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comparison_app.py
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comparison_app.py
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# -*- coding: utf-8 -*-
import dash
import dash_core_components as dcc
import dash_html_components as html
from dash.dependencies import Input, Output
import dash_table_experiments as dt
from plotly import tools
import plotly.plotly as py
import plotly.graph_objs as go
import numpy as np
import flask
import math
import base64
from io import StringIO
import sys
import os.path
import orbitdeterminator.kep_determination.ellipse_fit as e_fit
import orbitdeterminator.util.anom_conv as anom_conv
import orbitdeterminator.util.teme_to_ecef as teme_to_ecef
import orbitdeterminator.util.read_data
import orbitdeterminator.util.kep_state
import orbitdeterminator.util.rkf78
import orbitdeterminator.util.golay_window as golay_window
import orbitdeterminator.filters.sav_golay as sav_golay
import orbitdeterminator.filters.triple_moving_average as triple_moving_average
import orbitdeterminator.kep_determination.lamberts_kalman as lamberts_kalman
import orbitdeterminator.kep_determination.interpolation as interpolation
import orbitdeterminator.kep_determination.gibbsMethod as gibbsMethod
import argparse
import matplotlib as mpl
import matplotlib.pylab as plt
app = dash.Dash()
app.title = 'Orbit Determinator'
# setup static folder
STATIC_PATH = os.path.abspath(os.path.join(os.path.dirname(__file__), 'static'))
@app.server.route('/static/<resource>')
def serve_static(resource):
return flask.send_from_directory(STATIC_PATH, resource)
app.css.append_css({'external_url': '/static/style.css'})
app.layout = html.Div(children=[
html.Img(src='/static/logo.png',id='logo'),
html.H1(children='Orbit Determinator'),
html.Div('''
Orbit Determinator: A python package to predict satellite orbits.''',id='subtitle'),
# html.Div(['''
# Select mode:'''], style={'fontSize': 22,'marginBottom':7},id='subtitle_mode_selection'),
# dcc.Link('Switch to normal mode', href='/app.py'),
# html.Br(),
#html.Div([''' ''']),
#html.Div([''' '''],style={'display': 'inline-block'}),
#html.Div([''' ''']),
html.Div(['''
Choose appropriate unit according to .csv file you are going to upload:'''], style={'fontSize': 22,'marginBottom':7},id='unit-selection'),
html.Div(
dcc.Dropdown(
id='my-dropdown',
options=[
{'label': 'Kilometers(km)', 'value': '(km)'},
{'label': 'Metres(m)', 'value': '(m)'},
],
value='(km)'
)
,style={'width': 250, 'display': 'inline-block', 'fontSize': 18}),
html.Div([''' ''']),
html.Div([''' '''],style={'display': 'inline-block'}),
html.Div([''' ''']),
html.Div(['''
Select filter(for pre-processing):'''], style={'fontSize': 22,'marginBottom':7,'display': 'inline-block'},id='filter-selection'),
html.Div(['''
Select method for keplerian determination:'''], style={'fontSize': 22,'marginBottom':7,'display': 'inline-block','marginLeft':97},id='method-selection'),
html.Div([''' ''']),
html.Div(
dcc.Dropdown(
id='my-dropdown2',
options=[
{'label': 'Savintzky Golay', 'value': '(sg)'},
{'label': 'Triple moving average', 'value': '(tma)'},
{'label': 'Both', 'value': '(bo)'},
{'label': 'None', 'value': '(nf)'},
],
value='(sg)'
)
,style={'width': 250, 'display': 'inline-block', 'fontSize': 18}),
html.Div(
dcc.Dropdown(
id='my-dropdown3',
options=[
{'label': 'Ellipse Fit', 'value': '(ef)'},
{'label': 'Gibbs Method', 'value': '(gm)'},
{'label': 'Cubic Spline Interpolation', 'value': '(in)'},
{'label': 'Lamberts Kalman', 'value': '(lk)'}
],
value='(ef)'
)
,style={'width': 350, 'display': 'inline-block','marginLeft': 132, 'fontSize': 18}),
html.Div([''' ''']),
html.Div([''' '''],style={'display': 'inline-block'}),
html.Div([''' ''']),
html.Div([''' '''],style={'display': 'inline-block'}),
html.Div([''' ''']),
#html.Div(['''
