#!/usr/bin/env python
# coding: utf-8

# # Using Geodesics (Back-ends & Plotting)

# In[1]:


import numpy as np

from einsteinpy.geodesic import Timelike #, Geodesic, Nulllike
from einsteinpy.plotting import GeodesicPlotter, StaticGeodesicPlotter #, InteractiveGeodesicPlotter

# To ensure plots show up in the documentation
import plotly
plotly.offline.init_notebook_mode()


# ## Example 1: Exploring Schwarzschild Time-like Spiral Capture, using Python Backend and GeodesicPlotter
# 
# ### Defining initial conditions

# In[2]:


# Initial Conditions
position = [4., np.pi / 3, 0.]
momentum = [0., 0., -1.5]
a = 0. # Schwarzschild Black Hole


# ### Calculating Geodesic

# In[3]:


geod = Timelike(
    metric = "Schwarzschild",
    metric_params = (a,),
    position=position,
    momentum=momentum,
    steps=15543, # As close as we can get before the integration becomes highly unstable
    delta=0.0005,
    return_cartesian=True,
    omega=0.01, # Small omega values lead to more stable integration
    suppress_warnings=True, # Uncomment to view the tolerance warning
)

geod


# ### Plotting using `GeodesicPlotter`
# 
# Note that `GeodesicPlotter` automatically switches between "Static" and "Interactive" plots. Since we are in a Jupyter Notebook or Interactive Environment, it uses the "Interactive" backend.

# In[4]:


gpl = GeodesicPlotter()


# In[5]:


gpl.plot(geod, color="green", title="Geodesic Plot", aspect="auto")
gpl.show()


# In[6]:


gpl.clear() # In Interactive mode, `clear()` must be called before drawing another plot, to avoid overlap
gpl.plot2D(geod, coordinates=(1, 2), color="green", title="Top/Bottom View") # "top" / "bottom" view
gpl.show()


# In[7]:


gpl.clear()
gpl.plot2D(geod, coordinates=(1, 3), color="green", title="Face-On View") # "face-on" view
gpl.show()


# Each interactive plot instance (`gpl`) has a `fig` attribute that is a `plotly.graph_objs._figure.Figure` object. So, one can easily make modifications to the plots as they would to any plotly figure. For instance, we can update the title to clarify that the plot above is showing a face-on view.

# In[8]:


gpl.fig.layout.title = {
    'text': 'Face-On View', 'x': 0.46, 'xanchor': 'center', 'y': 0.9, 'yanchor': 'top'
}
gpl.show()


# In[9]:


gpl.clear()
gpl.parametric_plot(geod, colors=("red", "green", "blue"))
gpl.show()