import pyslammer as slam
import numpy as np
import matplotlib.pyplot as plt
%matplotlib widget

histories = slam.sample_ground_motions()
ky_const = 0.15
motion = histories["Chi-Chi_1999_TCU068-090"]
# t_step = motion[0][1] - motion[0][0]
# input_acc = motion[1] / 9.80665
inputs = {
    "ky":ky_const,
    "a_in":motion.accel,
    "dt":motion.dt,
    "height":50.0,
    "vs_slope":600.0,
    "vs_base":600.0,
    "damp_ratio":0.05,
    "ref_strain":0.0005,
    "target_pga":0.6,
    "soil_model":"equivalent_linear"
}
da = slam.Decoupled(**inputs)
ca = slam.Coupled(**inputs)

ca.ground_acc

array([-0.00694238, -0.00641323, -0.00555932, ..., -0.00087741,
       -0.0012186 , -0.00133446], shape=(13102,))

da.ground_acc

array([-0.00694238, -0.00641323, -0.00555932, ..., -0.00087741,
       -0.0012186 , -0.00133446], shape=(13102,))

fig = ca.sliding_block_plot()

fig2 = da.sliding_block_plot()

#! python3


class WordListCollection:
    # this will be treated as a class variable
    List1 = []


    def __init__(self, list_in):
        # this will be treated as an instance variable
        self.List2 = list_in

    def AddWordsToList1(self, words):
        for word in words:
            self.List1.append(word)

    def AddWordsToList2(self, words):
        for word in words:
            self.List2.append(word)

asdf = ["a", "s", "d", "f"]
WLC1 = WordListCollection(asdf)
WLC1.Name = "WordListCollection1"
WLC1.AddWordsToList1(["apple", "pear", "banana"])
WLC1.AddWordsToList2(["Ford", "Chevy", "Dodge"])

WLC2 = WordListCollection(asdf)
WLC2.Name = "WordListCollection2"
WLC2.AddWordsToList1(["peach", "cherry", "apricot"])
WLC2.AddWordsToList2(["Mercury", "Pontiac", "Jeep"])


print(WLC1.Name)
print("List1", WLC1.List1)
print("List2", WLC1.List2)

print("")
print("--------------")
print("")

print(WLC2.Name)
print("List1", WLC2.List1)
print("List2", WLC2.List2)

WordListCollection1
List1 ['apple', 'pear', 'banana', 'peach', 'cherry', 'apricot']
List2 ['a', 's', 'd', 'f', 'Ford', 'Chevy', 'Dodge', 'Mercury', 'Pontiac', 'Jeep']

--------------

WordListCollection2
List1 ['apple', 'pear', 'banana', 'peach', 'cherry', 'apricot']
List2 ['a', 's', 'd', 'f', 'Ford', 'Chevy', 'Dodge', 'Mercury', 'Pontiac', 'Jeep']

import numpy as np


class MyClass:
    def __init__(self, data_array):
        self.data = data_array.copy()  # Create a copy of the input array

    def process_data(self):
        # Example: Calculate the mean of the array
        return np.mean(self.data)


# Example usage
my_array = np.array([1, 2, 3, 4, 5])
instance = MyClass(my_array)
mean_value = instance.process_data()

print(f"The mean of the array is: {mean_value}")

The mean of the array is: 3.0

second = MyClass(my_array)

second.data

array([1, 2, 3, 4, 5])

second.data *= -1

second.data

array([-1, -2, -3, -4, -5])

instance.data

array([1, 2, 3, 4, 5])