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calculation_functions.py
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import numpy as np
import pandas as pd
from streamlit import cache
###############################################################################
# ^Python standard line length
###############################################################################
#Friciton Force (Ff)
@cache
def friction_f(total_mass, friction_u):
Ff = total_mass/1000*9.81*friction_u
return Ff
#---------------------------------------
#Friction Coeffe (u)
@cache
def friction_u(friction_u):
return friction_u
###############################################################################
#Net force (Fnet)
@cache
def force_net(force, friction_force, drag_force):
Fnet = force - friction_force - drag_force
return Fnet
###############################################################################
#CO2 Mass [will be added to car mass which is give to us]
@cache
def co2_mass(co2_mass):
return co2_mass
###############################################################################
#Dataframe to Dva Dataframe
@cache(allow_output_mutation=True)# <-- idk why I need to put this do more research
def dataframe_to_dva(dataframe, car_mass, friction_u):
"""Returns a dva_dataframe ready for the dva to be calculated. It takes in all the
data from the inputed CSV file and outputs only Time, total mass, and Fnet over time
"""
#Get Total Mass
dataframe["Total Mass"] = dataframe["CO2 Mass (Mco2)"] + car_mass
#Get Friction_u (subject to change cause friction coeffe changes)
dataframe["Friction Coeffe (u)"] = friction_u
#Get Friction Force (Ff)
dataframe["Friction Force (Ff)"] = friction_f(dataframe["Total Mass"], dataframe["Friction Coeffe (u)"])
#Get Force net (Fnet)
dataframe["Fnet"] = force_net(dataframe["Force (N)"], dataframe["Friction Force (Ff)"], dataframe["Drag (FD)"])
#---------------------------------------
#dva Calculationsi
#Create DataFrame
dva_dataframe = dataframe[["Time (s)", "Total Mass", "Fnet"]]
#Replace all negative with 0 (for covinence at this moment)
dva_dataframe[dva_dataframe < 0] = 0
# Find where to start
for index,row in dva_dataframe.iterrows():
if row['Fnet'] > 0:
# row_above = dva_dataframe.iloc[[index-1]]
# row_above_diff = 0-row_above['Fnet']
# row_diff = 0-row['Fnet']
# if abs(row_above_diff) < abs(row_diff):
# dva_dataframe = dva_dataframe.iloc[index-1:]
# break
dva_dataframe = dva_dataframe.iloc[index:]
break
dva_dataframe = dva_dataframe.reset_index(drop=True)
return dva_dataframe
###############################################################################
#Calculate Continuous Time
@cache
def find_continuous_time(dva_dataframe):
sec = []
for index,row in dva_dataframe.iterrows(): # <- index is not being used which makes it waste memory but if remove index variable row is not created
first_row = dva_dataframe.iloc[[0]]
sec.append(row['Time (s)'] - first_row['Time (s)'])
df = pd.concat(sec).reset_index(drop=True)
dva_dataframe = pd.concat([dva_dataframe, df], axis=1)
# dva_dataframe = dva_dataframe.iloc[: , 1:]
dva_dataframe = dva_dataframe.set_axis([*dva_dataframe.columns[:-1], 'Continuous Time'], axis=1, inplace=False)
return dva_dataframe
###############################################################################
#Acceleration (a)
#---------------------------------------
#Speed Change (delta v) [Calculated using acceleration]
@cache
def cal_speed_change(dva_dataframe):
ser = pd.Series({0:0}, name='Speed Change (delta v)')
delta_v = []
for index, row in dva_dataframe.iterrows():
row_above = dva_dataframe.iloc[[index-1]]
if index == 0:
row_above['Acceleration (a)'] = 0
delta_v.append((row['Time (s)'] - row_above['Time (s)'])*(row_above['Acceleration (a)']+row['Acceleration (a)'])/2)
delta_v[0] = ser
df = pd.concat(delta_v).reset_index(drop=True)
dva_dataframe = pd.concat([dva_dataframe, df], axis=1)
dva_dataframe = dva_dataframe.set_axis([*dva_dataframe.columns[:-1], 'Speed Change (delta v)'], axis=1, inplace=False)
# dva_dataframe = dva_dataframe[:-1]
return dva_dataframe
###############################################################################
#Speed (v) [Calculated using delta v]
@cache
def cal_speed(dva_dataframe):
ser = pd.Series({0:0}, name='Speed (v)')
v = [ser]
for index, row in dva_dataframe.iterrows():
row_above = dva_dataframe.iloc[[index-1]]
v.append(v[-1]+row['Speed Change (delta v)'])
del v[0]
df = pd.concat(v).reset_index(drop=True)
dva_dataframe = pd.concat([dva_dataframe, df], axis=1)
dva_dataframe = dva_dataframe.set_axis([*dva_dataframe.columns[:-1], 'Speed (v)'], axis=1, inplace=False)
return dva_dataframe
#---------------------------------------
#distance change (delta d) [calculated using speed]
@cache
def cal_distance_change(dva_dataframe):
ser = pd.Series({0:0}, name='Distance Change (delta d)')
delta_d = []
for index, row in dva_dataframe.iterrows():
row_above = dva_dataframe.iloc[[index-1]]
delta_d.append((row['Time (s)'] - row_above['Time (s)'])*(row_above['Speed (v)']+row['Speed (v)'])/2)
delta_d[0] = ser
df = pd.concat(delta_d).reset_index(drop=True)
dva_dataframe = pd.concat([dva_dataframe, df], axis=1)
dva_dataframe = dva_dataframe.set_axis([*dva_dataframe.columns[:-1], 'Distance Change (delta d)'], axis=1, inplace=False)
return dva_dataframe
###############################################################################
#distance (d) [calculated using delta d]
@cache
def cal_distance(dva_dataframe):
ser = pd.Series({0:0}, name='Distance (d)')
d = [ser]
for index, row in dva_dataframe.iterrows():
row_above = dva_dataframe.iloc[[index-1]]
d.append(d[-1]+row['Distance Change (delta d)'])
del d[0]
df = pd.concat(d).reset_index(drop=True)
dva_dataframe = pd.concat([dva_dataframe, df], axis=1)
dva_dataframe = dva_dataframe.set_axis([*dva_dataframe.columns[:-1], 'Distance (d)'], axis=1, inplace=False)
return dva_dataframe
###############################################################################
#d-t, v-t, a-t calculator
def calculate_dva_t(dataframe):
"""This function calculates the v-t and a-t using the d-t table"""
# get differences for time values
count_t_vals = dataframe['time'].values
diffs_t = count_t_vals[:-1] - count_t_vals[1:]
# get differences for displacement values
count_d_vals = dataframe['displacement'].values
diffs_d = count_d_vals[:-1] - count_d_vals[1:]
# create velocity column and calculte it
velocity = diffs_d / diffs_t
dataframe['velocity']= np.insert(velocity,0,0)
# calculate difference in velocity
count_v_vals = dataframe['velocity'].values
diffs_v = count_v_vals[:-1] - count_v_vals[1:]
diffs_v=np.round(diffs_v,1)
# calculate accelertaion
accel= diffs_v / diffs_t
dataframe['acceleration']=np.append(accel,0)
return dataframe
###############################################################################