Aggiunti tempi di albe e tramonti con twilight zones

.gitignore

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+/crps/

.idea/.gitignore

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+# Default ignored files
+/shelf/
+/workspace.xml

.idea/OCR_Dome.iml

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+<?xml version="1.0" encoding="UTF-8"?>
+<module type="PYTHON_MODULE" version="4">
+  <component name="NewModuleRootManager">
+    <content url="file://$MODULE_DIR$" />
+    <orderEntry type="inheritedJdk" />
+    <orderEntry type="sourceFolder" forTests="false" />
+  </component>
+</module>

.idea/inspectionProfiles/profiles_settings.xml

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+<component name="InspectionProjectProfileManager">
+  <settings>
+    <option name="USE_PROJECT_PROFILE" value="false" />
+    <version value="1.0" />
+  </settings>
+</component>

.idea/misc.xml

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+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="Black">
+    <option name="sdkName" value="Python 3.11" />
+  </component>
+  <component name="ProjectRootManager" version="2" project-jdk-name="Python 3.11" project-jdk-type="Python SDK" />
+</project>

.idea/modules.xml

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+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="ProjectModuleManager">
+    <modules>
+      <module fileurl="file://$PROJECT_DIR$/.idea/OCR_Dome.iml" filepath="$PROJECT_DIR$/.idea/OCR_Dome.iml" />
+    </modules>
+  </component>
+</project>

.idea/vcs.xml

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+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="VcsDirectoryMappings">
+    <mapping directory="$PROJECT_DIR$" vcs="Git" />
+  </component>
+</project>

README.md

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+Con ocr01.py acquisisci i dati dagli screenshot (in modo cumulativo su all_measures.json)
+Poi con reload_data.py ottieni la versione ripulita: clean_data.json
+Poi con show_data crei i file di visualizzazione.

json_extensions.py

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+#!/usr/bin/python
+# -*- coding: utf-8 -*-
+import json
+from decimal import Decimal
+# from task_row_x import TaskRow, SimpleTaskRow
+
+
+def load_from_json_file(infile):
+    with open(infile, 'r') as fin:
+        obj = json.load(fin)
+    return obj
+
+
+class SpecialEncoder(json.JSONEncoder):
+    def default(self, obj):
+        if isinstance(obj, Decimal):
+            return str(obj)  # Or you could return str(obj) depending on your needs
+        # if isinstance(obj, TaskRow) or isinstance(obj, SimpleTaskRow):
+        if hasattr(obj, 'get_dict') and callable(getattr(obj, 'get_dict')):
+            return obj.get_dict()
+        if isinstance(obj, set):
+            return [str(v) for v in obj]
+        return super().default(obj)
+
+
+def save_to_json_file(out_name, obj):
+    with open(out_name, 'w', encoding='utf-8', newline='\n') as fout:
+        json.dump(obj, fout, indent=4, cls=SpecialEncoder)
+
+
+def save_to_json_str(obj):
+    return json.dumps(obj, indent=4, cls=SpecialEncoder)
+
+def main():
+    pass
+
+
+if __name__ == '__main__':
+    main()

