From e5bcb0faccf67f213538cad3670a8d1378c56ce7 Mon Sep 17 00:00:00 2001
From: BonfaceKilz
Date: Mon, 8 Mar 2021 15:22:26 +0300
Subject: Remove "/k-gwa-computation"

---
 gn3/api/gemma.py | 58 --------------------------------------------------------
 1 file changed, 58 deletions(-)

(limited to 'gn3/api')

diff --git a/gn3/api/gemma.py b/gn3/api/gemma.py
index ed698d3..21c4cf5 100644
--- a/gn3/api/gemma.py
+++ b/gn3/api/gemma.py
@@ -26,64 +26,6 @@ def get_version():
     return jsonify(run_cmd(f"{gemma_cmd} -v | head -n 1"))
 
 
-# This is basically extracted from genenetwork2
-# wqflask/wqflask/marker_regression/gemma_ampping.py
-@gemma.route("/k-gwa-computation", methods=["POST"])
-def run_gemma():
-    """Generates a command for generating K-Values and then later, generate a GWA
-command that contains markers. These commands are queued; and the expected
-file output is returned.
-
-    """
-    data = request.get_json()
-    app_defaults = current_app.config
-    __hash = generate_hash_of_string(f"{data.get('genofile_name')}_"
-                                     ''.join(data.get("values", "")))
-    gemma_kwargs = {
-        "geno_filename":
-        os.path.join(app_defaults.get("GENODIR"), "bimbam",
-                     f"{data.get('geno_filename')}"),
-        "trait_filename":
-        generate_pheno_txt_file(
-            tmpdir=app_defaults.get("TMPDIR"),
-            values=data.get("values"),
-            # Generate this file on the fly!
-            trait_filename=(f"{data.get('dataset_groupname')}_"
-                            f"{data.get('trait_name')}_"
-                            f"{__hash}.txt"))
-    }
-    gemma_wrapper_kwargs = {}
-    if data.get("loco"):
-        gemma_wrapper_kwargs["loco"] = f"--input {data.get('loco')}"
-    k_computation_cmd = generate_gemma_computation_cmd(
-        gemma_cmd=app_defaults.get("GEMMA_WRAPPER_CMD"),
-        gemma_wrapper_kwargs={"loco": f"--input {data.get('loco')}"},
-        gemma_kwargs=gemma_kwargs,
-        output_file=(f"{app_defaults.get('TMPDIR')}/gn2/"
-                     f"{data.get('dataset_name')}_K_"
-                     f"{__hash}.json"))
-    gemma_kwargs["lmm"] = data.get("lmm", 9)
-    gemma_wrapper_kwargs["input"] = (f"{data.get('dataset_name')}_K_"
-                                     f"{__hash}.json")
-    gwa_cmd = generate_gemma_computation_cmd(
-        gemma_wrapper_kwargs=gemma_wrapper_kwargs,
-        gemma_cmd=app_defaults.get("GEMMA_WRAPPER_CMD"),
-        gemma_kwargs=gemma_kwargs,
-        output_file=(f"{data.get('dataset_name')}_GWA_"
-                     f"{__hash}.txt"))
-    if not all([k_computation_cmd, gwa_cmd]):
-        return jsonify(status=128,
-                       error="Unable to generate cmds for computation!"), 500
-    return jsonify(unique_id=queue_cmd(
-        conn=redis.Redis(),
-        email=data.get("email"),
-        job_queue=app_defaults.get("REDIS_JOB_QUEUE"),
-        cmd=f"{k_computation_cmd} && {gwa_cmd}"),
-                   status="queued",
-                   output_file=(f"{data.get('dataset_name')}_GWA_"
-                                f"{__hash}.txt"))
-
-
 @gemma.route("/status/<unique_id>", methods=["GET"])
 def check_cmd_status(unique_id):
     """Given a (url-encoded) UNIQUE-ID which is returned when hitting any of the
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