def declare_variables(self):
self.log_file_name = datetime.now().strftime(
'%Y-%m-%d %H:%M:%S') + 'logs.txt'
self.indicators = [
"label", "name", "style", "type", "interval", "position", "color",
"width"
]
self.dark_theme = RcParams({
'axes.edgecolor':
'white',
'axes.facecolor':
'#1F2A34',
'axes.labelcolor':
'white',
'axes.prop_cycle':
cycler('color', [
'#8dd3c7', '#feffb3', '#bfbbd9', '#fa8174', '#81b1d2',
'#fdb462', '#b3de69', '#bc82bd', '#ccebc4', '#ffed6f'
]),
'figure.edgecolor':
'#1F2A34',
'figure.facecolor':
'#1F2A34',
'grid.color':
'#504958',
'lines.color':
'white',
'patch.edgecolor':
'white',
'savefig.edgecolor':
'#1F2A34',
'savefig.facecolor':
'#1F2A34',
'text.color':
'white',
'xtick.color':
'white',
'ytick.color':
'white'
})
self.queryChartConfig = """query chartConfig {
chartConfig(strategy:"%s") {
panels {
name,
height,
indicators {
label,
name,
style,
type,
interval,
position,
color,
width
}
}
}
}"""
self.query_template_chartconfig = """query chartConfig {{
{market}
chartConfig({query}){{
panels {{
name,
height,
indicators {{{indicators}}} }}}}}}"""
self.queryChartData = """query chartData {
marketIndicators(
strategy:"%s",
market:"%s",
limit:%s,
optimizeIndicatorValuesForCharting:true,
index:1
) {
id,
timestamp,
open,
high,
low,
close,
volume,
indicators
}
}"""
self.queryChartData_with_indicators = """query chartData {
rc('font', **{'family': 'sans-serif', 'sans-serif': ['arial'], 'size': fontsz})
rc(('xtick.major', 'xtick.minor', 'ytick.major', 'ytick.minor'), pad=dist_tick_lab)
def figure(title, figs=None, figsize=(12, 10), **kwargs):
fig = plt.figure(figsize=figsize, **kwargs)
fig.canvas.set_window_title(title)
if figs != None:
figs.append(fig)
fig.patch.set_facecolor('w')
plt.suptitle(title, fontsize=16)
fig.subplots_adjust(left=0.07, right=0.80, wspace=0.5)
return fig
"""
RcParams
RcParams({u'agg.path.chunksize': 0,
u'animation.avconv_args': [],
u'animation.avconv_path': u'avconv',
u'animation.bitrate': -1,
u'animation.codec': u'mpeg4',
u'animation.convert_args': [],
u'animation.convert_path': u'convert',
u'animation.ffmpeg_args': [],
u'animation.ffmpeg_path': u'ffmpeg',
u'animation.frame_format': u'png',
u'animation.html': u'none',
u'animation.mencoder_args': [],
# -- custom rc ----------------------------------------------------------------
# set default params
GWPY_RCPARAMS = RcParams(**{
# axes boundary colours
'axes.edgecolor': 'gray',
# grid
'axes.grid': True,
'axes.axisbelow': False,
'grid.linewidth': .5,
# ticks
'axes.formatter.limits': (-3, 4),
'axes.formatter.use_mathtext': True,
# fonts
'axes.titlesize': 'large',
'axes.labelsize': 'large',
'font.family': ['sans-serif'],
'font.sans-serif': [
'FreeSans',
'Helvetica Neue',
'Helvetica',
'Arial',
] + rcParams['font.sans-serif'],
'font.size': 12,
# legend (revert to mpl 1.5 formatting in parts)
'legend.numpoints': 2,
'legend.handlelength': 1,
'legend.fancybox': False,
})
# set parameters only supported in matplotlib >= 1.5
# https://matplotlib.org/1.5.1/users/whats_new.html#configuration-rcparams
dark_theme = RcParams({
'axes.edgecolor':
'white',
'axes.facecolor':
'#1F2A34',
'axes.labelcolor':
'white',
'axes.prop_cycle':
cycler('color', [
