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getDataAndDiagram.py
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import math
import matplotlib
from matplotlib.colors import LinearSegmentedColormap, ListedColormap
import matplotlib.pyplot as plt
import numpy as np
import opertateOnMysql as osql
from points_analysis_2D import static_points_analysis_2d
import freud
R"""
#NEW plot standard:
#https://matplotlib.org/3.6.2/tutorials/introductory/quick_start.html#sphx-glr-tutorials-introductory-quick-start-py
import matplotlib.pyplot as plt
import numpy as np
points = np.random.random((100,2))#random.random () ()
fig,ax = plt.subplots()
ax.plot(points[:,0],points[:,1])
ax.scatter(points[:,0],points[:,1],c=points[:,1])
ax.set_xlabel('x label') # Add an x-label to the axes.
ax.set_ylabel('y label') # Add a y-label to the axes.
ax.set_title("Simple Plot") # Add a title to the axes
plt.show()
"""
def workflow_mysql_to_data_pin_hex_to_honeycomb():
R"""
simu_index | HarmonicK | LinearCompressionRatio | Psi3Global | Psi3Ratio
"""
U_interaction = 300*np.exp(-0.25)
points = osql.getDataFromMysql(table_name="pin_hex_to_honeycomb",
search_condition="where LinearCompressionRatio < 0.855")
points = np.asarray(points)
plt.figure()
plt.scatter(points[:, 2], 0.5*points[:, 1], c=points[:, 3])
plt.colorbar()
plt.title('LCR VS K,Psi3 as value, kBT=1, Uparticle='+str(int(U_interaction))+',pin')
plt.xlabel('Linear Compression Ratio (1)')
plt.ylabel('U trap (kBT)[honeycomb]')
prefix = '/home/tplab/Downloads/'
png_filename = prefix+'LCR_vs_K_Psi3_as_value_pin_hex_to_honeycomb'
plt.savefig(png_filename)
plt.close()
plt.figure()
plt.scatter(points[:, 2], 0.5*points[:, 1], c=points[:, 4])
plt.colorbar()
plt.title('LCR VS K,Psi3Ratio as value, kBT=1, Uparticle='+str(int(U_interaction))+',pin')
plt.xlabel('Linear Compression Ratio (1)')
plt.ylabel('U trap (kBT)[honeycomb]')
prefix = '/home/tplab/Downloads/'
png_filename = prefix+'LCR_vs_K_Psi3Ratio_as_value_pin_hex_to_honeycomb'
plt.savefig(png_filename)
plt.close()
def workflow_mysql_to_data_pin_hex_to_honeycomb_random():
R"""
Introduction:
table_name='pin_hex_to_honeycomb_repeat'
#the simu_index of 'pin_hex_to_honeycomb' is complex
simu_index | HarmonicK | LinearCompressionRatio |
Psi3Global | Psi6Global | RandomSeed
FIGURE scatter LinearCompressionRatio vs U_trap, Psi3 as value
Example:
import getDataAndScatter as scatt
scatt.workflow_mysql_to_data_pin_hex_to_honeycomb_random()
"""
# control table
save_data_txt = True
k1 = 0.0
k_step = 10.0
k_end = 90.0
lcr1 = 0.76
lcr_step = 0.01
lcr_end = 0.80
# getDataToMysql
import opertateOnMysql as osql
U_interaction = 300*np.exp(-0.25)
# list of HarmonicK
num = (k_end-k1)/k_step+1
num = round(num) # get the num of repeat times
# list of LCR
lcr_num = (lcr_end-lcr1)/lcr_step+1
lcr_num = round(lcr_num)
record = np.zeros((lcr_num*num, 6))
count = 0
# scatter cycle
for i in np.linspace(1, num, num):
for j in np.linspace(1, lcr_num, lcr_num):
kset = k1+(i-1)*k_step
cond1 = ' where HarmonicK >'+str(kset-0.5*k_step) + \
' and HarmonicK <'+str(kset+0.5*k_step)
lcrset = lcr1+(j-1)*lcr_step
cond2 = ' and LinearCompressionRatio > '+str(
lcrset-lcr_step*0.5)+' and LinearCompressionRatio <'+str(lcrset+lcr_step*0.5)
search_condition = cond1+cond2
data = osql.getDataFromMysql(
table_name='pin_hex_to_honeycomb_repeat', search_condition=search_condition)
data = np.array(data)
m3 = np.mean(data[:, 3]) # psi3
std3 = np.std(data[:, 3])
m6 = np.mean(data[:, 4]) # psi6
std6 = np.std(data[:, 4])
record[count, :] = [lcrset, kset, m3, std3, m6, std6]
count += 1
# print(data)
# print(m)
# print(std)
# rename "record"
data = record
# save data
if save_data_txt:
prefix = '/home/tplab/Downloads/'
save_file_name = prefix+"honeycomb_diagram_2"
np.savetxt(save_file_name, data)
# plot
plt.figure()
# plot LCR VS K, Psi3 as value
plt.scatter(data[:, 0], data[:, 1]*0.5, c=data[:, 2]) # LCR VS K, Psi3 as value
# plt.show()
plt.title('LCR VS K, Psi3 as value, Uparticle='+str(int(U_interaction)))
plt.xlabel('Linear Compression Ratio (1)')
