minor change

get_result_web.py

@@ -0,0 +1,85 @@
+import json
+import os
+
+import numpy as np
+import pandas as pd
+from tqdm import tqdm
+
+from dance.utils import try_import
+
+# os.environ["http_proxy"]="http://121.250.209.147:7890"
+# os.environ["https_proxy"]="http://121.250.209.147:7890"
+wandb = try_import("wandb")
+entity = "xzy11632"
+project = "dance-dev"
+collect_datasets = {
+    "cta_actinn": [
+        "84230ea4-998d-4aa8-8456-81dd54ce23af", "d3566d6a-a455-4a15-980f-45eb29114cab",
+        "4c4cd77c-8fee-4836-9145-16562a8782fe", "ae29ebd0-1973-40a4-a6af-d15a5f77a80f",
+        "bc260987-8ee5-4b6e-8773-72805166b3f7", "bc2a7b3d-f04e-477e-96c9-9d5367d5425c",
+        "d9b4bc69-ed90-4f5f-99b2-61b0681ba436"
+    ],
+    "cta_celltypist": [
+        "4c4cd77c-8fee-4836-9145-16562a8782fe", "ae29ebd0-1973-40a4-a6af-d15a5f77a80f",
+        "bc260987-8ee5-4b6e-8773-72805166b3f7", "bc2a7b3d-f04e-477e-96c9-9d5367d5425c",
+        "d9b4bc69-ed90-4f5f-99b2-61b0681ba436", "01209dce-3575-4bed-b1df-129f57fbc031",
+        "055ca631-6ffb-40de-815e-b931e10718c0", "2a498ace-872a-4935-984b-1afa70fd9886",
+        "2adb1f8a-a6b1-4909-8ee8-484814e2d4bf", "3faad104-2ab8-4434-816d-474d8d2641db"
+    ],
+    "cta_singlecellnet": [
+        "4c4cd77c-8fee-4836-9145-16562a8782fe", "ae29ebd0-1973-40a4-a6af-d15a5f77a80f",
+        "bc260987-8ee5-4b6e-8773-72805166b3f7", "bc2a7b3d-f04e-477e-96c9-9d5367d5425c",
+        "d9b4bc69-ed90-4f5f-99b2-61b0681ba436", "01209dce-3575-4bed-b1df-129f57fbc031",
+        "055ca631-6ffb-40de-815e-b931e10718c0", "2a498ace-872a-4935-984b-1afa70fd9886",
+        "2adb1f8a-a6b1-4909-8ee8-484814e2d4bf", "3faad104-2ab8-4434-816d-474d8d2641db"
+    ]
+}
+file_root = "/home/zyxing/dance/examples/tuning"
+
+
+def check_identical_strings(string_list):
+    if not string_list:
+        raise ValueError("列表为空")
+
+    arr = np.array(string_list)
+    if not np.all(arr == arr[0]):
+        raise ValueError("发现不同的字符串")
+
+    return string_list[0]
+
+
+    # if not string_list:
+    #     raise ValueError("列表为空")
+    # first_string = string_list[0]
+    # for s in string_list[1:]:
+    #     if s != first_string:
+    #         raise ValueError(f"发现不同的字符串: '{first_string}' 和 '{s}'")
+    # return first_string
+def get_sweep_url(step_csv: pd.DataFrame):
+    ids = step_csv["id"]
+    sweep_urls = []
+    for run_id in tqdm(ids, leave=False):
+        api = wandb.Api()
+        run = api.run(f"/{entity}/{project}/runs/{run_id}")
+        sweep_urls.append(run.sweep.url)
+    sweep_url = check_identical_strings(sweep_urls)
+    return sweep_url
+
+
+def write_ans():
+    ans = []
+    for method_folder in tqdm(collect_datasets):
+        for dataset_id in collect_datasets[method_folder]:
+            file_path = f"{file_root}/{method_folder}/{dataset_id}/results"
+            step2_url = get_sweep_url(pd.read_csv(f"{file_path}/pipeline/best_test_acc.csv"))
+            step3_urls = []
+            for i in range(3):
+                step3_urls.append(get_sweep_url(pd.read_csv(f"{file_path}/params/{i}_best_test_acc.csv")))
+            step3_str = ",".join(step3_urls)
+            step_str = f"step2:{step2_url}|step3:{step3_str}"
+            ans.append({"Dataset_id": dataset_id, method_folder: step_str})
+    with open('temp_ans.json', 'w') as f:
+        json.dump(ans, f)
+
+
+write_ans()