def get_from_database(x1, x2, mat, inquiry_keys = None, silent = None, ssh_object = None):
"""
inquiry_keys (list) - list of keys that should exist in filenames both for x1 and x2
ssh_object (SSHTools) - ssh object based on paramiko with access details
"""
def check(key, inquiry_keys):
return all([k in key for k in inquiry_keys])
path2database = '/home/Data/CEStorage/'
hash_dict_file = 'hash_dict.json'
cluster_path2hash = os.path.join(path2database, hash_dict_file)
if inquiry_keys is None:
inquiry_keys = []
if ssh_object:
# ssh_object.get()
tempdir = tempfile.gettempdir()
local_path2hash = os.path.join(tempdir, hash_dict_file)
ssh_object.get(cluster_path2hash, local_path2hash )
# sys.exit()
with open(local_path2hash, 'r') as fp:
hash_dict = json.load(fp)
# print(hash_dict)
x1s = []
x2s = []
# print(hash_dict)
for key, val in hash_dict.items():
if check(key, inquiry_keys+[x1, mat]):
x1s.append(key)
if check(key, inquiry_keys+[x2, mat]):
x2s.append(key)
x1s = sorted(x1s, key = lambda el: len(el) )
x2s = sorted(x2s, key = lambda el: len(el) )
for xi, xis in (x1, x1s), (x2, x2s):
if not silent:
print('\nFiles for',xi,':')
for i, f in enumerate(xis):
if not silent:
print(i+1,f)
if len(x1s) == 0 or len(x2s) == 0:
print('No information in database for this inquire:', x1, x2, mat, str(inquiry_keys) )
return None, None
key1 = x1s[0]
key2 = x2s[0]
if not silent:
print('\nI choose first entries for both concentrations:',key1, 'and', key2,'\n')
# print('Use *inquiry_keys* arg to clarify the output results.\n')
#get files
loc1 = os.path.join(tempdir, hash_dict[key1])
loc2 = os.path.join(tempdir, hash_dict[key2])
makedir(loc1)
makedir(loc2)
# print()/
ssh_object.get(os.path.join(path2database, hash_dict[key1]), loc1 )
ssh_object.get(os.path.join(path2database, hash_dict[key2]), loc2 )
cl1 = CalculationVasp().deserialize(loc1)
cl2 = CalculationVasp().deserialize(loc2)
return cl1, cl2
# 2. View the contents of the current folder
# 3. Delete folder
# 4. Create a folder
# When choosing items: 1, 2, 3, 4 the program asks for the name of the folder
# and displays the result of the action: "Successfully created / deleted / moved", "Unable to create / delete / to go to the folder"
# To solve this problem, use the algorithms from the easy task,
# designed as appropriate functions, and imported into this file from easy.py
import functions
import sys
import os
while True:
print('1 - Go to the folder',
'2 - View the contents of the current folder', '3 - Delete folder',
'4 - Create a folder')
a = int(input('Choose action'))
if a == 1:
functions.changedir()
elif a == 2:
functions.dirlist()
elif a == 3:
functions.deldir()
elif a == 4:
functions.makedir()
else:
print('There is no such function')
key = input("Press 'q' to")
if key == 'q':
sys.exit()
def fit_and_plot(power = None, xlabel = "xlabel", ylabel = "ylabel", image_name = None, show = None,
xlim = None, ylim = None, title = None, figsize = None,
xlog = False,ylog = False, scatter = False, legend = False, markersize = 10, linewidth = 3, hor = False, fig_format = 'eps', dpi = 300,
**data):
"""Should be used in two below sections!
Creates one plot with two dependecies and fit them;
return minimum fitted value of x2 and corresponding value of y2;
if name == "" image will not be plotted
power - the power of polynom
fig_format - format of saved file.
dpi - resolution of saved file
data - each entry should be (X, Y, 'r-')
"""
# print data
if 1:
plt.figure(figsize=figsize)
if title:
plt.title(title)
plt.ylabel(ylabel)
plt.xlabel(xlabel)
scatterpoints = 1
for key in sorted(data):
if scatter:
plt.scatter(data[key][0], data[key][1], s = data[key][2], c = data[key][-1], alpha = 0.8, label = key)
else:
try:
label = data[key][3]
except:
label = key
# print 'label is ', label
plt.plot(data[key][0], data[key][1], data[key][2], linewidth = linewidth, label = label, markersize = markersize, alpha = 0.8)
if hor: plt.axhline(color = 'k') #horizontal line
plt.axvline(color='k')
if xlim:
plt.xlim(xlim)
# axes = plt.gca()
# axes.set_xlim([xmin,xmax])
# axes.set_ylim([ymin,ymax])
if ylim:
plt.ylim(ymin=ylim[0])
if ylim[1]: plt.ylim(ymax=ylim[1])
if power:
for key in data:
coeffs1 = np.polyfit(data[key][0], data[key][1], power)
fit_func1 = np.poly1d(coeffs1)
x_range = np.linspace(min(data[key][0]), max(data[key][0]))
fit_y1 = fit_func1(x_range);
plt.plot(x_range, fit_y1, data[key][-1][0], )
# x_min = fit_func2.deriv().r[power-2] #derivative of function and the second cooffecient is minimum value of x.
# y_min = fit_func2(x_min)
slope, intercept, r_value, p_value, std_err = scipy.stats.linregress(data[key][0], data[key][1])
# print 'R^2 = ', r_value**2, key
if xlog: plt.xscale('log')
if ylog:
if "sym" in str(ylog):
plt.yscale('symlog', linthreshx=0.1)
else:
plt.yscale('log')
if legend:
plt.legend(loc = legend, scatterpoints = scatterpoints)
plt.tight_layout()
path2saved = ''
if image_name:
makedir(image_name)
try:
path_to_images
except:
path_to_images = ''
if fig_format in image_name:
path2saved = str(image_name)
elif str(image_name).split('.')[-1] in ['eps', 'png', 'pdf']:
path2saved = str(image_name)
fig_format = str(image_name).split('.')[-1]
else:
path2saved = str(image_name)+'.'+fig_format
plt.savefig(path2saved, dpi = dpi, format=fig_format)
plt.savefig(str(image_name)+'.png', dpi = 300)
print_and_log("Image saved to ", path2saved)
elif show is None:
show = True
# print_and_log(show)
if show:
plt.show()
plt.clf()
plt.close('all')
return path2saved