# Input data-- Filter-- Method for keplerian determination-- Orbit of the satellite'''], style={'fontSize': 26,'marginBottom':7,'display': 'inline-block','marginLeft':470},id='filter-selection'),
#html.Div([''' ''']),
html.Div(['''
Select filter(for pre-processing):'''], style={'fontSize': 22,'marginBottom':7,'display': 'inline-block'},id='filter-selection_'),
html.Div(['''
Select method for keplerian determination:'''], style={'fontSize': 22,'marginBottom':7,'display': 'inline-block','marginLeft':97},id='method-selection_'),
html.Div([''' ''']),
html.Div(
dcc.Dropdown(
id='my-dropdown2_',
options=[
{'label': 'Savintzky Golay', 'value': '(sg)'},
{'label': 'Triple moving average', 'value': '(tma)'},
{'label': 'Both', 'value': '(bo)'},
{'label': 'None', 'value': '(nf)'},
],
value='(sg)'
)
,style={'width': 250, 'display': 'inline-block', 'fontSize': 18}),
html.Div(
dcc.Dropdown(
id='my-dropdown3_',
options=[
{'label': 'Ellipse Fit', 'value': '(ef)'},
{'label': 'Gibbs Method', 'value': '(gm)'},
{'label': 'Cubic Spline Interpolation', 'value': '(in)'},
{'label': 'Lamberts Kalman', 'value': '(lk)'}
],
value='(ef)'
)
,style={'width': 350, 'display': 'inline-block','marginLeft': 132, 'fontSize': 18}),
html.Div([''' ''']),
html.Div([''' '''],style={'display': 'inline-block'}),
html.Div([''' ''']),
html.Div([''' '''],style={'display': 'inline-block'}),
html.Div([''' ''']),
####
html.Div(id='output-container',style={'fontSize': 0,'marginBottom':15}),
html.Div(['''Upload a csv file below:'''], style={'fontSize': 22,'marginBottom': 10, 'marginTop': 30}),
html.Div(id='upload-box',
children=dcc.Upload(id='file-upload',
children=html.Div([
'Drag and Drop or ',
html.A('click to select a file')
]),
multiple=False)),
html.Div(id='output-div',children=[dt.DataTable(rows=[{}])])
])
@app.callback(
dash.dependencies.Output('output-container', 'children'),
[dash.dependencies.Input('my-dropdown', 'value')])
def update_output(value):
return '- You have selected "{}" as unit of length.'.format(value)
def parse_file(file_content):
try:
file_content = file_content.split(',')[1]
decoded = base64.b64decode(file_content).decode('ascii')
data = np.loadtxt(StringIO(decoded),skiprows=1)
assert(data.shape[1] == 4)
return data
except Exception as e:
print(e)
return np.empty((0,4))
def gen_sphere():
RADIUS = 6371
u, v = np.mgrid[0:2*np.pi:20j, 0:np.pi/2:10j]
x = (RADIUS*np.cos(u)*np.sin(v)).flatten()
y = (RADIUS*np.sin(u)*np.sin(v)).flatten()
z = (RADIUS*np.cos(v)).flatten()
return x,y,z
def ground_track(kep,time0):
a = kep[0]
e = kep[1]
inc = math.radians(kep[2])
t0 = math.radians(kep[3])
lan = math.radians(kep[4])
tanom = math.radians(kep[5])
p_x = np.array([math.cos(lan), math.sin(lan), 0])
p_y = np.array([-math.sin(lan)*math.cos(inc), math.cos(lan)*math.cos(inc), math.sin(inc)])
# generate 2000 points on the ellipse
theta = np.linspace(t0+tanom,t0+tanom+4*math.pi,2000)
radii = a*(1-e**2)/(1+e*np.cos(theta-t0))
# convert to cartesian
x_s = np.multiply(radii,np.cos(theta))
y_s = np.multiply(radii,np.sin(theta))
# convert to 3D
mat = np.column_stack((p_x,p_y))
coords_3D = np.matmul(mat,[x_s,y_s])
ecc = anom_conv.true_to_ecc(theta,e)
mean = anom_conv.ecc_to_mean(ecc,e)
times = anom_conv.mean_to_t(mean,a)
times += time0
coords_teme = np.column_stack((times,coords_3D[0],coords_3D[1],coords_3D[2]))
coords_ecef = teme_to_ecef.conv_to_ecef(coords_teme)
return coords_ecef,times
@app.callback(Output('output-div','children'),
[Input('file-upload','contents'),
Input('file-upload','filename'),
Input('my-dropdown', 'value'),
Input('my-dropdown2','value'),
Input('my-dropdown3','value'),
Input('my-dropdown2_','value'),
Input('my-dropdown3_','value')])
def display_file(file_content, file_name, dropdown_value,dropdown_value_2,dropdown_value_3,dropdown_value_2_,dropdown_value_3_):
if file_content is None:
return html.Div(['Choose a file to process it.'])
