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https://gitlab.com/Luci_/arduino-photometrics.git
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add changes before migration on fablab cohabit
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@ -18,15 +18,15 @@ liste_data <- lapply(fichiers, read.csv, header = TRUE)
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summary(liste_data)
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print(typeof(liste_data))
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# partial_list_data <- liste_data[1:2]
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partial_list_data <- liste_data[7:8]
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partial_list_data <- liste_data[3:3]
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# partial_list_data <- liste_data[7:8]
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photo <- do.call(rbind, partial_list_data)
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max_val_sensor = 254
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photo <- photo %>%
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mutate(across(starts_with("Photo_sensor"), ~ {
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# .x <- sqrt(.x)
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# max_val_sensor = sqrt(max_val_sensor)
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.x <- sqrt(.x)
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max_val_sensor = sqrt(max_val_sensor)
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.x <- (.x*-1) + max_val_sensor
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.x <- as.numeric(scale(.x, center = TRUE, scale = TRUE))
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}))
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@ -1,4 +1,5 @@
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# install.packages('randomForest')
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# install.packages(c('neuralnet','keras','tensorflow'),dependencies = T)
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library(tidyverse)
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library(ggplot2)
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@ -6,12 +7,13 @@ library(lubridate)
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library(dplyr)
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library(randomForest)
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library(suntools)
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library(neuralnet)
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setwd("~/Documents/PlatformIO/Projects/Robot_Go_West/arduino-photometrics/exec")
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# Load
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# solar <- read.csv("../data/solar_pos_data/solar_data_2026-01-13_to_2026-01-16.csv", header=TRUE)
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photo <- read.csv("../data/photo_measures/arduino_data_package_auto_20260116_094653.csv", header=TRUE)
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photo <- read.csv("../data/photo_measures/merged_photo_data.csv", header=TRUE)
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# Time type changes
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# photo$time <- as.POSIXct(photo$Epoch)
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@ -48,7 +50,6 @@ photo <- photo %>%
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# retreive solar pos
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unix_time <- as.numeric(photo$datetime)
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lat <- 44.7912
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@ -129,3 +130,24 @@ test_random_results$predicted_azimut <- test_random_predictions
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head(test_random_results[, c("azimut", "predicted_azimut")])
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head(test_chrono_results[, c("azimut", "predicted_azimut")])
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comparison_chrono <- test_chrono_results[, c("azimut", "predicted_azimut", "timestamp", "decimal_hour")]
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# comparison_chrono$list = abs(comparison_chrono$azimut - comparison_chrono$predicted_azimut)
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# print(length(comparison_chrono$list))
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# print(as.integer(sum(comparison_chrono$list)))
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# mean_before_filter <- as.integer(sum(comparison_chrono$list)) / length(comparison_chrono$list)
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#
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comparison_chrono <- comparison_chrono %>%
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filter(decimal_hour > 7.0) %>%
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filter(decimal_hour < 20.0)
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comparison_chrono$comp <- abs(comparison_chrono$azimut - comparison_chrono$predicted_azimut)
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mean <- sum(comparison_chrono$comp) / length(comparison_chrono$comp)
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print(typeof(comparison_chrono))
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print(random_model)
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print(chrono_model)
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@ -10,7 +10,7 @@ class Storage_interface
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private:
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static constexpr uint8_t OFFSET_MEASURES_SCH = 1, OFFSET_NB_PHOTO_SENSOR = 2, OFFSET_NB_TEMP_SENSOR = 3, OFFSET_PHOTO_MEASURES_SIZE = 4, OFFSET_TEMP_MEASURES_SIZE = 5, OFFSET_NB_MEASURES = 6, OFFSET_NEXT_PACKAGE = 8, OFFSET_START_DATA_MEASURES = 10; // unit in byte
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static constexpr uint16_t MEGA_2560_EEPROM_SIZE = 4000; // bytes
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static constexpr uint16_t MEGA_2560_EEPROM_SIZE = 4096; // bytes
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void clear_eeprom_at(uint16_t idx);
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photos/1768293109490.jpeg
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photos/1768293109490.jpeg
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photos/PXL_20251217_135345575.jpg
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photos/PXL_20251217_135345575.jpg
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photos/PXL_20260113_081652912.MP.jpg
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photos/PXL_20260113_081652912.MP.jpg
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