ENH: added possibility to cut data at vmin/vmax for intercomp scatter plots

Author: wolfidan

src/pyrad_proc/pyrad/graph/plots.py

@@ -534,6 +534,8 @@ def plot_scatter(
     rad2_name="RADAR002",
     titl="colocated radar gates",
     cmap=None,
+    vmin=None,
+    vmax=None,
 ):
     """
     2D histogram
@@ -563,6 +565,10 @@ def plot_scatter(
     cmap : str or None
         name of the colormap. If None it will be choosen the default for the
         field_name
+    vmin: float
+        Minimum value of the 2D histogram.
+    vmax: float
+        Maximum value of the 2D histogram.
 
     Returns
     -------
@@ -616,6 +622,10 @@ def plot_scatter(
     ax.set_ylabel(labely)
     ax.set_title(titl)
 
+    if vmin and vmax:
+        ax.set_xlim([vmin, vmax])
+        ax.set_ylim([vmin, vmax])
+
     cb = fig.colorbar(cax)
     cb.set_label(label)
 

src/pyrad_proc/pyrad/prod/process_intercomp_products.py

@@ -87,6 +87,10 @@ def generate_intercomp_products(dataset, prdcfg):
                 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.
+                cap_limits: bool
+                    If set to 1, all values larger than vmax or smaller than vmin will be discarded from the
+                    scatter plot. If set to 0, they will be kept and assigned to the smallest/largest bin
+                    of the histogram. Default is 0.
                 scatter_type: str
                     Type of scatter plot. Can be a plot for each radar volume
                     (instant) or at the end of the processing period
@@ -214,6 +218,7 @@ def generate_intercomp_products(dataset, prdcfg):
         step = prdcfg.get("step", None)
         vmin = prdcfg.get("vmin", None)
         vmax = prdcfg.get("vmax", None)
+        cap_limits = prdcfg.get("cap_limits", 0)
 
         fname_list = []
         for i in range(len(range_bins) - 1):  # loop on range bins
@@ -260,6 +265,7 @@ def generate_intercomp_products(dataset, prdcfg):
                 transform=transform,
                 vmin=vmin,
                 vmax=vmax,
+                cap_limits=cap_limits,
             )
             if hist_2d is None:
                 return None
@@ -306,6 +312,8 @@ def generate_intercomp_products(dataset, prdcfg):
                 lin_regr_slope1=stats["intercep_slope_1"],
                 rad1_name=dataset["intercomp_dict"]["rad1_name"],
                 rad2_name=dataset["intercomp_dict"]["rad2_name"],
+                vmin=vmin,
+                vmax=vmax,
             )
 
             fname_list.extend(f_list)

src/pyrad_proc/pyrad/util/__init__.py

@@ -98,7 +98,4 @@
 from .data_retrieval_utils import retrieve_CPCCV  # noqa
 from .data_retrieval_utils import retrieve_AQC_XLS  # noqa
 
-from .math_utils import bit_pack  # noqa
-from .math_utils import bit_unpack  # noqa
-
 __all__ = [s for s in dir() if not s.startswith("_")]

src/pyrad_proc/pyrad/util/math_utils.py

@@ -1812,6 +1812,7 @@ def compute_2d_stats(
     vmin=None,
     vmax=None,
     transform=None,
+    cap_limits=False,
 ):
     """
     computes a 2D histogram and statistics of the data
@@ -1827,13 +1828,16 @@ def compute_2d_stats(
     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
+        Minimum value of the 2D histogram. 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
+        Maximum value of the 2D histogram. 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
+    cap_limits: bool
+        If true, all values larger than vmax or smaller than vmin will be discarded from the
+        scatter plot. Otherwise, they will be kept and assigned to the smallest/largest bin
 
     Returns
     -------
@@ -1875,6 +1879,7 @@ def compute_2d_stats(
         transform=transform,
         vmin=vmin,
         vmax=vmax,
+        cap_limits=cap_limits,
     )
     step_aux1 = bin_edges1[1] - bin_edges1[0]
     bin_centers1 = bin_edges1[:-1] + step_aux1 / 2.0
@@ -1960,9 +1965,10 @@ def compute_2d_hist(
     field_name2,
     step1=None,
     step2=None,
-    transform=None,
     vmin=None,
     vmax=None,
+    transform=None,
+    cap_limits=False,
 ):
     """
     computes a 2D histogram of the data
@@ -1977,10 +1983,17 @@ def compute_2d_hist(
         size of the bins along dimension 1
     step2 : float
         size of the bins along dimension 2
-
-
+    vmin: float
+        Minimum value of the 2D histogram. 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 2D histogram. 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 histogram bins
+    cap_limits: bool
+        If true, all values larger than vmax or smaller than vmin will be discarded from the
+        scatter plot. Otherwise, they will be kept and assigned to the smallest/largest bin
 
     Returns
     -------
@@ -2001,17 +2014,22 @@ def compute_2d_hist(
     step_aux2 = bin_edges2[1] - bin_edges2[0]
     bin_centers2 = bin_edges2[:-1] + step_aux2 / 2.0
 
-    field1[field1 < bin_centers1[0]] = bin_centers1[0]
-    field1[field1 > bin_centers1[-1]] = bin_centers1[-1]
+    if not cap_limits:
+        field1[field1 < bin_centers1[0]] = bin_centers1[0]
+        field1[field1 > bin_centers1[-1]] = bin_centers1[-1]
 
-    field2[field2 < bin_centers2[0]] = bin_centers2[0]
-    field2[field2 > bin_centers2[-1]] = bin_centers2[-1]
+        field2[field2 < bin_centers2[0]] = bin_centers2[0]
+        field2[field2 > bin_centers2[-1]] = bin_centers2[-1]
+        hist_range = None
+    else:
+        hist_range = [[vmin, vmax], [vmin, vmax]]
 
     fill_value = pyart.config.get_fillvalue()
     return np.histogram2d(
         field1.filled(fill_value=fill_value),
         field2.filled(fill_value=fill_value),
         bins=[bin_edges1, bin_edges2],
+        range=hist_range,
     )