.gross_rev_per_kg_bio)
|
499 |
+
if self.gross_rev_per_kg_bio
|
500 |
+
else 0.0
|
501 |
+
)
|
502 |
+
self.resin_spread_pct = (
|
503 |
+
((self.gross_rev_per_kg_bio - self.bio_cost) / self.bio_cost)
|
504 |
+
if self.bio_cost
|
505 |
+
else 0.0
|
506 |
+
)
|
507 |
+
|
508 |
+
self._update_tables_data()
|
509 |
+
|
510 |
+
@param.depends("labour_hours_per_shift", watch=True)
|
511 |
+
def _update_processing_hours_slider_constraints(self):
|
512 |
+
new_max_processing_hours = self.labour_hours_per_shift
|
513 |
+
|
514 |
+
# Get the current lower bound of the processing_hours_per_shift parameter
|
515 |
+
current_min_processing_hours = self.param.processing_hours_per_shift.bounds[0]
|
516 |
+
|
517 |
+
# Update the bounds of the underlying param.Number object for processing_hours_per_shift
|
518 |
+
# This allows the parameter to accept values up to the new maximum
|
519 |
+
self.param.processing_hours_per_shift.bounds = (
|
520 |
+
current_min_processing_hours,
|
521 |
+
new_max_processing_hours,
|
522 |
+
)
|
523 |
+
|
524 |
+
# Ensure the slider widget has been created before trying to access it
|
525 |
+
if hasattr(self, "processing_hours_per_shift_slider"):
|
526 |
+
# Update the 'end' property of the slider widget
|
527 |
+
self.processing_hours_per_shift_slider.end = new_max_processing_hours
|
528 |
+
|
529 |
+
# If the current value of processing_hours_per_shift is now greater than
|
530 |
+
# the new maximum, adjust it to be the new maximum.
|
531 |
+
if self.processing_hours_per_shift > new_max_processing_hours:
|
532 |
+
self.processing_hours_per_shift = new_max_processing_hours
|
533 |
+
|
534 |
+
def _calc_cogs(self):
|
535 |
+
worker_cost = self.workers_per_shift * self.worker_hourly_rate
|
536 |
+
manager_cost = self.managers_per_shift * self.manager_hourly_rate
|
537 |
+
self.labour_cost_per_shift = (
|
538 |
+
worker_cost + manager_cost
|
539 |
+
) * self.labour_hours_per_shift
|
540 |
+
|
541 |
+
power_cost_per_kg = self.kwh_rate * self.kwh_per_kg_bio
|
542 |
+
water_cost_per_kg = (
|
543 |
+
self.water_cost_per_1000l / 1000.0
|
544 |
+
) * self.water_liters_consumed_per_kg_bio
|
545 |
+
total_variable_consumable_cost_per_kg = (
|
546 |
+
self.consumables_per_kg_bio_rate + power_cost_per_kg + water_cost_per_kg
|
547 |
+
)
|
548 |
+
self.variable_cost_per_shift = (
|
549 |
+
total_variable_consumable_cost_per_kg * self.kg_processed_per_shift
|
550 |
+
)
|
551 |
+
|
552 |
+
self.overhead_cost_per_shift = (
|
553 |
+
self.fixed_overhead_per_week / self.shifts_per_week
|
554 |
+
if self.shifts_per_week > 0
|
555 |
+
else 0.0
|
556 |
+
)
|
557 |
+
|
558 |
+
shift_cogs_before_output_specific = (
|
559 |
+
self.labour_cost_per_shift
|
560 |
+
+ self.variable_cost_per_shift
|
561 |
+
+ self.overhead_cost_per_shift
|
562 |
+
)
|
563 |
+
shift_output_specific_cogs = (
|
564 |
+
self.consumables_per_kg_output * self.saleable_kg_per_shift
|
565 |
+
)
|
566 |
+
|
567 |
+
self.internal_cogs_per_shift = (
|
568 |
+
shift_cogs_before_output_specific + shift_output_specific_cogs
|
569 |
+
)
|
570 |
+
self.internal_cogs_per_kg_bio = (
|
571 |
+
self.internal_cogs_per_shift / self.kg_processed_per_shift
|
572 |
+
if self.kg_processed_per_shift > 0
|
573 |
+
else 0.0
|
574 |
+
)
|
575 |
+
self.internal_cogs_per_day = self.internal_cogs_per_shift * self.shifts_per_day
|
576 |
+
self.internal_cogs_per_week = (
