How to plot the accumulated (for a day/single plot) // how can i extract reflectivity values of stratiform and convective for evaluation

General
, , , ,
1

1)How to plot the accumulated (for a day/single plot) ?
2)how can i extract reflectivity values of stratiform and convective for evaluation ?

My code:

import numpy as np
import matplotlib.pyplot as plt
import cartopy.crs as ccrs
import cartopy.feature as cfeature
from cartopy.mpl.gridliner import LONGITUDE_FORMATTER, LATITUDE_FORMATTER
import glob
import pyart
import numpy.ma as ma
import matplotlib.colors as mcolors

grid_files = glob.glob(“D:\radar_data\radinout\gridded_20_jun_2022\gridded_20_jun_2022*nc”)

for i, file in enumerate(grid_files):
grid_data = pyart.io.read_grid(file)
feature_dict = pyart.retrieve.feature_detection(
grid_data,
dx=2000,
dy=2000,
field=“REF”,
always_core_thres=40,
bkg_rad_km=4,
use_cosine=True,
max_diff=5,
zero_diff_cos_val=55,
weak_echo_thres=10,
max_rad_km=5,
)

# Reshape the feature_detection field data
feature_data = feature_dict["feature_detection"]["data"][0, :, :]
feature_data_reshaped = np.broadcast_to(feature_data, (grid_data.nz,) + feature_data.shape)

# Mask the feature data
feature_masked = np.ma.masked_equal(feature_data_reshaped, 0)
feature_masked = np.ma.masked_equal(feature_masked, 3)

# Add the masked data to the grid
grid_data.add_field(
    "feature_detection", {"data": feature_masked}, replace_existing=True
)

display = pyart.graph.GridMapDisplay(grid_data)
plt.figure(figsize=(10, 8))
ax = plt.axes(projection=ccrs.PlateCarree())

display.plot_grid(
    "feature_detection",
    vmin=0,
    vmax=2,
    cmap=plt.get_cmap("viridis", 3),
    ax=ax,
    transform=ccrs.PlateCarree(),
    ticks=[1 / 3, 1, 5 / 3],
    ticklabs=["Mixed", "Stratiform", "Convective"],
)

plt.plot(75.8175, 26.8207, marker="x", color="black", markersize=15, markeredgewidth=2)
plt.title('convective stratiform-20/6/2022')
plt.show()