ocr01.py

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+#!/usr/bin/python
+# -*- coding: utf-8 -*-
+import pytesseract
+from PIL import Image
+from pathlib import Path
+from datetime import datetime
+# import numpy as np
+import colorsys
+from json_extensions import save_to_json_file, load_from_json_file
+
+save_file = Path('all_measurements.json')
+
+
+# FOLDER = Path('C:/Mc/Dome/Telecamere/ScreenShots')
+# FOLDER = Path('C:/Mc/Dome/Telecamere/ScreenShots2')
+FOLDER = Path('C:/Mc/Dome/Telecamere/ScreenShots3')
+
+
+CROPS = {
+    'batt_full': (351, 1109, 389, 101),
+    'name': (175, 143, 750, 109),
+    # 'batt': (48, 320, 25, 50),
+    'batt': (56, 345, 9, 2),
+    'perc': (83, 314, 123, 60),
+}
+
+
+def available_screenshot(base_folder: Path):
+    for f in base_folder.iterdir():
+        if f.is_file() and f.suffix == '.jpg' and f.stem.startswith('Screenshot') and f.stem.endswith('0a7d545a89c1640e78c89a2ce00d525b'):
+            yield f
+
+
+def main(base_folder: Path, out_folder=Path('crps')):
+    # for sc in sorted(available_screenshot(base_folder), key=lambda x:x.stem):
+    found = False
+    n = 0
+    if save_file.is_file():
+        measures = load_from_json_file(save_file)
+    else:
+        measures = []
+    for sc in available_screenshot(base_folder):
+        n += 1
+        _, f_date, _ = sc.stem.split('_')
+        dt = datetime.strptime(f_date[:-3], '%Y-%m-%d-%H-%M-%S')
+        # obj = {'dt': dt}
+        obj = {'epoch': dt.timestamp()}
+        # if f_date != '2025-03-16-07-59-52-21':
+        #     continue
+        # print(sc.stem)
+        src_img = Image.open(sc)
+        for k, crp in CROPS.items():
+            x0, y0, w, h = crp
+            x1 = x0 + w
+            y1 = y0 + h
+            cropped = src_img.crop((x0, y0, x1, y1))
+            if k == 'batt':
+                # new_name = f'{k}_{f_date}.png'
+                # cropped.save(out_folder / new_name)
+                tot, grey = 0, 0
+                for p in cropped.getdata():
+                    tot += 1
+                    r, g, b = p
+                    h, s, v = colorsys.rgb_to_hsv(r / 255, g / 255, b / 255)
+                    if s < 0.1 and v > 0.1:
+                        grey += 1
+                v = grey / tot
+                # print(f'{v:.1f}')
+                obj['charging'] = v > 0.8
+            # obj['charging'] = is_mostly_white(cropped)
+            if k != 'batt':
+                text = pytesseract.image_to_string(cropped)
+                obj[k] = text
+                if k == 'batt_full' and len(text) > 3:
+                    found = True
+        print(f'{f_date}: {obj}')
+        measures.append(obj)
+    save_to_json_file('all_measurements.json', measures)
+    return
+
+
+if __name__ == '__main__':
+    main(FOLDER)

plt_example.py

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+#!/usr/bin/python
+# -*- coding: utf-8 -*-
+import matplotlib.pyplot as plt
+import matplotlib.dates as mdates
+import datetime
+
+
+def main():
+    # Sample data
+    epoch_times = [1696000000, 1696086400, 1696172800, 1696259200]  # Epoch seconds
+    y_values = [10, 20, 15, 25]  # Some y-axis values
+
+    # Convert epoch times to datetime objects
+    dates = [datetime.datetime.fromtimestamp(ts) for ts in epoch_times]
+
+    # Create the plot
+    fig, ax = plt.subplots()
+    ax.plot(dates, y_values, marker='o', linestyle='-')
+
+    # Format the x-axis as date
+    # ax.xaxis.set_major_formatter(mdates.DateFormatter('%Y-%m-%d\n%H:%M:%S'))  # Customize as needed
+    ax.xaxis.set_major_locator(mdates.AutoDateLocator())  # Automatically adjusts for readability
+    ax.xaxis.set_major_formatter(
+        mdates.ConciseDateFormatter(ax.xaxis.get_major_locator()))
+
+    # Rotate date labels for better visibility
+    plt.xticks(rotation=45)
+
+    # Labels and title
+    plt.xlabel("Date & Time")
+    plt.ylabel("Values")
+    plt.title("Epoch to Human Readable Time Plot")
+
+    # Show the plot
+    plt.show()
+
+
+if __name__ == '__main__':
+    main()

