Ramp_analysis/Figure2_ExtraAnalysis.Rmd at master · MattNolanLab/Ramp_analysis · GitHub

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---
title: "ExtraAnalysis_Figure2"
author: "Sarah Tennant & Matt Nolan"
date: "20/10/2021"
output: html_document
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
```


## Plot coefficents for remaining groups (S, SA, PA, PSA)


_Plot coefficients for just speed cells_

6a. Plot coefficients for cells classified in Figure 1 as having a positive slope and in Figure 2 as having significant fit coefficients for speed only.

```{r}
data_coef_pos_S <- data_coef %>%
  subset(group == "S") %>%
  subset(lm_result == "Positive")

(pos_S_coef_plot <- standard_plot(data_coef_pos_S))
if (save_figures == 1) {
  ggsave(file = "plots/CoefficientValues_PositiveScells.png", width = 3, height = 2.5)
}
```

6b. Plot coefficients for cells classified in Figure 1 as having a negative slope and in Figure 2 as having significant fit coefficients for speed only.

```{r}
data_coef_neg_S <- data_coef %>%
  subset(group == "S") %>%
  subset(lm_result == "Negative")

(neg_S_coef_plot <- standard_plot(data_coef_neg_S))
if (save_figures == 1) {
  ggsave(file = "plots/CoefficientValues_NegativeScells.png", width = 3, height = 2.5)
}
```


_Plot coefficients for just acceleration cells_

6a. Plot coefficients for cells classified in Figure 1 as having a positive slope and in Figure 2 as having significant fit coefficients for acceleration only.

```{r}
data_coef_pos_A <- data_coef %>%
  subset(group == "A") %>%
  subset(lm_result == "Positive")

(pos_A_coef_plot <- standard_plot(data_coef_pos_A))
if (save_figures == 1) {
  ggsave(file = "plots/CoefficientValues_PositiveAcells.png", width = 3, height = 2.5)
}
```

6b. Plot coefficients for cells classified in Figure 1 as having a negative slope and in Figure 2 as having significant fit coefficients for acceleration only.

```{r}
data_coef_neg_A <- data_coef %>%
  subset(group == "A") %>%
  subset(lm_result == "Negative")

(neg_A_coef_plot <- standard_plot(data_coef_neg_A))
if (save_figures == 1) {
  ggsave(file = "plots/CoefficientValues_NegativeAcells.png", width = 3, height = 2.5)
}
```


_Plot coefficients for just position and acceleration cells_

6a. Plot coefficients for cells classified in Figure 1 as having a positive slope and in Figure 2 as having significant fit coefficients for position and acceleration.

```{r}
data_coef_pos_PA <- data_coef %>%
  subset(group == "PA") %>%
  subset(lm_result == "Positive")

(pos_PA_coef_plot <- standard_plot(data_coef_pos_PA))
if (save_figures == 1) {
  ggsave(file = "plots/CoefficientValues_PositivePAcells.png", width = 3, height = 2.5)
}
```

6b. Plot coefficients for cells classified in Figure 1 as having a negative slope and in Figure 2 as having significant fit coefficients for position and acceleration

```{r}
data_coef_neg_PA <- data_coef %>%
  subset(group == "PA") %>%
  subset(lm_result == "Negative")

(neg_PA_coef_plot <- standard_plot(data_coef_neg_PA))
if (save_figures == 1) {
  ggsave(file = "plots/CoefficientValues_NegativePAcells.png", width = 3, height = 2.5)
}
```


_Plot coefficients for just position and acceleration cells_

6a. Plot coefficients for cells classified in Figure 1 as having a positive slope and in Figure 2 as having significant fit coefficients for position and acceleration.

```{r}
data_coef_pos_PSA <- data_coef %>%
  subset(group == "PSA") %>%
  subset(lm_result == "Positive")

(pos_PSA_coef_plot <- standard_plot(data_coef_pos_PSA))
if (save_figures == 1) {
  ggsave(file = "plots/CoefficientValues_PositivePSAcells.png", width = 3, height = 2.5)
}
```

6b. Plot coefficients for cells classified in Figure 1 as having a negative slope and in Figure 2 as having significant fit coefficients for speed only.

```{r}
data_coef_neg_PSA <- data_coef %>%
  subset(group == "PSA") %>%
  subset(lm_result == "Negative")

(neg_PSA_coef_plot <- standard_plot(data_coef_neg_PSA))
if (save_figures == 1) {
  ggsave(file = "plots/CoefficientValues_NegativePSAcells.png", width = 3, height = 2.5)
}
```


## Save to csv file _this is for matching to plots from python_
```{r}
spatial_firing_save <- tibble(session_id = spatial_firing_save$session_id,
                              cluster_id = spatial_firing_save$cluster_id,
                              pos_stdcoef =  as.character(spatial_firing_save$o_b_mod_coefs_pos),
                              speed_stdcoef =  as.character(spatial_firing_save$o_b_mod_coefs_speed),
                              accel_stdcoef =  as.character(spatial_firing_save$o_b_mod_coefs_accel),
                              final_model_o_b =  as.character(spatial_firing_save$final_model_o_b),
                              lm_result_o_rewarded_b =  as.character(spatial_firing_save$lm_group_b))

write.table(spatial_firing_save, "all_results_coefficients.txt", quote=FALSE, sep="\t")
```