#####################################

#-----------import modules----------#

#####################################

import numpy as np

# controal plot behaviour

import matplotlib.pyplot as plt

import matplotlib.mlab as mlab

# control the tick

import matplotlib.ticker as ticker

################################

#----------rc setting----------#

################################

# global setting for journal paper

params = {

'axes.labelsize': 11,

'font.family': 'Arial',

'legend.fontsize': 11,

'xtick.labelsize': 11,

'ytick.labelsize': 11,

'figure.figsize': [3.54, 3.5]

#'mathtext.fontset': 'cm' # different font for epsilon

# 'axes.linewidth': 1,

# 'patch.linewidth': 1

}

# update parameters

plt.rcParams.update(params)

##########################

#----------plot----------#

##########################

# 2 represents 2 figures, sharex means share the x axis

fig, axs = plt.subplots(3,sharex=True, sharey=True,figsize=(10,8))

# plot line

ax.plot(t2,h2,color='#d95f02',linestyle=':', linewidth=7.0, label = 'xyz')

# plot scatter

ax.scatter(x,y,s = 10, c = '#d95f02', marker = 'o',label = 'CFD-DEM')

# turn on or off the grid

ax.grid (False)

# draw horizontal line pass y=0

ax.axhline(y=0.81, color='k',lw = 1,ls = '--' )

# plot with error bar

ax.errorbar(simulation[:,0],meangp,stdgp,linestyle='None',color = '#1b9e77', capsize=2,fmt = 'x',label = 'CFD-DEM')

###########################

#----------Title----------#

###########################

# set title font

Arialfont = {'fontname':'Arial'}

ax.set_title('Cd vs Time',**Arialfont)

###########################################

#----------axis and tick control----------#

###########################################

axs[1].tick_params(bottom='off')

# get the range of x axis, yaxis is ax.get_ylim(), set x axis tick range

start, end = ax.get_xlim()

ax.xaxis.set_ticks(np.arange(start, end, step))

plt.xticks(np.arange(0.2, 1.4, 0.4))

# set x axis major format

ax.xaxis.set_major_formatter(ticker.StrMethodFormatter("{x:3.1f}"))

# set both tick label to scientific number

plt.ticklabel_format(axis='both', style='sci', scilimits=(-2,2))

# set x tick direction

ax.tick_params(direction='in')

# set tick interval

ax.xaxis.set_major_locator(ticker.MultipleLocator(1.00))

# set max major tick number

ax.xaxis.set_major_locator(ticker.MaxNLocator(5))

# set fixed no. of major ticks

majors = [3, 4, 5, 6, 7]

ax.xaxis.set_major_locator(ticker.FixedLocator(majors))

# set x axis lable

ax.set_xlabel('xyz')

# set x axis range

plt.xlim(0,1)

ax.set_xlim([0., 1])

# x,y axis start from same position

plt.margins(0)

# move x-axis where y=0

pos1 = ax.spines['bottom'].set_position('zero') or

plt.margins(0)

# To shift the tick labels relative to the ticks use pad

ax.tick_params(which='both', direction='out', pad=5)

# set log scale

ax.set_yscale('log')

# turn off minor ticks

plt.minorticks_off()

plt.xscale('log', subsx=[2, 3, 4, 5, 6, 7, 8, 9])

ax.minorticks_off()

############################

#----------marker----------#

############################

# ================ ===============================

# character description

# ================ ===============================

# - solid line style

# -- dashed line style

# -. dash-dot line style

# : dotted line style

# . point marker

# , pixel marker

# o circle marker

# v triangle_down marker

# ^ triangle_up marker

# < triangle_left marker

# > triangle_right marker

# 1 tri_down marker

# 2 tri_up marker

# 3 tri_left marker

# 4 tri_right marker

# s square marker

# p pentagon marker

# * star marker

# h hexagon1 marker

# H hexagon2 marker

# + plus marker

# x x marker

# D diamond marker

# d thin_diamond marker

# | vline marker

# _ hline marker

# ================ ===============================

# plot empty marker

plt.scatter(data[:,0],data[:,1], s=14, facecolors='none', edgecolors='b', marker = 'o',label = 'simulation')

ax.plot(zenit_small[:,0], zenit_small[:,1], 'o', markersize=8, markeredgewidth=1 ,markeredgecolor='k', markerfacecolor='None',label = 'Zenit et al. 1997')

##########################

#----------text----------#

##########################

# add text to a point

ax[0].text(0.001,2,'xyz') # data coordinate

axs[0].text(0.8,0.1,r'$U_L=0.0535$',horizontalalignment='center',verticalalignment='center',transform=axs[0].transAxes) # axis coordinate

fig.text(0.01, 0.98, "A", weight="bold", horizontalalignment='left', verticalalignment='center')

ax.annotate("Re = %s, Cd = %s"%(str(round(Re)),str(round(abs(meanCd),3))),(0.41,0.36),xycoords='figure fraction')

# add text based on coordinates relative to the axis https://matplotlib.org/users/text_props.html

ax.text(0.2, 0.8,r'$\epsilon_{scrit}$'+'={:.2f}'.format(ec),

horizontalalignment='center',

verticalalignment='center',

transform = ax.transAxes)

############################

#----------legend----------#

############################

# show legend, this one should not coexit with next one

plt.legend(loc = 1)

# control the legend location

ax.legend(loc = 1)

# Location String Location Code

# ‘best’ 0

# ‘upper right’ 1

# ‘upper left’ 2

# ‘lower left’ 3

# ‘lower right’ 4

# ‘right’ 5

# ‘center left’ 6

# ‘center right’ 7

# ‘lower center’ 8

# ‘upper center’ 9

# ‘center’ 10

# ensure labels are not cut

plt.tight_layout()

# get the object of legend

leg = plt.legend()

# set legend frame color

leg.get_frame().set_edgecolor('k')

# set legend frame linewidth

leg.get_frame().set_linewidth(1)

# remove frame

plt.legend(frameon=False)

ax.legend(loc = 3,bbox_to_anchor=(0,0),frameon=False,borderaxespad=None,mode='expand')

##################

#---draw lines---#

##################

ax.axvline(x=maxgp,ymin=0,ymax=0.8,ls = 'dotted', c='b')

#################################################

#----------save figure with resolution----------#

#################################################

fig.savefig('xyz.tiff',bbox_inches='tight',dpi = 600)

#################################

#---------special cases---------#

#################################

# plot histgram figure

fig,ax = plt.subplots()

mu = np.average(pp)

sigma = np.std(pp)

num_bins = 2000

n,bins,patches = ax.hist(pp,num_bins,normed=True)

y = mlab.normpdf(bins, mu, sigma)

ax.plot(bins, y, '--')