glassure.pattern module

exception glassure.pattern.BkgNotInRangeError(pattern_name: str): Bases: Exception

pydantic model glassure.pattern.Pattern

Bases: BaseModel

A Pattern is a set of x and y values. It can be loaded from a file or created from scratch and can be modified by different methods. It builds the basis for all calculations in glassure.

Parameters:

x – x values of the pattern
y – y values of the pattern
name – name of the pattern

Show JSON schema

{
   "title": "Pattern",
   "description": "A Pattern is a set of x and y values.\nIt can be loaded from a file or created from scratch and can be modified by\ndifferent methods.\nIt builds the basis for all calculations in glassure.\n\n:param x: x values of the pattern\n:param y: y values of the pattern\n:param name: name of the pattern",
   "type": "object",
   "properties": {
      "x": {
         "title": "X"
      },
      "y": {
         "title": "Y"
      },
      "name": {
         "default": "",
         "title": "Name",
         "type": "string"
      }
   },
   "required": [
      "x",
      "y"
   ]
}

Config:

arbitrary_types_allowed: bool = True

Fields:

name (str)
x (numpy.ndarray)
y (numpy.ndarray)

Validators:

_validate_lengths » all fields

field name: str = ''

Validated by:

_validate_lengths

field x: PydanticNpArray [Required]

Constraints:

func = <function serialize at 0x71c7641865c0>
json_schema_input_type = typing.Any
return_type = PydanticUndefined
when_used = always

Validated by:

_validate_lengths

field y: PydanticNpArray [Required]

Constraints:

func = <function serialize at 0x71c7641865c0>
json_schema_input_type = typing.Any
return_type = PydanticUndefined
when_used = always

Validated by:

_validate_lengths

extend_to(x_value: float, y_value: float) → Pattern

Extends the current pattern to a specific x_value by filling it with the y_value. Does not modify inplace but returns a new filled Pattern

Parameters:: x_value – Point to which extending the pattern should be smaller than the lowest x-value in the pattern or

vice versa :param y_value: number to fill the pattern with :return: extended Pattern

static from_dict(json_dict: dict) → Pattern

Creates a new Pattern from a dictionary representation of a Pattern.

Parameters:: json_dict – dictionary representation of a Pattern
Returns:: new Pattern

static from_file(filename: str, skip_rows: int = 0) → Pattern

Loads a pattern from a file. The file can be either a .xy or a .chi file. The .chi file will be loaded with skiprows=4 by default.

Parameters:

filename – path to the file
skip_rows – number of rows to skip when loading the data (header)

Returns:

Pattern object loaded from the file

Raises:

PatternLoadError – if the file cannot be loaded

limit(x_min: float, x_max: float) → Pattern

Limits the pattern to a specific x-range. Does not modify inplace but returns a new limited Pattern

Parameters:

x_min – lower limit of the x-range
x_max – upper limit of the x-range

Returns:

limited Pattern

load(filename: str, skiprows: int = 0)

Loads a pattern from a file. The file can be either a .xy or a .chi file. The .chi file will be loaded with skiprows=4 by default.

Parameters:

filename – path to the file
skiprows – number of rows to skip when loading the data (header)

Raises:

PatternLoadError – if the file cannot be loaded

rebin(bin_size: float) → Pattern

Returns a new pattern, which is a rebinned version of the current one.

Parameters:: bin_size – Size of the bins
Returns:: rebinned Pattern

save(filename: str, header: str = '')

Saves the Pattern to a two-column xy file.

Parameters:

filename – path to the file
header – header to be written to the file

smooth(amount: float) → Pattern: Smoothing the pattern by applying a gaussian filter. Returns the smoothed pattern. :param amount: amount of smoothing to be applied

to_dict() → dict

Returns a dictionary representation of the pattern with x and y as plain lists. For JSON serialization with base64-encoded arrays, use model_dump() instead.

Returns:: dictionary representation of the pattern

property data: tuple[ndarray, ndarray]

Returns the data of the pattern as a tuple of x and y values.

Returns:: tuple of x and y values

exception glassure.pattern.PatternLoadError(filename: str, reason: str)

Bases: Exception

Exception raised when a pattern file cannot be loaded.

glassure.pattern.serialize(value)

Serializes a numpy array to a base64 encoded string. If the value is a numpy array, it is saved to a compressed bytes buffer and then encoded to a base64 string. If the value is a list, it is converted to a numpy array and then serialized. If the value is a string, it is decoded from a base64 encoded string and then deserialized. If the value is already a numpy array, it is returned as is.

Parameters:: value – The value to serialize
Returns:: The serialized numpy array

glassure.pattern.validate(value)

Validates a numpy array. If the value is a list, it is converted to a numpy array. If the value is a string, it is decoded from a base64 encoded string. If the value is already a numpy array, it is returned as is.

Parameters:: value – The value to validate
Returns:: The validated numpy array