reload_data.py

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+#!/usr/bin/python
+# -*- coding: utf-8 -*-
+from json_extensions import load_from_json_file, save_to_json_file
+
+
+def main():
+    clean_data: dict[str, list] = {}
+    obj = load_from_json_file('all_measurements.json')
+    names = set()
+    for row in obj:
+        name = row.get('name', '').strip('\n')
+        perc_s = row.get('perc', '').strip('\n')
+        charging = row.get('charging')
+        epoch = row.get('epoch')
+        batt_full_s = row.get('batt_full', '').strip('\n')
+        batt_full = 'The battery is full' in batt_full_s
+        if '%' not in perc_s:
+            raise ValueError(f'Missing % in {row}')
+        prc = int(perc_s.split('%', maxsplit=1)[0])
+        names.add(name)
+        if name not in clean_data:
+            clean_data[name] = []
+        new_row = {'epoch': epoch, 'soc': prc, 'battery_full': batt_full, 'charging': charging}
+        print(name, new_row)
+        clean_data[name].append(new_row)
+    print(names)
+    for lst in clean_data.values():
+        lst.sort(key=lambda x: x['epoch'])
+    save_to_json_file('clean_data.json', clean_data)
+
+
+if __name__ == '__main__':
+    main()

show_data.py

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+#!/usr/bin/python
+# -*- coding: utf-8 -*-
+import matplotlib.pyplot as plt
+import matplotlib.dates as mdates
+import matplotlib.patches as mpatches
+
+from astral import LocationInfo
+from astral.sun import sun
+
+import datetime
+from json_extensions import load_from_json_file
+
+
+city = LocationInfo("Rome", "Italy", "Europe/Rome", 44.448066, 11.270639)
+
+
+def main(data):
+    # Sample data
+    # epoch_times = [1696000000, 1696086400, 1696172800, 1696259200]  # Epoch seconds
+    # y_values = [10, 20, 15, 25]  # Some y-axis values
+
+    # Create the plot
+    fig, ax = plt.subplots(tight_layout=False, figsize=(30, 10))
+    earliest = None
+    latest = None
+    for name_raw, serie in data.items():
+        if name_raw in ('Security Camera', 'Ext Front'):
+            continue
+        name = {'Front door': 'Sample #1 No PV panel', 'Ext2': 'Sample #2 with PV Panel', }.get(name_raw, name_raw)
+        dates = [datetime.datetime.fromtimestamp(row['epoch']) for row in serie]
+        soc_v = [row['soc'] for row in serie]
+        if name_raw == 'Front door':
+            dates = dates[3:]
+            soc_v = soc_v[3:]
+        mi = min(dates)
+        ma = max(dates)
+        if earliest is None:
+            earliest = mi
+            latest = ma
+        else:
+            earliest = min(earliest, mi)
+            latest = max(latest, ma)
+
+        # charging = [row['charging'] for row in serie]
+        # batt_full = [row['battery_full'] for row in serie]
+        #
+        # sizes = []
+        # for c1, c2 in zip(charging, batt_full):
+        #     if c1 and c2:
+        #         sizes.append(100)  # Example: Both conditions true
+        #     elif c1:
+        #         sizes.append(200)  # Example: Only condition 1 true
+        #     elif c2:
+        #         sizes.append(300)  # Example: Only condition 2 true
+        #     else:
+        #         sizes.append(400)  # Example: Both conditions false
+        #
+
+        ax.plot(dates, soc_v, '-o', lw=3, label=name)
+
+        # for x, y, color in zip(dates, soc_v, sizes):
+
+        # ax.plot(dates, y_values, marker='o', linestyle='-')
+
+    print(earliest, latest)
+    current_day = earliest
+    first_time = True
+    while current_day < latest:
+        # print(current_day)
+        # Get solar times
+        s = sun(city.observer, date=current_day, tzinfo=city.timezone)
+        dawn = s['dawn']
+        sunrise = s['sunrise']
+        sunset = s['sunset']
+        dusk = s['dusk']
+        if first_time:
+            ax.axvspan(dawn, sunrise, color='deepskyblue', alpha=0.3, label='Twilight (-6°)')
+            ax.axvspan(sunset, dusk, color='deepskyblue', alpha=0.3)
+            ax.axvline(sunrise, color='orange', linestyle='--', label='Sunrise')
+            ax.axvline(sunset, color='red', linestyle='--', label='Sunset')
+            first_time = False
+        else:
+            ax.axvspan(dawn, sunrise, color='deepskyblue', alpha=0.3)
+            ax.axvspan(sunset, dusk, color='deepskyblue', alpha=0.3)
+            ax.axvline(sunrise, color='orange', linestyle='--')
+            ax.axvline(sunset, color='red', linestyle='--')
+
+        current_day += datetime.timedelta(days=1)