data_ini = parse_file(file_content)
if('{}'.format(dropdown_value_2)=='(sg)'):
window = golay_window.window(10.0, data_ini)
# Apply the Savintzky - Golay filter with window = 31 and polynomial parameter = 6
data = sav_golay.golay(data_ini, 31, 6)
res = data[:, 1:4] - data_ini[:, 1:4]
elif('{}'.format(dropdown_value_2)=='(tma)'):
data = triple_moving_average.generate_filtered_data(data_ini, 3)
res = data[:, 1:4] - data_ini[:, 1:4]
elif('{}'.format(dropdown_value_2)=='(bo)'):
data= sav_golay.golay(data_ini, 31, 6)
data = triple_moving_average.generate_filtered_data(data, 3)
res = data[:, 1:4] - data_ini[:, 1:4]
elif('{}'.format(dropdown_value_2)=='(nf)'):
data=data_ini
res = data[:, 1:4] - data_ini[:, 1:4]
#else:
#data=data_ini
####
if('{}'.format(dropdown_value_2_)=='(sg)'):
window = golay_window.window(10.0, data_ini)
# Apply the Savintzky - Golay filter with window = 31 and polynomial parameter = 6
data1 = sav_golay.golay(data_ini, 31, 6)
res1 = data1[:, 1:4] - data_ini[:, 1:4]
elif('{}'.format(dropdown_value_2_)=='(tma)'):
data1 = triple_moving_average.generate_filtered_data(data_ini, 3)
res1 = data1[:, 1:4] - data_ini[:, 1:4]
elif('{}'.format(dropdown_value_2_)=='(bo)'):
data1= sav_golay.golay(data_ini, 31, 6)
data1 = triple_moving_average.generate_filtered_data(data1, 3)
res1 = data1[:, 1:4] - data_ini[:, 1:4]
elif('{}'.format(dropdown_value_2_)=='(nf)'):
data1=data_ini
res1 = data1[:, 1:4] - data_ini[:, 1:4]
####
if (data.shape[0] > 0):
data_dict = [{'No.':'{:03d}'.format(i+1), 't (s)':data[i][0], 'x '+'{}'.format(dropdown_value):data[i][1], 'y '+'{}'.format(dropdown_value):data[i][2], 'z '+'{}'.format(dropdown_value):data[i][3]} for i in range(data.shape[0])]
####
if (data1.shape[0] > 0):
data_dict1 = [{'No.':'{:03d}'.format(i+1), 't (s)':data1[i][0], 'x '+'{}'.format(dropdown_value):data1[i][1], 'y '+'{}'.format(dropdown_value):data1[i][2], 'z '+'{}'.format(dropdown_value):data1[i][3]} for i in range(data1.shape[0])]
####
if('{}'.format(dropdown_value_3)=='(ef)'):
kep, res = e_fit.determine_kep(data[:,1:])
elif('{}'.format(dropdown_value_3)=='(gm)'):
# Apply gibbs method
kep_gibbs = gibbsMethod.gibbs_get_kep(data[:,1:])
kep_final_gibbs = lamberts_kalman.kalman(kep_gibbs, 0.01 ** 2)
kep_final_gibbs = np.transpose(kep_final_gibbs)
kep = np.resize(kep_final_gibbs, ((7, 1)))
elif('{}'.format(dropdown_value_3)=='(in)'):
# Apply the interpolation method
kep_inter = interpolation.main(data)
# Apply Kalman filters, estimate of measurement variance R = 0.01 ** 2
kep_final_inter = lamberts_kalman.kalman(kep_inter, 0.01 ** 2)
kep = np.transpose(kep_final_inter)
kep = np.resize(kep, ((7, 1)))
elif('{}'.format(dropdown_value_3)=='(lk)'):
# Apply Lambert's solution for the filtered data set
kep_lamb = lamberts_kalman.create_kep(data)
