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]


/*
 * This program is free software; you can redistribute it and/or
 * modify it under the terms of the GNU General Public License
 * as published by the Free Software Foundation; either version 2
 * of the License, or (at your option) any later version.
 *
 * This program is distributed in the hope that it will be useful,
 * but WITHOUT ANY WARRANTY; without even the implied warranty of
 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
 * GNU General Public License for more details.
 *
 * You should have received a copy of the GNU General Public License
 * along with this program; if not, write to the Free Software Foundation,
 * Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA.
 */

#ifndef __BC_ANIMATION_EXPORTER_H__
#define __BC_ANIMATION_EXPORTER_H__

#include <stdlib.h>
#include <stdio.h>
#include <math.h>

#include "BCAnimationCurve.h"

extern "C" {
#include "DNA_scene_types.h"
#include "DNA_object_types.h"
#include "DNA_anim_types.h"
#include "DNA_action_types.h"
#include "DNA_curve_types.h"
#include "DNA_light_types.h"
#include "DNA_camera_types.h"
#include "DNA_armature_types.h"
#include "DNA_material_types.h"
#include "DNA_constraint_types.h"
#include "DNA_scene_types.h"

#include "BLI_math.h"
#include "BLI_string.h"
#include "BLI_listbase.h"
#include "BLI_utildefines.h"

#include "BKE_fcurve.h"
#include "BKE_animsys.h"
#include "BKE_scene.h"
#include "BKE_action.h"  // pose functions
#include "BKE_armature.h"
#include "BKE_object.h"
#include "BKE_constraint.h"
#include "BIK_api.h"
#include "ED_object.h"
}

#include "MEM_guardedalloc.h"

#include "RNA_access.h"

#include "COLLADASWSource.h"
#include "COLLADASWInstanceGeometry.h"
#include "COLLADASWInputList.h"
#include "COLLADASWPrimitves.h"
#include "COLLADASWVertices.h"
#include "COLLADASWLibraryAnimations.h"
#include "COLLADASWParamTemplate.h"
#include "COLLADASWParamBase.h"
#include "COLLADASWSampler.h"
#include "COLLADASWConstants.h"
#include "COLLADASWBaseInputElement.h"

#include "EffectExporter.h"
#include "BCAnimationSampler.h"
#include "collada_internal.h"

#include "IK_solver.h"

#include <vector>
#include <map>
#include <algorithm>  // std::find

typedef enum BC_animation_source_type {
  BC_SOURCE_TYPE_VALUE,
  BC_SOURCE_TYPE_ANGLE,
  BC_SOURCE_TYPE_TIMEFRAME,
} BC_animation_source_type;

typedef enum BC_global_rotation_type {
  BC_NO_ROTATION,
  BC_OBJECT_ROTATION,
  BC_DATA_ROTATION
} BC_global_rotation_type;

class AnimationExporter : COLLADASW::LibraryAnimations {
 private:
  COLLADASW::StreamWriter *sw;
  BCExportSettings &export_settings;

  BC_global_rotation_type get_global_rotation_type(Object *ob);

 public:
  AnimationExporter(COLLADASW::StreamWriter *sw, BCExportSettings &export_settings)
      : COLLADASW::LibraryAnimations(sw), sw(sw), export_settings(export_settings)
  {
  }

  bool exportAnimations();

  // called for each exported object
  void operator()(Object *ob);

 protected:
  void export_object_constraint_animation(Object *ob);

  void export_morph_animation(Object *ob);

  void write_bone_animation_matrix(Object *ob_arm, Bone *bone);

  void write_bone_animation(Object *ob_arm, Bone *bone);

  void sample_and_write_bone_animation(Object *ob_arm, Bone *bone, int transform_type);

  void sample_and_write_bone_animation_matrix(Object *ob_arm, Bone *bone);

  void sample_animation(float *v,
                        std::vector<float> &frames,
                        int type,
                        Bone *bone,
                        Object *ob_arm,
                        bPoseChannel *pChan);

  void sample_animation(std::vector<float[4][4]> &mats,
                        std::vector<float> &frames,
                        Bone *bone,
                        Object *ob_arm,
                        bPoseChannel *pChan);

