Flow Processor. Debubbler influence.

cfatools/processor/flow.py

@@ -12,18 +12,78 @@ import matplotlib.pyplot as plt
 
 
 def get_flow_timeseries(dataset: DatasetReader):
-    colpump_df = pump.get_mlmin_df(dataset, "COLPUMP")
-    compump_df = pump.get_mlmin_df(dataset, "COMPUMP")
-    picpump_df = pump.get_mlmin_df(dataset, "PICPUMP")
+    pump_df = get_bubble_density_from_pump(dataset)
+
 
     iceblock_df = dataset.get_timeseries("ICBKCTRL_instant")
     melting_df = iceblock.get_melting_timeseries(iceblock_df)
+    melting_df["datetime_in"] = melting_df.index
+
+    com_water_df = pump_df[["com_water_pump"]]
+    com_water_df = com_water_df.rename(columns={"com_water_pump": "mlmin"})
+    melting_df["datetime_debubbler"] = get_datetime_out(melting_df["datetime_in"], com_water_df, 3.48, parallel=False)
+
+    colpic_df = pump_df[["pic", "col"]]
+    colpic_df["mlmin"] = colpic_df["pic"] + colpic_df["col"]
+    melting_df["datetime_T1"] = get_datetime_out(melting_df["datetime_debubbler"], colpic_df, 0.600, parallel=False)
+
+    pic_df = pump_df[["pic"]]
+    pic_df = pic_df.rename(columns={"pic": "mlmin"})
+    melting_df["datetime_T2"] = get_datetime_out(melting_df["datetime_T1"], pic_df, 0.095, parallel=False)
+
+    melting_df["datetime_picarro"] = melting_df["datetime_T2"] + datetime.timedelta(minutes=1, seconds=35)
+
 
     picarro_df = dataset.get_timeseries("PICARRO_periodic")
+    picarro_df["Delta_18_16"].plot()
+
+    pass
+
+
+def get_debubbler_effect(dataset: DatasetReader):
+    pump_df = get_bubble_density_from_pump(dataset)
+
     conduct_df = dataset.get_timeseries("CONDUCTI_periodic")
+    conduct_df = conduct_df[["C1"]]
+    # conduct_df = conduct_df[conduct_df["C1"] > 1.35]
+    conduct_df["datetime_C1"] = conduct_df.index
+
+    com_water_df = pump_df[["com_water_pump"]]
+    com_water_df = com_water_df.rename(columns={"com_water_pump": "mlmin"})
+    conduct_df["datetime_debubbler"] = get_datetime_out(conduct_df["datetime_C1"], com_water_df, 0.087, parallel=False)
+
+    vol_debub_C5 = 0.630
+    vol_debub_T1 = 0.432
+    vol_debub_C4 = 1.187
+    vol_T1_C4 = vol_debub_C4 - vol_debub_T1
+    vol_T1_C5 = vol_debub_C5 - vol_debub_T1
+
+    colpic_df = pump_df[["pic", "col"]]
+    colpic_df = colpic_df.ewm(alpha=0.05).mean()
+    colpic_df["mlmin"] = colpic_df["pic"] + colpic_df["col"]
+    conduct_df["datetime_T1"] = get_datetime_out(conduct_df["datetime_debubbler"], colpic_df, vol_debub_T1, parallel=False)
+
+    col_df = pump_df[["col"]]
+    col_df = col_df.rename(columns={"col": "mlmin"})
+    conduct_df["datetime_C4"] = get_datetime_out(conduct_df["datetime_T1"], col_df, vol_T1_C4, parallel=False)
+
+    pic_df = pump_df[["pic"]]
+    pic_df = pic_df.rename(columns={"pic": "mlmin"})
+    conduct_df["datetime_C5"] = get_datetime_out(conduct_df["datetime_T1"], pic_df, vol_T1_C5, parallel=False)
+
+    pass
+
+
+def compare_gasflow(dataset: DatasetReader):
+    "USELESS - For later reuse/refactor"
+    colpump_df = pump.get_mlmin_df(dataset, "COLPUMP")
+    compump_df = pump.get_mlmin_df(dataset, "COMPUMP")
+    picpump_df = pump.get_mlmin_df(dataset, "PICPUMP")
+
     gasflow_df = dataset.get_timeseries("GASFLOW_periodic")
 
