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%% Cell type:markdown id:a4d202eb-9d92-4857-b2af-aba670f9090b tags:
# Análisis de Datos Racimo Tormenta
%% Cell type:markdown id:52bc4c5f-1baf-4e8f-8a1d-0b0e51fa8695 tags:
Notebook para el análisis de datos del proyecto racimo tormenta
%% Cell type:markdown id:d277a53c-cccc-4996-8944-620130575372 tags:
## Librerias
%% Cell type:markdown id:e96a3270-365f-4f90-9d5a-d2673f176f11 tags:
Importar las librerias necesarias para el análisis e interacciones de los datos
%% Cell type:code id:5d4d6478-6b92-46a4-a849-7fc4d5a3b119 tags:
``` python
import numpy as np
import matplotlib.pylab as plt
import scipy
from scipy import stats
from scipy.fftpack import fftfreq, irfft, rfft
import sys
import os
from matplotlib import cm
from matplotlib.colors import ListedColormap, LinearSegmentedColormap
import math
import datetime as datetime
import time
import matplotlib.dates as md
%matplotlib inline
sys.getdefaultencoding()
```
%% Output
'utf-8'
%% Cell type:markdown id:960fdf13-2b85-4fca-a1fb-ed0aa016e468 tags:
## Calibración del detector
%% Cell type:markdown id:3b8b509b-c69e-4c8d-98e2-6f9d7cc825c3 tags:
Calibración de las mediciones del detector
%% Cell type:markdown id:440109c1-3272-4702-9a0c-fd5e2b8e6b1d tags:
### Vista preliminar de los datos de calibración
%% Cell type:markdown id:4ed58223-c091-4de4-b9c7-2cf4b3dd674f tags:
Cargar datos
%% Cell type:code id:78a31578-66f3-4363-80b4-856aabede298 tags:
``` python
data = np.loadtxt('../Data/Lighting_2021_04_13_00_6.dat', comments='#')
```
%% Cell type:markdown id:7c03fdf2-6a4a-4d30-87e3-3b025a43f6c1 tags:
Ver encabezado
%% Cell type:code id:c5141991-6dd0-42d6-a4bd-4cfe0a164bba tags:
``` python
data
```
%% Output
array([[0.00000e+00, 0.00000e+00],
[1.00000e-05, 9.00000e+01],
[2.00000e-05, 3.90000e+01],
...,
[1.19995e+00, 3.30000e+01],
[1.19996e+00, 5.30000e+01],
[1.19997e+00, 1.80000e+01]])
%% Cell type:markdown id:c754f55c-22ff-46b9-a414-7fa07a4497d6 tags:
### Amplitud y frecuencia de la señal
%% Cell type:markdown id:badb8819-ef05-4e8c-867c-8b4a03f554d2 tags:
Función para graficar amplitud y frecuencia.
%% Cell type:code id:05f9f0b6-dd57-4e7e-92ca-4718cf85808e tags:
``` python
def Lightning_Analysis(data, dt, Np):
mean = np.mean(data[:,1])
sigma = np.std(data[:,1])
peaks = []
MTFt = [] # Multiple-termination flash (MTF) relative times
MTSt = [] # Multiple.termination stroke (MTS) relative times
MTSv = []
T_count = 0 # Terminations counter
MTFc = 1 # MTF counter
MTSc = 0 # MTS counter
N = len(data)
MTSw = 1e-3 # time window for differentiating MTF and MTS events
threshold = mean + 5*sigma # Peak threshold
# Termination identification
for i in range(N):
if (data[i,1] > threshold):
T_count += 1
peaks.append(i)
t1 = data[i,0]
if T_count > 1:
Td = t1 - t0
if Td > MTSw:
MTFt.append(Td)
MTFc += 1
MTSv.append(MTSc)
MTSc = 0
else:
MTSt.append(Td)
MTSc += 1
t0 = t1
print (u'Terminations above 5\u03C3 = %d\n' %T_count)
print (u'Number of strokes = %d\n' %MTFc)
s = data[:,1]
Y = np.fft.fft(s)
N = len(Y)/2+1
fa = 1.0/dt
X = np.linspace(0, fa/2, int(N), endpoint=True)
sfft = np.abs(Y[:int(N)])
print('Sample Time = %.5f s' % dt)
print('Frequency = %.2f Hz' % fa)
sfft = np.array(sfft)
pos = int(np.where(sfft[1:-1] == np.amax(sfft[1:-1]))[0])
frec_pico = 868.35 # X[pos+1]
print ("Maximum frequency = %.2f Hz" %frec_pico)
if T_count >= Np:
# Signal plot
plt.figure(figsize = (16,4))
plt.subplot(1,2,1)
plt.plot(data[:,0], data[:,1])
plt.axhline(threshold, color='red')
plt.xlabel('Time [s]', fontsize = 20)
plt.ylabel('Amplitude [ADC]', fontsize = 20)
plt.savefig("amplitude.png", dpi=150)
# Spectrum plotting
plt.subplot(1,2,2)
plt.axvline(frec_pico, color='red')
plt.loglog(X, sfft)
plt.xlabel('Frequency [Hz]', fontsize = 20)
plt.axis([1e-1,1e5,1e1,1e7])
plt.grid()
plt.show()
return frec_pico, peaks, MTFt, MTSt, T_count, MTFc, MTSv
```
%% Cell type:markdown id:4da5b0b2-97c4-455b-b9f9-028e817f3fa9 tags:
Graficar
%% Cell type:code id:66982705-0db4-43d7-8bd0-22ec2ae7b907 tags:
``` python
dt = 10e-6 # sampling period
Np = 0. # filter signals per number of peaks above 5 sigma
fp1, peaks1, MTFt, MTSt, pN1, MTFc, MTSc = Lightning_Analysis(data, dt, Np) # Returns maximum peak frequency and peak positions
```
%% Output
Terminations above 5σ = 7
Number of strokes = 1
Sample Time = 0.00001 s
Frequency = 100000.00 Hz
Maximum frequency = 868.35 Hz
%% Cell type:code id:2c168963-a095-45b0-bcf1-e7943b3ba423 tags:
``` python
```
README.md
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# Análisis de Datos # Análisis de Datos
Análisis de datos racimo tormenta. Repositorio de análisis de datos del proyecto Racimo Tormenta.
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## Publicaciones
- Calibración del instrumento.
- Datos: [https://dataverse.redclara.net/dataverse/storm](https://dataverse.redclara.net/dataverse/storm)
- Código: [https://gitmilab.redclara.net/mxrtinez1/analisis-de-datos](https://gitmilab.redclara.net/mxrtinez1/analisis-de-datos)
- Artículo: [https://www.overleaf.com/read/yhvybynwktjv](https://www.overleaf.com/read/yhvybynwktjv)
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