| 1 | """ |
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| 2 | Functions used to calculate the root mean square deviation. |
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| 3 | |
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| 4 | Duncan Gray, GA - 2007 |
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| 5 | |
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| 6 | """ |
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| 7 | |
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| 8 | |
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| 9 | #---------------------------------------------------------------------------- |
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| 10 | # Import necessary modules |
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| 11 | #---------------------------------------------------------------------------- |
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| 12 | |
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| 13 | # Standard modules |
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| 14 | import os |
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| 15 | from os import sep, path |
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| 16 | from csv import writer |
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| 17 | from time import localtime, strftime |
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| 18 | |
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| 19 | # Related major packages |
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| 20 | from Numeric import arange, array, zeros, Float, where, greater, less, \ |
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| 21 | compress, argmin, choose, searchsorted, sqrt, sum |
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| 22 | |
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| 23 | import project |
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| 24 | from os import sep |
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| 25 | from anuga.shallow_water.data_manager import csv2dict |
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| 26 | from anuga.utilities.numerical_tools import ensure_numeric, err, norm |
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| 27 | |
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| 28 | from slope import load_sensors |
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| 29 | from anuga.utilities.interp import interp |
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| 30 | |
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| 31 | def get_max_min_condition_array(min, max, vector): |
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| 32 | """ |
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| 33 | Given a vector of values, and minimum and maximum values, return a |
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| 34 | vector of 0/1's that can be used to cut arrays so only the times |
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| 35 | in the min max range are used. |
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| 36 | |
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| 37 | precondition: The vector values are ascending. |
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| 38 | |
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| 39 | """ |
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| 40 | |
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| 41 | SMALL_MIN = -1e10 # Not that small, but small enough |
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| 42 | vector = ensure_numeric(vector) |
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| 43 | assert min > SMALL_MIN |
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| 44 | no_maxs = where(less(vector,max), vector, SMALL_MIN) |
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| 45 | #print "no_maxs", no_maxs |
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| 46 | band_condition = greater(no_maxs, min) |
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| 47 | return band_condition |
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| 48 | |
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| 49 | def auto_rrms(outputdir_tag, scenarios, quantity, y_location_tag=':0.0'): |
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| 50 | """ |
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| 51 | Given a list of scenarios that have CSV guage files, calc the |
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| 52 | err, Number_of_samples and rmsd for all gauges in each scenario. |
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| 53 | Write this info to a file for each scenario. |
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| 54 | """ |
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| 55 | for run_data in scenarios: |
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| 56 | # Don't need to do this. The simulation .csv files are already |
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| 57 | # anuga_times |
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| 58 | #anuga_start_stop_times = [] |
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| 59 | #for time in run_data['wave_start_stop_times']: |
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| 60 | # anuga_start_stop_times.append( \ |
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| 61 | # time - run_data['ANUGA_start_time']) |
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| 62 | |
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| 63 | location_sims = [] |
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| 64 | location_exps = [] |
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| 65 | for gauge_x in run_data['gauge_x']: |
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| 66 | gauge_x = str(gauge_x) |
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| 67 | location_sims.append(gauge_x + y_location_tag) |
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| 68 | location_exps.append(gauge_x) |
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| 69 | |
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| 70 | id = run_data['scenario_id'] |
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| 71 | outputdir_name = id + outputdir_tag |
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| 72 | pro_instance = project.Project(['data','flumes','Hinwood_2008'], |
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| 73 | outputdir_name=outputdir_name) |
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| 74 | end = id + ".csv" |
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| 75 | file_sim = pro_instance.outputdir + quantity + "_" + end |
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| 76 | file_exp = pro_instance.raw_data_dir + sep + id + 'pressfilt_exp_' \ |
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| 77 | + quantity + '.csv' |
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| 78 | file_err = pro_instance.rmsd_dir + sep + outputdir_name + "_" \ |
