viz

Visulaization modules

---

plot_lines_with_param_color

def plot_lines_with_param_color(
    param_array:array=None, # parameter array
    x_array:array=None, # x-axis array
    y_array_all:array=None, # y-axis array
    title_str:str=None, # Title string
    xlabel_str:str=None, # x-label string
    ylabel_str:str=None, # y-label string
    param_name_str:str=None, # Parameter string,
    ax:Axes=None
):

Call self as a function.

---

plot_scatter_matrix

def plot_scatter_matrix(
    df:DataFrame=None, colors:str=None
):

Call self as a function.

---

plot_train_diagnostics

def plot_train_diagnostics(
    sepia_model:SepiaModel=None, # Input data in SEPIA format, after PCA
)->tuple: # Pair-plot and Trace-plot

Call self as a function.

---

sensitivity_plot

def sensitivity_plot(
    k_all:array=None, # all wavenumbers
    params_all:array=None, # all parameters
    sepia_model:SepiaModel=None, # SEPIA emulator model
    sepia_data:SepiaData=None, # Input data in SEPIA format
    emulator_function:NoneType=None, # function which takes in sepia model and parameters
    param_name:tuple=None, # Parameter name
    xy_lims:array=[0.02, 10.0, 0.98, 1.3]
):

Call self as a function.

---

validation_plot

def validation_plot(
    k_all:array=None, target_vals:array=None, pred_mean:array=None, pred_std:array=None,
    xy_lims:array=[0.02, 10.0, 0.98, 1.3]
):

Call self as a function.

---

plot_mcmc

def plot_mcmc(
    samples:array, params_list:list, if_truth_know:bool=False
):

Call self as a function.

# #| hide

# from getdist import plots, MCSamples
# import re

# def latex_to_plain(text):
#     # Replace LaTeX specific symbols
#     text = re.sub(r'\$', '', text)  # Remove $ signs
#     text = re.sub(r'\\', '', text)  # Remove backslashes
#     text = re.sub(r'\{|\}', '', text)  # Remove braces
#     return text


# def plot_mcmc_getdist(samples:np.array, 
#               params_list:list, 
#               if_truth_know:bool=False):


#     # from getdist.gaussian_mixtures import GaussianND
#     # mat = - h
#     # cov = np.linalg.pinv(mat)

#     # covariance = cov #[[0.001**2, 0.0006*0.05, 0], [0.0006*0.05, 0.05**2, 0.2**2], [0, 0.2**2, 2**2]]
#     # mean =np.array([para4[1], para5[1]]) #params #[0.02, 1, -2] 
#     # gauss=GaussianND(mean, covariance, names=['logfr0','n'], labels=[para4[0], para5[0]], label = 'Fisher')
#     # # g = plots.get_subplot_plotter()
#     # # g.triangle_plot(gauss,filled=True)

#     # names = ['a', 'b', 'c', 'd', 'e']
#     # s1 = samples_plot[samples_plot[:, 0] > -5.3]

#     s1 = samples
#     param_names = [param[0] for param in params_list]
#     PARAM_NAME_trial = np.array([latex_to_plain(item) for item in param_names]) #['Omega_m', 'n_s', '10^{9} A_s', 'h', 'f_\phi']

#     samples1 = MCSamples(samples=s1, 
#                         names=PARAM_NAME_trial, 
#                         labels=PARAM_NAME_trial, 
#                         label='MCMC' 
#                         )#, ranges={'logfr0':(-5.2, -4.8), 'n':(0.5, 1.5)})
#     g = plots.get_subplot_plotter(subplot_size=4)
#     g.settings.axes_fontsize=27
#     g.settings.axes_labelsize = 27
#     g.settings.legend_fontsize = 27
#     g.settings.fontsize = 27
#     g.settings.alpha_filled_add=0.6
#     # g.settings.title_limit_fontsize = 27
#     g.settings.solid_contour_palefactor = 0.5
#     g.triangle_plot([samples1],  
#                     # ['logfr0','n'], 
#                     filled=True, 
#                     # markers={'logfr0':para4[1], 'n':para5[1]}, 
#                     markers=[param[1] for param in params_list],
#                     marker_args={'lw':2, 'ls':'dashed', 'color':'k'}
#                     )

#     # g.triangle_plot([samples1, gauss],  ['logfr0','n'], filled=True, markers={'logfr0':para4[1], 'n':para5[1]}, marker_args={'lw':2, 'ls':'dashed', 'color':'k'})
#     # g.plot_contours(h, params, fill=True, alpha=0.5, label = 'Fisher info', facecolor = 'red')

#     # g.export('../../../Plots/triangle_plot.png')

---

generate_param_grid_with_fixed

def generate_param_grid_with_fixed(
    param_name:list=None, param_indices:array=None, fixed_params:array=None, param_min:array=None,
    param_max:array=None, steps:int=40
):

Call self as a function.

---

plot_error_heatmap

def plot_error_heatmap(
    errors:array=None, param_names:list=None, param_range:tuple=None
):

Call self as a function.