add read_dss function to read in ts from dss with path

Author: lily-tomkovic-DWR

dms_datastore/read_dss.py

@@ -0,0 +1,74 @@
+from vtools.functions.interpolate import rhistinterp
+from vtools.data.vtime import days, minutes
+from pyhecdss import get_ts, DSSFile
+from pathlib import Path
+import pandas as pd
+import os
+
+
+dss_e2_freq = {"1HOUR": "H", "1DAY": "D", "1MON": "M"}
+
+
+def read_dss(
+    filename,
+    pathname,
+    dt=minutes(15),
+    p=2.0,
+    start_date=None,
+    end_date=None,
+):
+    """
+    Reads in a DSM2 dss file and interpolates
+    Outputs an interpolated DataFrame of that variable
+
+    Parameters
+    ----------
+    filename: str|Path
+        Path to the DSS file to read
+    pathname: str
+        Pathname within the DSS file to read.
+        Needs to be in the format '/A_PART/B_PART/C_PART/D_PART/E_PART/F_PART/'
+        (e.g. '//RSAN112/FLOW////')
+    """
+    ts_out_list = []
+    col_names = []
+    print(f"\t{pathname}")
+    if len(pathname.split("/")[1:-1]) != 6:
+        raise ValueError(f"Invalid DSS pathname: {pathname}, needs 6 parts (A-F)")
+    ts = get_ts(filename, pathname)
+    for i, tsi in enumerate(ts):
+        ts_path = tsi[0].columns.values[0]
+        path_lst = (ts_path).split("/")
+        path_e = path_lst[5]
+        # Set default start_date and end_date to cover the full period of record if not specified
+        tt_full = tsi[0]
+        if start_date is None:
+            start_date = tt_full.index[0]
+        if end_date is None:
+            end_date = tt_full.index[-1]
+        tt = tt_full[start_date:end_date]
+        pidx = pd.period_range(start_date, tt.index[-1], freq=dss_e2_freq[path_e])
+        ptt = pd.DataFrame(tt.values[:, 0], pidx)
+
+        # Interpolate with rhistinterp
+        if p != 0:
+            col_data = rhistinterp(ptt, dt, p=p)
+        elif p == 0:
+            col_data = rhistinterp(ptt, dt)
+        else:
+            col_data = tsi[0]
+        ts_out_list.append(col_data)
+        col_names.append(ts_path)
+
+    if ts_out_list:
+        ts_out = pd.concat(ts_out_list, axis=1)
+        ts_out.columns = col_names
+        ts_out = ts_out.copy()  # Defragment the DataFrame
+    else:
+        with DSSFile(filename) as dssh:
+            dfcat = dssh.read_catalog()
+        raise ValueError(
+            f"Warning: DSS data not found for {pathname}. Preview of available paths in {filename} are: {dfcat}"
+        )
+
+    return ts_out