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| 79 | + quantity + "_err.csv" |
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| 80 | |
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| 81 | |
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| 82 | simulation, _ = csv2dict(file_sim) |
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| 83 | experiment, _ = csv2dict(file_exp) |
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| 84 | |
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| 85 | time_sim = [float(x) for x in simulation['time']] |
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| 86 | time_exp = [float(x) for x in experiment['Time']] |
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| 87 | time_sim = ensure_numeric(time_sim) |
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| 88 | time_exp = ensure_numeric(time_exp) |
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| 89 | #print "min(time_exp)", min(time_exp) |
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| 90 | #print "max(time_exp)", max(time_exp) |
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| 91 | |
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| 92 | # Trim the experimental data |
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| 93 | condition_exp = get_max_min_condition_array(run_data['wave_times'][0], |
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| 94 | run_data['wave_times'][1], |
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| 95 | time_exp) |
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| 96 | time_exp_cut = compress(condition_exp, time_exp) #, axis=axis) |
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| 97 | #print "min(time_exp_cut)", min(time_exp_cut) |
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| 98 | #print "max(time_exp_cut)", max(time_exp_cut) |
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| 99 | |
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| 100 | #assert min(time_sim) < min(time_exp) |
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| 101 | |
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| 102 | # Trim the simulation data |
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| 103 | |
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| 104 | |
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| 105 | |
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| 106 | print "Writing to ", file_err |
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| 107 | |
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| 108 | err_list = [] |
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| 109 | points = [] |
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| 110 | rmsd_list = [] |
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| 111 | for location_sim, location_exp in map(None, location_sims, |
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| 112 | location_exps): |
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| 113 | quantity_sim = [float(x) for x in simulation[location_sim]] |
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| 114 | quantity_exp = [float(x) for x in experiment[location_exp]] |
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| 115 | |
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| 116 | quantity_exp_cut = compress(condition_exp, quantity_exp) |
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| 117 | |
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| 118 | # Now let's do interpolation |
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| 119 | quantity_sim_interp = interp(quantity_sim, time_sim, time_exp_cut) |
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| 120 | |
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| 121 | assert len(quantity_sim_interp) == len(quantity_exp_cut) |
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| 122 | norm = err(quantity_sim_interp, |
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| 123 | quantity_exp_cut, |
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| 124 | 2, relative = False) # 2nd norm (rel. RMS) |
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| 125 | err_list.append(norm) |
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| 126 | points.append(len(quantity_sim_interp)) |
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| 127 | rmsd_list.append(norm/sqrt(len(quantity_sim_interp))) |
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| 128 | #print "norm", norm |
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| 129 | #for i in range(len(quantity_sim_interp)): |
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| 130 | |
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| 131 | #print "quantity_sim_interp", quantity_sim_interp[i] |
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| 132 | #print "quantity_exp_cut", quantity_exp_cut[i] |
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| 133 | assert len(location_exps) == len(err_list) |
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| 134 | |
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| 135 | # Writing the file out for one scenario |
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| 136 | a_writer = writer(file(file_err, "wb")) |
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| 137 | a_writer.writerow(["x location", "err", "Number_of_samples", "rmsd"]) |
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| 138 | a_writer.writerows(map(None, |
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| 139 | location_exps, |
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| 140 | err_list, |
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| 141 | points, |
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| 142 | rmsd_list)) |
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| 143 | |
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| 144 | |
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| 145 | |
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| 146 | def plot_rrms_sensor_settings(run_data, outputdir_tags, quantity, |
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| 147 | save_as=True, |
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| 148 | is_interactive=False, max_rmsd=None): |
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| 149 | """ |
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| 150 | For a scenario, do |
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| 151 | """ |
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| 152 | from pylab import ion, plot, xlabel, ylabel, close, legend, \ |
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| 153 | savefig, title, axis, setp, subplot, grid, axvspan, figlegend |
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| 154 | from anuga.shallow_water.data_manager import csv2dict |
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| 155 | |
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| 156 | |
