| 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 | import numpy as np |
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| 13 | |
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| 14 | # Application library imports |
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| 15 | from gencmip6 import * |
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| 16 | from gencmip6_path import * |
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| 17 | |
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| 18 | |
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| 19 | ######################################## |
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| 20 | class BilanDict(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 | data = np.genfromtxt( |
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| 42 | filein, |
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| 43 | skip_header=1, |
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| 44 | converters={0: string_to_date, |
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| 45 | 1: string_to_float, |
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| 46 | 2: string_to_percent, |
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| 47 | 3: string_to_percent}, |
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| 48 | missing_values="nan", |
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| 49 | ) |
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| 50 | |
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| 51 | for date, conso, real_use, theo_use in data: |
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| 52 | if date in self: |
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| 53 | self.add_item(date, conso, real_use, theo_use) |
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| 54 | self[date].fill() |
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| 55 | |
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| 56 | #--------------------------------------- |
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| 57 | def add_item(self, date, conso=np.nan, |
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| 58 | real_use=np.nan, theo_use=np.nan): |
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| 59 | """ |
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| 60 | """ |
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| 61 | self[date] = Conso(date, conso, real_use, theo_use) |
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| 62 | |
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| 63 | #--------------------------------------- |
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| 64 | def theo_equation(self): |
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| 65 | """ |
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| 66 | """ |
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| 67 | (dates, theo_uses) = \ |
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| 68 | zip(*((item.date, item.theo_use) |
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| 69 | for item in self.get_items_in_full_range())) |
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| 70 | |
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| 71 | (idx_min, idx_max) = \ |
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| 72 | (np.nanargmin(theo_uses), np.nanargmax(theo_uses)) |
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| 73 | |
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| 74 | x1 = dates[idx_min].timetuple().tm_yday |
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| 75 | x2 = dates[idx_max].timetuple().tm_yday |
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| 76 | |
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| 77 | y1 = theo_uses[idx_min] |
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| 78 | y2 = theo_uses[idx_max] |
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| 79 | |
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| 80 | m = np.array([ |
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| 81 | [x1, 1.], |
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| 82 | [x2, 1.] |
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| 83 | ], dtype="float") |
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| 84 | n = np.array([ |
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| 85 | y1, |
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| 86 | y2 |
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| 87 | ], dtype="float") |
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| 88 | |
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| 89 | try: |
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| 90 | (a, b) = np.linalg.solve(m, n) |
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| 91 | except np.linalg.linalg.LinAlgError: |
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| 92 | (a, b) = (None, None) |
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| 93 | |
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| 94 | if a and b: |
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| 95 | for date in dates: |
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| 96 | self[date].theo_equ = date.timetuple().tm_yday*a + b |
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| 97 | |
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| 98 | #--------------------------------------- |
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| 99 | def get_items_in_range(self, date_beg, date_end, inc=1): |
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| 100 | """ |
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| 101 | """ |
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| 102 | items = (item for item in self.itervalues() |
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| 103 | if item.date >= date_beg and |
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| 104 | item.date <= date_end) |
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| 105 | items = sorted(items, key=lambda item: item.date) |
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| 106 | |
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| 107 | return items[::inc] |
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| 108 | |
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| 109 | #--------------------------------------- |
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| 110 | def get_items_in_full_range(self, inc=1): |
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| 111 | """ |
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| 112 | """ |
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| 113 | items = (item for item in self.itervalues()) |
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| 114 | items = sorted(items, key=lambda item: item.date) |
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| 115 | |
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| 116 | return items[::inc] |
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| 117 | |
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| 118 | #--------------------------------------- |
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| 119 | def get_items(self, inc=1): |
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| 120 | """ |
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| 121 | """ |
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| 122 | items = (item for item in self.itervalues() |
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| 123 | if item.isfilled()) |
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| 124 | items = sorted(items, key=lambda item: item.date) |
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| 125 | |
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| 126 | return items[::inc] |
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| 127 | |
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| 128 | |
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| 129 | class Conso(object): |
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| 130 | #--------------------------------------- |
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| 131 | def __init__(self, date, conso=np.nan, |
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| 132 | real_use=np.nan, theo_use=np.nan): |
