[2849] | 1 | #!/usr/bin/env python |
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| 2 | # -*- coding: utf-8 -*- |
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| 3 | |
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| 4 | # this must come first |
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| 5 | from __future__ import print_function, unicode_literals, division |
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| 6 | |
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| 7 | # standard library imports |
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| 8 | from argparse import ArgumentParser |
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| 9 | import os |
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| 10 | import os.path |
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| 11 | import datetime as dt |
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| 12 | from dateutil.relativedelta import relativedelta |
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| 13 | import numpy as np |
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| 14 | |
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| 15 | # Application library imports |
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| 16 | from libconso import * |
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| 17 | |
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| 18 | |
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| 19 | ######################################## |
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| 20 | class DataDict(dict): |
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| 21 | #--------------------------------------- |
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| 22 | def __init__(self): |
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| 23 | self = {} |
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| 24 | |
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| 25 | #--------------------------------------- |
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| 26 | def init_range(self, date_beg, date_end, inc=1): |
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| 27 | """ |
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| 28 | """ |
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| 29 | delta = date_end - date_beg |
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| 30 | |
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| 31 | (deb, fin) = (0, delta.days+1) |
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| 32 | |
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| 33 | dates = (date_beg + dt.timedelta(days=i) |
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| 34 | for i in xrange(deb, fin, inc)) |
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| 35 | |
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| 36 | for date in dates: |
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| 37 | self.add_item(date) |
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| 38 | |
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| 39 | #--------------------------------------- |
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| 40 | def fill_data(self, filein): |
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| 41 | """ |
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| 42 | """ |
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| 43 | try: |
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| 44 | data = np.genfromtxt( |
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| 45 | filein, |
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| 46 | skip_header=1, |
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| 47 | converters={ |
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| 48 | 0: string_to_date, |
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| 49 | 1: string_to_float, |
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| 50 | 2: string_to_percent, |
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| 51 | 3: string_to_percent, |
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| 52 | 4: string_to_float, |
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| 53 | 5: string_to_float, |
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| 54 | 6: string_to_float, |
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| 55 | 7: string_to_float, |
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| 56 | 8: string_to_float, |
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| 57 | 9: string_to_float, |
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| 58 | 10: string_to_float, |
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| 59 | 11: string_to_float, |
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| 60 | }, |
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| 61 | missing_values="nan", |
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| 62 | ) |
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| 63 | except Exception as rc: |
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| 64 | print("Empty file {}:\n{}".format(filein, rc)) |
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| 65 | exit(1) |
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| 66 | |
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| 67 | for date, conso, real_use, theo_use, \ |
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| 68 | runp_mean, penp_mean, runp_std, penp_std, \ |
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| 69 | runf_mean, penf_mean, runf_std, penf_std in data: |
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| 70 | if date in self: |
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| 71 | self.add_item( |
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| 72 | date, |
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| 73 | conso, |
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| 74 | real_use, |
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| 75 | theo_use, |
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| 76 | runp_mean, |
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| 77 | penp_mean, |
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| 78 | runp_std, |
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| 79 | penp_std, |
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| 80 | runf_mean, |
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| 81 | penf_mean, |
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| 82 | runf_std, |
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| 83 | penf_std, |
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| 84 | ) |
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| 85 | self[date].fill() |
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| 86 | |
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| 87 | #--------------------------------------- |
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| 88 | def add_item(self, date, conso=np.nan, |
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| 89 | real_use=np.nan, theo_use=np.nan, |
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| 90 | runp_mean=np.nan, penp_mean=np.nan, |
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| 91 | runp_std=np.nan, penp_std=np.nan, |
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| 92 | runf_mean=np.nan, penf_mean=np.nan, |
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| 93 | runf_std=np.nan, penf_std=np.nan): |
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| 94 | """ |
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| 95 | """ |
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| 96 | self[date] = Conso( |
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| 97 | date, conso, real_use, theo_use, |
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| 98 | runp_mean, penp_mean, runp_std, penp_std, |
