From 115f803d631e44c892b0d4a1afc90ea567998e33 Mon Sep 17 00:00:00 2001 From: bikegeek Date: Fri, 16 Feb 2024 17:38:51 -0700 Subject: [PATCH 01/72] Issue #383 modifications to support multiple plot types, list_stat_1 values --- .../tcmpr_plots/line/mean/tcmpr_line_mean.py | 36 ++++++++++++------- .../line/mean/tcmpr_series_line_mean.py | 2 +- .../line/median/tcmpr_line_median.py | 24 ++++++++----- .../line/median/tcmpr_series_line_median.py | 0 .../plots/tcmpr_plots/line/tcmpr_line.py | 2 +- metplotpy/plots/tcmpr_plots/tcmpr_config.py | 6 ++-- metplotpy/plots/tcmpr_plots/tcmpr_series.py | 3 +- metplotpy/plots/tcmpr_plots/tcmpr_util.py | 7 +++- 8 files changed, 51 insertions(+), 29 deletions(-) mode change 100644 => 100755 metplotpy/plots/tcmpr_plots/line/mean/tcmpr_line_mean.py mode change 100644 => 100755 metplotpy/plots/tcmpr_plots/line/mean/tcmpr_series_line_mean.py mode change 100644 => 100755 metplotpy/plots/tcmpr_plots/line/median/tcmpr_line_median.py mode change 100644 => 100755 metplotpy/plots/tcmpr_plots/line/median/tcmpr_series_line_median.py mode change 100644 => 100755 metplotpy/plots/tcmpr_plots/line/tcmpr_line.py mode change 100644 => 100755 metplotpy/plots/tcmpr_plots/tcmpr_config.py mode change 100644 => 100755 metplotpy/plots/tcmpr_plots/tcmpr_series.py mode change 100644 => 100755 metplotpy/plots/tcmpr_plots/tcmpr_util.py diff --git a/metplotpy/plots/tcmpr_plots/line/mean/tcmpr_line_mean.py b/metplotpy/plots/tcmpr_plots/line/mean/tcmpr_line_mean.py old mode 100644 new mode 100755 index 2ccb43af..71cac139 --- a/metplotpy/plots/tcmpr_plots/line/mean/tcmpr_line_mean.py +++ b/metplotpy/plots/tcmpr_plots/line/mean/tcmpr_line_mean.py @@ -5,30 +5,32 @@ class TcmprLineMean(TcmprLine): - def __init__(self, config_obj, column_info, col, case_data, input_df, baseline_data): - super().__init__(config_obj, column_info, col, case_data, input_df, None) + def __init__(self, config_obj, column_info, col, case_data, input_df, baseline_data, stat_name): + super().__init__(config_obj, column_info, col, case_data, input_df, None, stat_name) print("--------------------------------------------------------") print(f"Plotting MEAN time series by {self.config_obj.series_val_names[0]}") - self._adjust_titles() - self.series_list = self._create_series(self.input_df) + self._adjust_titles(stat_name) + self.series_list = self._create_series(self.input_df, stat_name) self.case_data = None self.cur_baseline = baseline_data['cur_baseline'] self.cur_baseline_data = baseline_data['cur_baseline_data'] self.baseline_lead_time = 'ind' self._init_hfip_baseline_for_plot() if self.config_obj.prefix is None or len(self.config_obj.prefix) == 0: - self.plot_filename = f"{self.config_obj.plot_dir}{os.path.sep}{self.config_obj.list_stat_1[0]}_mean.png" + # self.plot_filename = f"{self.config_obj.plot_dir}{os.path.sep}{self.config_obj.list_stat_1[0]}_{stat_name}_mean.png" + self.plot_filename = f"{self.config_obj.plot_dir}{os.path.sep}{stat_name}_mean.png" else: - self.plot_filename = f"{self.config_obj.plot_dir}{os.path.sep}{self.config_obj.prefix}.png" + self.plot_filename = f"{self.config_obj.plot_dir}{os.path.sep}{self.config_obj.prefix}_{stat_name}_mean.png" # remove the old file if it exist if os.path.exists(self.plot_filename): os.remove(self.plot_filename) self._create_figure() - def _adjust_titles(self): + def _adjust_titles(self, stat_name): if self.yaxis_1 is None or len(self.yaxis_1) == 0: - self.yaxis_1 = self.config_obj.list_stat_1[0] + '(' + self.col['units'] + ')' + # self.yaxis_1 = self.config_obj.list_stat_1[0] + '(' + self.col['units'] + ')' + self.yaxis_1 = stat_name + '(' + self.col['units'] + ')' if self.title is None or len(self.title) == 0: self.title = 'Mean of ' + self.col['desc'] + ' by ' \ @@ -42,17 +44,19 @@ def _init_hfip_baseline_for_plot(self): self.cur_baseline_data = self.cur_baseline_data[(self.cur_baseline_data['TYPE'] == 'CONS')] print('Plot HFIP Baseline:' + self.cur_baseline.replace('Error ', '')) - def _create_series(self, input_data): + def _create_series(self, input_data, stat_name): """ Generate all the series objects that are to be displayed as specified by the plot_disp setting in the config file. The points are all ordered by datetime. Each series object - is represented by a box in the diagram, so they also contain information + is represented by a line in the diagram, so they also contain information for plot-related/appearance-related settings (which were defined in the config file). + A series object is defined by the series_val_1 setting in the config file. Args: input_data: The input data in the form of a Pandas dataframe. This data will be subset to reflect the series data of interest. - + stat_name: Corresponds to the current list_stat_1 value (e.g. TK_ERR, ABS(AMAX_WIND-BMAX_WIND), etc.) + in the config file. Returns: a list of series objects that are to be displayed @@ -61,10 +65,16 @@ def _create_series(self, input_data): series_list = [] # add series for y1 axis - num_series_y1 = len(self.config_obj.get_series_y(1)) - for i, name in enumerate(self.config_obj.get_series_y(1)): + all_series = self.config_obj.get_series_y(1) + + # Limit the series to only the current statistic, list_stat_1 in config file + series_by_stat = [cur for cur in all_series if stat_name in cur] + + num_series_y1 = len(series_by_stat) + for i, name in enumerate(series_by_stat): if not isinstance(name, list): name = [name] + series_obj = TcmprSeriesLineMean(self.config_obj, i, input_data, series_list, name) series_list.append(series_obj) diff --git a/metplotpy/plots/tcmpr_plots/line/mean/tcmpr_series_line_mean.py b/metplotpy/plots/tcmpr_plots/line/mean/tcmpr_series_line_mean.py old mode 100644 new mode 100755 index 69dbe390..774c1cf0 --- a/metplotpy/plots/tcmpr_plots/line/mean/tcmpr_series_line_mean.py +++ b/metplotpy/plots/tcmpr_plots/line/mean/tcmpr_series_line_mean.py @@ -22,7 +22,7 @@ class TcmprSeriesLineMean(TcmprSeries): """ - Represents a Box plot series object + Represents a TCMPR mean series object of data points and their plotting style elements (line colors, etc.) diff --git a/metplotpy/plots/tcmpr_plots/line/median/tcmpr_line_median.py b/metplotpy/plots/tcmpr_plots/line/median/tcmpr_line_median.py old mode 100644 new mode 100755 index 3f234c93..ea0a49cb --- a/metplotpy/plots/tcmpr_plots/line/median/tcmpr_line_median.py +++ b/metplotpy/plots/tcmpr_plots/line/median/tcmpr_line_median.py @@ -5,20 +5,20 @@ class TcmprLineMedian(TcmprLine): - def __init__(self, config_obj, column_info, col, case_data, input_df): - super().__init__(config_obj, column_info, col, case_data, input_df, None) + def __init__(self, config_obj, column_info, col, case_data, input_df, stat_name): + super().__init__(config_obj, column_info, col, case_data, input_df, None, stat_name) print("--------------------------------------------------------") print(f"Plotting MEDIAN time series by {self.config_obj.series_val_names[0]}") print("Plot HFIP Baseline:" + self.cur_baseline) self._adjust_titles() - self.series_list = self._create_series(self.input_df) + self.series_list = self._create_series(self.input_df, stat_name) self.case_data = None if self.config_obj.prefix is None or len(self.config_obj.prefix) == 0: - self.plot_filename = f"{self.config_obj.plot_dir}{os.path.sep}{self.config_obj.list_stat_1[0]}_median.png" + self.plot_filename = f"{self.config_obj.plot_dir}{os.path.sep}{stat_name}_median.png" else: - self.plot_filename = f"{self.config_obj.plot_dir}{os.path.sep}{self.config_obj.prefix}.png" - + # self.plot_filename = f"{self.config_obj.plot_dir}{os.path.sep}{self.config_obj.prefix}.png" + self.plot_filename = f"{self.config_obj.plot_dir}{os.path.sep}{self.config_obj.prefix}_{stat_name}_median.png" # remove the old file if it exist if os.path.exists(self.plot_filename): os.remove(self.plot_filename) @@ -33,7 +33,7 @@ def _adjust_titles(self): + self.column_info[self.column_info['COLUMN'] == self.config_obj.series_val_names[0]][ "DESCRIPTION"].tolist()[0] - def _create_series(self, input_data): + def _create_series(self, input_data, stat_name): """ Generate all the series objects that are to be displayed as specified by the plot_disp setting in the config file. The points are all ordered by datetime. Each series object @@ -52,10 +52,16 @@ def _create_series(self, input_data): series_list = [] # add series for y1 axis - num_series_y1 = len(self.config_obj.get_series_y(1)) - for i, name in enumerate(self.config_obj.get_series_y(1)): + all_series = self.config_obj.get_series_y(1) + + # Limit the series to only the current statistic, list_stat_1 in config file + series_by_stat = [cur for cur in all_series if stat_name in cur] + + num_series_y1 = len(series_by_stat) + for i, name in enumerate(series_by_stat): if not isinstance(name, list): name = [name] + series_obj = TcmprSeriesLineMedian(self.config_obj, i, input_data, series_list, name) series_list.append(series_obj) diff --git a/metplotpy/plots/tcmpr_plots/line/median/tcmpr_series_line_median.py b/metplotpy/plots/tcmpr_plots/line/median/tcmpr_series_line_median.py old mode 100644 new mode 100755 diff --git a/metplotpy/plots/tcmpr_plots/line/tcmpr_line.py b/metplotpy/plots/tcmpr_plots/line/tcmpr_line.py old mode 100644 new mode 100755 index 7f5fe6a1..c79a44e9 --- a/metplotpy/plots/tcmpr_plots/line/tcmpr_line.py +++ b/metplotpy/plots/tcmpr_plots/line/tcmpr_line.py @@ -5,7 +5,7 @@ class TcmprLine(Tcmpr): - def __init__(self, config_obj, column_info, col, case_data, input_df, baseline_data): + def __init__(self, config_obj, column_info, col, case_data, input_df, baseline_data, stat_name): super().__init__(config_obj, column_info, col, case_data, input_df) def _create_figure(self): diff --git a/metplotpy/plots/tcmpr_plots/tcmpr_config.py b/metplotpy/plots/tcmpr_plots/tcmpr_config.py old mode 100644 new mode 100755 index 4c177d31..232ec1a3 --- a/metplotpy/plots/tcmpr_plots/tcmpr_config.py +++ b/metplotpy/plots/tcmpr_plots/tcmpr_config.py @@ -36,7 +36,7 @@ def __init__(self, parameters: dict) -> None: super().__init__(parameters) ############################################## - self.plot_list = self._get_plot() + self.plot_type = self._get_plot() self.tcst_files = self._get_tcst_files() self.tcst_dir = self._get_tcst_dir() self.rp_diff = self._get_rp_diff() @@ -219,9 +219,9 @@ def _get_markers_size(self) -> list: return self.create_list_by_series_ordering(markers_size) def _get_plot(self) -> list: - plot_list = self.get_config_value('plot_list') + plot_type = self.get_config_value('plot_type') # TODO validate plots BOXPLOT, POINT, MEAN, MEDIAN, RELPERF, RANK, SKILL_MN, SKILL_MD - return plot_list + return plot_type def _get_tcst_files(self) -> list: tcst_files = self.get_config_value('tcst_files') diff --git a/metplotpy/plots/tcmpr_plots/tcmpr_series.py b/metplotpy/plots/tcmpr_plots/tcmpr_series.py old mode 100644 new mode 100755 index 8ea3d5d4..f08bc4f2 --- a/metplotpy/plots/tcmpr_plots/tcmpr_series.py +++ b/metplotpy/plots/tcmpr_plots/tcmpr_series.py @@ -36,7 +36,8 @@ def __init__(self, config, idx: int, input_data, series_list: list, self.series_list = series_list self.series_name = series_name self.rank_min_val = [] - self.series_len = len(config.get_series_y(1)) + len(config.get_config_value('derived_series_1')) + # self.series_len = len(config.get_series_y(1)) + len(config.get_config_value('derived_series_1')) + self.series_len = len(self.series_list) + len(config.get_config_value('derived_series_1')) self.skill_ref_data = skill_ref_data if idx >= self.series_len: super().__init__(config, 0, input_data, 1) diff --git a/metplotpy/plots/tcmpr_plots/tcmpr_util.py b/metplotpy/plots/tcmpr_plots/tcmpr_util.py old mode 100644 new mode 100755 index 29d596e7..b9b229a4 --- a/metplotpy/plots/tcmpr_plots/tcmpr_util.py +++ b/metplotpy/plots/tcmpr_plots/tcmpr_util.py @@ -120,13 +120,18 @@ def init_hfip_baseline(config, baseline_file, input_df): all_filters = [baseline['BASIN'].isin(input_df['BASIN']), baseline['VARIABLE'].isin([stat]), baseline['LEAD_HR'].isin(input_df['LEAD_HR'])] mask = np.array(all_filters).all(axis=0) - cur_baseline_data = baseline.loc[mask] + cur_baseline_data_filtered = baseline.loc[mask] + # work on a copy to prevent the SettingWithCopyWarning + cur_baseline_data = cur_baseline_data_filtered.copy() + + # cur_baseline_data = cur_baseline_data_filtered.copy(deep=True) if config.hfip_bsln == "0": cur_baseline = "HFIP Baseline" elif config.hfip_bsln == "5": cur_baseline = 'Error Target for 20% HFIP Goal' cur_baseline_data['VALUE'] = cur_baseline_data['VALUE'].apply( lambda x: calc_util.round_half_up(x * 0.8, 1)) + else: # config.hfip_bsln == "10": cur_baseline = 'Error Target for 50% HFIP Goal' cur_baseline_data['VALUE'] = cur_baseline_data['VALUE'].apply( From 9001eb95e622d87d41a63dfe02ca2144450636b5 Mon Sep 17 00:00:00 2001 From: bikegeek Date: Fri, 16 Feb 2024 17:49:35 -0700 Subject: [PATCH 02/72] issue #383 modifications to support generating more than one plot type --- metplotpy/plots/tcmpr_plots/tcmpr.py | 107 ++++++++++++++------------- 1 file changed, 55 insertions(+), 52 deletions(-) mode change 100644 => 100755 metplotpy/plots/tcmpr_plots/tcmpr.py diff --git a/metplotpy/plots/tcmpr_plots/tcmpr.py b/metplotpy/plots/tcmpr_plots/tcmpr.py old mode 100644 new mode 100755 index 66ca3a3a..32fea75e --- a/metplotpy/plots/tcmpr_plots/tcmpr.py +++ b/metplotpy/plots/tcmpr_plots/tcmpr.py @@ -75,7 +75,7 @@ def __init__(self, config_obj, column_info, col, case_data, input_df): self.baseline_lead_time = 'lead' self.yaxis_1 = self.config_obj.yaxis_1 - self.plot_filename = f"{self.config_obj.plot_dir}{os.path.sep}{self.config_obj.list_stat_1[0]}_{self.config_obj.plot_list}.png" + self.plot_filename = f"{self.config_obj.plot_dir}{os.path.sep}{self.config_obj.list_stat_1[0]}_{self.config_obj.plot_type}.png" # Check that we have all the necessary settings for each series # TODO implement the consistency check if no series values were specified # is_config_consistent = self.config_obj._config_consistency_check() @@ -139,7 +139,7 @@ def _create_series(self, input_data): def _calc_stag_adjustments(self) -> list: """ Calculates the x-axis adjustment for each point if requested. - It needed so hte points and CIs for each x-axis values don't be placed on top of each other + It needed so the points and CIs for each x-axis values don't be placed on top of each other :return: the list of the adjustment values """ @@ -158,7 +158,7 @@ def _calc_stag_adjustments(self) -> list: return stag_vals def _add_hfip_baseline(self): - # Add HFIP baseline for each lead time + # Add baseline for each lead time if self.cur_baseline_data is not None: baseline_x_values = [] baseline_y_values = [] @@ -511,7 +511,7 @@ def main(config_filename=None): if config_obj.use_ee is True: output_data = pd.DataFrame() series = copy.deepcopy(config_obj.parameters['series_val_1']) - if 'skill_mn' in config_obj.plot_list or 'skill_md' in config_obj.plot_list: + if 'skill_mn' in config_obj.plot_type or 'skill_md' in config_obj.plot_type: series['AMODEL'].extend(config_obj.skill_ref) for series_var, series_var_vals in series.items(): @@ -533,7 +533,7 @@ def main(config_filename=None): input_df.reset_index(drop=True, inplace=True) # Define a demo and retro column - # TODO these values neve get used - maybe need to remove + # TODO these values never get used - maybe need to remove if config_obj.demo_yr is not None and config_obj.demo_yr != 'NA': demo_yr_obj = datetime.strptime(str(config_obj.demo_yr), '%Y') input_df.loc[input_df['VALID_TIME'] >= demo_yr_obj, "TYPE"] = "DEMO" @@ -546,52 +546,55 @@ def main(config_filename=None): sep=r'\s+', header='infer', quotechar='"', skipinitialspace=True, encoding='utf-8') - col_to_plot = get_dep_column(config_obj.list_stat_1[0], column_info, input_df) - input_df['PLOT'] = col_to_plot['val'] - - baseline_data = None - if common_member(config_obj.plot_list, PLOTS_WITH_BASELINE): - baseline_data = init_hfip_baseline(config_obj, config_obj.baseline_file, input_df) - - plot = None - common_case_data = None - for plot_type in config_obj.plot_list: - try: - if plot_type == 'boxplot': - from metplotpy.plots.tcmpr_plots.box.tcmpr_box import TcmprBox - plot = TcmprBox(config_obj, column_info, col_to_plot, common_case_data, input_df, baseline_data) - elif plot_type == 'point': - from metplotpy.plots.tcmpr_plots.box.tcmpr_point import TcmprPoint - plot = TcmprPoint(config_obj, column_info, col_to_plot, common_case_data, input_df, baseline_data) - elif plot_type == 'mean': - from metplotpy.plots.tcmpr_plots.line.mean.tcmpr_line_mean import TcmprLineMean - plot = TcmprLineMean(config_obj, column_info, col_to_plot, common_case_data, input_df, baseline_data) - elif plot_type == 'median': - from metplotpy.plots.tcmpr_plots.line.median.tcmpr_line_median import TcmprLineMedian - plot = TcmprLineMedian(config_obj, column_info, col_to_plot, common_case_data, input_df) - elif plot_type == 'relperf': - from metplotpy.plots.tcmpr_plots.relperf.tcmpr_relperf import TcmprRelPerf - plot = TcmprRelPerf(config_obj, column_info, col_to_plot, common_case_data, input_df) - elif plot_type == 'rank': - from metplotpy.plots.tcmpr_plots.rank.tcmpr_rank import TcmprRank - plot = TcmprRank(config_obj, column_info, col_to_plot, common_case_data, input_df) - elif plot_type == 'scatter': - from metplotpy.plots.tcmpr_plots.scatter.tcmpr_scatter import TcmprScatter - plot = TcmprScatter(config_obj, column_info, col_to_plot, common_case_data, input_df) - elif plot_type == 'skill_mn': - from metplotpy.plots.tcmpr_plots.skill.mean.tcmpr_skill_mean import TcmprSkillMean - plot = TcmprSkillMean(config_obj, column_info, col_to_plot, common_case_data, input_df, baseline_data) - elif plot_type == 'skill_md': - from metplotpy.plots.tcmpr_plots.skill.median.tcmpr_skill_median import TcmprSkillMedian - plot = TcmprSkillMedian(config_obj, column_info, col_to_plot, common_case_data, input_df) - - plot.save_to_file() - #plot.show_in_browser() - if common_case_data is None: - common_case_data = plot.case_data - - except (ValueError, Exception) as ve: - print(ve) + for cur_stat in config_obj.list_stat_1: + # col_to_plot = get_dep_column(config_obj.list_stat_1[0], column_info, input_df) + col_to_plot = get_dep_column(cur_stat, column_info, input_df) + input_df['PLOT'] = col_to_plot['val'] + + baseline_data = None + if common_member(config_obj.plot_type, PLOTS_WITH_BASELINE): + baseline_data = init_hfip_baseline(config_obj, config_obj.baseline_file, input_df) + + plot = None + common_case_data = None + for plot_type in config_obj.plot_type: + try: + if plot_type == 'boxplot': + from metplotpy.plots.tcmpr_plots.box.tcmpr_box import TcmprBox + plot = TcmprBox(config_obj, column_info, col_to_plot, common_case_data, input_df, baseline_data) + elif plot_type == 'point': + from metplotpy.plots.tcmpr_plots.box.tcmpr_point import TcmprPoint + plot = TcmprPoint(config_obj, column_info, col_to_plot, common_case_data, input_df, baseline_data) + elif plot_type == 'mean': + from metplotpy.plots.tcmpr_plots.line.mean.tcmpr_line_mean import TcmprLineMean + plot = TcmprLineMean(config_obj, column_info, col_to_plot, common_case_data, input_df, baseline_data, + cur_stat) + elif plot_type == 'median': + from metplotpy.plots.tcmpr_plots.line.median.tcmpr_line_median import TcmprLineMedian + plot = TcmprLineMedian(config_obj, column_info, col_to_plot, common_case_data, input_df, cur_stat) + elif plot_type == 'relperf': + from metplotpy.plots.tcmpr_plots.relperf.tcmpr_relperf import TcmprRelPerf + plot = TcmprRelPerf(config_obj, column_info, col_to_plot, common_case_data, input_df) + elif plot_type == 'rank': + from metplotpy.plots.tcmpr_plots.rank.tcmpr_rank import TcmprRank + plot = TcmprRank(config_obj, column_info, col_to_plot, common_case_data, input_df) + elif plot_type == 'scatter': + from metplotpy.plots.tcmpr_plots.scatter.tcmpr_scatter import TcmprScatter + plot = TcmprScatter(config_obj, column_info, col_to_plot, common_case_data, input_df) + elif plot_type == 'skill_mn': + from metplotpy.plots.tcmpr_plots.skill.mean.tcmpr_skill_mean import TcmprSkillMean + plot = TcmprSkillMean(config_obj, column_info, col_to_plot, common_case_data, input_df, baseline_data) + elif plot_type == 'skill_md': + from metplotpy.plots.tcmpr_plots.skill.median.tcmpr_skill_median import TcmprSkillMedian + plot = TcmprSkillMedian(config_obj, column_info, col_to_plot, common_case_data, input_df) + + plot.save_to_file() + #plot.show_in_browser() + if common_case_data is None: + common_case_data = plot.case_data + + except (ValueError, Exception) as ve: + print(ve) def print_data_info(input_df, series): @@ -616,7 +619,7 @@ def print_data_info(input_df, series): def read_tcst_files(config_obj, tcst_files): all_fields_values = copy.deepcopy(config_obj.parameters['series_val_1']) all_fields_values.update(config_obj.parameters['fixed_vars_vals_input']) - if 'skill_mn' in config_obj.plot_list or 'skill_md' in config_obj.plot_list: + if 'skill_mn' in config_obj.plot_type or 'skill_md' in config_obj.plot_type: all_fields_values['AMODEL'].extend(config_obj.skill_ref) input_df = None for file in tcst_files: From 992df4633be16a92b634ba22905fc56909555c60 Mon Sep 17 00:00:00 2001 From: bikegeek Date: Mon, 19 Feb 2024 13:17:39 -0700 Subject: [PATCH 03/72] issue #383 provide supporting plotting multiple plot types with single config file --- metplotpy/plots/tcmpr_plots/box/tcmpr_box.py | 20 +++++++++++--------- 1 file changed, 11 insertions(+), 9 deletions(-) mode change 100644 => 100755 metplotpy/plots/tcmpr_plots/box/tcmpr_box.py diff --git a/metplotpy/plots/tcmpr_plots/box/tcmpr_box.py b/metplotpy/plots/tcmpr_plots/box/tcmpr_box.py old mode 100644 new mode 100755 index 847c6349..24e223d2 --- a/metplotpy/plots/tcmpr_plots/box/tcmpr_box.py +++ b/metplotpy/plots/tcmpr_plots/box/tcmpr_box.py @@ -7,31 +7,33 @@ class TcmprBox(TcmprBoxPoint): - def __init__(self, config_obj, column_info, col, case_data, input_df, baseline_data): - super().__init__(config_obj, column_info, col, case_data, input_df, baseline_data) + def __init__(self, config_obj, column_info, col, case_data, input_df, baseline_data, stat_name): + super().__init__(config_obj, column_info, col, case_data, input_df, baseline_data, stat_name) print("--------------------------------------------------------") print(f"Plotting BOXPLOT time series by {self.config_obj.series_val_names[0]}") - self._adjust_titles() - self.series_list = self._create_series(self.input_df) + self._adjust_titles(stat_name) + self.series_list = self._create_series(self.input_df, stat_name) self.case_data = None self.cur_baseline = baseline_data['cur_baseline'] self.cur_baseline_data = baseline_data['cur_baseline_data'] self._init_hfip_baseline_for_plot() if self.config_obj.prefix is None or len(self.config_obj.prefix) == 0: - self.plot_filename = f"{self.config_obj.plot_dir}{os.path.sep}{self.config_obj.list_stat_1[0]}_boxplot.png" + self.plot_filename = f"{self.config_obj.plot_dir}{os.path.sep}{stat_name}_boxplot.png" else: - self.plot_filename = f"{self.config_obj.plot_dir}{os.path.sep}{self.config_obj.prefix}.png" + self.plot_filename = f"{self.config_obj.plot_dir}{os.path.sep}{self.config_obj.prefix}_{stat_name}_boxplot.png" - # remove the old file if it exist + # remove the old file if it exists if os.path.exists(self.plot_filename): os.remove(self.plot_filename) self._create_figure() - def _adjust_titles(self): + def _adjust_titles(self, stat_name): if self.yaxis_1 is None or len(self.yaxis_1) == 0: - self.yaxis_1 = self.config_obj.list_stat_1[0] + '(' + self.col['units'] + ')' + # ToDo Remove when done DEBUGGING + # self.yaxis_1 = self.config_obj.list_stat_1[0] + '(' + self.col['units'] + ')' + self.yaxis_1 = stat_name + '(' + self.col['units'] + ')' if self.title is None or len(self.title) == 0: self.title = 'Boxplots of ' + self.col['desc'] + ' by ' \ From 3371f461f78737ded6e55075040ec0e139d9999c Mon Sep 17 00:00:00 2001 From: bikegeek Date: Mon, 19 Feb 2024 13:19:33 -0700 Subject: [PATCH 04/72] issue #383 provide supporting plotting multiple plot types with single config file --- metplotpy/plots/tcmpr_plots/line/mean/tcmpr_line_mean.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/metplotpy/plots/tcmpr_plots/line/mean/tcmpr_line_mean.py b/metplotpy/plots/tcmpr_plots/line/mean/tcmpr_line_mean.py index 71cac139..237d6f83 100755 --- a/metplotpy/plots/tcmpr_plots/line/mean/tcmpr_line_mean.py +++ b/metplotpy/plots/tcmpr_plots/line/mean/tcmpr_line_mean.py @@ -25,7 +25,7 @@ def __init__(self, config_obj, column_info, col, case_data, input_df, baseline_d # remove the old file if it exist if os.path.exists(self.plot_filename): os.remove(self.plot_filename) - self._create_figure() + self._create_figure(stat_name) def _adjust_titles(self, stat_name): if self.yaxis_1 is None or len(self.yaxis_1) == 0: @@ -87,7 +87,7 @@ def _create_series(self, input_data, stat_name): if len(name) == 3: # add stat if needed oper = name[2] - name[:] = [(s + ' ' + self.config_obj.list_stat_1[0]) if ' ' not in s else s for s in name[:2]] + name[:] = [(s + ' ' + stat_name) if ' ' not in s else s for s in name[:2]] name.append(oper) series_obj = TcmprSeriesLineMean(self.config_obj, num_series_y1 + i, input_data, series_list, name) From 505fcbb66aea657426165a3ef5ef4a2040636cbc Mon Sep 17 00:00:00 2001 From: bikegeek Date: Mon, 19 Feb 2024 13:20:14 -0700 Subject: [PATCH 05/72] issue #383 provide supporting plotting multiple plot types with single config file --- metplotpy/plots/tcmpr_plots/line/median/tcmpr_line_median.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/metplotpy/plots/tcmpr_plots/line/median/tcmpr_line_median.py b/metplotpy/plots/tcmpr_plots/line/median/tcmpr_line_median.py index ea0a49cb..c8c3e6c2 100755 --- a/metplotpy/plots/tcmpr_plots/line/median/tcmpr_line_median.py +++ b/metplotpy/plots/tcmpr_plots/line/median/tcmpr_line_median.py @@ -22,7 +22,7 @@ def __init__(self, config_obj, column_info, col, case_data, input_df, stat_name) # remove the old file if it exist if os.path.exists(self.plot_filename): os.remove(self.plot_filename) - self._create_figure() + self._create_figure(stat_name) def _adjust_titles(self): if self.yaxis_1 is None or len(self.yaxis_1) == 0: @@ -74,7 +74,7 @@ def _create_series(self, input_data, stat_name): if len(name) == 3: # add stat if needed oper = name[2] - name[:] = [(s + ' ' + self.config_obj.list_stat_1[0]) if ' ' not in s else s for s in name[:2]] + name[:] = [(s + ' ' + stat_name) if ' ' not in s else s for s in name[:2]] name.append(oper) series_obj = TcmprSeriesLineMedian(self.config_obj, num_series_y1 + i, input_data, series_list, name) series_list.append(series_obj) From b4268b313229c76f7039cfd3a0b1c75be6e7ecca Mon Sep 17 00:00:00 2001 From: bikegeek Date: Mon, 19 Feb 2024 13:20:58 -0700 Subject: [PATCH 06/72] clean up comments --- metplotpy/plots/tcmpr_plots/line/tcmpr_line.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/metplotpy/plots/tcmpr_plots/line/tcmpr_line.py b/metplotpy/plots/tcmpr_plots/line/tcmpr_line.py index c79a44e9..d71c866b 100755 --- a/metplotpy/plots/tcmpr_plots/line/tcmpr_line.py +++ b/metplotpy/plots/tcmpr_plots/line/tcmpr_line.py @@ -8,7 +8,7 @@ class TcmprLine(Tcmpr): def __init__(self, config_obj, column_info, col, case_data, input_df, baseline_data, stat_name): super().__init__(config_obj, column_info, col, case_data, input_df) - def _create_figure(self): + def _create_figure(self, stat_name): """ Create a box plot from default and custom parameters""" self.figure = self._create_layout() @@ -45,7 +45,7 @@ def _create_figure(self): x_points_index_adj = x_points_index + stag_adjustments[series.idx] self._draw_series(series, x_points_index_adj) - print(f'Range of {self.config_obj.list_stat_1[0]}: {yaxis_min}, {yaxis_max}') + print(f'Range of {stat_name}: {yaxis_min}, {yaxis_max}') self._add_hfip_baseline() From 707e30580f50baef984315d21ac3ae0cc27cb932 Mon Sep 17 00:00:00 2001 From: bikegeek Date: Mon, 19 Feb 2024 13:21:37 -0700 Subject: [PATCH 07/72] issue #383 provide supporting plotting multiple plot types with single config file --- metplotpy/plots/tcmpr_plots/box/tcmpr_box_point.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) mode change 100644 => 100755 metplotpy/plots/tcmpr_plots/box/tcmpr_box_point.py diff --git a/metplotpy/plots/tcmpr_plots/box/tcmpr_box_point.py b/metplotpy/plots/tcmpr_plots/box/tcmpr_box_point.py old mode 100644 new mode 100755 index 25adecdb..bdcca284 --- a/metplotpy/plots/tcmpr_plots/box/tcmpr_box_point.py +++ b/metplotpy/plots/tcmpr_plots/box/tcmpr_box_point.py @@ -3,7 +3,7 @@ class TcmprBoxPoint(Tcmpr): - def __init__(self, config_obj, column_info, col, case_data, input_df, baseline_data): + def __init__(self, config_obj, column_info, col, case_data, input_df, baseline_data, stat_name): super().__init__(config_obj, column_info, col, case_data, input_df) def _init_hfip_baseline_for_plot(self): From 87b980e22e611696ce07fe52bad09d4aad7a6636 Mon Sep 17 00:00:00 2001 From: bikegeek Date: Mon, 19 Feb 2024 13:22:04 -0700 Subject: [PATCH 08/72] issue #383 provide supporting plotting multiple plot types with single config file --- metplotpy/plots/tcmpr_plots/box/tcmpr_point.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) mode change 100644 => 100755 metplotpy/plots/tcmpr_plots/box/tcmpr_point.py diff --git a/metplotpy/plots/tcmpr_plots/box/tcmpr_point.py b/metplotpy/plots/tcmpr_plots/box/tcmpr_point.py old mode 100644 new mode 100755 index 49315c03..d9305ee7 --- a/metplotpy/plots/tcmpr_plots/box/tcmpr_point.py +++ b/metplotpy/plots/tcmpr_plots/box/tcmpr_point.py @@ -22,7 +22,7 @@ def __init__(self, config_obj, column_info, col, case_data, input_df, baseline_d if self.config_obj.prefix is None or len(self.config_obj.prefix) == 0: self.plot_filename = f"{self.config_obj.plot_dir}{os.path.sep}{self.config_obj.list_stat_1[0]}_pointplot.png" else: - self.plot_filename = f"{self.config_obj.plot_dir}{os.path.sep}{self.config_obj.prefix}.png" + self.plot_filename = f"{self.config_obj.plot_dir}{os.path.sep}{self.config_obj.prefix}_pointplot.png" # remove the old file if it exist if os.path.exists(self.plot_filename): From 532dcc0c46ff67b2b4f8e09282c5486f3531d3f5 Mon Sep 17 00:00:00 2001 From: bikegeek Date: Mon, 19 Feb 2024 13:22:37 -0700 Subject: [PATCH 09/72] issue #383 provide supporting plotting multiple plot types with single config file --- metplotpy/plots/tcmpr_plots/rank/tcmpr_rank.py | 18 +++++++++--------- 1 file changed, 9 insertions(+), 9 deletions(-) mode change 100644 => 100755 metplotpy/plots/tcmpr_plots/rank/tcmpr_rank.py diff --git a/metplotpy/plots/tcmpr_plots/rank/tcmpr_rank.py b/metplotpy/plots/tcmpr_plots/rank/tcmpr_rank.py old mode 100644 new mode 100755 index 907b16f7..b10fb6ba --- a/metplotpy/plots/tcmpr_plots/rank/tcmpr_rank.py +++ b/metplotpy/plots/tcmpr_plots/rank/tcmpr_rank.py @@ -25,7 +25,7 @@ class TcmprRank(Tcmpr): """ - def __init__(self, config_obj, column_info, col, case_data, input_df): + def __init__(self, config_obj, column_info, col, case_data, input_df, stat_name): """ Creates a rank plot, based on settings indicated by parameters. @@ -34,7 +34,7 @@ def __init__(self, config_obj, column_info, col, case_data, input_df): """ # init common layout - super().__init__(config_obj, column_info, col, case_data, input_df) + super().