refactor ptimizing_parameterso

docs/source/intro/optimizing_parameters.rst

@@ -4,50 +4,10 @@
 通过 RQAlpha 进行参数调优
 ==================
 
-通过命令行传递参数
-====================================
-
-.. code-block:: python
-
-    import os
-    import json
-    import concurrent.futures
-    import multiprocessing
-
-
-    tasks = []
-    for short_period in range(3, 10, 2):
-	for long_period in range(30, 90, 5):
-	    extra_vars = {
-		"SHORTPERIOD": short_period,
-		"LONGPERIOD": long_period,
-	    }
-	    vars_params = json.dumps(extra_vars).encode("utf-8").decode("utf-8")
-
-	    cmd = ("rqalpha run -fq 1d -f rqalpha/examples/golden_cross.py --start-date 2015-01-01 --end-date 2016-01-01 "
-		   "-o results/out-{short_period}-{long_period}.pkl -sc 100000 --progress -bm 000001.XSHE --extra-vars '{params}' ").format(
-		       short_period=short_period,
-		       long_period=long_period,
-		       params=vars_params)
-
-	    tasks.append(cmd)
-
-
-    def run_bt(cmd):
-	print(cmd)
-	os.system(cmd)
-
-
-    with concurrent.futures.ProcessPoolExecutor(max_workers=multiprocessing.cpu_count()) as executor:
-	for task in tasks:
-	    executor.submit(run_bt, task)
-
 
 通过函数调用传递参数
 ====================================
 
-TBD
-
 .. code-block:: python
 
     import concurrent.futures
@@ -104,6 +64,46 @@ TBD
 
 
 
+通过命令行传递参数
+====================================
+
+.. code-block:: python
+
+    import os
+    import json
+    import concurrent.futures
+    import multiprocessing
+
+
+    tasks = []
+    for short_period in range(3, 10, 2):
+	for long_period in range(30, 90, 5):
+	    extra_vars = {
+		"SHORTPERIOD": short_period,
+		"LONGPERIOD": long_period,
+	    }
+	    vars_params = json.dumps(extra_vars).encode("utf-8").decode("utf-8")
+
+	    cmd = ("rqalpha run -fq 1d -f rqalpha/examples/golden_cross.py --start-date 2015-01-01 --end-date 2016-01-01 "
+		   "-o results/out-{short_period}-{long_period}.pkl -sc 100000 --progress -bm 000001.XSHE --extra-vars '{params}' ").format(
+		       short_period=short_period,
+		       long_period=long_period,
+		       params=vars_params)
+
+	    tasks.append(cmd)
+
+
+    def run_bt(cmd):
+	print(cmd)
+	os.system(cmd)
+
+
+    with concurrent.futures.ProcessPoolExecutor(max_workers=multiprocessing.cpu_count()) as executor:
+	for task in tasks:
+	    executor.submit(run_bt, task)
+
+
+
 分析批量回测结果
 ====================================