-    pump_df = pd.merge(colpump_df, compump_df, right_index=True, left_index=True, how="outer", suffixes=["_col", "_com"])
+    pump_df = pd.merge(colpump_df, compump_df, right_index=True, left_index=True, how="outer",
+                       suffixes=["_col", "_com"])
     pump_df = pd.merge(pump_df, picpump_df, right_index=True, left_index=True, how="outer")
     pump_df = pump_df.rename(columns={"mlmin": "mlmin_pic"})
     pump_df = pd.merge(pump_df, gasflow_df, right_index=True, left_index=True, how="outer")
@@ -36,7 +96,6 @@ def get_flow_timeseries(dataset: DatasetReader):
     pump_df["mlmin_air_diff"] = pump_df["mlmin_com_air"] - pump_df["mlmin_gas"]
     pump_df[["mlmin_air_diff"]].plot()
     plt.show()
-    pass
 
 
 def get_bubble_density(dataset: DatasetReader):
@@ -70,13 +129,10 @@ def get_bubble_density_from_pump(dataset: DatasetReader):
 
 
 def get_bubble_density_from_conduct(dataset: DatasetReader):
-    first_datetime = "2020-12-23 14:35:08"
-    last_datetime = "2020-12-23 15:02:49"
     conduct_df = dataset.get_timeseries("CONDUCTI_periodic")[["C1", "C2"]]
-    c1 = conduct_df[first_datetime:last_datetime]["C1"]
+    c1 = conduct_df["C1"]
     c2 = conduct_df["C2"]
-    c2.index = c2.index + datetime.timedelta(seconds=-11)
-    c2 = c2[first_datetime:last_datetime]
+    c2.index = c2.index + datetime.timedelta(seconds=-9)
     c2 = c2 - 0.05
 
     conduct_df = pd.merge(c1, c2, left_index=True, right_index=True, how="outer").fillna(method="ffill")
@@ -124,6 +180,9 @@ def get_datetime_out(datetime_in: pd.Series, mlmin_df: pd.DataFrame, tube_volume
     mlmin_df = mlmin_df[["mlmin"]].ffill()
     mlmin_df["ml_cumul"] = pump.add_cumulated_volume(mlmin_df["mlmin"])
 
+    # Make sure the earliest datetime_in is after the first available ml_cumul
+    datetime_in = datetime_in[datetime_in.index >= mlmin_df["ml_cumul"].dropna().index[0]]
+
     if parallel:
         pandarallel.initialize()
         datetime_out = datetime_in.parallel_apply(__get_single_datetime_out__, args=(mlmin_df, tube_volume_ml))
@@ -160,6 +219,8 @@ def __get_single_datetime_out__(datetime_in: pd.Timestamp, mlmin_df: pd.DataFram
 
     # Create a DataFrame of flow rate's evolution, starting from insertion (`datetime_in`)
     object_mlmin_df = mlmin_df[mlmin_df.index >= datetime_in]
+    if len(object_mlmin_df.index) == 0:
+        return
 
     # Get already-cumulated volume at datetime_in
     initial_volume = object_mlmin_df["ml_cumul"].iloc[0]

cfatools/tests/test_processor/test_flow.py

@@ -20,7 +20,7 @@ class TestFlow(TestCase):
         self.base_path = config_parser["base_data_path"]
 
     def test_get_flow_timeseries(self):
-        dataset_name = "20210122_mock_ice_bronkgas_debub"
+        dataset_name = "20210202_mock_core_flasks"
         dataset = DatasetReader(self.base_path, dataset_name)
 
         try:
@@ -28,6 +28,15 @@ class TestFlow(TestCase):
         except:
             self.fail("Exception raised!")
 
+    def test_get_debubbler_effect(self):
+        dataset_name = "20210212_conducti_transitions_various_speeds"
+        dataset = DatasetReader(self.base_path, dataset_name)
+
+        try:
+            flow.get_debubbler_effect(dataset)
+        except:
+            self.fail("Exception raised!")
+
     def test_get_datetime_out_artificialdataset(self):
         tube_volume_ml = 30
 
@@ -93,6 +102,6 @@ class TestFlow(TestCase):
         flow.get_bubble_density_from_conduct(dataset)
 
     def test_get_bubble_density(self):
-        dataset_name = "20201223_mock_core"
+        dataset_name = "20201223_mock_core_bronkhorst"
         dataset = DatasetReader(self.base_path, dataset_name)
         flow.get_bubble_density(dataset)
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