PVCollada

https://pvlib.github.io/pvcollada/
Admin
PVCollada is an extension for the COLLADA data exchange format, designed for representing PV system...
Tokens:4,280
Snippets:26
Trust Score:9.7
Update:4 weeks ago
Show doc for...
Tokens:
Raw
### PVCollada asset example with profile="PVCollada-2.0"

Source: https://pvlib.github.io/pvcollada/dev_guide.html

Shows the required structure for PVCollada data, which must be identified by profile="PVCollada-2.0". Includes geographic location, unit, up_axis, and an extra technique block with a software tag.

```xml
	<asset>
		<coverage>
			<geographic_location>
				<longitude>15.3</longitude>
				<latitude>10.1</latitude>
				<altitude mode="absolute">150</altitude>
			</geographic_location>
		</coverage>
		<unit meter="0.01" name="cm" />
		<up_axis>Z_UP</up_axis>
		<extra>
			<technique profile="PVCollada-2.0">
				<!-- software tag -->
				<pv:software>
					<pv:source>Helios 3D</pv:source>
					<pv:target>PVsyst</pv:target>
				</pv:software>
			</technique>
		</extra>
	</asset>

```

--------------------------------

### Convert ENU to geodetic coordinates using pyproj

Source: https://pvlib.github.io/pvcollada/pvcollada_coordinate_transformation_with_diagram.html

Compute WGS-84 geodetic coordinates from local ENU coordinates using a pyproj inverse pipeline with the topocentric projection. The example uses the same cube coordinates and origin. Requires pyproj and pandas. The output is printed as a Markdown table.

```python
import pandas as pd
import pyproj


# 1. Define the origin of your local topocentric system (tangent plane)
lat_0 = 35.0845   # Latitude of origin (degrees)
lon_0 = -106.651 # Longitude of origin (degrees)
h_0 = 1619.0      # Ellipsoidal height of origin (meters)

# 2. Build an inverse PROJ pipeline conversion string
# We use +inv because we are starting with topocentric coordinates and going backward
pipeline_str = (
    f"+proj=pipeline "
    f"+step +inv +proj=topocentric +lat_0={lat_0} +lon_0={lon_0} +h_0={h_0} +ellps=WGS84 "
    f"+step +inv +proj=cart +ellps=WGS84 "
    f"+step +proj=unitconvert +xy_in=rad +xy_out=deg "
    f"+step +proj=axisswap +order=2,1"
)

# 3. Create the transformer from the pipeline definition
transformer = pyproj.Transformer.from_pipeline(pipeline_str)

# 4. Input topocentric local data (East, North, Up in meters)
coords = pd.DataFrame(
    columns=['x', 'y', 'z'],
    data=[[1., 1., 1.],
          [4., 1., 1.],
          [1., 3., 1.],
          [4., 3., 1.],
          [1., 1., 2.],
          [4., 1., 2.],
          [1., 3., 2.],
          [4., 3., 2.]]
    )

# Translate the cube to geocoordinates

# 5. Transform the coordinates
# Note: The output layout matches traditional GIS structure (Longitude, Latitude, Height)
lon, lat, alt = transformer.transform(
    coords['x'], coords['y'], coords['z'])

geodetic_coords = pd.DataFrame({'lat': lat, 'lon': lon, 'alt': alt})

print('Topocentric to Geodetic coordinates using pymap3d')
print(geodetic_coords.to_markdown(index=False, floatfmt=".8f"))

```

--------------------------------

### Convert ENU to geodetic coordinates using pymap3d

Source: https://pvlib.github.io/pvcollada/pvcollada_coordinate_transformation_with_diagram.html

Compute WGS-84 geodetic coordinates from local ENU coordinates using pymap3d's enu2geodetic function. The example uses a cube defined in local coordinates and an origin at Albuquerque, NM (lat 35.0845, lon -106.651, alt 1619). Requires pymap3d and pandas. The output is printed as a Markdown table.

```python
import pandas as pd
import pymap3d as pm

lat0 = 35.0845
lon0 = -106.651
alt0 = 1619.0

# Local coordinates of corners of the cube
topocentric_coords = pd.DataFrame(
    columns=['x', 'y', 'z'],
    data=[[1., 1., 1.],
          [4., 1., 1.],
          [1., 3., 1.],
          [4., 3., 1.],
          [1., 1., 2.],
          [4., 1., 2.],
          [1., 3., 2.],
          [4., 3., 2.]]
    )

# Translate the cube to geocoordinates
# pymap3d.enu2geodetic uses WGS-84 by default. We'll specify a datum to show how
# it is done.

datum = pm.Ellipsoid.from_name('wgs84')

lat, lon, alt = pm.enu2geodetic(coords['y'], coords['x'], coords['z'],
                                lat0, lon0, alt0, ell=datum)

geodetic_coords = pd.DataFrame({'lat': lat, 'lon': lon, 'alt': alt})

print('Topocentric to Geodetic coordinates using pymap3d')
print(geodetic_coords.to_markdown(index=False, floatfmt=".8f"))