# Apply Kalman filters, estimate of measurement variance R = 0.01 ** 2
kep_final_lamb = lamberts_kalman.kalman(kep_lamb, 0.01 ** 2)
kep = np.transpose(kep_final_lamb)
kep = np.resize(kep, ((7, 1)))
####
if('{}'.format(dropdown_value_3_)=='(ef)'):
kep1, res1 = e_fit.determine_kep(data1[:,1:])
elif('{}'.format(dropdown_value_3_)=='(gm)'):
# Apply gibbs method
kep_gibbs1 = gibbsMethod.gibbs_get_kep(data1[:,1:])
kep_final_gibbs1 = lamberts_kalman.kalman(kep_gibbs1, 0.01 ** 2)
kep_final_gibbs1 = np.transpose(kep_final_gibbs1)
kep1 = np.resize(kep_final_gibbs1, ((7, 1)))
elif('{}'.format(dropdown_value_3_)=='(in)'):
# Apply the interpolation method
kep_inter1 = interpolation.main(data1)
# Apply Kalman filters, estimate of measurement variance R = 0.01 ** 2
kep_final_inter1 = lamberts_kalman.kalman(kep_inter1, 0.01 ** 2)
kep1 = np.transpose(kep_final_inter1)
kep1 = np.resize(kep1, ((7, 1)))
elif('{}'.format(dropdown_value_3_)=='(lk)'):
# Apply Lambert's solution for the filtered data set
kep_lamb1 = lamberts_kalman.create_kep(data1)
# Apply Kalman filters, estimate of measurement variance R = 0.01 ** 2
kep_final_lamb1 = lamberts_kalman.kalman(kep_lamb1, 0.01 ** 2)
kep1 = np.transpose(kep_final_lamb1)
kep1 = np.resize(kep1, ((7, 1)))
####
# Visuals
orbit_points = data[:,1:]+res
earth_points = gen_sphere()
xyz_org = go.Scatter3d(
name = 'Original Data',
legendgroup = 'org',
showlegend = False,
x = data[:,1],
y = data[:,2],
z = data[:,3],
mode = 'markers',
marker = {'size': 1, 'color':'black'}
)
xyz_fit = go.Scatter3d(
name = 'Fitted Ellipse',
legendgroup = 'fit',
showlegend = False,
x = orbit_points[:,0],
y = orbit_points[:,1],
z = orbit_points[:,2],
mode = 'lines',
line = {'width':5, 'color':'red'}
)
xyz_cur = go.Scatter3d(
name = 'Position at Epoch',
legendgroup = 'cur',
showlegend = False,
x = [orbit_points[0,0]],
y = [orbit_points[0,1]],
z = [orbit_points[0,2]],
mode = 'markers',
marker = {'size':3, 'color': 'blue'}
)
earth_top = go.Mesh3d(
x = earth_points[0],
y = earth_points[1],
z = earth_points[2],
color = '#1f77b4',
opacity = 0.5,
hoverinfo = 'skip',
showlegend = False
)
earth_bottom = go.Mesh3d(
x = earth_points[0],
y = earth_points[1],
z = -earth_points[2],
color = '#1f77b4',
opacity = 0.5,
hoverinfo = 'skip',
showlegend = False
)
xy_org = go.Scatter(
name = 'Original Data',
legendgroup = 'org',
showlegend = True,
x = data[:,1],
y = data[:,2],
mode = 'markers',
marker = {'size': 5, 'color':'black'}
)
xy_fit = go.Scatter(
name = 'Fitted Ellipse',
legendgroup = 'fit',
showlegend = True,
x = orbit_points[:,0],
y = orbit_points[:,1],
mode = 'lines',
line = {'width':2, 'color':'red'}
)
xy_cur = go.Scatter(
name = 'Position at Epoch',
legendgroup = 'cur',
showlegend = True,
x = [orbit_points[0,0]],
y = [orbit_points[0,1]],
mode = 'markers',