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| 99 | runf_mean, penf_mean, runf_std, penf_std, |
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| 100 | ) |
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| 101 | |
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| 102 | #--------------------------------------- |
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| 103 | def theo_equation(self): |
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| 104 | """ |
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| 105 | """ |
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| 106 | (dates, theo_uses) = \ |
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| 107 | zip(*((item.date, item.theo_use) |
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| 108 | for item in self.get_items_in_full_range())) |
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| 109 | |
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| 110 | (idx_min, idx_max) = \ |
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| 111 | (np.nanargmin(theo_uses), np.nanargmax(theo_uses)) |
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| 112 | |
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| 113 | x1 = dates[idx_min].timetuple().tm_yday |
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| 114 | x2 = dates[idx_max].timetuple().tm_yday |
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| 115 | |
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| 116 | y1 = theo_uses[idx_min] |
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| 117 | y2 = theo_uses[idx_max] |
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| 118 | |
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| 119 | m = np.array([[x1, 1.], [x2, 1.]], dtype="float") |
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| 120 | n = np.array([y1, y2], dtype="float") |
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| 121 | |
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| 122 | poly_ok = True |
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| 123 | try: |
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| 124 | poly_theo = np.poly1d(np.linalg.solve(m, n)) |
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| 125 | except np.linalg.linalg.LinAlgError: |
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| 126 | poly_ok = False |
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| 127 | |
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| 128 | if poly_ok: |
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| 129 | delta = (dates[0] + relativedelta(months=2) - dates[0]).days |
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| 130 | |
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| 131 | poly_delay = np.poly1d( |
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| 132 | [poly_theo[1], poly_theo[0] - poly_theo[1] * delta] |
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| 133 | ) |
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| 134 | |
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| 135 | self.poly_theo = poly_theo |
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| 136 | self.poly_delay = poly_delay |
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| 137 | |
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| 138 | #--------------------------------------- |
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| 139 | def get_items_in_range(self, date_beg, date_end, inc=1): |
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| 140 | """ |
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| 141 | """ |
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| 142 | items = (item for item in self.itervalues() |
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| 143 | if item.date >= date_beg and |
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| 144 | item.date <= date_end) |
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| 145 | items = sorted(items, key=lambda item: item.date) |
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| 146 | |
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| 147 | return items[::inc] |
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| 148 | |
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| 149 | #--------------------------------------- |
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| 150 | def get_items_in_full_range(self, inc=1): |
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| 151 | """ |
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| 152 | """ |
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| 153 | items = (item for item in self.itervalues()) |
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| 154 | items = sorted(items, key=lambda item: item.date) |
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| 155 | |
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| 156 | return items[::inc] |
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| 157 | |
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| 158 | #--------------------------------------- |
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| 159 | def get_items(self, inc=1): |
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| 160 | """ |
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| 161 | """ |
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| 162 | items = (item for item in self.itervalues() |
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| 163 | if item.isfilled()) |
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| 164 | items = sorted(items, key=lambda item: item.date) |
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| 165 | |
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| 166 | return items[::inc] |
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| 167 | |
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| 168 | |
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| 169 | class Conso(object): |
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| 170 | #--------------------------------------- |
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| 171 | def __init__( |
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| 172 | self, date, conso=np.nan, |
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| 173 | real_use=np.nan, theo_use=np.nan, |
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| 174 | runp_mean=np.nan, penp_mean=np.nan, |
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| 175 | runp_std=np.nan, penp_std=np.nan, |
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| 176 | runf_mean=np.nan, penf_mean=np.nan, |
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| 177 | runf_std=np.nan, penf_std=np.nan, |
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| 178 | ): |
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| 179 | self.date = date |
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| 180 | self.conso = conso |
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| 181 | self.real_use = real_use |
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| 182 | self.theo_use = theo_use |
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| 183 | self.poly_theo = np.poly1d([]) |
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| 184 | self.poly_delay = np.poly1d([]) |
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| 185 | self.runp_mean = runp_mean |
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| 186 | self.penp_mean = penp_mean |
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| 187 | self.runp_std = runp_std |
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| 188 | self.penp_std = penp_std |
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| 189 | self.runf_mean = runf_mean |
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| 190 | self.penf_mean = penf_mean |
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| 191 | self.runf_std = runf_std |
