docs: update mintpy references

Signed-off-by: Emmanuel Ferdman <emmanuelferdman@gmail.com>

docs/dask.md

@@ -1,6 +1,6 @@
 # Configure dask for parallel processing #
 
-Most computations in MintPy are operated in either a pixel-by-pixel or a epoch-by-epoch basis. This implementation strategy allows processing different blocks (in space or in time) in parallel. For this purpose, we use the [`Dask`](https://docs.dask.org/en/latest/) library for its dynamic task scheduling and data collection. Dask support is currently implemented in `ifgram_inversion.py` and `dem_error.py` only (expansions to other modules are welcomed) through a thin wrapper in [`mintpy.objects.cluster`](../mintpy/objects/cluster.py). We have tested two types of clusters:
+Most computations in MintPy are operated in either a pixel-by-pixel or a epoch-by-epoch basis. This implementation strategy allows processing different blocks (in space or in time) in parallel. For this purpose, we use the [`Dask`](https://docs.dask.org/en/latest/) library for its dynamic task scheduling and data collection. Dask support is currently implemented in `ifgram_inversion.py` and `dem_error.py` only (expansions to other modules are welcomed) through a thin wrapper in [`mintpy.objects.cluster`](../src/mintpy/objects/cluster.py). We have tested two types of clusters:
 
 + **local cluster:** on a single machine (laptop or computing node) with multiple CPU cores, suitable for laptops, local cluster/stations and distributed High Performance Cluster (HPC). No job scheduler is required.
 + **non-local cluster:** on a distributed HPC with job scheduler installed, including PBS, LSF and SLURM.
@@ -67,9 +67,9 @@ As of Jun 2020, we have tried on one HPC system where local cluster worked on th
 PBScluster did not work either. But we tested only on a small server without shared disk space between the workers and the client (the compute and login nodes respectively). This leads to the dask workers running on the compute nodes being unable to use mintpy code as the codebase is local to login node ([see this issue](https://github.com/dask/dask-jobqueue/issues/436)).
 
 -------------------------------------------
-The parallel proceesing on multiple machines is supported via [`Dask-jobqueue`](https://jobqueue.dask.org/en/latest/index.html). One can specify configuration either with keyword arguments when creating a `Cluster` object, or with a configuration file in YAML format. MintPy assumes the YAML configuration file only.
+The parallel proceeding on multiple machines is supported via [`Dask-jobqueue`](https://jobqueue.dask.org/en/latest/index.html). One can specify configuration either with keyword arguments when creating a `Cluster` object, or with a configuration file in YAML format. MintPy assumes the YAML configuration file only.
 
-We provide an example [YAML configuration file](../mintpy/defaults/mintpy.yaml), besides the `dask.yaml`,  `distributed.yaml` and `jobqueue.yaml` files in `~/.config/dask` installed by dask by default. One can copy it over to the `~/.config/dask` directory as below for dask to identify and use it.
+We provide an example [YAML configuration file](../src/mintpy/defaults/mintpy.yaml), besides the `dask.yaml`,  `distributed.yaml` and `jobqueue.yaml` files in `~/.config/dask` installed by dask by default. One can copy it over to the `~/.config/dask` directory as below for dask to identify and use it.
 
 ```bash
 cp $MINTPY_HOME/src/mintpy/defaults/mintpy.yaml ~/.config/dask/mintpy.yaml