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()