def build_xs(self, data): if data: if not isinstance(data, list): data = [data] lines = [] for d in data: line = d.label # print(f"label={d.label}") param = d.ds_param_info if param is not None: # print(f"meta={param.meta}") line += f" Par: {param.name}" meta = param.meta if meta.get("mars.type", "") == "an": pass else: r = meta.get("date", 0) h = meta.get("time", 0) s = meta.get("step", "") line += f" Run: {r} {h} UTC Step: +{s}h" lines.append(line) return mv.mtext(text_lines=lines, text_font_size=self.font_size) return mv.mtext(text_font_size=self.font_size)
def build_stamp(self, data, member=""): if data: if not isinstance(data, list): data = [data] # exp_conf = data[0].experiment label = data[0].label member_txt = "" if member: if member == "0": member_txt = "CF" else: member_txt = f"PF {member}" return mv.mtext( { "text_line_1": f"""{label} {member_txt} Step: +<grib_info key='step'/>h Valid: <grib_info key='valid-date' format='%Y-%m-%d %H'/>""", "text_font_size": self.font_size, } ) return mv.mtext( { "text_font_size": self.font_size, } )
def plot_obs_freq(predictor_matrix, code): coastline = mv.mcoast(map_coastline_thickness=2, map_boundaries="on", map_coastline_colour="chestnut") symbol = mv.msymb( legend="on", symbol_type="marker", symbol_table_mode="on", symbol_outline="on", symbol_min_table=[1, 2, 5, 10, 15, 20, 25, 30], symbol_max_table=[2, 5, 10, 15, 20, 25, 30, 100000], symbol_colour_table=[ "RGB(0.7020,0.7020,0.7020)", "RGB(0.4039,0.4039,0.4039)", "blue", "RGB(0.4980,1.0000,0.0000)", "RGB(1.0000,0.8549,0.0000)", "orange", "red", "magenta", ], symbol_marker_table=15, symbol_height_table=0.3, ) legend = mv.mlegend( legend_text_font="arial", legend_text_font_size=0.35, legend_entry_plot_direction="row", legend_box_blanking="on", legend_entry_text_width=50, ) title = mv.mtext( text_line_count=4, text_line_1= "OBS Frequency", # To sostitute with "FE" values when relevant. text_line_2=f"WT Code = {code}", text_line_4=" ", text_font="arial", text_font_size=0.4, ) df = predictor_matrix[["LonOBS", "LatOBS", "OBS"]] grouped_df = df.groupby(["LatOBS", "LonOBS"], as_index=False).count() geo = mv.create_geo(len(grouped_df), "xyv") geo = mv.set_latitudes(geo, grouped_df["LatOBS"].to_numpy(dtype=np.float)) geo = mv.set_longitudes(geo, grouped_df["LonOBS"].to_numpy(dtype=np.float)) geo = mv.set_values(geo, grouped_df["OBS"].to_numpy(dtype=np.float)) with NamedTemporaryFile(delete=False, suffix=".pdf") as pdf: pdf_obj = mv.pdf_output(output_name=pdf.name.replace(".pdf", "")) mv.setoutput(pdf_obj) mv.plot(coastline, symbol, legend, title, geo) return pdf.name
def plot_std(predictor_matrix, code): coastline = mv.mcoast(map_coastline_thickness=2, map_boundaries="on", map_coastline_colour="chestnut") symbol = mv.msymb( legend="on", symbol_type="marker", symbol_table_mode="on", symbol_outline="on", symbol_min_table=[0, 0.0001, 0.5, 1, 2, 5], symbol_max_table=[0.0001, 0.5, 1, 2, 5, 1000], symbol_colour_table=[ "RGB(0.7020,0.7020,0.7020)", "RGB(0.2973,0.2973,0.9498)", "RGB(0.1521,0.6558,0.5970)", "RGB(1.0000,0.6902,0.0000)", "red", "RGB(1.0000,0.0000,1.0000)", ], symbol_marker_table=15, symbol_height_table=0.3, ) legend = mv.mlegend( legend_text_font="arial", legend_text_font_size=0.35, legend_entry_plot_direction="row", legend_box_blanking="on", legend_entry_text_width=50, ) error = "FER" if "FER" in predictor_matrix.columns else "FE" title = mv.mtext( text_line_count=4, text_line_1=f"{error} Standard Deviation", text_line_2=f"WT Code = {code}", text_line_4=" ", text_font="arial", text_font_size=0.4, ) df = predictor_matrix[["LonOBS", "LatOBS", error]] grouped_df = df.groupby(["LatOBS", "LonOBS"])[error].mean().reset_index() geo = mv.create_geo(len(grouped_df), "xyv") geo = mv.set_latitudes(geo, grouped_df["LatOBS"].to_numpy(dtype=np.float)) geo = mv.set_longitudes(geo, grouped_df["LonOBS"].to_numpy(dtype=np.float)) geo = mv.set_values(geo, grouped_df[error].to_numpy(dtype=np.float)) with NamedTemporaryFile(delete=False, suffix=".pdf") as pdf: pdf_obj = mv.pdf_output(output_name=pdf.name.replace(".pdf", "")) mv.setoutput(pdf_obj) mv.plot(coastline, symbol, legend, title, geo) return pdf.name
