Radonometer/render.py at main · Qwert512/Radonometer · GitHub

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
import time, math
import numpy as np
import matplotlib.pyplot as plt
from brokenaxes import brokenaxes
from cycler import cycler

dark_mode_color = '#282828'

mpl_dark = {
            'axes.facecolor'    : dark_mode_color,
            'axes.labelcolor'   : 'white',
            'axes.edgecolor'    : 'white',
            'figure.facecolor'  : dark_mode_color,
            'figure.edgecolor'  : '#808080',
            'savefig.facecolor' : dark_mode_color,
            'savefig.edgecolor' : dark_mode_color,
            'xtick.color'       : 'white',
            'ytick.color'       : 'white',
            'text.color'        : 'white',
            'grid.color'        : '#CCCCCC',
            'axes.prop_cycle'   : cycler('color', ['r', 'g', 'c', 'm', 'y', 'w'])
            }

mpl_light = {
            'axes.facecolor'    : 'white',
            'axes.labelcolor'   : 'black',
            'axes.edgecolor'    : 'black',
            'figure.facecolor'  : 'white',
            'figure.edgecolor'  : '#808080',
            'savefig.facecolor' : 'white',
            'savefig.edgecolor' : 'white',
            'xtick.color'       : 'black',
            'ytick.color'       : 'black',
            'text.color'        : 'black',
            'grid.color'        : '#222222',
            'axes.prop_cycle'   : cycler('color', ['r', 'b', 'c', 'm', 'k'])
            }


async def render(dark_mode:bool,x_width:int,y_height:int,jumps_1:tuple,json_data:dict,x_values:list,start_time_ms:int,time_elapsed_calc_ms:int,y_values:list):
    x_axis_values, unit, plot_title, div_val = await label_x_axis_and_title(x_values=x_values)

    jumps_1 = tuple([list(map(lambda val: val / div_val, sublist)) for sublist in jumps_1])
    #divide all values in the jumps 1 tuple by the div values provided

    # convert all  minute values from str to int and substract the start value from them, so the diagram starts at 0

    window_size = min(10, len(y_values))  # Use a window size of 10 or the length of the data array, whichever is smaller
    smoothed_data = np.convolve((y_values), np.ones(window_size) / window_size, mode='same')
    # Plot data on the broken axes


    style_context = mpl_dark if dark_mode else mpl_light

    with plt.style.context(style_context):
        plt.figure(figsize=(x_width, y_height), dpi=120)

        if len(jumps_1) != 0:
            ax = brokenaxes(xlims=jumps_1, hspace=0.05)
            ax.plot(x_axis_values, y_values, 'c-', label="Geiger counter activity")
            ax.plot(x_axis_values, smoothed_data, 'r-', label="Smoothed Geiger counter activity")
        else:
            ax = brokenaxes(hspace=0.05)
            print("Plotting NO data")

        ax.set_xlabel("Time (" + unit + ")")
        ax.set_ylabel("Activity (CPM)")
        ax.legend(loc='upper right')
        plt.title(plot_title)
    # Save the plot
    plt.savefig("last_x_mins.png")
    plt.clf()
    plt.close()

    time_elapsed_render_ms = math.floor(time.time()*1000) - start_time_ms - time_elapsed_calc_ms
    time_diff_ms = time_elapsed_calc_ms+time_elapsed_render_ms
    render_time_percent = round((time_elapsed_render_ms/time_diff_ms)*100,2)
    calc_time_percent = round((time_elapsed_calc_ms/time_diff_ms)*100,2)

    print("Successfully updated all plots in "+str(time_diff_ms)+"ms. Off that rendering took up "
          +str(time_elapsed_render_ms)+"ms ("+str(render_time_percent)+"%) and processing took up "
          +str(time_elapsed_calc_ms)+"ms ("+str(calc_time_percent)+"%)")


async def label_x_axis_and_title(x_values:list):
    np_x_values = np.array(x_values)

    units = ["minutes","hours","days","weeks","months", "years"]
    breakpoints = [240,4320,30240,120960,1576800]
    # = [4h, 72h, 21d, 12w, 36m]
    dividing_values = [1,60,1440,10080,43200,525600]
    # 1h = 60min, 1d = 1440min, 1w = 10080min, 1M = 43200min, 1y = 525600min
    last_val = np_x_values[-1]

    div_factor = dividing_values[0]
    unit = units[0]
    final_x_values = list(np_x_values)

    for i in reversed(range(6)):
        if last_val >= breakpoints[i-1]:
            unit = units[i]
            np_x_values = np_x_values/dividing_values[i]
            final_x_values = list(np_x_values)
            div_factor =dividing_values[i]
            break


    title_val = round(last_val/div_factor,2)
    title = "Last "+str(title_val)+" "+unit+" of data"
    return(final_x_values,unit,title,div_factor)