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| 157 | plot_type = ".pdf" |
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| 158 | |
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| 159 | id = run_data['scenario_id'] |
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| 160 | |
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| 161 | if is_interactive: |
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| 162 | ion() |
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| 163 | time_date = strftime('plot date: %d/%m/%Y Time: %H:%M:%S', |
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| 164 | localtime()) |
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| 165 | subplot(212) |
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| 166 | plot_title = id + " Root Mean Square Deviation comparison" + '\n' \ |
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| 167 | + time_date |
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| 168 | |
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| 169 | title(plot_title) |
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| 170 | y_label = "RMSD" |
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| 171 | ylabel(y_label) |
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| 172 | xlabel("x location, m") |
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| 173 | grid(True) |
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| 174 | |
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| 175 | lines = [] |
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| 176 | for outputdir_tag in outputdir_tags: |
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| 177 | |
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| 178 | outputdir_name = id + outputdir_tag |
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| 179 | pro_instance = project.Project(['data','flumes','Hinwood_2008'], |
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| 180 | outputdir_name=outputdir_name) |
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| 181 | |
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| 182 | file_err = pro_instance.rmsd_dir + sep + outputdir_name + "_" \ |
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| 183 | + quantity + "_err.csv" |
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| 184 | |
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| 185 | simulation, _ = csv2dict(file_err) |
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| 186 | locations = [float(x) for x in simulation['x location']] |
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| 187 | rmsd_list = [float(x) for x in simulation['rmsd']] |
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| 188 | lines.append(plot(locations, rmsd_list)) |
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| 189 | |
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| 190 | if max_rmsd is not None: |
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| 191 | #print "setting axis" |
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| 192 | axis(ymin=0, ymax=max_rmsd) |
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| 193 | |
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| 194 | for break_x in run_data['break_xs']: |
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| 195 | axvspan(break_x-0.001,break_x+0.001, facecolor='g') |
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| 196 | |
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| 197 | legend(lines, outputdir_tags,'upper left') |
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| 198 | |
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| 199 | if is_interactive: |
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| 200 | # Wait for enter pressed |
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| 201 | raw_input() |
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| 202 | |
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| 203 | save_as = pro_instance.plots_dir + sep + \ |
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| 204 | id + "_rmsd" + plot_type |
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| 205 | if save_as is not None: |
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| 206 | savefig(save_as) |
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| 207 | |
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| 208 | #Need to close this plot |
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| 209 | close() |
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| 210 | |
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| 211 | def auto_plot_test_rmsd(scenarios, outputdir_tag, |
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| 212 | to_publish_indexes, quantity="stage", |
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| 213 | save_as=True,add_run_info=False, |
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| 214 | is_interactive=False, max_rmsd=0.012): |
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| 215 | """ |
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| 216 | Produce the RMSD graphs for the anuga article. |
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| 217 | |
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| 218 | """ |
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| 219 | |
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| 220 | tests = [] |
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| 221 | file_names = [] |
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| 222 | |
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| 223 | for i in range(0,len(scenarios),2): |
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| 224 | if to_publish_indexes.has_key(scenarios[i]['scenario_id']): |
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| 225 | tests.append([scenarios[i], scenarios[i+1]]) |
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| 226 | else: |
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| 227 | tests.append([scenarios[i+1], scenarios[i]]) |
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| 228 | |
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| 229 | for test in tests: |
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| 230 | file_name = plot_test_rmsd(test, outputdir_tag, quantity, |
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| 231 | to_publish_indexes, |
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| 232 | save_as=save_as, add_run_info=add_run_info, |
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| 233 | is_interactive=is_interactive, |
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| 234 | max_rmsd=max_rmsd) |
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| 235 | file_names.append(file_name) |
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| 236 | return file_names |
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| 237 | |
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| 238 | def plot_test_rmsd(test, outputdir_tag, quantity, |