def build(self, data, font_size=None): font_size = self._make_font_size(font_size) label = "" if data: if not isinstance(data, list): data = [data] lines = [] lines = {"text_line_count": len(data)} for i, d_item in enumerate(data): # print(f"d_item={d_item}") if isinstance(d_item, tuple): d = d_item[0] data_id = d_item[1] else: d = d_item data_id = None param = d.ds_param_info if param is not None: if param.meta.get("typeOfLevel", "") == "surface": # lines.append(self.build_surface_fc(d.experiment.label, d.param.name, condition=cond)) lines[f"text_line_{i+1}"] = self.build_surface_fc( d.label, param.name, data_id=data_id ) else: # lines.append(self.build_upper_fc(d.experiment.label, d.param.name, condition=cond)) lines[f"text_line_{i+1}"] = self.build_upper_fc( d.label, param.name, data_id=data_id ) # print(f"line={lines}") # return mv.mtext(text_lines=lines, text_font_size=font_size) return mv.mtext(**lines, text_font_size=font_size) return mv.mtext( { "text_line_1": f"""{label} Par: <grib_info key='shortName'/> Lev: <grib_info key='level'/> (<grib_info key='levelType'/>) Step: +<grib_info key='step'/>h Valid: <grib_info key='valid-date' format='%Y-%m-%d %H'/>""", "text_font_size": font_size, } )
def plot_avg(predictor_matrix, code): coastline = mv.mcoast(map_coastline_thickness=2, map_boundaries="on", map_coastline_colour="chestnut") symbol = mv.msymb( legend="on", symbol_type="marker", symbol_table_mode="on", symbol_outline="on", symbol_min_table=[-1, -0.25, 0.25, 2], symbol_max_table=[-0.025, 0.25, 2, 1000], symbol_colour_table=[ "RGB(0.0000,0.5490,0.1882)", "black", "RGB(1.0000,0.6902,0.0000)", "red", ], symbol_marker_table=15, symbol_height_table=0.3, ) legend = mv.mlegend( legend_text_font="arial", legend_text_font_size=0.35, legend_entry_plot_direction="row", legend_box_blanking="on", legend_entry_text_width=50, ) error = "FER" if "FER" in predictor_matrix.columns else "FE" title = mv.mtext( text_line_count=4, text_line_1=f"{error} Mean", text_line_2=f"WT Code = {code}", text_line_4=" ", text_font="arial", text_font_size=0.4, ) df = predictor_matrix[["LonOBS", "LatOBS", error]] grouped_df = df.groupby(["LatOBS", "LonOBS"])[error].mean().reset_index() geo = mv.create_geo(len(grouped_df), "xyv") geo = mv.set_latitudes(geo, grouped_df["LatOBS"].to_numpy(dtype=np.float)) geo = mv.set_longitudes(geo, grouped_df["LonOBS"].to_numpy(dtype=np.float)) geo = mv.set_values(geo, grouped_df[error].to_numpy(dtype=np.float)) return plot_geo(geo, coastline, symbol, legend, title)
def test_definitions(): mcont_def = mv.mcont({'legend': True}) msymb_def = mv.msymb({'symbol_type': 'marker'}) mcoast_def = mv.mcoast({'map_coastline_land_shade': True}) mobs_def = mv.mobs({'obs_temperature': False}) mtext_def = mv.mtext({'text_font_size': '0.80'}) geoview_def = mv.geoview({'map_projection': 'polar_stereographic'}) ps_output_def = mv.ps_output({'output_name': 'test'}) assert mcont_def['LEGEND'] == 'ON' assert msymb_def['SYMBOL_TYPE'] == 'MARKER' assert mcoast_def['MAP_COASTLINE_LAND_SHADE'] == 'ON' assert mobs_def['OBS_TEMPERATURE'] == 'OFF' assert mtext_def['TEXT_FONT_SIZE'] == 0.8 assert geoview_def['MAP_PROJECTION'] == 'POLAR_STEREOGRAPHIC' assert ps_output_def['OUTPUT_NAME'] == 'test'