esta.plot package#

Submodules#

esta.plot.atomic_Distance_Density module#

esta.plot.atomic_distance_density_class2 module#

class esta.plot.atomic_distance_density_class2.atom_distance_density#

Bases: object

script to calculate the atomic distance density for a specific bond of atoms in the POSCAR file

The probability density for the Gaussian distribution is

p(x) =

rac{1}{sqrt{ 2 pi sigma^2 }} e^{ - rac{ (x - mu)^2 } {2 sigma^2} },

where mu is the mean and sigma the standard deviation. The square of the standard deviation, sigma^2, is called the variance.

The function has its peak at the mean, and its “spread” increases with the standard deviation (the function reaches 0.607 times its maximum at x + sigma and x - sigma [2]). This implies that numpy.random.normal is more likely to return samples lying close to the mean, rather than those far away.

x : ?

atomic distance density array and distance array are returned.

# See Also # ——– # add other related things here.

# Notes # —–

# Examples # ——–

distance_array(natom_type, tau_cartesian)#
dos(array_distribution, sigma)#

Now calculation of atomic distance density

gaussian_distribution(x0, x, sigma)#
remove_duplicate(list_entries)#

esta.plot.broken_axis_plot__most_done_only_axis_allignmnet_left module#

esta.plot.broken_axis_plot__most_done_only_axis_allignmnet_left.get_bader_data()#
esta.plot.broken_axis_plot__most_done_only_axis_allignmnet_left.get_broken_axis_plot(x, y, y_lim1, y_lim2, y_lim3, y_lim4)#

Broken axis example, where the y-axis will have a portion cut out.

x : x data y : y data y_lim1 = [0.78, 1] –> range of y aixs for outlier data y_lim2 = [0 ,0.22] –> range of y aixs for main part of the data

# for -ve y axis data … y_lim3 = [0.78, 1] –> range of y aixs for outlier data y_lim4 = [0 ,0.22] –> range of y aixs for main part of the data

plot : broken axis plot

esta.plot.charge_bader module#

esta.plot.free_energy_2 module#

class esta.plot.free_energy_2.GibbsFreeEnergy(Edft, S, temp)#

Bases: object

A class to calculate the Gibbs free enegy G = E -TS + E_ZPE

TODO:

  • Temp and pressure dependence free energy formula and

its implementation.

  • ZPE calculations

get_free_energy()#
Units:: EdfteV

S : eV/K

temp : K

esta.plot.multiplot module#

create a class to store the data from all the files containing the dos/pdos information .. along with the information of Fermi energy

class esta.plot.multiplot.DataStore(Fermi_energy, **file_names)#

Bases: object

store data from the dos/pdos *dat files having rows and columns

read_data(**file_names)#
esta.plot.multiplot.plot_multiplot_in_1column(data, hspace=None, outfile=None)#

multiplot in one column with nrows of data from many files < = 4files .. more possible

Parameters

  • data (array of rank 4) – array of rank 4 i.e. data(nsystem, nfiles, rnows, ncols) e.g. (5, 3, 5438, 2)

  • hspace (hspace in plots (optional)) – horizontal space between plots

Return type

plot the multiplot data in along multiple rows

esta.plot.plot2D module#

esta.plot.plot2D.contour_plot(x, y, fxy)#
input:

x: 1D array y: 1D array fxy: 2D array over a 2D grid defined by x and y

output:

surface plot save jpg file

esta.plot.plot2D.rosenbrock_2D(xpos, ypos)#

Rosenbrock function in 2D

esta.plot.plot2D.surface_plot(x, y, fxy)#

surface plot of a function in 2D

input:

x: 1D array y: 1D array fxy: 2D array over a 2D grid defined by x and y

output:

surface plot save jpg file

esta.plot.plot_2Ddata_NEB module#

method to plot the neb energy plots

esta.plot.plot_2Ddata_NEB.get_neb_plot(energy_list, index)#

method to plot the neb energy plots

input:

list of energy for images index for those energy points

output:

plot the barrier/energy plots

esta.plot.plot_2Ddata_NEB_adv module#

esta.plot.plot_2Ddata_NEB_adv.get_neb_plot(energy_list, index)#

method to plot the neb energy plots using spline interpolate or simple fitting …

input:

list of energy for images index for those energy points

output:

plot the barrier/energy plots

esta.plot.plot_bar_chart_bader module#

esta.plot.plot_free_energy_vs_reaction_coordinate_adv module#

esta.plot.plot_free_energy_vs_reaction_coordinate_adv.plot_free_energy(data)#
argument:
data: NxM array of free energies at different temperatures

N = no of temp values, M number of free energies for a given temp value.