__init__(config_obj, column_info, col, case_data, input_df, stat_name) print("--------------------------------------------------------") if not self.config_obj.use_ee: @@ -47,7 +47,7 @@ def __init__(self, config_obj, column_info, col, case_data, input_df): # Each series object contains all the necessary information for plotting, # such as line color, marker symbol, # line width, and criteria needed to subset the input dataframe. - self.series_list = self._create_series(self.input_df) + self.series_list = self._create_series(self.input_df, stat_name) # Get the case data when necessary if self.case_data is None: @@ -55,11 +55,11 @@ def __init__(self, config_obj, column_info, col, case_data, input_df): self.config_obj.rp_diff, len(self.series_list)) if self.config_obj.prefix is None or len(self.config_obj.prefix) == 0: - self.plot_filename = f"{self.config_obj.plot_dir}{os.path.sep}{self.config_obj.list_stat_1[0]}_rank.png" + self.plot_filename = f"{self.config_obj.plot_dir}{os.path.sep}{stat_name}_rank.png" else: - self.plot_filename = f"{self.config_obj.plot_dir}{os.path.sep}{self.config_obj.prefix}.png" + self.plot_filename = f"{self.config_obj.plot_dir}{os.path.sep}{self.config_obj.prefix}_{stat_name}_rank.png" - # remove the old file if it exist + # remove the old file if it exists if os.path.exists(self.plot_filename): os.remove(self.plot_filename) # create figure @@ -67,7 +67,7 @@ def __init__(self, config_obj, column_info, col, case_data, input_df): # Need to have a self.figure that we can pass along to # the methods in base_plot.py (BasePlot class methods) to # create binary versions of the plot. - self._create_figure() + self._create_figure(stat_name) def _adjust_titles(self): if self.yaxis_1 is None or len(self.yaxis_1) == 0: @@ -80,7 +80,7 @@ def _adjust_titles(self): "DESCRIPTION"].tolist()[0] + ' ' \ + self.col['desc'] + 'Rank Frequency' - def _create_figure(self): + def _create_figure(self, stat_name): """ Create a box plot from default and custom parameters""" self.figure = self._create_layout() @@ -126,7 +126,7 @@ def _create_figure(self): # Draw a reference line at 100/n_series self.figure.add_hline(y=100 / len(self.series_list), line_width=1, line_dash="solid", line_color="#e5e7e9") - print(f'Range of {self.config_obj.list_stat_1[0]}: {yaxis_min}, {yaxis_max}') + print(f'Range of {stat_name}: {yaxis_min}, {yaxis_max}') # Draw an invisible line to create a CI legend self.figure.add_trace( go.Scatter(x=[0], From 9cb047695c815b4118137c746d01a39b89facfd7 Mon Sep 17 00:00:00 2001 From: bikegeek Date: Mon, 19 Feb 2024 13:23:22 -0700 Subject: [PATCH 10/72] issue #383 provide supporting plotting multiple plot types with single config file --- metplotpy/plots/tcmpr_plots/tcmpr.py | 135 +++++++++++++++------------ 1 file changed, 74 insertions(+), 61 deletions(-) diff --git a/metplotpy/plots/tcmpr_plots/tcmpr.py b/metplotpy/plots/tcmpr_plots/tcmpr.py index 32fea75e..1694af24 100755 --- a/metplotpy/plots/tcmpr_plots/tcmpr.py +++ b/metplotpy/plots/tcmpr_plots/tcmpr.py @@ -37,12 +37,12 @@ class Tcmpr(BasePlot): - """ Generates a Plotly box plot for 1 or more traces + """ Generates a Plotly plot for 1 or more traces where each box is represented by a text point data file. """ - def __init__(self, config_obj, column_info, col, case_data, input_df): - """ Creates a box plot, based on + def __init__(self, config_obj, column_info, col, case_data, input_df, stat_name=None): + """ Creates a plot, based on settings indicated by parameters. Args: @@ -91,7 +91,7 @@ def __init__(self, config_obj, column_info, col, case_data, input_df): if len(self.config_obj.indy_vals) == 0 and self.config_obj.indy_var != '': self.config_obj.indy_vals = sorted(self.input_df[self.config_obj.indy_var].unique()) - def _create_series(self, input_data): + def _create_series(self, input_data, stat_name): """ Generate all the series objects that are to be displayed as specified by the plot_disp setting in the config file. The points are all ordered by datetime. Each series object @@ -101,6 +101,9 @@ def _create_series(self, input_data): Args: input_data: The input data in the form of a Pandas dataframe. This data will be subset to reflect the series data of interest. + stat_name: The name of the current 'statistic', as specified as the list_stat_1 + list of values in the configuration file (e.g. TK_ERR, ABS(AMAX_WIND-BMAX_WIND), etc.) + Default is None. Returns: a list of series objects that are to be displayed @@ -110,12 +113,19 @@ def _create_series(self, input_data): series_list = [] # add series for y1 axis - num_series_y1 = len(self.config_obj.get_series_y(1)) - for i, name in enumerate(self.config_obj.get_series_y(1)): - if not isinstance(name, list): - name = [name] - series_obj = TcmprSeries(self.config_obj, i, input_data, series_list, name) - series_list.append(series_obj) + + # Determine the series list based on the current + # list_stat_1 value (e.g. TK_ERR, ABS(AMAX_WIND-BMAX_WIND), etc.) under consideration. + all_series = self.config_obj.get_series_y(1) + + # Limit the series to only the current statistic, list_stat_1 in config file + series_by_stat = [cur for cur in all_series if stat_name in cur] + num_series_y1 = len(series_by_stat) + for i, name in enumerate(series_by_stat): + if not isinstance(name, list): + name = [name] + series_obj = TcmprSeries(self.config_obj, i, input_data, series_list, name) + series_list.append(series_obj) # add derived for y1 axis for i, name in enumerate(self.config_obj.get_config_value('derived_series_1')): @@ -126,7 +136,7 @@ def _create_series(self, input_data): if len(name) == 3: # add stat if needed oper = name[2] - name[:] = [(s + ' ' + self.config_obj.list_stat_1[0]) if ' ' not in s else s for s in name[:2]] + name[:] = [(s + ' ' + stat_name) if ' ' not in s else s for s in name[:2]] name.append(oper) series_obj = TcmprSeries(self.config_obj, num_series_y1 + i, input_data, series_list, name) series_list.append(series_obj) @@ -457,7 +467,7 @@ def find_min_max(series: TcmprSeries, yaxis_min: Union[float, None], def main(config_filename=None): """ - Generates a sample, default, box plot using a combination of + Generates a sample, default, TCMPR plot using a combination of default and custom config files on sample data found in this directory. The location of the input data is defined in either the default or custom config file. @@ -467,7 +477,6 @@ def main(config_filename=None): # Retrieve the contents of the custom config file to over-ride # or augment settings defined by the default config file. - # with open("./custom_box.yaml", 'r') as stream: if not config_filename: config_file = util.read_config_from_command_line() else: @@ -547,54 +556,58 @@ def main(config_filename=None): quotechar='"', skipinitialspace=True, encoding='utf-8') for cur_stat in config_obj.list_stat_1: - # col_to_plot = get_dep_column(config_obj.list_stat_1[0], column_info, input_df) - col_to_plot = get_dep_column(cur_stat, column_info, input_df) - input_df['PLOT'] = col_to_plot['val'] - - baseline_data = None - if common_member(config_obj.plot_type, PLOTS_WITH_BASELINE): - baseline_data = init_hfip_baseline(config_obj, config_obj.baseline_file, input_df) - - plot = None - common_case_data = None - for plot_type in config_obj.plot_type: - try: - if plot_type == 'boxplot': - from metplotpy.plots.tcmpr_plots.box.tcmpr_box import TcmprBox - plot = TcmprBox(config_obj, column_info, col_to_plot, common_case_data, input_df, baseline_data) - elif plot_type == 'point': - from metplotpy.plots.tcmpr_plots.box.tcmpr_point import TcmprPoint - plot = TcmprPoint(config_obj, column_info, col_to_plot, common_case_data, input_df, baseline_data) - elif plot_type == 'mean': - from metplotpy.plots.tcmpr_plots.line.mean.tcmpr_line_mean import TcmprLineMean - plot = TcmprLineMean(config_obj, column_info, col_to_plot, common_case_data, input_df, baseline_data, - cur_stat) - elif plot_type == 'median': - from metplotpy.plots.tcmpr_plots.line.median.tcmpr_line_median import TcmprLineMedian - plot = TcmprLineMedian(config_obj, column_info, col_to_plot, common_case_data, input_df, cur_stat) - elif plot_type == 'relperf': - from metplotpy.plots.tcmpr_plots.relperf.tcmpr_relperf import TcmprRelPerf - plot = TcmprRelPerf(config_obj, column_info, col_to_plot, common_case_data, input_df) - elif plot_type == 'rank': - from metplotpy.plots.tcmpr_plots.rank.tcmpr_rank import TcmprRank - plot = TcmprRank(config_obj, column_info, col_to_plot, common_case_data, input_df) - elif plot_type == 'scatter': - from metplotpy.plots.tcmpr_plots.scatter.tcmpr_scatter import TcmprScatter - plot = TcmprScatter(config_obj, column_info, col_to_plot, common_case_data, input_df) - elif plot_type == 'skill_mn': - from metplotpy.plots.tcmpr_plots.skill.mean.tcmpr_skill_mean import TcmprSkillMean - plot = TcmprSkillMean(config_obj, column_info, col_to_plot, common_case_data, input_df, baseline_data) - elif plot_type == 'skill_md': - from metplotpy.plots.tcmpr_plots.skill.median.tcmpr_skill_median import TcmprSkillMedian - plot = TcmprSkillMedian(config_obj, column_info, col_to_plot, common_case_data, input_df) - - plot.save_to_file() - #plot.show_in_browser() - if common_case_data is None: - common_case_data = plot.case_data - - except (ValueError, Exception) as ve: - print(ve) + # col_to_plot = get_dep_column(config_obj.list_stat_1[0], column_info, input_df) + col_to_plot = get_dep_column(cur_stat, column_info, input_df) + input_df['PLOT'] = col_to_plot['val'] + + baseline_data = None + if common_member(config_obj.plot_type, PLOTS_WITH_BASELINE): + baseline_data = init_hfip_baseline(config_obj, config_obj.baseline_file, input_df) + + plot = None + common_case_data = None + for plot_type in config_obj.plot_type: + try: + if plot_type == 'boxplot': + from metplotpy.plots.tcmpr_plots.box.tcmpr_box import TcmprBox + plot = TcmprBox(config_obj, column_info, col_to_plot, common_case_data, input_df, baseline_data, + cur_stat) + elif plot_type == 'point': + from metplotpy.plots.tcmpr_plots.box.tcmpr_point import TcmprPoint + plot = TcmprPoint(config_obj, column_info, col_to_plot, common_case_data, input_df, baseline_data, + cur_stat) + elif plot_type == 'mean': + from metplotpy.plots.tcmpr_plots.line.mean.tcmpr_line_mean import TcmprLineMean + plot = TcmprLineMean(config_obj, column_info, col_to_plot, common_case_data, input_df, + baseline_data, + cur_stat) + elif plot_type == 'median': + from metplotpy.plots.tcmpr_plots.line.median.tcmpr_line_median import TcmprLineMedian + plot = TcmprLineMedian(config_obj, column_info, col_to_plot, common_case_data, input_df, cur_stat) + elif plot_type == 'relperf': + from metplotpy.plots.tcmpr_plots.relperf.tcmpr_relperf import TcmprRelPerf + plot = TcmprRelPerf(config_obj, column_info, col_to_plot, common_case_data, input_df, cur_stat) + elif plot_type == 'rank': + from metplotpy.plots.tcmpr_plots.rank.tcmpr_rank import TcmprRank + plot = TcmprRank(config_obj, column_info, col_to_plot, common_case_data, input_df, cur_stat) + elif plot_type == 'scatter': + from metplotpy.plots.tcmpr_plots.scatter.tcmpr_scatter import TcmprScatter + plot = TcmprScatter(config_obj, column_info, col_to_plot, common_case_data, input_df, cur_stat) + elif plot_type == 'skill_mn': + from metplotpy.plots.tcmpr_plots.skill.mean.tcmpr_skill_mean import TcmprSkillMean + plot = TcmprSkillMean(config_obj, column_info, col_to_plot, common_case_data, input_df, + baseline_data, cur_stat) + elif plot_type == 'skill_md': + from metplotpy.plots.tcmpr_plots.skill.median.tcmpr_skill_median import TcmprSkillMedian + plot = TcmprSkillMedian(config_obj, column_info, col_to_plot, common_case_data, cur_stat, input_df) + + plot.save_to_file() + # plot.show_in_browser() + if common_case_data is None: + common_case_data = plot.case_data + + except (ValueError, Exception) as ve: + print(ve) def print_data_info(input_df, series): From 375c4299ea480ea626fdfb0e4426d91c39c5bb1c Mon Sep 17 00:00:00 2001 From: bikegeek Date: Mon, 19 Feb 2024 13:27:02 -0700 Subject: [PATCH 11/72] fix colors and legends --- metplotpy/plots/tcmpr_plots/tcmpr_series.py | 3 +-- 1 file changed, 1 insertion(+), 2 deletions(-) diff --git a/metplotpy/plots/tcmpr_plots/tcmpr_series.py b/metplotpy/plots/tcmpr_plots/tcmpr_series.py index f08bc4f2..8ea3d5d4 100755 --- a/metplotpy/plots/tcmpr_plots/tcmpr_series.py +++ b/metplotpy/plots/tcmpr_plots/tcmpr_series.py @@ -36,8 +36,7 @@ def __init__(self, config, idx: int, input_data, series_list: list, self.series_list = series_list self.series_name = series_name self.rank_min_val = [] - # self.series_len = len(config.get_series_y(1)) + len(config.get_config_value('derived_series_1')) - self.series_len = len(self.series_list) + len(config.get_config_value('derived_series_1')) + self.series_len = len(config.get_series_y(1)) + len(config.get_config_value('derived_series_1')) self.skill_ref_data = skill_ref_data if idx >= self.series_len: super().__init__(config, 0, input_data, 1) From df9bd8ba99cd3c3388c9b98deea3d9d126eb4f1e Mon Sep 17 00:00:00 2001 From: bikegeek Date: Thu, 7 Mar 2024 16:01:15 -0700 Subject: [PATCH 12/72] issue #383 add logging to replace printing to stdout --- metplotpy/plots/tcmpr_plots/box/tcmpr_box.py | 16 ++++++++++++-- .../plots/tcmpr_plots/box/tcmpr_box_point.py | 22 ++++++++++++++----- 2 files changed, 30 insertions(+), 8 deletions(-) diff --git a/metplotpy/plots/tcmpr_plots/box/tcmpr_box.py b/metplotpy/plots/tcmpr_plots/box/tcmpr_box.py index 24e223d2..ec086111 100755 --- a/metplotpy/plots/tcmpr_plots/box/tcmpr_box.py +++ b/metplotpy/plots/tcmpr_plots/box/tcmpr_box.py @@ -1,17 +1,22 @@ import os +from datetime import datetime import plotly.graph_objects as go from metplotpy.plots.tcmpr_plots.box.tcmpr_box_point import TcmprBoxPoint from metplotpy.plots.tcmpr_plots.tcmpr_series import TcmprSeries +import metplotpy.plots.util as util class TcmprBox(TcmprBoxPoint): def __init__(self, config_obj, column_info, col, case_data, input_df, baseline_data, stat_name): super().__init__(config_obj, column_info, col, case_data, input_df, baseline_data, stat_name) - print("--------------------------------------------------------") - print(f"Plotting BOXPLOT time series by {self.config_obj.series_val_names[0]}") + # Set up Logging + self.box_logger = util.get_common_logger(self.config_obj.log_level, self.config_obj.log_filename) + + self.box_logger.info(f"--------------------------------------------------------\n") + self.box_logger.info(f"Plotting BOXPLOT time series by {self.config_obj.series_val_names[0]}") self._adjust_titles(stat_name) self.series_list = self._create_series(self.input_df, stat_name) self.case_data = None @@ -24,6 +29,8 @@ def __init__(self, config_obj, column_info, col, case_data, input_df, baseline_d else: self.plot_filename = f"{self.config_obj.plot_dir}{os.path.sep}{self.config_obj.prefix}_{stat_name}_boxplot.png" + self.box_logger.info(f"Plot will be saved as {self.plot_filename}") + # remove the old file if it exists if os.path.exists(self.plot_filename): os.remove(self.plot_filename) @@ -47,6 +54,7 @@ def _draw_series(self, series: TcmprSeries) -> None: :param series: Line series object with data and parameters """ + start_time = datetime.now() # defaults markers and colors for the regular box plot line_color = dict(color='rgb(0,0,0)') marker_color = series.color @@ -89,3 +97,7 @@ def _draw_series(self, series: TcmprSeries) -> None: ), secondary_y=series.y_axis != 1 ) + + end_time = datetime.now() + total_time = end_time - start_time + self.box_logger.debug(f"Drawing series points took {total_time} millisecs") diff --git a/metplotpy/plots/tcmpr_plots/box/tcmpr_box_point.py b/metplotpy/plots/tcmpr_plots/box/tcmpr_box_point.py index bdcca284..bff7b448 100755 --- a/metplotpy/plots/tcmpr_plots/box/tcmpr_box_point.py +++ b/metplotpy/plots/tcmpr_plots/box/tcmpr_box_point.py @@ -1,24 +1,30 @@ +import datetime + from metplotpy.plots.tcmpr_plots.tcmpr import Tcmpr from metplotpy.plots.tcmpr_plots.tcmpr_series import TcmprSeries - +import metplotpy.plots.util as util class TcmprBoxPoint(Tcmpr): def __init__(self, config_obj, column_info, col, case_data, input_df, baseline_data, stat_name): - super().__init__(config_obj, column_info, col, case_data, input_df) + super().__init__(config_obj, column_info, col, case_data, input_df, stat_name) + # Set up Logging + self.box_point_logger = util.get_common_logger(self.config_obj.log_level, self.config_obj.log_filename) + self.series_len = len(config_obj.get_series_y(1)) + len(config_obj.get_config_value('derived_series_1')) + def _init_hfip_baseline_for_plot(self): if 'Water Only' in self.config_obj.title or self.cur_baseline == 'no': - print("Plot HFIP Baseline:" + self.cur_baseline) + self.box_point_logger.info(f"Plot HFIP Baseline: {self.cur_baseline}") else: self.cur_baseline_data = self.cur_baseline_data[(self.cur_baseline_data['TYPE'] == 'CONS')] - print('Plot HFIP Baseline:' + self.cur_baseline.replace('Error ', '')) + self.box_point_logger.info(f"Plot HFIP Baseline: {self.cur_baseline.replace('Error ', '')}") def _draw_series(self, series: TcmprSeries) -> None: pass def _create_figure(self): """ Create a box plot from default and custom parameters""" - + start_time = datetime.datetime.now() self.figure = self._create_layout() self._add_xaxis() self._add_yaxis() @@ -48,7 +54,7 @@ def _create_figure(self): yaxis_min, yaxis_max = self.find_min_max(series, yaxis_min, yaxis_max) self._draw_series(series) - print(f'Range of {self.config_obj.list_stat_1[0]}: {yaxis_min}, {yaxis_max}') + self.box_point_logger.info(f'Range of {self.config_obj.list_stat_1[0]}: {yaxis_min}, {yaxis_max}') self._add_hfip_baseline() self.figure.update_layout(shapes=[dict( @@ -73,3 +79,7 @@ def _create_figure(self): # add x2 axis self._add_x2axis(self.config_obj.indy_vals) + end_time = datetime.datetime.now() + total_time = end_time - start_time + self.box_point_logger.info(f"Took {total_time} millisecs to create a boxplot") + From 7a366d4be17a52b9fdd291657a8ccfcfa4199b67 Mon Sep 17 00:00:00 2001 From: bikegeek Date: Thu, 7 Mar 2024 16:01:57 -0700 Subject: [PATCH 13/72] issue #383 add logging support --- .../plots/tcmpr_plots/line/tcmpr_line.py | 23 ++++++++++++++++--- 1 file changed, 20 insertions(+), 3 deletions(-) diff --git a/metplotpy/plots/tcmpr_plots/line/tcmpr_line.py b/metplotpy/plots/tcmpr_plots/line/tcmpr_line.py index d71c866b..f759e839 100755 --- a/metplotpy/plots/tcmpr_plots/line/tcmpr_line.py +++ b/metplotpy/plots/tcmpr_plots/line/tcmpr_line.py @@ -1,16 +1,22 @@ import plotly.graph_objects as go +from datetime import datetime from metplotpy.plots.tcmpr_plots.tcmpr import Tcmpr from metplotpy.plots.tcmpr_plots.tcmpr_series import TcmprSeries - +import metplotpy.plots.util as util class TcmprLine(Tcmpr): def __init__(self, config_obj, column_info, col, case_data, input_df, baseline_data, stat_name): - super().