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| 239 | to_publish_indexes, |
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| 240 | save_as=None, add_run_info=False, |
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| 241 | is_interactive=False, max_rmsd=None): |
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| 242 | """ |
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| 243 | For a test, plot rmsd vs x location for both runs. |
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| 244 | Also, add the break measurement. |
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| 245 | """ |
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| 246 | from pylab import ion, plot, xlabel, ylabel, close, legend, \ |
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| 247 | savefig, title, axis, setp, subplot, grid, axvspan, figlegend |
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| 248 | from anuga.shallow_water.data_manager import csv2dict |
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| 249 | |
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| 250 | plot_type = ".pdf" |
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| 251 | id = 'S' + test[0]['scenario_id'][1:2] |
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| 252 | |
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| 253 | if add_run_info is True: |
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| 254 | plot_title = "Title will not be in final draft \n" + \ |
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| 255 | id + outputdir_tag |
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| 256 | |
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| 257 | title(plot_title) |
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| 258 | else: |
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| 259 | plot_title = "" |
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| 260 | |
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| 261 | if is_interactive: |
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| 262 | ion() |
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| 263 | time_date = strftime('plot date: %d/%m/%Y Time: %H:%M:%S', |
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| 264 | localtime()) |
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| 265 | #subplot(212) |
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| 266 | |
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| 267 | |
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| 268 | #title(plot_title) |
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| 269 | y_label = "RMSD" |
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| 270 | ylabel(y_label) |
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| 271 | xlabel("x location, m") |
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| 272 | grid(True) |
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| 273 | |
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| 274 | lines = [] |
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| 275 | legend_name = [] |
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| 276 | i = 0 |
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| 277 | for run in test: |
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| 278 | i += 1 |
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| 279 | legend_name.append("S" + test[0]['scenario_id'][1:2]+"R"+str(i)) |
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| 280 | outputdir_name = run['scenario_id'] + outputdir_tag |
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| 281 | pro_instance = project.Project(['data','flumes','Hinwood_2008'], |
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| 282 | outputdir_name=outputdir_name) |
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| 283 | |
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| 284 | file_err = pro_instance.rmsd_dir + sep + outputdir_name + "_" \ |
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| 285 | + quantity + "_err.csv" |
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| 286 | |
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| 287 | simulation, _ = csv2dict(file_err) |
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| 288 | locations = [float(x) for x in simulation['x location']] |
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| 289 | rmsd_list = [float(x) for x in simulation['rmsd']] |
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| 290 | |
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| 291 | |
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| 292 | lines.append(plot(locations, rmsd_list, 'k-x')) # k is black |
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| 293 | |
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| 294 | for i_gauge, (location, rmsd) in enumerate(map(None, |
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| 295 | locations, |
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| 296 | rmsd_list)): |
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| 297 | if to_publish_indexes.has_key(run['scenario_id']) and \ |
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| 298 | to_publish_indexes[run['scenario_id']].count(i_gauge) == 1: |
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| 299 | plot([location], [rmsd], 'ko', markeredgewidth=2, |
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| 300 | markeredgecolor='k') |
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| 301 | |
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| 302 | |
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| 303 | |
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| 304 | for break_x in run['break_xs']: |
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| 305 | axvspan(break_x-0.001,break_x+0.001, facecolor='g') |
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| 306 | |
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| 307 | if max_rmsd is not None: |
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| 308 | #print "setting axis" |
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| 309 | axis(ymin=0, ymax=max_rmsd) |
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| 310 | |
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| 311 | if id == 'S2': |
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| 312 | # Hack to get the desired width |
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| 313 | axis(xmax=7.0) |
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| 314 | |
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| 315 | setp(lines[1], linestyle='--') |
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| 316 | legend(lines, legend_name,'upper left') |
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| 317 | |
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| 318 | if is_interactive: |
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| 319 | raw_input() |
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| 320 | |