plt.ylabel('U trap (kBT)[honeycomb]')
plt.colorbar()
prefix = '/home/tplab/Downloads/'
png_filename = prefix+'LCR_VS_K_Psi3_as_value_pin_hex_to_honeycomb_random'
plt.savefig(png_filename)
plt.close()
plt.figure()
# plot LCR VS K, Psi6 as value
plt.scatter(data[:, 0], data[:, 1]*0.5, c=data[:, 4]) # LCR VS K, Psi6 as value
# plt.show()
plt.title('LCR VS K, Psi6 as value, Uparticle='+str(int(U_interaction)))
plt.xlabel('Linear Compression Ratio (1)')
plt.ylabel('U trap (kBT)[honeycomb]')
plt.colorbar()
prefix = '/home/tplab/Downloads/'
png_filename = prefix+'LCR_VS_K_Psi6_as_value_pin_hex_to_honeycomb_random'
plt.savefig(png_filename)
plt.close()
plt.figure()
# plot LCR VS K, Psi3std as value
plt.scatter(data[:, 0], data[:, 1]*0.5, c=data[:, 3]) # LCR VS K, Psi3std as value
# plt.show()
plt.title('LCR VS K, Psi3std as value, Uparticle='+str(int(U_interaction)))
plt.xlabel('Linear Compression Ratio (1)')
plt.ylabel('U trap (kBT)[honeycomb]')
plt.colorbar()
prefix = '/home/tplab/Downloads/'
png_filename = prefix+'LCR_VS_K_Psi3std_as_value_pin_hex_to_honeycomb_random'
plt.savefig(png_filename)
plt.close()
plt.figure()
# plot LCR VS K, Psi6std as value
plt.scatter(data[:, 0], data[:, 1]*0.5, c=data[:, 5]) # LCR VS K, Psi6std as value
# plt.show()
plt.title('LCR VS K, Psi6std as value, Uparticle='+str(int(U_interaction)))
plt.xlabel('Linear Compression Ratio (1)')
plt.ylabel('U trap (kBT)[honeycomb]')
plt.colorbar()
prefix = '/home/tplab/Downloads/'
png_filename = prefix+'LCR_VS_K_Psi6std_as_value_pin_hex_to_honeycomb_random'
plt.savefig(png_filename)
plt.close()
def workflow_mysql_to_data_pin_hex_to_honeycomb_klt_2m(account='tplab'):
R"""
Note: the format of table_name='pin_hex_to_honeycomb_klt_2m'
| SimuIndex | HarmonicK | LinearCompressionRatio | kT |
Psi3 | Psi6 | RandomSeed |
FIGURE scatter HarmonicK vs KBT, Psi6 as value
import getDataAndScatter as scatt
scatt.workflow_mysql_to_data_pin_hex_to_honeycomb_klt_2m()
"""
import matplotlib.pyplot as plt
import numpy as np
# getDataToMysql
import opertateOnMysql as osql
U_interaction = 300*np.exp(-0.25)
con = 'where HarmonicK < 61'
data = osql.getDataFromMysql(table_name='pin_hex_to_honeycomb_klt_2m', search_condition=con)
data = np.array(data)
prefix = '/home/'+account+'/Downloads/'
postfix = '_pin_hex_to_honeycomb_klt_2m_weak.png'
plt.figure()
# plot lcr VS k, Psi3 as value
plt.scatter(data[:, 2], data[:, 1]*0.5, c=data[:, 4]) # LCR VS K, Psi3 as value
# plt.show()
plt.title('lcr VS k, Psi3 as value, Uparticle='+str(int(U_interaction)))
plt.xlabel('LinearCompressionRatio(1)')
plt.ylabel('U trap (kBT)[honeycomb]')
plt.colorbar()
png_filename = prefix+'K_VS_T_Psi3_as_value'+postfix
plt.savefig(png_filename)
plt.close()
def workflow_mysql_to_data_pin_hex_to_honeycomb_klt_2m_random(account='tplab'):
R"""
Note: the format of table_name='pin_hex_to_honeycomb_klt_2m'
| SimuIndex | HarmonicK | LinearCompressionRatio | kT |
Psi3 | Psi6 | RandomSeed |
FIGURE scatter HarmonicK vs KBT, Psi6 as value
import getDataAndScatter as scatt
scatt.workflow_mysql_to_data_pin_hex_to_honeycomb_klt_2m()
select distinct LinearCompressionRatio, HarmonicK
from pin_hex_to_honeycomb_klt_2m
where SimuIndex<4686
order by SimuIndex, RandomSeed asc;
"""
# import matplotlib.pyplot as plt
import numpy as np
# getDataToMysql
import opertateOnMysql as osql
U_interaction = 300*np.exp(-0.25)
cont = 'distinct LinearCompressionRatio'
con = 'where SimuIndex<4686 order by LinearCompressionRatio asc'
lcrs = osql.getDataFromMysql(table_name='pin_hex_to_honeycomb_klt_2m',
search_condition=con, select_content=cont)
# data=np.array(data)
cont = 'distinct HarmonicK'
con = 'where SimuIndex<4686 order by HarmonicK asc'
ks = osql.getDataFromMysql(table_name='pin_hex_to_honeycomb_klt_2m',
search_condition=con, select_content=cont)
record_lk3 = np.zeros((len(lcrs)*len(ks), 3))
cont = 'distinct LinearCompressionRatio,HarmonicK'
con = 'where SimuIndex<4686 order by LinearCompressionRatio,HarmonicK asc'
lks = osql.getDataFromMysql(table_name='pin_hex_to_honeycomb_klt_2m',
