Can I use this great libarary to read .uni file?

[syguan96]

Thanks for your great efforts in developing mantaflow and PhiFlow. Since the mantaflow stops update a long time ago. I wonder whether I can use the PhiFlow to read .uni file?

[holl-]

Hi @syguan96, the following script should be able to read .uni files as NumPy arrays.

Code

```python import os,gzip import struct from collections import namedtuple import glob,re import numpy as np # this is for reading the field def _read_content(bytestream, head): #dt = np.dtype(np.float64).newbyteorder('>') assert (head['bytesPerElement'] == 12 and head['elementType'] == 2) or head['bytesPerElement'] == 4 if (head['elementType'] == 0): data = np.frombuffer(bytestream.read(), dtype="int32") else: data = np.frombuffer(bytestream.read(), dtype="float32") if (head['elementType'] == 2): return data.reshape(head['dimX'], head['dimY'], head['dimZ'], 3, order='C') else: return data.reshape(head['dimX'], head['dimY'], head['dimZ'], order='C') # read important information in the header such as dimensions and grid type def _read_head(bytestream): ID = bytestream.read(4) #dimX, dimY, dimZ, gridType, elementType, bytesPerElement, info, timestamp = struct.unpack('iiiiii256sQ', bytestream.read(288)) # unpack header struct object head = namedtuple('UniHeader', 'dimX, dimY, dimZ, gridType, elementType, bytesPerElement, info, timestamp') # convert to namedtuple and then directly to a dict head = head._asdict(head._make(struct.unpack('iiiiii256sQ', bytestream.read(288)))) #head['ID'] = ID return head # use this to read the .uni file. It will return the header as dictionary and the content as np-array def readuni(filename): with gzip.open(filename, 'rb') as bytestream: head = _read_head(bytestream) content = _read_content(bytestream, head) return head, content # use this to write a .uni file. The head has to be supplied in the same dictionary format as the output of readuni def writeuni(filename, head, content): with gzip.open(filename, 'wb') as bytestream: # write the head of the uni file bytestream.write(b'MNT2') head_tuple = namedtuple('GenericDict', head.keys())(**head) head_buffer = struct.pack('iiiiii256sQ', *head_tuple) bytestream.write(head_buffer) if (head['elementType'] == 2): content = content.reshape(head['dimX']*head['dimY']*head['dimZ']*3, order='C') else: content = content.reshape(head['dimX']*head['dimY']*head['dimZ'], order='C') bytestream.write(content.tobytes()) def convert_to_npz(dir, file_name, header, quantization=0): #TODO reactivate assert path.suffix == '.npz', ("Serialization must be to a .npz file") fields = [] # gather file list of all files with ending .uni in dir dirlist = glob.glob(dir+"*.uni") # natural sort the array convert = lambda text: int(text) if text.isdigit() else text dirlist.sort(key=lambda k: [ convert(c) for c in re.split('([0-9]+)', k) ] ) # load every file remaining in list for index, filename in enumerate(dirlist): # extract data from uni file (headers are ignored) field = readuni(filename)[1] # if 3d add 4th dimension if field.ndim == 3: field = field[...,np.newaxis] fields.append(field) fields = np.array(fields) if quantization != 0: fields = np.around(fields, decimals=quantization) np.savez_compressed(dir + file_name, data=fields, header=header) for f in glob.glob(dir + "*.uni"): os.remove(f) ```

From there, you can use wrap or tensor to specify the dimensions and then give it to a centered or staggered grid.

Cheers!