Jyotisha/references/open_source_sources/VedicAstro/StudyNotebooks/AscMotionStudy.ipynb

Description

This notebook is an exercise to study the speed at which the Ascendant (Lagna) moves per sec, on average over the entire year. Please remember to install the following packages in your virtual environment before running this notebook.

pip install plotly
pip install --upgrade nbformat

In [15]:

from flatlib import const
import plotly.graph_objects as go
from datetime import datetime, timedelta
from vedicastro.VedicAstro import VedicHoroscopeData

In [16]:

def calculate_daily_asc_speed(year, lat, lon, utc, ayan, house_system):
    """Calculates the ascendant speed for each day of the year."""
    asc_speeds = []
    dates = []
    
    # Loop through each day of the year
    start_date = datetime(year, 1, 1)
    for day in range(365):
        current_date = start_date + timedelta(days=day)
        dates.append(current_date.strftime('%Y-%m-%d'))
        
        # Define two moments in time, at the start and end of the day
        datetime_start = current_date.replace(hour=0, minute=0, second=1)
        datetime_end = current_date.replace(hour=0, minute=0, second=11)
        # datetime_end = current_date.replace(hour=23, minute=59, second=59)
        difference = datetime_end - datetime_start
        diff_seconds = difference.total_seconds()

        
        # Generate horoscope data for both moments
        horoscope_start = VedicHoroscopeData(datetime_start.year, datetime_start.month, datetime_start.day, datetime_start.hour, datetime_start.minute, datetime_start.second, utc, lat, lon, ayan, house_system)
        final_chart_start = horoscope_start.generate_chart()
        asc_start = final_chart_start.get(const.ASC)
        asc_start_lon_deg = asc_start.lon
        
        horoscope_end = VedicHoroscopeData(datetime_end.year, datetime_end.month, datetime_end.day, datetime_end.hour, datetime_end.minute, datetime_end.second, utc, lat, lon, ayan, house_system)
        final_chart_end = horoscope_end.generate_chart()
        asc_end = final_chart_end.get(const.ASC)
        asc_end_lon_deg = asc_end.lon
        

        # Calculate the change in Ascendant position
        delta_degrees = (asc_end_lon_deg - asc_start_lon_deg) % 360
        
        
        asc_speeds.append(delta_degrees/ diff_seconds)  # Speed in degrees per second over the entire day
    
    return dates, asc_speeds

In [17]:

# Example usage parameters
year = 2024
lat = 11.020085773931049 # Example latitude
lon = 76.98319647719487  # Example longitude
utc = "+05:30"
ayan = "Krishnamurti" 
house_system = "Placidus"

dates, asc_speeds = calculate_daily_asc_speed(year, lat, lon, utc, ayan, house_system)
print(f"Asc Speed on {dates[0]}: {asc_speeds[0]:.5f} ° per second")

Asc Speed on 2024-01-01: 0.00420 ° per second

In [18]:

# Plotting with Plotly
fig = go.Figure()
fig.add_trace(go.Scatter(x=dates, y=asc_speeds, mode='lines',name = "",
                         hovertemplate="<b>Date</b>: %{x}<br>" + "<b>AscSpeed</b>: %{y:.5f}° per second"))

fig.update_layout(title=f'Ascendant Movement Per Second for Each Day of {year}',
                    xaxis_title='Date',
                    yaxis_title='Movement (degrees/sec)',
                    template='plotly_dark')
fig.show()

[Data output - unsupported data type map[string]interface {} for mime type application/vnd.plotly.v1+json]