search_condition=con, select_content=cont)
record_lk3[:, 0:2] = np.array(lks)
count = 0
cont = 'avg(Psi3)'
lcr_step = 0.01
for lcr in lcrs:
for k in ks:
lcr1 = np.array(lcr)
lcr_min = lcr1 - 0.5*lcr_step
lcr_max = lcr1 + 0.5*lcr_step
con = 'where SimuIndex<4686 and HarmonicK='+str(int(k[0])) + ' and LinearCompressionRatio >'+str(
lcr_min[0])+' and LinearCompressionRatio <'+str(lcr_max[0])
psi3_avg = osql.getDataFromMysql(table_name='pin_hex_to_honeycomb_klt_2m',
search_condition=con, select_content=cont)
psi3 = np.array(psi3_avg)
record_lk3[count, 2] = psi3[0]
count = count + 1
# data = record_lk3
mp = mysql_data_processor()
title = 'lcr VS k, Psi3 as value' # , Uparticle='+str(int(U_interaction))
xname = 'LinearCompressionRatio(1)'
yname = 'U trap ($k_BT$)[honeycomb]'
prefix = '/home/'+account+'/Downloads/'
postfix = '_pin_hex_to_honeycomb_klt_2m_random.png'
record_lk3[:, 1] = 0.5*record_lk3[:, 1] # k -> Utrap(kT)
mp.draw_diagram_scatter(record_lk3, title, xname, yname, prefix, postfix)
"""
plt.figure()
#plot lcr VS k, Psi3 as value
plt.scatter(data[:,2],data[:,1]*0.5,c=data[:,4])# LCR VS K, Psi3 as value
#plt.show()
plt.title('lcr VS k, Psi3 as value, Uparticle='+str(int(U_interaction)) )
plt.xlabel('LinearCompressionRatio(1)')
plt.ylabel('U trap (kBT)[honeycomb]')
plt.colorbar()
png_filename=prefix+'K_VS_T_Psi3_as_value'+postfix
plt.savefig(png_filename)
plt.close()
"""
def workflow_mysql_to_data_depin_from_honeycomb():
R"""
table_name='depin_from_honeycomb'
simu_index | HarmonicK | LinearCompressionRatio | Psi3Global | Psi6Global
FIGURE scatter HarmonicK vs LCR,
"""
import numpy as np
# getDataToMysql
import opertateOnMysql as osql
data = osql.getDataFromMysql(table_name='depin_from_honeycomb',
search_condition=' where HarmonicK <100')
data = np.array(data)
U_interaction = 300*np.exp(-0.25)
# plot
import matplotlib.pyplot as plt
from matplotlib import cm
from matplotlib.colors import ListedColormap, LinearSegmentedColormap
plt.figure()
# test new color map
# https://matplotlib.org/stable/tutorials/colors/colormap-manipulation.html#sphx-glr-tutorials-colors-colormap-manipulation-py
'''
viridis = cm.get_cmap('viridis',256)
newcolors = viridis(np.linspace(0,1,256))
num=54
orr = cm.get_cmap('Oranges_r',num)
inject_color = orr(np.linspace(0,1,num))
newcolors[0:num,:] = inject_color
newcmp = ListedColormap(newcolors)
'''
num = 54
top = cm.get_cmap('Oranges_r', 128)
bottom = cm.get_cmap('Blues', 128)
newcolors = np.vstack((top(np.linspace(0, 1, num)), bottom(np.linspace(0, 1, 256-num))))
newcmp = ListedColormap(newcolors)
value = data[:, 3]/data[:, 4]
value = np.log10(value)
plt.scatter(data[:, 2], 0.5*data[:, 1], c=value, cmap=newcmp) # K VS LCR, Psi3/Psi6 as value
plt.colorbar()
plt.title('LCR VS K,log(Psi3/Psi6) as value, kBT=1, Uparticle='+str(int(U_interaction)))
plt.xlabel('Linear Compression Ratio (1)')
plt.ylabel('U trap (kBT)[honeycomb]')
prefix = '/home/tplab/Downloads/'
png_filename = prefix+'LCR_VS_K_Psi3_over_Psi6_as_value_changecolor'
plt.savefig(png_filename)
plt.close()
'''
plt.scatter(0.5*data[:,1],data[:,2],c=value,cmap=newcmp)# K VS LCR, Psi3/Psi6 as value
plt.colorbar()
plt.title('K vs LCR,log(Psi3/Psi6) as value, kBT=1, Uparticle='+str(int(U_interaction)) )
plt.xlabel('U trap (kBT)')
plt.ylabel('Linear Compression Ratio (1)')
prefix='/home/tplab/Downloads/'
png_filename=prefix+'K_vs_LCR_Psi3_over_Psi6_as_value_changecolor'
plt.savefig(png_filename)
plt.close()
'''
def workflow_mysql_to_data_pin_hex_to_honeycomb_klt_2m_random_mark(account='tplab'):
R"""
Note: the format of table_name=
'pin_hex_to_honeycomb_klt_2m'
| SimuIndex | HarmonicK | LinearCompressionRatio | kT |
Psi3 | Psi6 | RandomSeed |
'depin_from_honeycomb_part1'
| simu_index | HarmonicK | LinearCompressionRatio |
Psi3Global | Psi6Global | RandomSeed |
https://matplotlib.org/stable/api/markers_api.html#module-matplotlib.markers
"H" <_> hexagon2
"^" triangle_up
"v" triangle_down
"d" v^ thin_diamond
example:
"""
import numpy as np
# getDataToMysql
import opertateOnMysql as osql
