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149 lines (130 loc) · 6.02 KB
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#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Thu May 30 15:17:22 2024
@author: chingchen
"""
import pandas as pd
import numpy as np
import numpy.ma as ma
from matplotlib import cm
import matplotlib as mpl
from scipy.misc import derivative
import matplotlib.pyplot as plt
from scipy.signal import find_peaks
def hat_graph(ax, xlabels, values, group_labels):
"""
Create a hat graph.
Parameters
----------
ax : matplotlib.axes.Axes
The Axes to plot into.
xlabels : list of str
The category names to be displayed on the x-axis.
values : (M, N) array-like
The data values.
Rows are the groups (len(group_labels) == M).
Columns are the categories (len(xlabels) == N).
group_labels : list of str
The group labels displayed in the legend.
"""
def label_bars(heights, rects):
"""Attach a text label on top of each bar."""
for height, rect in zip(heights, rects):
ax.annotate(f'{height}',
xy=(rect.get_x() + rect.get_width() / 2, height),
xytext=(0, 2), # 4 points vertical offset.
textcoords='offset points',
ha='center', va='bottom',fontsize=14)
values = np.asarray(values)
x = np.arange(values.shape[1])
ax.set_xticks(x, labels=xlabels)
spacing = 0.3 # spacing between hat groups
width = (1 - spacing) / values.shape[0]
heights0 = values[0]
for i, (heights, group_label) in enumerate(zip(values, group_labels)):
style = {'fill': False} if i == 0 else {'edgecolor': 'black'}
rects = ax.bar(x, heights - heights0,
width, bottom=heights0, label=group_label, **style)
label_bars(heights, rects)
labelsize = 20
bwith = 3
### PATH ###
path = '/Users/chingchen/Desktop/data/'
workpath = '/Users/chingchen/Desktop/StagYY_Works/thermal_evolution_v2/'
modelpath = '/Users/chingchen/Desktop/model/'
figpath = '/Users/chingchen/Desktop/figure/'
colors=['#282130','#3CB371','#4682B4','#CD5C5C','#97795D','#414F67','#4198B9','#3CB371']
header_list = ['time_Gyr','Prad','Ptidal','Fcore','Pint','Hint','conv',
'melt','P','zbot','%vol','Tbot','Tm','Fbot','Ftop','dlid','T_core']
#
fig,(aa1) = plt.subplots(1,1,figsize=(9,7))
ax=aa1
# ---------------------------------------- figure --------------------------------
model_list = ['Europa-tidal5_period0.14Gyr_emx10%_eta1.0d14_P1.0TW_1.5wt%_D5.0km-NH3_core0.10_Hvar_2',
'Europa-tidal5_period0.14Gyr_emx10%_eta1.0d14_P1.0TW_1.5wt%_D5.0km-NH3_core0.05_Hvar_2', # power
'Europa-tidal5_period0.14Gyr_emx10%_eta1.0d14_P1.0TW_1.5wt%_D5.0km-NH3_Hvar_2',
]
model_list = ['Europa-tidal1_eta5.6d13_P0.6TW_1.5wt%-NH3_core0.00_Hvar_2', # power
'Europa-tidal1_eta5.6d13_P0.6TW_1.5wt%-NH3_core0.05_Hvar_2',
'Europa-tidal1_eta5.6d13_P0.6TW_1.5wt%-NH3_core0.10_Hvar_2',
'Europa-tidal1_eta5.6d13_P0.6TW_1.5wt%-NH3_core0.15_Hvar_2'
]
model_list = ['Europa-tidal1_eta1.0d14_P0.6TW_1.5wt%-NH3_core0.00_Hvar_2', # power
'Europa-tidal1_eta1.0d14_P0.6TW_1.5wt%-NH3_core0.05_Hvar_2',
'Europa-tidal1_eta1.0d14_P0.6TW_1.5wt%-NH3_core0.10_Hvar_2',
'Europa-tidal1_eta1.0d14_P0.6TW_1.5wt%-NH3_core0.15_Hvar_2'
]
model_list2 = ['Europa-tidal1_eta5.6d13_P1.0TW_1.5wt%-NH3_core0.00_Hvar_2', # power
'Europa-tidal1_eta5.6d13_P1.0TW_1.5wt%-NH3_core0.05_Hvar_2',
'Europa-tidal1_eta5.6d13_P1.0TW_1.5wt%-NH3_core0.10_Hvar_2',
# 'Europa-tidal1_eta5.6d13_P0.8TW_1.5wt%-NH3_core0.15_Hvar_2'
]
model_list2 = [
'Europa-tidal1_eta1.0d14_P1.0TW_1.5wt%-NH3_core0.00_Hvar_2', # power
'Europa-tidal1_eta1.0d14_P1.0TW_1.5wt%-NH3_core0.05_Hvar_2',
'Europa-tidal1_eta1.0d14_P1.0TW_1.5wt%-NH3_core0.10_Hvar_2',
# 'Europa-tidal1_eta5.6d13_P0.8TW_1.5wt%-NH3_core0.15_Hvar_2'
]
label_list=['100%','95%','90%','85%']
label_list2=['100%','95%','90%']
for i, model in enumerate(model_list):
i = i
data = pd.read_csv(workpath+model+'_thermal-evolution.dat',
header=None,names=header_list,delim_whitespace=True)[2:].reset_index(drop=True)
data = data.replace('D','e',regex=True).astype(float) # data convert to float
x = data.time_Gyr
mask_cond = data.conv
mask_conv = ~ma.array(data.zbot, mask = data.conv).mask
zbot_cond = ma.array(data.zbot, mask = mask_cond)
zbot_conv = ma.array(data.zbot, mask = mask_conv)
ax.plot(x,zbot_conv,color=colors[i],label=label_list[i],lw=3)
ax.plot(x,zbot_cond,color=colors[i],linestyle='dashed')
for i, model2 in enumerate(model_list2):
i = i
data = pd.read_csv(workpath+model2+'_thermal-evolution.dat',
header=None,names=header_list,delim_whitespace=True)[2:].reset_index(drop=True)
data = data.replace('D','e',regex=True).astype(float) # data convert to float
x = data.time_Gyr
mask_cond = data.conv
mask_conv = ~ma.array(data.zbot, mask = data.conv).mask
zbot_cond = ma.array(data.zbot, mask = mask_cond)
zbot_conv = ma.array(data.zbot, mask = mask_conv)
ax.plot(x,zbot_conv,color=colors[i],lw=2,linestyle='dashed')
if i==0:
ax.plot(x,zbot_conv,color=colors[i],lw=3,linestyle='dashed')
# ax.plot(x,zbot_cond,color=colors[i],linestyle='dashed')
# ------------------------------ figure setting ------------------------------
ax.set_ylim(161,0)
ax.set_xlabel('Time (Gyr)',fontsize=labelsize)
ax.legend(fontsize=labelsize)
for aa in [ax]:
aa.set_ylabel('Ice layer thickness (km)',fontsize = labelsize)
aa.minorticks_on()
aa.tick_params(which='minor', length=5, width=2, direction='in')
aa.tick_params(labelsize=labelsize,width=3,length=10,right=True, top=True,direction='in',pad=15)
aa.set_xlim(0,4.55)
aa.grid()
for axis in ['top','bottom','left','right']:
aa.spines[axis].set_linewidth(bwith)
# fig.savefig('/Users/chingchen/Desktop/StagYY_Works/paper_europa_ice_shell/figure7_v2.pdf')