<commit_before>import matplotlib.pyplot as plt
import peakutils as pku
from lmfit import Parameters
from ResoFit._utilities import Experiment
from ResoFit._utilities import Simulation
import numpy as np
from scipy.interpolate import interp1d

# Global parameters
energy_min = 7
energy_max = 100
energy_step = 0.001
# Input sample name or names as str, case sensitive
_layer_1 = 'Gd'
_thickness_1 = 0.075  # mm
mass = 0.36  # gram
length = 25
width = 25
height = 0.075
mm3_to_cm3 = 0.001
density = mass / (length * width * height * mm3_to_cm3)
_density_1 = np.NaN

# Ideal
simulation = Simulation(layer_1=_layer_1,
                        thickness_1=_thickness_1,
                        density_1=np.NaN,
                        energy_min=energy_min,
                        energy_max=energy_max,
                        energy_step=energy_step)
simu_x = simulation.x()<commit_msg>calibrate script fixed.<commit_after>import matplotlib.pyplot as plt
import peakutils as pku
from lmfit import Parameters
from ResoFit._utilities import Experiment
from ResoFit._utilities import Simulation
import numpy as np

# Global parameters
energy_min = 7
energy_max = 100
energy_step = 0.001
# Input sample name or names as str, case sensitive
_layer_1 = 'Gd'
_thickness_1 = 0.075  # mm
mass = 0.36  # gram
length = 25
width = 25
height = 0.075
mm3_to_cm3 = 0.001
density = mass / (length * width * height * mm3_to_cm3)
_density_1 = np.NaN

# Ideal
simulation = Simulation(layer_1=_layer_1,
                        thickness_1=_thickness_1,
                        density_1=np.NaN,
                        energy_min=energy_min,
                        energy_max=energy_max,
                        energy_step=energy_step)
simu_x = simulation.x()
{'fraction_non_alphanumeric': 0.06670500287521564, 'fraction_numerical': 0.04542840713053479, 'mean_word_length': 2.663157894736842, 'pattern_counts': {'":': 0, '<': 3, '<?xml version=': 0, '>': 3, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'dir': 'git-commits-cleaned', 'id': '1760153', 'n_tokens_mistral': 607, 'n_tokens_neox': 550, 'n_words': 155}