# U_interaction=300*np.exp(-0.25)
table_name = 'pin_hex_to_honeycomb_klt_2m'
cont = 'distinct LinearCompressionRatio'
con = ' order by LinearCompressionRatio asc' # where SimuIndex<4686
lcrs = osql.getDataFromMysql(table_name=table_name,
search_condition=con, select_content=cont)
cont = 'distinct HarmonicK'
con = ' order by HarmonicK asc'
ks = osql.getDataFromMysql(table_name=table_name,
search_condition=con, select_content=cont)
cont = 'distinct LinearCompressionRatio,HarmonicK'
con = ' order by LinearCompressionRatio,HarmonicK asc'
lks = osql.getDataFromMysql(table_name=table_name,
search_condition=con, select_content=cont)
record_lk36 = np.zeros((len(lks), 4)) # (lcr,k,psi3,psi6)
# record_lk36[:,0:2]=np.array(lks)
count = 0
cont = ' avg(Psi3),avg(Psi6) '
lcr_step = 0.001
for lcr in lcrs:
for k in ks:
lcr1 = np.array(lcr)
lcr_min = lcr1 - 0.5*lcr_step
lcr_max = lcr1 + 0.5*lcr_step
con = ' where HarmonicK=' + str(int(k[0])) + ' and LinearCompressionRatio >' + str(
lcr_min[0]) + ' and LinearCompressionRatio <' + str(lcr_max[0])
psi36_avg = osql.getDataFromMysql(table_name=table_name,
search_condition=con, select_content=cont)
psi36 = np.array(psi36_avg[0])
# print(math.isnan(psi36[0]))#(np.nan(psi36_avg[0])
if not psi36[0] is None: # math.isnan(psi36[0]):
# if not (k[0]<101 and k[0]>97):
# print(k)
# record_lk36[count,2:] = psi36[0:2]
record_lk36[count, :] = [lcr[0], k[0], psi36[0], psi36[1]]
count = count + 1
record_lk36 = record_lk36[:count]
# data = record_lk3
record_lk36[:, 1] = 0.5*record_lk36[:, 1] # k -> Utrap(kT)
return record_lk36
def workflow_mysql_to_data_depin_from_honeycomb_mark():
R"""
Note: the format of table_name=
'depin_from_honeycomb'
| simu_index | HarmonicK | LinearCompressionRatio |
Psi3Global | Psi6Global | RandomSeed |
"""
data = osql.getDataFromMysql(
table_name='depin_from_honeycomb') # ,search_condition=' where HarmonicK <100'
data = np.array(data)
p36 = data[:, 3]/data[:, 4]
p36 = np.log10(p36)
sz = np.shape(data)
record_lklg3 = np.zeros((sz[0], 3))
record_lklg3[:, 0] = data[:, 2] # lcr
record_lklg3[:, 1] = data[:, 1]*0.5 # k
record_lklg3[:, 2] = p36
list_lg3 = record_lklg3[:, 1] < 11 # U(honeycomb pin stable)~10
return record_lklg3[list_lg3]
def workflow_data_to_diagram_honeycomb_mark(account='tplab', save_mode="csv"):
R"""
Note: the format of table_name=
'pin_hex_to_honeycomb_klt_2m'
| SimuIndex | HarmonicK | LinearCompressionRatio | kT |
Psi3 | Psi6 | RandomSeed |
'depin_from_honeycomb'
| simu_index | HarmonicK | LinearCompressionRatio |
Psi3Global | Psi6Global | RandomSeed |
https://matplotlib.org/stable/api/markers_api.html#module-matplotlib.markers
"H" <_> hexagon2
"^" triangle_up
"v" triangle_down
"d" v^ thin_diamond
example:
"""
fig_name = 'diagram_HC_mark'
record_lk36 = workflow_mysql_to_data_pin_hex_to_honeycomb_klt_2m_random_mark()
record_lklg3 = workflow_mysql_to_data_depin_from_honeycomb_mark()
mp = mysql_data_processor()
title = 'lcr VS k, Psi3 as value' # , Uparticle='+str(int(U_interaction))
xlabel_name = 'Linear Compression Ratio (1)'
ylabel_name = 'Usub ($k_BT$)[Honeycomb]' # [HC]
prefix = '/home/'+account+'/Downloads/'
if save_mode == "pdf":
postfix = '_'+fig_name+'.pdf'
fig, ax = mp.draw_diagram_scatter_mark_multi(
record_lk36, title, xlabel_name, ylabel_name, prefix, postfix=None, oop_check=0.85)
mp.draw_diagram_scatter_mark_multi(
record_lklg3, title, xlabel_name, ylabel_name, prefix, postfix, 0.2, fig, ax, "depin")
elif save_mode == "csv":
postfix = '_'+fig_name+'.csv'
df0 = mp.get_diagram_data_mark_multi(
record_lk36, title, xlabel_name, ylabel_name, prefix, csv_postfix=None, oop_check=0.85)
mp.get_diagram_data_mark_multi(record_lklg3, title, xlabel_name,
ylabel_name, prefix, postfix, 0.2, "depin", df0)
def workflow_mysql_to_data_depin_from_honeycomb_part1(num_to_zero=64):
R"""
table_name='depin_from_honeycomb_part1'
simu_index | HarmonicK | LinearCompressionRatio | Psi3Global | Psi6Global
FIGURE scatter HarmonicK vs LCR,
parameters:
num_to_zero: set a num(int) to let white fixed on zero,
then red and blue colorbar will distribute with symmetry.
