Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

visualizer interface #1062

Merged
merged 5 commits into from
Oct 8, 2024
Merged
Changes from 1 commit
Commits
File filter

Filter by extension

Filter by extension

Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
105 changes: 105 additions & 0 deletions python/src/robyn/visualization/visualizer.py
shivkanthb marked this conversation as resolved.
Show resolved Hide resolved
Original file line number Diff line number Diff line change
@@ -0,0 +1,105 @@
from typing import Dict, Any
import matplotlib.pyplot as plt
import seaborn as sns

class RobynVisualizer:
def __init__(self):
pass

def plot_adstock(self, plot: bool = False) -> plt.Figure:
"""
Create example plots for adstock hyperparameters.

Args:
plot (bool): Whether to display the plot.

Returns:
plt.Figure: The generated figure.
"""
pass

def plot_saturation(self, plot: bool = False) -> plt.Figure:
"""
Create example plots for saturation hyperparameters.

Args:
plot (bool): Whether to display the plot.

Returns:
plt.Figure: The generated figure.
"""
pass

def plot_moo_distribution(self, output_models: Dict[str, Any]) -> plt.Figure:
"""
Plot MOO (multi-objective optimization) distribution.

Args:
output_models (Dict[str, Any]): The output models data.

Returns:
plt.Figure: The generated figure.
"""
pass

def plot_moo_cloud(self, output_models: Dict[str, Any]) -> plt.Figure:
"""
Plot MOO (multi-objective optimization) cloud.

Args:
output_models (Dict[str, Any]): The output models data.

Returns:
plt.Figure: The generated figure.
"""
pass

def plot_ts_validation(self, output_models: Dict[str, Any]) -> plt.Figure:
"""
Plot time-series validation.

Args:
output_models (Dict[str, Any]): The output models data.

Returns:
plt.Figure: The generated figure.
"""
pass

def plot_onepager(self, input_collect: Dict[str, Any], output_collect: Dict[str, Any], select_model: str) -> Dict[str, plt.Figure]:
"""
Generate one-pager plots for a selected model.

Args:
input_collect (Dict[str, Any]): The input collection data.
output_collect (Dict[str, Any]): The output collection data.
select_model (str): The selected model identifier.

Returns:
Dict[str, plt.Figure]: A dictionary of generated figures.
"""
pass

def plot_allocator(self, allocator_collect: Dict[str, Any]) -> plt.Figure:
"""
Plot allocator's output.

Args:
allocator_collect (Dict[str, Any]): The allocator collection data.

Returns:
plt.Figure: The generated figure.
"""
pass

def plot_response(self, response_data: Dict[str, Any]) -> plt.Figure:
"""
Plot response curves.

Args:
response_data (Dict[str, Any]): The response data.

Returns:
plt.Figure: The generated figure.
"""
pass