imspy.algorithm package

Subpackages

• imspy.algorithm.ccs package
  • Submodules
  • imspy.algorithm.ccs.predictors module
    • DeepPeptideIonMobilityApex
      • DeepPeptideIonMobilityApex.fine_tune_model()
      • DeepPeptideIonMobilityApex.simulate_ion_mobilities()
      • DeepPeptideIonMobilityApex.simulate_ion_mobilities_pandas()
    • GRUCCSPredictor
      • GRUCCSPredictor.build()
      • GRUCCSPredictor.call()
      • GRUCCSPredictor.from_config()
      • GRUCCSPredictor.get_config()
    • PeptideIonMobilityApex
      • PeptideIonMobilityApex.simulate_ion_mobilities()
      • PeptideIonMobilityApex.simulate_ion_mobilities_pandas()
    • SquareRootProjectionLayer
      • SquareRootProjectionLayer.build()
      • SquareRootProjectionLayer.call()
      • SquareRootProjectionLayer.from_config()
      • SquareRootProjectionLayer.get_config()
    • get_sqrt_slopes_and_intercepts()
    • load_deep_ccs_predictor()
    • predict_inverse_ion_mobility()
  • Module contents
• imspy.algorithm.intensity package
  • Submodules
  • imspy.algorithm.intensity.predictors module
    • IonIntensityPredictor
      • IonIntensityPredictor.simulate_ion_intensities()
      • IonIntensityPredictor.simulate_ion_intensities_pandas()
    • Prosit2023TimsTofWrapper
      • Prosit2023TimsTofWrapper.predict_intensities()
      • Prosit2023TimsTofWrapper.simulate_ion_intensities()
      • Prosit2023TimsTofWrapper.simulate_ion_intensities_pandas()
      • Prosit2023TimsTofWrapper.simulate_ion_intensities_pandas_batched()
    • get_collision_energy_calibration_factor()
    • load_prosit_2023_timsTOF_predictor()
    • predict_intensities_prosit()
    • remove_unimod_annotation()
  • imspy.algorithm.intensity.utility module
    • beta_score()
    • generate_prosit_intensity_prediction_dataset()
    • get_prosit_intensity_flat_labels()
    • post_process_predicted_fragment_spectra()
    • seq_to_index()
    • to_prosit_tensor()
    • unpack_dict()
  • Module contents
• imspy.algorithm.ionization package
  • Submodules
  • imspy.algorithm.ionization.predictors module
    • BinomialChargeStateDistributionModel
      • BinomialChargeStateDistributionModel.simulate_charge_state_distribution_pandas()
      • BinomialChargeStateDistributionModel.simulate_ionizations()
    • DeepChargeStateDistribution
      • DeepChargeStateDistribution.simulate_charge_state_distribution_pandas()
      • DeepChargeStateDistribution.simulate_ionizations()
    • GRUChargeStatePredictor
      • GRUChargeStatePredictor.build()
      • GRUChargeStatePredictor.call()
      • GRUChargeStatePredictor.from_config()
      • GRUChargeStatePredictor.get_config()
    • PeptideChargeStateDistribution
      • PeptideChargeStateDistribution.simulate_charge_state_distribution_pandas()
      • PeptideChargeStateDistribution.simulate_ionizations()
    • charge_state_distribution_from_sequence_rust()
    • charge_state_distributions_from_sequences_rust()
    • load_deep_charge_state_predictor()
  • Module contents
• imspy.algorithm.pretrained package
  • Module contents
• imspy.algorithm.rt package
  • Submodules
  • imspy.algorithm.rt.predictors module
    • DeepChromatographyApex
      • DeepChromatographyApex.fine_tune_model()
      • DeepChromatographyApex.generate_tf_ds_inference()
      • DeepChromatographyApex.generate_tf_ds_train()
      • DeepChromatographyApex.simulate_separation_times()
      • DeepChromatographyApex.simulate_separation_times_pandas()
    • GRURetentionTimePredictor
      • GRURetentionTimePredictor.build()
      • GRURetentionTimePredictor.call()
      • GRURetentionTimePredictor.from_config()
      • GRURetentionTimePredictor.get_config()
    • PeptideChromatographyApex
      • PeptideChromatographyApex.simulate_separation_times()
      • PeptideChromatographyApex.simulate_separation_times_pandas()
    • get_rt_prediction_set()
    • get_rt_train_set()
    • load_deep_retention_time_predictor()
    • predict_retention_time()
  • Module contents

Submodules

imspy.algorithm.hashing module

class imspy.algorithm.hashing.CosimHasher(target_vector_length, trials=32, len_trial=20, seed=42)

Bases: object

calculate_keys(W)

Return type:

Tensor

class imspy.algorithm.hashing.TimsHasher(trials=32, len_trial=20, seed=5671, resolution=1, num_dalton=10)

Bases: CosimHasher

Class to create hash keys from a given set of weights.

Parameters:

• trials (int) – number of trials to use for random projection.

• len_trial (int) – length of each trial.

• seed (int) – seed for random projection.

• resolution (int) – resolution of the random projection.

• num_dalton (int) – number of dalton to use for random projection.

imspy.algorithm.mixture module

imspy.algorithm.utility module

class imspy.algorithm.utility.InMemoryCheckpoint(validation_target='val_loss')

Bases: Callback

on_epoch_end(epoch, logs=None)

Called at the end of an epoch.

Subclasses should override for any actions to run. This function should only be called during TRAIN mode.

Parameters:

• epoch – Integer, index of epoch.

• logs – Dict, metric results for this training epoch, and for the validation epoch if validation is performed. Validation result keys are prefixed with val_. For training epoch, the values of the Model’s metrics are returned. Example: {‘loss’: 0.2, ‘accuracy’: 0.7}.

on_train_begin(logs=None)

Called at the beginning of training.

Subclasses should override for any actions to run.

Parameters:

logs – Dict. Currently no data is passed to this argument for this method but that may change in the future.

on_train_end(logs=None)

Called at the end of training.

Subclasses should override for any actions to run.

Parameters:

logs – Dict. Currently the output of the last call to on_epoch_end() is passed to this argument for this method but that may change in the future.

imspy.algorithm.utility.get_model_path(model_name)

Get the path to a pretrained model

Parameters:

model_name (str) – The name of the model to load

Return type:

Traversable

Returns:

The path to the pretrained model

imspy.algorithm.utility.load_tokenizer_from_resources(tokenizer_name)

Load a tokenizer from resources

Return type:

Tokenizer

Returns:

The pretrained tokenizer

Module contents