Python get_project_root Examples

Example #1

def form_ed_tuple(ed_name, methods_names_tuple):
    ed_tuple = []
    for method_name in methods_names_tuple:
        file_path = str(get_project_root().parent) + '/results/best/' + ed_name + method_name
        ed = read(file_path)
        ed_tuple.append(ed)

    return ed_tuple

Example #2

                        new_slice_sec[i][j] = [1/255, 215/255, 36/255]
                        #print('FP')
                    else:
                        new_slice_sec[i][j] = [1.0, 1.0, 1.0]


        axes[k // 2, k % 2].set_title(name_tuple[k])
        axes[k // 2, k % 2].imshow(new_slice_sec)

    for ax in fig.get_axes():
        ax.label_outer()
        # pyplot.subplot(2, 2, k + 1)
        # pyplot.imshow(new_slice_sec)


    pyplot.show()

    #pyplot.savefig(''.join(['../results/', name, '/', optName ,'.png']))


if __name__ == '__main__':

    file = EMD_2984
    ed_name = 'EMD-2984'
    true_buffer = np.fromfile(''.join([str(get_project_root().parent), '/results/golden/', ed_name + '_c']), dtype=bool)
    origin = ed_parser.read(str(get_project_root().parent) + file)
    origin.re_normalize()
    mf3d = ed_parser.read(str(get_project_root().parent) + '/results/best/' + ed_name +'_mf3d.ccp4')
    nlm3d = ed_parser.read(str(get_project_root().parent) + '/results/best/' + ed_name + '_nlm3d.ccp4')
    bm4d = ed_parser.read(str(get_project_root().parent) + '/results/best/' + ed_name + '_bm4d.ccp4')
    edplot2d(true_buffer, [origin, mf3d, nlm3d, bm4d])

Example #3

from scripts.ed_parser import read
from scripts import get_project_root
from scripts.ccp4_parser import to_ccp4_file
from scripts import edplot
import denoise_methods.BM3D as BMND
import numpy as np
from scenarios import EMD_2984, _4NRE, EMD_3061, EMD_6479

if __name__ == '__main__':
    file_names = [EMD_6479] #, file_name2]
    for name in file_names:
        file_path = str(get_project_root().parent) + name

        ed = read(file_path)

        ed.re_normalize()
        denoiser = BMND.BM3D(ed.values)
        denoise_data = denoiser.execute_2d()

        ed.update_from_values(denoise_data)
        ed.header.mean = np.mean(ed.buffer)
        ed.header.stddev = np.std(ed.buffer)
        ed.header.min = np.min(ed.buffer)
        ed.header.max = np.max(ed.buffer)

        ed.header.fields["amean"] = ed.header.mean
        ed.header.fields["amax"] = ed.header.max
        ed.header.fields["amin"] = ed.header.min
        ed.header.fields["sd"] = ed.header.stddev

        print(ed.header.min, ed.header.max, ed.header.mean, ed.header.stddev)

Example #4

import time
import denoise_methods.nl_means3d as nlm
import denoise_methods.BM4D as bm4d

from scripts.ed_parser import read
from scripts import get_project_root
from scenarios import EMD_2984, _4NRE, EMD_3061, EMD_6479

if __name__ == '__main__':
    file_path = str(get_project_root().parent) + EMD_2984
    ed = read(file_path)

    start = time.time()
    ed.re_normalize()
    ed.update_from_buffer(ed.buffer)
    denoiser = nlm.NLMeans(ed.values, 40)
    denoise_data = denoiser.execute_3d()

    finish = time.time()

    print('NL-means:' + str(finish - start))

    ed = read(file_path)

    start = time.time()
    ed.re_normalize()
    ed.update_from_buffer(ed.buffer)
    denoiser = bm4d.BM4D(ed.values, 40)
    denoise_data = denoiser.execute_3d()

    finish = time.time()

Example #5

#
# thr_main = ed.header.mean + 1.2 * ed.header.stddev
# thr_help = ed_help.header.mean + ed_help.header.stddev
#
# true_signal = np.zeros((ed.header.fields["NS"] * ed.header.fields["NR"] * ed.header.fields["NC"]), dtype=bool)
#
# n = len(ed.buffer)
#
# for i in range(n):
#     if ed.buffer[i] >= thr_main and ed_help.buffer[i] >= thr_help:
#         true_signal[i] = True
#
# true_signal.tofile('EMD-2984')


if __name__ == '__main__':

    name ='EMD-2984'
    ed = read(str(get_project_root().parent) + '/mol_data/ccp4/vv2.ccp4')

    ed.re_normalize()

    true_signal = np.zeros((ed.header.fields["NS"] * ed.header.fields["NR"] * ed.header.fields["NC"]), dtype=bool)

    n = len(ed.buffer)

    for i in range(n):
        if ed.buffer[i] > 0.0:
            true_signal[i] = True

    true_signal.tofile(str(get_project_root().parent) + '/results/golden/' + name)

Example #6

File: slice_plot_scenario.py Project: LesikDee/ED_Denoising

# Step 1. Read data
from scripts.ed_parser import read
from scripts import get_project_root
from scenarios import EMD_2984, _4NRE, EMD_3061, EMD_6479

ed = read(str(get_project_root().parent) + _4NRE)
ed.re_normalize()
#Step 3. Plot slice
from scripts.edplot import edplot2d
edplot2d(ed, optName='slice_color')

Example #7

from scripts import get_project_root
from scripts.ed_parser import read
from scripts.f_measure import make_f_measure_report
import numpy as np

bm3d_path = '_bm3d.ccp4'
mf2d_path = '_mf2d.ccp4'
nlm2d_path = '_nlm2d.ccp4'

bm4d_path = '_bm4d.ccp4'
mf3d_path = '_mf3d.ccp4'
nlm3d_path = '_nlm3d.ccp4'
origin = '_origin.ccp4'

def form_ed_tuple(ed_name, methods_names_tuple):
    ed_tuple = []
    for method_name in methods_names_tuple:
        file_path = str(get_project_root().parent) + '/results/best/' + ed_name + method_name
        ed = read(file_path)
        ed_tuple.append(ed)

    return ed_tuple

if __name__ == '__main__':
    ed_name = 'EMD-6479'
    true_buffer = np.fromfile(''.join([str(get_project_root().parent), '/results/golden/', ed_name, '_c']), dtype=bool)
    ed_tuple = form_ed_tuple(ed_name, [origin, mf3d_path, nlm3d_path, bm4d_path])

    make_f_measure_report(true_buffer, ed_tuple)