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| 192 | self.penf_std = penf_std |
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| 193 | self.filled = False |
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| 194 | |
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| 195 | #--------------------------------------- |
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| 196 | def __repr__(self): |
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| 197 | return "{:.2f} ({:.2%})".format(self.conso, self.real_use) |
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| 198 | |
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| 199 | #--------------------------------------- |
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| 200 | def isfilled(self): |
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| 201 | return self.filled |
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| 202 | |
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| 203 | #--------------------------------------- |
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| 204 | def fill(self): |
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| 205 | self.filled = True |
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| 206 | |
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| 207 | |
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| 208 | ######################################## |
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| 209 | def plot_init(): |
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| 210 | paper_size = np.array([29.7, 21.0]) |
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| 211 | fig, (ax_jobsp, ax_jobsf) = plt.subplots( |
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| 212 | nrows=2, |
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| 213 | ncols=1, |
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| 214 | sharex=True, |
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| 215 | squeeze=True, |
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| 216 | figsize=(paper_size/2.54) |
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| 217 | ) |
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| 218 | |
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| 219 | return fig, ax_jobsp, ax_jobsf |
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| 220 | |
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| 221 | |
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| 222 | ######################################## |
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| 223 | def plot_data(ax_jobsp, ax_jobsf, xcoord, dates, |
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| 224 | runp_mean, penp_mean, runp_std, penp_std, |
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| 225 | runf_mean, penf_mean, runf_std, penf_std): |
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| 226 | """ |
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| 227 | """ |
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| 228 | |
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| 229 | line_width = 0. |
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| 230 | width = 1.05 |
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| 231 | |
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| 232 | ax_jobsp.bar( |
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| 233 | xcoord, runp_mean, width=width, align="center", |
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| 234 | # yerr=runp_std/2, ecolor="green", |
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| 235 | color="lightgreen", linewidth=line_width, |
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| 236 | antialiased=True, label="jobs running" |
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| 237 | ) |
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| 238 | ax_jobsp.bar( |
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| 239 | xcoord, penp_mean, bottom=runp_mean, width=width, align="center", |
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| 240 | # yerr=penp_std/2, ecolor="darkred", |
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| 241 | color="firebrick", linewidth=line_width, |
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| 242 | antialiased=True, label="jobs pending" |
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| 243 | ) |
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| 244 | |
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| 245 | ax_jobsf.bar( |
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| 246 | xcoord, runf_mean, width=width, align="center", |
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| 247 | # yerr=runf_std/2, ecolor="green", |
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| 248 | color="lightgreen", linewidth=line_width, |
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| 249 | antialiased=True, label="jobs running" |
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| 250 | ) |
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| 251 | ax_jobsf.bar( |
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| 252 | xcoord, penf_mean, bottom=runf_mean, width=width, align="center", |
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| 253 | # yerr=penf_std/2, ecolor="darkred", |
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| 254 | color="firebrick", linewidth=line_width, |
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| 255 | antialiased=True, label="jobs pending\n(Ressources & Priority)" |
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| 256 | ) |
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| 257 | |
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| 258 | |
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| 259 | ######################################## |
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| 260 | def plot_config(fig, ax_conso, ax_theo, xcoord, dates, title, |
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| 261 | conso_per_day, conso_per_day_2): |
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| 262 | """ |
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| 263 | """ |
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| 264 | from matplotlib.ticker import AutoMinorLocator |
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| 265 | |
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| 266 | # ... Config axes ... |
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| 267 | # ------------------- |
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| 268 | # 1) Range |
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| 269 | jobsp_max = np.nanmax(runp_mean) |
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| 270 | jobsf_max = np.nanmax(runf_mean) |
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| 271 | conso_jobsf = 80000. |
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| 272 | if args.max: |
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| 273 | ymax_jobsp = jobsp_max # * 1.1 |
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| 274 | ymax_jobsf = jobsf_max # * 1.1 |
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| 275 | else: |
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| 276 | ymax_jobsp = 2. * (max(conso_per_day, conso_per_day_2)/24.) |
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| 277 | ymax_jobsf = 3. * conso_jobsf |
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| 278 | |
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| 279 | xmin, xmax = xcoord[0]-1, xcoord[-1]+1 |
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| 280 | ax_jobsp.set_xlim(xmin, xmax) |
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| 281 | ax_jobsp.set_ylim(0., ymax_jobsp) |
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| 282 | ax_jobsf.set_ylim(0., ymax_jobsf) |
