fixing np issues

mhpi · Feb 20, 2024 · a27af89 · a27af89
1 parent ecbd3ba
commit a27af89
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Showing 6 changed files with 13 additions and 11 deletions.
diff --git a/.gitignore b/.gitignore
@@ -2,3 +2,5 @@
 *__pycache__*
 *mypy_cache*
 output/
+.idea/
+hydroDL.egg-info/
diff --git a/example/PUR/testPUR-Reg.py b/example/PUR/testPUR-Reg.py
@@ -232,7 +232,7 @@
                 for k in range(len(filePathLst)):
                     filePath = filePathLst[k]
                     dataPred[:, :, k] = pd.read_csv(
-                        filePath, dtype=np.float64 header=None
+                        filePath, dtype=float, header=None
                     ).values
                 # transform back to the original observation
                 temppred = camels.transNormbyDic(

diff --git a/hydroDL/data/dbCsv.py b/hydroDL/data/dbCsv.py
@@ -109,7 +109,7 @@ def readDBinfo(*, rootDB, subset):
     indSub = dfSubset.values.flatten()
 
     crdFile = os.path.join(rootDB, rootName, "crd.csv")
-    crdRoot = pd.read_csv(crdFile, dtype=np.float64 header=None).values
+    crdRoot = pd.read_csv(crdFile, dtype=float, header=None).values
 
     indAll = np.arange(0, crdRoot.shape[0], dtype=np.int64)
     if np.array_equal(indSub, np.array([-1])):
@@ -162,7 +162,7 @@ def readDataTS(*, rootDB, rootName, indSub, indSkip, yrLst, fieldName):
         t1 = time.time()
         dataFile = os.path.join(rootDB, rootName, str(yr), fieldName + ".csv")
         dataTemp = pd.read_csv(
-            dataFile, dtype=np.float64 skiprows=indSkip, header=None
+            dataFile, dtype=float, skiprows=indSkip, header=None
         ).values
         k2 = k1 + dataTemp.shape[1]
         data[:, k1:k2] = dataTemp
@@ -176,7 +176,7 @@ def readDataConst(*, rootDB, rootName, indSub, indSkip, fieldName):
     # read data
     dataFile = os.path.join(rootDB, rootName, "const", fieldName + ".csv")
     data = pd.read_csv(
-        dataFile, dtype=np.float64 skiprows=indSkip, header=None
+        dataFile, dtype=float, skiprows=indSkip, header=None
     ).values.flatten()
     data[np.where(data == -9999)] = np.nan
     return data
@@ -189,7 +189,7 @@ def readStat(*, rootDB, fieldName, isConst=False):
         statFile = os.path.join(
             rootDB, "Statistics", "const_" + fieldName + "_stat.csv"
         )
-    stat = pd.read_csv(statFile, dtype=np.float64 header=None).values.flatten()
+    stat = pd.read_csv(statFile, dtype=float, header=None).values.flatten()
     return stat
 
 

diff --git a/hydroDL/data/load_csv.py b/hydroDL/data/load_csv.py
@@ -92,7 +92,7 @@ def load_all_csv(self, var_s, var_type, select_date_list, csv_date_list):
                 path_xdata = os.path.join(
                     self.csv_path_s, str(year_int), var_s + ".csv"
                 )
-                df = pd.read_csv(path_xdata, dtype=np.float64, header=None)  # pixel, time
+                df = pd.read_csv(path_xdata, dtype=float, header=None)  # pixel, time
 
                 df_a = df.values  # pixel, time
                 if ndx_year == 0:
@@ -102,7 +102,7 @@ def load_all_csv(self, var_s, var_type, select_date_list, csv_date_list):
 
             elif var_type in ["var_c"]:
                 path_cData = os.path.join(self.csv_path_s, "const", var_s + ".csv")
-                df = pd.read_csv(path_cData, dtype=np.float64, header=None,)  # pixel,
+                df = pd.read_csv(path_cData, dtype=float, header=None,)  # pixel,
 
                 df_a = df.values  # pixel,
                 data = df_a

diff --git a/hydroDL/master/master.py b/hydroDL/master/master.py
@@ -95,7 +95,7 @@ def namePred(out, tRange, subset, epoch=None, doMC=False, suffix=None):
 #     for k in range(len(filePathLst)):
 #         filePath = filePathLst[k]
 #         dataPred[:, :, k] = pd.read_csv(
-#             filePath, dtype=np.float64 header=None).values
+#             filePath, dtype=float, header=None).values
 #     isSigmaX = False
 #     if mDict['loss']['name'] == 'hydroDL.model.crit.SigmaLoss':
 #         isSigmaX = True
@@ -737,7 +737,7 @@ def test(
                     doMC=doMC,
                 )
                 # read predicted results
-                dataPred = pd.read_csv(tempfilePath, dtype=np.float64 header=None).values
+                dataPred = pd.read_csv(tempfilePath, dtype=float, header=None).values
                 updateData = np.full(initobs.shape, 0.0)
                 updateData[:, 1:, 0] = dataPred[:, 0:-1]
                 updateData[:, fixIndex, :] = initobs[:, fixIndex, :]
@@ -761,7 +761,7 @@ def test(
     dataPred = np.ndarray([obs.shape[0], obs.shape[1], len(filePathLst)])
     for k in range(len(filePathLst)):
         filePath = filePathLst[k]
-        dataPred[:, :, k] = pd.read_csv(filePath, dtype=np.float64 header=None).values
+        dataPred[:, :, k] = pd.read_csv(filePath, dtype=float, header=None).values
     isSigmaX = False
     if mDict["loss"]["name"] == "hydroDL.model.crit.SigmaLoss" or doMC is not False:
         isSigmaX = True

diff --git a/hydroDL/utils/norm.py b/hydroDL/utils/norm.py
@@ -38,7 +38,7 @@ def trans_norm(
     if stat is None:
         # stat = [90 percentile,10 percentile, mean,std]
 
-        stat = pd.read_csv(csv_path_s, dtype=np.float64 header=None).values.flatten()
+        stat = pd.read_csv(csv_path_s, dtype=float, header=None).values.flatten()
 
     if from_raw:
         data_out = (data - stat[2]) / stat[3]