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

# In[2]:


get_ipython().run_line_magic('matplotlib', 'inline')
import numpy as np
import matplotlib.pyplot as plt


# In[3]:


import pandas as pd


# In[54]:


base_url = "http://golem.fjfi.cvut.cz/shots/{shot_no}/DAS/0417RigolDS1074{group}.ON/data_all"

def load_data(shot_no, identifier, fs_full, n_samp_full):
    url = base_url.format(shot_no=shot_no, group=identifier)
    data = pd.read_csv(url, header=None, sep='\\s+')
    fs_red = data.shape[0]/n_samp_full * fs_full
    dt = 1/fs_red
    data.index *= dt
    data.index.name = 'time'
    return data, dt


# In[61]:


df, dt = load_data(29703, 'd', 125e3, 3e6) # in S/ms -> ms time
df.head()


# In[47]:


df.plot(subplots=True)


# In[62]:


offset = df.loc[0:4,1].mean()
offset


# In[63]:


corrected = df[1] - offset


# In[64]:


dt = df.index[1] - df.index[0]
dt


# In[66]:


I_ch = np.cumsum(corrected) * dt * -5e3


# In[67]:


I_ch.plot()