File Path: /home/nicai_zht/.local/share/mamba/envs/idr_llm/lib/python3.13/site-packages/alphaPredict/__init__.py
short description of alphaPredict.
Predict confidence scores of alphaFold2
This section helps you understand how to run this library from the command line or entry points.
- ℹ️ No Direct Entry Point: This module seems to be a library intended for import, not direct execution.
Since no CLI entry point was found, here are the likely Python API entry points for your script:
| Type | API | Description |
|---|---|---|
ƒ |
alphaPredict.predict(sequence) | Function to return confidence scores from |
ƒ |
alphaPredict.graph(sequence, title, confidence_threshold, shaded_regions, shaded_region_color, confidence_line_color, threshold_line_color, DPI, output_file) | No description. |
Note: Bold parameters are required. Others are optional.
import alphaPredict
# --- Top 20 Ranked Functions ---
# 1. predict
result_1 = alphaPredict.predict(sequence=...)
# 2. graph
result_2 = alphaPredict.graph(sequence=...)No explicit argparse configuration detected in the main module.
| Library | Usage Count |
|---|---|
| _frozen_importlib_external | 4 |
| _frozen_importlib | 4 |
| Rank | Module | Score | Type | Role |
|---|---|---|---|---|
| 1 | _frozen_importlib_external |
0.2067 | External | External Lib |
| 2 | _frozen_importlib |
0.2067 | External | External Lib |
| 3 | alpha |
0.1085 | Internal | Utility / Core |
| 4 | alpha_exceptions |
0.1030 | Internal | Utility / Core |
| 5 | backend.parrot_alpha |
0.1030 | Internal | External Lib |
| 6 | backend.alpha_graph |
0.1030 | Internal | External Lib |
| 7 | alphaPredict |
0.0846 | Internal | Utility / Core |
| 8 | _version |
0.0846 | Internal | Utility / Core |
graph TD
classDef core fill:#f96,stroke:#333,stroke-width:2px;
classDef external fill:#9cf,stroke:#333,stroke-width:1px;
id_6["alphaPredict"] -.-> id_1["_frozen_importlib_external"]
class id_6 core;
class id_1 external;
id_6["alphaPredict"] -.-> id_4["_frozen_importlib"]
class id_6 core;
class id_4 external;
id_6["alphaPredict"] --> id_7["alpha"]
class id_6 core;
class id_7 core;
id_7["alpha"] --> id_10["alpha_exceptions"]
class id_7 core;
class id_10 core;
id_7["alpha"] -.-> id_1["_frozen_importlib_external"]
class id_7 core;
class id_1 external;
id_7["alpha"] -.-> id_4["_frozen_importlib"]
class id_7 core;
class id_4 external;
id_7["alpha"] --> id_5["parrot_alpha"]
class id_7 core;
class id_5 core;
id_7["alpha"] --> id_9["alpha_graph"]
class id_7 core;
class id_9 core;
id_2["_version"] -.-> id_1["_frozen_importlib_external"]
class id_2 core;
class id_1 external;
id_2["_version"] -.-> id_4["_frozen_importlib"]
class id_2 core;
class id_4 external;
id_10["alpha_exceptions"] -.-> id_1["_frozen_importlib_external"]
class id_10 core;
class id_1 external;
id_10["alpha_exceptions"] -.-> id_4["_frozen_importlib"]
class id_10 core;
class id_4 external;
id_8["AlphaError"] ==> id_0["Exception"]
class id_8 core;
class id_0 external;
id_8["AlphaError"] ==> id_0["Exception"]
class id_8 core;
class id_0 external;
id_3["DomainError"] ==> id_0["Exception"]
class id_3 core;
class id_0 external;
This graph visualizes how data flows between functions across the entire project.
graph TD
classDef main fill:#f9f,stroke:#333,stroke-width:2px;
classDef func fill:#fff,stroke:#333,stroke-width:1px;
f_3["predict"] -->|sequence| f_0["_alpha_predict"]
class f_3 func;
class f_0 func;
f_2["graph"] -->|sequence<br>title<br>confidence_threshold<br>shaded_regions<br>shaded_region_color<br>confidence_line_color<br>threshold_line_color<br>DPI<br>output_file| f_1["_graph"]
class f_2 func;
class f_1 func;
Want to use a specific function without the whole library? Here is the Dependency Closure for Top 20 key functions.
You need these 2 components:
_alpha_predict, predict
You need these 2 components:
_graph, graph
graph(sequence, title='Predicted Confidence Score', confidence_threshold=50, shaded_regions=None, shaded_region_color='red', confidence_line_color='blue', threshold_line_color='black', DPI=150, output_file=None)
No documentation available.
Full Docstring
No documentation available.
Function to return confidence scores from
Full Docstring
Function to return confidence scores from
Alpha fold 2 of a single input sequence. Returns the
predicted values as a float.
Parameters
------------
sequence : str
Input amino acid sequence (as string) to be predicted.
Returns
--------
Float
Returns a float of the confidence score value (predicted)