计算带格林内森参数投影的高温声子谱

## 1.算高温声子谱
算xxxK的MD之后，就在这个目录下
参考脚本一步步做，带#的也要做（浪潮服务器，老师账号）
```bash
#!/bin/sh
cp ../POSCAR infile.ucposcar
cp POSCAR infile.ssposcar
#module load  anaconda/2
python ~/intel/tdep-devel-master/bin/process_outcar_5.3.py OUTCAR

#source ~/intel/oneapi/setvars.sh #(intel oneapi)
#export LD_LIBRARY_PATH=/home/ding/intel/hdf5-1.8.15/hdf5/lib:$LD_LIBRARY_PATH
#export LD_LIBRARY_PATH=/home/ding/intel/oneapi/compiler/2022.0.1/linux/compiler/lib/intel64_lin:$LD_LIBRARY_PATH

#module rm anaconda/2
extract_forceconstants -rc2 8 #10可修改,对结果有影响
ln -s outfile.forceconstant infile.forceconstant
cp ../../../tdep/infile.qpoints_dispersion ./
#touch infile.qpoints_dispersion
phonon_dispersion_relations --readpath --unit thz
#outfile.dispersion_relations 作图
#module load gnuplot/5.4.0
gnuplot outfile.dispersion_relations.gnuplot

```
infile.qpoints_dispersion文件：
```
CUSTOM
   40  ! number of points on each path
   5   ! number of path
 0 0 0 0.5 0 0  G X
 0.5 0 0 0.5 0.5 0 X S
 0.5 0.5 0 0 0.5 0 S Y
 0 0.5 0 0 0 0     Y G
 0 0 0 0.5 0.5 0   G S

```
最终导出outfile.dispersion_relations到origin里面作图

## 2.画格林内森参数投影图
导入环境之后，提取三阶力常数，这个需要进结点交任务
`mpirun -np 4 extract_forceconstants -rc2 8 -rc3 4 > log &`
`cp outfile.forceconstant infile.forceconstant`
` ln -s outfile.forceconstant_thirdorder infile.forceconstant_thirdorder`
`phonon_dispersion_relations --gruneisen -rp`
将outfile.mode_gruneisen_parameters和 outfile.dispersion_relations 拷贝出来或者将plot.py放进目录中使用即可画图，需要修改路径（sys_list）和刻度（gamma_max）
```python
import pandas as pd
import matplotlib.pyplot as plt
from matplotlib.pyplot import MultipleLocator
from matplotlib.collections import LineCollection
from matplotlib.colors import BoundaryNorm, ListedColormap
import numpy as np

dispersion_data = pd.read_csv('outfile.dispersion_relations', sep='\s+', header=None)
gruneisen_data = pd.read_csv('outfile.mode_gruneisen_parameters', sep='\s+', header=None)

dispersion_x = dispersion_data.iloc[:, 0]

lines_lenth = len(dispersion_data)
sys_list = ['Γ', 'L', 'Z', 'F', 'Γ', 'Z']
sys_lenth = len(sys_list)

plt.rcParams["font.family"] = "Times New Roman"

fig1, ax1 = plt.subplots(1, 1, sharex=True, sharey=True)

bandmax = 12 #修改需要的带数
cmap = 'seismic'

gamma_max = 4
gamma_min = -4
#gamma_max = max(gruneisen_data.iloc[:,1:(bandmax+1)].max())
#gamma_min = min(gruneisen_data.iloc[:,1:(bandmax+1)].min())
norm = plt.Normalize(gamma_min, gamma_max)
print(gamma_max)
print(gamma_min)

for i in range(bandmax):
    points = np.array([dispersion_x, dispersion_data.iloc[:, i+1]]).T.reshape(-1, 1, 2)
    segments = np.concatenate([points[:-1], points[1:]], axis=1)
    lc = LineCollection(segments, cmap='seismic', norm=norm)
    lc.set_array(gruneisen_data.iloc[:, i+1])
    lc.set_linewidth(2)
    line = ax1.add_collection(lc)
cbar = fig1.colorbar(line, ax=ax1)
cbar.ax.tick_params(labelsize = 20)

special_labels = {}
for m in range(sys_lenth):
    if m == 0:
        special_labels[dispersion_x[(lines_lenth/(sys_lenth-1)) * m ]] = sys_list[m]
    else:
        special_labels[dispersion_x[(lines_lenth/(sys_lenth-1)) * m - 1]] = sys_list[m]

x_min, x_max = 0, max(dispersion_x)  # x轴范围
y_min, y_max = 0, max(dispersion_data.iloc[:,1:(bandmax+1)].max()) + 0.2 # y轴范围
plt.xlim(x_min, x_max)
plt.ylim(y_min, y_max)

# x轴
ymajor = MultipleLocator(1)  # 主 10 的倍数
yminor = MultipleLocator(0.5)  # 次 2的倍数

# 设置 x/y轴刻度，以及刻度标签
# x 轴
ax1.yaxis.set_minor_locator(yminor)
ax1.yaxis.set_major_locator(ymajor)

xticks = list(special_labels.keys())
xticklabels = list(special_labels.values())
print(xticks)
plt.xticks(xticks, xticklabels)
plt.tick_params(axis='x', which='both', bottom=False, labelsize = 20)
plt.tick_params(axis='y', which='both', direction='in', labelsize = 20)
for i in range(len(xticks)-1):
    plt.axvline(x=xticks[i], linestyle='dashed', color='gray', linewidth=1)

plt.show()

```

![](/media/202407/2024-07-09_161642_2415460.39842632459456995.png)

计算带格林内森参数投影的高温声子谱

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计算带格林内森参数投影的高温声子谱

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