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| 283 | |
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| 284 | # 2) Plot ideal daily consumption in hours |
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| 285 | line_color = "blue" |
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| 286 | line_alpha = 0.5 |
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| 287 | line_label = "conso journaliÚre\nidéale ({})" |
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| 288 | for ax, y_div, label in ( |
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| 289 | (ax_jobsp, 24., line_label.format("cÅurs")), |
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| 290 | ): |
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| 291 | if conso_per_day_2: |
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| 292 | list_x = [0, xmax/2, xmax/2, xmax] |
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| 293 | list_y = np.array( |
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| 294 | [conso_per_day, conso_per_day, conso_per_day_2, conso_per_day_2], |
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| 295 | dtype=float |
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| 296 | ) |
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| 297 | ax.plot( |
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| 298 | list_x, list_y/y_div, |
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| 299 | color=line_color, alpha=line_alpha, label=label, |
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| 300 | ) |
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| 301 | else: |
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| 302 | ax.axhline( |
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| 303 | y=conso_per_day/y_div, |
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| 304 | color=line_color, alpha=line_alpha, label=label, |
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| 305 | ) |
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| 306 | ax_jobsf.axhline( |
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| 307 | y=conso_jobsf, |
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| 308 | color=line_color, alpha=line_alpha |
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| 309 | ) |
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| 310 | |
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| 311 | # 3) Ticks labels |
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| 312 | (date_beg, date_end) = (dates[0], dates[-1]) |
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| 313 | date_fmt = "{:%d-%m}" |
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| 314 | |
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| 315 | if date_end - date_beg > dt.timedelta(weeks=9): |
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| 316 | maj_xticks = [x for x, d in zip(xcoord, dates) |
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| 317 | if d.weekday() == 0] |
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| 318 | maj_xlabs = [date_fmt.format(d) for d in dates |
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| 319 | if d.weekday() == 0] |
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| 320 | else: |
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| 321 | maj_xticks = [x for x, d in zip(xcoord, dates)] |
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| 322 | maj_xlabs = [date_fmt.format(d) for d in dates] |
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| 323 | |
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| 324 | ax_jobsf.set_xticks(xcoord, minor=True) |
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| 325 | ax_jobsf.set_xticks(maj_xticks, minor=False) |
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| 326 | ax_jobsf.set_xticklabels( |
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| 327 | maj_xlabs, rotation="vertical", size="x-small" |
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| 328 | ) |
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| 329 | |
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| 330 | for ax, y, label in ( |
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| 331 | (ax_jobsp, conso_per_day / 24., "cÅurs (projet)"), |
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| 332 | (ax_jobsf, conso_jobsf, "cÅurs (machine)"), |
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| 333 | ): |
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| 334 | minor_locator = AutoMinorLocator() |
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| 335 | ax.yaxis.set_minor_locator(minor_locator) |
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| 336 | |
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| 337 | yticks = list(ax.get_yticks()) |
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| 338 | yticks.append(y) |
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| 339 | ax.set_yticks(yticks) |
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| 340 | |
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| 341 | if conso_per_day_2: |
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| 342 | yticks.append(conso_per_day_2) |
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| 343 | |
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| 344 | for x, d in zip(xcoord, dates): |
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| 345 | if d.weekday() == 0 and d.hour == 0: |
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| 346 | for ax in (ax_jobsp, ax_jobsf): |
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| 347 | ax.axvline(x=x, color="black", alpha=0.5, |
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| 348 | linewidth=0.5, linestyle=":") |
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| 349 | |
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| 350 | # 4) Define axes title |
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| 351 | for ax, label in ( |
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| 352 | (ax_jobsp, "cÅurs (projet)"), |
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| 353 | (ax_jobsf, "cÅurs (machine)"), |
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| 354 | ): |
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| 355 | ax.set_ylabel(label, fontweight="bold") |
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| 356 | ax.tick_params(axis="y", labelsize="small") |
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| 357 | |
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| 358 | # 5) Define plot size |
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| 359 | fig.subplots_adjust( |
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| 360 | left=0.08, |
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| 361 | bottom=0.09, |
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| 362 | right=0.93, |
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| 363 | top=0.93, |
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| 364 | hspace=0.1, |
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| 365 | wspace=0.1, |
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| 366 | ) |
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| 367 | |
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| 368 | # ... Main title and legend ... |
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| 369 | # ----------------------------- |
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| 370 | fig.suptitle(title, fontweight="bold", size="large") |
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| 371 | for ax, subtitle, loc_legend in ( |
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| 372 | (ax_jobsp, "Projet", "upper right"), |
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| 373 | (ax_jobsf, "Tout Curie", "upper right"), |
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| 374 | ): |