__init__(config_obj, column_info, col, case_data, input_df) + super().__init__(config_obj, column_info, col, case_data, input_df, stat_name) + + # Set up Logging + self.line_logger = util.get_common_logger(self.config_obj.log_level, self.config_obj.log_filename) def _create_figure(self, stat_name): """ Create a box plot from default and custom parameters""" + start_time = datetime.now() + self.figure = self._create_layout() self._add_xaxis() self._add_yaxis() @@ -45,7 +51,7 @@ def _create_figure(self, stat_name): x_points_index_adj = x_points_index + stag_adjustments[series.idx] self._draw_series(series, x_points_index_adj) - print(f'Range of {stat_name}: {yaxis_min}, {yaxis_max}') + self.line_logger.info(f'Range of {stat_name}: {yaxis_min}, {yaxis_max}') self._add_hfip_baseline() @@ -70,6 +76,10 @@ def _create_figure(self, stat_name): # add x2 axis self._add_x2axis(list(range(0, len(self.config_obj.indy_vals)))) + end_time = datetime.now() + total_time = end_time - start_time + self.line_logger.info(f"Took {total_time} milliseconds to create figure for {stat_name}") + def _draw_series(self, series: TcmprSeries, x_points_index_adj: list) -> None: """ Draws the boxes on the plot @@ -77,6 +87,8 @@ def _draw_series(self, series: TcmprSeries, x_points_index_adj: list) -> None: :param series: Line series object with data and parameters """ + start_time = datetime.now() + y_points = series.series_points['val'] # show or not ci # see if any ci values in not 0 @@ -110,3 +122,8 @@ def _draw_series(self, series: TcmprSeries, x_points_index_adj: list) -> None: ), secondary_y=series.y_axis != 1 ) + + end_time = datetime.now() + total_time = end_time - start_time + self.line_logger.info( + f"Took {total_time} milliseconds to draw the series for one of the series values in: {series.series_vals_1}") \ No newline at end of file From 14b15a9fba4febc5a8da1511b07a780abcdbec5c Mon Sep 17 00:00:00 2001 From: bikegeek Date: Thu, 7 Mar 2024 16:03:48 -0700 Subject: [PATCH 14/72] issue #383 added logging support --- .../tcmpr_plots/line/mean/tcmpr_line_mean.py | 28 +++++++++++++------ .../line/mean/tcmpr_series_line_mean.py | 13 +++++++-- 2 files changed, 31 insertions(+), 10 deletions(-) diff --git a/metplotpy/plots/tcmpr_plots/line/mean/tcmpr_line_mean.py b/metplotpy/plots/tcmpr_plots/line/mean/tcmpr_line_mean.py index 237d6f83..e73a9608 100755 --- a/metplotpy/plots/tcmpr_plots/line/mean/tcmpr_line_mean.py +++ b/metplotpy/plots/tcmpr_plots/line/mean/tcmpr_line_mean.py @@ -1,14 +1,20 @@ import os +from datetime import datetime from metplotpy.plots.tcmpr_plots.line.mean.tcmpr_series_line_mean import TcmprSeriesLineMean from metplotpy.plots.tcmpr_plots.line.tcmpr_line import TcmprLine +import metplotpy.plots.util as util class TcmprLineMean(TcmprLine): def __init__(self, config_obj, column_info, col, case_data, input_df, baseline_data, stat_name): - super().__init__(config_obj, column_info, col, case_data, input_df, None, stat_name) - print("--------------------------------------------------------") - print(f"Plotting MEAN time series by {self.config_obj.series_val_names[0]}") + super().__init__(config_obj, column_info, col, case_data, input_df, baseline_data, stat_name) + + # Set up Logging + self.line_logger = util.get_common_logger(self.config_obj.log_level, self.config_obj.log_filename) + + self.line_logger.info(f"--------------------------------------------------------") + self.line_logger.info(f"Plotting MEAN time series by {self.config_obj.series_val_names[0]}") self._adjust_titles(stat_name) self.series_list = self._create_series(self.input_df, stat_name) @@ -18,11 +24,10 @@ def __init__(self, config_obj, column_info, col, case_data, input_df, baseline_d self.baseline_lead_time = 'ind' self._init_hfip_baseline_for_plot() if self.config_obj.prefix is None or len(self.config_obj.prefix) == 0: - # self.plot_filename = f"{self.config_obj.plot_dir}{os.path.sep}{self.config_obj.list_stat_1[0]}_{stat_name}_mean.png" self.plot_filename = f"{self.config_obj.plot_dir}{os.path.sep}{stat_name}_mean.png" else: self.plot_filename = f"{self.config_obj.plot_dir}{os.path.sep}{self.config_obj.prefix}_{stat_name}_mean.png" - # remove the old file if it exist + # remove the old file if it exists if os.path.exists(self.plot_filename): os.remove(self.plot_filename) self._create_figure(stat_name) @@ -39,10 +44,10 @@ def _adjust_titles(self, stat_name): def _init_hfip_baseline_for_plot(self): if 'Water Only' in self.config_obj.title or self.cur_baseline == 'no': - print("Plot HFIP Baseline:" + self.cur_baseline) + self.line_logger.info(f"Plot HFIP Baseline: {self.cur_baseline}") else: self.cur_baseline_data = self.cur_baseline_data[(self.cur_baseline_data['TYPE'] == 'CONS')] - print('Plot HFIP Baseline:' + self.cur_baseline.replace('Error ', '')) + self.line_logger.info(f"Plot HFIP Baseline: {self.cur_baseline.replace('Error ', '')}") def _create_series(self, input_data, stat_name): """ @@ -62,6 +67,9 @@ def _create_series(self, input_data, stat_name): """ + + start_time = datetime.now() + series_list = [] # add series for y1 axis @@ -75,7 +83,7 @@ def _create_series(self, input_data, stat_name): if not isinstance(name, list): name = [name] - series_obj = TcmprSeriesLineMean(self.config_obj, i, input_data, series_list, name) + series_obj = TcmprSeriesLineMean(self.config_obj, i, input_data, series_list, name, stat_name) series_list.append(series_obj) # add derived for y1 axis @@ -96,4 +104,8 @@ def _create_series(self, input_data, stat_name): # reorder series series_list = self.config_obj.create_list_by_series_ordering(series_list) + end_time = datetime.now() + total_time = end_time - start_time + self.line_logger.info(f"Took {total_time} milliseconds to create series for {stat_name}") + return series_list diff --git a/metplotpy/plots/tcmpr_plots/line/mean/tcmpr_series_line_mean.py b/metplotpy/plots/tcmpr_plots/line/mean/tcmpr_series_line_mean.py index 774c1cf0..cc013ca6 100755 --- a/metplotpy/plots/tcmpr_plots/line/mean/tcmpr_series_line_mean.py +++ b/metplotpy/plots/tcmpr_plots/line/mean/tcmpr_series_line_mean.py @@ -12,12 +12,14 @@ """ from typing import Union +from datetime import datetime import numpy as np import metcalcpy.util.utils as utils from metplotpy.plots.tcmpr_plots.tcmpr_series import TcmprSeries from metplotpy.plots.tcmpr_plots.tcmpr_util import get_mean_ci +import metplotpy.plots.util as util class TcmprSeriesLineMean(TcmprSeries): @@ -29,8 +31,11 @@ class TcmprSeriesLineMean(TcmprSeries): """ def __init__(self, config, idx: int, input_data, series_list: list, - series_name: Union[list, tuple]): - super().__init__(config, idx, input_data, series_list, series_name) + series_name: Union[list, tuple], stat_name): + super().__init__(config, idx, input_data, series_list, series_name, stat_name) + + # Set up Logging + self.seriesmn_logger = util.get_common_logger(config.log_level, config.log_filename) def _create_series_points(self) -> dict: """ @@ -43,6 +48,7 @@ def _create_series_points(self) -> dict: dictionary with CI ,point values and number of stats as keys """ + start_time = datetime.now() self._init_series_data() series_points_results = {'val': [], 'ncl': [], 'ncu': [], 'nstat': [], 'mean': []} @@ -76,4 +82,7 @@ def _create_series_points(self) -> dict: else: series_points_results['mean'].append(np.nanmean(point_data['PLOT'].tolist())) + end_time = datetime.now() + total_time = end_time - start_time + # self.seriesmn_logger.info(f"Took {total_time} milliseconds to calculate series points for line mean plot.") return series_points_results From 88029a621d942804f0e07dfad7c8f94b095e8ac6 Mon Sep 17 00:00:00 2001 From: bikegeek Date: Thu, 7 Mar 2024 16:05:22 -0700 Subject: [PATCH 15/72] issue #383 modifications to support plotting multiple plot types using one config file and logging to replace printing to stdout --- .../line/median/tcmpr_line_median.py | 32 +++++++++++++------ .../line/median/tcmpr_series_line_median.py | 4 +-- 2 files changed, 24 insertions(+), 12 deletions(-) diff --git a/metplotpy/plots/tcmpr_plots/line/median/tcmpr_line_median.py b/metplotpy/plots/tcmpr_plots/line/median/tcmpr_line_median.py index c8c3e6c2..a5cced49 100755 --- a/metplotpy/plots/tcmpr_plots/line/median/tcmpr_line_median.py +++ b/metplotpy/plots/tcmpr_plots/line/median/tcmpr_line_median.py @@ -1,32 +1,37 @@ import os +from datetime import datetime from metplotpy.plots.tcmpr_plots.line.median.tcmpr_series_line_median import TcmprSeriesLineMedian from metplotpy.plots.tcmpr_plots.line.tcmpr_line import TcmprLine +import metplotpy.plots.util as util class TcmprLineMedian(TcmprLine): def __init__(self, config_obj, column_info, col, case_data, input_df, stat_name): - super().__init__(config_obj, column_info, col, case_data, input_df, None, stat_name) - print("--------------------------------------------------------") - print(f"Plotting MEDIAN time series by {self.config_obj.series_val_names[0]}") + super().__init__(config_obj, column_info, col, case_data, input_df,stat_name, None ) - print("Plot HFIP Baseline:" + self.cur_baseline) - self._adjust_titles() + # Set up Logging + self.linemd_logger = util.get_common_logger(self.config_obj.log_level, self.config_obj.log_filename) + + self.linemd_logger.info(f"--------------------------------------------------------") + self.linemd_logger.info(f"Plotting MEDIAN time series by {self.config_obj.series_val_names[0]}") + + self.linemd_logger.info(f"Plot HFIP Baseline: {self.cur_baseline}") + self._adjust_titles(stat_name) self.series_list = self._create_series(self.input_df, stat_name) self.case_data = None if self.config_obj.prefix is None or len(self.config_obj.prefix) == 0: self.plot_filename = f"{self.config_obj.plot_dir}{os.path.sep}{stat_name}_median.png" else: - # self.plot_filename = f"{self.config_obj.plot_dir}{os.path.sep}{self.config_obj.prefix}.png" self.plot_filename = f"{self.config_obj.plot_dir}{os.path.sep}{self.config_obj.prefix}_{stat_name}_median.png" - # remove the old file if it exist + # remove the old file if it exists if os.path.exists(self.plot_filename): os.remove(self.plot_filename) self._create_figure(stat_name) - def _adjust_titles(self): + def _adjust_titles(self, stat_name): if self.yaxis_1 is None or len(self.yaxis_1) == 0: - self.yaxis_1 = self.config_obj.list_stat_1[0] + '(' + self.col['units'] + ')' + self.yaxis_1 = stat_name + '(' + self.col['units'] + ')' if self.title is None or len(self.title) == 0: self.title = 'Median of ' + self.col['desc'] + ' by ' \ @@ -49,6 +54,9 @@ def _create_series(self, input_data, stat_name): """ + + start_time = datetime.now() + series_list = [] # add series for y1 axis @@ -62,7 +70,7 @@ def _create_series(self, input_data, stat_name): if not isinstance(name, list): name = [name] - series_obj = TcmprSeriesLineMedian(self.config_obj, i, input_data, series_list, name) + series_obj = TcmprSeriesLineMedian(self.config_obj, i, input_data, series_list, name, stat_name) series_list.append(series_obj) # add derived for y1 axis @@ -82,4 +90,8 @@ def _create_series(self, input_data, stat_name): # reorder series series_list = self.config_obj.create_list_by_series_ordering(series_list) + end_time = datetime.now() + total_time = end_time - start_time + self.linemd_logger.info(f"Took {total_time} milliseconds to create series for {stat_name}") + return series_list diff --git a/metplotpy/plots/tcmpr_plots/line/median/tcmpr_series_line_median.py b/metplotpy/plots/tcmpr_plots/line/median/tcmpr_series_line_median.py index 1e2ebfd9..77e22742 100755 --- a/metplotpy/plots/tcmpr_plots/line/median/tcmpr_series_line_median.py +++ b/metplotpy/plots/tcmpr_plots/line/median/tcmpr_series_line_median.py @@ -27,9 +27,9 @@ class TcmprSeriesLineMedian(TcmprSeries): """ def __init__(self, config, idx: int, input_data, series_list: list, - series_name: Union[list, tuple]): + series_name: Union[list, tuple], stat_name): - super().__init__(config, idx, input_data, series_list, series_name) + super().__init__(config, idx, input_data, series_list, series_name, stat_name) def _create_series_points(self) -> dict: """ From b9e588ce52c22e049880e274d928015493d6ed0e Mon Sep 17 00:00:00 2001 From: bikegeek Date: Thu, 7 Mar 2024 16:07:46 -0700 Subject: [PATCH 16/72] issue #383 modifications to support multiple plot types in one config file, logging support added to replace print statements --- .../plots/tcmpr_plots/rank/tcmpr_rank.py | 41 +++++++++++++++---- 1 file changed, 32 insertions(+), 9 deletions(-) diff --git a/metplotpy/plots/tcmpr_plots/rank/tcmpr_rank.py b/metplotpy/plots/tcmpr_plots/rank/tcmpr_rank.py index b10fb6ba..8d348dcc 100755 --- a/metplotpy/plots/tcmpr_plots/rank/tcmpr_rank.py +++ b/metplotpy/plots/tcmpr_plots/rank/tcmpr_rank.py @@ -12,12 +12,15 @@ """ import os +import datetime import plotly.graph_objects as go from metplotpy.plots.tcmpr_plots.tcmpr import Tcmpr +from metplotpy.plots.tcmpr_plots.tcmpr_config import TcmprConfig from metplotpy.plots.tcmpr_plots.tcmpr_series import TcmprSeries from metplotpy.plots.tcmpr_plots.tcmpr_util import get_case_data +import metplotpy.plots.util as util class TcmprRank(Tcmpr): @@ -35,14 +38,19 @@ def __init__(self, config_obj, column_info, col, case_data, input_df, stat_name) # init common layout super().