|
577 |
+
self.internal_cogs_per_shift * self.shifts_per_week
|
578 |
+
)
|
579 |
+
self.internal_cogs_per_kg_output = (
|
580 |
+
(self.internal_cogs_per_kg_bio * self.biomass_kg_per_saleable_kg)
|
581 |
+
if self.biomass_kg_per_saleable_kg != 0
|
582 |
+
else 0.0
|
583 |
+
)
|
584 |
+
|
585 |
+
def _calc_gross_revenue(self):
|
586 |
+
self.gross_rev_per_kg_bio = (
|
587 |
+
self.saleable_kg_per_kg_bio * self.wholesale_cbx_price
|
588 |
+
)
|
589 |
+
self.gross_rev_per_shift = (
|
590 |
+
self.gross_rev_per_kg_bio * self.kg_processed_per_shift
|
591 |
+
)
|
592 |
+
self.gross_rev_per_day = self.gross_rev_per_shift * self.shifts_per_day
|
593 |
+
self.gross_rev_per_week = self.gross_rev_per_shift * self.shifts_per_week
|
594 |
+
|
595 |
+
def _calc_net_revenue(self):
|
596 |
+
self.net_rev_per_kg_bio = (
|
597 |
+
self.gross_rev_per_kg_bio - self.internal_cogs_per_kg_bio - self.bio_cost
|
598 |
+
)
|
599 |
+
self.net_rev_per_shift = self.net_rev_per_kg_bio * self.kg_processed_per_shift
|
600 |
+
self.net_rev_per_day = self.net_rev_per_shift * self.shifts_per_day
|
601 |
+
self.net_rev_per_week = self.net_rev_per_shift * self.shifts_per_week
|
602 |
+
self.net_rev_per_kg_output = (
|
603 |
+
(self.biomass_kg_per_saleable_kg * self.net_rev_per_kg_bio)
|
604 |
+
if self.biomass_kg_per_saleable_kg != 0
|
605 |
+
else 0.0
|
606 |
+
)
|
607 |
+
|
608 |
+
def _calc_biomass_cost(self):
|
609 |
+
self.biomass_cost_per_shift = self.kg_processed_per_shift * self.bio_cost
|
610 |
+
self.biomass_cost_per_day = self.biomass_cost_per_shift * self.shifts_per_day
|
611 |
+
self.biomass_cost_per_week = self.biomass_cost_per_shift * self.shifts_per_week
|
612 |
+
|
613 |
+
def _calc_saleable_kg(self):
|
614 |
+
if self.wholesale_cbx_pct == 0:
|
615 |
+
self.saleable_kg_per_kg_bio = 0.0
|
616 |
+
else:
|
617 |
+
self.saleable_kg_per_kg_bio = (
|
618 |
+
(self.bio_cbx_pct / 100.0)
|
619 |
+
* (self.finished_product_yield_pct / 100.0)
|
620 |
+
/ (self.wholesale_cbx_pct / 100.0)
|
621 |
+
)
|
622 |
+
self.saleable_kg_per_shift = (
|
623 |
+
self.saleable_kg_per_kg_bio * self.kg_processed_per_shift
|
624 |
+
)
|
625 |
+
self.saleable_kg_per_day = self.saleable_kg_per_shift * self.shifts_per_day
|
626 |
+
self.saleable_kg_per_week = self.saleable_kg_per_shift * self.shifts_per_week
|
627 |
+
self.biomass_kg_per_saleable_kg = (
|
628 |
+
1 / self.saleable_kg_per_kg_bio if self.saleable_kg_per_kg_bio > 0 else 0.0
|
629 |
+
)
|
630 |
+
self.biomass_cost_per_kg_output = (
|
631 |
+
self.biomass_kg_per_saleable_kg * self.bio_cost
|
632 |
+
)
|
633 |
+
|
634 |
+
def _update_tables_data(self):
|
635 |
+
money_data_dict = {
|
636 |
+
" ": ["Biomass cost", "Processing cost", "Gross Revenue", "Net Revenue"],
|
637 |
+
"$/kg Biomass": [
|
638 |
+
self.bio_cost,
|
639 |
+
self.internal_cogs_per_kg_bio,
|
640 |
+
self.gross_rev_per_kg_bio,
|
641 |
+
self.net_rev_per_kg_bio,
|
642 |
+
],
|
643 |
+
"$/kg Output": [
|
644 |
+
self.biomass_cost_per_kg_output,
|
645 |
+
self.internal_cogs_per_kg_output,
|
646 |
+
self.wholesale_cbx_price,
|
647 |
+
self.net_rev_per_kg_output,
|
648 |
+
],
|
649 |
+
"Per Shift": [
|
650 |
+
self.biomass_cost_per_shift,
|
651 |
+
self.internal_cogs_per_shift,
|
652 |
+
self.gross_rev_per_shift,
|
653 |
+
self.net_rev_per_shift,
|
654 |
+
],
|
655 |
+
"Per Day": [
|
656 |
+
self.biomass_cost_per_day,
|
