from test import downloadImg, getAllFields, getTestFileName, updateData
from create_instructions import isCloudyImg, getRedZones


# clean zones & cloudy
def clearZonesOfAllFields(uid):
    allFields = getAllFields(uid)
    # print(allFields)
    m = 0
    for fieldID, data in allFields.items():
        m += 1
        if m % 100 == 0:
            print(fieldID, m)
        # if m < 100:
        #   continue
        # print(fieldID)
        # if fieldID == '1680665632852':
        #    continue
        sensed_days_obj = data["SensedDays"]
        for lastDate, latest_day_obj in sensed_days_obj.items():
        #latest_day_obj = data["SensedDays"]
        # print(latest_day_obj)
        # latest_sar_days_obj =data.get("SARDays",{})
        # print(latest_sar_days_obj)
            #dates = list(latest_day_obj.keys())
            # sar_dates = list(latest_sar_days_obj.keys())
            # print(dates, sar_dates)
            # lastSARDate = sar_dates[len(sar_dates) - 1] if len(sar_dates) > 0 else None
            #lastDate = dates[len(dates) - 1] if len(dates) > 0 else None

            if lastDate == None:
                continue
            # if lastSARDate == None:
            #   continue
            # print("1")

            # get ndvi, tci; then isCloudy
            try:
                downloadImg(uid, fieldID, lastDate, "ndvi")
                downloadImg(uid, fieldID, lastDate, "tci")
            except:
                isCloudy = True

            ndviPath = getTestFileName(uid, "ndvi")
            tciPath = getTestFileName(uid, "tci")
            try:
                isCloudy = isCloudyImg(tciPath, ndviPath)
            except:
                isCloudy = True
            # print("2")

            # isCloudy2 = (
            #     None
            #     if type(latest_day_obj[lastDate]) == str
            #     else latest_day_obj[lastDate].get("isCloudy", None)
            # )

            # check is isCloudy is same
            if True:  # isCloudy2 != isCloudy:
                # get new zones & udpate it to DB
                health = data["Health"]

                ndviAvgVal = health["ndvi"][lastDate]
                ndwiAvgVal = health["ndwi"][lastDate]
                # print("ndvi, ndmi: ", ndviAvgVal, ndwiAvgVal)
                isSmallPlant = float(ndviAvgVal) < 40 and float(ndwiAvgVal) < 40

                if isCloudy:
                    if False:
                        # get rvi, rsm cmap2
                        downloadImg(uid, fieldID, lastDate, "rvi_cmap2")
                        downloadImg(uid, fieldID, lastDate, "rsm_cmap2")

                        cropPath = getTestFileName(uid, "rvi_cmap2")
                        irriPath = getTestFileName(uid, "rsm_cmap2")
                    else:
                        # get rvi, rsm
                        # if lastSARDate == None:
                        #   print("sar date is none", fieldID)
                        #  continue
                        try:
                            downloadImg(uid, fieldID, lastDate, "rvi")
                            downloadImg(uid, fieldID, lastDate, "rsm")
                        except:
                            print("rvi not found", fieldID, lastDate)
                            continue

                        cropPath = getTestFileName(uid, "rvi")
                        irriPath = getTestFileName(uid, "rsm")
                else:
                    if isSmallPlant:
                        # get ndvi, ndwi cmap2
                        downloadImg(uid, fieldID, lastDate, "ndvi_cmap2")
                        downloadImg(uid, fieldID, lastDate, "ndwi_cmap2")

                        cropPath = getTestFileName(uid, "ndvi_cmap2")
                        irriPath = getTestFileName(uid, "ndwi_cmap2")
                    else:
                        # get ndwi
                        downloadImg(uid, fieldID, lastDate, "ndwi")
                        ndwiPath = getTestFileName(uid, "ndwi")

                        cropPath = ndviPath
                        irriPath = ndwiPath

                # print("starting redzones cal")
                cropZones = getRedZones(cropPath, isCmap2=isSmallPlant and not isCloudy)
                irriZones = getRedZones(irriPath, isCmap2=isSmallPlant and not isCloudy)

                finalData = {
                    "cropRedZones": "empty" if len(cropZones) == 0 else cropZones,
                    "irrigationRedZones": "empty" if len(irriZones) == 0 else irriZones,
                    "isCloudy": isCloudy,
                }
                # print(finalData, isSmallPlant)
                updateData(f"{uid}/{fieldID}/SensedDays/{lastDate}", finalData)


uid = "M53J9SImW9My4vghlCaaWLYxsc22"
uid = "sAiJIWRbNOR5grDmRabVxW5BXp03"
uid = "OvNqMOrqpKQeaRsj2ByVx2AABK92"
uid = "6U2L0EV2mKXXh7xmQBlbyxTgltd2"
uid = "ENLgcB9pl2fH7MjsEH7oc72YBRh2"
clearZonesOfAllFields(uid)