Нахождение увеличения от «базовой линии» на графике, не знаю, как это сделать

введите описание изображения здесь

Я хочу написать алгоритм, который выплевывает точки, выделенные стрелками. Я попытался использовать вторую производную, но она возвращает график, похожий на приведенный выше, и не уверен, как его использовать.

Привет, извините за это, я не хочу пиков, я хочу точку, где график начинает увеличиваться - т.е. я хочу точку, где градиент изменяется от ~ 0 до чего-то большего, имеет ли это смысл

Пример данных приведен ниже.

df = structure(list(X1 = c("2729", "2730", "2731", "2732", "2733", 
"2734", "2735", "2736", "2737", "2738", "2739", "2740", "2741", 
"2742", "2743", "2744", "2745", "2746", "2747", "2748", "2749", 
"2750", "2751", "2752", "2753", "2754", "2755", "2756", "2757", 
"2758", "2759", "2760", "2761", "2762", "2763", "2764", "2765", 
"2766", "2767", "2768", "2769", "2770", "2771", "2772", "2773", 
"2774", "2775", "2776", "2777", "2778", "2779", "2780", "2781", 
"2782", "2783", "2784", "2785", "2786", "2787", "2788", "2789", 
"2790", "2791", "2792", "2793", "2794", "2795", "2796", "2797", 
"2798", "2799", "2800", "2801", "2802", "2803", "2804", "2805", 
"2806", "2807", "2808", "2809", "2810", "2811", "2812", "2813", 
"2814", "2815", "2816", "2817", "2818", "2819", "2820", "2821", 
"2822", "2823", "2824", "2825", "2826", "2827", "2828", "2829", 
"2830", "2831", "2832", "2833", "2834", "2835", "2836", "2837", 
"2838", "2839", "2840", "2841", "2842", "2843", "2844", "2845", 
"2846", "2847", "2848", "2849", "2850", "2851", "2852", "2853", 
"2854", "2855", "2856", "2857", "2858", "2859", "2860", "2861", 
"2862", "2863", "2864", "2865", "2866", "2867", "2868", "2869", 
"2870", "2871", "2872", "2873", "2874", "2875", "2876", "2877", 
"2878", "2879", "2880", "2881", "2882", "2883", "2884", "2885", 
"2886", "2887", "2888", "2889", "2890", "2891", "2892", "2893", 
"2894", "2895", "2896", "2897", "2898", "2899", "2900", "2901", 
"2902", "2903", "2904", "2905", "2906", "2907", "2908", "2909", 
"2910", "2911", "2912", "2913", "2914", "2915", "2916", "2917", 
"2918", "2919", "2920", "2921", "2922", "2923", "2924", "2925", 
"2926", "2927", "2928", "2929", "2930", "2931", "2932", "2933", 
"2934", "2935", "2936", "2937", "2938", "2939", "2940", "2941", 
"2942", "2943", "2944", "2945", "2946", "2947", "2948", "2949", 
"2950", "2951", "2952", "2953", "2954", "2955", "2956", "2957", 
"2958", "2959", "2960", "2961", "2962", "2963", "2964", "2965", 
"2966", "2967", "2968", "2969", "2970", "2971", "2972", "2973", 
"2974", "2975", "2976", "2977", "2978", "2979", "2980", "2981", 
"2982", "2983", "2984", "2985", "2986", "2987", "2988", "2989", 
"2990", "2991", "2992", "2993", "2994", "2995", "2996", "2997", 
"2998", "2999", "3000", "3001", "3002", "3003", "3004", "3005", 
"3006", "3007", "3008", "3009", "3010", "3011", "3012", "3013", 
"3014", "3015", "3016", "3017", "3018", "3019", "3020", "3021", 
"3022", "3023", "3024", "3025", "3026", "3027", "3028", "3029", 
"3030", "3031", "3032", "3033", "3034", "3035", "3036", "3037", 
"3038", "3039", "3040", "3041", "3042", "3043", "3044", "3045", 
"3046", "3047", "3048", "3049", "3050", "3051", "3052", "3053", 
"3054", "3055", "3056", "3057", "3058", "3059", "3060", "3061", 
"3062", "3063", "3064", "3065", "3066", "3067", "3068", "3069", 
"3070", "3071", "3072", "3073", "3074", "3075", "3076", "3077", 
"3078", "3079", "3080", "3081", "3082", "3083", "3084", "3085", 
"3086", "3087", "3088", "3089", "3090", "3091", "3092", "3093", 
"3094", "3095", "3096", "3097", "3098", "3099", "3100", "3101", 
"3102", "3103", "3104", "3105", "3106", "3107", "3108", "3109", 
"3110", "3111", "3112", "3113", "3114", "3115", "3116", "3117", 
"3118", "3119", "3120", "3121", "3122", "3123", "3124", "3125", 
"3126", "3127", "3128", "3129", "3130", "3131", "3132", "3133", 
"3134", "3135", "3136", "3137", "3138", "3139", "3140", "3141", 
"3142", "3143", "3144", "3145", "3146", "3147", "3148", "3149", 
"3150", "3151", "3152", "3153", "3154", "3155", "3156", "3157", 
"3158", "3159", "3160", "3161", "3162", "3163", "3164", "3165", 
"3166", "3167", "3168", "3169", "3170", "3171", "3172", "3173", 
"3174", "3175", "3176", "3177", "3178", "3179", "3180", "3181", 
"3182", "3183", "3184", "3185", "3186", "3187", "3188", "3189", 
"3190", "3191", "3192", "3193", "3194", "3195", "3196", "3197", 