657 |
+
self.internal_cogs_per_day,
|
658 |
+
self.gross_rev_per_day,
|
659 |
+
self.net_rev_per_day,
|
660 |
+
],
|
661 |
+
"Per Week": [
|
662 |
+
self.biomass_cost_per_week,
|
663 |
+
self.internal_cogs_per_week,
|
664 |
+
self.gross_rev_per_week,
|
665 |
+
self.net_rev_per_week,
|
666 |
+
],
|
667 |
+
}
|
668 |
+
self.money_data_df = pd.DataFrame(money_data_dict)
|
669 |
+
if hasattr(self, "money_table"):
|
670 |
+
self.money_table.value = self.money_data_df
|
671 |
+
|
672 |
+
profit_data_dict = {
|
673 |
+
"Metric": ["Operating Profit", "Resin Spread"],
|
674 |
+
"Value": [
|
675 |
+
f"{self.operating_profit_pct * 100.0:.2f}%",
|
676 |
+
f"{self.resin_spread_pct * 100.0:.2f}%",
|
677 |
+
],
|
678 |
+
}
|
679 |
+
self.profit_data_df = pd.DataFrame(profit_data_dict)
|
680 |
+
if hasattr(self, "profit_table"):
|
681 |
+
self.profit_table.value = self.profit_data_df
|
682 |
+
|
683 |
+
processing_values_formatted = [
|
684 |
+
f"{self.kg_processed_per_shift:,.0f}",
|
685 |
+
f"${self.labour_cost_per_shift:,.2f}",
|
686 |
+
f"${self.variable_cost_per_shift:,.2f}",
|
687 |
+
f"${self.overhead_cost_per_shift:,.2f}",
|
688 |
+
]
|
689 |
+
processing_data_dict = {
|
690 |
+
"Metric (Per Shift)": [
|
691 |
+
"Kilograms Extracted",
|
692 |
+
"Labour Cost",
|
693 |
+
"Variable Cost",
|
694 |
+
"Overhead",
|
695 |
+
],
|
696 |
+
"Value": processing_values_formatted,
|
697 |
+
}
|
698 |
+
self.processing_data_df = pd.DataFrame(processing_data_dict)
|
699 |
+
if hasattr(self, "processing_table"):
|
700 |
+
self.processing_table.value = self.processing_data_df
|
701 |
+
|
702 |
+
def _get_money_formatters(self):
|
703 |
+
return {
|
704 |
+
"$/kg Biomass": get_formatter("$%.02f"),
|
705 |
+
"$/kg Output": get_formatter("$%.02f"),
|
706 |
+
"Per Shift": get_formatter("$%.02f"),
|
707 |
+
"Per Day": get_formatter("$%.02f"),
|
708 |
+
"Per Week": get_formatter("$%.02f"),
|
709 |
+
}
|
710 |
+
|
711 |
+
def view(self):
|
712 |
+
input_col_max_width = 400
|
713 |
+
col1 = pn.Column(
|
714 |
+
"### Extraction",
|
715 |
+
self.kg_processed_per_hour_slider,
|
716 |
+
self.finished_product_yield_pct_slider,
|
717 |
+
sizing_mode="stretch_width",
|
718 |
+
max_width=input_col_max_width,
|
719 |
+
)
|
720 |
+
col2 = pn.Column(
|
721 |
+
pn.pane.Markdown("### Biomass parameters"),
|
722 |
+
self.bio_cbx_pct_slider,
|
723 |
+
self.bio_cost_slider,
|
724 |
+
sizing_mode="stretch_width",
|
725 |
+
max_width=input_col_max_width,
|
726 |
+
)
|
727 |
+
col3 = pn.Column(
|
728 |
+
pn.pane.Markdown("### Consumable rates"),
|
729 |
+
self.kwh_rate_slider,
|
730 |
+
self.water_cost_per_1000l_slider,
|
731 |
+
self.consumables_per_kg_bio_rate_slider,
|
732 |
+
sizing_mode="stretch_width",
|
733 |
+
max_width=input_col_max_width,
|
734 |
+
)
|
735 |
+
col4 = pn.Column(
|
736 |
+
pn.pane.Markdown("### Wholesale details"),
|
737 |
+
self.wholesale_cbx_price_slider,
|
738 |
+
self.wholesale_cbx_pct_slider,
|
739 |
+
sizing_mode="stretch_width",
|
740 |
+
max_width=input_col_max_width,
|
741 |
+
)
|
742 |
+
col5 = pn.Column(
|
743 |
+
pn.pane.Markdown("### Variable costs"),
|
744 |
+
self.kwh_per_kg_bio_slider,
|
745 |
+
self.water_liters_consumed_per_kg_bio_slider,
|
746 |
+
self.consumables_per_kg_output_slider,
|
747 |
+
sizing_mode="stretch_width",
|
748 |
+
max_width=input_col_max_width,
|
749 |
+
)
|
750 |
+
col6 = pn.Column(
|
751 |
