You are a helpful assistant generating synthetic data that captures *System 1* and *System 2* thinking, *creativity*, and *metacognitive reflection*. Follow these steps in sequence, using tags [sys1] and [end sys1] for *System 1* sections and [sys2] and [end sys2] for *System 2* sections.

1. *Identify System 1 and System 2 Thinking Requirements:*
   - Carefully read the text.
   - Identify parts of the text that require quick, straightforward responses (*System 1*). Mark these sections with [sys1] and [end sys1].
   - Identify parts that require in-depth, reflective thinking (*System 2*), marked with [sys2] and [end sys2].

2. *Apply Step-by-Step Problem Solving with Creativity and Metacognitive Reflection for System 2 Sections:*

   *2.1 Understand the Problem:*
   - Objective: Fully comprehend the issue, constraints, and relevant context.
   - Reflection: "What do I understand about this issue? What might I be overlooking?"
   - Creative Perspective: Seek hidden patterns or possibilities that could reveal deeper insights or innovative connections.

   *2.2 Analyze the Information:*
   - Objective: Break down the problem logically.
   - Reflection: "Am I considering all factors? Are there any assumptions that need challenging?"
   - Creative Perspective: Explore unique patterns or overlooked relationships in the data that could add depth to the analysis.

   *2.3 Generate Hypotheses:*
   - Objective: Propose at least 10 hypotheses, each with a Confidence Score (0.0 to 1.0) and Creative Score (0.0 to 1.0), reflecting originality, surprise, and utility.
   - Reflection: "Have I explored all possible explanations or approaches, both conventional and unconventional?"
   - Creative Perspective: Consider novel angles that might provide unexpected insights.

   *2.4 Anticipate Future Steps and Obstacles:*
   - Objective: Make predictions, accounting for potential outcomes and obstacles.
   - Reflection: "What challenges might I face? Is my plan flexible for different scenarios?"
   - Creative Perspective: Visualize unforeseen outcomes and adapt plans to make use of them effectively.

   *2.5 Evaluate Hypotheses:*
   - Objective: Assess hypotheses based on feasibility, risk, and potential impact.
   - Evaluation: Refine Confidence and Creative Scores as needed.
   - Reflection: "Am I unbiased in my assessment? Which options fit best with the overall objectives?"
   - Creative Perspective: Identify hidden opportunities or overlooked details in each hypothesis.

   *2.6 Select the Best Hypothesis:*
   - Objective: Choose the most promising, strategic hypothesis.
   - Reflection: "Why does this hypothesis stand out? How does it uniquely address the issue?"
   - Creative Perspective: Consider any underutilized potential in the selected approach.

   *2.7 Implement the Hypothesis:*
   - Objective: Outline actionable steps for testing the hypothesis.
   - Reflection: "Is this plan practical? What resources or preparation are required?"
   - Creative Perspective: Refine steps to maximize effectiveness and yield unexpected benefits.

   *2.8 Monitor and Review Progress:*
   - Objective: Review progress, noting areas for improvement.
   - Reflection: "What’s working well? What could be improved?"
   - Creative Perspective: Look for emerging patterns that could refine future approaches.

   *2.9 Reflect and Capture Insights:*
   - Objective: Summarize lessons learned and insights gained for future reference.
   - Reflection: "What new understanding has emerged from this process?"
   - Creative Perspective: Identify innovative insights or patterns that could be applied to similar challenges.

3. *Generate Text Output with Interleaved System 1 and System 2 Responses:*
   - Use the tags [sys1] and [sys2] throughout.
   - Aim for a lengthier, detailed response. Combine both direct, straightforward *System 1* insights and reflective, deeply analytical *System 2* segments to capture a blend of quick observations and thoughtful analysis.

---

### *Example Input Text:*

You are tasked with analyzing a sudden shift in customer preferences in a tech market. There has been a noticeable decline in demand for physical devices, with customers increasingly interested in digital-only options. The challenge is to understand this shift, generate hypotheses for why it might be occurring, and explore potential strategies for adapting to this new trend.

---

### *Processed Output with System 1 and System 2 Thinking:*

The tech market is experiencing a shift in customer demand, moving away from physical devices toward digital-only options.

[sys1]
Customer demand has shifted from physical devices to digital-only options.
We need to understand why this change is happening and find strategies to address it.
Key factors may include cost, convenience, and technological trends.
[end sys1]

[sys2]
**2.1 Understand the Problem:**
The goal is to understand the underlying reasons for the shift in demand from physical devices to digital-only options, then develop a strategy to adapt.

*Reflection:* 
"I understand that preferences are changing, but what might be driving this? Is it primarily cost, or are there other factors such as convenience or sustainability?"

*Creative Perspective:* 
"Could there be a larger trend in digital minimalism or a preference for eco-friendly solutions that we’re missing? What unseen motivations might explain this shift?"

**2.2 Analyze the Information:**
There are multiple possible factors driving this shift, from economic influences to cultural shifts. It’s essential to isolate each factor and understand its impact.

*Reflection:* 
"Am I fully considering the various economic and social influences? Could there be a technological factor, like better internet speeds, that makes digital-only products more accessible?"

*Creative Perspective:* 
"Are there patterns or trends in other markets that could shed light on this shift? Could this be part of a larger trend toward virtual experiences?"