Returns

plot the array of free energies as horizontal lines over the y axis

esta.plot.plot_pdos_Natoms_contribution_adv_both_spin_possible module#

esta.plot.plot_pdos_Natoms_contribution_adv_both_spin_possible.checkEqual_list(lst)#

comparing all the elements of list and return logical variable whether they are same or different

esta.plot.plot_pdos_Natoms_contribution_adv_both_spin_possible.get_fermi(filein)#
esta.plot.plot_pdos_Natoms_contribution_adv_both_spin_possible.get_fermi_from_dos(filedos)#
esta.plot.plot_pdos_Natoms_contribution_adv_both_spin_possible.get_pdos_files(atm_info)#

extract files based on the atomic number of atoms

atm_info: list of integers for atoms whose pdos is needed with all s,p,d…charaters

fileslist: list of all files whose pdos is needed

esta.plot.plot_pdos_Natoms_contribution_adv_both_spin_possible.get_plots(fileout, llabel, fil, refenergy=None, lspin=False)#

plot data in the form of single or multiple plots

Note

for multiple plots: try following

fig, (ax1, ax2, ax3) = plt.subplots(3, 1, sharex=True)

ax1.fill_between(x, 0, y1, facecolor=’yellow’, alpha=0.5)) ax1.set_ylabel(‘between y1 and 0’)

ax2.fill_between(x, y1, 1) ax2.set_ylabel(‘between y1 and 1’)

ax3.fill_between(x, y1, y2) ax3.set_ylabel(‘between y1 and y2’) ax3.set_xlabel(‘x’)

esta.plot.plot_pdos_Natoms_contribution_adv_both_spin_possible.get_plots1(filename, fileout, llabel, refenergy=None, lspin=False)#

plot data in the form of single or multiple plots

Note

for multiple plots: try following

fig, (ax1, ax2, ax3) = plt.subplots(3, 1, sharex=True)

ax1.fill_between(x, 0, y1, facecolor=’yellow’, alpha=0.5)) ax1.set_ylabel(‘between y1 and 0’)

ax2.fill_between(x, y1, 1) ax2.set_ylabel(‘between y1 and 1’)

ax3.fill_between(x, y1, y2) ax3.set_ylabel(‘between y1 and y2’) ax3.set_xlabel(‘x’)

esta.plot.plot_pdos_Natoms_contribution_adv_both_spin_possible.get_range_int_from_intervals(list_of_intervals)#

get range of integers from intervals (in the form of strings)

list of intervals: e.g. [‘1’,’2-4’,’6-10’] note that elements of list are strings

range of intervals: e.g. [1, 2, 3, 4, 6, 7, 8, 9, 10] note that elements are integers

esta.plot.plot_pdos_Natoms_contribution_adv_both_spin_possible.process_colums(filelist, lspin=None)#

  • summing the 2nd, and 3rd columns of the following multiple files and create new file with 0th column (from one file), 1st summed and 2nd summed columns from all files

filelist: list of all files whose columns hve to be processed

sum_data_file: file with resultant columns, data_array: array[:,:,0:3] data with processed columns

esta.plot.plot_pdos_with_atoms_contribution_2plots_qe module#

esta.plot.plot_pdos_with_atoms_contribution_2plots_qe.checkEqual_list(lst)#

comparing all the elements of list and return logical variable whether they are same or different

esta.plot.plot_pdos_with_atoms_contribution_2plots_qe.get_fermi(filein)#
esta.plot.plot_pdos_with_atoms_contribution_2plots_qe.get_fermi_from_dos(filedos)#
esta.plot.plot_pdos_with_atoms_contribution_2plots_qe.get_pdos_files(atm_info)#

extract files based on the atomic number of atoms

atm_info: list of integers for atoms whose pdos is needed with all s,p,d…charaters

fileslist: list of all files whose pdos is needed

esta.plot.plot_pdos_with_atoms_contribution_2plots_qe.get_plots(fileout, llabel, fil, refenergy=None, lspin=False)#

plot data in the form of single or multiple plots

Note

for multiple plots: try following

fig, (ax1, ax2, ax3) = plt.subplots(3, 1, sharex=True)

ax1.fill_between(x, 0, y1, facecolor=’yellow’, alpha=0.5)) ax1.set_ylabel(‘between y1 and 0’)

ax2.fill_between(x, y1, 1) ax2.set_ylabel(‘between y1 and 1’)

ax3.fill_between(x, y1, y2) ax3.set_ylabel(‘between y1 and y2’) ax3.set_xlabel(‘x’)

esta.plot.plot_pdos_with_atoms_contribution_2plots_qe.get_plots1(filename, fileout, llabel, refenergy=None, lspin=False)#

plot data in the form of single or multiple plots

Note

for multiple plots: try following

fig, (ax1, ax2, ax3) = plt.subplots(3, 1, sharex=True)

ax1.fill_between(x, 0, y1, facecolor=’yellow’, alpha=0.5)) ax1.set_ylabel(‘between y1 and 0’)

ax2.fill_between(x, y1, 1) ax2.set_ylabel(‘between y1 and 1’)

ax3.fill_between(x, y1, y2) ax3.set_ylabel(‘between y1 and y2’) ax3.set_xlabel(‘x’)

esta.plot.plot_pdos_with_atoms_contribution_2plots_qe.get_range_int_from_intervals(list_of_intervals)#

get range of integers from intervals (in the form of strings)