"3198", "3199", "3200", "3201", "3202", "3203", "3204", "3205", 
"3206", "3207", "3208", "3209", "3210", "3211", "3212", "3213", 
"3214", "3215", "3216", "3217", "3218", "3219", "3220", "3221", 
"3222", "3223", "3224", "3225", "3226", "3227", "3228", "3229", 
"3230", "3231", "3232", "3233", "3234", "3235", "3236", "3237", 
"3238", "3239", "3240", "3241", "3242", "3243", "3244", "3245", 
"3246", "3247", "3248", "3249", "3250", "3251", "3252", "3253", 
"3254", "3255", "3256", "3257", "3258", "3259", "3260", "3261", 
"3262", "3263", "3264", "3265", "3266", "3267", "3268", "3269", 
"3270", "3271", "3272", "3273", "3274", "3275", "3276", "3277", 
"3278", "3279", "3280", "3281", "3282", "3283", "3284", "3285", 
"3286", "3287", "3288", "3289", "3290", "3291", "3292", "3293", 
"3294", "3295", "3296", "3297", "3298", "3299", "3300", "3301", 
"3302", "3303", "3304", "3305", "3306", "3307", "3308", "3309", 
"3310", "3311", "3312", "3313", "3314", "3315", "3316", "3317", 
"3318", "3319", "3320", "3321", "3322", "3323", "3324", "3325", 
"3326", "3327", "3328", "3329", "3330", "3331", "3332", "3333", 
"3334", "3335", "3336", "3337", "3338", "3339", "3340", "3341", 
"3342", "3343", "3344", "3345", "3346", "3347", "3348", "3349", 
"3350", "3351", "3352", "3353", "3354", "3355", "3356", "3357", 
"3358", "3359", "3360", "3361", "3362", "3363", "3364", "3365", 
"3366", "3367", "3368", "3369", "3370", "3371", "3372", "3373", 
"3374", "3375", "3376", "3377", "3378", "3379", "3380", "3381", 
"3382", "3383", "3384", "3385", "3386", "3387", "3388", "3389", 
"3390", "3391", "3392", "3393", "3394", "3395", "3396", "3397", 
"3398", "3399", "3400", "3401", "3402", "3403", "3404", "3405", 
"3406", "3407", "3408", "3409", "3410", "3411", "3412", "3413", 
"3414", "3415", "3416", "3417", "3418", "3419", "3420", "3421", 
"3422", "3423", "3424", "3425", "3426", "3427", "3428", "3429", 
"3430", "3431", "3432", "3433", "3434", "3435", "3436", "3437", 
"3438", "3439", "3440", "3441", "3442", "3443", "3444", "3445"
), X2 = c(-0.00385000000001254, -0.0154500000000484, -0.0277600000000007, 
-0.0154500000000279, -0.0386000000000704, -0.0154500000000329, 
-0.0115500000000053, 2.5238009638656e-15, -0.00385000000000757, 
3.60475000000867, -0.470850000000881, -0.347350000000663, -0.173700000000328, 
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-0.0115500000000196, -0.0116000000000154, -0.0154500000000366, 
-0.00385000000000946, -0.0193000000000305, -0.00390000000000946, 
-0.00390000000000639, -0.00771000000000015, -0.000789999999999225, 
-4.97400384373025e-15, -0.00619000000000085, -0.0116000000000265, 
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-0.00385000000001751, -0.0146699999999988, -0.00619000000000085, 
-0.0116000000000265, 0.00153999999999996, 0.00385000000000546, 
-0.00231000000000233, -0.000780000000000314, -0.00230999999999884, 
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-0.00385000000001751, -0.00775000000003729, -0.00769999999999792, 
-1.1787959787484e-15, -0.00384999999999692, 0.00385000000001136, 
-0.00384999999999762, 0.00385000000000639, -0.00385000000001161, 
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0, -0.0154500000000091, -0.0077500000000059, -0.0154500000000335, 
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0.0116000000000272, -0.00230999999999994, 0.0116000000000172, 
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-0.0347500000000721, -0.0347500000000142, -0.00385000000001161, 
0.00770000000000401, -0.00385000000000197, 0.000769999999999982, 
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Всего 2 ответа


Как уже говорили другие, не ясно, что вы ищете. в частности, не ясно, насколько высоко над «базовой линией» слишком много.

Вот выстрел в это:

df_prime <- df$X2[-1] - df$X2[-length(df$X2)]
large_rise <- which(df_prime > sd(df_prime) & df$X2[-length(df$X2)] > -sd(df$X2))
df$X1[large_rise]

введите описание изображения здесь


Сложно понять по этому вопросу, но разве вы не ищете что-то подобное?

spikes <- as.numeric(df$X1[df$X2 > 0.1])
spikes <- spikes[which(diff(c(0, spikes)) > 3)]
spikes
#> [1] 2738 2758 2984 2994 3126 3139 3190 3260 3273 3309 3316 3363 3377

Так, например, если вы сделали

plot(df$X1, df$X2, type = "l")
points(spikes, rep(1, length(spikes)), col="red")

Вы бы получили введите описание изображения здесь


Есть идеи?

10000