ADD: possibility to define vmin and vmax for PLOT_SCATTER_INTERCOMP product

Author: wolfidan

src/pyrad_proc/pyrad/prod/process_intercomp_products.py

@@ -42,7 +42,8 @@ def generate_intercomp_products(dataset, prdcfg):
     Generates radar intercomparison products. Accepted product types:
         'PLOT_AND_WRITE_INTERCOMP_TS': Writes statistics of radar
             intercomparison in a file and plots the time series of the
-            statistics.
+            statistics. Note that in order to use this product you need
+            to also define the product WRITE_INTERCOMP_TIME_AVG for the dataset in question.
             User defined parameters:
                 voltype: str
                     name of the pyrad variable to use, it must be available in the dataset
@@ -71,14 +72,21 @@ def generate_intercomp_products(dataset, prdcfg):
                     The minimum correlation to consider the statistics
                     valid and therefore use the data point in the plotting.
                     Default 0.
-        'PLOT_SCATTER_INTERCOMP': Plots a density plot with the points of
-            radar 1 versus the points of radar 2
+        'PLOT_SCATTER_INTERCOMP': Plots a density plot (2D histogram) with the points of
+            radar 1 versus the points of radar 2. Note that in order to use this product you need
+            to also define the product WRITE_INTERCOMP_TIME_AVG for the dataset in question.
             User defined parameters:
                 voltype: str
                     name of the pyrad variable to use, it must be available in the dataset
                 step: float
                     The quantization step of the data. If none it will be
                     computed using the Py-ART config file. Default None
+                vmin: float
+                    Minimum value of the density plot. If vmin or vmax are not define the range limits
+                    of the field as defined in the Py-ART config file are going to be used.
+                vmax: float
+                    Maximum value of the density plot. If vmin or vmax are not define the range limits
+                    of the field as defined in the Py-ART config file are going to be used.
                 scatter_type: str
                     Type of scatter plot. Can be a plot for each radar volume
                     (instant) or at the end of the processing period
@@ -200,6 +208,8 @@ def generate_intercomp_products(dataset, prdcfg):
         transform = parse_math_expression(transform_str)
         range_bins = prdcfg.get("range_bins", [0, np.inf])
         step = prdcfg.get("step", None)
+        vmin = prdcfg.get("vmin", None)
+        vmax = prdcfg.get("vmax", None)
 
         fname_list = []
         for i in range(len(range_bins) - 1):  # loop on range bins
@@ -244,6 +254,8 @@ def generate_intercomp_products(dataset, prdcfg):
                 step1=step,
                 step2=step,
                 transform=transform,
+                vmin=vmin,
+                vmax=vmax,
             )
             if hist_2d is None:
                 return None
@@ -274,7 +286,6 @@ def generate_intercomp_products(dataset, prdcfg):
                 + "{:.2f}".format(float(stats["intercep"]))
                 + "\n"
             )
-
             if transform_str != "x":
                 field_name = f"{transform_str} of {field_name}"
             plot_scatter(
@@ -479,7 +490,10 @@ def generate_colocated_gates_products(dataset, prdcfg):
             gridMapImageConfig structure of the loc file.
             User defined parameters:
                 grid_size: float
-                    Size of the grid in degrees (lat/lon). Default is 0.02 degrees.
+                    Size of the grid in degrees (lat/lon). If not provided,
+                    the grid size defined in gridMapImageConfig with
+                    lat_min, lon_min, lat_max, lon_max and lonstep, latstep
+                    will be used.
         All the products of the 'VOL' dataset group
 
 

src/pyrad_proc/pyrad/util/radar_utils.py

@@ -1822,9 +1822,16 @@ def compute_2d_stats(
         the two fields
     field_name1, field_nam2: str
         the name of the fields
-    step1, step2 : float
-        size of bin
-    vmin
+    step1: float
+        size of the bins along dimension 1
+    step2 : float
+        size of the bins along dimension 2
+    vmin: float
+        Minimum value of the density plot. If vmin or vmax are not define the range limits
+        of the field as defined in the Py-ART config file are going to be used.
+    vmax: float
+        Maximum value of the density plot. If vmin or vmax are not define the range limits
+        of the field as defined in the Py-ART config file are going to be used.
     transform : func
         A function to use to transform the data prior to computing the stats
 
@@ -1866,6 +1873,8 @@ def compute_2d_stats(
         step1=step1,
         step2=step2,
         transform=transform,
+        vmin=vmin,
+        vmax=vmax,
     )
     step_aux1 = bin_edges1[1] - bin_edges1[0]
     bin_centers1 = bin_edges1[:-1] + step_aux1 / 2.0
@@ -1945,7 +1954,15 @@ def compute_1d_stats(field1, field2):
 
 
 def compute_2d_hist(
-    field1, field2, field_name1, field_name2, step1=None, step2=None, transform=None
+    field1,
+    field2,
+    field_name1,
+    field_name2,
+    step1=None,
+    step2=None,
+    transform=None,
+    vmin=None,
+    vmax=None,
 ):
     """
     computes a 2D histogram of the data
@@ -1956,8 +1973,12 @@ def compute_2d_hist(
         the radar fields
     field_name1, field_name2 : str
         field names
-    step1, step2 : float
-        size of the bins
+    step1: float
+        size of the bins along dimension 1
+    step2 : float
+        size of the bins along dimension 2
+
+
     transform: func
         A function to use to transform the histogram bins
 
@@ -1969,10 +1990,14 @@ def compute_2d_hist(
         the bin edges along each dimension
 
     """
-    bin_edges1 = get_histogram_bins(field_name1, step=step1, transform=transform)
+    bin_edges1 = get_histogram_bins(
+        field_name1, step=step1, transform=transform, vmin=vmin, vmax=vmax
+    )
     step_aux1 = bin_edges1[1] - bin_edges1[0]
     bin_centers1 = bin_edges1[:-1] + step_aux1 / 2.0
-    bin_edges2 = get_histogram_bins(field_name2, step=step2, transform=transform)
+    bin_edges2 = get_histogram_bins(
+        field_name2, step=step2, transform=transform, vmin=vmin, vmax=vmax
+    )
     step_aux2 = bin_edges2[1] - bin_edges2[0]
     bin_centers2 = bin_edges2[:-1] + step_aux2 / 2.0