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| 375 | ax.legend(loc=loc_legend, fontsize="x-small", frameon=False) |
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| 376 | ax.set_title(subtitle, loc="left") |
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| 377 | |
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| 378 | |
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| 379 | ######################################## |
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| 380 | def get_arguments(): |
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| 381 | parser = ArgumentParser() |
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| 382 | parser.add_argument("-v", "--verbose", action="store_true", |
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| 383 | help="verbose mode") |
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| 384 | parser.add_argument("-f", "--full", action="store_true", |
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| 385 | help="plot the whole period") |
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| 386 | parser.add_argument("-i", "--increment", action="store", |
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| 387 | type=int, default=1, dest="inc", |
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| 388 | help="sampling increment") |
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| 389 | parser.add_argument("-r", "--range", action="store", nargs=2, |
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| 390 | type=string_to_date, |
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| 391 | help="date range: ssaa-mm-jj ssaa-mm-jj") |
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| 392 | parser.add_argument("-m", "--max", action="store_true", |
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| 393 | help="plot with y_max = allocation") |
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| 394 | parser.add_argument("-s", "--show", action="store_true", |
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| 395 | help="interactive mode") |
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| 396 | parser.add_argument("-d", "--dods", action="store_true", |
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| 397 | help="copy output on dods") |
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| 398 | |
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| 399 | return parser.parse_args() |
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| 400 | |
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| 401 | |
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| 402 | ######################################## |
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| 403 | if __name__ == '__main__': |
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| 404 | |
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| 405 | # .. Initialization .. |
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| 406 | # ==================== |
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| 407 | # ... Command line arguments ... |
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| 408 | # ------------------------------ |
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| 409 | args = get_arguments() |
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| 410 | |
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| 411 | # ... Turn interactive mode off ... |
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| 412 | # --------------------------------- |
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| 413 | if not args.show: |
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| 414 | import matplotlib |
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| 415 | matplotlib.use('Agg') |
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| 416 | |
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| 417 | import matplotlib.pyplot as plt |
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| 418 | # from matplotlib.backends.backend_pdf import PdfPages |
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| 419 | |
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| 420 | if not args.show: |
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| 421 | plt.ioff() |
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| 422 | |
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| 423 | # ... Files and directories ... |
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| 424 | # ----------------------------- |
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| 425 | project_name, DIR, OUT = parse_config("bin/config.ini") |
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| 426 | |
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| 427 | (file_param, file_utheo, file_data) = \ |
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| 428 | get_input_files(DIR["SAVEDATA"], |
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| 429 | [OUT["PARAM"], OUT["UTHEO"], OUT["BILAN"]]) |
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| 430 | |
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| 431 | img_name = os.path.splitext( |
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| 432 | os.path.basename(__file__) |
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| 433 | )[0].replace("plot_", "") |
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| 434 | |
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| 435 | today = os.path.basename(file_param).strip(OUT["PARAM"]) |
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| 436 | |
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| 437 | if args.verbose: |
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| 438 | fmt_str = "{:10s} : {}" |
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| 439 | print(fmt_str.format("args", args)) |
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| 440 | print(fmt_str.format("today", today)) |
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| 441 | print(fmt_str.format("file_param", file_param)) |
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| 442 | print(fmt_str.format("file_utheo", file_utheo)) |
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| 443 | print(fmt_str.format("file_data", file_data)) |
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| 444 | print(fmt_str.format("img_name", img_name)) |
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| 445 | |
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| 446 | # .. Get project info .. |
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| 447 | # ====================== |
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| 448 | projet = Project(project_name) |
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| 449 | projet.fill_data(file_param) |
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| 450 | projet.get_date_init(file_utheo) |
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| 451 | |
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| 452 | # .. Fill in data .. |
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| 453 | # ================== |
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| 454 | # ... Initialization ... |
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| 455 | # ---------------------- |
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| 456 | bilan = DataDict() |
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| 457 | bilan.init_range(projet.date_init, projet.deadline) |
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| 458 | # ... Extract data from file ... |
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| 459 | # ------------------------------ |
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| 460 | bilan.fill_data(file_data) |
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| 461 | # ... Compute theoratical use from known data ... |
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| 462 | # ------------------------------------------------ |