+
+    # Format the x-axis as date
+    # ax.xaxis.set_major_formatter(mdates.DateFormatter('%Y-%m-%d\n%H:%M:%S'))  # Customize as needed
+    ax.xaxis.set_major_locator(
+        mdates.AutoDateLocator(minticks=30, maxticks=60))  # Automatically adjusts for readability
+    ax.xaxis.set_major_formatter(mdates.ConciseDateFormatter(ax.xaxis.get_major_locator()))
+
+    x_tail = datetime.datetime(year=2025, month=4, day=7, hour=7, minute=20)
+    y_tail = 85
+    x_head = datetime.datetime(year=2025, month=4, day=7, hour=6, minute=59)
+    y_head = 100
+    dx = x_head - x_tail
+    dy = y_head - y_tail
+
+    # Rotate date labels for better visibility
+    # plt.xticks(rotation=45)
+
+    arrow = mpatches.FancyArrowPatch((x_tail, y_tail), (x_head, y_head), mutation_scale=50)
+    ax.add_patch(arrow)
+
+    # Labels and title
+    ax.grid()
+    ax.legend(loc='lower right', framealpha=1.0)
+    plt.xlabel("Date & Time")
+    plt.ylabel("Reported State of Charge [%]")
+    plt.title('Camera battery behaviour')
+
+    img_num = 1
+    out_name = f'{img_num}_f11.png'
+    img_num += 1
+    fig.savefig(out_name, dpi=150)
+
+    st1 = datetime.datetime(year=2025, month=3, day=29)
+    end1 = datetime.datetime(year=2025, month=4, day=8, hour=12)
+    ax.set_xlim(st1, end1)
+    txt = f'Problems:\nSample#2: After FW upgrade the problem looks the same\nSample#1: Discharge is not monotonic.'
+    annt = ax.text(0.3, 0.1, txt, ha='left', fontsize=20, bbox={'facecolor': 'lightgray', 'alpha': 0.85, 'pad': 5},
+                   transform=ax.transAxes)
+    # annt.set_text(txt)
+    # print(txt)
+    out_name = f'{img_num}_overview.png'
+    # out_name_svg = f'{img_num}_overview.svg'
+    out_name_pdf = f'{img_num}_overview.pdf'
+    # fig.savefig(out_name_svg)
+    fig.savefig(out_name_pdf)
+    img_num += 1
+    fig.savefig(out_name, dpi=200)
+
+    #
+    # st1 = datetime.datetime(year=2025, month=3, day=1)
+    # end1 = datetime.datetime(year=2025, month=3, day=3)
+    # ax.set_xlim(st1, end1)
+    # txt = f'We noticed battery level anomaly'
+    # # print(txt)
+    # annt = ax.text(0.1, 0.2, txt, ha='left', fontsize=20, bbox={'facecolor': 'cyan', 'alpha': 0.7, 'pad': 5},
+    #         transform=ax.transAxes)
+    # print(annt, type(annt))
+    # out_name = f'{img_num}_first_anomaly.png'
+    # img_num += 1
+    # fig.savefig(out_name, dpi=150)
+    # # annt.remove()
+    #
+    # st1 = datetime.datetime(year=2025, month=3, day=17)
+    # end1 = datetime.datetime(year=2025, month=3, day=19)
+    # ax.set_xlim(st1, end1)
+    # txt = f'We noticed battery level anomaly Again!'
+    # annt.set_text(txt)
+    # # print(txt)
+    # out_name = f'{img_num}_second_anomaly.png'
+    # img_num += 1
+    # fig.savefig(out_name, dpi=150)
+    #
+    # st1 = datetime.datetime(year=2025, month=3, day=19)
+    # end1 = datetime.datetime(year=2025, month=4, day=1)
+    # ax.set_xlim(st1, end1)
+    # txt = f'We unplugged the PV panel as asked by supplier'
+    # annt.set_text(txt)
+    # # print(txt)
+    # out_name = f'{img_num}_unplugged.png'
+    # img_num += 1
+    # fig.savefig(out_name, dpi=150)
+    #
+    # st1 = datetime.datetime(year=2025, month=3, day=29)
+    # end1 = datetime.datetime(year=2025, month=4, day=1)
+    # ax.set_xlim(st1, end1)
+    # txt = f'We started testing a second sample'
+    # annt.set_text(txt)
+    # # print(txt)
+    # out_name = f'{img_num}_Sample2.png'
+    # img_num += 1
+    # fig.savefig(out_name, dpi=150)
+    #
+    # st1 = datetime.datetime(year=2025, month=3, day=30, hour=17, minute=30)
+    # end1 = datetime.datetime(year=2025, month=3, day=31, hour=9, minute=30)
+    # ax.set_xlim(st1, end1)
+    # txt = f'There are Anomalies in the evening and in the morning'
+    # annt.set_text(txt)
+    # # print(txt)
+    # out_name = f'{img_num}_Sample2_detail1.png'
+    # img_num += 1
+    # fig.savefig(out_name, dpi=150)
+    #
+    # st1 = datetime.datetime(year=2025, month=3, day=31, hour=15, minute=30)
+    # end1 = datetime.datetime(year=2025, month=4, day=1, hour=10)
+    # ax.set_xlim(st1, end1)
+    # txt = f'Second day Sample#2 still show anomaly\nSample#1 has increasing battery level (Impossible)'
+    # annt.set_text(txt)
+    # # print(txt)
+    # out_name = f'{img_num}_Sample2_detail2.png'
+    # img_num += 1
+    # fig.savefig(out_name, dpi=150)
+
+    # Show the plot
+    # plt.show()
+
+
+if __name__ == '__main__':
+    cln_data = load_from_json_file('clean_data.json')
+    main(cln_data)

