### 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
15.3
10.1
150
Z_UP
Helios 3D
PVsyst
```
--------------------------------
### 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
15.3
10.1
150
Helios 3D
PVsyst
```
--------------------------------
### 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)
```
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