__init__(config_obj, column_info, col, case_data, input_df, stat_name) - print("--------------------------------------------------------") + + + # Set up Logging + self.rank_logger = util.get_common_logger(self.config_obj.log_level, self.config_obj.log_filename) + + self.rank_logger.info(f"--------------------------------------------------------") if not self.config_obj.use_ee: raise Exception("ERROR: Cannot plot relative rank frequency when event equalization is disabled.") - print("Creating Rank plot") - print("Plot HFIP Baseline:" + self.cur_baseline) + self.rank_logger.info("Creating Rank plot") + self.rank_logger.info("Plot HFIP Baseline:" + self.cur_baseline) - self._adjust_titles() + self._adjust_titles(stat_name) # Create a list of series objects. # Each series object contains all the necessary information for plotting, # such as line color, marker symbol, @@ -51,6 +59,7 @@ def __init__(self, config_obj, column_info, col, case_data, input_df, stat_name) # Get the case data when necessary if self.case_data is None: + self.rank_logger.info("Getting case data") self.case_data = get_case_data(self.input_df, self.config_obj.series_vals_1, self.config_obj.indy_vals, self.config_obj.rp_diff, len(self.series_list)) @@ -58,6 +67,7 @@ def __init__(self, config_obj, column_info, col, case_data, input_df, stat_name) self.plot_filename = f"{self.config_obj.plot_dir}{os.path.sep}{stat_name}_rank.png" else: self.plot_filename = f"{self.config_obj.plot_dir}{os.path.sep}{self.config_obj.prefix}_{stat_name}_rank.png" + self.rank_logger.info(f"Plot will be saved as {self.plot_filename}" ) # remove the old file if it exists if os.path.exists(self.plot_filename): @@ -67,11 +77,13 @@ def __init__(self, config_obj, column_info, col, case_data, input_df, stat_name) # Need to have a self.figure that we can pass along to # the methods in base_plot.py (BasePlot class methods) to # create binary versions of the plot. + self.rank_logger.info(f"Creating figure {datetime.datetime.now()}") self._create_figure(stat_name) - def _adjust_titles(self): + + def _adjust_titles(self, stat_name): if self.yaxis_1 is None or len(self.yaxis_1) == 0: - self.yaxis_1 = 'Percent of Cases' + self.yaxis_1 = f'Percent of Cases for {stat_name}' if self.title is None or len(self.title) == 0: self.title = self.config_obj.series_vals_1[0][0] + ' ' + \ @@ -81,8 +93,10 @@ def _adjust_titles(self): + self.col['desc'] + 'Rank Frequency' def _create_figure(self, stat_name): - """ Create a box plot from default and custom parameters""" + self.rank_logger.info(f"Creating the rank plot figure...") + """ Create a box plot from default and custom parameters""" + start_time = datetime.datetime.now() self.figure = self._create_layout() self._add_xaxis() self._add_yaxis() @@ -114,19 +128,20 @@ def _create_figure(self, stat_name): self.config_obj.user_legends = legend_str yaxis_min = None yaxis_max = None - for series in self.series_list: + for idx, series in enumerate(self.series_list): # Don't generate the plot for this series if # it isn't requested (as set in the config file) if series.plot_disp: x_points_index_adj = x_points_index + stag_adjustments[series.idx] series.create_rank_points(self.case_data) yaxis_min, yaxis_max = self.find_min_max(series, yaxis_min, yaxis_max) + self.rank_logger.info(f"Drawing series for {stat_name} and {series.series_vals_1[idx-1][idx]}") self._draw_series(series, x_points_index_adj) # Draw a reference line at 100/n_series self.figure.add_hline(y=100 / len(self.series_list), line_width=1, line_dash="solid", line_color="#e5e7e9") - print(f'Range of {stat_name}: {yaxis_min}, {yaxis_max}') + self.rank_logger.info(f'Range of {stat_name}: {yaxis_min}, {yaxis_max}') # Draw an invisible line to create a CI legend self.figure.add_trace( go.Scatter(x=[0], @@ -152,6 +167,10 @@ def _create_figure(self, stat_name): # add x2 axis self._add_x2axis(list(range(0, len(self.config_obj.indy_vals)))) + end_time = datetime.datetime.now() + total_time = end_time - start_time + self.rank_logger.info(f"Creating rank plot figure took {total_time} milliseconds") + def _draw_series(self, series: TcmprSeries, x_points_index_adj: list) -> None: """ Draws the line on the plot @@ -159,6 +178,7 @@ def _draw_series(self, series: TcmprSeries, x_points_index_adj: list) -> None: :param series: Line series object with data and parameters """ + start_time = datetime.datetime.now() color = self.config_obj.colors_list[series.idx] width = self.config_obj.linewidth_list[series.idx] dash = self.config_obj.linestyles_list[series.idx] @@ -238,3 +258,6 @@ def _draw_series(self, series: TcmprSeries, x_points_index_adj: list) -> None: ), secondary_y=series.y_axis != 1 ) + end_time = datetime.datetime.now() + total_time = end_time - start_time + self.rank_logger.debug(f"Drawing series points took {total_time} millisecs") \ No newline at end of file From 4a704cd6b6d66a06203aa60e08396400dc46c880 Mon Sep 17 00:00:00 2001 From: bikegeek Date: Thu, 7 Mar 2024 16:09:26 -0700 Subject: [PATCH 17/72] issue #383 modifications to support multiple plot types in a single config file and logging to replace print statements --- .../tcmpr_plots/relperf/tcmpr_relperf.py | 61 +++++++++++++------ 1 file changed, 44 insertions(+), 17 deletions(-) mode change 100644 => 100755 metplotpy/plots/tcmpr_plots/relperf/tcmpr_relperf.py diff --git a/metplotpy/plots/tcmpr_plots/relperf/tcmpr_relperf.py b/metplotpy/plots/tcmpr_plots/relperf/tcmpr_relperf.py old mode 100644 new mode 100755 index d962a752..f6c35089 --- a/metplotpy/plots/tcmpr_plots/relperf/tcmpr_relperf.py +++ b/metplotpy/plots/tcmpr_plots/relperf/tcmpr_relperf.py @@ -1,27 +1,39 @@ import os - +from typing import Union +from datetime import datetime import numpy as np +from pandas import DataFrame import plotly.graph_objects as go + from metcalcpy.util import utils +from metplotpy.plots.series import Series from metplotpy.plots.tcmpr_plots.tcmpr import Tcmpr from metplotpy.plots.tcmpr_plots.tcmpr_series import TcmprSeries from metplotpy.plots.tcmpr_plots.tcmpr_util import get_case_data +import metplotpy.plots.util as util + class TcmprRelPerf(Tcmpr): - def __init__(self, config_obj, column_info, col, case_data, input_df): - super().__init__(config_obj, column_info, col, case_data, input_df) - print("--------------------------------------------------------") + def __init__(self, config_obj, column_info, col, case_data, input_df, stat_name): + super().__init__(config_obj, column_info, col, case_data, input_df, stat_name) + + # Set up Logging + self.relperf_logger = util.get_common_logger(self.config_obj.log_level, self.config_obj.log_filename) + self.relperf_logger.info(f"--------------------------------------------------------") if not self.config_obj.use_ee: + self.relpef_logger.error(f"Plotting RELPERF time series by {self.config_obj.series_val_names[0]}") raise Exception("ERROR: Cannot plot relative performance when event equalization is disabled.") - print(f"Plotting RELPERF time series by {self.config_obj.series_val_names[0]}") - print("Plot HFIP Baseline:" + self.cur_baseline) + self.relperf_logger.info(f"Plotting RELPERF time series by {stat_name}") + + self.relperf_logger.info("Plot HFIP Baseline:" + self.cur_baseline) self._adjust_titles() - self.series_list = self._create_series(self.input_df) + self.series_list = self._create_series(self.input_df, stat_name) if self.case_data is None: + self.relperf_logger.info(f"Getting case data for {stat_name}") self.case_data = get_case_data(self.input_df, self.config_obj.series_vals_1, self.config_obj.indy_vals, self.config_obj.rp_diff, len(self.series_list)) @@ -29,16 +41,16 @@ def __init__(self, config_obj, column_info, col, case_data, input_df): series.create_relperf_points(self.case_data) if self.config_obj.prefix is None or len(self.config_obj.prefix) == 0: - self.plot_filename = f"{self.config_obj.plot_dir}{os.path.sep}{self.config_obj.list_stat_1[0]}_relperf.png" + self.plot_filename = f"{self.config_obj.plot_dir}{os.path.sep}{stat_name}_relperf.png" else: - self.plot_filename = f"{self.config_obj.plot_dir}{os.path.sep}{self.config_obj.prefix}.png" - # remove the old file if it exist + self.plot_filename = f"{self.config_obj.plot_dir}{os.path.sep}{self.config_obj.prefix}_{stat_name}_relperf.png" + # remove the old file if it exists if os.path.exists(self.plot_filename): os.remove(self.plot_filename) - self.user_legends = self._create_user_legends() - self._create_figure() + self.user_legends = self._create_user_legends(stat_name) + self._create_figure(stat_name) - def _create_user_legends(self): + def _create_user_legends(self, stat_name): all_user_legends = self.config_obj.get_config_value('user_legend') legend_list = [] series = self.config_obj.get_series_y_relperf(1) @@ -52,7 +64,8 @@ def _create_user_legends(self): legend_list.append(all_user_legends[idx]) # add to legend list legends for y2-axis series - num_series_y1 = len(self.config_obj.get_series_y(1)) + # num_series_y1 = len(self.config_obj.get_series_y(1)) + num_series_y1 = len(stat_name) for idx, ser_components in enumerate(self.get_config_value('derived_series_1')): # index of the legend @@ -66,9 +79,10 @@ def _create_user_legends(self): return self.config_obj.create_list_by_series_ordering(legend_list) - def _create_figure(self): + def _create_figure(self, stat_name): """ Create a box plot from default and custom parameters""" + start_time = datetime.now() self.figure = self._create_layout() self._add_xaxis() self._add_yaxis() @@ -98,10 +112,12 @@ def _create_figure(self): yaxis_min, yaxis_max = self.find_min_max(series, yaxis_min, yaxis_max) self._draw_series(series, x_points_index) - series = TcmprSeries(self.config_obj, len(self.series_list), self.input_df, [], ['TIE']) + series = TcmprSeries(self.config_obj, len(self.series_list), self.input_df, [], ['TIE'], stat_name) + # Reset some series values. Series should be grouped by the plot type and not by the series_val + # series = self._setup_series(self.config_obj, len(self.series_list), self.input_df, [], ['TIE'], stat_name) series.create_relperf_points(self.case_data) yaxis_min, yaxis_max = self.find_min_max(series, yaxis_min, yaxis_max) - print(f'Range of {self.config_obj.list_stat_1[0]}: {yaxis_min}, {yaxis_max}') + self.relperf_logger.info(f'Range of {stat_name}: {yaxis_min}, {yaxis_max}') tie_conf = { 'line_color': '#808080', 'name': 'TIE', @@ -147,6 +163,10 @@ def _create_figure(self): # add x2 axis self._add_x2axis(list(range(0, len(self.config_obj.indy_vals)))) + end_time = datetime.now() + total_time = end_time - start_time + self.relperf_logger.info(f"Took {total_time} milliseconds to create the relative performance figure") + def _draw_series(self, series: TcmprSeries, x_points_index_adj: list, tie_conf=None) -> None: """ Draws the boxes on the plot @@ -154,6 +174,8 @@ def _draw_series(self, series: TcmprSeries, x_points_index_adj: list, tie_conf=N :param series: Line series object with data and parameters """ + start_time = datetime.now() + if tie_conf is None: color = self.config_obj.colors_list[series.idx] width = self.config_obj.linewidth_list[series.idx] @@ -219,6 +241,10 @@ def _draw_series(self, series: TcmprSeries, x_points_index_adj: list, tie_conf=N secondary_y=series.y_axis != 1 ) + end_time = datetime.now() + total_time = end_time - start_time + self.relperf_logger.info(f"Took {total_time} milliseconds to draw the series") + def _adjust_titles(self): if self.yaxis_1 is None or len(self.yaxis_1) == 0: self.yaxis_1 = 'Percent of Cases' @@ -230,3 +256,4 @@ def _adjust_titles(self): if len(np.unique(self.config_obj.rp_diff)) == 1: self.title = f"{self.title} Difference {self.config_obj.rp_diff[0]}{self.col['units']}" self.title = f'{self.title} by {self.column_info[self.column_info["COLUMN"] == self.config_obj.series_val_names[0]]["DESCRIPTION"].tolist()[0]}' + From 9ee97c338f5a53ed70012a77955a4a7af93c9ff7 Mon Sep 17 00:00:00 2001 From: bikegeek Date: Thu, 7 Mar 2024 16:10:57 -0700 Subject: [PATCH 18/72] issue #383 modifications to support multiple plot types in one config file and logging to replace print statements --- .../plots/tcmpr_plots/skill/tcmpr_skill.py | 43 ++++++++++++++----- 1 file changed, 32 insertions(+), 11 deletions(-) mode change 100644 => 100755 metplotpy/plots/tcmpr_plots/skill/tcmpr_skill.py diff --git a/metplotpy/plots/tcmpr_plots/skill/tcmpr_skill.py b/metplotpy/plots/tcmpr_plots/skill/tcmpr_skill.py old mode 100644 new mode 100755 index f057a9ef..0926ab4e --- a/metplotpy/plots/tcmpr_plots/skill/tcmpr_skill.py +++ b/metplotpy/plots/tcmpr_plots/skill/tcmpr_skill.py @@ -1,18 +1,31 @@ from typing import Union import plotly.graph_objects as go +from datetime import datetime from metplotpy.plots.tcmpr_plots.tcmpr import Tcmpr from metplotpy.plots.tcmpr_plots.tcmpr_series import TcmprSeries from metcalcpy.util import utils +import metplotpy.plots.util as util class TcmprSkill(Tcmpr): - def __init__(self, config_obj, column_info, col, case_data, input_df, baseline_data): - super().__init__(config_obj, column_info, col, case_data, input_df) + def __init__(self, config_obj, column_info, col, case_data, input_df, baseline_data, stat_name): + super().__init__(config_obj, column_info, col, case_data, input_df, stat_name) - def _create_figure(self): - """ Create a box plot from default and custom parameters""" + # Set up Logging + self.skill_logger = util.get_common_logger(config_obj.log_level, config_obj.log_filename) + def _create_figure(self, stat_name): + """ Create a skill line plot from default and custom parameters + + Args: + stat_name: the name of the current 'statistic' (eg TK_ERR, AMSLP-BMSLP, etc.) + corresponding to list_stat_1 in the config file + + + """ + + start_time = datetime.now() self.figure = self._create_layout() self._add_xaxis() self._add_yaxis() @@ -48,9 +61,12 @@ def _create_figure(self): x_points_index_adj = x_points_index + stag_adjustments[series.idx] self._draw_series(series, x_points_index_adj) - print(f'Range of {self.config_obj.list_stat_1[0]}: {yaxis_min}, {yaxis_max}') + self.skill_logger.info(f'Range of {stat_name}: {yaxis_min}, {yaxis_max}') - self._add_hfip_baseline() + if self.config_obj.hfip_bsln is not 'no': + # This will be a valid value for hfip_bsln. This has been + # validated/vetted in the configuration code (tcmpr_config.py). + super()._add_hfip_baseline() self.figure.update_layout(shapes=[dict( type='line', @@ -62,17 +78,22 @@ def _create_figure(self): )]) # add custom lines - if len(self.series_list) > 0: - self._add_lines( - self.config_obj, - sorted(self.series_list[0].series_data[self.config_obj.indy_var].unique()) - ) + num_series = len(self.series_list) + if num_series > 0: + for idx in range(num_series): + self._add_lines(self.config_obj, + sorted(self.series_list[idx].series_data[self.config_obj.indy_var].unique()) + ) # apply y axis limits self._yaxis_limits() # add x2 axis self._add_x2axis(list(range(0, len(self.config_obj.indy_vals)))) + end_time = datetime.now() + total_time = end_time - start_time + self.skill_logger.info(f"Took {total_time} milliseconds to create the figure for {stat_name}") + def _draw_series(self, series: TcmprSeries, x_points_index_adj: list) -> None: """ Draws the boxes on the plot From 3352da0ca7e464339792f06d1556adc8a886e335 Mon Sep 17 00:00:00 2001 From: bikegeek Date: Thu, 7 Mar 2024 16:12:20 -0700 Subject: [PATCH 19/72] issue #383 replace print statements with logging --- .../skill/mean/tcmpr_series_skill_mean.py | 16 ++++++++++++++-- 1 file changed, 14 insertions(+), 2 deletions(-) mode change 100644 => 100755 metplotpy/plots/tcmpr_plots/skill/mean/tcmpr_series_skill_mean.py diff --git a/metplotpy/plots/tcmpr_plots/skill/mean/tcmpr_series_skill_mean.py b/metplotpy/plots/tcmpr_plots/skill/mean/tcmpr_series_skill_mean.py old mode 100644 new mode 100755 index 4ee36762..d7632c17 --- a/metplotpy/plots/tcmpr_plots/skill/mean/tcmpr_series_skill_mean.py +++ b/metplotpy/plots/tcmpr_plots/skill/mean/tcmpr_series_skill_mean.py @@ -15,6 +15,8 @@ import numpy as np from pandas import DataFrame +from datetime import datetime +import metplotpy.plots.util as util import metcalcpy.util.utils as utils from metplotpy.plots.tcmpr_plots.tcmpr_series import TcmprSeries @@ -29,8 +31,13 @@ class TcmprSeriesSkillMean(TcmprSeries): """ def __init__(self, config, idx: int, input_data, series_list: list, - series_name: Union[list, tuple], skill_ref_data: DataFrame = None): - super().__init__(config, idx, input_data, series_list, series_name, skill_ref_data) + series_name: Union[list, tuple], stat_name, skill_ref_data: DataFrame = None): + + # Set up Logging + self.skill_series_logger = util.get_common_logger(config.log_level, config.log_filename) + + self.skill_series_logger.info(f"Creating TcmprSeriesSkillMean object: {datetime.now()}") + super().__init__(config, idx, input_data, series_list, series_name, stat_name, skill_ref_data) def _create_series_points(self) -> dict: """ @@ -43,6 +50,7 @@ def _create_series_points(self) -> dict: dictionary with CI ,point values and number of stats as keys """ + start_time = datetime.now() self._init_series_data() result_size = len(self.config.indy_vals) @@ -77,4 +85,8 @@ def _create_series_points(self) -> dict: series_points_results['nstat'][i] = len(point_data) + end_time = datetime.now() + total_time = end_time - start_time + self.skill_series_logger.info(f"Took {total_time} milliseconds to create series points") + return series_points_results From 2ebe3be5068b69c33b3a9e04ea7544bdc6e3049f Mon Sep 17 00:00:00 2001 From: bikegeek Date: Thu, 7 Mar 2024 16:16:21 -0700 Subject: [PATCH 20/72] Issue #383 logging support --- .../skill/mean/tcmpr_skill_mean.py | 67 ++++++++++++------- 1 file changed, 43 insertions(+), 24 deletions(-) mode change 100644 => 100755 metplotpy/plots/tcmpr_plots/skill/mean/tcmpr_skill_mean.py diff --git a/metplotpy/plots/tcmpr_plots/skill/mean/tcmpr_skill_mean.py b/metplotpy/plots/tcmpr_plots/skill/mean/tcmpr_skill_mean.py old mode 100644 new mode 100755 index 9dfae403..1f11bffc --- a/metplotpy/plots/tcmpr_plots/skill/mean/tcmpr_skill_mean.py +++ b/metplotpy/plots/tcmpr_plots/skill/mean/tcmpr_skill_mean.py @@ -1,4 +1,5 @@ import os +from datetime import datetime import numpy as np import plotly.graph_objects as go @@ -6,33 +7,38 @@ from metcalcpy.util import utils from metplotpy.plots.tcmpr_plots.skill.mean.tcmpr_series_skill_mean import TcmprSeriesSkillMean from metplotpy.plots.tcmpr_plots.skill.tcmpr_skill import TcmprSkill +import metplotpy.plots.util as util class TcmprSkillMean(TcmprSkill): - def __init__(self, config_obj, column_info, col, case_data, input_df, baseline_data): - super().