test_twilight.py

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+#!/usr/bin/python
+# -*- coding: utf-8 -*-
+import matplotlib.pyplot as plt
+import numpy as np
+import matplotlib.dates as mdates
+from datetime import datetime, timedelta
+from astral import LocationInfo
+from astral.sun import sun
+
+
+def main():
+    # Set your location
+    city = LocationInfo("Rome", "Italy", "Europe/Rome", 44.448066, 11.270639)
+
+    # Choose the date
+    # date = datetime(2023, 3, 29)
+    # dawn: 2023-03-29 06:32:45.166761+02:00
+    # sunrise: 2023-03-29 07:02:31.106176+02:00
+    # noon: 2023-03-29 13:19:52+02:00
+    # sunset: 2023-03-29 19:37:45.931604+02:00
+    # dusk: 2023-03-29 20:07:37.090448+02:00
+    date = datetime(2023, 3, 29)
+
+    # Get solar times
+    s = sun(city.observer, date=date, tzinfo=city.timezone)
+    for k, v in s.items():
+        print(f'{k}: {v}')
+    dawn = s['dawn']
+    sunrise = s['sunrise']
+    sunset = s['sunset']
+    dusk = s['dusk']
+
+    # Generate time series data for one day
+    times = [date + timedelta(minutes=15 * i) for i in range(96 * 1)]
+    values = np.sin(np.linspace(0, 4 * np.pi, len(times)))  # Some mock data
+
+    # Create the plot
+    fig, ax = plt.subplots(figsize=(10, 5))
+    ax.plot(times, values, label="Sensor Data", color='tab:blue')
+
+    # Plot twilight periods as vertical bands
+    ax.axvspan(dawn, sunrise, color='lightskyblue', alpha=0.3, label='Morning Twilight')
+    ax.axvspan(sunset, dusk, color='lightskyblue', alpha=0.3, label='Evening Twilight')
+
+    # Mark sunrise and sunset
+    ax.axvline(sunrise, color='orange', linestyle='--', label='Sunrise')
+    ax.axvline(sunset, color='red', linestyle='--', label='Sunset')
+
+    # Formatting
+    ax.set_title(f"Daylight and Twilight - {city.name} on {date.strftime('%Y-%m-%d')}")
+    ax.set_xlabel("Time")
+    ax.set_ylabel("Sensor Value")
+    ax.xaxis.set_major_formatter(mdates.DateFormatter('%H:%M'))
+    plt.xticks(rotation=45)
+    plt.legend()
+    plt.tight_layout()
+    plt.show()
+
+
+if __name__ == '__main__':
+    main()