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| 463 | bilan.theo_equation() |
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| 464 | |
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| 465 | # .. Extract data depending on C.L. arguments .. |
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| 466 | # ============================================== |
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| 467 | if args.full: |
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| 468 | selected_items = bilan.get_items_in_full_range(args.inc) |
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| 469 | elif args.range: |
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| 470 | selected_items = bilan.get_items_in_range( |
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| 471 | args.range[0], args.range[1], args.inc |
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| 472 | ) |
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| 473 | else: |
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| 474 | selected_items = bilan.get_items(args.inc) |
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| 475 | |
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| 476 | # .. Compute data to be plotted .. |
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| 477 | # ================================ |
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| 478 | nb_items = len(selected_items) |
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| 479 | |
---|
| 480 | xcoord = np.linspace(1, nb_items, num=nb_items) |
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| 481 | dates = [item.date for item in selected_items] |
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| 482 | |
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| 483 | if projet.project == "gencmip6": |
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| 484 | alloc1 = (1 * projet.alloc) / 3 |
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| 485 | alloc2 = (2 * projet.alloc) / 3 |
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| 486 | conso_per_day = 2 * alloc1 / projet.days |
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| 487 | conso_per_day_2 = 2 * alloc2 / projet.days |
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| 488 | else: |
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| 489 | conso_per_day = projet.alloc / projet.days |
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| 490 | conso_per_day_2 = None |
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| 491 | |
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| 492 | runp_mean = np.array( |
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| 493 | [item.runp_mean for item in selected_items], dtype=float |
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| 494 | ) |
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| 495 | penp_mean = np.array( |
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| 496 | [item.penp_mean for item in selected_items], dtype=float |
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| 497 | ) |
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| 498 | runp_std = np.array( |
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| 499 | [item.runp_std for item in selected_items], dtype=float |
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| 500 | ) |
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| 501 | penp_std = np.array( |
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| 502 | [item.penp_std for item in selected_items], dtype=float |
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| 503 | ) |
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| 504 | |
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| 505 | runf_mean = np.array( |
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| 506 | [item.runf_mean for item in selected_items], dtype=float |
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| 507 | ) |
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| 508 | penf_mean = np.array( |
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| 509 | [item.penf_mean for item in selected_items], dtype=float |
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| 510 | ) |
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| 511 | runf_std = np.array( |
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| 512 | [item.runf_std for item in selected_items], dtype=float |
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| 513 | ) |
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| 514 | penf_std = np.array( |
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| 515 | [item.penf_std for item in selected_items], dtype=float |
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| 516 | ) |
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| 517 | |
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| 518 | # .. Plot stuff .. |
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| 519 | # ================ |
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| 520 | # ... Initialize figure ... |
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| 521 | # ------------------------- |
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| 522 | (fig, ax_jobsp, ax_jobsf) = plot_init() |
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| 523 | |
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| 524 | # ... Plot data ... |
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| 525 | # ----------------- |
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| 526 | plot_data( |
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| 527 | ax_jobsp, ax_jobsf, xcoord, dates, |
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| 528 | runp_mean, penp_mean, runp_std, penp_std, |
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| 529 | runf_mean, penf_mean, runf_std, penf_std, |
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| 530 | ) |
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| 531 | |
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| 532 | # ... Tweak figure ... |
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| 533 | # -------------------- |
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| 534 | title = ( |
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| 535 | "{} : Suivi des jobs (moyenne journaliÚre)\n" |
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| 536 | "({:%d/%m/%Y} - {:%d/%m/%Y})" |
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| 537 | ).format( |
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| 538 | projet.project.upper(), |
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| 539 | projet.date_init, |
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| 540 | projet.deadline |
---|
| 541 | ) |
---|
| 542 | |
---|
| 543 | plot_config( |
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| 544 | fig, ax_jobsp, ax_jobsf, |
---|
| 545 | xcoord, dates, title, |
---|
| 546 | conso_per_day, conso_per_day_2 |
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| 547 | ) |
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| 548 | |
---|
| 549 | # ... Save figure ... |
---|
| 550 | # ------------------- |
---|
| 551 | img_in = os.path.join(DIR["PLOT"], "{}.pdf".format(img_name)) |
---|
| 552 | img_out = os.path.join(DIR["SAVEPLOT"], |
---|
| 553 | "{}_{}.pdf".format(img_name, today)) |
---|
| 554 | |
---|
| 555 | plot_save(img_in, img_out, title, DIR) |
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| 556 | |
---|
| 557 | # ... Publish figure on dods ... |
---|
| 558 | # ------------------------------ |
---|
| 559 | if args.dods: |
---|
| 560 | if args.verbose: |
---|
| 561 | print("Publish figure on dods") |
---|
| 562 | dods_cp(img_in, DIR) |
---|
| 563 | |
---|
| 564 | if args.show: |
---|
| 565 | plt.show() |
---|
| 566 | |
---|
| 567 | exit(0) |
---|
| 568 | |
---|