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| 133 | self.date = date |
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| 134 | self.conso = conso |
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| 135 | self.real_use = real_use |
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| 136 | self.theo_use = theo_use |
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| 137 | self.theo_equ = np.nan |
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| 138 | self.filled = False |
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| 139 | |
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| 140 | #--------------------------------------- |
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| 141 | def __repr__(self): |
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| 142 | return "{:.2f} ({:.2%})".format(self.conso, self.real_use) |
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| 143 | |
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| 144 | #--------------------------------------- |
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| 145 | def isfilled(self): |
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| 146 | return self.filled |
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| 147 | |
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| 148 | #--------------------------------------- |
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| 149 | def fill(self): |
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| 150 | self.filled = True |
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| 151 | |
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| 152 | |
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| 153 | ######################################## |
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| 154 | def plot_init(): |
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| 155 | paper_size = np.array([29.7, 21.0]) |
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| 156 | fig, ax_conso = plt.subplots(figsize=(paper_size/2.54)) |
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| 157 | ax_theo = ax_conso.twinx() |
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| 158 | |
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| 159 | return fig, ax_conso, ax_theo |
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| 160 | |
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| 161 | |
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| 162 | ######################################## |
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| 163 | def plot_data(ax_conso, ax_theo, xcoord, xlabels, |
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| 164 | consos, conso_per_day, theo_uses, real_uses, theo_equs): |
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| 165 | """ |
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| 166 | """ |
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| 167 | if args.full: |
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| 168 | line_style = "-" |
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| 169 | line_width = 0.1 |
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| 170 | else: |
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| 171 | line_style = "+-" |
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| 172 | line_width = 0.2 |
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| 173 | |
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| 174 | ax_conso.bar(xcoord, consos, align="center", color="linen", |
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| 175 | linewidth=line_width, label="conso (heures)") |
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| 176 | # ax_conso.plot(xcoord, conso_per_day, line_style, color="blue", |
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| 177 | # linewidth=1, markersize=8, alpha=0.5, |
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| 178 | # # solid_capstyle="round", solid_joinstyle="round", |
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| 179 | # label="conso journaliÚre idéale (heures)") |
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| 180 | ax_conso.axhline(y=conso_per_day[0], color="blue", alpha=0.5, |
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| 181 | label="conso journaliÚre idéale (heures)") |
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| 182 | |
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| 183 | ax_theo.plot(xcoord, theo_equs, "--", |
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| 184 | color="firebrick", linewidth=0.5, |
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| 185 | solid_capstyle="round", solid_joinstyle="round") |
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| 186 | ax_theo.plot(xcoord, theo_uses, line_style, color="firebrick", |
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| 187 | linewidth=1, markersize=8, |
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| 188 | # solid_capstyle="round", solid_joinstyle="round", |
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| 189 | label="conso théorique (%)") |
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| 190 | ax_theo.plot(xcoord, real_uses, line_style, color="forestgreen", |
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| 191 | linewidth=1, markersize=8, |
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| 192 | # solid_capstyle="round", solid_joinstyle="round", |
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| 193 | label="conso réelle (%)") |
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| 194 | |
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| 195 | |
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| 196 | ######################################## |
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| 197 | def plot_config(ax_conso, ax_theo, xcoord, xlabels, ymax, title): |
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| 198 | """ |
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| 199 | """ |
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| 200 | # ... Config axes ... |
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| 201 | # ------------------- |
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| 202 | # 1) Range |
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| 203 | xmin, xmax = xcoord[0]-1, xcoord[-1]+1 |
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| 204 | ax_conso.set_xlim(xmin, xmax) |
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| 205 | ax_conso.set_ylim(0., ymax) |
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| 206 | ax_theo.set_ylim(0., 100) |
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| 207 | |
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| 208 | # 2) Ticks labels |
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| 209 | inc_label = 7 if nb_items > 37 else 1 |
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| 210 | ax_conso.ticklabel_format(axis="y", style="sci", scilimits=(0, 0)) |
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| 211 | ax_conso.set_xticks(xcoord, minor=True) |
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| 212 | ax_conso.set_xticks(xcoord[::inc_label], minor=False) |
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| 213 | ax_conso.set_xticklabels( |
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| 214 | xlabels[::inc_label], rotation="45", size="x-small" |
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| 215 | ) |
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| 216 | |
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| 217 | # 3) Define axes title |
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| 218 | ax_conso.set_ylabel("heures", fontweight="bold") |
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| 219 | ax_theo.set_ylabel("%", fontweight="bold") |
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| 220 | |
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| 221 | # ... Main title and legend ... |
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| 222 | # ----------------------------- |
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| 223 | ax_conso.set_title(title, fontweight="bold", size="large") |
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| 224 | ax_theo.legend(loc="upper right", fontsize="x-small", frameon=False) |