__init__(config_obj, column_info, col, case_data, input_df, baseline_data) - print("--------------------------------------------------------") - print(f"Plotting SKILL_MN time series by {self.config_obj.series_val_names[0]}") + def __init__(self, config_obj, column_info, col, case_data, input_df, stat_name, baseline_data): + super().__init__(config_obj, column_info, col, case_data, input_df, baseline_data, stat_name) - self._adjust_titles() + # Set up Logging + self.skill_logger = util.get_common_logger(self.config_obj.log_level, self.config_obj.log_filename) + + self.skill_logger.info("--------------------------------------------------------") + self.skill_logger.info(f"Plotting SKILL_MN time series by {self.config_obj.series_val_names[0]}") + + self._adjust_titles(stat_name) self.cur_baseline = baseline_data['cur_baseline'] self.cur_baseline_data = baseline_data['cur_baseline_data'] self._init_hfip_baseline_for_plot() - self.series_list = self._create_series(self.input_df) + self.series_list = self._create_series(self.input_df, stat_name) self.case_data = None if self.config_obj.prefix is None or len(self.config_obj.prefix) == 0: - self.plot_filename = f"{self.config_obj.plot_dir}{os.path.sep}{self.config_obj.list_stat_1[0]}_skill_mn.png" + self.plot_filename = f"{self.config_obj.plot_dir}{os.path.sep}{stat_name}_skill_mn.png" else: - self.plot_filename = f"{self.config_obj.plot_dir}{os.path.sep}{self.config_obj.prefix}.png" + self.plot_filename = f"{self.config_obj.plot_dir}{os.path.sep}{self.config_obj.prefix}_{stat_name}_skill_mn.png" - # remove the old file if it exist + # remove the old file if it exists if os.path.exists(self.plot_filename): os.remove(self.plot_filename) - self._create_figure() + self._create_figure(stat_name) - def _adjust_titles(self): + def _adjust_titles(self, stat_name): if self.yaxis_1 is None or len(self.yaxis_1) == 0: - self.yaxis_1 = self.config_obj.list_stat_1[0] + '(' + self.col['units'] + ')' + self.yaxis_1 = 'Skill for ' + stat_name + ' (' + self.col['units'] + ')' if self.title is None or len(self.title) == 0: self.title = 'Mean Skill Scores of ' + self.col['desc'] + ' by ' \ @@ -41,15 +47,16 @@ def _adjust_titles(self): def _init_hfip_baseline_for_plot(self): if 'Water Only' in self.title: - print("Plot HFIP Baseline:" + self.cur_baseline) + self.skill_logge.info(f"Plot HFIP Baseline: {self.cur_baseline}") else: self.cur_baseline = self.cur_baseline.replace('Error', 'Skill') self.cur_baseline = self.cur_baseline.replace('HFIP Baseline ', 'HFIP Skill Baseline') - print('Plot HFIP Baseline:' + self.cur_baseline.replace('Error ', '')) + self.skill_logger.info(f"Plot HFIP Baseline: {self.cur_baseline.replace('Error ', '')}") def _add_hfip_baseline(self): # Add HFIP baseline for each lead time if self.cur_baseline_data is not None: + self.skill_logger.info(f"Adding HFIP baseline: {datetime.now()}") baseline_x_values = [] baseline_y_values = [] lead_times = np.unique(self.series_list[0].series_data[self.config_obj.indy_var].tolist()) @@ -59,16 +66,13 @@ def _add_hfip_baseline(self): ocd5_data = self.cur_baseline_data.loc[ (self.cur_baseline_data['LEAD'] == lead) & (self.cur_baseline_data['TYPE'] == "OCD5")][ 'VALUE'].tolist() - if len(ocd5_data) > 1: - raise ValueError( - f"ERROR: Can't crate HFIP baseline for lead time {lead} : too many values of OCD5 in .dat file") ocd5_data = ocd5_data[0] cons_data = self.cur_baseline_data.loc[ (self.cur_baseline_data['LEAD'] == lead) & (self.cur_baseline_data['TYPE'] == "CONS")][ 'VALUE'].tolist() if len(cons_data) > 1: raise ValueError( - f"ERROR: Can't crate HFIP baseline for lead time {lead} : too many values of CONS in .dat file") + f"ERROR: Can't create HFIP baseline for lead time {lead} : too many values of CONS in .dat file") cons_data = cons_data[0] baseline_lead = utils.round_half_up(100 * (ocd5_data - cons_data) / ocd5_data, 1) @@ -93,7 +97,7 @@ def _add_hfip_baseline(self): ) ) - def _create_series(self, input_data): + def _create_series(self, input_data, stat_name): """ Generate all the series objects that are to be displayed as specified by the plot_disp setting in the config file. The points are all ordered by datetime. Each series object @@ -103,27 +107,39 @@ def _create_series(self, input_data): Args: input_data: The input data in the form of a Pandas dataframe. This data will be subset to reflect the series data of interest. + stat_name: The current value of the list_stat_1 specified in the configuration file. This represents + type of plot (e.g. TK_ERR, ABS(AMAX_WIND-BMAX-WIND), etc.). Returns: a list of series objects that are to be displayed """ + + start_time = datetime.now() all_fields_values = {'AMODEL': [utils.GROUP_SEPARATOR.join(self.config_obj.skill_ref)], 'fcst_var': self.config_obj.list_stat_1} permutations = utils.create_permutations_mv(all_fields_values, 0) ref_model_data_series = TcmprSeriesSkillMean(self.config_obj, 0, - input_data, [], permutations[0]) + input_data, [], permutations[0], stat_name, None) ref_model_data = ref_model_data_series.series_data series_list = [] # add series for y1 axis - num_series_y1 = len(self.config_obj.get_series_y(1)) - for i, name in enumerate(self.config_obj.get_series_y(1)): + unique_series = [] + for cur in self.config_obj.get_series_y(1): + if cur[0] not in unique_series: + unique_series.append(cur[0]) + + num_series_y1 = len(unique_series) + # num_series_y1 = len(self.config_obj.get_series_y(1)) + # for i, name in enumerate(self.config_obj.get_series_y(1)): + for i, name in enumerate(unique_series): if not isinstance(name, list): name = [name] - series_obj = TcmprSeriesSkillMean(self.config_obj, i, input_data, series_list, name, ref_model_data) + + series_obj = TcmprSeriesSkillMean(self.config_obj, i, input_data, series_list, name, stat_name, ref_model_data) series_list.append(series_obj) # add derived for y1 axis @@ -133,10 +149,13 @@ def _create_series(self, input_data): name.append("DIFF") # include the series only if the name is valid if len(name) == 3: - series_obj = TcmprSeriesSkillMean(self.config_obj, num_series_y1 + i, input_data, series_list, name) + series_obj = TcmprSeriesSkillMean(self.config_obj, num_series_y1 + i, input_data, series_list, name, stat_name) series_list.append(series_obj) # reorder series series_list = self.config_obj.create_list_by_series_ordering(series_list) + end_time = datetime.now() + total_time = end_time - start_time + self.skill_logger.info(f"Total time to create series list for {stat_name}: {total_time} milliseconds ") return series_list From 433fd629aa23b7f18c57e6120d3514f6b35ab8eb Mon Sep 17 00:00:00 2001 From: bikegeek Date: Thu, 7 Mar 2024 16:17:30 -0700 Subject: [PATCH 21/72] issue #383 modifications to support multiple plot types in a single config file and logging replaces printing to stdout --- .../skill/median/tcmpr_skill_median.py | 59 +++++++++++++------ 1 file changed, 40 insertions(+), 19 deletions(-) mode change 100644 => 100755 metplotpy/plots/tcmpr_plots/skill/median/tcmpr_skill_median.py diff --git a/metplotpy/plots/tcmpr_plots/skill/median/tcmpr_skill_median.py b/metplotpy/plots/tcmpr_plots/skill/median/tcmpr_skill_median.py old mode 100644 new mode 100755 index bf718138..cc0d9406 --- a/metplotpy/plots/tcmpr_plots/skill/median/tcmpr_skill_median.py +++ b/metplotpy/plots/tcmpr_plots/skill/median/tcmpr_skill_median.py @@ -1,42 +1,48 @@ import os +from datetime import datetime from metcalcpy.util import utils from metplotpy.plots.tcmpr_plots.skill.median.tcmpr_series_skill_median import TcmprSeriesSkillMedian from metplotpy.plots.tcmpr_plots.skill.tcmpr_skill import TcmprSkill +import metplotpy.plots.util as util class TcmprSkillMedian(TcmprSkill): - def __init__(self, config_obj, column_info, col, case_data, input_df): - super().__init__(config_obj, column_info, col, case_data, input_df, None) - print("--------------------------------------------------------") - print(f"Plotting SKILL_MD time series by {self.config_obj.series_val_names[0]}") + def __init__(self, config_obj, column_info, col, case_data, input_df, stat_name): + super().__init__(config_obj, column_info, col, case_data, input_df, stat_name, None) - print("Plot HFIP Baseline:" + self.cur_baseline) + # Set up Logging + self.skillmd_logger = util.get_common_logger(self.config_obj.log_level, self.config_obj.log_filename) - self._adjust_titles() - self.series_list = self._create_series(self.input_df) + self.skillmd_logger.info("--------------------------------------------------------") + self.skillmd_logger.info(f"Plotting SKILL_MD time series by {self.config_obj.series_val_names[0]}") + + self.skillmd_logger.info("Plot HFIP Baseline:" + self.cur_baseline) + + self._adjust_titles(stat_name) + self.series_list = self._create_series(self.input_df, stat_name) self.case_data = None if self.config_obj.prefix is None or len(self.config_obj.prefix) == 0: - self.plot_filename = f"{self.config_obj.plot_dir}{os.path.sep}{self.config_obj.list_stat_1[0]}_skill_md.png" + self.plot_filename = f"{self.config_obj.plot_dir}{os.path.sep}{stat_name}_skill_md.png" else: - self.plot_filename = f"{self.config_obj.plot_dir}{os.path.sep}{self.config_obj.prefix}.png" + self.plot_filename = f"{self.config_obj.plot_dir}{os.path.sep}{self.config_obj.prefix}_{stat_name}_skill_md.png" - # remove the old file if it exist + # remove the old file if it exists if os.path.exists(self.plot_filename): os.remove(self.plot_filename) - self._create_figure() + self._create_figure(stat_name) - def _adjust_titles(self): + def _adjust_titles(self, stat_name): if self.yaxis_1 is None or len(self.yaxis_1) == 0: - self.yaxis_1 = self.config_obj.list_stat_1[0] + '(' + self.col['units'] + ')' + self.yaxis_1 = 'Skill for ' + stat_name + ' (' + self.col['units'] + ')' if self.title is None or len(self.title) == 0: self.title = 'Median Skill Scores of ' + self.col['desc'] + ' by ' \ + self.column_info[self.column_info['COLUMN'] == self.config_obj.series_val_names[0]][ "DESCRIPTION"].tolist()[0] - def _create_series(self, input_data): + def _create_series(self, input_data, stat_name): """ Generate all the series objects that are to be displayed as specified by the plot_disp setting in the config file. The points are all ordered by datetime. Each series object @@ -47,26 +53,38 @@ def _create_series(self, input_data): input_data: The input data in the form of a Pandas dataframe. This data will be subset to reflect the series data of interest. + stat_name: The current name of the "statistic" specified in list_stat_1 of the config file + Returns: a list of series objects that are to be displayed """ + + start_time = datetime.now() + all_fields_values = {'AMODEL': [utils.GROUP_SEPARATOR.join(self.config_obj.skill_ref)], 'fcst_var': self.config_obj.list_stat_1} permutations = utils.create_permutations_mv(all_fields_values, 0) ref_model_data_series = TcmprSeriesSkillMedian(self.config_obj, 0, - input_data, [], permutations[0]) + input_data, [], permutations[0], stat_name) ref_model_data = ref_model_data_series.series_data series_list = [] # add series for y1 axis - num_series_y1 = len(self.config_obj.get_series_y(1)) - for i, name in enumerate(self.config_obj.get_series_y(1)): + unique_series = [] + for cur in self.config_obj.get_series_y(1): + if cur[0] not in unique_series: + unique_series.append(cur[0]) + + num_series_y1 = len(unique_series) + # num_series_y1 = len(self.config_obj.get_series_y(1)) + # for i, name in enumerate(self.config_obj.get_series_y(1)): + for i, name in enumerate(unique_series): if not isinstance(name, list): name = [name] - series_obj = TcmprSeriesSkillMedian(self.config_obj, i, input_data, series_list, name, ref_model_data) + series_obj = TcmprSeriesSkillMedian(self.config_obj, i, input_data, series_list, name, stat_name, ref_model_data) series_list.append(series_obj) # add derived for y1 axis @@ -76,10 +94,13 @@ def _create_series(self, input_data): name.append("DIFF") # include the series only if the name is valid if len(name) == 3: - series_obj = TcmprSeriesSkillMedian(self.config_obj, num_series_y1 + i, input_data, series_list, name) + series_obj = TcmprSeriesSkillMedian(self.config_obj, num_series_y1 + i, input_data, series_list, name, stat_name) series_list.append(series_obj) # reorder series series_list = self.config_obj.create_list_by_series_ordering(series_list) + end_time = datetime.now() + total_time = end_time - start_time + self.skillmd_logger.info(f"Took {total_time} milliseconds to create series for {stat_name}") return series_list From 4114269c8a80f6396b5eb9270be199c389b6cf79 Mon Sep 17 00:00:00 2001 From: bikegeek Date: Thu, 7 Mar 2024 16:18:24 -0700 Subject: [PATCH 22/72] issue #383 modifications to support plotting multiple plot types defined in a single config file --- .../tcmpr_plots/skill/median/tcmpr_series_skill_median.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) mode change 100644 => 100755 metplotpy/plots/tcmpr_plots/skill/median/tcmpr_series_skill_median.py diff --git a/metplotpy/plots/tcmpr_plots/skill/median/tcmpr_series_skill_median.py b/metplotpy/plots/tcmpr_plots/skill/median/tcmpr_series_skill_median.py old mode 100644 new mode 100755 index 2afd49f1..132e4c32 --- a/metplotpy/plots/tcmpr_plots/skill/median/tcmpr_series_skill_median.py +++ b/metplotpy/plots/tcmpr_plots/skill/median/tcmpr_series_skill_median.py @@ -29,8 +29,8 @@ class TcmprSeriesSkillMedian(TcmprSeries): """ def __init__(self, config, idx: int, input_data, series_list: list, - series_name: Union[list, tuple], skill_ref_data: DataFrame = None): - super().__init__(config, idx, input_data, series_list, series_name, skill_ref_data) + series_name: Union[list, tuple], stat_name, skill_ref_data: DataFrame = None): + super().__init__(config, idx, input_data, series_list, series_name, stat_name, skill_ref_data) def _create_series_points(self) -> dict: """ From 0b683021c26206fbe4ee7cf764b7ab8d841f4383 Mon Sep 17 00:00:00 2001 From: bikegeek Date: Thu, 7 Mar 2024 16:19:51 -0700 Subject: [PATCH 23/72] issue #383 modifications to support multiple plot types in a single config file and added logging --- metplotpy/plots/tcmpr_plots/tcmpr.py | 163 +++++++++++++++++---------- 1 file changed, 104 insertions(+), 59 deletions(-) diff --git a/metplotpy/plots/tcmpr_plots/tcmpr.py b/metplotpy/plots/tcmpr_plots/tcmpr.py index 1694af24..5ac4cc8d 100755 --- a/metplotpy/plots/tcmpr_plots/tcmpr.py +++ b/metplotpy/plots/tcmpr_plots/tcmpr.py @@ -16,7 +16,9 @@ import sys from datetime import datetime from typing import Union - +# Ignore DeprecationWarning for pyarrow in Pandas3 for now +import warnings +warnings.filterwarnings('ignore') import numpy as np import pandas as pd import plotly.graph_objects as go @@ -41,7 +43,7 @@ class Tcmpr(BasePlot): where each box is represented by a text point data file. """ - def __init__(self, config_obj, column_info, col, case_data, input_df, stat_name=None): + def __init__(self, config_obj, column_info, col, case_data, input_df, stat_name): """ Creates a plot, based on settings indicated by parameters. @@ -53,6 +55,9 @@ def __init__(self, config_obj, column_info, col, case_data, input_df, stat_name= # init common layout super().