Merge github.com:timcera/mettoolbox

src/mettoolbox/disaggregate.py

@@ -276,10 +276,12 @@ def humidity(
     hum_mean_col: Optional[Union[tsutils.IntGreaterEqualToOne, str, pd.Series]] = None,
     temp_min_col: Optional[Union[tsutils.IntGreaterEqualToOne, str, pd.Series]] = None,
     temp_max_col: Optional[Union[tsutils.IntGreaterEqualToOne, str, pd.Series]] = None,
+    precip_col: Optional[Union[tsutils.IntGreaterEqualToOne, str, pd.Series]] = None,
     a0=None,
     a1=None,
     kr=None,
     hourly_temp=None,
+    hourly_precip_hum=None,
     preserve_daily_mean=None,
 ):
     """Disaggregate daily humidity to hourly humidity data."""
@@ -294,6 +296,15 @@ def humidity(
             )
         )
 
+    if method == "month_hour_precip_mean" and precip_col is None:
+        raise ValueError(
+            tsutils.error_wrapper(
+                """
+If `method` is "month_hour_precip_mean" then the daily precip is a required column
+identified with the keyword `precip_col`"""
+            )
+        )
+
     if (
         method in ["minimal", "dewpoint_regression", "linear_dewpoint_variation"]
         and temp_min_col is None
@@ -359,7 +370,6 @@ def humidity(
             "dewpoint_regression",
             "linear_dewpoint_variation",
             "min_max",
-            "month_hour_precip_mean",
         ]
         and hourly_temp is None
     ):
@@ -374,6 +384,64 @@ def humidity(
 
     pd.options.display.width = 60
 
+    columns = []
+    if method == "equal":
+        try:
+            hum_mean_col = int(hum_mean_col)
+        except TypeError:
+            pass
+        columns.append(hum_mean_col)
+
+    if method == "min_max":
+        try:
+            temp_min_col = int(temp_min_col)
+        except TypeError:
+            pass
+        columns.append(temp_min_col)
+        try:
+            temp_max_col = int(temp_max_col)
+        except TypeError:
+            pass
+        columns.append(temp_max_col)
+        try:
+            hum_min_col = int(hum_min_col)
+        except TypeError:
+            pass
+        columns.append(hum_min_col)
+        try:
+            hum_max_col = int(hum_max_col)
+        except TypeError:
+            pass
+        columns.append(hum_max_col)
+
+    if method in ["minimal", "dewpoint_regression", "linear_dewpoint_variation"]:
+        try:
+            temp_min_col = int(temp_min_col)
+        except TypeError:
+            pass
+        columns.append(temp_min_col)
+
+    if method == "month_hour_precip_mean":
+        try:
+            precip_col = int(precip_col)
+        except TypeError:
+            pass
+        columns.append(precip_col)
+
+    if preserve_daily_mean is not None:
+        if method in [
+            "minimal",
+            "dewpoint_regression",
+            "linear_dewpoint_variation",
+            "min_max",
+            "month_hour_precip_mean",
+        ]:
+            try:
+                hum_mean_col = int(preserve_daily_mean)
+            except TypeError:
+                pass
+            columns.append(hum_mean_col)
+
     tsd = tsutils.common_kwds(
         tsutils.read_iso_ts(
             input_ts, skiprows=skiprows, names=names, index_type=index_type
@@ -389,36 +457,42 @@ def humidity(
     )
 
     if method == "equal":
-        tsd["hum"] = tsd["hum_mean_col"]
-
-    if method in ["minimal", "dewpoint_regression", "linear_dewpoint_variation"]:
-        tsd["tmin"] = tsd["temp_min_col"]
-
-    if method == "min_max":
-        tsd["hum_min"] = tsd["hum_min_col"]
-        tsd["hum_max"] = tsd["hum_max_col"]
-        tsd["tmin"] = tsd["temp_min_col"]
-        tsd["tmax"] = tsd["temp_max_col"]
+        tsd.columns = ["hum"]
 