marker = {'size':10, 'color':'blue'}
)
yz_org = go.Scatter(
name = 'Original Data',
legendgroup = 'org',
showlegend = False,
x = data[:,2],
y = data[:,3],
mode = 'markers',
marker = {'size': 5, 'color':'black'}
)
yz_fit = go.Scatter(
name = 'Fitted Ellipse',
legendgroup = 'fit',
showlegend = False,
x = orbit_points[:,1],
y = orbit_points[:,2],
mode = 'lines',
line = {'width':2, 'color':'red'}
)
yz_cur = go.Scatter(
name = 'Position at Epoch',
legendgroup = 'cur',
showlegend = False,
x = [orbit_points[0,1]],
y = [orbit_points[0,2]],
mode = 'markers',
marker = {'size':10, 'color':'blue'}
)
xz_org = go.Scatter(
name = 'Original Data',
legendgroup = 'org',
showlegend = False,
x = data[:,1],
y = data[:,3],
mode = 'markers',
marker = {'size': 5, 'color':'black'}
)
xz_fit = go.Scatter(
name = 'Fitted Ellipse',
legendgroup = 'fit',
showlegend = False,
x = orbit_points[:,0],
y = orbit_points[:,2],
mode = 'lines',
line = {'width':2, 'color':'red'}
)
xz_cur = go.Scatter(
name = 'Position at Epoch',
legendgroup = 'cur',
showlegend = False,
x = [orbit_points[0,0]],
y = [orbit_points[0,2]],
mode = 'markers',
marker = {'size':10, 'color':'blue'}
)
xyz_fig = tools.make_subplots(rows=2,cols=2,specs=[[{},{}],
[{},{'is_3d':True}]])
xyz_fig.append_trace(xz_org,1,1)
xyz_fig.append_trace(xz_fit,1,1)
xyz_fig.append_trace(xz_cur,1,1)
xyz_fig.append_trace(yz_org,1,2)
xyz_fig.append_trace(yz_fit,1,2)
xyz_fig.append_trace(yz_cur,1,2)
xyz_fig.append_trace(xy_org,2,1)
xyz_fig.append_trace(xy_fit,2,1)
xyz_fig.append_trace(xy_cur,2,1)
xyz_fig.append_trace(xyz_org,2,2)
xyz_fig.append_trace(xyz_fit,2,2)
xyz_fig.append_trace(xyz_cur,2,2)
xyz_fig.append_trace(earth_top,2,2)
xyz_fig.append_trace(earth_bottom,2,2)
xyz_fig['layout']['xaxis1'].update(title='x '+'{}'.format(dropdown_value))
xyz_fig['layout']['yaxis1'].update(title='z '+'{}'.format(dropdown_value), scaleanchor='x')
xyz_fig['layout']['xaxis2'].update(title='y '+'{}'.format(dropdown_value), scaleanchor='x')
xyz_fig['layout']['yaxis2'].update(title='z '+'{}'.format(dropdown_value), scaleanchor='x2')
xyz_fig['layout']['xaxis3'].update(title='x '+'{}'.format(dropdown_value), scaleanchor='x')
xyz_fig['layout']['yaxis3'].update(title='y '+'{}'.format(dropdown_value), scaleanchor='x3')
xyz_fig['layout']['scene1']['xaxis'].update(showticklabels=True, showspikes=False, title='x '+'{}'.format(dropdown_value))
xyz_fig['layout']['scene1']['yaxis'].update(showticklabels=True, showspikes=False, title='y '+'{}'.format(dropdown_value))
xyz_fig['layout']['scene1']['zaxis'].update(showticklabels=True, showspikes=False, title='z '+'{}'.format(dropdown_value))
xyz_fig['layout'].update(width=1050, height=700, margin={'t':50})
xyz_fig['layout']['legend'].update(orientation='h')
###
orbit_points = data1[:,1:]+res1
earth_points = gen_sphere()