list of intervals: e.g. [‘1’,’2-4’,’6-10’] note that elements of list are strings

range of intervals: e.g. [1, 2, 3, 4, 6, 7, 8, 9, 10] note that elements are integers

esta.plot.plot_pdos_with_atoms_contribution_2plots_qe.process_colums(filelist)#

  • summing the 2nd, and 3rd columns of the following multiple files and create new file with 0th column (from one file), 1st summed and 2nd summed columns from all files

filelist: list of all files whose columns hve to be processed

sum_data_file: file with resultant columns, data_array: array[:,:,0:3] data with processed columns

esta.plot.plot_xanes_ module#

esta.plot.plot_xanes_.get_fermi(filein)#
esta.plot.plot_xanes_.get_plots(filename, fileout, refenergy=None)#

plot data in the form of single or multiple plots

esta.plot.plotxy module#

esta.plot.plotxy.get_plot(*args, markersize=None, xLabel=None, yLabel=None, Title=None, fileout=None)#

plot data in the form of single or multiple plots

Parameters

  • args (keyword argumets) – args contains x, y, marker, linestyle, and color; marker, linestyle and color are optional

  • markersize (scalar) – size of marker, optional

  • xLabel (str) – x label, optional

  • yLabel (str) – y label, optional

  • Title (str) – Title, optional

  • fileout (str, optional) – name of the output file

Return type

fileout.png file as output

esta.plot.plotxy.get_plot1(*args, markersize=None, xLabel=None, yLabel=None, Title=None, fileout=None)#

plot data in the form of single or multiple plots

esta.plot.plotxy.get_plot_multiple(*args, ylimits=None, markersize=None, llegend=None, xLabel=None, yLabel=None, Title=None, fileout=None)#

plot multiple data in a single plot by making multiple calls to this method

Parameters

  • args (keyword argumets) – args contains x, y, marker, linestyle, and color; marker, linestyle, and color are optional and for single plot only

  • ylimits (list) – scalars for min and max y limits, optional, but better input the limits

  • markersize (scalar) – size of marker, optional

  • llegend (list) – a list of labels for the legends, optional

  • xLabel (str) – x label, optional

  • yLabel (str) – y label, optional

  • Title (str) – Title, optional

  • fileout (str, optional) – name of the output file

Return type

fileout.png file as output

esta.plot.plotxy0 module#

esta.plot.plotxy0.get_plot(x, y, xLabel, yLabel, Title=None, fileout=None)#

plot data in the form of single or multiple plots

esta.plot.plotxy1 module#

esta.plot.plotxy1.get_plot(x, y, marker=None, markersize=None, xLabel=None, yLabel=None, Title=None, fileout=None)#

plot data in the form of single or multiple plots

esta.plot.plotxy_adv module#

esta.plot.plotxy_adv.get_plot(x, y, marker=None, markersize=None, xLabel=None, yLabel=None, Title=None, fileout=None)#

plot data in the form of single or multiple plots

esta.plot.plotxy_advv module#

esta.plot.plotxy_advv.get_plot(*args, markersize=None, xLabel=None, yLabel=None, Title=None, fileout=None)#

plot data in the form of single or multiple plots

Parameters

  • args (keyword argumets) – args contains x, y, marker, linestyle, and color; marker, linestyle and color are optional

  • markersize (scalar) – size of marker, optional

  • xLabel (str) – x label, optional

  • yLabel (str) – y label, optional

  • Title (str) – Title, optional

  • fileout (str, optional) – name of the output file

Return type

fileout.png file as output

esta.plot.plotxy_advv.get_plot1(*args, markersize=None, xLabel=None, yLabel=None, Title=None, fileout=None)#

plot data in the form of single or multiple plots

esta.plot.plotxy_advv.get_plot_multiple(*args, ylimits=None, markersize=None, llegend=None, xLabel=None, yLabel=None, Title=None, fileout=None)#

plot multiple data in a single plot by making multiple calls to this method

Parameters

  • args (keyword argumets) – args contains x, y, marker, linestyle, and color; marker, linestyle, and color are optional and for single plot only

  • ylimits (list) – scalars for min and max y limits, optional, but better input the limits

  • markersize (scalar) – size of marker, optional

  • llegend (list) – a list of labels for the legends, optional

  • xLabel (str) – x label, optional

  • yLabel (str) – y label, optional

  • Title (str) – Title, optional

  • fileout (str, optional) – name of the output file

Return type

fileout.png file as output

esta.plot.polar_plot module#

esta.plot.polar_plot.plot_polar()#

esta.plot.tex_demo module#

Rendering math equations using TeX#

You can use TeX to render all of your Matplotlib text by setting :rc:`text.usetex` to True. This requires that you have TeX and the other dependencies described in the /tutorials/text/usetex tutorial properly installed on your system. Matplotlib caches processed TeX expressions, so that only the first occurrence of an expression triggers a TeX compilation. Later occurrences reuse the rendered image from the cache and are thus faster.

Unicode input is supported, e.g. for the y-axis label in this example.

Module contents#