"""
import numpy as np
# getDataToMysql
import opertateOnMysql as osql
# ,search_condition=' where HarmonicK <100'
data = osql.getDataFromMysql(table_name='depin_from_honeycomb_part1')
data = np.array(data)
U_interaction = 300*np.exp(-0.25)
# plot
import matplotlib.pyplot as plt
from matplotlib import cm
from matplotlib.colors import ListedColormap, LinearSegmentedColormap
plt.figure()
# test new color map
# https://matplotlib.org/stable/tutorials/colors/colormap-manipulation.html#sphx-glr-tutorials-colors-colormap-manipulation-py
'''
viridis = cm.get_cmap('viridis',256)
newcolors = viridis(np.linspace(0,1,256))
num=54
orr = cm.get_cmap('Oranges_r',num)
inject_color = orr(np.linspace(0,1,num))
newcolors[0:num,:] = inject_color
newcmp = ListedColormap(newcolors)
'''
num = num_to_zero
top = cm.get_cmap('Oranges_r', 128)
bottom = cm.get_cmap('Blues', 128)
newcolors = np.vstack((top(np.linspace(0, 1, num)), bottom(np.linspace(0, 1, 256-num))))
newcmp = ListedColormap(newcolors)
value = data[:, 3]/data[:, 4]
value = np.log10(value)
plt.scatter(data[:, 2], 0.5*data[:, 1], c=value, cmap=newcmp) # LCR vs K, Psi3/Psi6 as value
plt.colorbar()
plt.title('LCR VS K,log(Psi3/Psi6) as value, kBT=1, Uparticle='+str(int(U_interaction))+',depin')
plt.xlabel('Linear Compression Ratio (1)')
plt.ylabel('U trap (kBT)[honeycomb part1]')
prefix = '/home/tplab/Downloads/'
png_filename = prefix+'LCR_vs_K_Psi3_over_Psi6_as_value_changecolor_part1_depin'
plt.savefig(png_filename)
plt.close()
def workflow_mysql_to_data_depin_from_honeycomb_part_36_kt(num_to_zero=64):
R"""
table_name='depin_from_honeycomb_part_klt'
| simu_index | HarmonicK | LinearCompressionRatio | kT | Psi3Global | Psi6Global | RandomSeed |
FIGURE scatter HarmonicK vs LCR,
parameters:
num_to_zero: set a num(int) to let white fixed on zero,
then red and blue colorbar will distribute with symmetry.
"""
import numpy as np
# getDataToMysql
import opertateOnMysql as osql
# depin_from_honeycomb_part1,search_condition=' where HarmonicK <100'
data = osql.getDataFromMysql(table_name='depin_from_honeycomb_part_klt')
data = np.array(data)
U_interaction = 300*np.exp(-0.25)
# plot
import matplotlib.pyplot as plt
from matplotlib import cm
from matplotlib.colors import ListedColormap, LinearSegmentedColormap
plt.figure()
# test new color map
# https://matplotlib.org/stable/tutorials/colors/colormap-manipulation.html#sphx-glr-tutorials-colors-colormap-manipulation-py
'''
viridis = cm.get_cmap('viridis',256)
newcolors = viridis(np.linspace(0,1,256))
num=54
orr = cm.get_cmap('Oranges_r',num)
inject_color = orr(np.linspace(0,1,num))
newcolors[0:num,:] = inject_color
newcmp = ListedColormap(newcolors)
'''
num = num_to_zero
top = cm.get_cmap('Oranges_r', 128)
bottom = cm.get_cmap('Blues', 128)
newcolors = np.vstack((top(np.linspace(0, 1, num)), bottom(np.linspace(0, 1, 256-num))))
newcmp = ListedColormap(newcolors)
value = data[:, 4]/data[:, 5]
value = np.log10(value)
plt.scatter(0.5*data[:, 1], data[:, 3], c=value, cmap=newcmp) # LCR vs K, Psi3/Psi6 as value
plt.colorbar()
plt.title('K VS T,log(Psi3/Psi6) as value, kBT=1, Uparticle='+str(int(U_interaction))+',depin')
plt.xlabel('U trap (kBT)[honeycomb part1]')
plt.ylabel('kBT')
prefix = '/home/tplab/Downloads/'
png_filename = prefix+'K_vs_T_Psi3_over_Psi6_as_value_changecolor_part1_depin'
plt.savefig(png_filename)
plt.close()
def workflow_mysql_to_data_depin_from_honeycomb_part_kt():
R"""
table_name='depin_from_honeycomb_part_klt'
| simu_index | HarmonicK | LinearCompressionRatio | kT | Psi3Global | Psi6Global | RandomSeed |
FIGURE scatter HarmonicK vs LCR,
parameters:
num_to_zero: set a num(int) to let white fixed on zero,
then red and blue colorbar will distribute with symmetry.
