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Anomalies Plot Example
# Metview Macro # **************************** LICENSE START *********************************** # # Copyright 2020 ECMWF. This software is distributed under the terms # of the Apache License version 2.0. In applying this license, ECMWF does not # waive the privileges and immunities granted to it by virtue of its status as # an Intergovernmental Organization or submit itself to any jurisdiction. # # ***************************** LICENSE END ************************************ # ------------------------------------------------------------------------- # Description: Demonstrates how to plot anomalies from GRIB data (ERA5 here) # ------------------------------------------------------------------------- # read the GRIB data into a Fieldset diff = read("1month_anomaly_Global_ea_2t_201805_v02.grib") # compute the absolute maximum value and compute a scale for the contouring maxdiff = maxvalue(abs(diff)) levels_relative = [-1, -0.75, -0.5, -0.25, -0.1, 0.1, 0.25, 0.5, 0.75, 1] levels = maxdiff * levels_relative # generate a contouring definition # - we must set grib_scaling_of_retrieved_fields=off in order # - to prevent scaling from K to C diff_cont = mcont( legend : "on", contour : "off", contour_level_selection_type : "level_list", contour_level_list : levels, contour_shade : "on", contour_shade_technique : "grid_shading", contour_shade_colour_method : "palette", contour_shade_palette_name : "eccharts_blue_white_red_9", grib_scaling_of_retrieved_fields : "off" ) # increase font size in the legend (cm) legend = mlegend(legend_text_font_size : 0.3) # define the output plot file setoutput(pdf_output(output_name : 'field_anomalies')) # generate the plot plot(diff, diff_cont, legend)
Anomalies Plot Example
# **************************** LICENSE START *********************************** # # Copyright 2020 ECMWF. This software is distributed under the terms # of the Apache License version 2.0. In applying this license, ECMWF does not # waive the privileges and immunities granted to it by virtue of its status as # an Intergovernmental Organization or submit itself to any jurisdiction. # # ***************************** LICENSE END ************************************ # ------------------------------------------------------------------------- # Description: Demonstrates how to plot anomalies from GRIB data (ERA5 here) # ------------------------------------------------------------------------- import metview as mv # read the GRIB data into a Fieldset diff = mv.read("1month_anomaly_Global_ea_2t_201805_v02.grib") # compute the absolute maximum value and compute a scale for the contouring maxdiff = mv.maxvalue(abs(diff)) levels_relative = [-1, -0.75, -0.5, -0.25, -0.1, 0.1, 0.25, 0.5, 0.75, 1] levels = [lev * maxdiff for lev in levels_relative] # generate a contouring definition # - we must set grib_scaling_of_retrieved_fields=off in order # - to prevent scaling from K to C diff_cont = mv.mcont( legend = "on", contour = "off", contour_level_selection_type = "level_list", contour_level_list = levels, contour_shade = "on", contour_shade_technique = "grid_shading", contour_shade_colour_method = "palette", contour_shade_palette_name = "eccharts_blue_white_red_9", grib_scaling_of_retrieved_fields = "off" ) # increase font size in the legend (cm) legend = mv.mlegend(legend_text_font_size = 0.3) # define the output plot file mv.setoutput(mv.pdf_output(output_name = 'field_anomalies')) # generate the plot mv.plot(diff, diff_cont, legend)