__init__(None, "tcmpr_defaults.yaml") + # Set up Logging + self.logger = util.get_common_logger(config_obj.log_level, config_obj.log_filename) + self.series_list = [] # instantiate a BoxConfig object, which holds all the necessary settings from the @@ -75,7 +80,7 @@ def __init__(self, config_obj, column_info, col, case_data, input_df, stat_name= self.baseline_lead_time = 'lead' self.yaxis_1 = self.config_obj.yaxis_1 - self.plot_filename = f"{self.config_obj.plot_dir}{os.path.sep}{self.config_obj.list_stat_1[0]}_{self.config_obj.plot_type}.png" + self.plot_filename = f"{self.config_obj.plot_dir}{os.path.sep}{self.config_obj.list_stat_1[0]}_{self.config_obj.plot_type_list}.png" # Check that we have all the necessary settings for each series # TODO implement the consistency check if no series values were specified # is_config_consistent = self.config_obj._config_consistency_check() @@ -110,6 +115,7 @@ def _create_series(self, input_data, stat_name): """ + self.logger.info(f"Creating series for {stat_name}: {datetime.now()}") series_list = [] # add series for y1 axis @@ -124,7 +130,9 @@ def _create_series(self, input_data, stat_name): for i, name in enumerate(series_by_stat): if not isinstance(name, list): name = [name] - series_obj = TcmprSeries(self.config_obj, i, input_data, series_list, name) + # cur_plot_type = self.config_obj.get_config_value('plot_type_list') + series_obj = TcmprSeries(self.config_obj, i, input_data, series_list, + name, stat_name) series_list.append(series_obj) # add derived for y1 axis @@ -138,12 +146,12 @@ def _create_series(self, input_data, stat_name): oper = name[2] name[:] = [(s + ' ' + stat_name) if ' ' not in s else s for s in name[:2]] name.append(oper) - series_obj = TcmprSeries(self.config_obj, num_series_y1 + i, input_data, series_list, name) + series_obj = TcmprSeries(self.config_obj, num_series_y1 + i, input_data, series_list, name, stat_name) series_list.append(series_obj) # reorder series series_list = self.config_obj.create_list_by_series_ordering(series_list) - + self.logger.info(f"Series list created: {datetime.now()}") return series_list def _calc_stag_adjustments(self) -> list: @@ -168,6 +176,8 @@ def _calc_stag_adjustments(self) -> list: return stag_vals def _add_hfip_baseline(self): + + self.logger.info(f"Adding the hfip baseline: {datetime.now()}") # Add baseline for each lead time if self.cur_baseline_data is not None: baseline_x_values = [] @@ -412,7 +422,7 @@ def save_to_file(self): dirname = os.path.dirname(os.path.abspath(self.plot_filename)) if not os.path.exists(dirname): os.mkdir(dirname) - print(f'Creating image file: {self.plot_filename}') + self.logger.info(f'Saving the image file: {self.plot_filename}') if self.figure: try: self.figure.write_image(file=self.plot_filename, format='png', @@ -420,11 +430,11 @@ def save_to_file(self): height=self.config_obj.plot_height, scale=2) except FileNotFoundError: - print("Can't save to file " + self.plot_filename) + self.logger.error(f"Cannot save to file {self.plot_filename}") except ValueError as ex: print(ex) else: - print("Oops! The figure was not created. Can't save.") + self.logger.error(f"The figure wasn't created. Nothing to save") @staticmethod def find_min_max(series: TcmprSeries, yaxis_min: Union[float, None], @@ -464,6 +474,44 @@ def find_min_max(series: TcmprSeries, yaxis_min: Union[float, None], return min(yaxis_min, low_range), max(yaxis_max, upper_range) +def perform_event_equalization(input_df:pd.DataFrame, is_skill:bool, config_obj:dict) -> pd.DataFrame: + ''' + Performs event equalization. The skill_mn and skill_md plots require the skill_ref value to be included. + + Args: + @param input_df: The original input data, comprised of all the specified data files. + + @param is_skill: Boolean value to indicate whether the plot type is skill_mn or skill_md. + + @param config_obj: A dictionary representation of the settings and values in the yaml config file. + + Returns: + output_data: pd.Dataframe containing the results + + ''' + + + logger = util.get_common_logger(config_obj.log_level, config_obj.log_filename) + logger.info(f"Performing requested event equalization: {datetime.now()}") + output_data = pd.DataFrame() + series = copy.deepcopy(config_obj.parameters['series_val_1']) + if is_skill: + series['AMODEL'].extend(config_obj.skill_ref) + + for series_var, series_var_vals in series.items(): + series_data = input_df[input_df[series_var].isin(series_var_vals)] + + # Run event_equalize as a process to capture the stdout to the logfile + series_data = event_equalize(series_data, '', config_obj.parameters['series_val_1'], [], [], True, False) + if output_data.empty: + output_data = series_data + else: + output_data.append(series_data) + + return output_data + + + def main(config_filename=None): """ @@ -514,59 +562,57 @@ def main(config_filename=None): if file not in tcst_files: tcst_files.append(file) - input_df = read_tcst_files(config_obj, tcst_files) - - # Apply event equalization, if requested - if config_obj.use_ee is True: - output_data = pd.DataFrame() - series = copy.deepcopy(config_obj.parameters['series_val_1']) - if 'skill_mn' in config_obj.plot_type or 'skill_md' in config_obj.plot_type: - series['AMODEL'].extend(config_obj.skill_ref) - - for series_var, series_var_vals in series.items(): - series_data = input_df[input_df[series_var].isin(series_var_vals)] - series_data = event_equalize(series_data, '', config_obj.parameters['series_val_1'], [], [], True, False) - if output_data.empty: - output_data = series_data - else: - output_data.append(series_data) - - input_df = output_data - # input_df = output_data.copy(deep=True) - # output_data = output_data.drop(columns=['equalize', 'VALID_TIME']) - # output_data.to_csv('/Users/tatiana/PycharmProjects/METplotpy/metplotpy/plots/tcmpr_plots/tc_pairs_2.tcst', index=False, sep='\t', na_rep='NA') - - input_df.rename({'equalize': 'CASE'}, axis=1, inplace=True) - # Sort the data by the CASE column - input_df = input_df.sort_values(by=['CASE', 'AMODEL']) - input_df.reset_index(drop=True, inplace=True) + orig_input_df = read_tcst_files(config_obj, tcst_files) + input_df = orig_input_df.copy(deep=True) # Define a demo and retro column - # TODO these values never get used - maybe need to remove - if config_obj.demo_yr is not None and config_obj.demo_yr != 'NA': - demo_yr_obj = datetime.strptime(str(config_obj.demo_yr), '%Y') - input_df.loc[input_df['VALID_TIME'] >= demo_yr_obj, "TYPE"] = "DEMO" - input_df.loc[input_df['VALID_TIME'] < demo_yr_obj, "TYPE"] = "RETRO" - - print_data_info(input_df, config_obj.series_val_names[0]) + # TODO these values never get used comment out for now + # input_df = orig_input_df.copy(deep=True) + # if config_obj.demo_yr is not None and config_obj.demo_yr != 'NA': + # demo_yr_obj = datetime.strptime(str(config_obj.demo_yr), '%Y') + # input_df.loc[input_df['VALID_TIME'] >= demo_yr_obj, "TYPE"] = "DEMO" + # input_df.loc[input_df['VALID_TIME'] < demo_yr_obj, "TYPE"] = "RETRO" # Read the TCMPR column information from a data file. column_info = pd.read_csv(os.path.join(sys.path[0], config_obj.column_info_file), sep=r'\s+', header='infer', quotechar='"', skipinitialspace=True, encoding='utf-8') - for cur_stat in config_obj.list_stat_1: - # col_to_plot = get_dep_column(config_obj.list_stat_1[0], column_info, input_df) - col_to_plot = get_dep_column(cur_stat, column_info, input_df) - input_df['PLOT'] = col_to_plot['val'] - - baseline_data = None - if common_member(config_obj.plot_type, PLOTS_WITH_BASELINE): - baseline_data = init_hfip_baseline(config_obj, config_obj.baseline_file, input_df) - - plot = None - common_case_data = None - for plot_type in config_obj.plot_type: + logger = util.get_common_logger(config_obj.log_level, config_obj.log_filename) + for plot_type in config_obj.plot_type_list: + + # Apply event equalization, if requested + # Event equalization is different for the skill_mn and skill_md + is_skill = False + if config_obj.use_ee: + if plot_type == 'skill_mn' or plot_type == 'skill_md': + is_skill = True + # perform event equalization on the skill_mn|skill_md plot type + logger.info(f"Perform event equalization for {plot_type}: {datetime.now()}") + output_result = perform_event_equalization(orig_input_df, is_skill, config_obj) + input_df = output_result + else: + logger.info(f"Perform event equalization for {plot_type}: {datetime.now()}") + output_result = perform_event_equalization(orig_input_df, is_skill, config_obj) + input_df = output_result + + input_df.rename({'equalize': 'CASE'}, axis=1, inplace=True) + # Sort the data by the CASE column + input_df = input_df.sort_values(by=['CASE', 'AMODEL']) + input_df.reset_index(drop=True, inplace=True) + + for cur_stat in config_obj.list_stat_1: + logger.info(f"Statistic of interest: {cur_stat}") + # col_to_plot = get_dep_column(config_obj.list_stat_1[0], column_info, input_df) + col_to_plot = get_dep_column(cur_stat, column_info, input_df) + input_df['PLOT'] = col_to_plot['val'] + + baseline_data = None + if common_member(config_obj.plot_type_list, PLOTS_WITH_BASELINE): + baseline_data = init_hfip_baseline(config_obj, config_obj.baseline_file, input_df) + + plot = None + common_case_data = None try: if plot_type == 'boxplot': from metplotpy.plots.tcmpr_plots.box.tcmpr_box import TcmprBox @@ -579,8 +625,7 @@ def main(config_filename=None): elif plot_type == 'mean': from metplotpy.plots.tcmpr_plots.line.mean.tcmpr_line_mean import TcmprLineMean plot = TcmprLineMean(config_obj, column_info, col_to_plot, common_case_data, input_df, - baseline_data, - cur_stat) + baseline_data, cur_stat) elif plot_type == 'median': from metplotpy.plots.tcmpr_plots.line.median.tcmpr_line_median import TcmprLineMedian plot = TcmprLineMedian(config_obj, column_info, col_to_plot, common_case_data, input_df, cur_stat) @@ -596,10 +641,10 @@ def main(config_filename=None): elif plot_type == 'skill_mn': from metplotpy.plots.tcmpr_plots.skill.mean.tcmpr_skill_mean import TcmprSkillMean plot = TcmprSkillMean(config_obj, column_info, col_to_plot, common_case_data, input_df, - baseline_data, cur_stat) + cur_stat, baseline_data) elif plot_type == 'skill_md': from metplotpy.plots.tcmpr_plots.skill.median.tcmpr_skill_median import TcmprSkillMedian - plot = TcmprSkillMedian(config_obj, column_info, col_to_plot, common_case_data, cur_stat, input_df) + plot = TcmprSkillMedian(config_obj, column_info, col_to_plot, common_case_data, input_df, cur_stat) plot.save_to_file() # plot.show_in_browser() @@ -632,7 +677,7 @@ def print_data_info(input_df, series): def read_tcst_files(config_obj, tcst_files): all_fields_values = copy.deepcopy(config_obj.parameters['series_val_1']) all_fields_values.update(config_obj.parameters['fixed_vars_vals_input']) - if 'skill_mn' in config_obj.plot_type or 'skill_md' in config_obj.plot_type: + if 'skill_mn' in config_obj.plot_type_list or 'skill_md' in config_obj.plot_type_list: all_fields_values['AMODEL'].extend(config_obj.skill_ref) input_df = None for file in tcst_files: From 26caa2269e914ca59e42e967a5de443982d3db8f Mon Sep 17 00:00:00 2001 From: bikegeek Date: Thu, 7 Mar 2024 16:21:11 -0700 Subject: [PATCH 24/72] issue #383 add more checking and modifications to support multiple plot types defined in a single config file. Also added logging --- metplotpy/plots/tcmpr_plots/tcmpr_config.py | 33 +++++++++++++++++---- 1 file changed, 27 insertions(+), 6 deletions(-) diff --git a/metplotpy/plots/tcmpr_plots/tcmpr_config.py b/metplotpy/plots/tcmpr_plots/tcmpr_config.py index 232ec1a3..721516d3 100755 --- a/metplotpy/plots/tcmpr_plots/tcmpr_config.py +++ b/metplotpy/plots/tcmpr_plots/tcmpr_config.py @@ -13,19 +13,21 @@ Holds values set in the box plot config file(s) """ +import warnings import itertools import metcalcpy.util.utils as utils from .. import constants from .. import util from ..config import Config +import metplotpy.plots.util as util class TcmprConfig(Config): """ Prepares and organises Line plot parameters """ - + SUPPORTED_PLOT_TYPES = ['boxplot', 'point', 'mean', 'median', 'relperf', 'rank', 'skill_mn', 'skill_md'] def __init__(self, parameters: dict) -> None: """ Reads in the plot settings from a box plot config file. @@ -35,8 +37,13 @@ def __init__(self, parameters: dict) -> None: """ super().__init__(parameters) + # Logging + self.log_filename = self.get_config_value('log_filename') + self.log_level = self.get_config_value('log_level') + self.logger = util.get_common_logger(self.log_level, self.log_filename) + ############################################## - self.plot_type = self._get_plot() + self.plot_type_list = self._get_plot() self.tcst_files = self._get_tcst_files() self.tcst_dir = self._get_tcst_dir() self.rp_diff = self._get_rp_diff() @@ -219,9 +226,12 @@ def _get_markers_size(self) -> list: return self.create_list_by_series_ordering(markers_size) def _get_plot(self) -> list: - plot_type = self.get_config_value('plot_type') - # TODO validate plots BOXPLOT, POINT, MEAN, MEDIAN, RELPERF, RANK, SKILL_MN, SKILL_MD - return plot_type + plot_type_list = self.get_config_value('plot_type_list') + for cur_plot_type in plot_type_list: + if cur_plot_type not in self.SUPPORTED_PLOT_TYPES: + raise ValueError("Requesting an unsupported plot type. Supported types: boxplot, " + "point, mean, median, relperf, rank, skill_mn, and skill_md ") + return plot_type_list def _get_tcst_files(self) -> list: tcst_files = self.get_config_value('tcst_files') @@ -235,8 +245,19 @@ def _get_rp_diff(self) -> list: return rp_diff def _get_hfip_bsln(self) -> str: + """ + Expect hfip_bsln value to be 'no', 0, 5, or 10 + + """ + hfip_bsln = str(self.get_config_value('hfip_bsln')) - # TODO validate hfip_bsln (no, 0, 5, 10 year goal) + hfip_bsln.lower() + + # Validate that hfip_bsln is one of the following; (no, 0, 5, 10 year goal) + supported_bsln = ['no', '0', '5', '10'] + if hfip_bsln not in supported_bsln: + raise ValueError(f"Error: Valid hfip_bsln values are: {supported_bsln}. ") + return hfip_bsln def _get_plot_disp(self) -> list: From 54c07c6aaffeac6ae7bf1533c0d276b14066832c Mon Sep 17 00:00:00 2001 From: bikegeek Date: Thu, 7 Mar 2024 16:22:17 -0700 Subject: [PATCH 25/72] issue #383 modifications to support plotting multiple plot types defined in a single config file and added logging --- metplotpy/plots/tcmpr_plots/tcmpr_series.py | 42 +++++++++++++++++++-- 1 file changed, 38 insertions(+), 4 deletions(-) diff --git a/metplotpy/plots/tcmpr_plots/tcmpr_series.py b/metplotpy/plots/tcmpr_plots/tcmpr_series.py index 8ea3d5d4..3d88bfef 100755 --- a/metplotpy/plots/tcmpr_plots/tcmpr_series.py +++ b/metplotpy/plots/tcmpr_plots/tcmpr_series.py @@ -13,6 +13,7 @@ import re from typing import Union +from datetime import datetime import numpy as np import pandas as pd @@ -21,6 +22,7 @@ import metcalcpy.util.utils as utils from .tcmpr_util import get_prop_ci from ..series import Series +import metplotpy.plots.util as util class TcmprSeries(Series): @@ -32,11 +34,23 @@ class TcmprSeries(Series): """ def __init__(self, config, idx: int, input_data, series_list: list, - series_name: Union[list, tuple], skill_ref_data: DataFrame = None): + series_name: Union[list, tuple], stat_name, skill_ref_data: DataFrame = None): self.series_list = series_list self.series_name = series_name self.rank_min_val = [] - self.series_len = len(config.get_series_y(1)) + len(config.get_config_value('derived_series_1')) + unique_series_val = [] + + # Set up Logging + self.series_logger = util.get_common_logger(config.log_level, config.log_filename) + + # The number of series for each plot is determined by the number of entries under series_val_1 + all_series:list = config.get_series_y(1) + for cur in all_series: + if cur[0] not in unique_series_val: + unique_series_val.append(cur[0]) + + self.series_len = len(unique_series_val) + len(config.get_config_value('derived_series_1')) + self.skill_ref_data = skill_ref_data if idx >= self.series_len: super().__init__(config, 0, input_data, 1) @@ -74,6 +88,8 @@ def _create_series_points(self) -> dict: dictionary with CI ,point values and number of stats as keys """ + start_time = datetime.now() + self._init_series_data() series_points_results = {'val': [], 'ncl': [], 'ncu': [], 'nstat': [], 'mean': []} @@ -93,6 +109,9 @@ def _create_series_points(self) -> dict: series_points_results['mean'].append(None) else: series_points_results['mean'].append(np.nanmean(point_data['PLOT'].tolist())) + end_time = datetime.now() + total_time = end_time - start_time + self.series_logger.info(f"Took {total_time} milliseconds to generate series points.") return series_points_results @@ -151,14 +170,17 @@ def _init_series_data(self): self._calculate_derived_values(operation, series_data_1, series_data_2) def create_relperf_points(self, case_data): - print('Case_data size =' + str(len(case_data.index))) + + start_time = datetime.now() + + self.series_logger.info('Case_data size =' + str(len(case_data.index))) for indy in self.config.indy_vals: if utils.is_string_integer(indy): indy = int(indy) elif utils.is_string_strictly_float(indy): indy = float(indy) - print("indy float =" + str(indy)) + self.series_logger.info("indy float =" + str(indy)) if self.idx >= self.series_len: series_val = self.series_name[0] else: @@ -173,7 +195,15 @@ def create_relperf_points(self, case_data): self.series_points['val'].append(s['val']) self.series_points['ncu'].append(s['ncu']) + end_time = datetime.now() + total_time = end_time - start_time + self.series_logger.info(f"Took {total_time} milliseconds to compute relative performance and CI points") + + def create_rank_points(self, case_data): + + start_time = datetime.now() + for indy in self.config.indy_vals: if utils.is_string_integer(indy): indy = int(indy) @@ -200,6 +230,10 @@ def create_rank_points(self, case_data): rank_min = 100 * n_cur / n_tot self.rank_min_val.append(rank_min) + end_time = datetime.now() + total_time = end_time - start_time + self.series_logger.info(f"Took {total_time} milliseconds to create rank points for relative performance") + def _calculate_derived_values(self, operation: str, series_data_1: DataFrame, From d83921d6263300aa335accf3d226fedcde09df87 Mon Sep 17 00:00:00 2001 From: bikegeek Date: Thu, 7 Mar 2024 16:38:38 -0700 Subject: [PATCH 26/72] issue #383 update the plot name to include the plot type --- metplotpy/plots/tcmpr_plots/scatter/tcmpr_scatter.