```

--------------------------------

### Convert geographic to ENU with pymap3d geodetic2enu

Source: https://pvlib.github.io/pvcollada/pvcollada_coordinate_transformation_with_diagram.html

Converts WGS-84 geographic coordinates to PVCollada ENU coordinates using pymap3d's geodetic2enu function. Requires a DataFrame with lat, lon, and alt columns, plus the ENU origin (lat0, lon0, alt0). The example uses the WGS84 ellipsoid and prints the resulting ENU coordinates as a markdown table.

```python
import numpy as np
import pandas as pd
import pymap3d as pm


geocoords = pd.DataFrame(
    columns=['lat', 'lon', 'alt'],
    data = np.array(
	    [[35.08450901, -106.65098904, 1620.00000016],
         [35.08453605, -106.65098904, 1620.00000134],
         [35.08450901, -106.65096711, 1620.00000078],
         [35.08453605, -106.65096711, 1620.00000196],
         [35.08450901, -106.65098904, 1621.00000016],
         [35.08453605, -106.65098904, 1621.00000134],
         [35.08450901, -106.65096711, 1621.00000078],
         [35.08453605, -106.65096711, 1621.00000196]]
        )
    )

# origin of ENU coordinates
lat0 = 35.0845
lon0 = -106.651
alt0 = 1619.0
datum = pm.Ellipsoid.from_name('wgs84')

x, y, z = pm.geodetic2enu(
    geocoords['lat'], geocoords['lon'], geocoords['alt'], 
    lat0, lon0, alt0, ell=datum
	)

# put x, y, z into a DataFrame for convenient printing
enucoords = pd.DataFrame({'x': x, 'y': y, 'z': z})

print('Geodetic to Topocentric coordinates using pymap3d')
print(coords.to_markdown(index=False, floatfmt=".8f"))
```

--------------------------------

### Extending PVCollada with custom technique

Source: https://pvlib.github.io/pvcollada/dev_guide.html

Shows how to extend a PVCollada file with custom elements. Adds a custom technique with a unique profile (e.g., "PVCollada-2.0-PVsyst") in parallel with the standard technique, using a unique namespace.

```xml
<COLLADA xmlns:xsd="http://www.w3.org/2001/XMLSchema" 
  xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" 
  xmlns:pv="http://www.example.com/pvcollada" 
  xmlns:pvsyst="https://www.pvsyst.com/pvcollada-2.0-extensions"
  version="1.5.0" 
  xmlns="http://www.collada.org/2008/03/COLLADASchema">	
  <asset>
      <coverage>
          <geographic_location>
              <longitude>15.3</longitude>
              <latitude>10.1</latitude>
              <altitude mode="absolute">150</altitude>
          </geographic_location>
      </coverage>
      <extra>
          <technique profile="PVCollada-2.0">
              <!-- software tag -->
              <pv:software>
                  <pv:source>Helios 3D</pv:source>
                  <pv:target>PVsyst</pv:target>
              </pv:software>
          </technique>
          <technique profile="PVCollada-2.0-PVsyst">
              <pvsyst:tag specific to PVsyst/>
          </technique>
      </extra>
  </asset>
</COLLADA>

```

--------------------------------

### Schema file location

Source: https://pvlib.github.io/pvcollada/dev_guide.html

Specifies the location of the PVCollada 2.0 schema file within the repository. This schema imports the COLLADA schema and defines PV-specific enumerations and types.

```text
schema/pvcollada_schema_2.0.xsd

```

--------------------------------

### Validate PVCollada XML with lxml

Source: https://pvlib.github.io/pvcollada/dev_guide.html

Validates a PVCollada XML file against the schema using lxml. Prints a success message or lists validation errors from the schema error log.

```python
from lxml import etree

XML_FILE_PATH = "../Examples/05 - VerySimpleFixedPVC2_with_electrical_layout.pvc2"
XSD_FILE_PATH = "pvcollada_schema_2.0.xsd"

with open(XML_FILE_PATH, "rb") as xml:
    xml_doc = etree.XML(xml.read())
with open(XSD_FILE_PATH, "rb") as xsd:
    schema_root = etree.XML(xsd.read())

schema = etree.XMLSchema(schema_root)

if schema.validate(xml_doc):
    print("XML is valid.")
else:
    print("! XML is invalid.")
    for error in schema.error_log:
        print("  -", error.message)

```
Tokens:
Raw