Metadata-Version: 2.4
Name: india-map-corrector
Version: 0.1.0
Summary: Python module to visualize maps with correct (de jure) India borders
Author-email: Your Name <your.email@example.com>
Keywords: india,map,geojson,visualization,borders,folium,plotly,matplotlib
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Programming Language :: Python :: 3.13
Classifier: Topic :: Scientific/Engineering :: GIS
Classifier: Topic :: Scientific/Engineering :: Visualization
Requires-Python: >=3.10
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: folium>=0.20.0
Requires-Dist: geopandas>=1.0.0
Requires-Dist: matplotlib>=3.8.0
Requires-Dist: plotly>=5.18.0
Requires-Dist: pandas>=2.0.0
Requires-Dist: numpy>=1.24.0
Requires-Dist: nbformat>=5.10.4
Provides-Extra: dev
Requires-Dist: pytest>=7.0.0; extra == "dev"
Requires-Dist: jupyter>=1.0.0; extra == "dev"
Dynamic: license-file

# India Map Corrector 🗺️


[![Python 3.10+](https://img.shields.io/badge/python-3.10+-blue.svg)](https://www.python.org/downloads/)

A Python module to visualize maps with **correct (de jure) India borders**.

Most mapping libraries (Plotly, Folium, etc.) show India's de facto borders by default. This module provides an easy overlay to display the legally recognized boundaries of India, including:
- ✅ Jammu & Kashmir (complete)
- ✅ Arunachal Pradesh  
- ✅ Aksai Chin region

## 📦 Installation


### From Source

```bash
cd india-map-corrector
pip install -e .
```

### Dependencies

The package will automatically install:
- `folium>=0.20.0`
- `geopandas>=1.0.0`
- `matplotlib>=3.8.0`
- `plotly>=5.18.0`
- `pandas>=2.0.0`
- `numpy>=1.24.0`
- `nbformat>=5.10.4`

## 🚀 Quick Start

### Interactive Map (Folium)

```python
from india_map_corrector import create_folium_map

m = create_folium_map()
m  # Display in Jupyter
```

### 🏛️ Official Government Map (ISRO Bhuvan)

Use official tiles from ISRO's Bhuvan portal:

```python
from india_map_corrector import create_bhuvan_map

# Creates map with ISRO tiles + correct overlay
m = create_bhuvan_map()
m
```

### Interactive Map (Plotly)

```python
from india_map_corrector import create_plotly_map

fig = create_plotly_map(title="India Map")
fig.show()
```

### Static Map (Matplotlib)

```python
from india_map_corrector import plot_static
import matplotlib.pyplot as plt

fig, ax = plot_static(title="India with Correct Borders")
plt.show()
```

### 🌟 Fix Existing Plotly Maps (Key Feature!)

```python
import plotly.express as px
from india_map_corrector import correct_map

# Your existing Plotly code
fig = px.choropleth_mapbox(data, ...)

# Just wrap it to fix borders!
fig = correct_map(fig)
fig.show()
```

### Decorator for Automatic Correction

```python
from india_map_corrector import with_correct_borders

@with_correct_borders()
def create_my_map(data):
    return px.choropleth_mapbox(data, ...)

fig = create_my_map(my_data)  # Automatically has correct borders!
```

## 🎨 Available Map Styles

### Folium Styles

| Style | Description |
|-------|-------------|
| `"OpenStreetMap"` | Standard OSM with roads and labels |
| `"CartoDB positron"` | Light, minimal - great for data viz |
| `"CartoDB dark_matter"` | Dark theme |
| `"Esri.WorldImagery"` | Satellite imagery |
| `"Esri.WorldTopoMap"` | Topographic map |
| `"Stamen Terrain"` | Terrain with hill shading |
| `"Stamen Watercolor"` | Artistic watercolor style |
| `None` or `"blank"` | No background (overlay only) |

### Plotly Styles (Free - No Token Required)

| Style | Description |
|-------|-------------|
| `"open-street-map"` | Standard OSM |
| `"carto-positron"` | Light minimal |
| `"carto-darkmatter"` | Dark theme |
| `"white-bg"` | Plain white background |

```python
# List all available styles
from india_map_corrector import print_all_styles
print_all_styles()
```

## 📖 API Reference

### Visualization Functions

| Function | Library | Output |
|----------|---------|--------|
| `plot_static()` | Matplotlib | Static PNG/PDF |
| `create_folium_map()` | Folium | Interactive HTML |
| `create_plotly_map()` | Plotly | Interactive widget |

### Convenience Functions

| Function | Description |
|----------|-------------|
| `create_satellite_map()` | Folium with satellite background |
| `create_blank_map()` | Folium with no background |
| `create_bhuvan_map()` | **Official ISRO Bhuvan** tiles (WMS) |
| `create_dark_map()` | Plotly dark theme |
| `create_minimal_map()` | Plotly minimal/white theme |

### Wrapper Functions

| Function | Description |
|----------|-------------|
| `correct_map(fig)` | Add correct borders to any Plotly figure |
| `@with_correct_borders()` | Decorator for automatic correction |

### Core Functions

| Function | Description |
|----------|-------------|
| `get_corrected_geojson()` | Get the corrected world boundaries GeoDataFrame |
| `get_india_center()` | Returns `(22.5, 82.5)` lat/lon |
| `get_india_bounds()` | Returns bounding box tuple |

## 💡 Examples

Check out the example files to get started quickly:

| File | Description |
|------|-------------|
| 📓 [complete_guide.ipynb](examples/complete_guide.ipynb) | **Comprehensive Jupyter notebook** with interactive demos of all features - static maps, Folium, Plotly, wrapper functions, and styling options |
| 🐍 [usage_examples.py](examples/usage_examples.py) | **Python script** with runnable examples for each functionality |

### Running Examples

```bash
# Run the Python examples
cd examples
python usage_examples.py

# Or open the Jupyter notebook
jupyter notebook examples/complete_guide.ipynb
```

## 🎯 Customization

### Custom Colors

```python
m = create_folium_map(
    fill_color="#e8f4f8",
    line_color="#2c3e50",
    fill_opacity=0.6,
    line_weight=2
)
```

### World View

```python
m = create_folium_map(focus_india=False, zoom_start=2)
fig = create_plotly_map(focus_india=False, zoom=1.5)
```

### Save Maps

```python
# Folium to HTML
m = create_folium_map(save_html="map.html")

# Matplotlib to PNG/PDF
fig, ax = plot_static(save_path="map.png", dpi=300)

# Plotly to HTML
fig = create_plotly_map()
fig.write_html("map.html")
```