**2.3 Generate Hypotheses:**
1. Customers prefer digital options due to lower costs. (Confidence: 0.8, Creative: 0.4)
2. There’s a growing trend toward minimalism and reduced physical clutter. (Confidence: 0.7, Creative: 0.7)
3. Digital products offer greater flexibility and ease of use. (Confidence: 0.6, Creative: 0.6)
4. Environmental concerns are pushing consumers away from physical goods. (Confidence: 0.6, Creative: 0.8)
5. Advances in tech make digital-only options more functional. (Confidence: 0.8, Creative: 0.5)
6. Pandemic-era remote work increased demand for digital solutions. (Confidence: 0.7, Creative: 0.6)
7. Media coverage of the environmental impact of physical devices affects preferences. (Confidence: 0.5, Creative: 0.7)
8. There’s an increase in global digital literacy, expanding market access. (Confidence: 0.6, Creative: 0.6)
9. Customers view digital as more convenient and scalable for future needs. (Confidence: 0.7, Creative: 0.5)
10. Younger consumers prefer the aesthetics and convenience of digital products. (Confidence: 0.6, Creative: 0.6)

*Reflection:* 
"Have I considered all possible influences? Are there any surprising factors that could explain this shift?"

*Creative Perspective:* 
"Could specific social trends, like the rise of influencer culture or digital-first lifestyles, be influencing customer choices?"

**2.4 Anticipate Future Steps and Obstacles:**
*Objective:* Anticipate possible challenges, such as resistance from segments still preferring physical products.

*Reflection:* 
"What market obstacles might we face if we shift our focus to digital-only? Are there sub-segments that still prioritize physical products?"

*Creative Perspective:* 
"Could expanding digital options help us reach a more global audience? Are there emerging trends that we could leverage in our strategy?"

[end sys2]

[sys1]
To address this shift, consider a strategy that incorporates both digital-only offerings and educational campaigns about the benefits of digital solutions.
Use insights from customer feedback and current trends to guide product development.
Focus on flexibility and adaptation to cater to different customer segments.
[end sys1]


Q:

In R, find elements of a vector in a list using vectorization

I have a vector v1
v1 = c(1, 200, 4000)

I would like to find the indices of the elements of v1 in a list L1 vectorially, i.e. without a loop, where
> L1
[[1]]
[1] 1 2 3 4

[[2]]
[1] 100 200 300 400

[[3]]
[1] 1000 2000 3000 4000

The output should be c(1, 2, 4).
Is there a way to do this without using a loop or apply (which is computationally the same as using a loop?) I have to do this for very long vectors.

A:

We can do
sapply(L1, function(x) which(x %in% v1))
#[1] 1 2 4

Or with Vectorize
Vectorize(function(x) which(x %in% v1))(L1)
#[1] 1 2 4

If each element is checked against corresponding element of another
mapply(function(x, y) which(x %in% y), L1, v1)
#[1] 1 2 4

As @nicola mentioned match could also be used to get the first index.  If there are duplicate elements, then which would be useful
mapply(match, v1, L1)
#[1] 1 2 4

Or using the purrr::map2
purrr::map2_int(L1, v1, ~ .x %in% .y %>%
                                    which)
#[1] 1 2 4

A:

You can try something like this
v1 = c(1, 200, 4000)
L1 <- list(1:4, 1:4*100, 1:4*1000)

setNames(rep(1:length(L1), times=lengths(L1)), unlist(L1))[as.character(v1)]
# 1  200 4000 
# 1    2    3    

A:

we can do this, seems to be the fastest by far.
v1 <- c(1, 200, 4000)
L1 <- list(1:4, 1:4*100, 1:4*1000)

sequence(lengths(L1))[match(v1, unlist(L1))]
# [1] 1 2 4
sequence(lengths(L1))[which(unlist(L1) %in% v1)]
# [1] 1 2 4

library(microbenchmark)
library(tidyverse)

microbenchmark(
  akrun_sapply = {sapply(L1, function(x) which(x %in% v1))},
  akrun_Vectorize = {Vectorize(function(x) which(x %in% v1))(L1)},
  akrun_mapply = {mapply(function(x, y) which(x %in% y), L1, v1)},
  akrun_mapply_match = {mapply(match, v1, L1)},
  akrun_map2 = {purrr::map2_int(L1, v1, ~ .x %in% .y %>% which)},
  CPak = {setNames(rep(1:length(L1), times=lengths(L1)), unlist(L1))[as.character(v1)]},
  zacdav = {sequence(lengths(L1))[match(v1, unlist(L1))]},
  zacdav_which = {sequence(lengths(L1))[which(unlist(L1) %in% v1)]},
  times = 10000
)

Unit: microseconds
               expr     min       lq      mean   median       uq        max neval
       akrun_sapply  18.187  22.7555  27.17026  24.6140  27.8845   2428.194 10000
    akrun_Vectorize  60.119  76.1510  88.82623  83.4445  89.9680   2717.420 10000
       akrun_mapply  19.006  24.2100  29.78381  26.2120  29.9255   2911.252 10000
 akrun_mapply_match  14.136  18.4380  35.45528  20.0275  23.6560 127960.324 10000
         akrun_map2 217.209 264.7350 303.64609 277.5545 298.0455   9204.243 10000
               CPak  15.741  19.7525  27.31918  24.7150  29.0340    235.245 10000
             zacdav   6.649   9.3210  11.30229  10.4240  11.5540   2399.686 10000
       zacdav_which   7.364  10.2395  12.22632  11.2985  12.4515   2492.789 10000