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| 321 | save_as = pro_instance.plots_dir + sep + \ |
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| 322 | id + "-rmsd" + plot_type |
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| 323 | print "save_as", save_as |
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| 324 | if save_as is not None: |
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| 325 | savefig(save_as) |
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| 326 | |
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| 327 | close() |
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| 328 | |
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| 329 | return save_as |
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| 330 | |
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| 331 | # Return a bunch of lists |
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| 332 | # The err files, for all scenarios |
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| 333 | def err_files(scenarios, outputdir_tag, rmsd_dir, quantity): |
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| 334 | """ |
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| 335 | Create a list of err files, for a list of scenarios. |
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| 336 | """ |
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| 337 | file_errs = [] |
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| 338 | for scenario in scenarios: |
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| 339 | id = scenario['scenario_id'] |
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| 340 | outputdir_name = id + outputdir_tag |
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| 341 | file_err = rmsd_dir + sep + outputdir_name + "_" \ |
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| 342 | + quantity + "_err.csv" |
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| 343 | file_errs.append(file_err) |
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| 344 | return file_errs |
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| 345 | |
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| 346 | |
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| 347 | def compare_different_settings(outputdir_tags, scenarios, quantity, |
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| 348 | save_as=None, |
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| 349 | is_interactive=False): |
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| 350 | """ |
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| 351 | Calculate the RMSD for all the tests in a scenario |
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| 352 | """ |
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| 353 | |
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| 354 | # A bit hacky. Getting a pro_instance to get the rmsd_dir. |
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| 355 | outputdir_name = scenarios[0]['scenario_id'] + outputdir_tags[0] |
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| 356 | pro_instance = project.Project(['data','flumes','Hinwood_2008'], |
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| 357 | outputdir_name=outputdir_name) |
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| 358 | |
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| 359 | |
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| 360 | settings = {} # keys are different settings. |
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| 361 | # For each setting there will be err and amount |
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| 362 | |
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| 363 | for outputdir_tag in outputdir_tags: |
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| 364 | files = err_files(scenarios, outputdir_tag, pro_instance.rmsd_dir, |
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| 365 | quantity) |
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| 366 | sim = {} |
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| 367 | for run_data, file in map(None, scenarios, files): |
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| 368 | |
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| 369 | simulation, _ = csv2dict(file) |
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| 370 | #locations = [float(x) for x in simulation['x location']] |
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| 371 | err_list = [float(x) for x in simulation['err']] |
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| 372 | amount_list = [float(x) for x in simulation['Number_of_samples']] |
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| 373 | |
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| 374 | if sim.has_key('err'): |
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| 375 | err_list.append(sim['err']) |
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| 376 | amount_list.append(sim['amount']) |
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| 377 | sim['err'], sim['amount'] = err_addition(err_list, |
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| 378 | amount_list) |
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| 379 | sim['rmsd'] = sim['err']/sqrt(sim['amount']) |
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| 380 | settings[outputdir_tag] = sim |
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| 381 | #print "settings", settings |
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| 382 | |
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| 383 | aux = [(settings[k]['rmsd'], k) for k in settings.keys()] |
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| 384 | aux.sort() |
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| 385 | for val, key in aux: |
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| 386 | print key + " " + str(val) |
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| 387 | |
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| 388 | |
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| 389 | |
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| 390 | def err_addition(err_list, amount_list): |
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| 391 | """ |
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| 392 | err1 is the err value (sqrt(sum_over_x&y((xi - yi)^2))) for a set of values |
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| 393 | amount1 is the number of values associated with the err. |
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| 394 | |
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| 395 | If this function gets used alot, maybe pull this out and make it an object |
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| 396 | """ |
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| 397 | err = norm(ensure_numeric(err_list)) |
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| 398 | amount = sum(ensure_numeric(amount_list)) |
