Mock Data Updates #447
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Mock Data Updates #447
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JackWilb
requested changes
Oct 16, 2025
| elif hgb < 8: rbc_units = random.randint(0, 2) | ||
| elif hgb < 9 and random.random() < 0.4: rbc_units = 1 | ||
| elif hgb < 10 and random.random() < 0.25: rbc_units = 1 | ||
| rbc_units = min(rbc_units, 6) |
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| transfusion_events = [ | ||
| (datetime.strptime(lab["lab_draw_dtm"], DATE_FORMAT), lab) | ||
| for lab in v_labs | ||
| if (not has_surg or datetime.strptime(lab["lab_draw_dtm"], DATE_FORMAT) <= datetime.strptime(surg["surgery_end_dtm"], DATE_FORMAT)) | ||
| and ( | ||
| (score := ( | ||
| (max(0, 10 - float(lab["result_value"])) if lab["result_desc"] in ("HGB", "Hemoglobin") else 0) + | ||
| (max(0, float(lab["result_value"]) - 1) if lab["result_desc"] == "INR" else 0) + | ||
| (max(0, (150000 - float(lab["result_value"])) / 50000) if lab["result_desc"] in ("PLT", "Platelet Count") else 0) + | ||
| (max(0, (150 - float(lab["result_value"])) / 50) if lab["result_desc"] == "Fibrinogen" else 0) | ||
| )) > 0.5 and random.random() < min(0.9, 0.1 + score/12) | ||
| ) | ||
| ] | ||
| # Extra chance for intra-op/trauma transfusion event | ||
| if has_surg and random.random() < 0.1: | ||
| mid_surg = datetime.strptime(surg["surgery_start_dtm"], DATE_FORMAT) + timedelta(minutes=random.randint(30, int(surg_len*60-10))) | ||
| transfusion_events.append((mid_surg, None)) | ||
| if has_surg and (("Emergent" in surg_type or "Trauma" in surg_type or surg_len > 4) and random.random() < 0.2): | ||
| mid_surg = datetime.strptime(surg["surgery_start_dtm"], DATE_FORMAT) + timedelta(minutes=random.randint(10, int(surg_len*60-10))) | ||
| transfusion_events.append((mid_surg, None)) | ||
| # Limit to 1–3 transfusion events per visit | ||
| if transfusion_events: | ||
| transfusion_events = random.sample(transfusion_events, min(len(transfusion_events), random.choices([1,2,3],[0.8,0.1,0.05])[0])) |
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Refactor or comment this. Why is this clinically relevant?
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Does this PR close any open issues?
Closes #305
Give a longer description of what this PR addresses and why it's needed
recreatedata.pyfor recreating data (combiningmigrate,mock50million,generate_parquets)Provide pictures/videos of the behavior before and after these changes (optional)
Have you added or updated relevant tests?
Have you added or updated relevant documentation?
Are there any additional TODOs before this PR is ready to go?
N/A