'#8dd3c7', '#feffb3', '#bfbbd9', '#fa8174', '#81b1d2', '#fdb462',
'#b3de69', '#bc82bd', '#ccebc4', '#ffed6f'
]),
'figure.edgecolor':
'#1F2A34',
'figure.facecolor':
'#1F2A34',
'grid.color':
'#504958',
'lines.color':
'white',
'patch.edgecolor':
'white',
'savefig.edgecolor':
'#1F2A34',
'savefig.facecolor':
'#1F2A34',
'text.color':
'white',
'xtick.color':
'white',
'ytick.color':
'white'
})
import numpy as np
import os
from os import listdir
from os.path import isfile, join
import matplotlib.pyplot as plt
import matplotlib.tri as mtri
from matplotlib import RcParams
## =============================================================================
## Plot font
## =============================================================================
#
fig, ax = plt.subplots(figsize=(6 * 0.9, 5 * 0.9))
latex_style_times = RcParams({
'font.family': 'serif',
'font.serif': ['cmr10'],
'text.usetex': True,
'font.size': 15
})
# =============================================================================
# Reads the data
# =============================================================================
file_name = "results/solution.txt"
dir_path = os.path.dirname(os.path.realpath(__file__))
path = os.path.join(dir_path, file_name)
results = np.loadtxt(path)
file_name = "results/nodes_coordinates.txt"
dir_path = os.path.dirname(os.path.realpath(__file__))
path = os.path.join(dir_path, file_name)
coordinates = np.loadtxt(path)
import torch
import torch.nn as nn
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
import numpy as np
import os
import torch.nn.functional as F
from matplotlib import RcParams
latex_style_times = RcParams({
'font.family': 'serif',
'font.serif': ['Times'],
'text.usetex': True,
})
plt.style.use(latex_style_times)
plt.rcParams['font.size'] = 12
def plot_feature(net,
args,
plotloader,
device,
dirname,
epoch=0,
plot_class_num=10,
plot_quality=150,
testmode=False):
plot_features = []
plot_labels = []
GWPY_RCPARAMS = RcParams(
**{
# axes boundary colours
'axes.edgecolor':
'gray',
# grid
'axes.grid':
True,
'axes.axisbelow':
False,
'grid.linewidth':
.5,
# ticks
'axes.formatter.limits': (-3, 4),
'axes.formatter.use_mathtext':
True,
# fonts
'axes.titlesize':
'large',
'axes.labelsize':
'large',
'font.family': ['sans-serif'],
'font.sans-serif': [
'FreeSans',
'Helvetica Neue',
'Helvetica',
'Arial',
] + rcParams['font.sans-serif'],
'font.size':
12,
# legend (revert to mpl 1.5 formatting in parts)
'legend.numpoints':
2,
'legend.handlelength':
1,
'legend.fancybox':
False,
})
import pandas as pd
from matplotlib import RcParams
import matplotlib.pyplot as plt
# Plot style
latex_style_cm = RcParams({
"font.family": "serif",
"font.serif": ["Computer Modern Roman"],
"font.size": 10,
"text.usetex": True,
# 'text.latex.unicode': True,
"text.latex.preamble": ["\\usepackage{siunitx}"],
"axes.linewidth": 0.4,
"xtick.major.width": 0.2,
"xtick.minor.width": 0.2,
"ytick.major.width": 0.2,
"ytick.minor.width": 0.2,
"grid.linestyle": "-",
"grid.linewidth": 0.3,
"grid.color": [0.5] * 3,
})
plt.style.use(latex_style_cm)
# Loading data
log_data = pd.read_csv("log", sep=" ").to_numpy()
t = log_data[:, 0]
depth_min = log_data[:, 1]
depth_max = log_data[:, 2]
# Plot
plt.figure()