"""
import numpy as np
# getDataToMysql
import opertateOnMysql as osql
# depin_from_honeycomb_part1,search_condition=' where HarmonicK <100'
data = osql.getDataFromMysql(table_name='depin_from_honeycomb_part_klt')
data = np.array(data)
U_interaction = 300*np.exp(-0.25)
# plot
import matplotlib.pyplot as plt
from matplotlib import cm
from matplotlib.colors import ListedColormap, LinearSegmentedColormap
plt.figure()
plt.scatter(0.5*data[:, 1], data[:, 3], c=data[:, 4]) # K VS T, Psi3 as value
plt.colorbar()
plt.title('K VS T,log(Psi3/Psi6) as value, kBT=1, Uparticle='+str(int(U_interaction))+',depin')
plt.xlabel('U trap (kBT)[honeycomb part1]')
plt.ylabel('kBT')
prefix = '/home/tplab/Downloads/'
png_filename = prefix+'K_vs_T_Psi3_as_value_honeycomb_part1_depin'
plt.savefig(png_filename)
plt.close()
def workflow_mysql_to_data_pin_hex_to_honeycomb_part1(compare36=False, num_to_zero=64, p3=False):
R"""
table_name='pin_hex_to_honeycomb_part1'
simu_index | HarmonicK | LinearCompressionRatio | Psi3Global | Psi6Global
FIGURE scatter HarmonicK vs LCR,
"""
import numpy as np
# getDataToMysql
import opertateOnMysql as osql
# ,search_condition=' where HarmonicK <100'
data = osql.getDataFromMysql(table_name='pin_hex_to_honeycomb_part1',
search_condition="where HarmonicK > 99")
data = np.array(data)
U_interaction = 300*np.exp(-0.25)
# plot
import matplotlib.pyplot as plt
from matplotlib import cm
from matplotlib.colors import ListedColormap, LinearSegmentedColormap
plt.figure()
if compare36:
# test new color map
# https://matplotlib.org/stable/tutorials/colors/colormap-manipulation.html#sphx-glr-tutorials-colors-colormap-manipulation-py
num = num_to_zero
top = cm.get_cmap('Oranges_r', 128)
bottom = cm.get_cmap('Blues', 128)
newcolors = np.vstack((top(np.linspace(0, 1, num)), bottom(np.linspace(0, 1, 256-num))))
newcmp = ListedColormap(newcolors)
value = data[:, 3]/data[:, 4]
value = np.log10(value)
plt.scatter(data[:, 2], 0.5*data[:, 1], c=value,
cmap=newcmp) # LCR vs K, Psi3/Psi6 as value
plt.colorbar()
plt.title('LCR vs K,log(Psi3/Psi6) as value, kBT=1, Uparticle='+str(int(U_interaction))+',pin')
plt.xlabel('Linear Compression Ratio (1)')
plt.ylabel('U trap (kBT)[honeycomb part1]')
# plt.yscale('symlog') #log is not suitable
prefix = '/home/tplab/Downloads/'
png_filename = prefix+'LCR_vs_K1k_Psi3_over_Psi6_as_value_changecolor_part1_pin'
plt.savefig(png_filename)
plt.close()
elif p3:
plt.scatter(data[:, 2], 0.5*data[:, 1], c=data[:, 3]) # LCR vs K, Psi3 as value
plt.colorbar()
plt.title('LCR vs K,Psi3 as value, kBT=1, Uparticle='+str(int(U_interaction))+',pin')
plt.xlabel('Linear Compression Ratio (1)')
plt.ylabel('U trap (kBT)[honeycomb part1]')
# plt.yscale('symlog') #log is not suitable
prefix = '/home/tplab/Downloads/'
png_filename = prefix+'LCR_vs_K1k_Psi3_as_value_changecolor_part1_pin'
plt.savefig(png_filename)
plt.close()
else:
plt.scatter(data[:, 2], 0.5*data[:, 1], c=data[:, 4]) # LCR vs K, Psi6 as value
plt.colorbar()
plt.title('LCR vs K,Psi6 as value, kBT=1, Uparticle='+str(int(U_interaction))+',pin')
plt.xlabel('Linear Compression Ratio (1)')
plt.ylabel('U trap (kBT)[honeycomb part1]')
# plt.yscale('symlog') #log is not suitable
prefix = '/home/tplab/Downloads/'
png_filename = prefix+'LCR_vs_K1k_Psi6_as_value_changecolor_part1_pin'
plt.savefig(png_filename)
plt.close()
def workflow_mysql_to_data_pin_hex_to_honeycomb_part_klt(account='tplab'):
R"""
Note: the format of table_name='pin_hex_to_honeycomb_part_klt'
| SimuIndex | HarmonicK | LinearCompressionRatio | kT |
CoordinationNum3Rate | CoordinationNum4Rate | RandomSeed |
FIGURE scatter HarmonicK vs KBT, Psi6 as value
import getDataAndScatter as scatt
scatt.workflow_mysql_to_data_pin_hex_to_honeycomb_part_klt()
"""
import matplotlib.pyplot as plt
import numpy as np
# getDataToMysql
import opertateOnMysql as osql
U_interaction = 300*np.exp(-0.25)
data = osql.getDataFromMysql(table_name='pin_hex_to_honeycomb_part_klt')
data = np.array(data)
prefix = '/home/'+account+'/Downloads/'
postfix = '_pin_hex_to_honeycomb_part_klt.png'
plt.figure()
# plot k VS T, CN4 as value
plt.scatter(data[:, 1]*0.5, data[:, 3], c=data[:, 4]) # LCR VS K, CN4 as value
# plt.show()
plt.title('k VS T, CN3 as value, LCRc, Uparticle='+str(int(U_interaction)))
plt.xlabel('U trap (kBT)[Honeycomb part]')