  // dae_bone_animation -> add_bone_animation
  // (blend this into dae_bone_animation)
  void dae_bone_animation(std::vector<float> &fra,
                          float *v,
                          int tm_type,
                          int axis,
                          std::string ob_name,
                          std::string bone_name);

  void dae_baked_animation(std::vector<float> &fra, Object *ob_arm, Bone *bone);

  void dae_baked_object_animation(std::vector<float> &fra, Object *ob);

  float convert_time(float frame);

  float convert_angle(float angle);

  std::vector<std::vector<std::string>> anim_meta;

  /* Main entry point into Animation export (called for each exported object) */
  void exportAnimation(Object *ob, BCAnimationSampler &sampler);

  /* export animation as separate trans/rot/scale curves */
  void export_curve_animation_set(Object *ob, BCAnimationSampler &sampler, bool export_tm_curves);

  /* export one single curve */
  void export_curve_animation(Object *ob, BCAnimationCurve &curve);

  /* export animation as matrix data */
  void export_matrix_animation(Object *ob, BCAnimationSampler &sampler);

  /* step through the bone hierarchy */
  void export_bone_animations_recursive(Object *ob_arm, Bone *bone, BCAnimationSampler &sampler);

  /* Export for one bone */
  void export_bone_animation(Object *ob, Bone *bone, BCFrames &frames, BCMatrixSampleMap &outmats);

  /* call to the low level collada exporter */
  void export_collada_curve_animation(std::string id,
                                      std::string name,
                                      std::string target,
                                      std::string axis,
                                      BCAnimationCurve &curve,
                                      BC_global_rotation_type global_rotation_type);

  /* call to the low level collada exporter */
  void export_collada_matrix_animation(std::string id,
                                       std::string name,
                                       std::string target,
                                       BCFrames &frames,
                                       BCMatrixSampleMap &outmats,
                                       BC_global_rotation_type global_rotation_type,
                                       Matrix &parentinv);

  BCAnimationCurve *get_modified_export_curve(Object *ob,
                                              BCAnimationCurve &curve,
                                              BCAnimationCurveMap &curves);

  /* Helper functions */
  void openAnimationWithClip(std::string id, std::string name);
  bool open_animation_container(bool has_container, Object *ob);
  void close_animation_container(bool has_container);

  /* Input and Output sources (single valued) */
  std::string collada_source_from_values(BC_animation_source_type tm_channel,
                                         COLLADASW::InputSemantic::Semantics semantic,
                                         std::vector<float> &values,
                                         const std::string &anim_id,
                                         const std::string axis_name);

  /* Output sources (matrix data) */
  std::string collada_source_from_values(BCMatrixSampleMap &samples,
                                         const std::string &anim_id,
                                         BC_global_rotation_type global_rotation_type,
                                         Matrix &parentinv);

  /* Interpolation sources */
  std::string collada_linear_interpolation_source(int tot, const std::string &anim_id);

  /* source ID = animation_name + semantic_suffix */

  std::string get_semantic_suffix(COLLADASW::InputSemantic::Semantics semantic);

  void add_source_parameters(COLLADASW::SourceBase::ParameterNameList &param,
                             COLLADASW::InputSemantic::Semantics semantic,
                             bool is_rot,
                             const std::string axis,
                             bool transform);

  int get_point_in_curve(BCBezTriple &bezt,
                         COLLADASW::InputSemantic::Semantics semantic,
                         bool is_angle,
                         float *values);
  int get_point_in_curve(const BCAnimationCurve &curve,
                         float sample_frame,
                         COLLADASW::InputSemantic::Semantics semantic,
                         bool is_angle,
                         float *values);

  std::string collada_tangent_from_curve(COLLADASW::InputSemantic::Semantics semantic,
                                         BCAnimationCurve &curve,
                                         const std::string &anim_id,
                                         const std::string axis_name);

  std::string collada_interpolation_source(const BCAnimationCurve &curve,
                                           const std::string &anim_id,
                                           std::string axis_name,
                                           bool *has_tangents);

  std::string get_axis_name(std::string channel, int id);
  const std::string get_collada_name(std::string channel_target) const;
  std::string get_collada_sid(const BCAnimationCurve &curve, const std::string axis_name);

  /* ===================================== */
  /* Currently unused or not (yet?) needed */
  /* ===================================== */

  bool is_bone_deform_group(Bone *bone);

#if 0
  BC_animation_transform_type _get_transform_type(const std::string path);
  void get_eul_source_for_quat(std::vector<float> &cache, Object *ob);
#endif

#ifdef WITH_MORPH_ANIMATION
  void export_morph_animation(Object *ob, BCAnimationSampler &sampler);
#endif
};

#endif