     if preserve_daily_mean is not None:
-        tsd["hum"] = tsd[preserve_daily_mean]
+        if method in ["minimal", "dewpoint_regression", "linear_dewpoint_variation"]:
+            tsd.columns = ["tmin", "hum"]
+        if method == "month_hour_precip_mean":
+            tsd.columns = ["precip", "hum"]
+        if method == "min_max":
+            tsd.columns = ["tmin", "tmax", "hum_min", "hum_max", "hum"]
         preserve_daily_mean = True
+    else:
+        if method in ["minimal", "dewpoint_regression", "linear_dewpoint_variation"]:
+            tsd.columns = ["tmin"]
+        if method == "month_hour_precip_mean":
+            tsd.columns = ["precip"]
+        if method == "min_max":
+            tsd.columns = ["tmin", "tmax", "hum_min", "hum_max"]
 
     if method in [
         "minimal",
         "dewpoint_regression",
         "linear_dewpoint_variation",
         "min_max",
-        "month_hour_precip_mean",
     ]:
         hourly_temp = tstoolbox.read(hourly_temp)
+        hourly_temp = hourly_temp.astype(float).squeeze()
 
     if method == "month_hour_precip_mean":
-        month_hour_precip_mean = calculate_month_hour_precip_mean(hourly_temp)
+        hourly_precip_hum = tstoolbox.read(hourly_precip_hum)
+        month_hour_precip_mean = calculate_month_hour_precip_mean(hourly_precip_hum)
+    else:
+        month_hour_precip_mean = "None"
 
     ntsd = pd.DataFrame(
         disaggregate_humidity(
-            tsd,
+            tsd.astype(float),
             method=method,
             temp=hourly_temp,
             a0=a0,

src/mettoolbox/mettoolbox.py

@@ -162,13 +162,17 @@ def humidity_cli(
     target_units=None,
     print_input=False,
     tablefmt="csv",
+    precip_col=None,
+    temp_min_col=None,
+    temp_max_col=None,
     hum_min_col=None,
     hum_max_col=None,
     hum_mean_col=None,
     a0=None,
     a1=None,
     kr=None,
     hourly_temp=None,
+    hourly_precip_hum=None,
     preserve_daily_mean=None,
 ):
     """Disaggregate daily relative humidity to hourly humidity.
@@ -190,6 +194,19 @@ def humidity_cli(
     |              | calculated as average of `hum_tmin_col` and |
     |              | `hum_tmax_col`.                             |
     +--------------+---------------------------------------------+
+    | temp_min_col | Required column name or number representing |
+    |              | the minimum daily temperature for `minimal`,|
+    |              | `dewpoint regression`, `linear dewpoint     |
+    |              | variation`, and `min_max` methods.          |
+    +--------------+---------------------------------------------+
+    | temp_max_col | Required column name or number representing |
+    |              | the maximum daily temperature for min_max   |
+    |              | method.                                     |
+    +--------------+---------------------------------------------+
+    | precip_col   | Required column name or number representing |
+    |              | the total precipitation for                 |
+    |              | month_hour_precip_mean method.              |
+    +--------------+---------------------------------------------+
 
     Parameters
     ----------
@@ -291,6 +308,18 @@ def humidity_cli(
 
     ${tablefmt}
 
+    precip_col:
+        Column index (data columns start numbering at 1) or column name
+        from the input data that contains the daily precipitation.
+
+    temp_min_col:
+        Column index (data columns start numbering at 1) or column name
+        from the input data that contains the daily minimum temperature.
+
+    temp_max_col:
+        Column index (data columns start numbering at 1) or column name
+        from the input data that contains the daily maximum temperature.
+
     hum_min_col:
         Column index (data columns start numbering at 1) or column name
         from the input data that contains the daily minimum humidity.
@@ -319,6 +348,10 @@ def humidity_cli(
         Filename of a CSV file that contains an hourly time series of
         temperatures.
 
+    hourly_precip_hum: str
+        Filename of a CSV file that contains an hourly time series of
+        precipitation and humidity.
+
     preserve_daily_mean: str
         Column name or index (data columns start at 1) that identifies
         the observed daily mean humidity.  If not None will correct the
@@ -341,12 +374,16 @@ def humidity_cli(
             source_units=source_units,
             target_units=target_units,
             print_input=print_input,
+            precip_col=hum_min_col,
+            temp_min_col=hum_min_col,
+            temp_max_col=hum_max_col,
             hum_min_col=hum_min_col,
             hum_max_col=hum_max_col,
             hum_mean_col=hum_mean_col,
             a0=a0,
             a1=a1,
             kr=kr,
+            hourly_precip_hum=hourly_precip_hum,
             hourly_temp=hourly_temp,
             preserve_daily_mean=preserve_daily_mean,
         ),