plt.ylabel('kBT')
plt.colorbar()
png_filename = prefix+'K_VS_T_CN3_as_value'+postfix
plt.savefig(png_filename)
plt.close()
def workflow_mysql_to_data_pin_hex_to_honeycomb_part_klt_2m(account='tplab'):
R"""
Note: the format of table_name='pin_hex_to_honeycomb_part_klt_2m'
| SimuIndex | HarmonicK | LinearCompressionRatio | kT |
Psi3 | Psi6 | RandomSeed |
FIGURE scatter HarmonicK vs KBT, Psi6 as value
example:
import getDataAndScatter as scatt
scatt.workflow_mysql_to_data_pin_hex_to_honeycomb_part_klt_2m(account='remote')
example:
# lcr=0.77-0.78,seed=0-9
$ select * from pin_hex_to_honeycomb_part_klt_2m where SimuIndex >4335 and SimuIndex <4356;
#"where SimuIndex > 5298"
# lcr=0.79-0.8165-0.84,seed=0-9
$ select * from pin_hex_to_honeycomb_part_klt_2m where SimuIndex >4265 and SimuIndex <4336;
"""
import matplotlib.pyplot as plt
import numpy as np
# getDataToMysql
import opertateOnMysql as osql
U_interaction = 300*np.exp(-0.25)
condition = "where SimuIndex > 4265 and SimuIndex<4336"
data = osql.getDataFromMysql(
table_name='pin_hex_to_honeycomb_part_klt_2m', search_condition=condition)
data = np.array(data)
prefix = '/home/'+account+'/Downloads/'
postfix = '_pin_hex_to_honeycomb_part_klt_2m_random.png'
# print(data[:,4])
plt.figure()
# plot k VS T, Psi3 as value
plt.scatter(data[:, 2], data[:, 1]*0.5, c=data[:, 4]) # LCR VS K, Psi3 as value
# plt.show()
plt.title('k VS T, Psi3 as value, Uparticle='+str(int(U_interaction)))
plt.xlabel('Linear Compression Ratio (1)')
plt.ylabel('U trap ($k_BT_m$)[Honeycomb part]')
plt.colorbar()
png_filename = prefix+'K_VS_T_Psi3_as_value'+postfix
plt.savefig(png_filename)
plt.close()
plt.figure()
# plot k VS T, Psi6 as value
plt.scatter(data[:, 2], data[:, 1]*0.5, c=data[:, 5]) # LCR VS K, Psi6 as value
# plt.show()
plt.title('k VS T, Psi6 as value, Uparticle='+str(int(U_interaction)))
plt.xlabel('Linear Compression Ratio (1)')
plt.ylabel('U trap (kBTm)[Honeycomb part]')
plt.colorbar()
png_filename = prefix+'K_VS_T_Psi6_as_value'+postfix
plt.savefig(png_filename)
plt.close()
def workflow_mysql_to_data_pin_hex_to_honeycomb_part_klt_2m_random_oop(account='tplab'):
R"""
Note: the format of table_name='pin_hex_to_honeycomb_part_klt_2m'
| SimuIndex | HarmonicK | LinearCompressionRatio | kT |
Psi3 | Psi6 | RandomSeed |
FIGURE scatter HarmonicK vs KBT, Psi6 as value
example:
import getDataAndScatter as scatt
scatt.workflow_mysql_to_data_pin_hex_to_honeycomb_part_klt_2m_random_oop(account='remote')
example:
# lcr=0.77-0.78,seed=0-9
$ select * from pin_hex_to_honeycomb_part_klt_2m where SimuIndex >4335 and SimuIndex <4356;
#"where SimuIndex > 5298"
# lcr=0.79-0.8165-0.84,seed=0-9
$ select * from pin_hex_to_honeycomb_part_klt_2m where SimuIndex >4265 and SimuIndex <4336;
"""
import matplotlib.pyplot as plt
import numpy as np
# getDataToMysql
import opertateOnMysql as osql
pr = mysql_data_processor()
U_interaction = 300*np.exp(-0.25)
condition = "where SimuIndex > 4265 and SimuIndex<4336"
data = osql.getDataFromMysql(
table_name='pin_hex_to_honeycomb_part_klt_2m', search_condition=condition)
data = np.array(data)
prefix = '/home/'+account+'/Downloads/'
postfix = '_pin_hex_to_honeycomb_part_klt_2m_random.png'
list_k, k_num = pr.unique_param(data[:, 1])
list_lcr, lcr_num = pr.unique_param(data[:, 2])
record = np.zeros((lcr_num*k_num, 6))
row = 0
for k in list_k:
for lcr in list_lcr:
list_row = (data[:, 1] == k) & (data[:, 2] == lcr)
random_point = data[list_row, 4:5+1]
record[row, 0] = k*0.5
record[row, 1] = lcr
record[row, 2], record[row, 3] = pr.average_std(random_point[:, 0]) # psi3
record[row, 4], record[row, 5] = pr.average_std(random_point[:, 1]) # psi6
row = row+1
xlabel_name = 'Linear Compression Ratio (1)'
ylabel_name = 'U trap ($k_BT_m$)[Honeycomb part]'
title_name = 'lcr_VS_K_Psi3_as_value'
results = pr.record_to_results_for_scatter(record, 1, 0, 2)
pr.draw_diagram_scatter(results, title_name, xlabel_name, ylabel_name, prefix, postfix)
title_name = 'lcr_VS_K_Psi3std_as_value'
results = pr.record_to_results_for_scatter(record, 1, 0, 3)
pr.draw_diagram_scatter(results, title_name, xlabel_name, ylabel_name, prefix, postfix)
title_name = 'lcr_VS_K_Psi6_as_value'
results = pr.record_to_results_for_scatter(record, 1, 0, 4)
pr.draw_diagram_scatter(results, title_name, xlabel_name, ylabel_name, prefix, postfix)