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| 225 | ax_conso.legend(loc="upper left", fontsize="x-small", frameon=False) |
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| 226 | |
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| 227 | |
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| 228 | ######################################## |
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| 229 | def plot_save(img_name): |
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| 230 | """ |
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| 231 | """ |
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| 232 | dpi = 200. |
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| 233 | |
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| 234 | with PdfPages(img_name) as pdf: |
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| 235 | pdf.savefig(dpi=dpi) |
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| 236 | |
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| 237 | # pdf file's metadata |
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| 238 | d = pdf.infodict() |
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| 239 | d["Title"] = "Conso GENCMIP6" |
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| 240 | d["Author"] = "plot_bilan.py" |
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| 241 | # d["Subject"] = "Time spent over specific commands during create_ts \ |
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| 242 | # jobs at IDRIS and four configurations at TGCC" |
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| 243 | # d["Keywords"] = "bench create_ts TGCC IDRIS ncrcat" |
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| 244 | # d["CreationDate"] = dt.datetime(2009, 11, 13) |
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| 245 | # d["ModDate"] = dt.datetime.today() |
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| 246 | |
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| 247 | |
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| 248 | ######################################## |
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| 249 | def get_arguments(): |
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| 250 | parser = ArgumentParser() |
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| 251 | parser.add_argument("-v", "--verbose", action="store_true", |
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| 252 | help="verbose mode") |
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| 253 | parser.add_argument("-f", "--full", action="store_true", |
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| 254 | help="plot the whole period") |
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| 255 | parser.add_argument("-i", "--increment", action="store", |
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| 256 | type=int, default=1, dest="inc", |
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| 257 | help="sampling increment") |
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| 258 | parser.add_argument("-r", "--range", action="store", nargs=2, |
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| 259 | type=string_to_date, |
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| 260 | help="date range: ssaa-mm-jj ssaa-mm-jj") |
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| 261 | parser.add_argument("-m", "--max", action="store_true", |
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| 262 | help="plot with y_max = allocation") |
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| 263 | parser.add_argument("-s", "--show", action="store_true", |
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| 264 | help="interactive mode") |
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| 265 | parser.add_argument("-d", "--dods", action="store_true", |
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| 266 | help="copy output on dods") |
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| 267 | |
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| 268 | return parser.parse_args() |
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| 269 | |
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| 270 | |
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| 271 | ######################################## |
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| 272 | if __name__ == '__main__': |
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| 273 | |
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| 274 | # .. Initialization .. |
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| 275 | # ==================== |
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| 276 | # ... Command line arguments ... |
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| 277 | # ------------------------------ |
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| 278 | args = get_arguments() |
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| 279 | if args.verbose: |
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| 280 | print(args) |
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| 281 | |
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| 282 | # ... Turn interactive mode off ... |
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| 283 | # --------------------------------- |
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| 284 | if not args.show: |
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| 285 | import matplotlib |
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| 286 | matplotlib.use('Agg') |
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| 287 | |
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| 288 | import matplotlib.pyplot as plt |
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| 289 | from matplotlib.backends.backend_pdf import PdfPages |
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| 290 | |
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| 291 | if not args.show: |
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| 292 | plt.ioff() |
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| 293 | |
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| 294 | # ... Files and directories ... |
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| 295 | # ----------------------------- |
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| 296 | file_param = get_last_file(DIR["SAVEDATA"], OUT["PARAM"]) |
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| 297 | file_utheo = get_last_file(DIR["SAVEDATA"], OUT["UTHEO"]) |
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| 298 | file_bilan = get_last_file(DIR["SAVEDATA"], OUT["BILAN"]) |
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| 299 | img_name = "bilan" |
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| 300 | |
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| 301 | today = os.path.basename(file_param).strip(OUT["PARAM"]) |
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| 302 | |
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| 303 | if args.verbose: |
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| 304 | print(file_param) |
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| 305 | print(file_utheo) |
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| 306 | print(file_bilan) |
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| 307 | print(img_name) |
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| 308 | print(today) |
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| 309 | print(DIR) |
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| 310 | print(OUT) |
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| 311 | |
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| 312 | # .. Get project info .. |
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| 313 | # ====================== |
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| 314 | gencmip6 = Project() |
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| 315 | gencmip6.fill_data(file_param) |
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| 316 | gencmip6.get_date_init(file_utheo) |
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| 317 | |
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| 318 | # .. Fill in conso data .. |