+
pn.pane.Markdown("### Compliance"),
|
752 |
+
self.batch_test_cost_slider,
|
753 |
+
pn.pane.Markdown("### Overhead"),
|
754 |
+
self.fixed_overhead_per_week_slider,
|
755 |
+
sizing_mode="stretch_width",
|
756 |
+
max_width=input_col_max_width,
|
757 |
+
)
|
758 |
+
col8 = pn.Column(
|
759 |
+
pn.pane.Markdown("### Worker Details"),
|
760 |
+
self.workers_per_shift_slider,
|
761 |
+
self.worker_hourly_rate_slider,
|
762 |
+
self.managers_per_shift_slider,
|
763 |
+
self.manager_hourly_rate_slider,
|
764 |
+
sizing_mode="stretch_width",
|
765 |
+
max_width=input_col_max_width,
|
766 |
+
)
|
767 |
+
col9 = pn.Column(
|
768 |
+
pn.pane.Markdown("### Shift details"),
|
769 |
+
self.labour_hours_per_shift_slider,
|
770 |
+
self.processing_hours_per_shift_slider,
|
771 |
+
self.shifts_per_day_slider,
|
772 |
+
self.shifts_per_week_slider,
|
773 |
+
sizing_mode="stretch_width",
|
774 |
+
max_width=input_col_max_width,
|
775 |
+
)
|
776 |
+
|
777 |
+
input_grid = pn.FlexBox(
|
778 |
+
col1, col2, col3, col4, col5, col8, col9, col6, align_content="normal"
|
779 |
+
)
|
780 |
+
|
781 |
+
money_table_display = pn.Column(
|
782 |
+
pn.pane.Markdown("### Financial Summary", styles={"text-align": "center"}),
|
783 |
+
self.money_table,
|
784 |
+
sizing_mode="stretch_width",
|
785 |
+
max_width=700,
|
786 |
+
)
|
787 |
+
|
788 |
+
profit_table_display = pn.Column(
|
789 |
+
pn.pane.Markdown("### Profitability", styles={"text-align": "center"}),
|
790 |
+
self.profit_table,
|
791 |
+
sizing_mode="stretch_width",
|
792 |
+
max_width=input_col_max_width,
|
793 |
+
)
|
794 |
+
|
795 |
+
processing_table_display = pn.Column(
|
796 |
+
pn.pane.Markdown("### Processing Summary", styles={"text-align": "center"}),
|
797 |
+
self.processing_table,
|
798 |
+
sizing_mode="stretch_width",
|
799 |
+
max_width=input_col_max_width,
|
800 |
+
)
|
801 |
+
|
802 |
+
profit_weekly = pn.indicators.Number(
|
803 |
+
name="Weekly Profit",
|
804 |
+
value=self.net_rev_per_week,
|
805 |
+
format=f"${self.net_rev_per_week / 1000:.0f} k",
|
806 |
+
default_color="green",
|
807 |
+
align="center",
|
808 |
+
)
|
809 |
+
|
810 |
+
profit_pct = pn.indicators.Number(
|
811 |
+
name="Operating Profit",
|
812 |
+
value=self.operating_profit_pct,
|
813 |
+
format=f"{self.operating_profit_pct * 100.0:.2f}%",
|
814 |
+
default_color="green",
|
815 |
+
align="center",
|
816 |
+
)
|
817 |
+
|
818 |
+
table_grid = pn.FlexBox(
|
819 |
+
profit_weekly,
|
820 |
+
profit_pct,
|
821 |
+
processing_table_display,
|
822 |
+
profit_table_display,
|
823 |
+
money_table_display,
|
824 |
+
align_content="normal",
|
825 |
+
)
|
826 |
+
|
827 |
+
main_layout = pn.Column(
|
828 |
+
input_grid,
|
829 |
+
pn.layout.Divider(margin=(10, 0)),
|
830 |
+
table_grid,
|
831 |
+
styles={"margin": "0px 10px"},
|
832 |
+
)
|
833 |
+
|
834 |
+
return main_layout
|
835 |
+
|
836 |
+
|
837 |
+
estimator_app = CannabinoidEstimator()
|
838 |
+
# To run in a Panel server:
|
839 |
+
# pn.config.raw_css = custom_themes.get_base_css(custom_themes.DARK_THEME_VARS)
|
840 |
+
estimator_app.view().servable(title="CBx Revenue Estimator")
|
841 |
+
|
842 |
+
if __name__ == "__main__":
|
843 |
+
pn.serve(
|
844 |
+
estimator_app.view(),
|
845 |
+
title="CBx Revenue Estimator (Panel)",
|
846 |
+
show=True,
|
847 |
+
port=5007,
|
848 |
+
)
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|