Isaiahensley
commented
6 months ago Description:
Completed the Quiver Plot visualization option.
Steps to reproduce:
1) Go to the Dataset Management page
2) Upload .nc file(s)
3) Select Quiver Plot as the Visualization Option
4) Choose the x-velocity and y-velocity (in most cases this will be "u" and "v")
5) A Quiver Plot is generated and the Time and Depth can be adjusted.
Quiver Plot GIF:
Code Snippet:
def quiverplot(variables_not_dimensions, file_content, datetime_str, depth, selected_xvelocity, selected_yvelocity):
# Load the NetCDF file from BytesIO object
nc_file = nc.Dataset('in-memory', memory=file_content)
try:
# Convert the selected datetime string back to a datetime object
selected_datetime = parse_datetime(datetime_str)
# Find the index of the selected time
time_var = nc_file.variables['time']
time_units = time_var.units
selected_time_index = np.where(nc.num2date(time_var[:], units=time_units) == selected_datetime)[0][0]
# Access the data for the selected u and v velocity variables
u_data = nc_file.variables[selected_xvelocity][selected_time_index, depth, :, :]
v_data = nc_file.variables[selected_yvelocity][selected_time_index, depth, :, :]
# Ensure lat and lon are 2D arrays for quiver plotting
lat = nc_file.variables['lat'][:]
lon = nc_file.variables['lon'][:]
Lon, Lat = np.meshgrid(lon, lat)
# Optionally, reduce the density of arrows for clarity
skip = (slice(None, None, 5), slice(None, None, 5)) # Adjust the slicing for desired arrow density
u_data = u_data[skip]
v_data = v_data[skip]
Lon = Lon[skip]
Lat = Lat[skip]
# Setting up the plot with a dark background for white elements to stand out
plt.style.use('dark_background')
fig, ax = plt.subplots(figsize=(10, 6))
q = ax.quiver(Lon, Lat, u_data, v_data, color='white') # Set arrow color to white
# Include a key to indicate scale, with text in white
ax.quiverkey(q, X=0.9, Y=1.05, U=10, label='10 units', labelpos='E', color='white')
# Set axis labels and title with white text
ax.set_xlabel('Longitude', color='white')
ax.set_ylabel('Latitude', color='white')
#ax.set_title(f'Quiver plot for {selected_xvelocity} and {selected_yvelocity} at depth {depth} on {datetime_str}', color='white')
# Changing tick parameters to white
ax.tick_params(axis='both', colors='white')
fig.tight_layout()
buf = BytesIO()
fig.savefig(buf, format="png", dpi=300, transparent=True)
#st.image(buf, use_column_width=True)
st.image(buf, width=1080)
except Exception as e:
st.error(f"Error generating quiver plot: {e}")
finally:
nc_file.close()
Description: This issue is focused on creating a Quiver Plot option on the Dataset Management page. This visualization option will be similar to the Heat Map option that was completed. This will allow users to visualize water currents in an aquatic source.
Expected vs. Actual Behavior: Users should be able to select "Quiver plot" as a Visualization option and be prompted to select the: U - water current velocity on the Zonal axis (left to right) V - water current velocity on the Meridional axis (up to down) These values should change depending on the time and depth dimension that is selected. This should update in real-time when a different dimension is selected.
Screenshot Example:
Objective: Creating User-friendly Quiverplot for water current plot.