xyz_org = go.Scatter3d(
name = 'Original Data',
legendgroup = 'org',
showlegend = False,
x = data1[:,1],
y = data1[:,2],
z = data1[:,3],
mode = 'markers',
marker = {'size': 1, 'color':'black'}
)
xyz_fit = go.Scatter3d(
name = 'Fitted Ellipse',
legendgroup = 'fit',
showlegend = False,
x = orbit_points[:,0],
y = orbit_points[:,1],
z = orbit_points[:,2],
mode = 'lines',
line = {'width':5, 'color':'red'}
)
xyz_cur = go.Scatter3d(
name = 'Position at Epoch',
legendgroup = 'cur',
showlegend = False,
x = [orbit_points[0,0]],
y = [orbit_points[0,1]],
z = [orbit_points[0,2]],
mode = 'markers',
marker = {'size':3, 'color': 'blue'}
)
earth_top = go.Mesh3d(
x = earth_points[0],
y = earth_points[1],
z = earth_points[2],
color = '#1f77b4',
opacity = 0.5,
hoverinfo = 'skip',
showlegend = False
)
earth_bottom = go.Mesh3d(
x = earth_points[0],
y = earth_points[1],
z = -earth_points[2],
color = '#1f77b4',
opacity = 0.5,
hoverinfo = 'skip',
showlegend = False
)
xy_org = go.Scatter(
name = 'Original Data',
legendgroup = 'org',
showlegend = True,
x = data[:,1],
y = data[:,2],
mode = 'markers',
marker = {'size': 5, 'color':'black'}
)
xy_fit = go.Scatter(
name = 'Fitted Ellipse',
legendgroup = 'fit',
showlegend = True,
x = orbit_points[:,0],
y = orbit_points[:,1],
mode = 'lines',
line = {'width':2, 'color':'red'}
)
xy_cur = go.Scatter(
name = 'Position at Epoch',
legendgroup = 'cur',
showlegend = True,
x = [orbit_points[0,0]],
y = [orbit_points[0,1]],
mode = 'markers',
marker = {'size':10, 'color':'blue'}
)
yz_org = go.Scatter(
name = 'Original Data',
legendgroup = 'org',
showlegend = False,
x = data[:,2],
y = data[:,3],
mode = 'markers',
marker = {'size': 5, 'color':'black'}
)
yz_fit = go.Scatter(
name = 'Fitted Ellipse',
legendgroup = 'fit',
showlegend = False,
x = orbit_points[:,1],
y = orbit_points[:,2],
mode = 'lines',
line = {'width':2, 'color':'red'}
)
yz_cur = go.Scatter(
name = 'Position at Epoch',
legendgroup = 'cur',
showlegend = False,
x = [orbit_points[0,1]],
y = [orbit_points[0,2]],
mode = 'markers',
marker = {'size':10, 'color':'blue'}
)
xz_org = go.Scatter(
name = 'Original Data',
legendgroup = 'org',
showlegend = False,
x = data[:,1],
y = data[:,3],
mode = 'markers',
marker = {'size': 5, 'color':'black'}
)
xz_fit = go.Scatter(
name = 'Fitted Ellipse',
legendgroup = 'fit',
showlegend = False,
x = orbit_points[:,0],
y = orbit_points[:,2],
mode = 'lines',
line = {'width':2, 'color':'red'}
)
xz_cur = go.Scatter(
name = 'Position at Epoch',
legendgroup = 'cur',
showlegend = False,
x = [orbit_points[0,0]],
y = [orbit_points[0,2]],
mode = 'markers',
marker = {'size':10, 'color':'blue'}
)
xyz_fig1 = tools.make_subplots(rows=2,cols=2,specs=[[{},{}],
[{},{'is_3d':True}]])
xyz_fig1.append_trace(xz_org,1,1)
xyz_fig1.append_trace(xz_fit,1,1)
