Added para datasource to database, modified calling method of database

pyat/DataBase.py

@@ -33,7 +33,7 @@ class DataBase():
     """
     获取数据库中的剖面信息
     """
-    def __init__(self,ETOPO1path,STpath):
+    def __init__(self,ETOPO1path,STpath,dataSource):
         # 打开ETOPO1数据
         fileETOPO1 = ETOPO1path+'/ETOPO1_Bed_g_gmt4.nc'
         dataETOPO1 = Dataset(fileETOPO1)

pyat/czcore.py

@@ -277,22 +277,16 @@ def call_fangwei(freq, sd, rd, bathm, ssp, sed, base, isPlot=False):
         czdetail.reflectCz = []
     return Pos.r.range, Pos.r.depth, TL[0, 0, :, :], bathm, Rays, czdetail
 
-def call_cz(ETOPO1Path, STPath, freq, lat, lon, azi, sourceDepth=10, receiveDepth=10, timeType='Annual', isPlot=False):
+def call_cz(database, freq, lat, lon, azi, sourceDepth=10, receiveDepth=10, isPlot=False):
     sd = np.array([sourceDepth])  # Source depth
     rd = np.linspace(0, receiveDepth, 351)  # Receiving depth
-    # 定义时间段
-    timeIndex = timeType
-    # 创建类
-    data = DataBase(ETOPO1Path, STPath)
-    # 设置时间段
-    data.set_timePeriod(timeIndex)
 
     results = []
     ranges, depths, TL, bathym, Rays = [], [], [], [], []
 
     ''' 计算单个方向的会聚区 '''
     if azi != None:
-        [bathm, ssp, sed, base] = GetEnv(data, 25, Coord(lon, lat), R=100, azi=azi)
+        [bathm, ssp, sed, base] = GetEnv(database, 25, Coord(lon, lat), R=100, azi=azi)
         if np.mean(bathm.d) < 2000:
             return results
         else:
@@ -302,7 +296,7 @@ def call_cz(ETOPO1Path, STPath, freq, lat, lon, azi, sourceDepth=10, receiveDept
             return results
 
     ''' 计算8个方向的会聚区 '''
-    [bathm, ssp, sed, base] = GetEnv(data, 25, Coord(lon, lat), R=100, azi=0)
+    [bathm, ssp, sed, base] = GetEnv(database, 25, Coord(lon, lat), R=100, azi=0)
     if bathm.d[0] < 2000:
         # file_cz_data.write("各个方位都不会出现会聚区")
         return results
@@ -310,7 +304,7 @@ def call_cz(ETOPO1Path, STPath, freq, lat, lon, azi, sourceDepth=10, receiveDept
         descripts = ["正北方向", "东北方向", "正东方向", "东南方向", "正南方向", "西南方向", "正西方向", "西北方向"]
         theta = np.arange(0, 359, 45)
         for i in range(8):
-            [bathm, ssp, sed, base] = GetEnv(data, 25, Coord(lon, lat), R=100, azi=theta[i])
+            [bathm, ssp, sed, base] = GetEnv(database, 25, Coord(lon, lat), R=100, azi=theta[i])
             if np.mean(bathm.d) < 2000:
                 # 不会出现会聚区
                 continue

pyat/tlcore.py

@@ -6,8 +6,8 @@ from pyat.krakenc import call_krakenc
 from pyat.ram import call_ram
 import matplotlib.pyplot as plt
 
-def call_tl(ETOPO1Path, STPath, freq, sourceDepth, sourceLat, sourceLon, receiveDepth,
- receiveLat=None, receiveLon=None, range=None, azi=None, timeType='Annual', modelType='kraken', isPlot=False):
+def call_tl(database, freq, sourceDepth, sourceLat, sourceLon, receiveDepth,
+ receiveLat=None, receiveLon=None, range=None, azi=None, modelType='kraken', isPlot=False):
     """ Input:
     freq - float, Frequency
     sourceDepth - float, Source depth
@@ -29,18 +29,12 @@ def call_tl(ETOPO1Path, STPath, freq, sourceDepth, sourceLat, sourceLon, receive
     TL 传播损失
     bathym类 地形数据 bathym.r距离 bathym.d深度
     """
-    # 定义时间段
-    timeIndex = timeType
-    # 创建类
-    data = DataBase(ETOPO1Path, STPath)
-    # 设置时间段
-    data.set_timePeriod(timeIndex)
 
     bathym, ssp, sed, base = [], [], [], []
     if (receiveLat != None) and (receiveLon != None):
-        [bathym, ssp, sed, base] = GetEnv(data, 25, Coord(sourceLon, sourceLat), coordR=Coord(receiveLon, receiveLat))
+        [bathym, ssp, sed, base] = GetEnv(database, 25, Coord(sourceLon, sourceLat), coordR=Coord(receiveLon, receiveLat))
     elif (range != None) and (azi != None):
-        [bathym, ssp, sed, base] = GetEnv(data, 25, Coord(sourceLon, sourceLat), R=range, azi=azi)
+        [bathym, ssp, sed, base] = GetEnv(database, 25, Coord(sourceLon, sourceLat), R=range, azi=azi)
     else:
         print('no receive info!')
         return [], [], [], bathym