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| 399 | |
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| 400 | return err, amount |
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| 401 | |
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| 402 | |
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| 403 | def calc_max_rmsd(scenarios, outputdir_tags, quantity): |
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| 404 | |
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| 405 | max_rmsd = 0 |
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| 406 | |
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| 407 | for run_data in scenarios: |
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| 408 | id = run_data['scenario_id'] |
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| 409 | for outputdir_tag in outputdir_tags: |
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| 410 | |
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| 411 | outputdir_name = id + outputdir_tag |
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| 412 | pro_instance = project.Project(['data','flumes','Hinwood_2008'], |
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| 413 | outputdir_name=outputdir_name) |
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| 414 | |
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| 415 | file_err = pro_instance.rmsd_dir + sep + outputdir_name + "_" \ |
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| 416 | + quantity + "_err.csv" |
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| 417 | |
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| 418 | simulation, _ = csv2dict(file_err) |
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| 419 | rmsd_list = [float(x) for x in simulation['rmsd']] |
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| 420 | max_rmsd = max(max(rmsd_list), max_rmsd) |
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| 421 | return max_rmsd |
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| 422 | |
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| 423 | |
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| 424 | def auto_plot_rrms_sensor_settings(outputdir_tags, scenarios, quantity, |
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| 425 | save_as=None, |
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| 426 | is_interactive=False): |
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| 427 | """ |
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| 428 | The general auto, for comparing things. |
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| 429 | |
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| 430 | """ |
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| 431 | max_rmsd = calc_max_rmsd(scenarios, outputdir_tags, quantity) |
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| 432 | print "max_rmsd", max_rmsd |
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| 433 | for run_data in scenarios: |
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| 434 | plot_rrms_sensor_settings(run_data, outputdir_tags, quantity, |
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| 435 | max_rmsd=max_rmsd) |
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| 436 | |
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| 437 | #------------------------------------------------------------- |
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| 438 | if __name__ == "__main__": |
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| 439 | """ |
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| 440 | """ |
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| 441 | from scenarios import scenarios |
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| 442 | |
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| 443 | outputdir_tags = [] |
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| 444 | outputdir_tags.append("_lmts_wdth_0.1_z_0.0_ys_0.01_mta_0.01_I") |
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| 445 | outputdir_tags.append("_no_velocity_nolmts_wdth_0.1_z_0.0_ys_0.01_mta_0.01_I") |
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| 446 | outputdir_tags.append("_nolmts_wdth_0.1_z_0.0_ys_0.01_mta_0.0001_I") |
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| 447 | outputdir_tags.append("_nolmts_wdth_0.1_z_0.0_ys_0.01_mta_0.001_I") |
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| 448 | outputdir_tags.append("_nolmts_wdth_0.1_z_0.0_ys_0.01_mta_0.01_I") |
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| 449 | outputdir_tags.append("_nolmts_wdth_0.1_z_0.012_ys_0.01_mta_0.01_I") |
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| 450 | outputdir_tags.append("_nolmts_wdth_1.0_z_0.0_ys_0.01_mta_0.01_I") |
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| 451 | outputdir_tags.append("_nolmts_wdth_0.1_z_0.012_ys_0.01_mta_0.0001_I") |
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| 452 | outputdir_tags.append("_lmts_wdth_0.1_z_0.0_ys_0.01_mta_0.0001_I") |
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| 453 | outputdir_tags.append("_no_velocity_nolmts_wdth_0.1_z_0.0_ys_0.01_mta_0.0001_I") |
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| 454 | |
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| 455 | outputdir_tags = [] |
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| 456 | outputdir_tags.append("_nolmts_wdth_0.1_z_0.0_ys_0.01_mta_0.01_I") |
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| 457 | #outputdir_tag = "_test_limiterC" |
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| 458 | #scenarios = [scenarios[0]] # !!!!!!!!!!!!!!!!!!!!!! |
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| 459 | #scenarios = scenarios[4:] # !!!!!!!!!!!!!!!!!!!!!! |
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| 460 | calc_rmsds = True |
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| 461 | #calc_rmsds = False |
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| 462 | if calc_rmsds: |
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| 463 | for outputdir_tag in outputdir_tags: |
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| 464 | auto_rrms(outputdir_tag, scenarios, "stage", y_location_tag=':0.0') |
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| 465 | |
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| 466 | #scenarios = [scenarios[0]] # !!!!!!!!!!!!!!!!!!!!!! |
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| 467 | #auto_plot_rrms_sensor_settings(outputdir_tags, scenarios, "stage") |
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| 468 | compare_different_settings(outputdir_tags, scenarios, "stage") |
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| 469 | |
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| 470 | outputdir_tag = "_nolmts_wdth_0.1_z_0.0_ys_0.01_mta_0.01_I" |
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| 471 | #auto_plot_test_rmsd(scenarios, outputdir_tag) |
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