title_name = 'lcr_VS_K_Psi6std_as_value'
results = pr.record_to_results_for_scatter(record, 1, 0, 5)
pr.draw_diagram_scatter(results, title_name, xlabel_name, ylabel_name, prefix, postfix)
def workflow_mysql_to_data_pin_hex_to_honeycomb_part_klt_2m_random_mark(account='tplab'):
R"""
Note: the format of table_name=
'pin_hex_to_honeycomb_part_klt_2m'
| SimuIndex | HarmonicK | LinearCompressionRatio | kT |
Psi3 | Psi6 | RandomSeed |
'depin_from_honeycomb_part1'
| simu_index | HarmonicK | LinearCompressionRatio |
Psi3Global | Psi6Global | RandomSeed |
https://matplotlib.org/stable/api/markers_api.html#module-matplotlib.markers
"H" <_> hexagon2
"^" triangle_up
"v" triangle_down
"d" v^ thin_diamond
example:
"""
import numpy as np
# getDataToMysql
import opertateOnMysql as osql
# U_interaction=300*np.exp(-0.25)
table_name = 'pin_hex_to_honeycomb_part_klt_2m'
cont = 'distinct LinearCompressionRatio'
con = ' order by LinearCompressionRatio asc' # where SimuIndex<4686
lcrs = osql.getDataFromMysql(table_name=table_name,
search_condition=con, select_content=cont)
cont = 'distinct HarmonicK'
con = ' order by HarmonicK asc'
ks = osql.getDataFromMysql(table_name=table_name,
search_condition=con, select_content=cont)
cont = 'distinct LinearCompressionRatio,HarmonicK'
con = ' order by LinearCompressionRatio,HarmonicK asc'
lks = osql.getDataFromMysql(table_name=table_name,
search_condition=con, select_content=cont)
record_lk36 = np.zeros((len(lks), 4)) # (lcr,k,psi3,psi6)
# record_lk36[:,0:2]=np.array(lks)
count = 0
cont = ' avg(Psi3),avg(Psi6) '
lcr_step = 0.001
for lcr in lcrs:
for k in ks:
lcr1 = np.array(lcr)
lcr_min = lcr1 - 0.5*lcr_step
lcr_max = lcr1 + 0.5*lcr_step
con = ' where HarmonicK=' + str(int(k[0])) + ' and LinearCompressionRatio >' + str(
lcr_min[0]) + ' and LinearCompressionRatio <' + str(lcr_max[0])
psi36_avg = osql.getDataFromMysql(table_name=table_name,
search_condition=con, select_content=cont)
psi36 = np.array(psi36_avg[0])
# print(math.isnan(psi36[0]))#(np.nan(psi36_avg[0])
if not psi36[0] is None: # math.isnan(psi36[0]):
if not (k[0] < 101 and k[0] > 97):
# print(k)
# record_lk36[count,2:] = psi36[0:2]
record_lk36[count, :] = [lcr[0], k[0], psi36[0], psi36[1]]
count = count + 1
record_lk36 = record_lk36[:count]
# data = record_lk3
record_lk36[:, 1] = 0.5*record_lk36[:, 1] # k -> Utrap(kT)
return record_lk36
def workflow_mysql_to_data_depin_from_honeycomb_part1_mark():
R"""
Note: the format of table_name=
'depin_from_honeycomb_part1'
| simu_index | HarmonicK | LinearCompressionRatio |
Psi3Global | Psi6Global | RandomSeed |
"""
data = osql.getDataFromMysql(
table_name='depin_from_honeycomb_part1') # ,search_condition=' where HarmonicK <100'
data = np.array(data)
p36 = data[:, 3]/data[:, 4]
p36 = np.log10(p36)
sz = np.shape(data)
record_lklg3 = np.zeros((sz[0], 3))
record_lklg3[:, 0] = data[:, 2] # lcr
record_lklg3[:, 1] = data[:, 1]*0.5 # k
record_lklg3[:, 2] = p36
list_lg3 = record_lklg3[:, 1] < 31 # U(honeycomb_part pin stable)~30
return record_lklg3[list_lg3]
def workflow_data_to_diagram_honeycomb_part_mark(account='tplab', save_mode="csv"):
R"""
Note: the format of table_name=
'pin_hex_to_honeycomb_part_klt_2m'
| SimuIndex | HarmonicK | LinearCompressionRatio | kT |
Psi3 | Psi6 | RandomSeed |
'depin_from_honeycomb_part1'
| simu_index | HarmonicK | LinearCompressionRatio |
Psi3Global | Psi6Global | RandomSeed |
https://matplotlib.org/stable/api/markers_api.html#module-matplotlib.markers
"H" <_> hexagon2
"^" triangle_up
"v" triangle_down
"d" v^ thin_diamond
example:
"""
fig_name = 'diagram_HCP_mark'
record_lk36 = workflow_mysql_to_data_pin_hex_to_honeycomb_part_klt_2m_random_mark()
record_lklg3 = workflow_mysql_to_data_depin_from_honeycomb_part1_mark()
mp = mysql_data_processor()
title = 'lcr VS k, Psi3 as value' # , Uparticle='+str(int(U_interaction))
xlabel_name = 'Linear Compression Ratio (1)'
ylabel_name = 'Usub ($k_BT$)[Honeycomb_part]'
prefix = '/home/'+account+'/Downloads/'
if save_mode == "pdf":
postfix = '_'+fig_name+'.pdf'
fig, ax = mp.draw_diagram_scatter_mark_multi(
record_lk36, title, xlabel_name, ylabel_name, prefix, postfix=None, oop_check=0.85)
mp.draw_diagram_scatter_mark_multi(
record_lklg3, title, xlabel_name, ylabel_name, prefix, postfix, 0.3, fig, ax, "depin")