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) mode change 100644 => 100755 metplotpy/plots/tcmpr_plots/scatter/tcmpr_scatter.py diff --git a/metplotpy/plots/tcmpr_plots/scatter/tcmpr_scatter.py b/metplotpy/plots/tcmpr_plots/scatter/tcmpr_scatter.py old mode 100644 new mode 100755 index 8a5cfc70..54c80f80 --- a/metplotpy/plots/tcmpr_plots/scatter/tcmpr_scatter.py +++ b/metplotpy/plots/tcmpr_plots/scatter/tcmpr_scatter.py @@ -76,7 +76,7 @@ def __init__(self, config_obj, column_info, col, case_data, input_df): if self.config_obj.prefix is None or len(self.config_obj.prefix) == 0: self.plot_filename = f"{self.config_obj.plot_dir}{os.path.sep}{out_file_x}_vs_{out_file_y}_scatter.png" else: - self.plot_filename = f"{self.config_obj.plot_dir}{os.path.sep}{self.config_obj.prefix}.png" + self.plot_filename = f"{self.config_obj.plot_dir}{os.path.sep}{self.config_obj.prefix}_scatter.png" # remove the old file if it exist if os.path.exists(self.plot_filename): From dc2be9a69b8afbf990c58ce55a0f91cbce481ff0 Mon Sep 17 00:00:00 2001 From: bikegeek Date: Tue, 12 Mar 2024 17:51:42 -0600 Subject: [PATCH 27/72] issue #383 TCMPR plot documentation initial content --- docs/Users_Guide/tcmpr_plots.rst | 335 +++++++++++++++++++++++++++++++ 1 file changed, 335 insertions(+) create mode 100755 docs/Users_Guide/tcmpr_plots.rst diff --git a/docs/Users_Guide/tcmpr_plots.rst b/docs/Users_Guide/tcmpr_plots.rst new file mode 100755 index 00000000..b1ead24d --- /dev/null +++ b/docs/Users_Guide/tcmpr_plots.rst @@ -0,0 +1,335 @@ +*********** +TCMPR Plots +*********** + +Description +=========== + +The TCMPR plots were originally available under the MET repository: https://github.com/dtcenter/MET +and written in R script. The code has been rewritten in Python and is located in the METplotpy repository: +https://github.com/dtcenter/METplotpy/metplotpy/plots/tcmpr_plots + + +There are numerous TCMPR plots that can be generated within **one** YAML configuration files: + + * mean line plot + * median line plot + * boxplot + * relative performance plot + * rank plot + * mean skill line plot + * median skill line plot + +Generating multiple plots within a single configuration file reduces the number of command line +commands to generate the plots. + +However, when more specific titles and plot customizations are desired for particular plot types, +each plot type can be defined with a corresponding configuration file +(e.g. a box plot will have a config file specifying settings specific to the +boxplot, a reliability plot will have a corresponding config file with settings relevant to a reliability plot, etc.). + +Example +======= + +Sample Data +----------- + +The data is text output from MET in columnar format. The sample data used to +create various TCMPR plots is available in the +`METplotpy `_ repository, where the TCMPR plot tests are located: + +*$METPLOTPY_BASE/metplotpy/test/tcmpr_plots/Data* + +*$METPLOTPY_BASE* is the directory where the METplotpy code is saved: + +e.g. + +*/usr/path/to/METplotpy* if the source code was cloned or forked from the Github repository + +or + +*/usr/path/to/METplotpy-x.y.z* if the source code was downloaded as a zip or gzip'd tar file from the Release link of +the Github repository. The *x.y.z* is the release number. + + +Configuration Files +------------------- + +The TCMPR plots utilize *two* YAML configuration files to indicate where input +data is located and to set plot attributes. + +YAML is a recursive acronym for "YAML Ain't Markup Language" and according to +`yaml.org `_, it is a +"human-friendly data serialization language". +It is commonly used for configuration files and in applications where +data is being stored or transmitted. + +A **mandatory default configuration** file specifies line/series colors, symbol shapes, symbol sizes, +margins, log levels, x- and y-label settings that can be used by numerous plot types. These default values +can be overridden by the custom configuration file. + +A **mandatory custom configuration file is also required**. Multiple plot types can be requested +in **one** configuration file (resulting in a single call to tcmpr.py to generate all the specified plots). +In this case, the TCMPR plotting scripts can create the title and x- and y-axis +labels based on the plot type and requested statistics specified in the config file. + +If particular plot types require specific/custom titles and/or +x- and y-axis labels, then each plot type can have a corresponding configuration file with values specific to this plot +type, statistics of interest (e.g. ABS(AMSLP-BMSLP), TK_ERR, etc.), fixed variables +(e.g. BASIN:AL, LEVEL:[SS, HU, TS]), and series (e.g. AMODEL:[H221, M221]). + +.. note:: + + The YAML configuration files **do not support expanding environment variables**. + If you see an environment variable referenced in this documentation for a YAML configuration item, + please be aware the **full value of that environment variable must be used**. + +METplus Configuration +===================== + +Default Configuration File +-------------------------- + +A default configuration file, tcmpr_defaults.yaml has some default settings for three lines/series such as plot +size, margins, etc. that don't require modification. There are some example colors and line and symbol styles and +sizes for three lines/series. The default logging level is set to ERROR, the least verbose. Any of these +settings can be overridden by setting new values in the custom configuration file(s). + +.. literalinclude:: ../../metplotpy/plots/config/tcmpr_defaults.yaml + +**NOTE**: This default configuration file is automatically loaded by +**tcmpr.py** and **does not require any modifications**. + +In the default config file, logging is set to stdout and the log level is ERROR (i.e. any log messages +of type ERROR will be logged). If the log_filename and log_level are +not specified in the custom configuration file, these settings will be used. + + +Custom Configuration File +------------------------- + +A second, *mandatory* configuration file is required, which is +used to customize the settings to the specified TCMPR plot type(s). The **tcmpr_multi_plots.yaml** +file is included with the source code. The settings in this custom configuration file override those in the +default config file. + +Copy this custom config file from the directory where the source code was +saved to the working directory: + +.. code-block:: ini + + cp $METPLOTPY_BASE/test/tcmpr_plots/tcmpr_multi_plots.yaml $WORKING_DIR/tcmpr_multi_plots.yaml + +Specify the input data in one of two ways: + +* Specify by directory (use all files under this directory): + + tcst_dir: '/path/to/tcmpr_sample_data' + + Replace the */path/to* with the full path to the sample data + +* Specify by list of .tcst files: + + tcst_files: ['a.tcst', 'b.tcst', 'w.tcst', 'z.tcst' ] + +Specify the series/line values of interest: + +* series_val_1: + AMODEL: + - H221 + - M221 + + specify a key (AMODEL) and a list of one or more values of interest (e.g. the H221 and M221 models) + +Specify the independent (x-axis) variable, values and labels: + +* indy_var: 'LEAD' + +* indy_vals: + - 0 + - 6 + - 12 + - 18 + +* indy_labels: + - '00' + - '06' + - '12' + - '18' + +The example above is requesting the forecast lead times ('LEAD' for the example data set provided) for 0, 6, 12, and 18 +hours with the corresponding labels (surrounded by either single or double quotes). The indy_var is set to 'LEAD' in +the tcmpr_defaults.yaml config file. Override this to the name of the forecast lead column in the input +data. + + +Specify the criteria for subsetting the input data: + +* fixed_vars_vals_input: + BASIN: + - AL + LEVEL: + - SS + - SD + - TS + - TD + - HU + + +In the example above, the data to be considered should correspond to the Atlantic Basin and the five specified levels. + +Modify the *tcst_dir* setting in the +*$WORKING_DIR/tcmpr_multi_plots.yaml* file to +explicitly point to the *$METPLOTPY_BASE/test/tcmpr_plots/Data* +directory to use the sample data. +Replace the */path/to/tcmpr_sample_data* with the full path +*$METPLOTPY/test/tcmpr_plots/Data* +(including replacing *$METPLOTPY_BASE* with the full path to the METplotpy +installation on the system). Modify the *tcst_dir* +setting to point to the output path where the plot will be saved. + + +For example: + +*tcst_dir: /username/myworkspace/METplotpy/test/tcmpr_plots/Data* + +*prefix: /prefix_applied_to_all_plot_names* + +The */username/myworkspace/METplotpy* corresponds to *$METPLOTPY_BASE* and +*/username/working_dir* corresponds to *$WORKING_DIR*. Make sure that the +*$WORKING_DIR* directory that is specified exists and has the appropriate +read and write permissions. The prefix specified for *plot_filename* may be +changed to the output directory of one's choosing. If this is not set, +then the *plot_filename* setting specified in the +*$METPLOTPY_BASE/metplotpy/plots/config/line_defaults.yaml* +configuration file will be used. + +To save the intermediate **.points1** file (used by METviewer and is useful +for debugging but not required), set the *dump_points_1* +setting to True. Uncomment or add (if it doesn't exist) the +*points_path* setting. + +*dump_points_1: 'True'* + +*points_path: '/dir_to_save_points1_file'* + +Replace the */dir_to_save_points1_file* to the same directory where +the **.points1** file is saved. +If *points_path* is commented out (indicated by a '#' symbol in front of it), +remove the '#' symbol to uncomment the points_path so that it will be +used by the code. Make sure that this directory exists and has the +appropriate read and write permissions. **NOTE**: the *points_path* setting +is **optional** and does not need to be defined in the configuration file +unless saving the intermediate **.points1** file is desired. + +To save the log output to a file, uncomment the *log_filename* entry and specify the path and +name of the log file. Select a directory with the appropriate read and write +privileges. To modify the verbosity of logging than what is set in the default config +file, uncomment the *log_level* entry and specify the log level (debug and info are higher verbosity, warning and error +are lower verbosity). + + +Generate seven different plot types in one configuration file: +------------------------------------------------------------- + +To use the *default* settings defined in the **line_defaults.yaml** +file, specify a minimal custom configuration file (**minimal_line.yaml**), +which consists of only a comment block, but can be any empty file +(if the user has write permissions for the output filename path corresponding +to the *plot_filename* setting in the default configuration file. +Otherwise the user will need to specify a *plot_filename* in the +**minimal_line.yaml** file): + +.. literalinclude:: ../../test/line/minimal_line.yaml + + +Copy this file to the working directory: + +.. code-block:: ini + + cp $METPLOTPY_BASE/test/line/minimal_line.yaml $WORKING_DIR/minimal_line.yaml + + +Add the *stat_input* (input data) and *plot_filename* (output file/plot path) +settings to the **$WORKING_DIR/minimal_line.yaml** +file (anywhere below the comment block). The *stat_input* setting +explicitly indicates where the sample data and custom configuration +files are located. Set the *stat_input* to +*$METPLOTPY_BASE/test/line/line.data* and set the +*plot_filename* to *$WORKING_DIR/output_plots/line_default.png* (making sure to +replace environment variables with their actual values): + +*stat_input: $METPLOTPY_BASE/test/line/line.data* + +*plot_filename: $WORKING_DIR/output_plots/line_default.png* + +*$WORKING_DIR* is the working directory where all the custom +configuration files are being saved. **NOTE**: If the *plot_filename* +(output directory) is specified to a directory other than the +*$WORKING_DIR/output_plots*, the user must have read and write permissions +to that directory. + +**NOTE**: This default plot does not display any of the data points. +It is to be used as a template for setting up margins, captions, +label sizes, etc. + +Run from the Command Line +========================= + +The **tcmpr_multi_plots.yaml** configuration file, in combination with the +**tcmpr_defaults.yaml** configuration file, generates the following plots: + * + +.. image:: figure/line.png + +To generate the seven plot types using the **tcmpr_defaults.yaml** and +**tcmpr_multi_plots.yaml** config files, perform the following: + +* If using the conda environment, verify the conda environment + is running and has the required + `Python packages + `_ + outlined in the requirements section. + +* Set the METPLOTPY_BASE environment variable to point to + *$METPLOTPY_BASE*. + + For the ksh environment: + + .. code-block:: ini + + export METPLOTPY_BASE=$METPLOTPY_BASE + + For the csh environment: + + .. code-block:: ini + + setenv METPLOTPY_BASE $METPLOTPY_BASE + + Recall that *$METPLOTPY_BASE* is the directory path indicating where the METplotpy source code was saved. + + To generate the above **"custom"** plot (i.e using some custom + configuration settings), use the custom configuration file, + **custom_line.yaml**. + +* Enter the following command: + + .. code-block:: ini + + python $METPLOTPY_BASE/metplotpy/plots/tcmpr_plots/tcmpr.py $WORKING_DIR/tcmpr_multi_plots.yaml + + +* Fourteen different output files will be created in the directory specified in + the *plot_dir* configuration setting in the **tcmpr_multi_plots.yaml** config file. + + + +* A **line_default.png** output file will be created in the + directory specified in the *plot_filename* configuration setting + in the **line_defaults.yaml** config file. + + .. image:: figure/line_default.png + + **NOTE**: This default plot does not display any of the data points. + It is to be used as a template for + setting up margins, captions, label sizes, etc. From 55e23d29705ffaf6918e60e7f43fd9ab1d58fc51 Mon Sep 17 00:00:00 2001 From: bikegeek Date: Tue, 12 Mar 2024 17:52:42 -0600 Subject: [PATCH 28/72] changed file permissions --- docs/Users_Guide/tcmpr_plots.rst | 0 1 file changed, 0 insertions(+), 0 deletions(-) mode change 100755 => 100644 docs/Users_Guide/tcmpr_plots.rst diff --git a/docs/Users_Guide/tcmpr_plots.rst b/docs/Users_Guide/tcmpr_plots.rst old mode 100755 new mode 100644 From 0e537762004cf1151c63137ab55878fae747aecb Mon Sep 17 00:00:00 2001 From: bikegeek Date: Tue, 12 Mar 2024 17:54:22 -0600 Subject: [PATCH 29/72] Added tcmpr_plots to the Table of Contents --- docs/Users_Guide/index.rst | 1 + 1 file changed, 1 insertion(+) diff --git a/docs/Users_Guide/index.rst b/docs/Users_Guide/index.rst index acd7b539..6ee9fad2 100644 --- a/docs/Users_Guide/index.rst +++ b/docs/Users_Guide/index.rst @@ -92,6 +92,7 @@ Atmospheric Research (NCAR), sponsored by National Science Foundation. polar_plot wind_rose fv3_physics + tcmpr_plots release-notes references From 57a78cb7072a01e7a818ee59c39d9d2566b960ef Mon Sep 17 00:00:00 2001 From: bikegeek Date: Wed, 13 Mar 2024 17:44:19 -0600 Subject: [PATCH 30/72] issue #383 plot images added for TCMPR plotter --- .../ABS(AMAX_WIND-BMAX_WIND)_boxplot.png | Bin 0 -> 216471 bytes .../figure/ABS(AMAX_WIND-BMAX_WIND)_mean.png | Bin 0 -> 167485 bytes .../figure/ABS(AMAX_WIND-BMAX_WIND)_median.png | Bin 0 -> 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