xyz_fig1.append_trace(xz_cur,1,1)
xyz_fig1.append_trace(yz_org,1,2)
xyz_fig1.append_trace(yz_fit,1,2)
xyz_fig1.append_trace(yz_cur,1,2)
xyz_fig1.append_trace(xy_org,2,1)
xyz_fig1.append_trace(xy_fit,2,1)
xyz_fig1.append_trace(xy_cur,2,1)
xyz_fig1.append_trace(xyz_org,2,2)
xyz_fig1.append_trace(xyz_fit,2,2)
xyz_fig1.append_trace(xyz_cur,2,2)
xyz_fig1.append_trace(earth_top,2,2)
xyz_fig1.append_trace(earth_bottom,2,2)
xyz_fig1['layout']['xaxis1'].update(title='x '+'{}'.format(dropdown_value))
xyz_fig1['layout']['yaxis1'].update(title='z '+'{}'.format(dropdown_value), scaleanchor='x')
xyz_fig1['layout']['xaxis2'].update(title='y '+'{}'.format(dropdown_value), scaleanchor='x')
xyz_fig1['layout']['yaxis2'].update(title='z '+'{}'.format(dropdown_value), scaleanchor='x2')
xyz_fig1['layout']['xaxis3'].update(title='x '+'{}'.format(dropdown_value), scaleanchor='x')
xyz_fig1['layout']['yaxis3'].update(title='y '+'{}'.format(dropdown_value), scaleanchor='x3')
xyz_fig1['layout']['scene1']['xaxis'].update(showticklabels=True, showspikes=False, title='x '+'{}'.format(dropdown_value))
xyz_fig1['layout']['scene1']['yaxis'].update(showticklabels=True, showspikes=False, title='y '+'{}'.format(dropdown_value))
xyz_fig1['layout']['scene1']['zaxis'].update(showticklabels=True, showspikes=False, title='z '+'{}'.format(dropdown_value))
xyz_fig1['layout'].update(width=1050, height=700, margin={'t':50})
xyz_fig1['layout']['legend'].update(orientation='h')
###
rel_time = data[:,0] - data[0,0]
xt_org = go.Scatter(
name = 'Original Data',
legendgroup = 'org',
x = rel_time,
y = data[:,1],
mode = 'markers',
marker = {'size': 5, 'color':'black'}
)
xt_fit = go.Scatter(
name = 'Fitted Ellipse',
legendgroup = 'fit',
x = rel_time,
y = orbit_points[:,0],
mode = 'lines',
line = {'width':2, 'color':'red'}
)
xt_cur = go.Scatter(
name = 'Position at Epoch',
legendgroup = 'cur',
x = [rel_time[0]],
y = [orbit_points[0,0]],
mode = 'markers',
marker = {'size': 10, 'color':'blue'}
)
yt_org = go.Scatter(
name = 'Original Data',
legendgroup = 'org',
showlegend = False,
x = rel_time,
y = data[:,2],
mode = 'markers',
marker = {'size': 5, 'color':'black'}
)
yt_fit = go.Scatter(
name = 'Fitted Ellipse',
legendgroup = 'fit',
showlegend = False,
x = rel_time,
y = orbit_points[:,1],
mode = 'lines',
line = {'width':2, 'color':'red'}
)
yt_cur = go.Scatter(
name = 'Position at Epoch',
legendgroup = 'cur',
showlegend = False,
x = [rel_time[0]],
y = [orbit_points[0,1]],
mode = 'markers',
marker = {'size': 10, 'color':'blue'}
)
zt_org = go.Scatter(
name = 'Original Data',
legendgroup = 'org',
showlegend = False,
x = rel_time,
y = data[:,3],
mode = 'markers',
marker = {'size': 5, 'color':'black'}
)
zt_fit = go.Scatter(
name = 'Fitted Ellipse',
legendgroup = 'fit',
showlegend = False,
x = rel_time,