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| 319 | # ======================== |
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| 320 | # ... Initialization ... |
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| 321 | # ---------------------- |
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| 322 | bilan = BilanDict() |
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| 323 | bilan.init_range(gencmip6.date_init, gencmip6.deadline) |
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| 324 | # ... Extract data from file ... |
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| 325 | # ------------------------------ |
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| 326 | bilan.fill_data(file_bilan) |
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| 327 | # ... Compute theoratical use from known data ... |
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| 328 | # ------------------------------------------------ |
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| 329 | bilan.theo_equation() |
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| 330 | |
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| 331 | # .. Extract data depending on C.L. arguments .. |
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| 332 | # ============================================== |
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| 333 | if args.full: |
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| 334 | selected_items = bilan.get_items_in_full_range(args.inc) |
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| 335 | elif args.range: |
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| 336 | selected_items = bilan.get_items_in_range( |
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| 337 | args.range[0], args.range[1], args.inc |
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| 338 | ) |
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| 339 | else: |
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| 340 | selected_items = bilan.get_items(args.inc) |
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| 341 | |
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| 342 | # .. Compute data to be plotted .. |
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| 343 | # ================================ |
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| 344 | nb_items = len(selected_items) |
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| 345 | |
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| 346 | xcoord = np.linspace(1, nb_items, num=nb_items) |
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| 347 | xlabels = ["{:%d-%m}".format(item.date) |
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| 348 | for item in selected_items] |
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| 349 | cumul = np.array([item.conso for item in selected_items], |
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| 350 | dtype=float) |
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| 351 | consos = [] |
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| 352 | consos.append(cumul[0]) |
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| 353 | consos[1:nb_items] = cumul[1:nb_items] - cumul[0:nb_items-1] |
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| 354 | consos = np.array(consos, dtype=float) |
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| 355 | |
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| 356 | conso_per_day = np.array([gencmip6.alloc / nb_items |
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| 357 | for item in selected_items], dtype=float) |
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| 358 | |
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| 359 | theo_uses = np.array([100.*item.theo_use for item in selected_items], |
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| 360 | dtype=float) |
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| 361 | real_uses = np.array([100.*item.real_use for item in selected_items], |
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| 362 | dtype=float) |
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| 363 | theo_equs = np.array([100.*item.theo_equ for item in selected_items], |
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| 364 | dtype=float) |
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| 365 | |
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| 366 | # .. Plot stuff .. |
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| 367 | # ================ |
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| 368 | # ... Initialize figure ... |
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| 369 | # ------------------------- |
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| 370 | (fig, ax_conso, ax_theo) = plot_init() |
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| 371 | |
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| 372 | # ... Plot data ... |
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| 373 | # ----------------- |
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| 374 | plot_data(ax_conso, ax_theo, xcoord, xlabels, |
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| 375 | consos, conso_per_day, theo_uses, real_uses, theo_equs) |
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| 376 | |
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| 377 | # ... Tweak figure ... |
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| 378 | # -------------------- |
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| 379 | if args.max: |
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| 380 | ymax = gencmip6.alloc |
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| 381 | else: |
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| 382 | ymax = np.nanmax(consos) + np.nanmax(consos)*.1 |
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| 383 | |
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| 384 | title = "Consommation {}\n({:%d/%m/%Y} - {:%d/%m/%Y})".format( |
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| 385 | gencmip6.project.upper(), |
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| 386 | gencmip6.date_init, |
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| 387 | gencmip6.deadline |
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| 388 | ) |
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| 389 | |
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| 390 | plot_config(ax_conso, ax_theo, xcoord, xlabels, ymax, title) |
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| 391 | |
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| 392 | # ... Save figure ... |
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| 393 | # ------------------- |
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| 394 | # plot_save(os.path.join(DIR["PLOT"], img_name)) |
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| 395 | img_in = os.path.join(DIR["PLOT"], "{}.pdf".format(img_name)) |
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| 396 | plot_save(img_in) |
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| 397 | if os.path.isdir(DIR["SAVEPLOT"]): |
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| 398 | img_out = os.path.join(DIR["SAVEPLOT"], |
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| 399 | "{}_{}.pdf".format(img_name, today)) |
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| 400 | shutil.copy(img_in, img_out) |
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| 401 | |
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| 402 | # ... Publish figure on dods ... |
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| 403 | # ------------------------------ |
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| 404 | if args.dods: |
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| 405 | dods_cp(img_in) |
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| 406 | |
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| 407 | if args.show: |
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| 408 | plt.show() |
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| 409 | |
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| 410 | exit() |
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