def actigraphy_load_data(filename):
    f = open(filename, "r")
    count = 0
    while count < 50:
        count += 1

        # Get next line from file
        line = f.readline()
        if '+-------------------------------------------------------+' in line:
            break
    df = pd.read_csv(filename, delimiter = ';', header = count, parse_dates = False)
    df['DATE/TIME'] = pd.to_datetime(df['DATE/TIME'], format = '%d/%m/%Y %H:%M:%S')
    df.set_index( df['DATE/TIME'], inplace = True)
    return df   

def actigraphy_select_period(start_date, end_date):
    index = np.logical_and(df.index >= start_date, df.index < end_date)
    filtered_df = df[index]
    return filtered_df

filename = "Example_Log.txt"
url ='https://github.com/Condor-Instruments/actigraphy-tutorials-sample/blob/master/Example_Log.txt?raw=true'
urllib.request.urlretrieve(url, filename)

df = actigraphy_load_data(filename)

start_date = pd.Timestamp('2015-12-26 00:00:00')
end_date = df.index[-1]
df = actigraphy_select_period(start_date,end_date)

# We will create a color list to be used sequentially for each signal we add to the plot

color_list = [
    '#1f77b4',  # muted blue
    '#ff7f0e',  # safety orange
    '#2ca02c',  # cooked asparagus green
    '#d62728',  # brick red
    '#9467bd',  # muted purple
    '#8c564b',  # chestnut brown
    '#e377c2',  # raspberry yogurt pink
    '#7f7f7f',  # middle gray
    '#bcbd22',  # curry yellow-green
    '#17becf'   # blue-teal
    ]

def actigraphy_split_by_day(df, start_hour = 0):
    ldays = []
    ldays_ref = []
    
    #First day is the start of the day of the first Epoch
    sdate = pd.Timestamp(year = df.index[0].year, month = df.index[0].month, day = df.index[0].day)
    if(df.index[0].hour <= start_hour):
        sdate = sdate - pd.Timedelta(hours = start_hour) 
    else:
        sdate = sdate + pd.Timedelta(hours = start_hour)         
    
    while sdate < df.index[-1]:
        day = np.logical_and(df.index >= sdate, df.index < sdate + pd.Timedelta(hours = 24))
        ldays.append(df[day])
        ldays_ref.append(pd.Timestamp(year = sdate.year, month = sdate.month, day = sdate.day))
        sdate += pd.Timedelta(hours = 24)
        
    return ldays, ldays_ref

def actigraphy_single_plot_actogram(df, cols, secondary_y, start_hour):
    ldays = []
    ldays_ref = []
    
    #First day is the start of the day of the first Epoch
    ldays, ldays_ref = actigraphy_split_by_day(df, start_hour)

    specs = [[{"secondary_y": True}]] * len(ldays)
    fig = make_subplots(len(ldays), 1, specs = specs)
    
    for i in range(len(ldays)):
        j = 0
        showlegend = False
        if(i == 0):
            showlegend = True
        for cn in cols: 
            fig.add_trace(go.Scattergl(x=ldays[i].index,
                                          y=ldays[i][cn],
                                          opacity=0.8, 
                                          fillcolor= 'rgb(0,160,255)',line=dict(color=color_list[j%len(color_list)]),
                                          legendgroup=cn,
                                          showlegend=showlegend,
                                          name = cn,
                                         )
                              , i+1, 1,  secondary_y = secondary_y[j])
            j = j+1
        fig.update_xaxes(range=[ldays_ref[i] + pd.Timedelta(hours = 12), ldays_ref[i] + pd.Timedelta(hours = 36)], row=i+1, col=1)
    fig.update_layout(height=len(ldays)*200)
    return fig    

def rescale(x, min_val, max_val):
    resc = (x - min_val)/(max_val - min_val)
    return resc
    

def actigraphy_double_plot_actogram(df, column):
    max_val = max(df[column])*1.1
    min_val = min(df[column])
    if min_val > 0:
        min_val = min_val*0.9
    
    #First day is the start of the day of the first Epoch
    ldays, ldays_ref = actigraphy_split_by_day(df) 
    fig = go.Figure()    
    i = 0
    for i in range(len(ldays)-1):
        d1 = ldays[i]
        d2 = ldays[i+1]
        x1 = d1.index.hour + d1.index.minute/60.0 + d1.index.second/3600.0
        x2 = d2.index.hour + d2.index.minute/60.0 + d2.index.second/3600.0 + 24.0
        x = np.append(x1,x2)
        y = np.append(d1[column],d2[column])
        y = (i+1)-rescale(y, min_val, max_val)
        fig.add_trace(go.Scatter(x=x,y=y,line=dict(color='royalblue')))
        i +=1
    d1 = ldays[-1]
    x = d1.index.hour + d1.index.minute/60.0 + d1.index.second/3600.0
    y = d1[column]
    y = (i+1)-rescale(y, min_val, max_val)
    fig.add_trace(go.Scatter(x=x,y=y,line=dict(color='royalblue')))
    
    
    fig.update_yaxes(range=[len(ldays), 0])    
    fig.update_layout(showlegend=False)
    fig.update_xaxes(tick0=0, dtick=2)
    fig.update_layout(height=len(ldays)*70)

    
    return fig