y = orbit_points[:,2],
mode = 'lines',
line = {'width':2, 'color':'red'}
)
zt_cur = go.Scatter(
name = 'Position at Epoch',
legendgroup = 'cur',
showlegend = False,
x = [rel_time[0]],
y = [orbit_points[0,2]],
mode = 'markers',
marker = {'size': 10, 'color':'blue'}
)
rt_org = go.Scatter(
name = 'Original Data',
legendgroup = 'org',
showlegend = False,
x = rel_time,
y = (data[:,1]**2+data[:,2]**2+data[:,3]**2)**0.5,
mode = 'markers',
marker = {'size': 5, 'color':'black'}
)
rt_fit = go.Scatter(
name = 'Fitted Ellipse',
legendgroup = 'fit',
showlegend = False,
x = rel_time,
y = ((orbit_points[:,0])**2+
(orbit_points[:,1])**2+
(orbit_points[:,2])**2)**0.5,
mode = 'lines',
line = {'width':2, 'color':'red'}
)
rt_cur = go.Scatter(
name = 'Position at Epoch',
legendgroup = 'cur',
showlegend = False,
x = [rel_time[0]],
y = [((orbit_points[0,0])**2+
(orbit_points[0,1])**2+
(orbit_points[0,2])**2)**0.5],
mode = 'markers',
marker = {'size': 10, 'color':'blue'}
)
t_fig = tools.make_subplots(rows=4,cols=1,shared_xaxes=True)
t_fig.append_trace(xt_org,1,1)
t_fig.append_trace(xt_fit,1,1)
t_fig.append_trace(xt_cur,1,1)
t_fig.append_trace(yt_org,2,1)
t_fig.append_trace(yt_fit,2,1)
t_fig.append_trace(yt_cur,2,1)
t_fig.append_trace(zt_org,3,1)
t_fig.append_trace(zt_fit,3,1)
t_fig.append_trace(zt_cur,3,1)
t_fig.append_trace(rt_org,4,1)
t_fig.append_trace(rt_fit,4,1)
t_fig.append_trace(rt_cur,4,1)
t_fig['layout']['xaxis1'].update(title='t (s)')
t_fig['layout']['yaxis1'].update(title='x '+'{}'.format(dropdown_value))
t_fig['layout']['yaxis2'].update(title='y '+'{}'.format(dropdown_value), scaleanchor='y')
t_fig['layout']['yaxis3'].update(title='z '+'{}'.format(dropdown_value), scaleanchor='y')
t_fig['layout']['yaxis4'].update(title='|r| '+'{}'.format(dropdown_value), scaleanchor='y', scaleratio=100)
t_fig['layout'].update(width=1050, height=700, margin={'t':50})
t_fig['layout']['legend'].update(orientation='h')
####
rel_time = data1[:,0] - data1[0,0]
xt_org = go.Scatter(
name = 'Original Data',
legendgroup = 'org',
x = rel_time,
y = data[:,1],
mode = 'markers',
marker = {'size': 5, 'color':'black'}
)
xt_fit = go.Scatter(
name = 'Fitted Ellipse',
legendgroup = 'fit',
x = rel_time,
y = orbit_points[:,0],
mode = 'lines',
line = {'width':2, 'color':'red'}
)
xt_cur = go.Scatter(
name = 'Position at Epoch',
legendgroup = 'cur',
x = [rel_time[0]],
y = [orbit_points[0,0]],
mode = 'markers',
marker = {'size': 10, 'color':'blue'}
)
yt_org = go.Scatter(
name = 'Original Data',
legendgroup = 'org',
showlegend = False,
x = rel_time,
y = data[:,2],
mode = 'markers',
marker = {'size': 5, 'color':'black'}
)
yt_fit = go.Scatter(
name = 'Fitted Ellipse',
legendgroup = 'fit',
showlegend = False,
x = rel_time,
y = orbit_points[:,1],
mode = 'lines',
line = {'width':2, 'color':'red'}